SYSTEM AND METHOD FOR ADAPTIVE CONTROL OF AN ADIABATIC HEAT PUMP

Abstract

An intelligent heat pump system autonomously manages thermal regulation in heating and cooling modes using real-time sensor data and adaptive control algorithms. The system comprises a heat pump integrated with components including a supply valve, regulating valve, return valve, and compressor expander, along with multiple sensors configured to monitor temperature and pressure conditions at various points, including the reservoir, cold side, and hot side. A removable memory stores a directive file containing operational parameters, including target temperatures, valve timing, and pressure control data. A control unit with a processor executes firmware modules that include sensor calibration routines, motor and valve control logic, and an adaptive algorithm that continuously compares real-time sensor input against target parameters. Based on deviations, the system dynamically adjusts component operations to regulate refrigerant flow, internal energy, temperature, and pressure, thereby driving the system toward a steady-state thermal condition. This autonomous system ensures efficient performance, enhanced temperature stability, and optimal energy usage across a range of varying environmental conditions.

Claims

1. An intelligent heat pump system comprising: a heat pump including one or more components selected from a supply valve, a regulating valve, a return valve, or a compressor-expander and a plurality of sensors configured to monitor thermal and pressure conditions, including at least reservoir temperature of the heat pump; a removable memory storing a directive file comprising operational parameters, including target reservoir temperature, target cold side temperature, pressure control data, valve timing, and temperature cycle instructions; a control unit comprising a processor and a memory, communicably connected with the heat pump wherein the processor is configured to execute one or more modules stored in the memory, the modules comprising: a data acquisition module configured to receive real-time data, collected from the plurality of sensors; a firmware module, comprising sensor calibration routines, motor and valve control logic, and an adaptive control algorithm, wherein the firmware module is configured to: (a) compare the real-time sensor data with the target parameters stored in the directive file to determine deviations in pressure and temperature of the heat pump; and (b) adjust the operation of said one or more components based on the detected deviations, thereby regulating temperature and pressure to drive the system toward a target steady-state thermal condition.

2. The heat pump system of claim 1, further comprising a temperature control cycle module, wherein the temperature control cycle module is configured to implement one of a linear or loop-based sequence of temperature adjustments, wherein the cycle involves a set of current temperatures used to guide the system to a final operating temperature incrementally.

3. The heat pump system of claim 1, wherein the plurality of sensors comprise temperature sensors positioned to measure the reservoir temperature (T1), the cold side temperature (T2) at a cold side heat exchanger, the hot side temperature (T3) at a hot side heat exchanger, the room temperature (T4) within an interior environment, and the outdoor temperature (T5) in an exterior environment, and also further comprises pressure sensors configured to measure: the reservoir pressure (P1), the wet mixture pressure (P2), and the hot side pressure (P3).

4. The heat pump system of claim 1, further comprising a fan control module configured to control one or more heat exchanger fans in the heat pump system based on temperature thresholds and adaptive control commands.

5. The heat pump system of claim 1, further comprising a heat pump simulator module configured to evaluate refrigerant behavior under application-specific environmental conditions using thermodynamic properties including internal energy (IE), pressure, entropy(S), and volume (V), for refrigerants.

6. The heat pump system of claim 1, wherein the control unit is configured to operate in either a cooling mode or a heating mode based on a mode selection parameter stored in the directive file.

7. The heat pump system of claim 1, wherein the memory further stores temperature control cycle data comprising a list including a set of current temperature, fill stroke degrees, and corresponding adaptive control settings for each step.

8. The heat pump system of claim 1, wherein the adaptive algorithm comprises a reservoir temperature correction mechanism to compensate for internal energy loss by modifying the predetermined pressure and temperature of the hot side vapor.

9. The heat pump system of claim 4, wherein the fan control module comprises a variable speed control using pulse width modulation (PWM) signals to adjust the speed of the heat addition or rejection heat exchanger fans.

10. The heat pump system of claim 1, wherein the heat pump system operates with a refrigerant selected from a group consisting of non-toxic, low GWP (Global Warming Potential), low ODP (Ozone Depletion Potential), and non-flammable refrigerants.

11. The heat pump system of claim 1, wherein the heat rejection heat exchanger includes a bypass valve that is controlled based on operational mode to optimize thermal efficiency.

12. The heat pump system of claim 1, wherein the processor is further configured to access a dual-ported RAM shared with an external application software module for advanced real-time control coordination.

13. The heat pump system of claim 1, wherein the control unit periodically evaluates system efficiency metrics, including mechanical power output, volumetric efficiency, and coefficient of performance (COP), to optimize control decisions.

14. A method for controlling an intelligent heat pump system, the method comprising: receiving real-time thermal and pressure data from a plurality of sensors monitoring the heat pump, including reservoir temperature; retrieving operational parameters from a directive file stored in a removable memory, the parameters including target reservoir temperature, target cold side temperature, pressure control data, valve timing, and temperature cycle instructions; comparing the received real-time sensor data with the target parameters to determine deviations in pressure and temperature of the heat pump by executing an adaptive control algorithm; adjusting operation of one or more components of the heat pump selected from a supply valve, a regulating valve, a return valve, or a compressor-expander based on the determined deviations; and regulating temperature and pressure to drive the heat pump system toward a target steady-state thermal condition.

15. The method of claim 14, wherein regulating temperature and pressure includes executing a temperature control cycle as a loop method, the loop comprising a repeating sequence of final current temperature values configured to toggle between reservoir temperature correction and fan operation, thereby maintaining the reservoir temperature within a defined target range.

16. The method of claim 14, wherein the adaptive control algorithm dynamically adjusts the fill stroke degree of a piston valve in response to pressure deviations during heating or cooling operations.

17. The method of claim 14, wherein internal energy changes are calculated using thermodynamic fluid properties.

18. The method of claim 14, further comprising the step of switching control from a set of temperatures, i.e., T2 to T1, once the cold side temperature reaches its final target setpoint.

19. The method of claim 14, wherein the hot side pressure is adjusted using a stepper motor-controlled pressure regulator valve with a specified maximum response pressure and motor transit time.

20. The method of claim 14, wherein the control unit operates with a solenoid valve delay calibration to synchronize refrigerant flow timing in coordination with temperature control cycles.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0033] FIG. 1 illustrates an intelligent heat pump system in accordance with an embodiment of the present invention.

[0034] FIG. 2 illustrates a flowchart of the functioning of a smart heat pump in accordance with an embodiment of the present invention.

[0035] FIG. 3 illustrates the simulation of the smart heat pump, in accordance with an embodiment of the present invention.

[0036] FIG. 4 illustrates the simulation of the smart heat pump, showing the relationship between pressure and volume in accordance with an embodiment of the present invention.

[0037] FIG. 5 illustrates a graph of pressure and volume for adiabatic and isothermal expansion, in accordance with an embodiment of the present invention.

[0038] FIG. 6 illustrates the operating characteristics of a single-stage unmodulated heat pump, in accordance with an embodiment of the present invention.

[0039] FIG. 7 illustrates a temperature variation of the reservoir, cold liquid, and hot vapor over a specific time period of the heat pump, in accordance with an embodiment of the present invention.

[0040] FIG. 8 illustrates the functioning of the heat pump in heating mode and cooling mode, in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

[0041] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and the following description. Numerous variations, changes, and substitutions may occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the present disclosure herein may be employed.

[0042] At the outset, for ease of reference, certain terms used in this application and their meanings as used in this context are set forth. To the extent a term used herein is not defined below, it should be given the broadest definition that persons in the pertinent art have given that term as reflected in at least one printed publication or issued patent. Furthermore, the present techniques are not limited by the terms used in the application, as all equivalents, synonyms, new developments, and terms or techniques that serve the same or a similar purpose are considered to be within the scope of the present claims.

[0043] The articles a and an as used herein mean one or more when applied to any feature in embodiments of the present invention described in the specification and claims. The use of a and an does not limit the meaning to a single feature unless such a limit is specifically stated. The article the preceding singular or plural nouns or noun phrases denotes a particular specified feature or particular specified features and may have a singular or plural connotation depending upon the context in which it is used. The adjective any means one, some, or all indiscriminately of whatever quantity.

[0044] It will be further understood that the terms comprises and/or comprising, when used in this specification, specify the presence of stated features, steps, operations, elements, and/or components but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof.

[0045] As used herein, the term or includes and/or and the term and/or includes any and all combinations of one or more of the associated listed items. Expressions such as at least one of when preceding a list of elements modify the entire list of elements and do not modify the individual elements of the list.

[0046] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one having ordinary skill in the art to which this invention pertains. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0047] The instant invention addresses key limitations in current heat pump control technologies by providing a robust, adaptive, and thermodynamically informed controller that optimizes performance across a broad range of heating and cooling scenarios.

[0048] The heat transfer apparatus is designed as an integrated assembly of mechanical, electrical, and software components working cohesively to regulate thermal conditions efficiently. At its core, the system comprises a compressor-expander driven by a prime mover, a reservoir for managing the working fluid, multiple solenoid valves for precise control of fluid flow, and an array of temperature and pressure sensors that provide real-time operational data. These hardware components are orchestrated by a centralized control unit equipped with an adaptive algorithm, which dynamically adjusts valve timings and compressor operation based on sensor feedback and predefined operational directives stored in external memory. This architecture enables continuous monitoring and adjustment, maintaining target temperatures and pressures under varying environmental and load conditions.

[0049] Referring to FIG. 1, an intelligent heat pump system 100 comprises a heat pump 102 including one or more components such as a supply valve, a regulating valve, a return valve, or a compressor-expander 104. The heat pump 102 further includes a plurality of sensors 106 strategically positioned to monitor thermal and pressure conditions, including at least the reservoir temperature. A removable memory device 108 is configured to store a directive file 110 containing operational parameters, including target reservoir temperature, target cold side temperature, pressure control data, valve timing, and temperature cycle instructions. A control unit 112 comprising a processor 114 and memory 116 is communicably connected to the heat pump 102. The processor 114 is configured to execute one or more modules stored in memory 116. These modules include a data acquisition module 118 configured to receive real-time data collected from the plurality of sensors 106 and a firmware module 120 comprising sensor calibration routines, motor and valve control logic, and an adaptive control algorithm. The firmware module 120 is further configured to (a) compare real-time sensor data with target parameters from the directive file 110 to detect deviations in temperature and pressure and (b) adjust the operation of the supply valve, regulating valve, return valve, or compressor-expander 104 accordingly. This control logic enables the system to regulate temperature and pressure efficiently, driving the system toward a desired steady-state thermal condition.

[0050] In an intelligent heat pump system 100, the steady-state thermal condition refers to the operational state in which the system 100 maintains a substantially constant temperature and pressure over time, with minimal fluctuation. This state is achieved after the adaptive control algorithm has continuously adjusted the operation of one or more components, including the supply valve, regulating valve, return valve, or compressor-expander 104, based on real-time sensor data and the target parameters stored in the directive file 110 within the removable memory device 108. Upon reaching the steady-state condition, heat pump 102 operates in thermal equilibrium, where the rate of heat absorbed equals the rate of heat rejected, ensuring consistent performance and energy efficiency. Maintaining this state is essential for optimal thermal regulation of the reservoir and cold-side temperatures, contributing to both performance stability and system longevity.

[0051] The data acquisition module 118 collects real-time data from a plurality of temperature and pressure sensors installed across various critical points of the heat pump apparatus. The pressure sensors are typically installed at the compressor inlet, outlet, reservoir, and expansion chamber, as well as at both the hot-side and cold-side heat exchangers. These sensors provide essential pressure readings that inform the system about the state of the refrigerant and fluid flow dynamics at each stage of the cycle.

[0052] In parallel, temperature sensors monitor key locations, including the reservoir (for measuring T1), the cold side outlet (for T2), the compressor body, and the return lines. These temperature readings are vital for the adaptive algorithm to determine thermal deviations and guide corrective actions in both heating and cooling modes.

[0053] The temperature sensors are strategically placed to monitor critical points within and around the heat pump system. These include sensors at the reservoir, which measure the temperature of the working fluid stored there, as well as sensors on the cold-side and hot-side heat exchangers to track the refrigerant temperatures during cooling and heating cycles. Additionally, temperature sensors monitor both the ambient room temperature where the heat pump is installed and the outside or ambient outdoor temperature, as applicable. These multiple temperature readings provide comprehensive thermal data that the control system uses to accurately adjust and maintain the desired operating conditions of the heat pump.

[0054] The room thermostat functions as both a temperature sensor and a controller, monitoring the ambient temperature of a room and helping to maintain a desired comfort level. It measures the current room temperature and compares it to a set target temperature set by the user. Based on this comparison, the thermostat sends signals to the heating or cooling system to turn on or off, adjusting the operation to keep the room temperature within the desired range. Essentially, it acts as an automatic switch that ensures efficient climate control by preventing the room from becoming too hot or too cold.

[0055] The real-time data from the plurality of sensors 106 is continuously received and processed by the data acquisition module 118 of the control unit 112, which is communicably connected to the heat pump 102. Control unit 112 has firmware module 120, which runs an adaptive control algorithm designed to analyze deviations between actual sensor readings and target values stored in a directive file. Based on this analysis, the system dynamically adjusts the operation of solenoid valves, including the supply valve and return valve, as well as the pressure regulator. Furthermore, it modulates the compressor-expander mechanism to steer the system toward a steady-state thermal condition.

[0056] Through this closed-loop control architecture, the system 100 not only ensures precise regulation of temperature and pressure conditions but also supports energy-efficient operation across a range of varying environmental conditions. This capability enables the heat pump to maintain optimal performance over a wide operational range while adapting to the specific characteristics of the refrigerant in use.

[0057] Each sensor is carefully calibrated using data stored in Directive File 110 on a removable or external memory device 108, ensuring that every reading is accurate. This file also contains key control directivesincluding the duration to open certain valves, target temperatures to achieve, and timing delaysall tailored to the specific environment in which the pump operates.

[0058] When the thermostat sends a signal to turn on, the heat pump control unit wakes up and starts the system. It reads important instructions from a directive file that tells it the target temperatures and how the valves should operate.

[0059] The control unit 112 then activates the DC motor, which in turn moves the piston inside the compressor-expander 104. It uses sensors to track the piston's position carefully. Based on this, control unit 112 decides when to open and close two key valvesvalve V1 (which lets fluid into the piston chamber) and valve V2 (which lets fluid out).

[0060] At the start, the system quickly brings the cold side temperature close to the desired level without any smart adjustments. Once it's near the target, control unit 112 activates an adaptive algorithma kind of smart learning systemthat fine-tunes how long valve V1 stays open during each piston cycle. This helps the system maintain the exact temperature needed.

[0061] The control unit 112 also watches pressures and temperatures from various sensors and adjusts the valves and compressor accordingly. It even controls fans that help move heat into or out of the system, depending on whether heating or cooling is needed.

[0062] If the thermostat sends a signal to turn off, the control unit doesn't stop everything right away. Instead, it carefully shuts down by keeping the valves open just long enough to avoid any damage, then safely powers down the motor and other components, waiting for the next signal to start again.

[0063] After the room thermostat sends a signal to turn the heat pump on or off, the system starts the DC motor, which drives the piston inside the compressor-expander 104. The position of the piston is continuously monitored by an encoder, which provides real-time feedback on the piston's location within its cycle, such as when it reaches the Top Dead Center (TDC) or Bottom Dead Center (BDC). This information is crucial because it allows the control system to precisely time the opening and closing of the solenoid valves. Valve V1 controls the flow of fluid into the piston chamber from the reservoir, while Valve V2 controls the flow of fluid out of the chamber back to the reservoir. Based on the piston's position as measured by the encoder, the system determines the exact intervals to open and close these valves during each piston cycle, ensuring the correct amount of working fluid flows through the system. This precise timing is crucial for maintaining the desired pressure and temperature levels within the heat pump. Meanwhile, the control system constantly compares real-time sensor data with target temperatures and pressures. Using an adaptive algorithm, the system adjusts the valve timings to fine-tune its operation, enabling the heat pump to smoothly reach and maintain the set temperature. This cycle of piston movement, encoder feedback, valve control, and adaptive adjustment repeats continuously, allowing the heat pump to efficiently provide heating or cooling as needed.

[0064] In the heat pump system, an external memory device 108 stores a specially prepared file 110 containing data tailored to the specific application. When the heat pump starts, the firmware module 120 within the control unit 112 reads this file to retrieve critical operational information. The data includes sensor calibration values for both pressure and temperature sensors, ensuring accurate readings during operation. It also contains the response delays for solenoid valves V1 and V2, which help the system adjust valve timings accurately.

[0065] Additionally, the file includes a time adjustment gain value for the adaptive algorithm, which determines how quickly the system should respond to temperature differences. The V1 On Interval Degrees are defined for two different control phases: the Initial Temperature Control phase, which is active when the system first starts and rapidly moves toward the target temperature, and the At Temperature Control phase, which is activated once the target temperature is nearly reached and requires more precise adjustments.

[0066] Target temperatures for the reservoir (T1) and the cold side (T2) are specified, along with an optional differential change value for T2, allowing the system to approach the target cold side temperature in smaller steps if needed. This helps reduce overshooting or oscillations. The file also includes the Hot Side Condensation pressure, which determines Condensation Temperature, which is used by the V4 electronic pressure regulator to maintain optimal conditions for condensation and overall heat pump performance.

[0067] A directive file 110 contains the following information, which is presented below in tabular form:

a Directive File Provides the Following Information

TABLE-US-00001 TABLE 1 Contents Of External File Sensor calibration data, Pressure, and Temperature. Valve V1 and V2 Response Delay V1/V2 Time Adjust Gain For Adaptive Algorithm V1 On Interval Degrees 1. Initial Temperature Control 2. At Temperature Control T1 Target Temperature Reservoir target temperature T2 Target Temperature Cold side target temperature T2 Target Differential Optional: if other than zero is enabled. Temperature Change Temperature Control provides the V1 On Interval for each T2 Target Temperature. Hot Side Condensation Used by V4 Electronic Pressure Temperature Regulator

[0068] Referring to FIG. 2, a flowchart of the functioning of the smart heat pump is disclosed in accordance with an embodiment of the present invention.

[0069] The Smart Heat Pump's operation begins at Step 200, where the system waits for a signal from the thermostat to initiate heating or cooling. Once activated, the system determines the operating modeheating or coolingand sets the reversing valve accordingly. It captures room temperature (T4) and outside temperature (T5) and proceeds to read sensor calibration data and HPcontrol directives from an external memory device. These directives include parameters such as valve response delays, target temperatures (T1, T2), gain settings for adaptive control, and pressure regulator settings. After loading the necessary files, solenoid valves V1 and V2 are energized fully (set to ON) to ensure uninterrupted fluid flow during synchronization.

[0070] At Step 202/204, the system initiates DC motor control by energizing the motor and aligning its operation with signals from the piston position encoder at Bottom Dead Center (BDC). This alignment process is repeated three times to ensure precise timing. Once synchronization is complete, the system calculates the V1 On Interval based on encoder resolution, taking into account valve delays and directive parameters. It also determines the initial V2 On Interval and initializes the cycle time counter, setting the stage for the dynamic control loop to commence.

[0071] Step 204 marks the entry into the continuous heat pump control cycle. The controller determines the V1 Cycle Time and recalculates the V1 On Interval based on current motor speed and position encoder feedback. Temperature T1 (reservoir temperature) is captured during this phase for later use in adaptive control.

[0072] In Step 206, the V1 On Interval is confirmed and refined, and the initial V2 On Interval is established. The V2 timing is based on the calculated end of the V1 interval and adjusted for the valve delay. This interval will continue to be updated dynamically in the next block.

[0073] Step 208 involves the real-time calculation of V2 Cycle Time and V2 On Interval. The system takes into account piston movement, encoder signals, and time delays to ensure that the fluid is effectively expelled from the cylinder during each cycle.

[0074] At Step 210, the system confirms the V2 On Interval and activates solenoid valve V2 for the defined period. This step completes the main metering function of the fluid during one full piston cycle.

[0075] During Step 212, as the piston reaches Top Dead Center (TDC), the system captures critical temperature and pressure values. These include cold side temperature (T2), hot side temperature (T3), and pressures P1 (reservoir), P2 (wet mixture), and P3 (hot side). These readings are crucial for assessing performance and adjusting control parameters.

[0076] Step 214 initiates preparation for the next cycle by executing the V1 Interval Adaptive Algorithm Adjustment. This algorithm evaluates the difference between current and target temperatures (T1 or T2) and adaptively modifies the V1 On Interval. The gain setting, as specified in the directive file, determines how quickly the system converges on the target temperature, striking a balance between speed and stability.

[0077] In Step 216, the system evaluates whether reservoir temperature control should take priority over cold-side temperature control. If the reservoir temperature deviates beyond a threshold defined in the directive, the adaptive algorithm temporarily switches control from T2 to T1 using the same core method.

[0078] Step 218 handles the transition from the initial temperature control phase to the steady-state or At Temperature Control phase. Once the target T2 temperature is reached, the V1 adaptive algorithm becomes fully active for maintaining stable operation.

[0079] At Step 220, if enabled, the system performs differential temperature control. This feature steps the T2 temperature down incrementally based on a defined differential, retrieving new V1 On Interval values from an array in the directive file. This approach helps avoid overshoot and ensures smoother convergence, particularly at low cold-side temperatures.

[0080] Finally, Step 222 initiates the shutdown sequence of the heat pump. The system safely powers down the valves and motor in a controlled manner, ensuring no mechanical or pressure-related issues occur. The system then returns to standby, waiting for the next thermostat signal to repeat the process.

[0081] The simulation of the Smart Heat Pump, as illustrated in FIG. 3, begins with Step 300, where the piston design criteria are retrieved. These are sourced from Table 2.2a, and all thermodynamic data used in the simulation are derived from the NIST RefProp DLL library. Table 2.2a is presented below:

[0082] Following is a description of the variables which are in English units.

TABLE-US-00002 TABLE 2.2a Pistonhp Input Arguments Mnemonic Description (meaning) Units Trl Temperature of the System Reservoir F. dPrl Pressure above saturation pressure (sub-cooled). psi Tpe Temperature (cold side) of the piston expansion fluid F. DIAp Diameter of the piston inches STp Maximum stroke of the piston, if >0 STprl is calculated and the inches STprl on the command line replaced with this value. If 0 maximum piston stroke is defined by STprl. STprl Stroke of the piston reservoir inlet liquid to meet Tpe inches requirement. Tvrtcnd Condensation temperature of the hot side vapor F. Troom Temperature of the room desired (from thermostat) F. RPM Speed of the heat pump RPM Tout Temperature Outside. Only used for heating mode F. Hdr Predefined types of test results written to PistonHP.txt SVdelay Solenoid Valve response delay, i.e. turn on/turn off time ms Cool If a 1 informs HPsimulator that the simulation is for cooling, otherwise for heating

[0083] This command configures the simulation for refrigerant R134a, running in cooling mode, with all relevant physical and environmental parameters providedsuch as temperatures, piston specs, RPM, and valve timing. The simulator will utilize this data to simulate the behavior of the heat pump, analyzing energy transfer, pressure changes, and cycle efficiency. An example of this simulation:

TABLE-US-00003 Tvrt- SV- Trl dPrl Tpe DIAp STp STprl cnd Troom RPM Tout Hdr delay Cool PistonHP R134A75.0 5.0 55.0 2.50 5.0 0.948 78.5 75.0 60 75.0 3 30 30 1

[0084] The following are the results returned in the PistonHP.txt file. The first two lines echo the command line, followed by the data returned.

TABLE-US-00004 ControData Refrigerant Trl dPrl Tpe DIAp STp STparl Tvrtend Troom RPM Toutside Hdr SVdelay Cool PistonHP R134A 75.0 5.0 55.0 2.50 5.0 0.948 79.72 75.0 60 75.0 3 30 30 1 [0085] PWR at 60 RPM Tvrtcnd=79.72 F. Pvrtcnd=100.92 psi

TABLE-US-00005 Fill Stroke Degrees PWR- PWR- PWR- PWR- PWR- (SV Trl Tresv Prl Ppe Tpe Tpcv out inGen outVC outMech inEff Refrig COPr- Deg F. F. psi psi F. F. hp hp hp hp hp Tons COPr COPh Carnot On) 75.0 73.5 98.4 65.9 55.0 82.4 0.067 0.062 0.021 0.049 0.041 0.372 42.74 43.93 . . . 45.5 (34.7) 75.0 75.0 98.4 65.9 55.0 134.6 0.405 0.062 0 200 0.206 0.138 0.372 12.71 14.13 6.47 45.5 18.76 (34.7)

[0086] The smart heat pump uses a control strategy for T1 (reservoir temperature) inspired by car oxygen sensors. In cars, oxygen sensors switch between rich and lean fuel-air mixtures based on a nonlinear relationship between voltage and oxygen. This oscillation helps maintain efficiency despite sensor delays or inaccuracies.

[0087] Similarly, instead of holding T1 at a fixed value, the heat pump allows it to cycle within a defined range. This threshold-based approach adjusts the system only when T1 crosses upper or lower limits, making it more stable and adaptive. Like the oxygen sensor method, this avoids inefficiencies caused by slow sensor response or external disturbances, ensuring reliable and efficient temperature control.

[0088] Following that, in Step 302, the system gathers fluid thermodynamic data for various states of the working fluid, including pressure, temperature, density, enthalpy, entropy, internal energy, and vapor-liquid quality factor, covering conditions such as reservoir saturation, sub-cooled reservoir liquid, and cold side or hot side phase behavior.

[0089] In Step 304, expansion data is calculated, including piston inlet stroke, cold liquid and vapor mass, and volume. Depending on whether a specific command-line parameter (STp) is defined, the simulator computes stroke values accordingly to determine piston performance. Step 306 focuses on obtaining condensation data for the hot side. This is where cooling and heating modes diverge: in cooling, the rejection heat exchanger is bypassed; in heating, both heat addition and rejection exchangers are utilized, and their thermodynamic behaviors are analyzed.

[0090] Proceeding to Step 308, the reservoir liquid temperature correction (Trl correction) is performed, particularly for cooling mode, where it is essential for accurately modeling the reservoir's thermal behavior. Steps 309 and 310 gather ambient thermodynamic data: in cooling, only room temperature is required; in heating, both indoor and outdoor data are essential. This includes the full thermodynamic profile (temperature, pressure, etc.) of the surrounding environment.

[0091] In Step 312, the simulator distinguishes between heating and cooling modes for heat addition and rejection calculations. Variables such as Hadd\Delta H_{\text{add}}Hadd and Hrej\Delta H_{\text{rej}}Hrej represent the change in enthalpy due to temperature differences in returned cold side liquid and condensed hot side vapor. Separate calculations are executed in Steps 312, 314, and 316, depending on whether the cooling mode involves a heat rejection heat exchanger or not.

[0092] Step 314 initiates the calculation of expansion work using a dedicated subroutine (Wabdct_exp( )). Two key values are derived: W2ipdv\text{W2}_{\text{ipdv}}W2ipdv}}, representing work done during liquid vaporization, and W2hsipdv\text{W2hs}_{\text{ipdv}}W2hsipdv}}, indicating total work returned in the compression phase. These are crucial for understanding how energy is stored and transferred throughout the cycle.

[0093] Next, in Step 316, the compression work developed during the cold vapor compression phase is computed using Wabdct_cmp( ), resulting in the variable W3ipdv\text{W3}_{\text{ipdv}}W3ipdv}}, which quantifies the adiabatic energy needed to compress the cold vapor. These three energy variables are summarized in Step 322, where mechanical work, thermal work, and effective input power are reconciled:

TABLE-US-00006 PWRinGEN=W2ipdv\text{PWRinGEN} = \text{W2}_{\text{ipdv}}PWRinGEN=W2ipdv} }, PWRoutTotal=W2hsipdv\text{PWRoutTotal} = \text{W2hs}_{\text{ipdv}}PWRoutTotal=W2hsipdv}}, and PWRoutVC=W3ipdv\text{PWRoutVC} = \text{W3}_{\text{ipdv}}PWRoutVC=W3ipdv}}. Derived values such as mechanical output power (PWRoutMechanical\text{PWRoutMechanical}PWRoutMechanical) and effective input power (PWRinEff\text{PWRinEff}PWRinEff) provide insights into system efficiency.

[0094] Step 318 compiles all simulation results into a report, as shown in Table 2.2b. This leads to Step 320, which redefines traditional approaches to energy balance. The simulator employs a bulk analysis model, where the cold and hot side masses are independently tracked from the reservoir inlet through expansion and compression, and into their respective heat exchangers. The difference in internal energy before and after the cycle (rather than enthalpy or entropy) reveals an important insight: in cooling mode, the reservoir consistently loses energy unless it is compensated, indicating an inherent system inefficiency that requires mitigation.

[0095] The following is a description of the variables, which are expressed in English units.

TABLE-US-00007 TABLE 2.2b PHP Design Simulation Values Mnemonic Description (meaning) Units Tvrtcnd Condensation temperature of the hot side vapor F. Pvrtcnd Condensation pressure of the hot side vapor psia Trl Temperature of the System Reservoir F. Tresv Temperature of the combined mass of the cold side F. and hot side returned to the reservoir Prl Pressure of the System Reservoir psia Ppe Piston cold side expansion pressure psia Tpe Temperature (cold side) of the piston expansion fluid F. Tpcv Temperature (hot side) of the piston compression fluid F. W2ipdv Work generated during expansion: integrated P?V, in-lbs 1,000 integrations W2hs_ipdv Total Work stored during expansion for return in Compression: integrated P?V, 1,000 integrations W3ipdv Work of vapor compression: integrated P?V, 1,000 in-lbs integrations Wt Net work: Used for determining COPr and COPh in-lbs values STp Maximum stroke of the piston inches Eff % of W2ipdv returned: W2hs_ipdv/W2ipdv * 100 PWRinGen Power of W2ipdv: Power generated from liquid hp vaporization PWRoutVapCmp Power of W3ipdv: Vapor Compression hp PWRoutTotal Power in during liquid expansion and stored for the hp compression part of the cycle. Vapor compression and Mechanical power generated PWRoutMechanical Mechanical power is generated during the hp compression part of the cycle. PWRinEff Effective Power In required from an external hp source. See section 4.4 for how this is calculated. Refrig Cooling capacity in tons of ice tons COPr COP of cooling COPh COP of heating COPratio COPr/COPrCarnot for cooling and COPh/(COPrCarnot + 1.0) for heating COPr Carnot COP of theoretical refrigeration cycle EFFcarnot Efficiency of Carnot thermal motor % QFpev Expansion quality factor of the wet mixture, fraction as vapor QFpcv Compression quality factor of the wet mixture, fraction as vapor Fill Stroke Cylinder inlet volume of System Reservoir fluid for Degrees expansion SV Deg On Fill Stroke adjusted for SVdelay Degrees SVdelay Solenoid Valve response delay, i.e., turn on/turn off ms time Cool If a 1 informs HPcontrol Firmware that the cooling mode is requested, otherwise heating mode is requested.

[0096] To support adaptive control, Step 322 calculates the total solenoid valve on Duration for the inlet of reservoir liquid based on piston stroke and system geometry. This is refined in Step 324, where the actual solenoid valve On Duration is adjusted to account for the inherent delay in valve operation. The formula includes the directive-defined delay and cycle time.

[0097] Finally, Step 326 executes the Trl Correction necessary to address the energy loss observed in Step 320. It does so by increasing the hot side superheated vapor energy using NIST RefProp to determine new target internal energy values. The method involves first determining internal energy loss and then computing a new superheated pressure and temperature that compensates for this loss. This correction ensures that the reservoir does not experience continuous cooling during operation. A concise explanation of the given thermodynamic values and their relevance:

TABLE-US-00008 Vm 0.014403 lb Vapor mass IEmass 0.04985 Btu Fluid Internal Energy, IE, btu lost IE 170.770 Btu/lbm Compression IE now Sv 0.415176 Btu/lbm-R Compression entropy now IEnew 174.2308 Btu/lbm Calculate IEnew = IEmass/Vm + IE now Tcv 112.86 oF New compressed vapor temperature Pnewsh 138.61 psia New compressed super heated pressure Tnewcond 99.885 oF New condensation temperature

[0098] A key advantage of the described heat pump system lies in its ability to operate as a thermal motor in cooling mode, potentially becoming self-powered. This means that under certain conditions, the energy output can exceed the energy input required to run the pump. This feature enhances the heat pump's efficiency and versatility, enabling it to function effectively whether installed indoors or outdoors.

[0099] To achieve steady-state operation and high efficiency, the system utilizes a Temperature Control Cycle, which manages transitions from start-up to target conditions. This cycle can follow either a linear or a loop method. The linear method progresses through a fixed array of target temperatures, switching from T2 (cold side) to T1 (reservoir) control once the cold side target is met. The loop method, used primarily in cooling mode, cycles between selected temperature steps indefinitely to maintain stability and improve performance, especially when using Trl Correction or fan cycling strategies.

[0100] In cooling mode, the loop method is essential for realizing a self-powered heat pump. It achieves this by alternating between steps that either apply Trl Correction or operate the additional heat exchanger fan. Trl Correction, a step-change method, raises the reservoir temperature when needed. This method improves efficiency and can be enhanced by adopting a car oxygen sensor-like strategy, which mimics how automotive sensors rapidly adjust air-fuel mixtures based on binary rich/lean conditions.

[0101] To effectively manage the reservoir temperature T1, three control strategies are employed. First, adaptive control makes gradual, cycle-to-cycle adjustments and is best for general use. Second, Trl Correction applies step changes and is effective in specialized scenarios, especially when faster temperature increases are needed. Third, fan speed control adjusts the additional heat exchanger's fan gradually, making it suitable for situations where airflow management is critical.

[0102] Adaptive control of both T1 and T2 is crucial because these temperatures directly affect the heat pump's efficiency, particularly in cooling mode, where the heat rejection exchanger is bypassed. However, adaptive control of the hot side temperature (T3) is not recommended. T3 is indirectly influenced by pressure and heat balance, not by inlet valve control. Attempting to manage T3 adaptively could lead to system instability or oscillations, which outweigh any minimal efficiency gains.

[0103] The operational strategy prioritizes simplicity and consistency across applications. The target reservoir temperature (T1) should match the indoor room setpoint. The Trl correction is only applied after this target is met. Cold side temperature (T2) should be approached in equal 5 F. steps, using consistent adaptive gain values. A reservoir sub-cooled pressure of 5 psi is recommended, and piston backflow valves should maintain a pressure differential of at least 10 psi to offset flow resistance.

[0104] For cooling mode, the strategy begins by bringing the reservoir temperature (T1) to its target before adjusting the cold side (T2). The loop method should be used, ending with a Trl Correction step. The controller must monitor T1 and switch between loop control and adaptive control as needed to keep T1 within bounds. This process is continuous throughout the operation.

[0105] In heating mode, the reservoir temperature is raised to its target before adjusting T2. Here, the linear method is preferred. Just as in cooling mode, the system monitors T1 and switches between control strategies to maintain stability and efficiency. Although some future strategies are under consideration, the current approach provides a solid foundation for most applications.

[0106] The heat pump controller can receive its operating directives via two methods: either from an external file or via embedded software using dual-port RAM. This setup allows real-time control and communication between the application logic and the heat pump hardware. Directive data includes mode selection, valve delays, adaptive control parameters, target temperatures, temperature steps, fan speed settings, and calibration data. These parameters are crucial for the correct and efficient operation of heat pumps in various environments and scenarios. Note: means use the most recent stroke calculated

[0107] Refer to Appendix A for a cooling mode example, Appendix B for a heating mode example, and Appendix C for a special case.

TABLE-US-00009 APPENDIX A: Ambient outdoor temperature: Irrelevant, heat rejection heat exchanger bypassed. Cooling/Heating Mode (1 = Cooling, 0 = Heating, 1 = Heat Pump Off) 1 Solenoid Valve V1 and V2 Response Delay in ms V1 V2 Off On response response time time 30 30 Adaptive Control Algorithm GainT1 and threshold, F., for turning on T1 Adaptive Control. 0.25 +/2.0 Adaptive Control Algorithm GainT2 0.25 Target T1 Reservoir temperature F. 75 Target T2 Cold Side temperature F. 55 Temperature Control Cycle Mode (0 or 1 = Linear, 2 or more = Loop) 2 Temperature Control Cycle Interval time in seconds: 1 to (N-2), Piston Cycles: N-1, N 300 1 1 Temperature Control Cycle list: Adaptive Control (T1 or T2 Target) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 (1 = T1 Enable, 1 = T1 Disable, 2 = T2 Enable, 2 = T2 Disable, 3 = T1 Trl Correction) 1 2 2 2 2 2 3 Temperature Control Cycle list: Temperature F. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 75 70 65 60 55 55 55 Temperature Control Cycle list: Fill stroke degree 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 45.5 85.1 64.6 53.2 45.5 45.5 Rejection Heat Exchanger variable fan speed control (1.0 is full on, 0.0 is full off) 0 0 0 0 0 0 0 Addition Heat Exchanger variable fan speed control (1.0 is full on, 0.0 is full off) 0 1 1 1 1 1 1 Hot side V4 regulator pressure psi (Cooling or Heating), assumes reservoir is 5 psi sub-cooled pressure Max. 1 + 10 = 11 Info only: includes 1 psi V5 backflow valve and 10 psi piston backflow valve Hot Side Sub-cooled Differential Pressure psi, number of steps, Maximum pressure psi (MRP) Full stepper motor transit time seconds (time (sec.) to go from 0 psi to 700 psi 30 2500 700 12.5 Rejection Heat Exchanger Bypass Valve control (1 = open, 0 = closed) 1

TABLE-US-00010 Appendix B: Ambient outdoor temperature: 25 F. Cooling/Heating Mode (1 = Cooling, 0 = Heating, 1 = Heat Pump Off)) 0 Solenoid Valve V1 and V2 Response Delay in ms V1 V2 Off On response response time time 30 30 Adaptive Control Algorithm GainT1 and threshold, F., for turning on T1 Adaptive Control. 0.25 +/2.0 Adaptive Control Algorithm GainT2 0.25 Target T1 Reservoir temperature F. 75 Target T2 Cold Side temperature F. 15 Temperature Control Cycle Mode (0 or 1 = Linear, 2 or more = Loop) 0 Temperature Control Cycle Interval time in seconds: 1 to (N-2), Piston Cycles: N-1, N 300 NA NA Temperature Control Cycle list: Adaptive Control (T1 or T2 Target) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 (1 = T1 Enable, 1 = T1 Disable, 2 = T2 Enable, 2 = T2 Disable, 3 = T1 Trl Correction) 1 2 2 2 2 2 2 1 Temperature Control Cycle list: Temperature F. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 15 65 55 45 35 25 15 15 Temperature Control Cycle list: Fill stroke degree 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 28.7 104.6 67.8 51.6 41.4 34.2 28.7 Rejection Heat Exchanger variable fan speed control (1.0 is full on, 0.0 is full off) 1 1 1 1 1 1 1 1 Addition Heat Exchanger variable fan speed control (1.0 is full on, 0.0 is full off) 1 1 1 1 1 1 1 1 Hot side regulator pressure psi (Cooling or Heating), assumes reservoir is 5 psi sub-cooled pressure 48 N/A Info only: Does not include 10 psi piston backflow valve Hot Side Sub-cooled Differential Pressure psi, number of steps, Maximum pressure psi (MRP) Full stepper motor transit time seconds (time (sec.) to go from 0 psi to 700 psi 30 2500 700 12.5 Rejection Heat Exchanger Bypass Valve control (1 = open, 0 = closed) 0

TABLE-US-00011 Appendix C: This is a special case for cooling mode where the heat pump becomes self-powered when operating at steady state. Trl dPrl Tpe DIAp STp STprl Tvrt-cnd Troom RPM Tout Hdr SV-delay Cool Piston R134A 75.0 5.0 5.0 2.50 10.0 0.288 79.7 75.0 60 75.0 3 30 30 1 HP PWR- PWR- PWR- out PWR- PWR- Trl Tresv Prl Ppe Tpe Tpcv out inGen VC outMech inEff Refrig CO F. F. psi psi F. F. hp hp hp hp hp Tons COPr Ph 75.0 73.4 98.4 23.8 5.0 94.9 0.465 0.403 0.333 0.132 0.070 0.321 21.55 4.74 75.0 75.0 98.4 23.8 5.0 113.2 0.742 0.403 0.519 0.223 0.116 0.321 13.00 4.46 Cooling/Heating Mode (1 = Cooling, 0 = Heating, 1 = Heat Pump Off)) 1 Solenoid Valve V1 and V2 Response Delay in ms V1 Off V2 On response response time time 30 30 Adaptive Control Algorithm GainT1 and threshold, F., for turning on T1 Adaptive Control. 0.25 +/2.0 Adaptive Control Algorithm GainT2 0.25 Target T1 Reservoir temperature F. 75 Target T2 Cold Side temperature F. 5 Temperature Control Cycle Mode (0 or 1 = Linear, 2 or more = Loop) 2 Temperature Control Cycle Interval time in seconds: 1 to (N-2), Piston Cycles: N-1, N 300 1 1 Temperature Control Cycle list: Adaptive Control (T1 or T2 Target) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 (1 = T1 Enable, 1 = T1 Disable, 2 = T2 Enable, 2 = T2 Disable, 3 = T1 Trl Correction) 1 2 2 2 2 2 2 2 2 3 Temperature Control Cycle list: Temperature F. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 5 65 55 45 35 25 15 5 5 5 Temperature Control Cycle list: Fill stroke degree 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 24.4 104.6 67.8 51.6 41.4 34.2 28.7 24.4 24.4 24.4 Rejection Heat Exchanger variable fan speed control (1.0 is full on, 0.0 is full off) 0 0 0 0 0 0 0 0 0 0 Addition Heat Exchanger variable fan speed control (1.0 is full on, 0.0 is full off) 0 1 1 1 1 1 1 1 1 1 Hot side V4 regulator pressure psi (Cooling or Heating), assumes reservoir is 5 psi sub-cooled pressure Max. 1 + 10 = 11 Info only: includes 1 psi V5 backflow valve and 10 psi piston backflow valve Hot Side Sub-cooled Differential Pressure psi, number of steps, Maximum pressure psi (MRP) Full stepper motor transit time seconds (time (sec.) to go from 0 psi to 700 psi 30 2500 700 12.5 Rejection Heat Exchanger Bypass Valve control (1 = open, 0 = closed) 1

[0108] Referring to FIG. 4, the simulation of data from the heat pump is disclosed in accordance with an embodiment of the present invention. At step 400, a PHP design simulation is executed. At step 402, gathering of user input arguments is required, which includes calculating the piston area as detailed in Table 2.2a. At step 404, thermodynamic data are collected from the NIST RefProp program, encompassing various data points, including reservoir fluid saturation, thermodynamic properties, hot-side condensation pressure, reservoir sub-cooled thermodynamic properties, and data for adiabatic expansion and compression, as well as the wet mixture quality factor. In step 406, the cylinder inlet piston stroke and associated mass are calculated, along with retrieving additional thermodynamic and physical property data. This is followed by step 408, where work input is determined through the product of pressure and deviation in volume integration using the W2pdv function by calling Wadbr_exp( ). Next, Step 410 calculates work output via a similar PV integration with W3pdv, utilizing the Wadbc_cmp( ) function. The compression enthalpy is computed by integrating the deviation in heat from the compression temperature to the reservoir's temperature and pressure using the Heat_Rejhxgr ( ) function. Subsequently, step 412 involves calculating all simulation values, which are summarized in Table 2.2b. Finally, in step 414, the simulation results are stored in a specified text file named piston.txt.

[0109] The invention departs from traditional enthalpy-based thermodynamic models. Instead, it defines system performance in terms of mechanical and thermal energy separation using pressure-volume work analysis:

Enthalpy Assumption Flaw: Enthalpy assumes all energy within the cycle is thermal energy. In adiabatic systems, however, part of the energy is converted to mechanical work that exits the thermodynamic boundary.
PV Correction: By separating mechanical and thermal components (PWRoutVapCmp and PWRoutMechanical), the system calculates a corrected effective energy input (PWRinEff), accurately representing the true work required to operate the heat pump.

[0110] Two control cycle methods are employed:

Linear Method: A sequence of preset temperatures (Tnow) moves the system to the target reservoir temperature in discrete steps.
Loop Method: Alternates between specific temperatures within a loop. When Trl Correction is toggled on and off in alternating cycles, the average net input power (PWRinEff) approaches zero, effectively rendering the system self-powered.

Operating Behavior:

Without Trl Correction: The system produces mechanical energy in excess of what is required for expansion (PWRinEff<0), causing a natural cooling effect and driving the reservoir temperature downindicative of self-powered operation.
With Trl Correction: Maintains the target reservoir temperature (e.g., 75 F.), resulting in a positive PWRinEff, meaning net energy input is required.
Cycle Averaging: The alternating use of Trl Correction leads to an average PWRinEff0, supporting a self-sustaining thermodynamic state.

[0111] This section explains the fundamental differences between using enthalpy-based calculations and PV (pressure-volume energy)) based calculations in evaluating the performance of a new adiabatic heat pump technology. Tables 5.2a and 5.2b compare these two approaches. Table 5.2a uses enthalpy-based methods, which assume all energy transformations are thermal in nature. As a result, it shows misleading values, such as COPh always being equal to COPr+1. In contrast, Table 5.2b employs a new set of thermodynamic variables based on PV energy properties, which more accurately represent how energy is handled in this adiabatic system, where energy encompasses both thermal and mechanical components.

[0112] Several critical observations arise from this comparison. First, COPh is no longer equal to COPr+1 in the PV-based calculations, which is reasonable because mechanical energy is lost from the system during the compression cycle. This suggests that enthalpy is not a valid measure for evaluating performance in this new system, as it cannot account for the energy that is mechanically transferred or lost. For example, the effective input power (PWRinEff) becomes negative when Trl Correction is not used, indicating that more mechanical energy is returned during compression than is required during expansion, demonstrating a self-powered heat pump behavior. On the other hand, when Trl Correction is used, PWRinEff becomes positive, indicating that external energy is required, and the system is no longer self-powered.

[0113] Further analysis reveals that alternating between a cycle with Trl Correction and one without, while maintaining the T1 adaptive control algorithm always on and the T2 algorithm always off, can theoretically result in zero or even negative net power input. This means the heat pump can sustain operation on its own energy, making it effectively self-powered. The significance of this finding is profound: the heat pump's performance becomes independent of outdoor temperature, making this method universally applicable across all climates. Consequently, traditional performance metrics, including COP and SEER, become irrelevant.

[0114] This innovative approach makes the technology especially suitable for residential and commercial refrigeration and freezer applications. However, certain technical considerations must be addressed: a specialized addition heat exchanger is recommended for low cold-side temperatures, and it should have a modulated fan for better control. The T2 adaptive control algorithm might offer additional benefits if kept active. The heat pump should ideally be located indoors to avoid the long start-up period required to reach a steady state. Energy loss from the DC motor driving the pump should be minimized, though fan energy consumption has not yet been considered. Additionally, the reservoir should be filled to between one-third and one-half of its total volume to maintain a stable subcooled pressure. The inlet/outlet valves should utilize stepper motor-controlled rotary mechanisms for precise control.

TABLE-US-00012 TABLE 5.1a PV Properties Of The Piston Expansion And Compression Part Of The Cycle. Property Part of Property Description Piston cycle Functional Description PWRinGen Energy In Expansion PV energy is produced due to expansion of the vapor, which in turn lowers the pressure, causing the liquid to vaporize. Refer to section 7.3 for a graph of this thermodynamic principle. PWRoutTotal Energy Out Compression All PV energy is stored for this part of the piston cycle. Includes: 1) Vapor of expansion cycle. 2) Hot side vapor compression. PWRoutVapCMP Energy of Cold Compression PV thermal energy, which Vapor produces a hot vapor. Compression PWRoutMechanical Mechanical Compression PV mechanical energy or Energy Returned electrical energy as a result of mechanical energy derived from the cold side liquid vaporization. PWRinEff Effective Energy Expansion Effective Power in after adjustment In of returned power during the compression part of the piston cycle.

TABLE-US-00013 TABLE 5.1b Equations For Evaluating The PV Simulation Properties Equations used to evaluate COPr and COPh Variable to be From simulator: PowerinGen, PWRoutVapCmp, Evaluated PWRoutTotal PWRoutMechanical= PWRoutTotal PWRoutVapCmp PWRinEff= PWRoutTotal PWRoutMechanical PWRinGen COPr= PWR Cooling / PWRinEff COPh= PWRoutVapCmp / PWRinEff PWRcooling: From simulator (Energy Balance Equations), trustworthy.

[0115] The numbers highlighted in bold are enthalpy-derived and misleading, as explained in this section.

TABLE-US-00014 TABLE 5.2a Heat Pump Cooling Mode Parameters, Temperatures and test results using enthalpy Hot Side Condensation Piston Trl Trl Prl Ppe Tpe Tpcv Ppcv Tcond Pcond COPr- Cycles Correc. F. psia psia F. F. psia F. psia COPr COPh Ratio 209 Not 75.0 98.4 23.8 5.0 91.1 100.9 79.7 100.9 12.47 13.47 2.393 Used Used 75.0 98.4 23.8 5.0 113.2 145.4 103.9 145.4 8.32 9.32 1.939

TABLE-US-00015 TABLE 5.2b Heat Pump Heating Mode Parameters And Temperatures Using Adiabatic PV Properties PWR- PWR- PWRin out PWR-out out PWR-in PWR Tr Gen Total VapCmp Mechanical Eff cooling COPr COPr Correc. HP HP HP HP HP HP COPr COPh Carnot Ratio Not 0.403 0.421 0.2297 0.1217 0.1032 1.515 11.19 0.506 5.40 N/A used Used 0.403 0.742 0.5193 0.2231 0.1164 1.515 13.02 4.46 4.29 3.03

[0116] Table 5.2b illustrates the difference in COPr and COPh calculations when using PV properties instead of the enthalpy property of the fluid in the simulator and Energy Balance Equations that are enthalpy-based in Table 5.2a.

Observations and Conclusions

[0117] In accordance with the present invention, simulation data were analyzed using two fundamentally different thermodynamic models to evaluate system performance: traditional enthalpy-based energy calculations and the novel pressure-volume (PV) based method. This distinction underpins the core innovation of the invention.

[0118] Observation 1: As illustrated in Table 5.2a, enthalpy-based calculations result in a consistent relationship where the Coefficient of Performance for heating (COPh) equals the Coefficient of Performance for cooling (COPr) plus one (COPh=COPr+1). However, Table 5.2b, which uses the PV method, does not exhibit this relationship. Instead, COPh is significantly less than COPr, which is consistent with the expected behavior of an adiabatic thermodynamic system. In such systems, a portion of thermal energy is converted into mechanical energy that exits the system boundary, thus altering the energy balance.

[0119] Observation 2: Enthalpy is demonstrated to be an invalid thermodynamic property for evaluating this new adiabatic heat pump system. The enthalpy model assumes that all input work is converted into thermal energy, disregarding the contribution of mechanical energy. In contrast, the present invention accurately accounts for mechanical work (e.g., PWRoutMechanical), which is either returned to the system or extracted as useful output. Therefore, enthalpy-based performance metrics provide misleading results for this technology.

[0120] Observation 3: The system's behavior differs significantly depending on whether the Trl Correction is applied during Control Cycle 1. Without the Trl Correction, the system naturally cools as energy leaves the reservoir; with the correction, the reservoir is maintained at a stable target temperature (e.g., 75 F.). This distinction highlights the impact of thermal control on the system's energy balance.

[0121] Observation 4: When Trl Correction is not used, the effective power input (PWRinEff) becomes negative. This condition indicates that more mechanical energy is returned during compression than is consumed during expansion, which qualifies the system as self-powered. The reservoir temperature decreases with each piston cycle, evidencing net energy loss from the system.

[0122] Observation 5: When Trl Correction is applied, PWRinEff becomes positive, indicating that external energy is being consumed to maintain system operation. In this state, the system is no longer self-powered and functions as a conventional, externally powered device.

[0123] Observation 6: The difference in effective energy between operating modes (Trl Correction used vs. not used) is calculated as:

PWRinEff_withPWRinEff_without=0.1164+(0.1032)=0.0132

This average net energy value, being so small, implies that the system operates with the benefit of returned mechanical energy across cycles, further supporting the concept of a self-powered operational mode.

[0124] Observation 7: A continuous control scheme that toggles between two control cyclesone with Trl Correction off (self-powered) and the next with Trl Correction on (externally powered)can achieve zero net energy input. When the T1 adaptive control algorithm remains active and the T2 adaptive control algorithm remains inactive, this cyclical approach enables sustained operation with minimal or no external power, thereby establishing a closed-loop, self-sustained cycle.

Conclusions

[0125] Conclusion 1: A self-powered heat pump is demonstrably achievable under the described control methodology. The following points are critical:

[0126] Point 1: The system's performance and efficiency are not influenced by outdoor ambient temperature. This eliminates dependency on environmental conditions.

[0127] Point 2: The same control methodology applies universally across all climates and typical indoor room temperature requirements.

[0128] Point 3: Conventional efficiency metrics such as COP and SEER are no longer valid due to their reliance on enthalpy-based energy assumptions, which this invention bypasses.

[0129] Conclusion 2: This operating mode and control architecture are ideally suited for refrigeration applications, including both residential and commercial systems, where continuous cooling at low energy cost is desirable.

Technical Implementation Considerations

[0130] A specialized addition heat exchanger is recommended to operate efficiently at the lower cold side temperatures required. Fan modulation for the heat exchanger should be employed to maintain precise thermal conditions.

[0131] Consider enabling the T2 adaptive control algorithm in specific use cases for enhanced system stability or performance optimization.

[0132] The heat pump should be installed indoors to eliminate unnecessary startup cycles (e.g., 209 cycles to steady-state), which improves initial energy consumption and system responsiveness.

[0133] The DC motor used for piston drive should be optimized for minimal electrical losses to preserve the system's self-powered nature.

[0134] The power consumption of the fans used in heat exchangers was not included in this study and should be considered separately during the final system design and integration.

[0135] The reservoir fill level should be maintained between and of the total volume to minimize pressure variations and subcooling effects.

[0136] All inlet and outlet metering valves should utilize stepper motor rotary actuators for fine control over fluid flow and system pressure.

Simulation Results Supporting Heating Mode Start-Up Procedure

the desired indoor targete.g., 75 F. regardless of the initial system temperature at the start of the heating mode. Table 6.1a presents the results of such a start-up simulation with an initial outdoor temperature of 25 F. and a target indoor reservoir temperature of 75 F.

[0137] The simulations were conducted using the PistonHPs simulator, specifically engineered to evaluate heat pump systems based on pressure-volume (PV) thermodynamics. The simulator accounts for both thermal and mechanical energy contributions across the piston cycle, as explained in Section 5 (Study Results for Cooling), which remains applicable to heating mode analysis.

Thermodynamic Evaluation Methodologies

[0138] Table 6.1a shows results based on conventional enthalpy-based energy calculations.

[0139] Table 6.1b reflects results based on the proposed PV-based energy model detailed in Table 5.1a.

[0140] It is noted that enthalpy-derived datahighlighted in boldare misleading for evaluating the true performance of adiabatic heat pump systems, as further described below.

TABLE-US-00016 TABLE 6.1a Heat Pump Parameters, Temperatures And Test Results Using Enthalpy Hot Side Condensation Piston Trl Trl Prl Ppe Tpe Tpcv Ppcv Tcond Pcond COPh Cycles Correc F. psia psia F. F. psia F. psia COPr COPh Ratio 402 Not 75.0 98.4 29.7 15.0 119.4 156.4 108.0 156.4 1.283 9.146 1.645 Used Used 75.0 98.4 29.7 15.0 116.5 150.4 105.3 150.4 1.34 9.48 1.666

TABLE-US-00017 TABLE 6.1b Heat Pump Heating Mode Parameters And Temperatures Using Adiabatic PV Property PWR- PWR- PWR PWR- out PWR-out out PWR- Heating Trl inGen Total VapCmp Mechanical inEff Cooling COPh COPh Correc HP HP HP HP HP HP COPr COPh Carnot Ratio Not 0.353 0.7675 0.5430 0.2244 0.1903 2.092 1.542 10.99 5.56 1.98 Used 0.293 Used 0.353 0.7421 0.5481 0.2159 0.1554 2.092 0.293 3.85 5.69 0.68 0.293

Observations and Conclusions

[0141] Observation 1: Enthalpy is no longer a valid thermodynamic property for evaluating this adiabatic heat pump technology. Conventional enthalpy methods assume all input work manifests solely as thermal energy, which does not reflect the true energy dynamics of the current system. The invention accounts for both thermal energy (e.g., PWRoutVapCMP) and mechanical energy (PWRoutMechanical) that exits the system or is recycled into subsequent cycles through PWRinGen.

[0142] Observation 2: Table 6.1b illustrates the operational difference between Control Cycle 1 when Trl Correction is not applied (the system cools unintentionally) and when it is applied (the system maintains the target reservoir temperature). Utilizing Trl Correction at the beginning significantly reduces the number of cycles required to reach steady-state operation, avoiding up to 402 piston cycles and associated energy costs.

[0143] Observation 3: Notably, when Trl Correction is not applied in heating mode, the Coefficient of Performance for heating (COPh) is 10.99, compared to 3.85 with

[0144] correction applied. This result indicates that Trl Correction is not necessary or beneficial for heating efficiency. Across both enthalpy and PV-based evaluations, COPr values remain relatively consistent, suggesting stable cooling-side behavior in heating mode.

[0145] Observation 4: Unlike in cooling mode (Table 5.2b), where COPh and COPr diverge significantly, in heating mode (Table 6.1b), the two coefficients track more closely. This finding implies that enthalpy-based evaluations may still play a substantial role in heating mode, whereas in cooling mode, enthalpy is largely irrelevant. This observation underscores the differing thermodynamic behaviors between heating and cooling operations.

[0146] Conclusion: The simulations suggest that achieving a self-powered heat pump in heating mode is impractical due to the positive effective power input required (PWRinEff). In contrast, self-powered cooling mode operation is viable. This aligns with the principle that in heating mode, energy must be actively added to the system, while in cooling mode, energy can be extracted and recycled.

Design Recommendation:

[0147] To minimize energy consumption during startup and reduce the required 402 piston cycles to reach thermal equilibrium, the heat pump should be installed within the conditioned space. This configuration prevents energy loss to the ambient environment and facilitates faster stabilization, thereby improving overall system efficiency.

[0148] Referring to FIG. 5, a graph of pressure and volume for adiabatic and isothermal expansion is shown. An adiabatic process is defined as a thermodynamic transformation in which no heat is exchanged between the system and its surroundings. In such a process, the system under investigation is considered thermally insulated, and as a result, the heat transfer term q=0q=0q=0. During an adiabatic expansion, the system performs work by utilizing its internal energy. Consequently, the internal energy of the working fluid decreases, resulting in a decrease in temperature. This contrasts with isothermal expansion, where temperature remains constant through continuous heat input from the environment. The graphical representation of pressure-volume (P-V) behavior for both processes reveals a clear distinction: the adiabatic expansion curve is steeper than the isothermal expansion curve for the exact change in volume, due to the absence of heat input. This fundamental thermodynamic principle is essential for analyzing and designing systems, including the adiabatic heat pump described herein, where energy efficiency and self-powered operation depend critically on converting internal thermal energy to mechanical work without external heat transfer.

[0149] The system defined herein differs significantly from traditional vapor compression heat pumps (VCHPs), particularly single-stage, unmodulated systems that operate in binary on/off capacity modes. While the proposed Vapor Expansion Heat Pump (VEHP) also uses a single-stage mechanical structure, its capacity inherently varies due to adaptive thermodynamic control and mechanical energy recycling.

[0150] FIG. 6 illustrates the operating characteristics of a single-stage unmodulated heat pump. A conventional VCHP delivers a COPh in the range of 1.8 to 3.0, requiring resistive backup heating below 25 F. ambient. At this same ambient temperature, the VEHP achieves a COPh of 13.40 (Table 6.1b), a 5.6 improvement over conventional systems (13.40/2.4). This substantial performance enhancement underscores the transformative efficiency gains enabled by the new PV-based thermodynamic model and control architecture.

[0151] The present invention demonstrates that a self-powered heat pump operating in cooling mode is achievable. The Study Results for cooling are facilitated by the conversion of cooling energy into mechanical output energy, measured at 1.513 horsepower (HP) under controlled conditions. The underlying thermodynamic behavior observed in the heat pump bears significant similarity to that of a Vortex Thermal Motor (VTM). The VTM operates on the principle of thermal-to-mechanical energy conversion, wherein the system expels mechanical energy that originated as internal thermal energy. This expelled mechanical energy must be replenished, or the VTM will undergo a net temperature decrease.

[0152] By comparison, the heat pump described herein, categorized as a fifth-generation (5G) design, operates on the same principle when in cooling mode. During the expansion portion of the piston cycle, the refrigerant fluid undergoes a transformation in which part of its thermal internal energy is converted into PV mechanical work that leaves the system. Unless compensated via a thermal correction mechanism (such as the Trl Correction), the system temperature will continuously decrease.

[0153] This observed behavior establishes that the cooling-mode heat pump functions thermodynamically as a thermal motor, recycling thermal energy into mechanical output. This realization supports the feasibility of a self-powered cooling cycle, a novel departure from conventional vapor-compression-based refrigeration systems.

[0154] The objective of this study is to evaluate the performance of various refrigerants in the described adiabatic piston-type heat pump, specifically in terms of their capability to operate in a cooling-mode self-powered configuration.

[0155] Twenty-nine refrigerants were initially considered. Simulations were conducted using a proprietary heat pump simulator (PistonHP) under fixed mechanical parameters: [0156] Rotation speed: 60 RPM [0157] Piston stroke: 10 inches [0158] Solenoid valve delay: 30 milliseconds

[0159] Four refrigerants failed to meet the predefined operational criteria (Table 5.2a) and were excluded. The remaining twenty-five refrigerants were simulated under identical conditions.

Each Simulation Tested Two Sequential Temperature Control Cycles:

[0160] 1. Cycle 1: Trl Correction not usedthe reservoir is expected to cool. [0161] 2. Cycle 2: Trl Correction usedthe reservoir is restored to the target temperature (75 F.).

[0162] While this study executed the cycle pair only once per refrigerant, in practice, this control cycle would repeat continuously in an alternating fashion to sustain long-term operation. [0163] 1. Refrigeration Capacity (Refrig Tons) Column 9 [0164] 2. Cooling Efficiency (COPr Adiabatic) Column 11 [0165] Note: A negative COPr Adiabatic indicates self-powered operation. [0166] 3. Fill Stroke RequirementColumn 14 [0167] A minimum of 10.8 degrees is necessary to meet timing constraints imposed by the 30 ms solenoid valve delay.

[0168] Table 9.1 presents the results. Refrigerants are classified into three performance tiers: Data marked with superscript 3: Refrigerants with COPr Adiabatic <0, suitable for self-powered cooling operation. Sixteen refrigerants qualify; Data marked with superscript 2: Refrigerants demonstrating the highest cooling capacity, with reservoir temperature close to their critical temperature, resulting in minimal heat of vaporization, and Data marked with superscript 1: Refrigerants identified as second-best options, balancing capacity and fill stroke requirements.

TABLE-US-00018 TABLE 9.1 Tpcy PWPinEff Control Control Cycle COPr Cycle 1 & 2 PWRout 1 & 2 Cycle 2 Cooling Adiab Fill Cycle 1 Cycle 2 STpa Mech. Cycle 1 Cycle 2 Cycle 1 Refrig Power Avg. COPb COPr Stroke Refrig F. F. In. HP HP HP Diff. Tons HP HP Adiab Carrot Degrees R12 88.93 123.06 0.38 0.1130 0.1388 0.1411 0.0023 0.3280 1.5474 0.091 N/A 5.54 28.10 ETHANE 108.14 139.96 2.24 0.4839 0.4771 0.9016 0.4295 1.4670 6.9224 3.493 N/A 4.51 75.30 H25 158.05 254.36 0.87 0.4052 0.4125 0.6187 0.2062 1.0590 4.9985 2.019 N/A 3.04 43.30 N2O 132.67 209.91 2.10 0.8091 0.7801 1.4663 0.6862 2.2210 10.4793 3.143 N/A 3.64 72.30 SO2 187.56 231.78 0.14 0.0815 0.1106 0.0277 0.0829 0.2060 0.9737 13.174 N/A 2.62 17.00 SF6 78.33 110.31 1.15 0.2805 0.2843 0.4479 0.1636 0.8640 4.0771 2.619 N/A 6.30 50.60 R41 134.66 208.93 1.65 0.6204 0.6072 1.0015 0.3941 1.6680 7.8721 2.352 N/A 3.58 62.50 R32 137.54 197.78 0.70 0.3195 0.3293 0.4184 0.0891 0.8550 4.0374 1.305 N/A 3.51 38.70 R23 116.26 161.57 3.10 0.5317 0.5082 0.9189 0.4107 1.5630 7.3787 3.245 N/A 4.18 72.30 R22 113.09 158.42 0.53 0.1885 0.2079 0.2462 0.0383 0.5310 2.5067 0.938 N/A 4.30 33.40 R161 106.03 146.31 0.43 0.1686 0.1899 0.2669 0.0170 0.4770 2.2528 0.487 N/A 4.60 30.66 R152A 103.78 136.25 0.27 0.1065 0.1326 0.1041 0.9285 0.3030 1.4317 1.478 N/A 4.70 23.70 R134A 87 02 113.24 0.29 0.1106 0.1354 0.1164 0.0190 0.3210 1.5474 0.933 N/A 5.67 24.40 R143A 88.27 123.09 0.64 0.1976 0.2143 0.2837 0.0714 0.5820 2.7452 1.601 N/A 5.58 36.80 R13 97.68 136.81 1.99 0.3568 0.3489 0.7017 0.3528 1.1260 5.3143 3.829 N/A 5.01 70.00 R125 39.04 108.65 0.65 0.2002 0.2149 0.2842 0.0693 0.5950 2.8059 1.592 N/A 6.28 37.10 PROPYNE 106.88 143.39 0.31 0.1100 0.1365 0.1034 0.0311 0.3100 1.4624 1.581 N/A 4.56 25.10 PROPYLEN 95.38 137.89 0.66 0 1955 0.2143 0.2940 0.0797 0.5690 2.6843 1.698 N/A 5.14 37.50 PROPANE 87.01 123.66 0.55 0.1594 0.1811 0.2306 0.0495 0.4680 2.2067 1.308 N/A 5.67 34.00 AMMONIA 185.42 251.08 0.25 0.2169 0.2354 0.1732 0.0622 0.5420 2.5599 1.953 N/A 2.58 22.60 CFM 96.84 132.60 0.33 0.0884 0.1165 0.0950 0.0215 0.2550 1.2901 1.253 N/A 5.06 26.00 CO2 139.80 213.93 2.19 0.9041 0.8651 1.5395 0.6744 2.4140 11.3936 2.885 N/A 3.45 74.20 CO8 134.02 204.78 0.71 0 2470 0.2641 0.3637 0.0996 0.6750 3.1861 1.652 N/A 3.60 39.10 CYCLOPRO 113.90 152.53 0.34 0.1441 0.1690 0.1233 0.0457 0.3810 1.7976 1.971 N/A 4.27 26.50 DME 101.17 133.06 0.27 0.1070 0.1335 0.1121 0.0214 0.3050 1.4417 1.031 N/A 4.83 23.76 indicates data missing or illegible when filed

Example Critical Temperatures:

TABLE-US-00019 Refrigerant N.sub.2O R41 R23 CO.sub.2 Tc ( F.) 97.7 111.4 78.1 87.9

[0169] This classification suggests that proximity to the refrigerant's critical temperature enhances cooling cycle efficiency by reducing latent heat demands, thereby enabling the transformation of thermal energy into mechanical output with minimal phase transition energy costs.

[0170] The study identifies sixteen refrigerants capable of supporting self-powered operation in cooling mode, with multiple candidates offering superior refrigeration capacity due to their favorable thermodynamic properties near 75 F. The results validate the versatility of the proposed system and offer a refrigerant selection matrix for optimized design and deployment in diverse cooling applications.

[0171] The purpose of this study is to identify and evaluate suitable refrigerants that can operate efficiently in heating mode using the proposed adiabatic piston-based heat pump system. The goal is to determine which refrigerants demonstrate favorable thermal and mechanical performance characteristics under standardized operational parameters.

[0172] A total of twenty-nine refrigerants were initially considered for simulation using the proprietary PistonHP simulator. Of these, four refrigerants failed to meet the thermal and mechanical requirements defined in Table 6.1a and were excluded from further analysis. The remaining twenty-four refrigerants were simulated using the following fixed conditions: [0173] Piston stroke: 10 inches [0174] Solenoid valve delay: 30 milliseconds [0175] Operating speed: 60 RPM

[0176] Each refrigerant was evaluated under steady-state conditions, using the Trl Correction during the heating control cycle. This simulation condition represents the normal operating state of the heat pump after initial warm-up cycles in which the Trl Correction is not applied.

[0177] The viability and suitability of each refrigerant for heating mode operation were assessed based on the following parameters extracted from Table 10.1: [0178] 1. Heating Capacity (Heating Power, HP) Column 6 [0179] 2. Heating Efficiency (COPh Adiabatic) Column 8 [0180] 3. Fill Stroke RequirementColumn 10 [0181] Minimum acceptable value: 10.8 degrees (required to meet solenoid valve timing constraints with a 30 ms delay)

[0182] All simulations referenced the thermodynamic properties and bulk analysis models consistent with prior sections. Refer to Appendix B for definitions of all mnemonics and units.

Observation #1:

[0183] A trend was observed in which higher COPh Adiabatic values correlate with larger Fill Stroke Degrees. While the exact mechanism driving this correlation remains the subject of ongoing study, it is suggested that refrigerants with a more extended vapor expansion phase allow for greater energy transfer and more efficient compression during the heating cycle.

Table 10.1:

[0184] Refrigerants are categorized according to performance using the following highlights: [0185] Data marked with superscript 1: Refrigerants with performance closest to the critical temperature (75 F.), resulting in diminished latent heat of vaporization and higher thermal efficiency. [0186] Data marked with superscript 2: Refrigerants offering second-best performance, balancing heating capacity, and fill stroke compliance.

TABLE-US-00020 PWRout Heating COPh Fill STpa Mech. PWRinEff Power COPr Adiab COPh Stroke Refrig Tpcv In. HP HP HP Adiab HP Carnot Degrees R12 126.54 0.38 0.1765 0.1317 1.5544.sup.4 N/A 11.80 5.44 28.10 ETHANE 159.84 2.24 0.2810 0.7630 7.3936.sup.2 N/A 9.69 5.37 75.30.sup.2 H2S 252.01 0.87 1.9819 1.4367 13.415.sup.2 N/A 9.34 3.43 43.30.sup.1 N2O 207.32 2.10 0.1576 1.2624 11.322.sup.1 N/A 8.97 4.23 72.30 SO2 225.42 0.14 0.10826 0.0441 0.959 N/A 21.72 3.14 17.00 SF6 114.53 1.15 0.05179 0.0506 0.5452 N/A 10.78 5.69 50.60 R41 206.49 1.65 0.5688 0.8805 8.3417.sup.1 N/A 9.47 3.85 62.50.sup.1 R32 196.67 0.70 0.5224 0.3862 4.1160 N/A 10.657 3.83 38.70 R23 159.22 2.10 0.6315 0.7772 7.8813.sup.1 N/A 10.14 5.75 72.30.sup.1 R22 159.76 0.53 0.2995 0.2262 2.5824 N/A 11.18 4.48 33.40 R161 148.34 0.45 0.2651 0.1961 2.2624 N/A 11.54 3.74 30.60 R152A 138.18 0.27 0.1549 0.1044 1.4240 N/A 13.64 4.83 23.70 R134A 116.53 0.29 0.1564 0.1125 1.5083 N/A 13.40 5.55 24.40 R143A 126.91 0.64 0.3030 0.2579 2.7822 N/A 10.79 4.39 36.80 R13 138.03 1.99 0.3412 0.5916 5.6441.sup.2 N/A 9.54 5.21 70.00.sup.2 R125 113.39 0.65 0.2921 0.2566 2.8490 N/A 11.10 5.81 37.10 PROPYNE 145.33 0.31 0.1636 0.1054 1.4453 N/A 13.71 4.71 25.10 PROPYLEN 140.68 0.66 0.3237 0.2606 2.7282 N/A 10.469 3.78 37.50 PROPANE 127.45 0.55 0.2591 0.2100 2.2371 N/A 10.66 5.54 34.00 AMMONIA 246.04 0.25 0.3214 0.1925 2.5634 N/A 13.31 3.09 22.60 CF3I 135.47 0.33 0.8351 0.5667 7.3375 N/A 12.95 5.08 26.00 CO2 209.17 2.19 0.6379 1.3263 12.4083.sup.1 N/A 9.35 4.49 74.20.sup.1 COS 204.29 0.71 0.4437 0.3264 3.2666 N/A 10.09 3.91 39.10 CYCLOPRO 154.53 0.34 0.2133 0.1333 1.7647 N/A 13.23 4.57 26.50 DME 137.14 0.27 0.1606 0.1103 1.4367 N/A 3.02 3.89 23.70

Example Critical Temperatures:

TABLE-US-00021 Refrigerant N.sub.2O R41 R23 CO.sub.2 Tc ( F.) 97.7 111.4 78.1 87.9

[0187] Conclusion: None of the tested refrigerants demonstrated the ability to operate the heat pump in a self-powered heating mode based on COPh Adiabatic values.

[0188] However, several refrigerants exhibit excellent heating capacity and efficiency performance, making them highly suitable candidates for conventional heating applications within the proposed system.

[0189] Refrigerants highlighted in bold are identified as optimal for combined heating and cooling performance due to their proximity to the operational reservoir temperature and favorable phase characteristics.

[0190] Subscripted 2 refrigerants serve as strong secondary candidates where trade-offs in fill stroke or power output may be acceptable.

[0191] Implications: The data confirms that while cooling mode self-powered operation is achievable, heating mode will require continuous external energy input. Nonetheless, the high COPh Adiabatic values attainable with selected refrigerants validate the system's efficiency potential in traditional heating applications, particularly in residential or commercial HVAC systems, where operational reliability and energy performance are crucial.

[0192] Referring to FIG. 7, The purpose of the three graphs is to illustrate the temperature response of the adiabatic heat pump temperatures T1 (Reservoir), T2 (Cold liquid), and T3 (Hot Vapor) for refrigerant R134a with both the hot side and cold side heat exchangers bypassed, i.e. removed from the system, and all adaptive control disabled. All three graphs have the same initial conditions of T1 at 75 C. and the hot side at 85 C. The target cold side temperatures are as follows: first graph T2 is 70 F., second graph is 65 F., and third graph is 60 F. All three temperatures should reach a steady state at the end of the ten-minute test. Clearly illustrated is mechanical energy leaving the system in the first graph when the reservoir temperature T1 decreases to the cold side temperature T2 of 70 F., instead of holding steady at 75 F., it holds steady at the temperature T2 of 70 F. This phenomenon is also illustrated for the second and third graphs, given a longer test time. In the third graph, the line, Tresend, beginning at 450 seconds and continuing to the end of the test, is the heat pump simulator predicting this behavior. The heat pump simulator for the first and second graphs was also done and plotted, but not visible because of a perfect match. Another interesting phenomenon is that the reservoir temperature T1 is initially steady, then begins to decrease as the hot side temperature T3 approaches its target temperature of 85 C. Tresend stands for the temperature of the reservoir after each piston cycle, where the reservoir calculates the new temperature for the next piston cycle simulation, at the heat pump running at 15 RPM, that would result in 150 simulations plotted for each graph. Temperature changes over a specified period. Each graph is plotted against time in seconds, showcasing varying temperature trends. The first graph displays a gradual temperature decrease, stabilizing around 50-90 degrees for all three temperature points, indicating a relatively consistent thermal state. The second graph shows steady temperature levels over time with a slight decline in T3, suggesting a controlled heat release from the hot vapor. The third graph shows a more pronounced fluctuation in temperature, particularly with T3, which shows less stability overall. This suggests variations in heat retention or transfer during the experiment. Overall, these graphs offer valuable insights into the thermal behavior over time and reveal the system's heat transfer dynamics.

[0193] Referring to FIG. 8, an embodiment of the present invention discloses the heating mode 800A of the heat pump system. In the heating mode of the intelligent heat pump system, the system componentsincluding the piston 808, inlet valve 804 and outlet valve 806, heat exchangers, pressure regulator, bypass valve, and DC motoroperate in a coordinated cycle to transfer heat from the cold side to a reservoir or indoor space. The function of a heat pump in heating mode 800A is disclosed in accordance with an embodiment of the present invention. In the heating mode of the intelligent heat pump system, the pump absorbs heat from the ambient outdoor environment and rejects it to reservoir 802. The cycle begins when the DC motor drives the piston 808 upward (expansion stroke), which draws in refrigerant through the V1 inlet valve 804 from reservoir 802, creating a cold liquid and cold vapor. This refrigerant enters the piston chamber, where it expands, decreasing temperature and pressure, i.e., cold liquid and cold vapor. During the downward (compression) stroke, the piston compresses the cold vapor, raising its pressure and temperature. The piston back flow valve 818 passes the hot vapor to the hot side heat exchanger 812, where the hot side pressure and temperature are controlled by V4 electronic pressure regulator 816, which maintains proper hot side vapor pressure and temperature, ensuring efficient heat rejection, and then to the reservoir 802. The V2 outlet valve 806 opens, allowing the cold liquid to flow into the cold liquid heat exchanger 814, where it absorbs heat from the ambient outdoor environment to replenish thermal energy converted to mechanical energy during the expansion stroke. As a result of the cold side liquid thermal energy addition not meeting the requirements of reservoir 802, additional thermal energy is supplied by increasing the hot side vapor pressure and temperature through adjustment of V4 electronic pressure regulator 816. This additional thermal energy is supplied from the large amount of mechanical energy generated in the expansion stroke, which is returned, and increases the heat pump's efficiency.

[0194] The function of a heat pump in cooling mode 800B is disclosed in accordance with an embodiment of the present invention. In the cooling mode of the intelligent heat pump system, the pump extracts heat from the indoor space and rejects it to reservoir 802. The cycle begins when the DC motor drives the piston 808 upward (expansion stroke), which draws in refrigerant through the V1 inlet valve 804 from reservoir 802, creating a cold liquid and cold vapor. This refrigerant enters the piston chamber, where it expands, decreasing temperature and pressure, i.e., cold liquid and cold vapor.

[0195] During the downward (compression) stroke, the piston compresses the cold vapor, raising its pressure and temperature. The piston backflow valve 818 passes the hot vapor to the bypass valve 810 and then to the reservoir 802. The V2 outlet valve 806 opens, allowing the cold liquid to flow into the cold liquid heat exchanger 814, where it absorbs heat from the indoor space to replenish thermal energy converted to mechanical energy during the expansion stroke. The V5 bypass valve 810 is used to bypass the hot vapor heat exchangers, thereby optimizing efficiency.

[0196] The processor continuously monitors sensor data, and the firmware module adjusts valve timings and measures motor speed to maintain a stable reservoir temperature and system pressure. In this mode, the system operates in a repeating thermal cycle, using the adaptive control algorithm to shift between reservoir cooling and temperature correction cycles, ultimately aiming to maintain a steady-state thermal condition where the reservoir temperature remains within a defined target range.

[0197] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept and, therefore, such adaptations and modifications should and are intended to be comprehended within understood that the phraseology or the terminology employed herein is for description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the appended claims.

[0198] The advantages set forth above, and those made apparent from the foregoing description, are efficiently attained. Since certain changes may be made in the above construction without departing from the scope of the invention, it is intended that all matters contained in the foregoing description be interpreted as illustrative and not in a limiting sense.

[0199] It is also to be understood that the following claims are intended to cover all the generic and specific features of the invention herein described and all statements of the scope of the invention that, as a matter of language, might fall therewithin.