Heater element as sensor for temperature control in transient systems
10934921 ยท 2021-03-02
Assignee
Inventors
- David P. CULBERTSON (Bristol, WI, US)
- Jeremy Ohse (St. Louis, MO, US)
- Mark D. EVERLY (St. Charles, MO, US)
- Jeremy J. QUANDT (Winona, MN, US)
- James Pradun (Lake Geneva, WI, US)
- John Rohde (Winona, MN, US)
- Mark L. G. Hoven (Winona, MN, US)
- Bret Wadewitz (Winona, MN, US)
- Sanhong ZHANG (Ballwin, MO, US)
Cpc classification
F02D41/22
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
G05D23/30
PHYSICS
F28F2200/00
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D41/1446
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2560/07
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
H05B3/141
ELECTRICITY
F01N2610/102
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2560/20
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N9/005
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2240/36
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2900/1602
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N9/002
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2900/1404
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D41/1447
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2240/16
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/2006
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2900/1411
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2900/0416
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
G01M15/05
PHYSICS
F01N3/106
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
Y02T10/12
GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
F01N3/103
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/2066
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N11/005
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2550/22
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2240/10
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2410/00
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D2041/228
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/2013
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/023
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2410/04
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N11/002
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2900/1406
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/027
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
Y02T10/40
GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
F01N2560/12
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N9/00
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N13/0097
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/0814
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N2560/06
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
H05B2203/022
ELECTRICITY
H05B2203/019
ELECTRICITY
F02D41/024
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D2041/1433
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
H05B3/20
ELECTRICITY
G01F1/86
PHYSICS
F01N3/021
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D41/222
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
International classification
F01N9/00
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D41/14
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/20
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F02D41/22
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
G01M15/05
PHYSICS
G07C5/08
PHYSICS
G05D23/24
PHYSICS
G05D23/30
PHYSICS
G01F1/86
PHYSICS
F01N3/023
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N11/00
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N3/027
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
H05B1/02
ELECTRICITY
F02D41/02
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
F01N13/00
MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
Abstract
A method of predicting the temperature of a resistive heating element in a heating system is provided. The method includes obtaining resistance characteristics of resistive heating elements and compensating for variations in the resistance characteristics over a temperature regime. The resistance characteristics of the resistive heating element include, but are not limited to, inaccuracies in resistance measurements due to strain-induced resistance variations, variations in resistance due to the rate of cooling, shifts in power output due to exposure to temperature, resistance to temperature relationships, non-monotonic resistance to temperature relationships, system measurement errors, and combinations of resistance characteristics. The method includes interpreting and calibrating resistance characteristics based on a priori measurements and in situ measurements.
Claims
1. A method of predicting temperature of a resistive heating element in a heating system, the method comprising: obtaining resistance characteristics of the resistive heating element; interpreting and calibrating the resistance characteristics of the resistive heating element based on at least one of a priori measurements and in situ measurements, wherein the a priori measurements include a resistance to temperature relationship that is interpreted and calibrated by using a model-based determination of resistive heating element temperature and resistance measurements, the model-based determination including at least one of a local dR/dT maximum and a local dR/dT minimum of the temperature and resistance measurements; and compensating for variations in the resistance characteristics of the resistive heating element over a temperature regime such that the heating system is adjusted near at least one of the local dR/dT maximum and the local dR/dT minimum.
2. The method according to claim 1, wherein the resistive heating element is a nickel chromium alloy.
3. The method according to claim 1, wherein the resistance characteristics of the resistive heating element include at least one of inaccuracies in resistance measurements due to strain-induced resistance variations, variations in resistance due to the rate of cooling, shifts in power output due to exposure to temperature, resistance to temperature relationships, non-monotonic resistance to temperature relationships, system measurement errors, and combinations thereof.
4. The method according to claim 1, wherein: the a priori measurements comprise at least one of shift in resistance due to time, shift in resistance due to temperature exposure, resistive heating element temperature, hysteresis in resistance, emissivity, transient rate of heating to applied power, specific transient rate of heating to applied power, specific emissivity, and combinations thereof; and the in situ measurements comprise at least one of fluid mass flow, heater inlet temperature, heater outlet temperature, ambient temperature, resistive heating element temperature, temperature of various masses in the proximity of the heater, resistance at local dR/dT maximums, resistance at local dR/dT minimums, room temperature resistance, resistance at service temperatures, leakage current, power applied to the heater, and combinations thereof.
5. The method according to claim 4, wherein resistance changes at local dR/dT maximums and changes in resistance at service temperatures are operable as a multi-point in situ resistance calibration.
6. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining the local dR/dT maximum as a single point in situ calibration, and the method further comprising the step of adjusting the resistance to temperature characteristic.
7. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining the local dR/dT maximum and a plurality of resistance to temperature measurements, wherein the method further comprises the step of determining a multi-point in situ resistance to temperature calibration.
8. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining at least one of the local dR/dT maximums and the local dR/dT minimums as an input for at least one of a steady state modeling of the heating system and a transient modeling of the heating system.
9. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by comparing at least one of the local dR/dT maximums and the local dR/dT minimums with a thermal model for a multi-point in situ calibration.
10. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining in situ heating system information to calibrate the resistance to temperature characteristic without at least one of local dR/dT maximum information and local dR/dT minimum information.
11. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining a slope of the resistance to temperature relationship from a power input.
12. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining shifts in an output of the heating system.
13. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining either shift or drift measurements in a material lot characteristic.
14. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining a resistance thermal model to identify changes in a resistance to temperature curve over time.
15. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining a slope of the resistance to temperature relationship and corresponding temperature of the resistive heating element.
16. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining a plurality of voltage and amperage measurements.
17. The method according to claim 1, wherein the resistance to temperature relationship is calibrated and interpreted by obtaining resistive heating element temperature measurements and at least one of a resistive heating element reliability curve and resistive heating element reliability data.
18. The method according to claim 1, wherein the resistance to temperature relationship is compared to a resistance-based temperature measurement providing a diagnostic capability.
19. The method according to claim 1, wherein a model of the heating system is calibrated and interpreted by obtaining at least one of the local dR/dT maximums and the local dR/dt minimums; and wherein the model of the heating system comprises transient models of the heating system and in situ models of the heating system.
20. The method according to claim 1, wherein the resistive heating element temperature is adjusted by obtaining a resistive heating element average temperature measurement to reduce a measurement response delay due to a thermal junction impedance between the resistive heating element and a measuring sensor, and adjusting a control response of a thermal control loop.
21. The method according to claim 1, wherein a convective heat transfer coefficient (h.sub.c) is determined by parameters determined from characteristics of the heating system.
Description
DRAWINGS
(1) In order that the disclosure may be well understood, there will now be described various forms thereof, given by way of example, reference being made to the accompanying drawings, in which:
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DETAILED DESCRIPTION
(10) The following description is merely exemplary in nature and is in no way intended to limit the present disclosure, its application, or uses. It should also be understood that steps within a method may be executed in different order without altering the principles of the present disclosure.
(11) In the present disclosure, a priori (prior known) and in situ (in use) information is used to calibrate the resistive elements of a heater such that the resistive elements can be used as temperature sensors as well as heating elements. In one form, the system combines two-wire control with model-based control to improve heater life and reduce resistive element thermal variations.
(12) Two-wire heaters generally employ a material for the resistive heating element with sufficient TCR (temperature coefficient of resistance) characteristics such that the resistive heating element can function as both a heater and a temperature sensor. Examples of such two-wire heaters are disclosed in U.S. Pat. Nos. 5,280,422, 5,521,850, and 7,196,295, which are commonly assigned with the present application and the contents of which are incorporated herein by reference in their entirety. Appropriate two-wire heater materials may include noble metals, metal alloys of platinum, copper, nickel, chromium, nickel-iron alloys, copper, platinum, nickel, nickel-chromium alloys, nickel-silicone, semiconductor materials such as silicon, germanium, gallium-arsenide, and derivatives thereof. These materials are merely exemplary and should not be construed as limiting the scope of the present disclosure.
(13) Resistance characteristics of a given resistive heating element have inaccuracies due to strain-induced resistance variations, variations in resistance due to the rate of cooling, shifts in output from exposure to temperature, non-monotonic resistance to temperature relationships, system measurement errors, and among others.
(14) Referring to
(15) In one form, the present disclosure provides for a system that interprets and calibrates the relationship of resistance to temperature based on a priori and in situ information. Table 1 below provides examples of various types of a priori and in situ information that may be employed.
(16) TABLE-US-00001 TABLE 1 A priori In situ General Unique System Product Characteristic Characteristic Characteristic Characteristic Typical drift/shift Initial resistance- Fluid mass flow Resistance at in resistance due to temperature local time & temperature characteristic maximum exposure Typical hysteresis Initial local Heater inlet Resistance at in resistance- maximum temperature local temperature characteristic minimum characteristic Typical emissivity Initial local Heater outlet Room characteristics minimum temperature temperature characteristic resistance Typical transient Initial dynamic Ambient Resistance rate of heating to power to heater Temperature at other applied power temperature temperatures characteristic characteristics Heater lot drift/shift Temperature of Leakage characteristic various masses current in the proximity of the heater Specific transient Power rate of heating to applied applied power to heater characteristic Specific emissivity characteristic
(17) For example, in the a priori category, general characteristics are behaviors that are exhibited by heating systems while unique characteristics apply to individual components or groups of components. For the in situ category, system characteristics apply to information that is available outside of the heating system and product characteristics apply to information directly related to the heating system.
(18) Referring again to
(19)
(20) Therefore, a variety of approaches can be used to interpret and calibrate the R-T characteristic, including but not limited to:
(21) 1. The local maximum could be used as a single point in situ calibration to adjust the R-T characteristic based on the R value at that point;
(22) 2. The local maximum plus additional R-T point(s) could be used as a multi-point in situ calibration. Additional points could be R-T at room temperature or R at any other known temperature(s).
(23) 3. By identifying the local maximum or minimum while the resistive heating element is heating or cooling, it enables a heating system to know which portion of the non-monotonic R-T characteristic applies at a particular time (in other words, if an R value corresponds to multiple temperatures, it can be used to determine which one applies);
(24) 4. The local maximum or minimum could be used as an input for steady state or transient modeling of the heating system. For a model that is estimating the temperature of the heater, the ability to know the R value and/or the temperature that is indicated by the local maximum or minimum would calibrate the model;
(25) 5. The local maximum or minimum could be combined with thermal modeling to achieve a multi-point in situ calibration. For instance, based on a priori (either general or unique) transient rate of heating characteristics, along with in situ mass flow and temperature information, a second R-T point could be inferred based on the model and a time period. When combined with local maximum or minimum R-T information, this would provide a multi-point calibration;
(26) 6. The model based approach, using system in situ information such as mass flow, heater inlet and/or temperature(s) and power applied to the heater could be used to calibrate the R-T characteristic without local maximum or minimum information. In addition, ambient temperature information and/or temperature information of regions surrounding the heating system could be used to improve the calibration;
(27) 7. Another in-situ measurement that could be used for improved calibration includes measuring the slope of the resistance to temperature relationship when exposed to a known power input. Information about the mass flow rate and inlet temperature could improve this measurement;
(28) 8. Since the resistance of the heater conductor does not change significantly with temperatures that are near the local maximum or minimum, virtual sensing and model-based determination of resistive heating element temperature could be used in combination with physical resistance measurements to provide better control near the local maximum and minimum;
(29) 9. Any drifts/shifts in output that are able to be characterized based on general or material lot characteristics can be used to improve measurement by updating the R-T calibration;
(30) 10. When combined with resistance heating element or heater sheath thermal models (as described above), methods could be employed to identify changes in the R-T curve over time, providing information for the characteristic to be updated to compensate for shifts and enable improved temperature control;
(31) 11. Identification of the slope and corresponding temperature of the resistive heating element could enable different control schemes. For example, on-off control may be employed in the positive slope portion of
(32) 12. Due to the challenges of making precise amperage measurements in some AC powered systems, the measurement accuracy may not support a two point in situ correction.
(33) 13. The use of alternative means to determine the resistive heating element temperature (such as virtual sensing and model-based methods as set forth above) can be used to compare to a resistance-based temperature measurement and provide both diagnostic capability and improve the accuracy of the resistance-based measurement;
(34) 14. The resistive heating element temperature measurement will allow the use of different heater control schemes. Based on resistive heating element reliability curves and data, the control can switch between increasing heater life operation and increasing heater performance;
(35) 15. Directly controlling the resistive heating element temperature: a. The use of the actual resistive heating element average temperature measurement can reduce measurement response delays from thermal junction impedances between the resistive heating element and the measuring sensor. This will allow for the faster control response of a thermal control loop; b. The actual resistive heating element temperature measurement can be used to enable the resistive heating element to maintain a constant temperature with a reduced amount of temperature deviations, which will promote longer heater life; c. The resistive heating element temperature measurement will allow heater temperatures to be controlled to a higher level, regardless of the control scheme, so as to allow for a faster thermal response. Because the resistive heating element temperature is known, the design margins added to compensate for manufacturing and material variabilities can be reduced, allowing the resistive heating element to be operated at higher temperatures. Higher operating temperatures will result in faster thermal response; d. The resistive heating element temperature measurement can be used to reduce mechanical failures of externally mounted sensors in high vibration applications;
(36) Accordingly, by calculating the temperature of the resistive heating element and accounting for the R-T characteristics as set forth above, safety margins can be reduced, the heater can operate at higher temperatures, and faster response times for the heater such that heat may be transferred more rapidly to a target, such as by way of example, the exhaust gas so that a catalyst can rise to its target temperature faster.
(37) In one form of the present disclosure, control algorithms are employed that use differential equations for change in temperature over time (dT/dt). The control system is operable to measure voltage and current and then calculate real time power and resistance for each element above. In one form, a J1939 communications bus is used to provide exhaust mass flow from an engine controller and heater inlet temperature (T.sub.in) from a sensor to a power switch, for example, a DC power switch.
(38) In one form, a convective heat transfer coefficient (h.sub.c) can be calculated based on heater geometry, mass flow ({dot over (m)}), and T.sub.in, as shown below for one example heater geometry and at least the following or similar equations:
(39)
where:
Ac=Heater cross-sectional area;
C=A first constant based on Reynolds number (Re) and Table 2 shown below;
C.sub.2=Offset based on number of heater elements, when evaluating element 1, see Table 2 below, use N.sub.L=1; when evaluating 6 elements, N.sub.L starts at 0.7 and increases to 0.92 as each element is analyzed;
D=Heater element diameter;
h.sub.c=Convective heat transfer coefficient;
k=Thermal conductivity of air;
m=A second constant based on Reynolds number (Re) and Table 2 shown below;
{dot over (m)}=Mass flow;
{dot over (m)}.sub.exh=Mass flow rate of the exhaust;
{dot over (m)}.sub.in=Mass flow rate of the inlet;
{dot over (m)}.sub.fuel=Mass flow rate of the fuel;
N.sub.L=Number of elements;
Pr=Prandtl number of air taken at gas temperature;
Pr.sub.s=Prandtl number of air taken at sheath temperature;
=Density;
Re.sub.D=Reynolds number for a given diameter and velocity;
S.sub.T=Transverse distance between elements;
T.sub.out=Heater outlet temperature;
T.sub.sheath=Sheath temperature;
=Viscosity of air;
V.sub.in=Velocity of the fluid flow at the inlet;
V.sub.max=Velocity of the fluid flow at maximum; and
wsm=Watts per square meter.
(40) TABLE-US-00002 TABLE 2 Re.sub.D, max C (C.sub.1) m 10-100 0.80 0.40 100-1000 (Single cylinder approx.) (Single cylinder approx.) 1000-200k 0.27 0.63 Single Cylinder 40-4000 0.683 0.466 N.sub.L 1 2 3 4 5 6 C.sub.2 0.70 0.80 0.86 0.89 0.90 0.92
(41) In another form, the thermal conductivity (k), or the thermal diffusivity (), of an insulator (example material may include MgO) is calibrated to a two-wire resistance measurement. As shown in
(42) In summary, the disclosed virtual sensing according to the teachings of the present disclosure reduces the number of physical sensors based on a model-based interpretation and processing of system parameters. In some cases, a physical sensor may still be used in the thermal system, however, the total number that may be desired is reduced by using virtual sensing. Also, the virtual sensing improves the responsiveness of feedback signals or parameters used for control. More specifically, a model of the system is used to predict the system response based on available signals. Further, the accuracy of a temperature is improved in applications where the physical temperature is difficult to obtain.
(43) Referring to
(44) As used herein, the term model should be construed to mean an equation or set of equations, a tabulation of values representing the value of a parameter at various operating conditions, an algorithm, a computer program or a set of computer instructions, a signal conditioning device or any other device that modifies the controlled variable (e.g., power to the heater) based on predicted/projected/future conditions, wherein the prediction/projection is based on a combination of a priori and in-situ measurements.
(45) Accordingly, a variety of different forms of heaters, sensors, control systems, and related devices and methods have been disclosed herein for use in fluid flow systems. Many of the different forms can be combined with each other and may also include additional features specific to the data, equations, and configurations as set forth herein. Such variations should be construed as falling within the scope of the present disclosure.
(46) The description of the disclosure is merely exemplary in nature and, thus, variations that do not depart from the substance of the disclosure are intended to be within the scope of the disclosure. Such variations are not to be regarded as a departure from the spirit and scope of the disclosure.