The invention concerns a control device (1) for a heating and/or ventilation and/or air conditioning installation of a motor vehicle, the installation comprising an air treatment unit (9) comprising air outlets intended to open into a zone (ZG, ZD) of the passenger compartment of the vehicle, including at least first and second air outlets, and at least first (21) and second (23, 25) members for mixing the air flow. According to the invention, the device (1) comprises a user interface (5) comprising at least first (51) and second (53) control members, and a control circuit (7) for receiving, from each control member (51, 53), an input signal with its own temperature setpoint, and for delivering separate control signals for controlling the first and second mixing members (21, 23, 25).

An appliance includes a temperature control system, a light source, and a spectrometer. The spectrometer works in conjunction with the light source to obtain a measured value of a foodstuff. The measured value is at least one of an absorbance value, a transmittance value, and a reflectance value. The measured value from the foodstuff is compared to a reference value for the foodstuff.

Provided is a thermal displacement correction method using a machine learning method but making it possible to, on a user side, calculate a thermal displacement amount appropriate to a machine tool of the user and correct the thermal displacement. In a machine tool on a target user side, a thermal displacement amount between workpiece and tool corresponding to a temperature at a preset measurement point is calculated based on a parameter defining a relation between the temperature and the thermal displacement amount, and a positioning position for workpiece and tool is corrected in accordance with the calculated thermal displacement amount. On a manufacturer side, operational status information of the machine tool on the target user side is obtained, an operational status identical to the obtained operational status on the target user side is reproduced with a machine tool of a same type as the machine tool on the target user side based on the obtained operational status information, a temperature at a measurement point identical to the measurement point on the machine tool on the target user side and a thermal displacement amount between workpiece and tool are measured during reproduction, and the parameter is calculated by machine learning based on the measured temperature and thermal displacement amount. The parameter in the machine tool on the target user side is updated with the calculated parameter.

The invention relates to a thermal-management system for a vehicle comprising: at least one calories storage and/or frigories storage (S1, S2), at least one element of the vehicle to be heated or cooled, at least one source of calories or frigories, detection means adapted to detect whether calories or frigories are available at one of the said sources, control means able to distribute the calories or frigories available at the sources to the elements to be heated or cooled, according to transient and nominal needs. characterized in that it comprises prediction means capable of making at least one prediction aimed at determining: whether calories or frigories will be available at a later date from any of the said sources and/or, whether a need for calories or frigories will exist at a later date at one of the said elements to be heated or cooled.

The present invention relates to a temperature control device for growing a single crystal ingot capable of accurately measuring a temperature of a silicon melt and quickly controlling to a target temperature during an ingot growing process, and a temperature control method applied thereto. The present invention provides a temperature control device for growing a single crystal ingot, which controls an operation of a heater for heating a crucible configured to accommodate a silicon melt, the device including: an input unit configured to measure a temperature of the silicon melt accommodated in the crucible and process the measured temperature of the silicon melt; a control unit configured to perform a proportional-integral-derivative (PID) calculation of one of the measured temperature T1 and the processing temperature T2 of the input unit and a set target temperature T0 and calculate as an output of the heater; and an output unit configured to input the output of the heater calculated in the control unit to the heater.

A substrate processing system is provided and includes a substrate support, a memory, and calibration, operating parameter, and solving modules. The substrate support supports a substrate and includes temperature control elements. The memory stores, for the temperature control elements, temperature calibration values and sensitivity calibration values. The calibration module, during calibration of the temperature control elements, performs a first calibration process to determine the temperature calibration values or a second calibration process to determine the sensitivity calibration values. The sensitivity calibration values relate at least one of trim amounts or deposition amounts to temperature changes. The operating parameter module determines operating parameters for the temperature control elements based on the temperature and sensitivity calibration values. The solving module, subsequent to the calibration of the temperature control elements, controls operation of the temperature control elements during at least one of a trim or deposition step based on the operating parameters.

A system and method for configuring a water heater. The method includes capturing, with a mobile device a scannable feature of a rating plate, establishing a network connection between the mobile device and a server, transmitting information captured from the scannable feature by the mobile device to the server over the network connection, receiving from the server to the mobile device a plurality of water heater configurations in response to the information, receiving, with the mobile device, an input indicative of a configuration selection selected from the plurality of water heater configurations, and transmitting configuration information from the mobile device to the water heater to configure the water heater based on the configuration selection.

A method of detecting anomalies of a fan within an appliance includes receiving, at a service computer and/or remote server, data indicative of usage of the fan, analyzing the data indicative of usage of the fan with a machine learning model on the service computer and/or remote server, and flagging the fan for replacement when the machine learning model detects an anomaly in the data indicative of usage of the fan.

A control system operable to train a control tuner to generate temperature setpoint tracking improvements for a thermal processing system is provided. In one example implementation, temperature setpoint tracking improvements are achieved by generating system controller parameter adjustments based on a difference between a simulated workpiece temperature estimate and an actual workpiece temperature estimate. For example, a system model can generate a simulated workpiece temperature estimate simulating an actual workpiece temperature estimate, and based on the difference between the simulated and actual workpiece temperature estimates, generate clone controller parameter adjustments. The clone controller parameter adjustments can be used to generate system controller parameter adjustments, which can improve temperature setpoint tracking for the thermal processing system.

A method and system for control of BTM of electric drive bulldozers based on deep learning includes: obtaining a micro-load segment at the current moment in a load spectrum and predicting a micro-load segment at the next moment using a Markov chain model; carrying out a weighting calculation of the segment using the segment at the current moment and a corresponding weight thereof with the predicted segment and a corresponding weight thereof, and then calculating motor speed, motor torque, and a state of charge (SOC) of battery under the segment after being weighted; and taking a real-time battery outlet water temperature, occupant cabin temperature, occupant cabin target temperature and ambient temperature as well as the motor speed, motor torque and SOC, so as to obtain a control strategy of the electric compressor speed, and further obtain a method for control of BTM of the electric drive bulldozer.