All-condition double-area temperature calibration method and automobile air conditioner control system

Abstract

The invention discloses an all-condition double-area temperature calibration method and an automobile air conditioner control system, and a BP neural network model of the temperature at a left area and a right area where human body perception positions are can be established when a temperature sensor in a car is calibrated. The method comprises determining an input signal of a network model, collecting training data of the network model in all conditions, processing the input and the output of the network model in normalization and processing the output in reverse normalization, and initializing and training the network model using a Matlab toolset. Because the input and the output of the network model are processed in normalization and the output is processed in reverse normalization, the defect that a conventional temperature calibration method depends on a control time axis can be thoroughly overcome. On the premise that all factors influencing on a temperature sensor in a car are in consideration, the accuracy of temperature calibration and the anti-interference performance are improved, accurate feedback can be provided to an in-car temperature closed loop control system, so the stability and accuracy on temperature control can be raised by adopting the automobile air conditioner control system.

Description

technical field [0001] The present invention relates to the field of an automobile air-conditioning control system and a dual-zone temperature control method thereof, in particular to a 16-bit single-chip microcomputer using BP neural network modeling to realize the full-working-condition dual-zone temperature of an interior temperature sensor of an automobile air-conditioning control system Calibration method. Background technique [0002] The interior temperature parameter of the automobile air-conditioning control system is one of the most important parameters in the interior temperature calibration algorithm. In the actual application process, the temperature calibration of the traditional automobile air-conditioning interior temperature sensor adopts the automatic working condition calibration method, namely In the automatic mode, the air-conditioning controller collects the temperature values ​​at the sensory positions of the human body in the left and right dual areas...

AI Technical Summary

Problems solved by technology

[0003] However, the traditional temperature calibration method using difference compensation is highly dependent on the time axis of the air-conditioning control system. The temperature balance in the car is destroyed, which in turn affects the accuracy of the temperature sensor calibration in the car; moreover, the traditional temperature calibration method is based on the temperature set in the car, which cannot achieve accurate temperature scanning control, especially only applicable Because of single-zone temperature control, it cannot meet the requirements of precise dual-zone temperature control; in addition, the air-conditioning system of the traditional temperature calibration method is always in automatic mode, which is not suitable for manual mode, such as manual adjustment of internal and external circulation, wind speed In the case of isochronism, it cannot meet the feedback requirements of the closed-loop control of the temperature in the car

[0004] Therefore, the existing technology still needs to be improved and developed

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