论文部分内容阅读
本文提出了一种汽车空调车内温度计算方法,采用BP神经网络建立左右双区乘员呼吸点位置的温度值预测模型,用于校准车内温度传感器。本方法在考虑车内温度传感器的各种影响因素的基础上,提高了温度校准的准确性和抗干扰能力,为车内温度控制系统提供了准确地反馈,有效提高汽车空调控制系统对温度控制的稳定性和准确性。
In this paper, a temperature calculation method for car air-conditioners is put forward. The BP neural network is used to establish the temperature prediction model for the position of air-breathing points in the double-left and right-hand passengers. It is used to calibrate the temperature sensor inside the car. Based on the various influencing factors of the temperature sensor in the vehicle, the method improves the accuracy of the temperature calibration and the anti-interference ability, provides accurate feedback for the temperature control system in the vehicle and effectively improves the temperature control of the vehicle air-conditioning control system The stability and accuracy.