基于BP神经网络的汽车车内温度计算方法

摘要

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。%A method to calculate vehicle in-car temperature was proposed and the prediction model for the breath point temperature of the passenger in left/right zones was developed based on BP neural network, which is used to correct the in-car temperature sensor. The accuracy and the antijamming capability are improved by taking multi influence factors into consideration;the accurate temperature feedback for in-car temperature controlling system is provided, and the stability and accuracy of the temperature control for the vehicle air conditioner controller system are improved effectively.