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.
出处
《制冷技术》
2014年第6期65-67,共3页
Chinese Journal of Refrigeration Technology
关键词
BP神经网络
车内温度计算
汽车空调
BP neural network
Vehicle in-car temperature calculation
Automobile air conditioning