以人体热舒适性为目标，综合考虑汽车空调控制系统的复杂性，对某SUV6双蒸发器汽车空调系统的控制策略进行优化。在联合仿真的基础上，建立了基于模糊PID调节的汽车空调闭环控制系统，引入粒子群优化算法(PSO)优化PID控制器的参数，对风机风速和压缩机开度进行调控。对比PID、模糊PID和PSO模糊PID调节，分析得出：PSO模糊PID控制调节没有超调的缺陷，可以使乘客舱温度更快、更平稳地趋向目标舒适温度，有效降低汽车能耗，满足节能减耗要求。

Aiming at the thermal comfort of human body and considering the complexity of air conditioner control system, the control strategy of double-evaporator air conditioning system of SUV6 is optimized. On the basis of joint simulation, the closed-loop control system of automobile air conditioner based on fuzzy-PID control is established. Particle swarm optimization (PSO) is introduced to optimize the parameters of PID controller and regulate the fan speed and compressor opening ratio. Compared with the PID control and the fuzzy-PID control, it is found that the fuzzy-PID control based on PSO can overcome the defect of overshoot, make the temperature in the passenger compartment approach to the target faster and more stably, reduce the temperature control error, effectively reduce the energy consumption of the car, and meet the requirements of energy saving and consumption reduction.

国家自然科学基金重点项目(51736007);上海理工大学科技发展项目(2018KJFZ179)