电动空调匹配及模糊控制研究

Matching and fuzzy control for electric air conditioner

以保证整车室内温度舒适性和提高整车续驶里程为目标,基于整车热负荷及制冷剂循环过程,提出了电动空调匹配流程。针对电动空调能耗高的问题,基于气候适应性模型,提出了以外界温度与舒适温度差值、动力电池荷电状态(SOC)作为输入变量的模糊控制策略,搭建了电动空调仿真模型,通过单次中国典型城市工况和连续35次中国典型城市工况对电动空调的有效性和经济性进行验证。结果表明:所提出控制方案与现有方案相比,SOC大于0.3时,制冷效果相当;行驶100 km可节省电量6.9 kW·h,节能效果显著;随着电池SOC的降低,可逐步限制空调功率,直至关闭空调,从而在尽量保证整车室内温度舒适性的前提下,有效延长整车行驶里程。

In order to improve the driving range and indoor temperature comfort of vehicle,based on the vehicle heat load and refrigerant cycle process,the matching process for electric air conditioner is proposed.For the problem of energy consumption for traditional electric air conditioner,the fuzzy control with two input variables is adopted based on climate adaptability model.One input variable is the difference between external temperature and comfortable temperature.The other is the state of charge(SOC)of battery.The model for electric air conditioner is built based on Matlab/Simulink.The effectiveness and economy for electric air conditioner are verified through typical Chinese urban condition.The simulation results show that the electric air conditioner can meet the needs of vehicle.Compared with the existing control scheme,the cooling effect of the proposed control scheme is equivalent when SOC is greater than 0.3.The proposed control scheme can save 6.9 kW·h/100 km,with remarkable energy saving effect.With the decrease of SOC,the power of air conditioner can be gradually limited until the air conditioner is turned off,so as to effectively extend the driving range of vehicle on the premise of ensuring the indoor temperature comfort as much as possible.