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作 者:方祥建 王建平[1] FANG Xiangjian;WANG Jianping(School of Mechanical Engineering,Anhui Polytechnic University,Wuhu 241000,China;Intelligent Chassis Business Division,China Automotive Innovation Corporation,Nanjing 211100,China)
机构地区:[1]安徽工程大学机械工程学院,安徽芜湖241000 [2]中汽创智科技有限公司智能底盘事业部,江苏南京211100
出 处:《安徽工程大学学报》2022年第2期34-42,共9页Journal of Anhui Polytechnic University
基 金:芜湖市科技计划基金资助项目(2020BB0183)。
摘 要:电动汽车的空调系统作为汽车的主要耗电模块,在气温较低或者较高的时候,耗电量大,导致整车续航能力大幅降低。为了提升续航里程,提高汽车座舱舒适性,降低电动汽车的整车能耗,本文通过对模糊比例积分微分(Proportional Integral Derivation,PID)模型预测控制的算法进行研究,在未知空调系统控制逻辑,不改变系统结构的情况下,基于模糊PID模型预测控制,建立汽车热力学模型,并分析了汽车空调系统的能耗参数。基于MATLAB仿真验证结果表明,相较于单独的模糊PID及模型预测控制,模糊PID模型预测控制能耗有明显降低,说明该控制系统在一定程度上降低了整车能耗,有利于提升电动汽车的续航里程,达到了设计标准要求。The air conditioning system of electric vehicles,as the main power consumption module of the vehicle,consumes a lot of power when the temperature is relatively low or high,resulting in a substantial decrease in the vehicle endurance.To lift driving range,improve the car cabin comfort and reduce energy consumption of the electric car vehicle,this paper established a fuzzy PID modol prediction algorithm,under unknown Air-Conditioning system control logic,without changing the system structure,based on the fuzzy PID model predictive control,car thermodynamics model to analyze the energy consumption of the heating system parameters.Based on MATLAB simulation verification,the results show that compared with the fuzzy PID and model predictive control alone,the fuzzy PID model predictive control energy consumption is significantly reduced,indicating that the control system can reduce the energy consumption of the vehicle to a certain extent and improve the driving range of electric vehicles,which meets the design standards.
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