摘要
电动车驱动系统冷却系统具有非线性、传热迟滞和时变性等特点,电机控制器功耗受工作温度影响较大,传统的冷却辅机控制策略无法满足最低功耗需求。针对此问题,利用STAR-CCM+和Amesim仿真软件建立冷却系统多维耦合仿真模型,研究电机控制器冷却系统最优门限值,并联合Matlab/Simulink仿真平台对比多挡、PID和自适应模糊PID3种控制方法的系统功耗。结果表明自适应模糊PID控制能够提升冷却系统的动态性能,降低整车能耗。
The cooling system of electric vehicle drive system has the characteristics of non-linearity, heat transfer hysteresis, and time variability. The power consumption of motor controller is greatly affected by operating temperature, and the traditional cooling auxiliary control strategy cannot meet the minimum power consumption requirement. To solve this problem, STAR CCM+ and Amesim simulation software were used to establish a multidimensional coupled simulation model of cooling system, and the optimal threshold value of motor controller cooling system is studied. The overall power consumption of three control methods including multi-speed, PID and adaptive fuzzy PID was compared with Matlab/Simulink simulation platform. The results show that the adaptive fuzzy PID control can improve the dynamic performance of cooling system and reduce the energy consumption of the vehicle.
作者
张楠
桂经良
马明霞
李加军
范文杰
ZHANG Nan;GUI Jing-liang;MA Ming-xia;Li Jia-jun;FAN Wen-jie(New Energy R&D Center,Weichai Power Co.,Ltd.,Weifang 261000,China)
出处
《汽车电器》
2023年第3期8-11,共4页
Auto Electric Parts
关键词
冷却系统
多维耦合仿真
自适应模糊PID控制
coolant system
multi-dimensional coupling simulation
adaptive fuzzy PID control
