电动汽车用永磁同步电机自适应PI控制仿真分析

Simulation Analysis on Adaptive PI Control of Permanent Magnet Synchronous Motors for Electric Vehicles

为提高永磁同步电机矢量控制系统的响应速度,提高系统鲁棒性,文章使用一种自适应比例积分(PI)矢量控制策略对传统矢量控制进行改进。文章根据一款混合动力电动汽车用永磁同步电机的相关参数建立了电机模型和传统矢量控制仿真模型;设计了基于BP神经网络的自适应PI控制器,对传统矢量控制模型进行了改进;最后对两种控制系统转矩突变的工况进行了仿真对比和分析。结果表明:与传统矢量控制策略相比,设计的基于BP神经网络的自适应PI矢量控制策略能够有效提高系统的响应速度,增强控制系统的鲁棒性,满足了车用电机的使用要求。

In order to improve the response speed of the permanent magnet synchronous motor vector control system and improve the robustness of the system,this paper uses an adaptive proportional integral(PI)vector control strategy to improve the traditional vector control strategy.According to the relevant parameters of a permanent magnet synchronous motor for a hybrid electric vehicle,the paper establishes a motor model and a traditional vector control simulation model;designs an adaptive PI controller based on BP neural network,improves traditional vector control simulation model.Finally,the simulation comparison and analysis of the two control system are carried out under torque sudden change conditions.The results show that:compared with the traditional vector control strategy,the designed adaptive PI vector control strategy based on BP neural network can effectively improve the response speed of the system,enhance the robustness of the control system,and meet the requirements of vehicle motors.