【摘要】 电动汽车运行工况复杂多变,传统PID控制方法无法根据实际工况进行参数调整,已无法满足电机驱动系统对快响应和强鲁棒性的要求。设计了一种将BP神经网络与传统PID控制方法相结合的永磁同步电机(PMSM)转速控制器,将设计好的BP神经网络PID控制器应用到控制系统转速闭环控制中,实现了PID参数的自整定。在MATLAB平台下进行仿真验证,结果表明,基于BP神经网络PID自整定的电机转速控制器具有响应速度快、超调量小、鲁棒性强等优点。更多还原

【Abstract】 The operating conditions of electric vehicles are complex and changeable. Because the traditional PID control method cannot adjust parameters according to the actual operating conditions,and unable to meet the requirements of the motor drive system for quick response and strong robustness. This paper designs a permanent magnet synchronous motor(PMSM)speed controller that combines BP neural network with traditional PID control method. The designed PID controller-based on BP neural network is applied to the speed loop control of the control system to realize self-tuning of PID’s parameters. The simulation verification is carried out on the MATLAB platform,and the results show that the motor speed controller based on BP neural network PID self-tuning has the advantages of quick response speed,small overshoot and strong robustness,etc.更多还原