摘要
轮毂电机驱动是电动汽车采取的一种新型驱动方式。针对电动汽车轮毂永磁无刷直流电机的多变量、高度非线性以及强耦合的特点,将电机控制系统的转速控制器设计为模糊神经网络PID调节器,通过鸡群算法和改进BP算法分别对模糊神经网络进行优化和训练,实现模糊神经网络PID调节器的最优参数输出。系统仿真和实验分析验证表明,基于模糊神经网络PID转速调节器的电机控制系统具有很强的转速跟踪、抑制超调、抗干扰、鲁棒性等动态性能。
The wheel hub motor drive is a new type of drive for electric vehicles.In view of the multivariate,highly nonlinear and strong coupling characteristics of permanent magnet brushless DC motor in the wheel hub of electric vehicles,the speed controller of the motor con-trol system is designed as a fuzzy neural network PID regulator,and the fuzzy neural network is optimized and trained by the chicken flock algorithm and the improved BP algorithm respectively,so as to realize the optimal parameter output of the fuzzy neural network PID regula-tor.The system simulation and experimental analysis show that the motor control system based on fuzzy neural network PID speed regulator has strong dynamic performance such as speed tracking,overshoot suppression,anti-interference,and robustness.
作者
乔维德
QIAO Wei-de(Scientific Research and Development Planning Office of Wuxi Open University,Wuxi 214011,China)
出处
《电工电气》
2024年第12期15-21,共7页
Electrotechnics Electric
关键词
电动汽车
永磁无刷直流电机
模糊神经网络PID调节器
鸡群算法
改进BP算法
速度控制
electric vehicle
permanent magnet brushless DC motor
fuzzy neural network PID regulator
chicken flock algorithm
im-proved BP algorithm
speed control
