摘要
对双轮毂电机驱动型电动汽车的驱动防滑控制进行了研究。针对目标车型,分析了双后轮轮毂电机传动方式下的电机转矩输出特性。结合T-S(Takagi-Sugeno)型模糊路面识别系统,开发了一种基于径向基函数的单神经元自适应控制算法,实现了比例积分微分参数在线自适应调控,并采用遗传算法对参数进行了优化。研究结果表明,所设计的驱动防滑控制策略能够有效辨识路况,准确预估路面最优滑转率,将车辆的滑转率保持在目标值附近。
The anti-skid control of the double-wheel motor-driven electric vehicle was studied. Aiming at the target vehicle, the output characteristics of the motor torque under the double rear wheel motor drive mode were analyzed. Based on the T-S fuzzy pavement recognition system, a single neuron adaptive control algorithm based on RBF was developed to realize the on-line adaptive control of PID parameters and the parameters were optimized by genetic algorithm. The findings show that the designed anti-skid control strategy can effectively identify the road condition, accurately estimate the optimal skid rate of the pavement and keep the skid rate of the vehicle near the target value.
出处
《机械制造》
2017年第11期29-32,共4页
Machinery
基金
浙江省自然科学基金资助项目(编号:LY16E050003)
浙江省教育厅一般科研项目(编号:Y201635219)
关键词
电动汽车
驱动
防滑
Electric Vehicle Driving Anti-skid
