摘要
为了进一步提高双电机四驱电动汽车防抱死控制的响应速度和精度,在电液复合变参数PID防抱死系统的基础上,采用径向基函数神经网络系统对电动汽车电液复合制动系统进行在线辨识,利用车轮滑移率对于电机制动转矩变化的灵敏度信息对PID的控制参数进行滚动优化调整,实现自适应复合防抱死控制。运用离线仿真和快速控制原型在环实时实验对控制算法和在线实时控制效果进行了验证,结果表明:改进的控制算法提高了系统的控制精度和响应速度,而且满足控制系统的实时性要求。
On the basis of electro-hydraulic varying parameters PID control,to further improve the response rate and accuracy of anti-lock breaking system of a dual-motor four-wheel drive electric vehicle,the neural network system based on radial basis function is introduced to realize online identification of electro-hydraulic braking system.The sensitivity of the wheel slip ratio to motor braking torque is used to achieve scroll optimal adjustment of parameters of PID control,and to increase the response rate and accuracy.The off-line simulation and hardware in loop real time simulation are carried out to test the control algorithm.Results show that the improve control algorithm can increase the accuracy and regulating rate of the system,and meet the real time requirements of the control system.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2016年第5期1405-1413,共9页
Journal of Jilin University:Engineering and Technology Edition
基金
广东省科技计划项目(2014B010106002
2014B010125001)
关键词
车辆工程
径向基函数
神经网络
防抱死系统
电动汽车
vehicle engineering
radial basis function
neural network
anti-lock braking system（ABS）
electric vehicle
