电动车驱动防滑控制策略研究

Study on the Strategy of Acceleration Slip Regulation Control for Electric Vehicle

针对驱动轮在附着条件恶劣的路面行驶时滑转问题,对后轮独立驱动电动汽车进行驱动防滑控制研究。提出了基于自适应模糊神经网络控制的驱动防滑控制策略,提高汽车在极限工况下车辆的稳定性。根据车辆运动状态,路面识别算法对当前路面和最优滑转率进行辨识。采用自适应模糊神经控制器将驱动轮滑转率实时控制在最优滑转率附近。仿真结果表明:模糊路面识别算法能够较好识别路面附着系数和其最优滑转率;基于自适应模糊神经控制的驱动防滑具有良好的控制效果,提高了恶劣路面行驶时车辆的稳定性与动力性。

Aiming at the problem of the slip on driving wheel for EV（ Electric Vehicle）under the condition of low adhesion road,the ASR（ Acceleration Slip Regulation）technology was researched for the RWID（Rear-Wheel Independent Drive）EV. A ASR control method based on fuzzy neural control was proposed to improve vehicle stability under ultimate driving condition. Controlled by the adaptive fuzzy neural controller,the drive wheels will work in the vicinity of the optimal slip ratio.The results indicate that the fuzzy road identification can identify the road adhesion coefficient and the optimal slip ratio accurately,and the ASR control method based on the fuzzy neural control has a good control effect,which improves vehicle stability and power under extreme condition obviously.