基于道路自动识别的混合动力牵引控制系统自适应模糊控制器

Jianlong Zhang, Deling Chen, Chengliang Yin
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引用次数: 6

摘要

在正常情况下,前轮跟随驾驶员的控制轨迹,后轮跟随车辆的方向。如果牵引力大于摩擦力,车辆将旋转并失去驾驶员的控制轨迹。因此,车辆应保持适当的轮胎滑移率,并遵循驾驶员的控制轨迹。本文介绍了一种用于混合动力汽车牵引控制系统的模糊控制器,该控制器通过在电机转矩中有针对性的短暂制动脉冲来防止驱动轮在起飞和加速过程中旋转。任务是利用模糊监控产生混合动力汽车电机的电动制动转矩。电动制动扭矩作为参考输入再生制动扭矩,用于低层控制模块。当这些低电平电机控制器跟踪其参考输入时,可以减小所需的转差率。通过紧急变道和轮胎滑移率变化仿真,验证了该控制方法的有效性。模糊控制器的效率和易于实现的特点表明,模糊逻辑是一种理想的混合动力汽车牵引控制框架。
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Adaptive Fuzzy Controller for Hybrid Traction Control System based on Automatic Road Identification
In the normal condition, the front wheels follow the control trace of the driver and rear wheels follow the direction of the vehicle. The vehicle will spin and lose the control trace of the driver if the traction force is greater than the friction force. Therefore, a vehicle should maintain an adequate slip ratio of the tires and follow the control trace of the driver. This paper describes a fuzzy controller for hybrid traction control system in hybrid electric vehicles (HEVs) that prevents the spinning of the drive wheels during take-off and acceleration through targeted, brief brake impulses in motor torque. The task is to have the fuzzy supervisory controller generate the electric brake torque, for motor of a HEV. The electric brake torque is treated as reference input regenerative braking torque, for lower level control modules. When these lower level motor controller tracks its reference input, the desired slip ratio, can be reduced. Emergency lane change and tire slip ratio change simulations are performed to show the effectiveness of the control. The efficiency and easy implementation of the fuzzy controller lead to the conclusion that fuzzy logic is an adequate and promising framework for hybrid traction control system in hybrid electric vehicles.
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