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Variable Universe Fuzzy Control for Direct Yaw Moment of Distributed Drive Electric Vehicle

机译:可变宇宙模糊控制分布式驱动电动汽车直接横摆力矩

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A direct yaw moment control (DYC) system based on variable universe fuzzy logic is proposed to improve the stability of distributed drive electric vehicle in this paper. The upper layer of controller is a two-stage variable universe fuzzy controller, and the deviation between actual value and reference of yaw rate and side slip angle is used to calculate the required yaw moment. The lower layer of the controller adopts the redistribution pseudo inverse (RPI) algorithm, which takes the tire utilization rate as the optimization target and the maximum driving torque of the motor as the constraint target, and effectively distributes the required yaw moment to each wheel. The proposed control system is simulated and verified under J-turn and single shift line condition, and the control effect is reflected by comparison control in the uncontrolled, fuzzy PI control and variable universe fuzzy control. The simulation results show that it can make the vehicle track the reference better and enhance vehicle's handing and stability, and that the control algorithm is effective and feasible.
机译:提出了一种基于可变宇宙模糊逻辑的直接横摆力量控制(DYC)系统,以提高本文分布式驱动电动车辆的稳定性。控制器的上层是两级变量宇宙模糊控制器,并且使用横摆率和侧滑角的实际值和参考之间的偏差来计算所需的偏航力矩。控制器的下层采用重新分配伪逆(RPI)算法,其将轮胎利用率作为优化目标和电动机的最大驱动扭矩作为约束目标,并且有效地将所需的偏航力矩分配给每个轮子。在j转弯和单个换档线条件下模拟和验证所提出的控制系统,并且通过在不受控制的模糊PI控制和可变宇宙模糊控制中的比较控制来反映控制效果。仿真结果表明,它可以使车辆追踪参考更好,提高车辆的递送和稳定性,并且控制算法是有效和可行的。

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