无迹卡尔曼滤波观测下轮毂电机电动车横摆稳定性控制
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河南科技大学车辆与交通工程学院

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U469.72+2

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国家自然科学基金资助项目(51805149);河南省高等学校青年骨干教师培养计划项目(2017GGJS063)


Yaw Stability Control of Hub Motor Electric Vehicle Based on Unscented Kalman Filter
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School of Vehicle and Traffic Engineering,Henan University of Science and Technology

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    摘要:

    为了提高轮毂电机驱动电动汽车在不同路面附着系数下的横摆稳定性,设计了轮毂电机电动车稳定性控制系统。为提高控制系统的控制效果,搭建了无迹卡尔曼滤波观测器,用来实时观测汽车的行驶状态以及附着系数。并提出基于无迹卡尔曼滤波状态观测的制动力矩分配控制策略。控制策略采用分层控制结构,上层采用模糊神经网络控制,计算汽车稳定行驶所需期望横摆力矩;下层根据观测到的附着系数,提出单轮/单侧差动制动控制策略。仿真结果表明,在高、低附着系数情况下,横摆稳定性控制策略能够使汽车横摆角速度较好的跟随理想值,将质心侧偏角偏差分别控制在0.4°和0.3°以内,改善了轮毂电机电动车的稳定性以及安全性。

    Abstract:

    In order to improve the yaw stability of hub motor-driven electric vehicle under different road adhesion coefficient, the stability control system of hub motor-driven electric vehicle was designed. In order to improve the control effect of the control system, the unscented Kalman filter observer is built to observe the driving state and adhesion coefficient of the vehicle in real time. The control strategy of braking torque distribution based on Unscented Kalman filter state observation is proposed. The control strategy adopts hierarchical control structure, and the upper layer adopts fuzzy neural network control to calculate the desired yaw moment for stable driving; According to the observed adhesion coefficient, a single wheel / single side differential braking control strategy is proposed. The simulation results show that the yaw stability control strategy can make the vehicle"s yaw rate follow the ideal value better under the condition of high and low adhesion coefficient, and the sideslip angle deviation of the center of mass is controlled at 0.4° And 0.3°, In this way, the stability and safety of hub motor electric vehicle are improved.

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孟祥明,周志刚,杨文豪. 无迹卡尔曼滤波观测下轮毂电机电动车横摆稳定性控制[J]. 科学技术与工程, , ():

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  • 收稿日期:2021-08-18
  • 最后修改日期:2021-10-25
  • 录用日期:2021-11-01
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