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Chapter 57 Road Friction Coefficient Estimation by Using Lateral Dynamics Based on In-Wheel Motor Driven Electric Vehicle

机译:第57章基于轮毂电机驱动电动汽车横向动力学的道路摩擦系数估算

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By adopting a measurement noise adaptive Kalman filter and using the accurate information of driving torque provided by in-wheel motor driven electric vehicles, the tire longitudinal forces are extracted. Meanwhile, this paper puts forward a method to modify the original Dugoff tire model to expand the tire force working range as well as improve the precision. Then, the joint estimation of road friction and vehicle sideslip angle is carried out based on a reduced-order extended Kalman filter with longitudinal forces as inputs. Simulation results show that the algorithm can accurately estimate road friction coefficient when vehicle is under lateral dynamics.
机译:通过采用测量噪声自适应卡尔曼滤波器,并利用轮毂电机驱动的电动汽车提供的准确的驱动扭矩信息,可以提取轮胎纵向力。同时,提出了一种修改原有Dugoff轮胎模型的方法,以扩大轮胎力的工作范围,提高精度。然后,基于以纵向力为输入的降阶扩展卡尔曼滤波器,对道路摩擦力和车辆侧滑角进行联合估计。仿真结果表明,该算法能够在车辆处于侧向动力学条件下准确估计道路摩擦系数。

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