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

机译：基于轮内电动机驱动电动车的横向动力学，第57章道路摩擦系数估计

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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使用由轮式电动机驱动的电动车辆提供的驱动扭矩的精确信息，提取轮胎纵向力。同时，本文提出了一种修改原始Dugoff轮胎模型的方法，以扩大轮胎力工作范围，提高精度。然后，基于作为输入的纵向力的减小的延伸卡尔曼滤波器来执行道路摩擦和车辆侧坡角度的联合估计。仿真结果表明，当车辆处于横向动态时，该算法可以准确地估计道路摩擦系数。

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