The invention provides a road feeling feedback torque estimation method based on an unscented Kalman filter. The road feeling feedback torque estimation method comprises the following steps: acquiring three-phase current, a rotor angle and automobile state parameters of a brushless direct current motor; an unscented Kalman filter is constructed through an automobile two-degree-of-freedom model, a Dugoff tire model and a current torque conversion equation, and rack torque is determined according to the three-phase current of a motor, a rotor angle and automobile state parameters; calculating an inertia moment, a damping moment, a friction moment and an EPS assisting moment of a steering system according to the automobile state parameters; calculating a road feeling feedback torque through a rack torque calculated by an unscented Kalman filter, and the calculated inertia torque, damping torque, friction torque and EPS assistance torque; compared with the prior art, the method has the advantage of more accurate road feeling feedback.
本发明提出一种基于无迹卡尔曼滤波器的路感反馈力矩估算方法,包括以下步骤:获取无刷直流电机的三相电流、转子转角及汽车状态参数;通过汽车二自由度模型、Dugoff轮胎模型以及电流转矩转换方程构建无迹卡尔曼滤波器,根据电机的三相电流、转子转角以及汽车状态参数确定齿条力矩;根据汽车状态参数计算转向系统的惯性力矩、阻尼力矩、摩擦力矩以及EPS助力矩;通过无迹卡尔曼滤波器计算的齿条力矩,与所计算的惯性力矩、阻尼力矩、摩擦力矩以及EPS助力矩,计算路感反馈力矩;与现有技术相比,本发明具有路感反馈更准确的优点。
Road feeling feedback torque estimation method based on unscented Kalman filter
一种基于无迹卡尔曼滤波器的路感反馈力矩估算方法
18.06.2024
Patent
Elektronische Ressource
Chinesisch
A QUATERNION UNSCENTED KALMAN FILTER FOR ROAD GRADE ESTIMATION
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