基于纵-横向动力学耦合的整车质量与道路坡度估计

Mass Estimation and Slope Estimation Based on Longitudinal-Transverse Dynamic Coupling

针对汽车行驶过程中存在侧向分力时应用纵向动力学模型进行整车质量与道路坡度估计存在偏差的问题,提出了基于纵-横向动力学耦合的质量估计模型和坡度估计算法。通过分析加速阶段对质量估计的影响,设定质量估计触发条件,并使用带遗忘因子的递推最小二乘法对整车质量进行估计,融合运动学卡尔曼滤波算法与动力学扩展卡尔曼滤波算法对道路坡度进行联合估计。通过Simulink-CarSim联合仿真与实车试验对算法进行验证,结果表明,基于纵-横向动力学的质量估计算法误差为0.82%,融合坡度估计算法误差在3%以内,验证了该算法具有较好的准确性与实时性。

To address the issue of deviation in the estimation of vehicle mass and road gradient by applying the longitudinal dynamics model when there is a lateral component force in the driving process of vehicles,this paper proposes a coupled mass estimation model based on longitudinal-horizontal dynamics and an algorithm for slope estimation.By analyzing the effect of the acceleration phase on mass estimation,the mass estimation trigger condition is set and the recursive least squares method with forgetting factor is used to estimate the vehicle mass,and the kinematic Kalman filter is fused with the kinematic extended Kalman filter to jointly estimate the road slope.The algorithm is validated by Simulink-CarSim joint simulation and real vehicle test.The results show that the error of the mass estimation algorithm based on longitudinaltransverse dynamics is 0.82%,and the error of the fusion slope estimation algorithm is within 3%,which verifies that the algorithm has good accuracy and real-time performance.