分布式驱动电动汽车纵向车速非线性自适应估计

Vehicle Longitudinal Velocity Nonlinear Adaptive Estimation of Distributed Drive Electric Vehicle

摘要:

基于分布式驱动电动汽车，提出了一种纵向车速非线性自适应估计算法.该算法使用车辆加速度传感器信息和各车轮滑移率反馈值对车辆纵向车速进行估计.从理论上证明了纵向速度估计误差收敛.根据各车轮滑移率的大小确定各轮速估计误差在估计算法中的反馈修正比例.使用带遗忘因子的递推最小二乘算法在坡道路面对路面坡度进行了在线实时估计，进而使用坡度估计值修正纵向加速度传感器信息，实现了坡度自适应纵向车速估计.该方法具有计算量小、估计精度高的优点.通过多工况的实车试验验证了算法的有效性.

Abstract:

A new algorithm for vehicle longitudinal velocity using the nonlinear adaptive estimation method was proposed based on distributed drive electric vehicle. According to the information of longitudinal acceleration sensor and the feedback value of each wheel slip ratio, the vehicle longitudinal velocity was estimated and algorithm proved the longitudinal velocity estimation error convergence. Depending on each wheel slip ratio, the feedback correction proportion for estimation algorithm of each wheel speed estimation error was determined. The road slope was estimated online using recursive least square with forgetting factor in rampway. In addition, the longitudinal acceleration sensor information was calibrated by the slope estimation value for slope adaptive longitudinal velocity estimation. The amount of computations for this method was small but with high estimation precision. Furthermore, the effectiveness of the algorithm was validated through experiments under multiple working conditions.