基于向量式多遗忘因子最小二乘法的城轨列车储能元件充放电参数辨识

采用一种改进的向量式遗忘因子最小二乘法(vector forgetting factor-least square,VFF-LS)作为城轨列车储能元件参数辨识的方法。首先,对比分析了典型储能电池相关等效电路模型,选取Thevenin等效电路模型降低参数辨识过程复杂度;其次,在传统最小二乘法(least square,LS)参数辨识原理的基础上推导出VFF-LS的储能元件参数辨识方法;最后,采用上述方法对2种典型的城轨列车典型储能元件电池组及单体进行了参数辨识。结果表明,通过VFF-LS方法得到的参数辨识误差均小于15 mV,低于传统LS方法。所采用的方法在充分降低辨识过程复杂性的基础上,能够对不同类型的电池进行精确参数辨识,这将为城轨列车电池管理系统(battery management system,BMS)的设计提供有力支持。

An Effective Multiple Model Least Squares Method in Tracking of a Maneuvering Target

A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.

坡度和整车质量识别及其在AMT换挡规律中的应用

针对带两挡AMT变速箱的纯电动客车在实际运行时因整车质量和道路坡度的变化导致最佳换挡点发生变化的问题,采用多遗忘因子递推最小二乘法对道路坡度和整车质量进行了在线辨识,将识别的道路坡度作为换挡控制参数,制定了以加速踏板开度、车速、车辆纵向加速度和道路坡度为控制参数的四参数换挡控制策略,采用Simulink和AVLCruise软件搭建了控制策略模型和整车模型,两软件联合仿真对平路空载得到的三参数动力性换挡规律和新制定的四参数换挡策略进行了仿真计算,结果表明:多遗忘因子递推最小二乘法能准确识别道路坡度,与平路空载得到的三参数动力性换挡规律相比,新制定的四参数换挡策略能够适应道路坡度的变化。