Proper braking force distribution strategies can improve both stability and economy performance of hybrid electric vehicles,which is prominently proved by many studies.To achieve better dynamic stable performance and ...Proper braking force distribution strategies can improve both stability and economy performance of hybrid electric vehicles,which is prominently proved by many studies.To achieve better dynamic stable performance and higher energy recovery efficiency,an effective braking control strategy for hybrid electric buses(HEB)based on vehicle mass and road slope estimation is proposed in this paper.Firstly,the road slope and the vehicle mass are estimated by a hybrid algorithm of extended Kalman filter(EKF)and recursive least square(RLS).Secondly,the total braking torque of HEB is calculated by the sliding mode controller(SMC),which uses the information of brake intensity,whole vehicle mass,and road slope.Finally,comprehensively considering driver’s braking intention and regulations of the Economic Commission for Europe(ECE),the optimal proportional relationship between regenerative braking and pneumatic braking is obtained.Furthermore,related simulations and experiments are carried out on the hardware-in-the-loop test bench.Results show that the proposed strategy can effectively improve the braking performance and increase the recovered energy through precise control of the braking torque.展开更多
汽车质量与道路坡度是汽车主动安全控制系统的重要参数.提出一种汽车质量与道路坡度串行估计算法.根据汽车质量与道路坡度变化的快慢进行分层串行估计,将缓慢变化的汽车质量作为第一层的估计输出,将快速变化的道路坡度作为第二层的估计...汽车质量与道路坡度是汽车主动安全控制系统的重要参数.提出一种汽车质量与道路坡度串行估计算法.根据汽车质量与道路坡度变化的快慢进行分层串行估计,将缓慢变化的汽车质量作为第一层的估计输出,将快速变化的道路坡度作为第二层的估计输出.基于纵向动力学,首先由轮胎驱动力矩与横摆角速度通过递推最小二乘法(Recursive Least Squares,RLS)算法进行第一层的汽车质量估计;接着将估计得到的汽车质量代入至第二层牛顿迭代法进行道路坡度估计.与传统的自适应估计方法相比,提出的算法可以减少实时估计参数的耦合效应,且不需要额外的传感器;最后通过仿真及模型车辆道路试验对所提出的算法进行验证,仿真及试验结果表明:所提出的辨识算法能够准确实时地估计汽车质量与道路坡度.展开更多
基金Electric Automobile and Intelligent Connected Automobile Industry Innovation Project of Anhui Province of China(Grant No.JAC2019022505)Key Research and Development Projects in Shandong Province of China(Grant No.2019TSLH701).
文摘Proper braking force distribution strategies can improve both stability and economy performance of hybrid electric vehicles,which is prominently proved by many studies.To achieve better dynamic stable performance and higher energy recovery efficiency,an effective braking control strategy for hybrid electric buses(HEB)based on vehicle mass and road slope estimation is proposed in this paper.Firstly,the road slope and the vehicle mass are estimated by a hybrid algorithm of extended Kalman filter(EKF)and recursive least square(RLS).Secondly,the total braking torque of HEB is calculated by the sliding mode controller(SMC),which uses the information of brake intensity,whole vehicle mass,and road slope.Finally,comprehensively considering driver’s braking intention and regulations of the Economic Commission for Europe(ECE),the optimal proportional relationship between regenerative braking and pneumatic braking is obtained.Furthermore,related simulations and experiments are carried out on the hardware-in-the-loop test bench.Results show that the proposed strategy can effectively improve the braking performance and increase the recovered energy through precise control of the braking torque.
文摘汽车质量与道路坡度是汽车主动安全控制系统的重要参数.提出一种汽车质量与道路坡度串行估计算法.根据汽车质量与道路坡度变化的快慢进行分层串行估计,将缓慢变化的汽车质量作为第一层的估计输出,将快速变化的道路坡度作为第二层的估计输出.基于纵向动力学,首先由轮胎驱动力矩与横摆角速度通过递推最小二乘法(Recursive Least Squares,RLS)算法进行第一层的汽车质量估计;接着将估计得到的汽车质量代入至第二层牛顿迭代法进行道路坡度估计.与传统的自适应估计方法相比,提出的算法可以减少实时估计参数的耦合效应,且不需要额外的传感器;最后通过仿真及模型车辆道路试验对所提出的算法进行验证,仿真及试验结果表明:所提出的辨识算法能够准确实时地估计汽车质量与道路坡度.
