Heavy commercial vehicles equipped with a hydraulic hub-motor auxiliary system(HHMAS)often operate under complex road conditions.Selecting appropriate operating mode and realizing reasonable energy management to match...Heavy commercial vehicles equipped with a hydraulic hub-motor auxiliary system(HHMAS)often operate under complex road conditions.Selecting appropriate operating mode and realizing reasonable energy management to match unpredictable road conditions are the keys to the driving performance and fuel economy of HHMAS.Therefore,a multi-mode energy management strategy(MM-EMS)based on improved global optimization algorithm is proposed in this study for HHMAS.First,an improved dynamic programming(DP)algorithm for HHMAS is developed.This improved DP algorithm considers the effect of SOC and vehicle speed,thereby preventing the calculation results from falling into local optimization.This algorithm also reduces the dimension of the control variable data grid,and the calculation time is reduced by 35%without affecting the accuracy.Second,a MM-EMS with hierarchical control is proposed.This strategy extracts the optimal control rules from the results of the improved DP algorithm.Then it divides the system’s operating region into two types,namely,single-mode working region and mixedmode working region.In the single-mode working region,mode switching is realized through fixed thresholds.In the mixedmode working region,a linear quadratic regulator(LQR)is adopted to determine a target mode and realize SOC tracking control.Finally,the designed MM-EMS is verified separately in offline simulation and hardware-in-the-loop(HIL)under actual vehicle test cycles.Simulation results show that the results between HIL and offline simulation are largely coincidence.Besides,in comparison with the engine optimal control strategy,the designed MM-EMS can achieve an approximate optimal control,with oil savings of 3.96%.展开更多
以轮毂电动机驱动电动汽车为研究对象,采用分层控制策略提出自适应巡航系统,结合上层模型预测控制器与下层PID(proportion integral differential)控制器,针对复杂的纵向跟随工况,对轮毂电动机输出的驱动力矩进行精确控制.提出基于前车...以轮毂电动机驱动电动汽车为研究对象,采用分层控制策略提出自适应巡航系统,结合上层模型预测控制器与下层PID(proportion integral differential)控制器,针对复杂的纵向跟随工况,对轮毂电动机输出的驱动力矩进行精确控制.提出基于前车加速度的可变车头时距策略,利用模型预测控制算法(model predictive control,MPC)求解本车期望加速度的上层控制器,利用PID算法求解整车前后轴驱动力矩,并输入到轮毂电动机的下层控制器,实现前后轮驱动力矩分配,最终实现车辆纵向自适应巡航.建立联合仿真模型,针对匀速前进、紧急制动、城市循环工况等场景,对所提出的自适应巡航分层控制策略进行验证,结果表明:所提出的自适应巡航系统控制策略针对纵向复杂行驶工况的跟驰效果良好,跟驰过程中车间距误差较小,加速度变化与电动机驱动转矩变化可以较好地进行同步与响应.展开更多
基金the National Key Research and Development Program of China (Grant No. 2018YFB0105900)。
文摘Heavy commercial vehicles equipped with a hydraulic hub-motor auxiliary system(HHMAS)often operate under complex road conditions.Selecting appropriate operating mode and realizing reasonable energy management to match unpredictable road conditions are the keys to the driving performance and fuel economy of HHMAS.Therefore,a multi-mode energy management strategy(MM-EMS)based on improved global optimization algorithm is proposed in this study for HHMAS.First,an improved dynamic programming(DP)algorithm for HHMAS is developed.This improved DP algorithm considers the effect of SOC and vehicle speed,thereby preventing the calculation results from falling into local optimization.This algorithm also reduces the dimension of the control variable data grid,and the calculation time is reduced by 35%without affecting the accuracy.Second,a MM-EMS with hierarchical control is proposed.This strategy extracts the optimal control rules from the results of the improved DP algorithm.Then it divides the system’s operating region into two types,namely,single-mode working region and mixedmode working region.In the single-mode working region,mode switching is realized through fixed thresholds.In the mixedmode working region,a linear quadratic regulator(LQR)is adopted to determine a target mode and realize SOC tracking control.Finally,the designed MM-EMS is verified separately in offline simulation and hardware-in-the-loop(HIL)under actual vehicle test cycles.Simulation results show that the results between HIL and offline simulation are largely coincidence.Besides,in comparison with the engine optimal control strategy,the designed MM-EMS can achieve an approximate optimal control,with oil savings of 3.96%.
文摘以轮毂电动机驱动电动汽车为研究对象,采用分层控制策略提出自适应巡航系统,结合上层模型预测控制器与下层PID(proportion integral differential)控制器,针对复杂的纵向跟随工况,对轮毂电动机输出的驱动力矩进行精确控制.提出基于前车加速度的可变车头时距策略,利用模型预测控制算法(model predictive control,MPC)求解本车期望加速度的上层控制器,利用PID算法求解整车前后轴驱动力矩,并输入到轮毂电动机的下层控制器,实现前后轮驱动力矩分配,最终实现车辆纵向自适应巡航.建立联合仿真模型,针对匀速前进、紧急制动、城市循环工况等场景,对所提出的自适应巡航分层控制策略进行验证,结果表明:所提出的自适应巡航系统控制策略针对纵向复杂行驶工况的跟驰效果良好,跟驰过程中车间距误差较小,加速度变化与电动机驱动转矩变化可以较好地进行同步与响应.