为了解决电动汽车在加速和制动过程中容易发生滑移和抖动、不能满足稳定性和舒适性的要求,提出了一种基于主从式非线性模型预测(nonlinear model prediction,NMP)直接转矩控制(direct torque controt,DTC)的电动汽车鲁棒控制策略。采用...为了解决电动汽车在加速和制动过程中容易发生滑移和抖动、不能满足稳定性和舒适性的要求,提出了一种基于主从式非线性模型预测(nonlinear model prediction,NMP)直接转矩控制(direct torque controt,DTC)的电动汽车鲁棒控制策略。采用双电机-单控制器主从式驱动模型,基于模糊逻辑控制器,在线确定权重因子的精确值,生成优化电动汽车驱动决策的最优切换状态,保证电机速度的精确跟踪。结合NMP-DTC电机控制方法,设计了一种模糊逻辑ASR/ABS控制器,以角加速度变化和滑移率变化为输入,以补偿转矩为输出变量,根据道路特性的变化提供补偿转矩,保证电动汽车行驶在最佳滑移率范围内,提高行驶的稳定性。基于MATLAB/Simulink进行变负载转矩电机跟踪和汽车纵向稳定性仿真,与参考速度进行对比分析。结果表明,所提出的主从式NMP-DTC的电动汽车ASR/ABS控制,在变负载下不仅电机跟踪轨迹误差降低,而且可保证在加速和制动过程中车辆的纵向稳定性控制。展开更多
为了解决混合动力汽车的实时能量管理及优化问题,在保证不过多简化被控对象的基础上得到最优解,该文提出一种基于V2X(vehicle to vehicle,车车通信,以及vehicle to infrastructure,车与交通设施通信)的分层控制方法。设计了一种分层控制...为了解决混合动力汽车的实时能量管理及优化问题,在保证不过多简化被控对象的基础上得到最优解,该文提出一种基于V2X(vehicle to vehicle,车车通信,以及vehicle to infrastructure,车与交通设施通信)的分层控制方法。设计了一种分层控制器,上层控制器基于交通信号灯正时(signal phase and timing,SPAT)得到目标车速的初始值,并采用多岛遗传算法和非线性模型预测得到最优目标车速。下层控制器根据上层控制器的最优目标车速,采用自适应等效燃油消耗最小原理(adaptive equivalent consumption minimization strategy,A-ECMS),得到发动机和电机的最优输出功率。该文对分层控制方法进行了硬件在环仿真,仿真结果表明,该文提出的分层控制方法可以很好地实现混合动力汽车的实时能量管理,有效地避免混合动力汽车红灯停车,实现良好的车速跟随并减少百公里油耗。该研究可为解决混动力汽车实时能量管理及优化提供参考。展开更多
With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is establish...With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is established for HEV forward simulation and controller design. Considering the fact that the operation modes of the HEV are event-driven and the system dynamics is continuous time-driven for each mode, the structure of the controller is built and described with the hybrid automaton control theory. In this control structure, the mode selection process is depicted by the finite state machine （FSM）. The multi-mode switch controller is designed to realize power distribution. Furthermore, the vehicle mode operations are optimized, and the nonlinear model predictive control （NMPC） strategy is applied by implementing dynamic programming （DP） in the finite pre- diction horizon. Comparative simulation results demonstrate that the hybrid control structure is effective and feasible for HEV energy management design. The NMPC optimal strategy is superior in improving fuel economy.展开更多
文摘为了解决电动汽车在加速和制动过程中容易发生滑移和抖动、不能满足稳定性和舒适性的要求,提出了一种基于主从式非线性模型预测(nonlinear model prediction,NMP)直接转矩控制(direct torque controt,DTC)的电动汽车鲁棒控制策略。采用双电机-单控制器主从式驱动模型,基于模糊逻辑控制器,在线确定权重因子的精确值,生成优化电动汽车驱动决策的最优切换状态,保证电机速度的精确跟踪。结合NMP-DTC电机控制方法,设计了一种模糊逻辑ASR/ABS控制器,以角加速度变化和滑移率变化为输入,以补偿转矩为输出变量,根据道路特性的变化提供补偿转矩,保证电动汽车行驶在最佳滑移率范围内,提高行驶的稳定性。基于MATLAB/Simulink进行变负载转矩电机跟踪和汽车纵向稳定性仿真,与参考速度进行对比分析。结果表明,所提出的主从式NMP-DTC的电动汽车ASR/ABS控制,在变负载下不仅电机跟踪轨迹误差降低,而且可保证在加速和制动过程中车辆的纵向稳定性控制。
文摘为了解决混合动力汽车的实时能量管理及优化问题,在保证不过多简化被控对象的基础上得到最优解,该文提出一种基于V2X(vehicle to vehicle,车车通信,以及vehicle to infrastructure,车与交通设施通信)的分层控制方法。设计了一种分层控制器,上层控制器基于交通信号灯正时(signal phase and timing,SPAT)得到目标车速的初始值,并采用多岛遗传算法和非线性模型预测得到最优目标车速。下层控制器根据上层控制器的最优目标车速,采用自适应等效燃油消耗最小原理(adaptive equivalent consumption minimization strategy,A-ECMS),得到发动机和电机的最优输出功率。该文对分层控制方法进行了硬件在环仿真,仿真结果表明,该文提出的分层控制方法可以很好地实现混合动力汽车的实时能量管理,有效地避免混合动力汽车红灯停车,实现良好的车速跟随并减少百公里油耗。该研究可为解决混动力汽车实时能量管理及优化提供参考。
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the National Natural Science Foundation of China(Grant Nos.51475213&51305167)the Scientific Research Innovation Projects of Jiangsu Province(Grant No.KYLX_1022)
文摘With the combination of engine and two electric machines, the power split device allows higher efficiency of the engine. The operation modes of a power split HEV are analyzed, and the system dynamic model is established for HEV forward simulation and controller design. Considering the fact that the operation modes of the HEV are event-driven and the system dynamics is continuous time-driven for each mode, the structure of the controller is built and described with the hybrid automaton control theory. In this control structure, the mode selection process is depicted by the finite state machine （FSM）. The multi-mode switch controller is designed to realize power distribution. Furthermore, the vehicle mode operations are optimized, and the nonlinear model predictive control （NMPC） strategy is applied by implementing dynamic programming （DP） in the finite pre- diction horizon. Comparative simulation results demonstrate that the hybrid control structure is effective and feasible for HEV energy management design. The NMPC optimal strategy is superior in improving fuel economy.
