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
An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile th...An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile that compromises fuel economy andmobility while guaranteeing the safety of each vehicle. In the model predictive control framework, an engine-map-based fuelconsumption model is established by implementing a backward conventional vehicle model in the cost function. Moreover,the cost function is normalized by dividing each term by its reference value. An extra cost is added to the safety term when thedistance between adjacent vehicles drops to a critical value to guarantee vehicle safety, while another extra cost is consideredfor the velocity tracking term to prevent the violation of traffic rules. The results of simulation show the effectiveness of theproposed control method.展开更多
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.
基金the National Hi-Tech Research and Development Program of China(“863”Project)(Grant No.2015BAG17B04)National Natural Science Foundation of China(Grant No.51875149)China Scholarship Council(Grant No.201506690009)and U.S.Department of Energy GATE program.
文摘An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile that compromises fuel economy andmobility while guaranteeing the safety of each vehicle. In the model predictive control framework, an engine-map-based fuelconsumption model is established by implementing a backward conventional vehicle model in the cost function. Moreover,the cost function is normalized by dividing each term by its reference value. An extra cost is added to the safety term when thedistance between adjacent vehicles drops to a critical value to guarantee vehicle safety, while another extra cost is consideredfor the velocity tracking term to prevent the violation of traffic rules. The results of simulation show the effectiveness of theproposed control method.
