The energy management may perform well under normal conditions, but may lead to poor behavior under abnormal situations. To tackle this problem, an optimal control strategy called rule-based equivalent fuel consumptio...The energy management may perform well under normal conditions, but may lead to poor behavior under abnormal situations. To tackle this problem, an optimal control strategy called rule-based equivalent fuel consumption minimization strategy （RECMS） is developed for a new complex hybrid electric vehicle （CHEV）. It optimizes the energy efficiency and drive performance to cater for normal and power-loss operations of the tractive motor. Firstly, the strategy formulates a novel objective function based on the equivalent fuel concept. By accounting for the actual fuel cost, the equivalent fuel cost for the electric machines and virtual fuel cost for the drivability, the cost function is obtained. Furthermore, some penalty factors are presented to optimize the performance target. Finally, experiments for a practical CHEV are performed to validate a simulation model. Then simulations are carried out for both rule-based and RECMS. The results show that the optimal energy management is working well.展开更多
基金the National High Technology Research and Development Program (863) of China(No. 2006AA11A127)
文摘The energy management may perform well under normal conditions, but may lead to poor behavior under abnormal situations. To tackle this problem, an optimal control strategy called rule-based equivalent fuel consumption minimization strategy （RECMS） is developed for a new complex hybrid electric vehicle （CHEV）. It optimizes the energy efficiency and drive performance to cater for normal and power-loss operations of the tractive motor. Firstly, the strategy formulates a novel objective function based on the equivalent fuel concept. By accounting for the actual fuel cost, the equivalent fuel cost for the electric machines and virtual fuel cost for the drivability, the cost function is obtained. Furthermore, some penalty factors are presented to optimize the performance target. Finally, experiments for a practical CHEV are performed to validate a simulation model. Then simulations are carried out for both rule-based and RECMS. The results show that the optimal energy management is working well.
