Research On Optimization Method Of Energy Management Control Strategy For Plug-in Hybrid Electric Bus

As the number of traditional fuel vehicles in China has steadily increased,the urban traffic congestion and air pollution caused by vehicles driving are becoming more and more serious.Relied on excellent energy-saving and environmental protection characteristics,the plug-in electric bus(PHEB)is expected to become one of the important solutions to alleviate these social problems.The advantages of PHEB come from hybrid powertrain consisting of an engine and an electronic motor,which enables the vehicle to cope efficiently with complex vehicle driving conditions in a variety of operating modes,through dynamic coupling in different operating states.Of course,the control role of energy management strategy(EMS)is indispensable,to make them operate ideally in coordination and drive vehicle with higher fuel economy.To ensure that EMS could effectively exert a great control effect,this paper is committed to study and explore strategy optimization methods,so that the excellent performance of PHEB could be fully displayed.To further improve the fuel economy of PHEB,this paper studies the design of EMS and its optimization methods,combined with the configuration of studied coaxial parallel hybrid powertrain,the working characteristics of its internal engine,electric motor,battery and gearbox and so on.Specific research contents are as follow:To enable the powertrain to propel PHEB with high fuel economy,an EMS based on fuzzy control is designed in this paper,which could distribute the working torque between the engine and electric motor,so that the output torque of the engine could be optimized and adjusted in the auxiliary role of the electric motor.In addition,considering the influence of internal parameters of EMS on the control effect and the problem that traditional optimization algorithm is easy to fall into local optimal,this paper uses individual selection method based on Gaussian distribution probability to improve original genetic algorithm,and proposes an enhanced genetic algorithm(EGA).This novel algorithm could optimize the membership function of fuzzy controller,according to the characteristics of driving road.The relevant simulation results show that this strategy could make the engine operating points converge to the region with low effective fuel consumption rate as far as possible,so as to effectively reduce the PHEB total energy consumption.Considering the potential adverse brought by expert empirical rule base on the improvement of strategy performance in classical fuzzy control,this paper reconstructs the torque distribution controller by adopting the Takagi-Sugeno(T-S)architecture,whose control rules can be optimized.Otherwise,to optimize the engine speed additionally,the gear shifting problem in powertrain is also taken into account in EMS.Based on this,this paper proposes a more efficient adaptive firework algorithm(AFWA),which could quickly optimize parameters of T-S fuzzy controller and gear shift controller.In this way,the optimized EMS enables engine output power in a more ideal working state,to further improve the fuel economy of PHEB.The effectiveness,the improvement of vehicle fuel economy and real-time control performance of this strategy are verified by simulation and hardware-in-loop(HIL)tests,respectively.