Research On Control Strategy Of Plug - In Hybrid Gas - Electric Hybrid Bus

Exhaust pollution, shortage of oil resources and other issues are outstanding, which makes people increasingly realize the importance of the development of new energy vehicles, triggering a worldwide wave of research for new energy vehicles. As one kind of electric vehicles, plug-in hybrid electric vehicle has the function of the pure electric vehicle and hybrid electric vehicle, can be charged by external power and is considered to be the optimal transition to pure electric vehicles under present condition.The design of plug-in hybrid electric vehicle control strategy is difficult. Based on the analysis of different control strategies, the fuzzy control strategy was proposed. In view of the problems which exist in the fuzzy control, the multiple population genetic algorithm was adopted to optimize the membership function of fuzzy controller and the main control parameters of the control strategy.Plug-in hybrid development status at home and abroad, Plug-in hybrid electric vehicle working characteristics and the commonly used control strategies are summarized, and then fuzzy control strategy was put forward. The main characteristics of simulation software ADVISOR were introduced.Under the condition of selecting plug-in parallel gas-electric hybrid bus as research object produced by a vehicle company, the main components and vehicle simulation model in MATLAB / Simulink environment are established. On the basis of full knowledge of the basic characteristics and mathematics theory of fuzzy control theory, the fuzzy controller was established. The SOC value of battery and the total demand for the input torque were designed as input parameters and the engine torque output of the fuzzy controller were designed as output parameter. Based on the second development of ADVISOR, the fuzzy controller is mounted to the vehicle simulation model of ADVISOR. Based on the comparative simulations of fuzzy control strategy and electric auxiliary control strategy, the simulation results showed that fuzzy control Strategies is better than electric auxiliary control strategy on the aspect of acceleration and fuel economy performance.For the problem that the design of the membership function shapes and control parameters of the fuzzy control strategy is full of subjective arbitrariness, multiple population genetic algorithm is selected to optimize the membership function of fuzzy controller and the six main control parameter. Through M file written in MATLAB, the multiple population genetic algorithm and ADVISOR function without the graphical interface were combined to optimize the membership function of fuzzy controller and the six main control parameter. The optimized parameters are embedded into ADVISOR and compared to fuzzy control strategy that is not optimized, finding that gas consumption per hundred kilometers and NOX emissions of the optimized control strategy have been greatly reduced, acceleration performance has also been a certain degree of increase.