Research On Control Strategy And Assembly Parameter Matching For Series Hybrid Electric Bus

Nowadays,the whole globe is facing the problems of energy crisis and air pollution.These problems propel us to consider the development of the future vehicle.If human further adopt internal combustion engine(ICE) technique to develop automotive industry,energy security and environmental protection will assume huge pressure.How to improve the performance of the automobile and reduce energy consumption and the amount of pollution is the important content of the automotive technique research at present.Therefore,many countries are now researching and developing electric vehicle(EV) in order to reduce energy consumption and the amount of pollution.Having the benefits of both EV and traditional internal combustion vehicle, Hybrid Electric Vehicle(HEV) becomes the focus of vehicle research and development.As there are many different projects to construct a certain HEV,it's waste of capital and time to design and test HEV one by one.It's necessary to research HEV structure and control strategy by using computer simulation technology.The driving cycle has great effect on fuel economy for the HTB(Hybrid Transit Bus),at the same time,the power train configuration,parameters matching,control strategy and control algorithm for HEV are based on driving cycle.Based on the study on HEV and city driving cycle,the parameters of its power train are matched and the models for the main power train parts are created for preparation of simulation later.Then a performance simulation of the whole vehicle is analyzed.The results show:the parts parameters selected can meet the demand of the project.The "thermostat" and "power-follow" control strategy are compared and analyzed. Afterward,a new control method is introduced,namely fuzzy logic control strategy targeted on constant SOC.The simulation result shows a anticipative purpose is achieved through this model.Finally the parameters are researched primarily,thus a theoretical instruction is provided for the optimization of HEV bus power train later.