Study And Optimization On The Power Train For Parallel Hybrid Electric City Bus

The development of vehicle industry brings the fast development of human civilizations and social economy. Nowadays, there are 0.8 billion cars all over the world and there will be more and more cars as time goes by. But as the increase of the number, exhaust gas also brings the deterioration of air quality and the shortage of energy. The city bus travels slowly in the city, and starts, brakes, idles frequently, these all lead to the high oil consumption and emissions. So, it is emergent to improve a new kind of bus, which lets less while consumes less.Because of the fatal technical defects, electric vehicles can not be industrialized in the short term. So, improving the HEV is good for solving the problem of circumstances and energy.This text has presented an electromechanical coupling program and chosen some components including the diesel engines, AC induction motor and nickel-metal hydride batteries on the basis of analyzing the different structural types and mixes of the existing hybrid vehicles.In this paper, it have introduced some major subsystems (such as engines, motors, batteries and transmission) of the power system, and used the MATLAB/SIMULINK to establish a mathematical model for components and vehicle.This paper also have developed a fuzzy control strategy in the line with ECE-EUDC-LOW for the hybrid city bus, including for the drive model and the brake model, and used the MATLAB/SIMULINK to establish a mathematical model for the fuzzy control strategy on the basis of the electromechanical coupling program and fuzzy logic control theory.After introducing the working principle of ADVISOR2002, this paper used the software to simulate the hybrid electric city bus and have verified that the power system can meet the design requirements. As soon as this paper has analyzed the result of simulation and optimized this system. After the contrast of the simulation results, this paper has verified that the optimized model can also catch the design requirement and the normalized objective.