Research Of Pure Electric Vehicle Dynamic Parameter Optimization Based On Ant Colony Algorithm

In recent years, with the rapid development of automobile industry, the traditional fuel cars not only bring too much harm to environment and people’s living healthy, but also make the energy shortage problem has become increasingly prominent. Thus the new energy vehicles become a hot topic in the field of automobile, pure electric vehicle is one of the main research directions in the future. Pure electric vehicle has advantages of simple structure, high energy efficiency, zero emissions, low noise, easy to shape and so on. Based on these advantages, with the support of national policy and the development of electric vehicle technology, pure electric vehicle in the future will be massive popularity.Power system is one of the key systems of the car, in the other conditions remain constant, the rational parameters match the power system can maximize the power of pure electric vehicles and driving range. Therefore, this article mainly aims at the dynamic system of pure electric vehicles, parameters matching and optimization.In this paper, take a model of fuel vehicle as prototype, laid out a restructuring of its power system structure. Then according to the vehicle parameters and its performance index, combined with the automobile theory and other related knowledge, making a reasonable match for drive motor, battery and transmission parameters. And then establish various auto parts based on the simulation model of ADVISOR, edit each module M file in Matlab environment, simulate and analyze the results. Finally, based on the ant colony algorithm to optimize the parameters of the power system, and associate with performance simulation. By comparing the optimized scheme and the design scheme of simulation results, the optimized result has reached the expected goals, ant colony algorithm can be applied to pure electric vehicle power system parameter optimization.