Multi-objective Energy Consumption Optimization Of Electric Vehicle Based On Genetic Algorithms

In recent years,the development of electric vehicles has entered the high-speed lane,and the scale of industrialization is growing.Technological innovation has led to the increasing mileage of electric vehicles,but the technical bottleneck of industrial development still exists.New energy vehicles and not only the driving mileage,energy consumption rate has become the focus of attention.The drive motor and speed reducer system of pure electric vehicle greatly affect the performance of electric vehicle.How to achieve the optimal matching of the two parameters has a great impact on the performance of the vehicle before the breakthrough of the core technology of power battery has not been achieved.In this paper,the influence factors of energy consumption,the matching method of power system parameters,the optimization of drive system parameters and the energy consumption optimization scheme of pure electric vehicles are studied and analyzed in depth.The specific contents are as follows:(1)To design an optimal matching method of comprehensive power and economy,which can improve the economy on the premise of considering both power and economy.(2)A multi-objective optimization model is established on AMESim engineering software platform by using genetic algorithm to realize the optimal matching method of motor and speed reduction parameters.(3)Through software simulation and vehicle experiment,the optimized economic results are verified,and the ideas and methods of further energy saving and consumption reduction in the process of prototype development are analyzed according to the related factors of the prototype.