A Study On The Parameters Matching And Optimization Of Power Drive System For Pure Electric Vehicle

With the energy shortages and environmental pollution problems have become increasingly prominent, it is imperative to develop energy-efficient and new energy vehicles for the global car industry. As a typical representative of new energy vehicles, Pure electric vehicles, with its advantages of low-power and zero-emission, is becoming the most feasible and effective solutions to solve the two major problemsundoubtedly. Power battery is one of the core component of pure electric vehicles.Its indicators, such as security, specific energy, longevity, plays the decisive role for vehicle performance. Whether power system parametersmatchingis reasonable or notwill also have a significant impact on vehicle performance. Therefore, the purpose of this article is, through matchingpower system parametersreasonably, to reduce energy consumption and increase driving range under the premise of meeting power and reliability performance.Based ondesign requires of the development of new energy vehiclespowertrain, developa set of feasible power system parameter matching and optimization scheme. Firstly, analyzing the power systemstructureand mechanical properties, then according to the requirements of pure electric vehicle drive motor, battery power,transmission ratio,etc. selectionand the calculations carried out. Secondly, The simulation models of all parts which make up the power system of pure electric vehicles(including motor, battery, themain reducer) are established, the wholeperformance of vehicle is simulated, such as dynamic performance and endurancemileage.Thirdly, presenting an optimized scheme based on multi-objective genetic algorithm for pure electric vehicle.The multi-objective optimization model use the gear ratio of final drive as design variable, use the acceleration time and specific energy consumption as the dual objective functions, use the requirement of vehicle power performance as the constraint condition, to solve with proportion weighted coefficient method. Analysis the parameter matching results showed that the vehicle top speed reduced by 0.09% after optimization, 0 to 50 km/h acceleration times reduced 0.28 s, driving cycle and constant speed driving range respectively increased by 2.25%, 2.76%. Finally, Vehicle verification experiments were carried out according to relevant national standards. The simulation and experiments results verified that the presenting optimized scheme based on multi-objective genetic algorithm for pure electric vehicle is Reasonable and effective.