| With the rapid increase in the number of electric vehicles,there is an urgent need to solve the problems of environmental pollution and energy scarcity.In recent years,battery electric vehicle(BEV)has become the choice of more and more people because of its low cost,simple structure and low pollution emission.However,there is still a long way to go before battery electric vehicles become fully widespread.At present,battery electric vehicles are mainly constrained by bottlenecks such as power performance and range,which affect the overall performance of electric vehicles.In response to the problems of battery electric vehicles,this paper takes a battery electric vehicle developed by an automobile company as the research object,mainly to match and optimize the powertrain parameters to effectively improve the performance of the electric vehicles.The study of regenerative braking control strategies can reduce the energy consumption of electric vehicles and recover more energy lost during braking,thus extending the range of electric vehicles.The main research components are as follows:First,the initial parameters of the main components of the powertrain are designed.The power system arrangement scheme is determined according to the basic structure of the battery electric vehicle,and the longitudinal dynamics model of the vehicle is analyzed in depth.Based on this,the initial parameter design of the main components of the powertrain is completed using the vehicle parameters in combination with the design index parameters of the vehicle performance and the corresponding regulatory requirements,in preparation for the subsequent modeling of battery electric vehicles.Second,the initial matching results are verified and the drive train parameters are optimized.The construction of the electric vehicle model is completed in CRUISE software and the rationality of the initial parameter matching is verified.From the results,the target model has some room for optimization in terms of power and economy.The secondgeneration non-dominated ranking genetic algorithm(NSGA-Ⅱ)is used for multi-objective optimization of the transmission system,and the results show that the overall performance of the whole vehicle is improved after the optimization of the main gearbox speed ratio.Then,this article analyzes the force situation during the braking process of electric vehicles and the principle of braking force distribution,which is to further extend the driving range and improve energy utilization.This paper makes improvements to the front and rear braking force distribution strategies by analyzing typical braking force distribution strategies.The regenerative braking fuzzy controller was designed considering three factors:braking intensity,state of charge(SOC)and vehicle speed to coordinate the proportional relationship between electric power and mechanical braking force.At the same time,the constraints of motor performance and battery charging on regenerative braking energy recovery are adequately considered.To address the defects of fuzzy control,the adaptive fuzzy neural network algorithm(ANFIS)is used to further optimize the fuzzy control regenerative braking control strategy.Finally,the regenerative braking control strategy is simulated and analyzed.The braking energy recovery evaluation index is selected,and the simulation analysis is carried out by Simulink and CRUISE integrated control method in NEDC,CLTC-P city cycle conditions and typical braking conditions,which verifies that the designed regenerative braking control strategy can meet the braking safety requirements and has stronger braking energy recovery capability.In addition,compared with the fuzzy control strategy,the optimized regenerative braking control strategy has improved braking energy recovery and SOC contribution under urban cycle conditions and has good braking performance under typical braking conditions. |
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