Research On Energy Management Strategy And Performance Optimization Of Extended Range Electric Logistics Vehicle

As the development direction of global automotive industry technology transformation,new energy vehicles have developed rapidly in recent years.However,due to the fact that the technical performance,cost and life of power battery have not yet made a revolutionary breakthrough,the problems of pure electric vehicle products such as driving range anxiety,high cost,long charging time and poor environmental adaptability have not been well solved.As a new energy vehicle with longer driving range and lower cost,extended range electric vehicle is widely concerned by the industry.Especially with the rapid development of domestic logistics industry in recent years,the extended range electric logistics vehicle has become a popular new energy vehicle product with great development potential in urban environment because of its relatively simple structure,low comprehensive cost,and can greatly increase the driving range of the whole vehicle,so as to avoid the mileage anxiety of users.There are many kinds of energy sources in extended range electric vehicles,and their energy management strategy has an important impact on the key technical indicators such as vehicle energy consumption,economy and power performance.Therefore,it is a key problem to propose and formulate a scientific and reasonable energy management strategy in the development process of extended range electric vehicles.In this paper,relying on a production university research cooperation project,focusing on the product development and industrial promotion needs of an extended range electric logistics vehicle,on the basis of meeting the main technical indicators such as vehicle power performance and driving range,combined with the specific use and operation conditions of the product,the goal is to improve the comprehensive energy utilization efficiency and minimize energy consumption per unit driving cycle,focus on the vehicle energy management control strategy and performance optimization methods.A fuzzy control strategy of energy management for fuel economy optimization of unit driving cycle is formulated,and a fast optimization control algorithm based on BP artificial neural network for fuel economy performance of energy management strategy is proposed.The simulation results show that the new fuzzy control strategy can significantly improve the vehicle energy efficiency in unit driving cycle compared with the energy management strategy based on deterministic rules.The specific research contents are as follows:1.According to the design index of pure electric driving range of the target vehicle,the key assembly and components of the power system of an extended range electric logistics vehicle are selected and matched.The cruise platform of AVL company is used to model the vehicle and verify the result of parameter matching.Based on the MATLAB / Simulink platform,the control strategy model of subsystems such as range extender is built,and the vehicle simulation technology platform is developed.2.This paper analyzes the energy management strategy of extended range electric vehicle widely used in the industry,puts forward the development requirements of energy management strategy combined with the characteristics of the research object vehicles,and formulates a fuzzy control energy management strategy based on the minimum equivalent fuel consumption per unit driving cycle,The expected driving range is introduced into the control strategy to ensure that the battery power can be fully and reasonably utilized at the end of a single driving cycle,and the low-efficiency power holding stage in the driving cycle can be reduced or eliminated.The control strategy is modeled and compiled in Simulink environment,and the vehicle model and control strategy are jointly simulated on cruise platform.The simulation results show that the SOC value of the vehicle battery conforms to the expected planning curve,and the fuel economy is improved by about 5%.3.Based on the performance characteristics of fuzzy control strategy and its dependence on empirical value,in order to reduce the requirement of empirical data for optimization strategy and further improve the vehicle economy,intelligent technology is applied to optimize the control algorithm,and a fast optimization method based on BP artificial neural network is proposed.The algorithm structure of the neural network is designed.The neural network is trained by the optimized vehicle simulation data set,and the energy management strategy model based on BP neural network is built.Simulation analysis and comparison results show that the optimization algorithm can meet the requirements of fast optimization of control algorithm,and the fuel economy of the whole vehicle is improved by about 1.3%.The research content of this paper can provide reference for the research of energy management strategy of extended range electric vehicles.The research results of this paper have reference value for accelerating the application of engineering technology of extended range electric vehicles and promoting the improvement of vehicle performance.