Research On The Optimization Of Battery Distribution Of Shared Vehicles Considering The Whole Process Of Charging And Swapping

To achieve China’s "30·60" decarbonization goal is a major strategic decision made by China in coordination with the overall situation at domestic and abroad.By accelerating the construction of a low-carbon transportation system and promoting energy-saving and low-carbon transportation tools,it can help achieve clean energy substitution in the field of transportation.Shared electric vehicles can not only improve the utilization rate of vehicles in the field of transportation,reduce the pressure on public transportation,but also have the advantages of integrating various resources,reducing equipment energy consumption,and reducing environmental pollution.At present,the core problem restricting the popularity of shared electric vehicles is the "dilemma" of charging and scheduling,and the charging and replacement battery distribution network of shared electric vehicles is constructed,which can effectively solve the problem of charging shared electric vehicles on the one hand,and reduce the real-time scheduling pressure of shared electric vehicles on the other.Based on this background,this paper constructs a battery distribution path optimization model for shared electric vehicles based on NSGA-Ⅱ algorithm,conducts research on charging and swapping battery allocation of shared electric vehicles,and conducts research on transportation path optimization for charging and swapping batteries of shared electric vehicles,which can effectively improve the problems existing in battery scheduling of shared electric vehicles,and has strong feasibility and application.The research content and results of this paper are as follows:Firstly,the relevant factors affecting the construction of the charging and swapping battery distribution network and the battery delivery path were analyzed.This article studies the current shared electric vehicle system and operating mode,the existing planning of the charging and swapping battery distribution network,and the relevant factors that affect the construction of the charging and swapping battery distribution network and battery distribution path,providing a theoretical basis and research ideas for the construction of a shared electric vehicle battery distribution path optimization model in the following text.Secondly,an optimization model for the distribution of shared electric vehicle batteries considering the demand for charging and swapping has been established.This paper considers the main service characteristics of shared electric vehicles,plans a typical charging and swapping battery distribution network scenario for shared electric vehicles,and considers the uncertainty of large-scale battery charging in time and space.It constructs a phased control battery scheduling strategy model for centralized charging stations,targeting relevant factors that affect the operating cost and user satisfaction of charging and swapping batteries,We have constructed a dual objective battery delivery path optimization model that considers the lowest total operating cost and the highest user satisfaction.This paper introduces the NSGA-Ⅱ algorithm to solve the optimization model,effectively improving the accuracy and efficiency of the model constructed in this paper.Thirdly,select a city to conduct simulation analysis on the shared electric vehicle battery delivery path optimization model that considers the entire process of charging and swapping constructed in this paper.By collecting the relevant data of shared electric vehicles in a city,this paper uses the model constructed in this paper to determine the dual-objective path optimization scheme to minimize total operating costs and maximize user satisfaction,and carries out the sensitivity analysis of the model around the influence of the maximum number of mobile battery loads,the number of chargers at centralized charging stations,the driving speed and the linear weighting method weight on the solution results,and the simulation results effectively verify the rationality and feasibility of the model constructed in this paper.It can provide auxiliary decision support for battery path optimization in battery swap mode of shared electric vehicle operators.