Research On Estimation Method Of Remaining Range Of Electric Vehicle Based On Condition Prediction

The increasing number of cars has brought great challenges to the environment and energy.Electric vehicles have become a good solution to the problems due to their advantages of non-polluting,high efficiency,and wide energy sources.However,electric vehicle owners generally have "range anxiety" for pure electric vehicles,and the currently generally inaccurate remaining range estimation will exacerbate the "range anxiety" of car owners.Therefore,it is necessary to develop a method that can accurately predict the remaining cruising range of electric vehicles and alleviate the "range anxiety" of drivers,which can contribute to the popularization of electric vehicles,thereby alleviating the severe challenges faced by the environment and energy.The estimation of the remaining cruising range of electric vehicles is mainly divided into two major aspects,one is the estimation of the remaining energy of the electric vehicle,and the other is the estimation of the future energy consumption of the electric vehicle.Combined with some existing research,this paper develops a method for estimating the remaining cruising range of pure electric vehicles based on working condition prediction,and analyzes and verifies it.The main research contents of this paper are as follows:(1)Complete the modeling of the battery equivalent circuit model considering the timevarying temperature.When estimating the remaining cruising range,it is first necessary to estimate the remaining energy of the current battery pack.In order to ensure the estimation accuracy of the remaining energy,it is first necessary to ensure that the external characteristics of the power battery can be accurately described.After comparison,this paper finally chooses to use the second-order RC equivalent circuit model to describe the external characteristics of the power battery.At the same time,considering that the battery model parameters will change under different temperatures,discharge rates and SOC,firstly,the charge and discharge experiments under different states are designed to obtain the external characteristics of the power battery under different states,and then the genetic algorithm is used to analyze the characteristics of the battery under different states.The model parameters are identified,and finally the second-order RC equivalent circuit model of the power battery is built in MATLAB/Simulink to verify the accuracy of the battery model and parameter identification under different working conditions.(2)Complete the construction of the battery pack temperature field model.One of the main inputs of the built second-order RC equivalent circuit model is temperature,that is,the temperature will have an impact on the external characteristics of the battery.Therefore,we need to know the temperature of the power battery pack.In the real vehicle,the temperature of the battery is collected through the temperature sensor.This paper calculates the temperature of the battery pack by building a temperature field model of the battery pack.Firstly,the establishment of the thermoelectric coupling model of the power battery cell is introduced in detail;then the establishment of the temperature field distribution model of the battery pack is completed based on the heat transfer theory;after the simulation results of the temperature field distribution of the battery pack are obtained,it is necessary to determine whether the results are accurate or not.The analysis is limited by the experimental conditions,and considering that CFD simulation is a relatively accurate temperature field simulation method recognized by the industry,finally,based on the STARCCM+CFD simulation software,the simulation results of the established battery pack temperature field distribution model are compared and analyzed.(3)Complete the research on the estimation method of the remaining energy of the battery pack considering the temperature distribution.The remaining energy of an electric vehicle is the energy that can be released from the battery pack from the current moment until the electric vehicle runs out of energy and cannot run normally.It can be seen from the definition that the remaining energy of electric vehicles is mainly related to SOC and voltage,so the estimation of the remaining energy of the battery pack can be attributed to the SOC estimation problem.In this paper,the EKF is used to estimate the battery SOC.Due to the uneven temperature distribution of the battery pack,the external characteristics of each single battery will be different,so the SOC estimation results of each single battery will also be different.This paper estimates the SOC of each single battery,Taking into account the protection of battery over-discharge,the minimum value of the SOC of all single cells is taken as the estimated value of the SOC of the battery pack.After the battery pack SOC estimation result is obtained,a residual energy prediction method based on SOC estimation is developed,and simulation analysis is performed.(4)Complete the research on the future energy consumption prediction method of pure electric vehicles based on vehicle speed prediction.First,a real vehicle data collection platform was built to collect the working condition data of a certain pure electric vehicle in Chongqing for 3000 s.Then,60 s is used as the working condition segment division unit,and combined with the NEDC and WLTC standard working conditions,it is divided into a total of 100 working condition segments.The next step is to select the appropriate feature parameters,and extract the feature parameters in the working condition segments,and divide them into four typical working conditions in the offline state based on the bipartite K-means clustering algorithm.Then,the current cycle operating conditions are identified online,combined with the current cycle speed,based on the NAR neural network to predict the next cycle speed.Calculation method for future energy consumption of electric vehicles.(5)Development of an estimation model for the remaining cruising range of pure electric vehicles.This chapter develops the remaining cruising range estimation model.First,a complete vehicle model of pure electric vehicle is built,including the vehicle dynamics model,motor model,and battery model.The predicted time and speed curve results in Chapter 5 are input into the vehicle model to obtain the demand.Current,used to calculate the change in remaining energy.Then,an evaluation method for the estimation accuracy of the remaining cruising range of electric vehicles is proposed.The next step is to develop the remaining cruising range estimation model.The idea of the development of the remaining cruising range estimation model is as follows: Calculate the energy consumption of the vehicle in the next cycle through the result of the speed prediction,and at the same time substitute the predicted speed curve into the vehicle model.,the predicted operating condition current can be obtained,the vehicle speed curve predicted in the next cycle can be integrated to obtain the driving distance,and the average energy consumption per kilometer of the vehicle can be obtained by combining the driving distance and driving energy consumption,and then combined with the calculation result of the remaining energy,you can get the remaining cruising range.Finally,based on the evaluation method of the estimation accuracy of the remaining cruising range,the simulation results of the estimation of the remaining cruising range are analyzed.