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Research On Multi-stage Constant Current Charging Method Of Power Lithium Battery Based On Lowest Energy Loss

Posted on:2020-08-19Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y YangFull Text:PDF
GTID:2392330596474793Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
As the United Kingdom,France,Germany and other countries have clearly defined the time schedule for a total ban on fuel vehicles,the popularity of electric vehicles has become an inevitable trend in the development of the global automotive industry.China’s Ministry of Industry and Information Technology also launched a "double points" policy in 2018 to promote the rapid spread of electric vehicles.Lithium-ion battery has become the ideal power source for electric vehicles with its high specific energy and specific power.However,the problem of large energy loss and low charging capacity of the power battery during rapid charging has always restricted the further development of the electric vehicle.Therefore,to explore the charging characteristics of the power battery,research on optimized charging control technology,and achieve the improvement of the comprehensive performance of power batteries is an important technical path to solve the problem of popularization and promotion of electric vehicles in China.This article takes 26650 power lithium battery as the research object.The battery charging energy loss model is established based on the multi-stage constant current charging combining the lithium battery thevenin equivalent circuit model.A multi-stage constant current charging strategy with minimum charging energy loss under the premise of ensuring that the charging time is not extended and the charging capacity is not reduced is designed,to achieve the purpose of improving charging efficiency.The following research work is mainly done:Firstly,build a power lithium battery test system to provide reliable battery charging test data.The characteristics of the battery equivalent circuit model are analyzed,and the Thevenin model with moderate complexity and easy engineering implementation is selected.Identify the parameters in the model by mixing the pulse power characteristic test,verify the identification results under constant current discharge conditions.The experimental results show that the error of the output voltage of the model is kept within 0.03 V.The Thevenin model can accurately describe the external characteristics of the battery.Secondly,combining with the Thevenin model to analyze the multi-stage constant current charging process,it can be seen that the charging energy loss mainly comes from the consumption of resistive components in the model.Based on this,a mathematical model of charging energy loss is established to realize quantitative analysis of battery charging energy loss.And introduce the ampere-time integral formula with Coulomb efficiency coefficient in the model to eliminate the influence of different charging currents on SOC estimation and model parameters.Estimation of polarization voltage and Coulomb efficiency coefficient using constant current charging method with different charging rates,the correctness of the established charging energy loss model is verified by constant current charging experiments.Finally,combined with the charging energy loss model and the SOC as the scale,a segmented constant current charging strategy with the lowest energy loss is proposed.The design of the objective function and the constraint conditions is given in detail,and the objective function is solved by genetic algorithm.The charging experiments were carried out on the proposed strategy under different initial SOC,different charging rates and different battery aging degrees.The results show that compared with constant current charging with different magnifications,the proposed charging strategy can not only effectively reduce the battery charging energy loss but also shorten the charging time to some extent.
Keywords/Search Tags:Multi-stage constant current charging, Energy loss model, Coulomb efficiency coefficient, Genetic algorithm
PDF Full Text Request
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