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Simulation Of Thermal Characteristics Of Lithium Ion Battery And Optimization Design Of Liquid Cooling System

Posted on:2022-12-24Degree:MasterType:Thesis
Country:ChinaCandidate:C Y LiFull Text:PDF
GTID:2492306761497854Subject:Automation Technology
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Aiming at the sustainable development goal of "carbon peak and carbon neutral" proposed by China,thermal management technology of power battery,as an important technical means to promote the vigorous development of new energy vehicle industry,has attracted more and more attention from many scholars at home and abroad.Although researchers have carried out relevant studies on technical feasibility,single heat management technology is still in the stage of theoretical research.The main bottleneck restricting its wide application is that the maximum temperature range of battery pack is difficult to control,and the temperature difference between batteries is uneven,which makes it difficult to ensure the safe and reliable operation of batteries.Aiming at the above problems,this paper designed a battery thermal management system,which can ensure that the battery pack can work in a good environment,which has a certain reference significance for the further research and practical application of electric vehicle power battery thermal management technology.In this paper,a single battery model was established,and the basic heat generation characteristics of the battery were obtained by analyzing the voltage characteristics and temperature characteristics of the single battery,and the accuracy of the model was verified by comparing the experimental data.On this basis,a battery pack model with eight single batteries in parallel was created.The battery pack model was analyzed by single factor analysis.The influences of the number of cold plate,the thickness of cold plate and the inlet direction of micro channel on the maximum temperature and temperature difference of the battery module were analyzed under constant discharge rate.Choose the microchannel width,cold plate thickness and the coolant inlet velocity as test factors,using the orthogonal experiment method,comprehensive analysis of factors on the battery level,the influence of the maximum temperature and maximum temperature difference makes the battery heat dissipation performance are obtained the optimal level of the best combination,namely when choosing the level 4 test factors,the highest temperature can be below 299.55 K,The maximum temperature difference between batteries is reduced to 1.37 K.In order to more comprehensively analyze the influence of test factors on the maximum temperature,maximum temperature difference and pressure drop of battery pack,the thickness of cold plate,the width of microchannel and the flow rate of coolant inlet were selected as optimization variables,and the maximum temperature,maximum temperature difference and pressure drop were selected as optimization objectives.Under the same boundary conditions,the sampling data of the optimization variables were numerically calculated in the multi-physical field simulation software COMSOL,and the mathematical expressions between the optimization variables and the optimization objectives were constructed by response surface method based on the sampling data and the calculation results,and the high-quality proxy model was fitted.Then,differential evolution algorithm was used to transform multi-objective optimization into single-objective optimization for further analysis of the agent model.Finally,36 groups of optimal solution sets were obtained by weight coefficient method,in which the minimum maximum temperature of the battery pack was 299.197 K,and the minimum maximum temperature difference of the battery pack was 1.127 K.The multi-objective analysis method makes the research more consistent with the actual situation,and the decision maker can choose different working conditions for deployment according to the actual demand,so that the battery pack can achieve better working effect.
Keywords/Search Tags:Battery thermal management, Liquid cooling heat dissipation, Numerical simulation, Differential evolution algorithm, Multi-objective optimization
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