| Global energy problem and environment problem increasingly serious,the clean energy of electric vehicles is widely popular with the masses,is often accompanied by large current in the operation of electric vehicles,battery will produce large amounts of heat,then cause the battery temperature rise sharply,and lithium ion battery is very sensitive to temperature,should guarantee the battery temperature all the time stay in 20 to 45 ℃,high and low temperature will be serious influence on the battery,serious and even explosion happens when the thermal runaway.So you need a complete thermal management to control the battery temperature and battery thermal management research adopts the method of finite element,this kind of modeling method can not achieve real-time control algorithm,so the need for a precise control can be used in battery thermal management develop these models,this model can effectively shorten the development cycle thermal management,save time cost,based on this the paper puts forward a MATLAB/Simulink to use the life of the battery cooling characteristics of thermal model,and design the temperature control algorithm is set up by simulating the thermal model,to sum up,in this paper,the research content as follows:(1)This paper is based on the study of the battery thermal model.The accuracy of the external battery characteristic model should be guaranteed first,and then the accuracy of the established thermal model should be guaranteed.Therefore,the time-varying and nonlinearity of the battery model parameters should be taken into account.In this chapter,after comparing a variety of equivalent circuit models,the second-order RC model was finally selected to design experiments to obtain the rebound data at different rates,SOC and temperatures,and the ant colony algorithm was used to identify the model parameters.The equivalent circuit model was built in Matlab /Simulink,and the simulation value and test value of voltage were compared under different working conditions to verify the accuracy of ACO for power battery parameter identification and equivalent circuit model.(2)According to the analysis of the heat generation characteristics of the battery,the establishment of the battery heat generation model was completed,and the main influencing factors in the heat generation model were analyzed.In order to get the accurate heat generation,the internal resistance of the main source of heat was considered as the parameters of different rates,temperature and SOC changes.Then analyze the heat dissipation characteristics,determine the heat dissipation method and structure,and deduct and analyze the heat transfer coefficient which has the largest impact on the heat dissipation,and establish the heat dissipation model of the battery,which is composed of the thermal model of the battery.The heat generation of the battery is calculated by the established second-order RC model and transferred to the thermal model.The thermal model calculates the temperature of the battery and then transfers it back to the second-order RC model to find and calculate the parameters needed for the heat generation.The above process is the coupling process of the equivalent circuit model and the thermal model,also known as the thermoelectric coupling model of the single cell.Then the thermoelectric coupling model of the battery pack is established by analyzing the heat transfer between the battery cores.(3)The CFD(Computational Fluid Dynamics)model was established in STAR-CCM+.Firstly,the test and thermal simulation of the single cell and the test and thermal simulation of the battery module under natural cooling were used to verify whether the CFD model established in STAR-CCM+ can truly simulate the temperature change of the battery.Then,the model established in STAR-CCM+ and the battery pack thermoelectric coupling model built in Matlab/Simulink were compared under different working conditions to verify whether the battery pack thermoelectric coupling model built in Simulink can replace the thermal model built in CFD.(4)Finally,according to the characteristics of the battery pack thermoelectric coupling model is set up by,choose the model predictive control algorithm to control the battery temperature,while the previous model predictive control for battery temperature regulation is often only for a controlled variable(the temperature of the cooling fluid or coolant flow),can lead to extreme conditions control volume no matter how to change the battery temperature is more than appropriate temperature;Or due to the single variable,the adjustment rate is obviously insufficient,and the battery temperature is slow to reach the target temperature,which is not conducive to the normal operation of the battery pack.To solve the above problems,a model predictive control was proposed to adjust the temperature and flow rate of the bivariate coolant simultaneously.Firstly,the reliability and excellence of the model predictive control are proved by comparing the effects of PID control and univariate model predictive control.Then,the performance of univariate model predictive control and bivariate model predictive control in extreme working conditions is compared.The simulation results show that the bivariate model predictive control can adapt to various operating conditions,including some extreme operating conditions and high rate discharge operating conditions,and the battery module can be maintained within the target temperature.It also shows that the thermal model established can be simulated in real time with the temperature control algorithm,which can effectively shorten the development cycle of thermal management. |
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