Research On Charging Optimization Control Strategy Based On Aging Characteristic Parameters Of Lithium-Ion Batteries

The development of industrial society has accelerated the deterioration of the environment while consuming non-renewable energy.Finding clean and efficient renewable energy is an important means to alleviate the energy crisis and improve environmental problems.Lithiumion batteries are widely used in the fields of electric vehicles,power storage and mobile electronic devices due to their high energy density,low self-discharge rate,no memory effect and no pollution.Charging state is the most common mode of battery operation.In order to pursue better charging experience,it is often expected to increase the charging power to shorten the charging time.Lithium-ion batteries generate heat under the action of charging current,and the selection of charging current is restricted by both heating and charging speed.In addition,the aging process is accompanied by the use of batteries.The use of the equivalent constant current charging for both aged and new batteries cannot fully consider the temperature changes caused by the variation of internal resistance and capacity of aged batteries,and the temperature changes directly affect the battery aging and performance.Therefore,it is necessary to adjust the charging strategy according to different aging states during the battery usage,which can not only effectively improve the charging efficiency but also ensure the charging safety.This dissertation proposes a charging optimization strategy suitable for the lithium nickelemanganese-cobalt oxide(Li NMC)battery with different aging states.The main contents include:Firstly,the mechanism of battery aging was investigated to solve the problem of battery performance degradation after aging.The battery was aged under constant temperature and constant current conditions.Through capacity test and Hybrid Pulse Power Characteristic(HPPC)test,the capacity,open circuit voltage,internal resistance and other parameters of the battery under different aging states were obtained,and the variation law of battery parameters with aging was studied.Incremental Capacity Analysis(ICA)was utilized to analyze the change of Incremental Capacity(IC)peak,and the reasons for lithium-ion battery aging were analyzed from the mechanism.Secondly,aiming at the problem of battery temperature estimation during charging,the thermoelectric coupling model of battery is established based on the Thevenin equivalent circuit model and Bernardi heat generation model.The parameters required by the equivalent circuit model were obtained by HPPC experiment,and the thermophysiological parameters required by the heat generation model,such as the equivalent specific heat capacity and heat transfer coefficient,were obtained by pulse experiment.A simulation model was built on Simulink platform to simulate the battery charging process under constant temperature and current conditions.The accuracy of the model was verified by comparing the changes of the battery terminal voltage and temperature in the charging experiment under the constant current 1C at25℃.Finally,in view of the formulation of the optimization strategy of aging battery charging,combined with the battery aging experiment and HPPC experimental data,the principal component regression(PCR)method was used to establish the battery parameter estimation model,and the capacity and internal resistance of batteries with different aging states were estimated.Based on the estimation of the battery parameters,the five-stage constant current charging process was optimized by means of particle swarm optimization(PSO)method based on fuzzy reasoning,taking charging time and charging temperature rise as the optimization objectives.In order to verify the effectiveness of the proposed method,the optimized charging strategy and constant current-constant voltage(CC-CV)method were used to conduct the charging experiment for the batteries in different aging states,and the charging time and charging temperature rise of the two methods were compared.The results show that the charging strategy proposed in this paper can effectively reduce the charging time and charging temperature rise,and the optimization effect is gradually obvious as the aging degree increases.