Study On Estimation Of State Of Charge Of Lithium-Ion Battery Packs In Echelon Utilization

Lithium-ion batteries have been applied to electric vehicles on a large scale due to their superior performance.However,the power battery needs to be decommissioned after a certain number of cycles and the rated capacity drops to 80% of the original value.How to tap and make full use of the remaining value of the battery not only has obvious economic value,but also has extremely important significance for saving resources and protecting the environment.In order to achieve efficient utilization of retired power lithium batteries,accurate estimation of the state of charge(SOC)of the battery pack is a key issue that must be solved.For this reason,the paper focuses on the echelon utilization of lithium-ion battery packs,and systematically studies the degradation mechanism of the battery,circuit characteristic modeling,parameter identification,and state-of-charge estimation methods.The main work and results are as follows:1.Starting from the working principle and performance parameters of lithium-ion batteries,the degradation mechanism of single lithium-ion batteries and battery packs,as well as the causes and effects of inconsistencies,are analyzed.On the basis of comprehensive lithium-ion battery appearance recognition,internal resistance test,capacity measurement and other methods,the lithium-ion power batteries retired from electric vehicles were quickly screened,and the single batteries that met the echelon utilization conditions were sorted into groups.,Which provides a reliable basis for subsequent battery modeling and SOC estimation;2.In view of the effects of aging on decommissioned batteries,traditional parameter identification methods are prone to parameter oversaturation and unable to track time-varying parameters.After analyzing and comparing the principles and advantages and disadvantages of different lithium-ion battery modeling methods,first-order RC is used The equivalent circuit model is used for modeling and parameter identification of cascaded lithium-ion batteries.Since the parameters to be identified have very strong nonlinear characteristics,on this basis,a variable forgetting factor least square method is proposed to accurately identify model parameters.The identification results show that the proposed method has improved the identification accuracy of the model parameters,and can realize the accurate identification of the model parameters of the battery equivalent circuit of the echelon utilization;3.In order to achieve accurate SOC estimation of battery packs for cascade utilization,the traditional Thevenin equivalent circuit model has been unable to meet the accuracy requirements for the estimation of SOC for cascade utilization battery packs with strong inconsistencies.In order to balance the calculation amount and estimation accuracy of the model,This paper proposes to use the CDM model that can characterize the inconsistency of terminal voltage and internal resistance for SOC estimation,and on this basis,proposes the AFUKF algorithm,which combines the time-varying adaptive fading factor into the predicted state covariance matrix to suppress the first The influence of empirical knowledge on the estimation of the current state can be used to reduce the error of the estimation and be able to track the change of the actual value.Finally,an experimental simulation platform is built in Matlab/Simulink through the method proposed above,and the retired batteries after screening are tested under different working conditions,and the test data results are configured with the input and output interfaces of the simulation model.The experimental results show that the proposed method It can effectively reduce the SOC estimation error of the lithium-ion battery pack in cascade utilization,reduce the difficulty of convergence of the estimation result due to the inconsistency between single cells,and improve the estimation accuracy.The proposed method can provide theoretical basis and engineering application guidance for the key technical problems faced in the process of cascade utilization.