Joint Estimation Of SOC And SOP For Aging Lithium-ion Batteries Based On Migration Model

Lithium-ion batteries,as the electrical energy storage equipment and power source for electric vehicles,It is an important foundation to ensure the safe and efficient driving of electric vehicles.Therefore,it is a very important task to perfect manage lithium-ion batteries.Among them,the state of charge(State of Charge,SOC)and the state of power(State of Power,SOP)are important parameters necessary for the battery management process,it is related to the distribution of electric vehicle electricity and energy.However,due to the fact that the battery is easily affected by aging during actual use,the capacity decline and the non-linear change of battery parameters will eventually lead to the reduction of the estimation accuracy of the traditional battery SOC and SOP algorithm.Therefore,this paper takes the automotive ternary lithium-ion battery as the research Object,carried out research on the joint estimation method of SOC and SOP of aging lithium-ion battery,mainly completed the following work:(1)Establishment of battery migration model.First,the concept of migration model and common battery models are analyzed,and the second-order RC equivalent circuit model is selected as the initial model of the battery migration model.Secondly,under the Hybrid Pulse Power Characterization(HPPC)experimental conditions of the initial battery state,the adaptive forgetting factor recursive Least Square(AFFRLS)algorithm is used to identify the parameters of the initial model.Then the polynomial fitting method is used to extract the relationship curve between SOC and model parameters,and finally the establishment of the battery migration model is completed according to the extracted relationship curve.(2)Aiming at the nonlinear non-Gaussian nature of the battery migration model,a Risk Sensitive Particle Filter(RSPF)algorithm is proposed to determine the migration factor of the migration model online,thereby realizing the online migration process of the battery migration model.At the same time,in order to realize the accurate estimation of the SOC of the battery migration model,this paper inputs the initial SOC estimation value of the battery output by the migration model into the Savitzky-Golay Filter(S-GF)for denoising processing,and The battery migration model and SOC estimation results were verified by using the urban road cycle test(Urban Dynamometer Driving Schedule,UDDS)and dynamic test conditions(Dynamic Stress Test,DST)in the initial state of the battery.(3)Aiming at the common aging effect during battery usage,an algorithm for joint estimation of SOC and SOP of aging lithium-ion battery is proposed.The algorithm combines the battery migration model with the battery capacity reverse estimation method and the SOP estimation method based on multiple constraints to realize the joint estimation of the SOC and SOP of lithium-ion batteries under different aging states.By using four groups of different aging states The experimental data of UDDS operating conditions verify it,and the verification results show that the joint estimation algorithm of SOC and SOP of aging lithium-ion battery proposed in this paper has good estimation accuracy.