Research On Intelligent Monitoring Technology Of State Of Charge Of Energy Storage Battery For Echelon Utilization

In order to cope with the challenges of energy and environment to the survival and development of modern human society,it has become a mainstream trend to promote new energy vehicles mainly composed of electric vehicles under the background of "dual carbon".The rapid increase of the number of electric vehicles also means a huge pressure to deal with the large-scale retirement of power batteries in the future,so the reuse of retired power batteries has become a hot issue of social concern.Echelon utilization is to apply the retired power batteries,which have been reevaluated,sorted and recombined,to relatively mild operating conditions,so as to maximize the residual value and enhance the life cycle value of the power batteries.However,compared with new power batteries,echelon utilization batteries have the characteristics of "congenital inconsistent production and large difference in postnatal recombination",performance aging and secondary recombination of echelon utilization batteries increase the uncertainty and instability of the overall operation.Accurate state-of-charge(SOC)estimation is the key of battery management system,and it is the precondition of energy management,balance control and safety management.Through the analysis of domestic and foreign research status quo,There are strong inconsistency of SOC and capacity of retired power batteries,it brings great challenges to SOC estimation,which is mainly reflected in the following two aspects:(1)echelon utilization of SOC information at cell level in a battery pack is the basis of equilibrium control and safety management,however,the strong inconsistency in modules will lead to difficulty in the estimation results converging to the true values,resulting in large estimation errors,and the state information at cell level can not be accurately and efficiently described.The battery cell model has poor operating condition adaptability,which leads to low estimation accuracy of the SOC of the echelon utilization battery group,the calculation amount is doubled after the group is connected in series,which cannot give consideration to both high accuracy and low complexity,and is difficult to meet the practical application.In this paper,we focus on the SOC estimation of echelon utilization of batteries.In order to overcome the above shortcomings,a representative-difference model is proposed,which can not only estimate the state information of the cells in the module,but also calculate the SOC of echelon utilization of batteries quickly and efficiently.The intelligent monitoring system of SOC for echelon utilization of batteries is designed and implemented.The main research contents of this paper are as follows:1)Aiming at the problem that the strong inconsistency in the battery will make it difficult to converge to the true values and can not describe the state information of the individual layer accurately and efficiently,the representative-difference model for estimating the SOC of the echelon utilization is put forward considering the distribution of the capacity and SOC of the retired power battery.Firstly,based on the Thevenin model and the idea of time scale separation,the SOC of the representative cell is estimated by the adaptive extended Kalman filter on the microscopic time scale;on the macroscopic time scale,non-representative cells select representative cells with similar characteristics in the pack as reference,and then combine the difference model to accurately estimate the SOC;and the charge transfer quantity is used as the time scale of capacity update,the lowest available cell is determined by combining the change rate of SOC and the estimated capacity of the representative cell,which solves the problem that it is difficult to determine the lowest available cell and its capacity on line in the echelon utilization battery.Finally,the simulation results show that the method can converge to the true value rapidly and the root mean square error of the estimated SOC is less than 3% for all the cells in the case of large discrepancy between the initial SOC and the capacity.According to the accurate SOC estimation at the cell level,the lowest capacity cell in the group can be located accurately,and the online capacity estimation can be realized.2)Since the calculation amount multiplies after series grouping,and the calculation resource of the embedded micro-controller is limited,in order to estimate the SOC of the battery accurately and efficiently with low calculation cost,in combination with the grouping characteristic of the series battery whose estimation accuracy is mainly affected by the power battery single unit with large inconsistency in the group,the representative single unit is used to represent the whole performance of the echelon utilization series battery,and on the basis of the theory of SOC estimation of the battery of echelon utilization,the software and hardware system of the SOC intelligent monitoring of the battery of echelon utilization is designed,the parameters such as single unit voltage,group terminal voltage,current and temperature are accurately collected,the charging and discharging experiment platform based on the echelon utilization of the lithium iron phosphate battery is established,and the related test and verification work of the SOC intelligent monitoring system is completed.The simulation results show that the estimation error of SOC is less than 5%,which is one order of magnitude shorter than the single cell model.