Research On State Monitoring And Optimization Method For Lithium-ion Battery Packs

Limited to the voltage and capacity of a single lithium ion battery,the energy storage system allways consist of cells in series or in parallel.Due to the inconsistency of the manufacturing process and the using condition,there is always variation among the cells.After the cells are grouped,the key properties such as energy density,durability and safety of the battery pack will decrease due to inconsistencies among the cells.This paper focuses on the lithium ion battery pack,we optimize the grouping method when the cells are grouped to obtain larger available capacity,then estimate the initial capacity and monitor the state of health of the battery pack on-line after grouping.We also present a charging optimization method,aiming to decrease the heat releasing during charging and to improve the cycle life of the battery pack.Based on the study of the inconsistency of the lithium-ion battery cell,the initial discharge capacity of the parallel lithium-ion battery pack is estimated.With the information of performance parameters of the in-pack cells,we propose a method to estimate the initial discharge capacity of parallel connected cells based on discharge current prediction of in-pack cells.Then we propose a method to estimate SOH(State of Health)of the lithium-ion battery pack consist of cells connected in parallel on-line.After introduction of incremental capacity analysis method for on-line SOH estimation of single cells,we present the method used in parallel connected batteries.The result indicates that the method is precise even if the variation of in-pack cells is obvious.After that,based on consideration of inconsistency of the lithium-ion battery capacity and the internal resistance,the optimization method for grouping based on Simulated Annealing Algorithms is presented.This paper analyzes the impact of cell inconsistency on the capacity of the battery pack,build a grouping optimization model of the lithium-ion battery pack,and use Simulated Annealing Algorithms to solve this optimization problem.We analyze the practicability of the method by different simulation experiments.Finally,the method is validated by the real experiment.The experimental results show that the optimization algorithm can effectively improve the capacity of the lithium-ion battery pack.Finally,the optimization method of lithium-ion battery charging based on dynamic current curve is studied.On the basis of known SOH and SOC(State of Charge),an optimized dynamic charging current curve can be obtained.The use of the dynamic current curve of the battery charging can effectively reduce the heat of the lithium-ion battery pack in the process of charging.To a certain extent,the optimized charging method may enhance the cycle life of lithium-ion battery.At the end of this chapter,a serie of simulation examples illustrate the application process and optimization results of the method.