Study On Lithium-ion Battery State Estimation And Control Optimization

With the rapid development of new energy,lithium-ion battery has been used widely and promote vigorously.However,in the use of lithium batteries,the battery over-charge and over-discharge will cause irreversible damage,and there is the risk of explosion at high temperature,as a result a BMS（Battery Management System）is needed to manage the batteries.The battery state estimation is the key technology and the battery control optimization is one research goals of BMS.Here,NCM(LiCo_xNi_yMn_1-x-y-x-y O₂)power battery is used as the research object and some necessary problems focus on modeling and estimation of battery SOC（State of Charge）,modeling and estimation of battery SOH（State of Health）,and optimized control battery pack will be studied deeply:Firstly,based on the study of the discharge characteristics of NCM battery,the traditional estimation algorithms of SOC are improved.A dual-power equivalent circuit model is established for the problem that the traditional equivalent circuit models neglect the effect of discharge rate on the discharge capacity of the battery.The dual-power model through the main and secondary power can simulate the battery characteristics,and reflect the internal changes in the battery state at the same time,to achieve the impact of the discharge rate on the battery SOC by distinguishing large and small discharge conditions to different model expressions.And the validity of the model and the accuracy of the SOC are verified through the experiments.Secondly,against the limitation for the aging mechanisms that need specific experiment or detected offline,a charge and discharge voltage recovery curve is proposed necessarily to identify the aging mechanism of battery.The aging mechanism is applied to the equivalent circuit model,and the capacity fade model is established.On the one hand,it can get the voltage recovery curve by the battery stop when charge and discharge,and the aging mechanism of the battery resistance,available lithium ion and active material are analyzed in detail;on the other hand,the capacity fade model determines the capacity degradation through the daily charging curve,and then predicts the battery SOH.Finally the accuracy of the model and the reliability of the predicted SOH is verified through the experiments.Finally,Aimed at the problem that the lithium battery has short life and low energy utilization and estimates the state of lithium batteries accurately,the discharge optimization and performance optimization are proposed,they lead to the maximum throughput and the minimum energy loss in the life cycle of the battery.Based on the impractical of the equalization control,the voltage prediction model which is not affected by the implicitness in battery difference and the discharge equilibrium strategy based on the difference interval are put forward,it ensures the accuracy and simplifies the complexity.For the complex and changing conditions,a double lithium battery system is presented,which reduces the damage to the battery caused by the large discharge current in the electric vehicle and switching charge and discharge frequently in the smart grid storage systems,and the experimental results show that the dual battery system is superior to the traditional single system.