Research On SOC Estimation And Balance Control Strategy Of Energy Storage Lithium Battery Pack

With the positive response from countries around the world to protect the environment,save energy and reduce emissions,new energy technologies such as wind power and solar power have been continuously developed and applied.However,renewable energy sources such as wind power are intermittent and fluctuating,affecting the stability of the power system.To improve the stability of the power system,it is necessary to strengthen the research on energy storage technology.Connecting the energy storage power station in the power system can effectively improve the reliability and stability of the system.In recent years,energy storage technology,especially battery energy storage technology,has developed rapidly.Large-scale battery energy storage system has the advantages of large capacity,flexible configuration,environmental protection and so on,which plays the role of absorbing new energy power generation and cutting peak and filling valley.The battery management system(BMS)is a "safety steward" for the normal and stable operation of energy storage power stations,which can monitor the energy storage battery in real time,warn the safety,manage the energy and balance the electric quantity.State of charge(SOC)is one of the most important state of battery.Estimating SOC is the premise of BMS operation and the basis of other battery management algorithms.The single battery has a low voltage level and small capacity.To meet the demand of high-voltage and high-power of energy storage system,the battery cells need to be connected in series and in parallel to form a battery pack.In the process of using the battery pack,there will be inconsistencies,which will reduce the available capacity and cycle life of the battery pack,and lead to fire accidents caused by overcharge and overdischarge of the battery.Battery balancing technology is an effective way to solve this problem.In this context,this paper focuses on the two key technologies of SOC estimation and active equalization in energy storage BMS.This article takes lithium iron phosphate battery as the research object.First,the working principle of lithium-ion battery is analyzed.The charge and discharge experiments of lithium-ion battery are carried out on the built battery test platform.The analysis and arrangement of the experimental data are completed.The relationship between SOC and temperature,charge and discharge ratio and other factors are obtained,which provides the basis for the later SOC estimation.Second,the battery SOC estimation model based on Extreme Learning Machine(ELM)is established,and the charge and discharge experiments of lithium battery at different temperatures are designed.The experimental data is extracted to train the model,and the simulation is carried out.The results show that the model can effectively reduce the estimation accuracy,and the estimation error is within 2%.Then,the cause of the inconsistency of the battery pack is analyzed,and the battery SOC is selected as the equilibrium variable.The multilevel balancing between battery modules and within the battery module is explained,and the structure of the battery balancing system in the module is designed.The bidirectional forward converter is used as the energy transfer circuit topology,combined with the gating effect of the switch matrix,to achieve the energy transfer between the single cell and the battery pack.A fuzzy controller is designed to control the equalization current,and a battery pack equalization control strategy based on cluster analysis is proposed.Through the equalization experiment on 18650 battery pack,the equilibrium control strategy proposed in this paper is verified.Finally,the circuit principle of the main modules of the battery equalization system is analyzed,and the software control process is introduced.On this basis,the experiment is designed to test the equalization system and verify the scheme.