Research On SOE Estimation Algorithm For Energy Storage Lithium Iron Phosphate Battery Based On Characteristic Interval

Energy storage technology is very important for environmental protection and renewable energy development.Lithium iron phosphate battery has been paid more and more attention because of its technical performance advantages.With the rapid development,it has become one of the most ideal choice of energy storage devices in modern power system.In actual working conditions,state of energy(SOE)can directly reflect the battery energy availability and the ability at work,provide the basis for power dispatch scheduling,effectively prevent the battery overcharge and over discharge,improve the using efficiency of the battery,help improve the controllability,reliability and stability of the grid energy storage system.Being through the analysis of the lithium iron phosphate battery energy storage characteristic interval under the condition of application,a SOE estimation method based on the battery characteristic interval is proposed in this paper,which has a high estimation precision and provides a new idea for SOE estimation of lithium ion batteries.The algorithm also provides a theoretical support for the efficient and management of the storage battery.This paper makes an investigation and analysis of existing battery SOE algorithms at home and abroad.A new SOE estimation algorithm is proposed to accurately reflect the real energy state of lithium ion battery for energy storage.Lithium iron phosphate is the research object which is most commonly used in energy storage system.Firstly,it makes the analysis of technical characteristics of lithium iron phosphate battery.Then the paper extracts dV/dE differential curve of battery by charging and discharging the battery in particular temperature and specific conditions.Thirdly,according to the change characteristics of OCV-SOE,the working area of the battery is analyzed.The characteristic interval of lithium battery is divided and the range of SOE is estimated.Fourthly,combined with the traditional SOE integral algorithm,the SOE estimation algorithm based on the battery characteristic interval is proposed to estimate the battery SOE.Finally,based on the proposed algorithm,the lithium ion battery energy storage system(cell&3 parallel and 16 series)was used as the experimental object.In the laboratory,the characteristics of the battery in different magnification,temperature and operating conditions are tested.The proposed SOE algorithm is verified and the next research direction and improvement scheme are given.The OCV-SOE curves are different due to different batteries and different operating conditions,and the identification and voltage stability are different.In this paper,the recognition region and the voltage stability region are applied in the LiFeP4 battery to the discharge conditions at a rate of 0.2 constant current and of the temperature 20?.When the battery type,the operating temperature of the battery and the charging and discharging rate change,it is necessary to redemarcate the calibration range.