Capacity Estimation of lithium battery based on charging data and Long Short-term Memory Recurrent Neural Network

Battery management system (BMS) plays an important role in ensuring the safe and stable operation of batteries. In BMS, the State of Health (SOH) status as a measure of the battery storage and release of the ability to change, in essence reflects the aging and damage of batteries. However, in actual operation, the capacity of the battery is difficult to measure directly. This paper presents a method, the voltage, current and temperature data extracted from the charging and discharging process of the battery are directly used as Health Factors(HF), which are divided into training set verification set and test set. The battery capacity estimation model is established based on the Long Short-term Memory Recurrent Neural Network (LSTM, RNN) to estimate SOH.