Since the SOC of lithium­ion battery packs is related to many factors (such as temperature, polarization effect, battery life, etc.) and has strong nonlinearity, to improve the accuracy of SOC estimation, it is necessary to improve the measurement method, battery model and estimation algorithm. In­depth research on etc. The methods commonly used at home and abroad are: discharge test method, ampere­hour method, open circuit voltage method, internal resistance method, Kalman filter method, linear model method and neural network method.
At present, there are many methods for SOC estimation, but each estimation method has some defects.
1) The discharge test method requires that the lithium iron phosphate battery pack is in a constant current discharge state, and it takes a lot of measurement time;
Method for SOC estimation of lithium iron phosphate battery pack
Since the SOC of lithium­ion battery packs is related to many factors (such as temperature, polarization effect, battery life, etc.) and has strong nonlinearity, to improve the accuracy of SOC estimation, it is necessary to improve the measurement method, battery model and estimation algorithm. In­depth research on etc. The methods commonly used at home and abroad are: discharge test method, ampere­hour method, open circuit voltage method, internal resistance method, Kalman filter method, linear model method and neural network method.
At present, there are many methods for SOC estimation, but each estimation method has some defects. 
1) The discharge test method requires that the lithium iron phosphate battery pack is in a constant current discharge state, and it takes a lot of measurement time;
Low temperature lithium iron phosphate battery 3.2V 20A
Low temperature lithium iron phosphate battery 3.2V 20A
­20℃ charge, ­40℃ 3C discharge capacity≥70%
Charging temperature: ­20~45℃
­Discharge temperature: ­40~+55℃
­40℃ support maximum discharge rate: 3C
­40℃ 3C discharge capacity retention rate≥70%
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2) The ampere­hour method is easily affected by the current measurement accuracy, and the accuracy is very poor in the case of high temperature or severe current fluctuation;
3) When the open­circuit voltage method is used to estimate the battery SOC, the lithium iron phosphate battery must be left standing for a long time to reach a stable state, and it is only suitable for SOC estimation under the non­dramatic change of battery current, and cannot meet the requirements of online detection; 
4) The internal resistance method needs to accurately measure the internal resistance of the battery. Generally, the internal resistance of the battery is in the milliohm level, which requires very high measuring instruments and is difficult to apply in practice;
5) The Kalman filter method is currently a more widely used estimation method. It has a strong dependence on the battery model. To obtain an accurate SOC, a relatively accurate battery model must be established, and the accuracy and complexity of the battery model are proportional;
6) Linear models are roughly divided into equivalent circuit models and simplified electrochemical models. The equivalent circuit model mostly adopts the simpler Thevein model, and if a more complex circuit model is used, the identification of the model parameters and the establishment of the state equation will be a great challenge. Due to the simplification of the model, it cannot fully reflect the internal laws of the battery, which will cause a large estimation error.