Battery SOC estimation

Open circuit voltage (OCV), which is the terminal voltage of battery in open circuit state, is monotonous with SOC. If the data of open circuit voltage under different SOC are measured by experiment and the relationship curve between them is fitted, then the SOC of battery can be estimated according to the measured open circuit voltage.

This method has high estimation accuracy, but it also has obvious disadvantages. It needs to measure the open circuit voltage in the case of open circuit, and it needs to stand for a period of time to ensure the estimation accuracy. Therefore, its application scope is limited. Generally, the initial SOC value is estimated by this method before the vehicle starts (the battery has no charging and discharging current).

On the premise that the initial value of SOC is known, as long as the battery current can be measured (where the discharge current is positive), the change of battery power can be accurately calculated through current integration, and then the SOC of residual power can be obtained.

However, due to the measurement error of current sensor and the gradual decline of battery capacity, the long-time current integration will lead to a certain deviation. Therefore, it can be used for SOC estimation with low accuracy, and it can also be used for short-term SOC prediction with model-based method.

The most classic model-based method is to estimate SoC Based on equivalent circuit model and Kalman filter algorithm.

In this method, the prior estimation of SOC and the prediction of terminal voltage are carried out by using the established accurate model, and then gain correction is carried out according to the comparison between the actual measured value and the predicted value of terminal voltage, and the optimal estimation of SOC is realized by iterative optimization. Based on the accurate model, this method can achieve high-precision SOC estimation. Even if the initial SOC error is large, the SOC estimation value can converge quickly and has good robustness. It is the most mainstream method in engineering.