High Precision State-of-Charge (SOC) Estimation of Lithium-ion Batteries Based on Adaptive Model of Noise Suppression

In estimation of state-of-charge (SOC) for lithium batteries, the accuracy of the noise initial value will affect the SOC estimation accuracy. Based on the multi-iterative extended Kalman filter algorithm (IEKF), the second-order resistor-capacitor (RC) model with high precision and moderate amount of calculation is selected as the lithium-ion battery model. The SOC estimation is further improved by the noise suppression in the battery model. Experiments show that the SOC estimation error is reduced by 2% compared with the no noise suppression, and the adaptive noise suppression of the battery equivalent model is achieved by using the IEKF algorithm with high estimation accuracy for the lithium-ion battery SOC estimation system.