State of charge estimation method based on linearization of voltage hysteresis curve

The lithium-ion battery equalization method with voltage equalization is relatively mature and convenient to implement. However, this equalization method may cause excessive energy consumption. The equalization method with state of charge (SOC) equalization can reduce this kind of energy consumption. To use the equalization method with SOC, we should estimate the SOC first. So this paper proposes a SOC estimation method based on linearization of voltage hysteresis curve (EMBL). This paper linearizes the voltage hysteresis curve of lithium-ion battery and proposes a novel equivalent model of lithium-ion battery based on linear neural network (LEM). The performance superiority of the LEM is verified through the intermittent charging and dis-charging experiments. Then the SOC estimation method based on linearization of voltage hysteresis curve is constructed. The equalization experiments with voltage equalization and SOC equalization are carried out respectively. And the results prove that the method with SOC equalization can significantly reduce energy consumption compared to the method with voltage equalization, and the EMBL based SOC equalization can slightly reduce energy consumption compared to the extended Kalman filter (EKF) algorithm based SOC equalization.

Automated summary

This paper proposes a SOC estimation method based on the linearization of voltage hysteresis curve (EMBL) and establishes a novel equivalent model of lithium-ion battery based on a linear neural network (LEM). The superior performance of the LEM is verified through intermittent charging and discharging experiments. Furthermore, this paper constructs a SOC estimation method based on the linearization of voltage hysteresis curve and carries out equalization experiments with voltage equalization and SOC equalization. The results demonstrate that SOC equalization can significantly reduce energy consumption compared to voltage equalization, and the EMBL-based SOC equalization slightly outperforms the extended Kalman filter (EKF) algorithm-based SOC equalization in terms of energy consumption reduction.