SOC Estimation Based on Combination of Electrochemical and External Characteristics for Hybrid Lithium-Ion Capacitors

Abstract

Hybrid lithium-ion capacitors (HyLICs) have received considerable attention because of their ability to combine the advantages of high-energy lithium-ion batteries and high-power supercapacitors. State of charge (SOC) is the main factor affecting the practical application of HyLICs; therefore, it is essential to estimate the SOC accurately. In this paper, a partition SOC-estimation method that combines electrochemical and external characteristics is proposed. The discharge process of the HyLICs was divided into three phases based on test results of electrochemical characteristics. To improve the estimation accuracy and reduce the amount of calculation, the Extended Kalman Filter (EKF) method was applied for SOC estimation at the interval where the capacitor energy storage characteristics dominated, and the Ampere-hour (Ah) method was used to estimate the SOC at the interval where battery energy storage characteristics dominated. The proposed method is verified under different operating conditions. The experimental results show good agreement with the estimation results, which indicates that the proposed method can estimate the SOC of the HyLICs accurately.

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“…After developing the ECM of the proposed SLB, HPPC pulses are applied to the theoretical model as the input current, and the voltage response is compared to the experimental values obtained in the laboratory [97,98]. Following that, optimum values of the ECM parameters in various SOCs are identified using fitting algorithms such as the Levenberg-Marquardt [99,100], trust-region reflective [101,102], and genetic [103,104] algorithms to minimise the error between the voltage response obtained by the model and the experiments. The overall process of the ECM characterisation is presented in Figure 12.…”