A novel SOC-OCV separation and extraction technology suitable for online joint estimation of SOC and SOH in lithium-ion batteries

To accurately estimate the state of charge(SOC) and state of health(SOH) of lithium-ion batteries under varying operating conditions and temperatures using the equivalent circuit model(ECM), it is crucial to obtain precise open-circuit voltage(OCV) data. To address this challenge, this paper proposes a novel SOC-OCV decoupling extraction technique suitable for the online joint estimation of SOC and SOH in lithium-ion batteries. First, the variational mode decomposition method is used to decompose the measured voltage, obtaining the OCV curve. Next, the parameters of the ECM, including R0, Rp and Cp, are identified online through an edge-computing-based parameter identification process. These parameters, combined with the OCV curve, are then used to construct a terminal voltage curve under real experimental operating conditions. Finally, online SOC estimation is conducted, with the useable capacity calculated using the coulomb counting method, and SOH is updated accordingly. Experimental validation shows that the proposed method achieves a maximum SOC estimation error of 0.95 %, an RMSE below 1 %, and an SOH absolute error of 0.86 % for ternary lithium batteries.