Beyond Classical HPPC: A Novel Two-Component Parameter Identification Method for LFP Cell Equivalent Circuit

Accurate identification of equivalent circuit model parameters of lithium-ion cells is essential for reliable prediction of voltage fluctuation dynamics in traction and stationary energy storage applications. This paper presents a novel parameter identification approach for a Thévenin equivalent circuit-based model (ECM) of an LFP (LiFePO4) battery cell using results of the Hybrid Pulse Power Characterization (HPPC) test. A major limitation of the classical HPPC-based method arises from the mismatch between the short duration of test current pulses and the long time constants characteristic of LFP cells, which significantly reduces identification accuracy. While increasing pulse duration could improve identification, it tends to affect the cell’s state of charge and thermal equilibrium. To overcome this problem, a two-component identification method is proposed that simultaneously exploits the voltage response during the current pulse and the voltage relaxation transient, recorded after pulse termination. Parameter identification is performed using a particle swarm optimization (PSO) algorithm for equivalent circuits with two and three RC pairs. The proposed approach is experimentally validated using a Winston Thundersky LFP040AHA cell. The obtained cell equivalent circuits are verified under a Charge-Depleting Cycle (CDC) test by comparing measured and simulated voltage responses. The proposed two-component approach provides an effective and practical solution for high-fidelity modeling of LFP cells, supporting model-based design, simulation of battery-powered systems, and testing and validation of BMS.