Evolution of Battery Parameters, State of Charge, and State of Health in Aging Lithium Batteries Using a PSO Algorithm at High Temperature

To encourage a wild spread of EVs, accurate SoC and SoH estimation under thermally accelerated aging is critical for advanced BMS systems. This study presents a lifelong degradation analysis of LiBs cells over a 7700 cycle at 40 °C. An adaptive third-order ECM, coupled with a hybrid polynomial–logarithmic OCV formulation, is continuously identified via PSO. The experimental data reveals a distinct degradation profile where the cell crosses the 80% SoH EoL threshold at cycle 5500, steadily declining to a terminal state of 75.7% SoH. Continuous parameter tracking isolates key electrochemical transitions: an initial kinetic stabilization phase is followed by a synchronized thermodynamic OCV realignment near cycle 2000, consistent with increasing LLI. Mid-life aging features a pronounced increase in the time constants, while a late-life degradation is characterized by increasing transport limitations, reflected in the evolution of the slow diffusion-related model parameters, inducing parameter boundary clipping in the slow diffusion branch. Despite these physical non-linearities, the proposed framework maintains high global fidelity throughout the 7700-cycle lifespan, strictly bounding the SoC RMSE below 2.5%, keeping Voltage RMSE under 35 mV, and preserving an R2 above 0.970. Comparative evaluations indicate that the proposed framework achieves a favorable balance between computational efficiency, tracking accuracy, and long-term diagnostic stability.