Circuit modeling provides an efficient way to analyze early-stage faults in lithium-ion batteries by simulating key aging processes with a balance of detail and speed. Our research develops a coupled circuit model that captures two critical early degradation mechanisms: SEI growth via a 1RC equivalent circuit and metal dendrite growth via a transmission line circuit model.
By formulating both processes as functions of key electrochemical parameters, the model reproduces their distinct electrical effects on terminal voltage. Parameters are calibrated with a genetic algorithm and validated against experimental data, showing close alignment between simulation and measurement. This offers a computationally efficient basis for early fault prediction and future online diagnostics.
Publications:
[1] Ziqi Wang and Mo-Yuen Chow, “Battery Modeling of SEI and Metal Dendrite Growth: A Transmission Line Circuit Framework with Genetic Algorithm-Identified Parameters ,” 2025 IEEE 20th Conference on Industrial Electronics and Applications (ICIEA), Yantai, China, 2025, pp. 1-6, doi: 10.1109/ICIEA65512.2025.11149030.
[2] Ziqi Wang, Mo-Yuen Chow, Zhiping Tan and Huiqin Jin, “Modelling of the Solid Electrolyte Interface Growth Using Physics-Based Equivalent Circuit Model,” 2025 IEEE International Conference on Industrial Technology (ICIT), Wuhan, China, 2025, pp. 1-6, doi: 10.1109/ICIT63637.2025.10965250.
