A Fast Activation Energy Derivation (FAED) approach for Lumped Single Particle model in lithium-ion battery module-level heat generation prediction

Abstract

The performance of electric vehicles (EVs) heavily relies on the durability and longevity of lithium-ion cells, which are strongly affected by operating temperatures. Various electrochemical models have been developed to investigate the impact of operating temperature on the dynamic heat generation at cell level. Among these, the Lumped Single Particle (LSP) model stands out due to its lower computational cost and higher accuracy under >1C-rates. However, key electrochemical parameters (i.e. the ohmic overpotential, exchange current, and diffusion time constant) in the LSP model are temperature-sensitive, requiring Arrhenius dependencies. Conventional activation energy measuring approaches, relying on testing under discrete fixed temperatures to obtain activation energies, are time-consuming. To address this, this paper proposes a FAED approach that fits the temperature-sensitive parameters and corresponding activation energies to experimental data with a single discharge process, reducing the testing time to a minimum of one hour. This approach was experimentally validated on a Tesla battery module (74P6S), demonstrating a good agreement between simulation and experimental results up to 1.5 C-rates, ranging from 16 ℃ to 46 ℃. Furthermore, this approach is suitable for cells with different lithium chemistries, formats, and properties, making it an effective method for thermal analysis of EV packs.