Fully coupled simplified electrochemical and thermal model for series-parallel configured battery pack. (April 2021)

• Record Type: Journal Article
• Authors: Gottapu, Manohar; Goh, Taedong; Kaushik, Anshul; Adiga, Shashishekar P.; Bharathraj, Sagar; Patil, Rajkumar S.; Kim, Daehyun; Ryu, Youngho
• Is Part Of: Journal of energy storage. Volume 36(2021)
• Publication Date: 2021-04
• Subjects: Electric vehicle -- Battery pack -- Battery management system -- Electrochemical modelling -- Thermal modelling -- State of charge; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2021.102424
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: Fully coupled electrochemical-thermal model. Series-parallel battery pack state estimation. Cell-to-cell estimations of temperature variations. Abstract: Battery packs are often designed with multiple battery cells configured in series and/or parallel combinations to meet the energy and/or power requirements of target applications. Modeling of these battery packs is very complex, computationally challenging and requires extending a single cell model to multi-cell models including electrical connections between cells. Also, the cell-to-cell variations of capacity, resistance, and temperature in the pack are vital in the battery pack design and battery management system development. Therefore, a robust modeling platform with in-built physics and fully coupled models both at the cell and the pack level is developed. The modeling framework consists of Simplified Electrochemical and lumped Thermal Model (SEM-T) at the cell level and Equivalent-Circuit Model (ECM) for Ohmic calculations and natural Convective Thermal Model (CTM) for thermal distribution at the pack level. A 7S4P battery pack with 21700 NCA cylindrical cells is considered in this study and the model is validated with the experimental data sets at different c-rates and temperatures. The developed model is able to successfully predict the pack voltage, capacities, and temperatures. The proposed model is computationally efficient and can be easily adopted for on-board implementation in battery management system for safe and reliable operations.