A reduced low-temperature electro-thermal coupled model for lithium-ion batteries. (1st September 2016)

• Record Type: Journal Article
• Authors: Jiang, Jiuchun; Ruan, Haijun; Sun, Bingxiang; Zhang, Weige; Gao, Wenzhong; Wang, Le Yi; Zhang, Linjing
• Is Part Of: Applied energy. Volume 177(2016)
• Page Start: 804
• Page End: 816
• Publication Date: 2016-09-01
• Subjects: Lithium-ion battery -- Low temperature -- Electro-thermal coupled model -- Frequency dependence -- Model reduction; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.05.153
• Languages: English
• ISSNs: 0306-2619

Abstract

Graphical abstract: Highlights: A reduced low-temperature electro-thermal coupled model is proposed. A novel frequency-dependent equation for polarization parameters is presented. The model is validated under different frequency and low-temperature conditions. The reduced model exhibits a high accuracy with a low computational effort. The adaptability of the proposed methodology for model reduction is verified. Abstract: A low-temperature electro-thermal coupled model, which is based on the electrochemical mechanism, is developed to accurately capture both electrical and thermal behaviors of batteries. Activation energies reveal that temperature dependence of resistances is greater than that of capacitances. The influence of frequency on polarization voltage and irreversible heat is discussed, and frequency dependence of polarization resistance and capacitance is obtained. Based on the frequency-dependent equation, a reduced low-temperature electro-thermal coupled model is proposed and experimentally validated under different temperature, frequency and amplitude conditions. Simulation results exhibit good agreement with experimental data, where the maximum relative voltage error and temperature error are below 2.65% and 1.79 °C, respectively. The reduced model is demonstrated to have almost the same accuracy as the original model and require a lower computational effort. The effectiveness and adaptability of the proposed methodology for model reduction is verified using batteries with three different cathode materials from different manufacturers. The reduced model, thanks to its high accuracy and simplicity, provides a promising candidate for development of rapid internal heating and optimal charging strategies at low temperature, and for evaluation of the state of battery health in on-board battery management system.