Parametric Optimization Study of a Lithium-ion Cell. (October 2017)

• Record Type: Journal Article
• Authors: Nileshwar, Pramila Rao; McGordon, A.; Ashwin, T.R.; Greenwood, D.
• Is Part Of: Energy procedia. Volume 138(2017)
• Page Start: 829
• Page End: 834
• Publication Date: 2017-10
• Subjects: Lithium-ion cell -- Electrochemical model -- Parameter optimization; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.10.088
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Lithium-ion cell technology is well known for its high power and energy density in the automotive application. This paper presents development of a 1D electrochemical model which can be used to predict 18650 lithium-ion cell performance under different operating conditions. COMSOL Multiphysics 5.2a software has been utilized to develop the electrochemical model to predict the cell behaviour under various discharge rates. This tool uses the finite element method (FEM) to solve the conservation equations of charge and species in solid and electrolyte phase. And Butler-Volmer equation for reaction rates of lithium insertion and extraction. In an event that the electrochemical parameters of the cell are not known, determination of these parameters by measurements or experiments is a difficult and challenging task. An attempt has been made in this paper to estimate unknown cell parameters by two methods, first by performing a parametric study on cell parameters such as particle radius, diffusion coefficient, porosity etc. within a known range from literature studies and analyse the sensitivity of these parameters on the model results. Secondly, to improve the accuracy of the simulation results, COMSOL optimization module is used and the simulation results are validated against the experimental data. Apart from the discharge profiles, the proposed model can also be used to study the time dependent distribution of lithium-ion concentration, electrolyte concentration, lithium diffusivity and ionic conductivity in the cell.