Parameter Sensitivity Analysis of Cylindrical LiFePO₄Battery Performance Using Multi-Physics Modeling

Abstract

A multi-physics model for a cylindrical Li-ion battery has been developed by coupling the thermal distribution in the radial direction to an electrochemical P2D model. The model can predict both terminal voltage and surface temperature, which has the advantage that it can be readily validated by measurement. A sensitivity analysis of up to 30 parameters was carried out using model simulation. A parameter sensitivity matrix was established to describe the parameter sensitivity under different operating conditions and the parameters were grouped according to their average sensitivity. The parameters were clustered based on their sensitivity matrix with Fuzzy C-Means (FCM) method. The cluster centers are special operating conditions on which the parameters in the same cluster have high identifiability. Finally, a stepwise experiment is designed based on the analysis results of parameter sensitivity, and the rationality and effectiveness are also validated. It was shown that the stepwise approach to parameter identification results in significantly higher accuracy.In recent years, Li-ion batteries have been widely used in electric vehicles due to their relatively high energy and power density. In such demanding applications, Prognostics and Health Management (PHM) of Li-ion batteries is a key issue and has attracted increasing interest from researchers. The aim of our research is to build a PHM database for Li-ion batteries by determining which parameters will change and how they change under different aging patterns. This database could be used for characterization of State-of-Health (SOH) and estimation of remnant lifetime. The core work is to develop a numerical model that can predict battery behavior and identify the critical model parameters accurately and nondestructively using simple and rational experiments.The Newman P2D model is a type of first principle model commonly used in the analysis of Li-ion battery performance. 1-3 It addresses the complex interaction of physicochemical processes such as diffusion, ion migration, ohmic phenomena and electrochemical reaction using a group of partial differential and algebraic equations. The parameters of the P2D model have corresponding physical meaning and can be treated as an indicator of battery SOH, e.g. Zhang et al. used the stoichiometric number of the electrode material to indicate the stages of capacity fading. 4,5 Schmidt et al. investigated the relationship between the parameters ε s , κ e and the cycle number during aging and used them to evaluate the SOH of batteries. 6 Ramadesigan et al. found that the parameters k s,a and D s,a degraded with cycle number according to a power-law. 7 These papers have established relationships between a limited number of parameters and battery SOH. The aim of this work was to investigate a much larger set of model parameters under different stages of aging. Therefore, a rapid, accurate and non-invasive identification method is necessary.However, the large number of parameters in the P2D model makes parameter identificati...

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