Aging Effect–Aware Finite Element Model and Parameter Identification Method of Lithium-Ion Battery

Author:

Tian Aina1,Yang Chen1,Gao Yang23,Jiang Yan4,Chang Chun1,Wang Lujun1,Jiang Jiuchun54

Affiliation:

1. Hubei University of Technology Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, , Wuhan 430068 , China

2. Sunwoda Electronic Co., Ltd. , Shenzhen 518108 , China ;

3. South China University of Technology School of Electric Power, , Guangzhou 510640 , China

4. Sunwoda Electronic Co., Ltd. , Shenzhen 518108 , China

5. Hubei University of Technology Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, , Wuhan 430068 , China ;

Abstract

Abstract Battery aging is an inevitable macroscopic phenomenon in the use of the battery, which is characterized by capacity decline and power reduction. If the charging and discharging strategy does not adjust with the aging state, it is easy to cause battery abuse and accelerate the decline. To avoid this situation, the aging model with consideration of the battery degradation is coupled into the pseudo-two-dimensional (P2D) model. An aging effect-aware finite element model that can describe battery physical information accurately is presented in this article. The model parameters are divided into four parts: structure parameters, thermodynamic parameters, kinetic parameters, and aging parameters. The identification experiments are designed based on the characteristics of these types of parameters. The decoupling and parameter identification methods of kinetic parameters according to the response characteristics of each parameter under specific excitation, and state-of-charge (SOC) partitioned range identification technology of aging parameters is proposed and verified. Finally, the aging effect-aware model and the identification parameters are verified under constant current (CC) and different dynamic conditions with different charge rate (C-rate). The ability of the proposed model to track the aging trajectory in the whole life cycle is verified under various cycle conditions. The proposed model can be applied to aging mechanism analysis and health management from point of inner properties of the batteries.

Funder

Hubei University of Technology

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Publisher

ASME International

Subject

Mechanical Engineering,Mechanics of Materials,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electronic, Optical and Magnetic Materials

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