Parameter Identification Method for a Fractional-Order Model of Lithium-Ion Batteries Considering Electrolyte-Phase Diffusion

The physics-based fractional-order model (FOM) for lithium-ion batteries has shown good application prospects due to its mechanisms and simplicity. To adapt the model to higher-level applications, this paper proposes an improved FOM considering electrolyte-phase diffusion (FOMe) and then proposes a...

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Bibliographic Details
Main Authors: Yanbo Jia, Lei Dong, Geng Yang, Feng Jin, Languang Lu, Dongxu Guo, Minggao Ouyang
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Batteries
Subjects:
Online Access:https://www.mdpi.com/2313-0105/8/8/90
Description
Summary:The physics-based fractional-order model (FOM) for lithium-ion batteries has shown good application prospects due to its mechanisms and simplicity. To adapt the model to higher-level applications, this paper proposes an improved FOM considering electrolyte-phase diffusion (FOMe) and then proposes a complete method for parameter identification based on three characteristic SOC intervals: the positive solid phase, negative solid phase, and electrolyte phase. The method mainly determines the above three characteristic intervals and identifies four thermodynamic parameters and five dynamic parameters. Furthermore, the paper describes a framework, which first verifies the model and parameter identification method separately based on pseudo two-dimensional model simulations, and secondly verifies FOMe and its parameters as a whole based on the experiments. The results, which are based on simulations and actual <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">L</mi><msub><mi mathvariant="normal">i</mi><mrow><mn>0</mn><mrow><mo>.</mo><mn>8</mn></mrow></mrow></msub><mi mathvariant="normal">C</mi><msub><mi mathvariant="normal">o</mi><mrow><mn>0</mn><mrow><mo>.</mo><mn>1</mn></mrow></mrow></msub><mi mathvariant="normal">M</mi><msub><mi mathvariant="normal">n</mi><mrow><mn>0</mn><mrow><mo>.</mo><mn>1</mn></mrow></mrow></msub><msub><mi mathvariant="normal">O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> lithium-ion batteries under multiple typical operating profiles and comparisons with other parameter identification methods, show that the proposed model and parameter identification method is highly accurate and efficient.
ISSN:2313-0105