Cited by 143Advanced Battery Technologies ResearchAdvancements in Battery MaterialsModel Reduction and Neural Networks

Reduced-order electrochemical model for lithium-ion battery with domain decomposition and polynomial approximation methods

Li, Changlong, Cui, Naxin, Wang, Chunyu, Zhang, Chenghui·2021·Energy

Abstract

Abstract The pseudo-two-dimensional (P2D) electrochemical model can give insight into the internal behavior of lithium-ion batteries, which is of great significance for intelligent battery management. However, the computational complexity of the P2D model greatly limits its onboard application. This paper devotes to develop a reduced-order electrochemical model (ROEM) with high fidelity yet low computational cost. First, for the simplification of the electrolyte diffusion process in batteries, domain decomposition technique is applied to divide the whole cell sandwich into two computation domains. The polynomial approximation method is adopted to describe the electrolyte concentration distribution in each domain, so that the electrolyte diffusion process is represented by two independent state variables. Next, combining the simplified electrolyte diffusion process and other dynamics in lithium-ion batteries, the complete ROEM is obtained as a five-state diagonal system. Finally, the prediction accuracy of the ROEM on electrolyte concentration, electrolyte diffusion overpotential and terminal voltage is verified by comparing with the P2D model and experimental results. Moreover, the proposed ROEM has an ideal computing speed for real-time application, which is at least 600 times faster than the rigorous P2D model.

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Crossref · 10.1016/j.energy.2020.119662

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References 45 · Cited by 143

Authors
Li, C., Cui, N., Wang, C., & Zhang, C.
Affiliations
Shandong University (CN)
Corresponding author
Cui, Naxin
Venue
Energy
Publisher
Elsevier BV
Published
2021-04
Volume
221
Pages
119662
ISSN
0360-5442 (ISSN-L)
OpenAlex
W3125460992
Cited by
143
References
45
Citations by year
2026: 20 · 2025: 36 · 2024: 27 · 2023: 25 · 2022: 24 · 2021: 11
FWCI
7.07
Type
journal article
Language
en
Open access
closed
Locations
  • Energy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • Key Technology Research and Development Program of Shandong (2019JZZY020814, U1764258)
  • National Natural Science Foundation of China (U1764258, U1864202, 61633015, U1864205)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Model Reduction and Neural Networks
Keywords
lithium-ion batteries, reduced-order electrochemical model, pseudo-two-dimensional model, domain decomposition, polynomial approximation, electrolyte diffusion, overpotential, terminal voltage prediction, battery management systems

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