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Journal of Power Sources
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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A computational multi-node electro-thermal model for large prismatic lithium-ion batteries

Authors: Pan, Y-W; Hua, Y; Zhou, S; He, R; Zhang, Y; Yang, S; Liu, X; +3 Authors

A computational multi-node electro-thermal model for large prismatic lithium-ion batteries

Abstract

Abstract During operation of large prismatic lithium-ion batteries, temperature heterogeneities are aggravated which affect the performance, lifetime and safety of the cells and packs. Therefore, an accurate model to predict the evolution of temperature profiles in a cell is essential for effective thermal management. In this paper, a pseudo 3D coupled multi-node electro-thermal model is presented for real-time prediction of the heterogeneous temperature field evolution on the surface and inside the battery. The model consists of two parts: a heat generation model based on a second-order equivalent-circuit model and a multi-node heat transfer model based on the battery geometry. Three types of nodes are adopted to describe the thermal characteristics of various components of the cell. Simulation results show that the proposed model has a great consistency with finite element method, and its computational cost is reduced by 90%. The validity of the coupled electrical and thermal model is also demonstrated experimentally for a 105 Ah prismatic cell applying wide ranges of temperature and SOC. The maximum error is less than 2 K throughout the cycles. The proposed model holds a great potential for online temperature estimation in advanced lithium-ion battery thermal management system design.

Country
United Kingdom
Related Organizations
Keywords

Energy, 03 Chemical Sciences, 09 Engineering, 620

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
65
Top 1%
Top 10%
Top 1%
Green