Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/34841
Title: Universal Li-Ion Cell Electrothermal Model
Authors: Stocker, Richard 
Mumtaz, Asim 
Paramjeet 
Braglia, Michele 
Lophitis, Neophytos 
Major Field of Science: Engineering and Technology
Keywords: Battery cell;lithium-ion;model;simulation;time domain
Issue Date: 1-Mar-2021
Source: IEEE Transactions on Transportation Electrification, 2021, vol. 7, no 1, pp. 6 - 15
Volume: 7
Issue: 1
Start page: 6
End page: 15
Journal: IEEE Transactions on Transportation Electrification 
Abstract: This article describes and verifies a Li-ion cell electrothermal model and the associated data analysis process. It is designed to be adaptable and provide accurate results across all variations of operating conditions and cell design based only on the time-domain voltage, current, and temperature measurements. The creation of this model required an analysis process ensuring consistency in expressing the underlying cell behavior. This revealed a flexible modeling structure adaptable both to cell performance variations and the limitations of the available test data. The model has been created with a combined thermal and electrical approach enabling 1-D nodal distribution adaptable to both cylindrical and prismatic cells. These features combine with an intelligent parameter identification process identifying model structure and parameterization across the usage range, adaptable to any nickel-manganese-cobalt Li-ion cell. It is designed to retain physical meaning and representation to each circuit element across the temperature operating range. The model is verified in several different operating conditions through representative automotive cycling on an 18 650 cell and a BEV2 format prismatic cell, representing the extremes of automotive cell design. The consistency of the model parameters with real phenomena is also analyzed and validated against electrochemical impedance spectroscopy data.
URI: https://hdl.handle.net/20.500.14279/34841
ISSN: 2332-7782
2372-2088
DOI: 10.1109/TTE.2020.2986606
Type: Article
Affiliation : Coventry University 
University of Liverpool 
Horizon Scanning, HORIBA MIRA 
University of Nottingham 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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