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Issue 1, 2019
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The effect of electrode design parameters on battery performance and optimization of electrode thickness based on the electrochemical–thermal coupling model

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Abstract

Electrodes are the most important components in the lithium-ion battery, and their design, which ultimately determines the quantity and speed of lithium storage, directly affects the capacity, power density, and energy density of the battery. Herein, an electrochemical–thermal coupling model was established for an 18.5 A h lithium-ion battery, and the model was validated by experiment at four discharge rates. Based on this model, the effects of the electrode design parameters (electrode thickness, volume fraction of active material and particle size) on the battery performance (electrochemical characteristics, thermal behavior, energy density and power density) were initially investigated. It was found that as the electrode thickness and volume fraction of the active material increased, the polarization, heat generation rate and energy density increased, while the power density degraded. In addition, as the particle size decreased, both the energy density and power density improved, which can provide guidance for the design of electrodes. Subsequently, a multi-parameter (thickness of the positive and negative electrodes) and multi-objective (energy density and power density) optimization procedure was performed via two optimization methods, and the positive electrode thickness of 55.335 μm and negative electrode thickness of 63.188 μm were determined to be the optimized parameters.

Graphical abstract: The effect of electrode design parameters on battery performance and optimization of electrode thickness based on the electrochemical–thermal coupling model

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Article information


Submitted
16 Oct 2018
Accepted
10 Nov 2018
First published
12 Nov 2018

Sustainable Energy Fuels, 2019,3, 148-165
Article type
Paper

The effect of electrode design parameters on battery performance and optimization of electrode thickness based on the electrochemical–thermal coupling model

W. Mei, H. Chen, J. Sun and Q. Wang, Sustainable Energy Fuels, 2019, 3, 148
DOI: 10.1039/C8SE00503F

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