Effect of Electrode Thickness and Operating Temperature on Electrochemical Performance of Li‐Ion Batteries

ABSTRACT Lithium‐ion batteries (LIBs) have emerged of late as the most popular high‐energy storage devices with a variety of uses, including electric vehicles and cell phones. Due to structural stability, low cost, and longer cycle life compared to other LIB systems, the lithium titanate and lithium manganese oxide (LTO‐LMO) pair has gained wide interest. Researchers have investigated how the electrode thickness affects the LIBs performance. However, there is still limited understanding of how the LIB cell performance depends on the operating temperature. In this paper, a 1D electrochemical model has been developed to predict the LTO‐LMO cell performance under different operating conditions using the COMSOL multiphysics simulation software. The model predictions are successfully validated with published experimental studies. Further, a parametric study is performed by varying the electrode thickness and operating temperature. The results established that for low discharge rates (C rates), higher thickness results in increased cell discharge capacity, but for higher C rates, this is not true due to poor electrode utilization. This study also effectively optimizes the cell cathode and anode thickness using response surface methodology based ANOVA to maximize discharge capacity. This study could prove very useful in the future development of LIBs.

Authors

Institutions

Publication Details

Journal
Energy Storage
Published
2025-04-21
DOI
https://doi.org/10.1002/est2.70172
Citations
3
Primary Topic
Advancements in Battery Materials
Type
article
Field-Weighted Citation Impact
2.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of Electrode Thickness and Operating Temperature on Electrochemical Performance of Li‐Ion Batteries

Mukul Shukla, Aparajita Mishra
3 citations
Energy Storage
Advancements in Battery Materials
2.19
article

Effect of Electrode Thickness and Operating Temperature on Electrochemical Performance of Li‐Ion Batteries

Mukul Shukla, Aparajita Mishra
article en
3 citations

Abstract

ABSTRACT Lithium‐ion batteries (LIBs) have emerged of late as the most popular high‐energy storage devices with a variety of uses, including electric vehicles and cell phones. Due to structural stability, low cost, and longer cycle life compared to other LIB systems, the lithium titanate and lithium manganese oxide (LTO‐LMO) pair has gained wide interest. Researchers have investigated how the electrode thickness affects the LIBs performance. However, there is still limited understanding of how the LIB cell performance depends on the operating temperature. In this paper, a 1D electrochemical model has been developed to predict the LTO‐LMO cell performance under different operating conditions using the COMSOL multiphysics simulation software. The model predictions are successfully validated with published experimental studies. Further, a parametric study is performed by varying the electrode thickness and operating temperature. The results established that for low discharge rates (C rates), higher thickness results in increased cell discharge capacity, but for higher C rates, this is not true due to poor electrode utilization. This study also effectively optimizes the cell cathode and anode thickness using response surface methodology based ANOVA to maximize discharge capacity. This study could prove very useful in the future development of LIBs.

Energy StorageVol. 7(4)
Motilal Nehru National Institute of Technology (IN), University of Johannesburg (ZA)
Openalex Percentile: Top 13%
Advancements in Battery Materials
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.