Design and Multiobjective Optimization of Fin‐Assisted Air‐Cooled <scp>BTMS</scp> for 21 700 Lithium‐Ion Cylindrical Cells Using <scp>CFD</scp> – <scp>RSM</scp> Integration

ABSTRACT This study presents a comprehensive numerical and statistical investigation of an air‐cooled BTMS for a single 21 700 cylindrical lithium‐ion cell, focusing on the influence of airflow velocity, discharge rate (C‐rate), and longitudinal fin configuration. A 3D CFD model, validated against experimental data, was developed to evaluate four configurations (bare cell, 2 fins, 4 fins, 6 fins) under velocities of 2–6 m/s and C‐rates of 1C–3C. The analysis assessed peak temperature ( T max ), temperature difference (Δ T ), and average temperature ( T avg ) to determine thermal safety and uniformity. Results indicate that C‐rate is the dominant factor, with T max rising from 30°C at 1C to over 100°C for the bare cell at 3C–2 m/s. Increasing airflow from 2 to 6 m/s reduced T max by up to 15°C at high C‐rates, while adding fins improved heat spreading, lowering T max by 8°C–10°C and Δ T by up to 4°C compared to the bare cell. At 3C–6 m/s, a 6‐fin configuration achieved T max ≈60°C and Δ T &lt; 8°C, ensuring safe operation. Velocity streamline and temperature contour analyses revealed that fins enhance circumferential flow coverage, reduce recirculation zones, and improve thermal uniformity. Response Surface Methodology (RSM) models for T max , Δ T , and T avg achieved R 2 &gt; 0.97, with ANOVA confirming significant main and interaction effects. Multiresponse optimization identified an optimal low‐load condition (2 m/s, 1C, 2 fins) yielding T max = 39.16°C, Δ T = 6.78°C, and T avg = 32.08°C (desirability = 0.798). At high C‐rates, optimal thermal performance required ≥ 4 fins and ≥ 4 m/s airflow. The integrated CFD–RSM approach provides both qualitative flow‐thermal insights and quantitative design guidelines, enabling efficient BTMS optimization for varying load conditions while balancing safety, uniformity, and energy efficiency.

Authors

Institutions

Publication Details

Journal
Energy Storage
Published
2026-02-15
DOI
https://doi.org/10.1002/est2.70358
Primary Topic
Heat Transfer and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and Multiobjective Optimization of Fin‐Assisted Air‐Cooled BTMS for 21 700 Lithium‐Ion Cylindrical Cells Using CFD – RSM Integration

Praveen Barmavatu, S. K. Gugulothu, S. M. D. Shehabaz, Raju Muthyala
Energy Storage
Heat Transfer and Optimization
article

Design and Multiobjective Optimization of Fin‐Assisted Air‐Cooled BTMS for 21 700 Lithium‐Ion Cylindrical Cells Using CFD – RSM Integration

Praveen Barmavatu, S. K. Gugulothu, S. M. D. Shehabaz, Raju Muthyala
article en

Abstract

ABSTRACT This study presents a comprehensive numerical and statistical investigation of an air‐cooled BTMS for a single 21 700 cylindrical lithium‐ion cell, focusing on the influence of airflow velocity, discharge rate (C‐rate), and longitudinal fin configuration. A 3D CFD model, validated against experimental data, was developed to evaluate four configurations (bare cell, 2 fins, 4 fins, 6 fins) under velocities of 2–6 m/s and C‐rates of 1C–3C. The analysis assessed peak temperature ( T max ), temperature difference (Δ T ), and average temperature ( T avg ) to determine thermal safety and uniformity. Results indicate that C‐rate is the dominant factor, with T max rising from 30°C at 1C to over 100°C for the bare cell at 3C–2 m/s. Increasing airflow from 2 to 6 m/s reduced T max by up to 15°C at high C‐rates, while adding fins improved heat spreading, lowering T max by 8°C–10°C and Δ T by up to 4°C compared to the bare cell. At 3C–6 m/s, a 6‐fin configuration achieved T max ≈60°C and Δ T &lt; 8°C, ensuring safe operation. Velocity streamline and temperature contour analyses revealed that fins enhance circumferential flow coverage, reduce recirculation zones, and improve thermal uniformity. Response Surface Methodology (RSM) models for T max , Δ T , and T avg achieved R 2 &gt; 0.97, with ANOVA confirming significant main and interaction effects. Multiresponse optimization identified an optimal low‐load condition (2 m/s, 1C, 2 fins) yielding T max = 39.16°C, Δ T = 6.78°C, and T avg = 32.08°C (desirability = 0.798). At high C‐rates, optimal thermal performance required ≥ 4 fins and ≥ 4 m/s airflow. The integrated CFD–RSM approach provides both qualitative flow‐thermal insights and quantitative design guidelines, enabling efficient BTMS optimization for varying load conditions while balancing safety, uniformity, and energy efficiency.

Energy StorageVol. 8(2)
Sri Venkateswara University (IN), Sri Venkateswara Medical College and Ruia Hospital (IN), Metropolitan University of Technology (CL), National Institute of Technology Andhra Pradesh (IN)
Openalex Percentile: Top 55%
Heat Transfer and Optimization
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.