Design and Multiobjective Optimization of Fin‐Assisted Air‐Cooled BTMS for 21 700 Lithium‐Ion Cylindrical Cells Using CFD – RSM Integration
Year: 2026
Type: article
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 < 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 > 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.
Source: Energy Storage
DOI: 10.1002/est2.70358
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7128964306