This paper is published in Volume-11, Issue-3, 2025
Area
Battery Thermal Management System In EVs
Author
Abhishek Guleria
Org/Univ
Independent Researcher, India
Pub. Date
27 June, 2025
Paper ID
V11I3-1390
Publisher
Keywords
Battery Thermal Management System (BTMS), Electric Vehicle (EV), Computational Fluid Dynamics (CFD), Fin Spacing, Fin Geometry, Heat Dissipation

Citationsacebook

IEEE
Abhishek Guleria. Optimization of Battery Thermal Management System using Fin Spacing and Fin Count Parameters in Electric Vehicles, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Abhishek Guleria (2025). Optimization of Battery Thermal Management System using Fin Spacing and Fin Count Parameters in Electric Vehicles. International Journal of Advance Research, Ideas and Innovations in Technology, 11(3) www.IJARIIT.com.

MLA
Abhishek Guleria. "Optimization of Battery Thermal Management System using Fin Spacing and Fin Count Parameters in Electric Vehicles." International Journal of Advance Research, Ideas and Innovations in Technology 11.3 (2025). www.IJARIIT.com.

Abstract

Efficient battery thermal management is pivotal for ensuring the safety, performance, and extended lifespan of electric vehicle (EV) batteries. This study presents a comprehensive Computational Fluid Dynamics (CFD)-based analysis on the influence of fin geometry, spacing, and quantity on heat dissipation efficiency. Thermal simulations were conducted using ANSYS Fluent, allowing evaluation of radiator models under varied fin geometries and boundary conditions to observe temperature uniformity and heat removal performance. Emphasis was placed on comparing different fin shapes (square, circular, curved), spacings (5 mm to 12.5 mm), and fin counts. Results indicate that 7.5 mm spacing provides optimal thermal efficiency regardless of geometry, and increasing fin number beyond a threshold yields diminishing returns. Copper showed superior thermal performance over aluminum, though cost and weight favoured aluminum. The findings provide practical insights into radiator fin optimization for advanced BTMS design.