Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm

Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm

Abstract Addressing a key research gap in the lack of unified AI-based approaches that ensure both high predictive accuracy and informed design trade-offs, this study presents a synergistic methodology that integrates advanced intelligent techniques to optimize the thermal and hydraulic performance...

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Bibliographic Details
Main Authors: Anjan Kumar, Laith Hussein Jasim, Padmanabha Vijaya, Dipak Patel, J. Gowrishankar, R. Sivaranjani, Ankur Srivastava, Mayank Kundlas, Sarbeswara Hota, Banafshe Hamidi
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Lithium-ion battery
Thermal management system
Multilayer perceptron neural network
Metaheuristic algorithms
Salp swarm algorithm
Multi-criteria decision-making
Online Access:https://doi.org/10.1038/s41598-025-15359-0
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https://doi.org/10.1038/s41598-025-15359-0

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