A reinforcement learning-based multi-objective optimization algorithm: ATP-QL-MOPSO for lightweight and crashworthiness design of battery pack system
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Published online on November 04, 2025
Abstract
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
This study presents an improved MOPSO algorithm, ATP-QL-MOPSO, for lightweight and crashworthiness optimization of automotive battery pack systems (BPS). Traditional MOPSO struggles with hyperparameter tuning and local optima. The proposed method ...
This study presents an improved MOPSO algorithm, ATP-QL-MOPSO, for lightweight and crashworthiness optimization of automotive battery pack systems (BPS). Traditional MOPSO struggles with hyperparameter tuning and local optima. The proposed method ...