Benallal, Abdellah, Cheggaga, Nawal, Hebib, Amine and Ilinca, Adrian.
2025.
« LSTM-based state-of-charge estimation and user interface development for lithium-ion battery management ».
World Electric Vehicle Journal, vol. 16, nº 3.
Compte des citations dans Scopus : 1.
Preview |
PDF
Ilinca-A-2025-30761.pdf - Published Version Use licence: Creative Commons CC BY. Download (5MB) | Preview |
Abstract
State-of-charge (SOC) estimation is pivotal in optimizing lithium-ion battery management systems (BMSs), ensuring safety, performance, and longevity across various applications. This study introduces a novel SOC estimation framework that uniquely integrates Long Short-Term Memory (LSTM) neural networks with Hyperband-driven hyperparameter optimization, a combination not extensively explored in the literature. A comprehensive experimental dataset is created using data of LG 18650HG2 lithium-ion batteries subjected to diverse operational cycles and thermal conditions. The proposed framework demonstrates superior prediction accuracy, achieving a Mean Square Error (MSE) of 0.0023 and a Mean Absolute Error (MAE) of 0.0043, outperforming traditional estimation methods. The Hyperband optimization algorithm accelerates model training and enhances adaptability to varying operating conditions, making it scalable for diverse battery applications. Developing an intuitive, real-time user interface (UI) tailored for practical deployment bridges the gap between advanced SOC estimation techniques and user accessibility. Detailed residual and regression analyses confirm the proposed solution’s robustness, generalizability, and reliability. This work offers a scalable, accurate, and userfriendly SOC estimation solution for commercial BMSs, with future research aimed at extending the framework to other battery chemistries and hybrid energy systems.
| Item Type: | Peer reviewed article published in a journal |
|---|---|
| Professor: | Professor Ilinca, Adrian |
| Affiliation: | Génie mécanique |
| Date Deposited: | 10 Apr 2025 18:06 |
| Last Modified: | 17 Apr 2025 15:09 |
| URI: | https://espace2.etsmtl.ca/id/eprint/30761 |
Actions (login required)
 |
View Item |