Battery Life Prediction Using Physics-Based Modeling and Coati Optimization

Vahid Safavi*, Arash Mohammadi Vaniar, Najmeh Bazmohammadi, Juan C. Vasquez, Josep M. Guerrero

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

Accurate remaining useful life (RUL) prediction is essential for ensuring the reliability and efficiency of Lithium-ion (Li-ion) batteries. This paper presents an approach using the Coati Optimization Algorithm (COA) to optimize the physics-based model for RUL prediction of Li-ion batteries. This method combines COA to optimize the physics-based degradation model to improve battery aging predictions, considering factors like cycle time, rest time, temperature, state of charge (SOC), and load conditions. The model can more accurately simulate real-world battery usage patterns and degradation mechanisms by incorporating these variables. Simulation results show that COA enhances the accuracy of the model's calendar and cycle aging prediction, and reduces RMSE and MAE values for RUL prediction. Furthermore, the robustness of the proposed method is demonstrated through extensive testing under various operational scenarios, highlighting its potential for application in battery management systems to extend battery life and improve performance.
Original languageEnglish
Title of host publicationEnergy Informatics - 4th Energy Informatics Academy Conference, EI.A 2024, Proceedings
EditorsBo Nørregaard Jørgensen, Zheng Grace Ma, Fransisco Danang Wijaya, Roni Irnawan, Sarjiya Sarjiya
Number of pages11
Volume15272
Place of PublicationKuta, Bali, Indonesia
PublisherSpringer Nature Switzerland AG
Publication date18 Oct 2024
Pages303-313
ISBN (Print)978-3-031-74740-3
ISBN (Electronic)978-3-031-74741-0
DOIs
Publication statusPublished - 18 Oct 2024
SeriesLecture Notes in Computer Science
Volume15272
ISSN0302-9743

Keywords

  • COA optimization
  • Battery RUL prediction
  • Physics based model

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