A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems

Valentina Lucaferri, Michele Quercio, Antonino Laudani and Francesco Riganti Fulginei ()
Additional contact information
Valentina Lucaferri: Department of Industrial Engineering, Electronics and Mechanics, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Michele Quercio: Department of Industrial Engineering, Electronics and Mechanics, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Antonino Laudani: Department of Electrical, Electronic and Computer Engineering (DIEEI), University of Catania, Viale Andrea Doria 6, 95125 Catania, Italy
Francesco Riganti Fulginei: Department of Industrial Engineering, Electronics and Mechanics, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy

Energies, 2023, vol. 16, issue 23, 1-19

Abstract: Battery state estimation is fundamental to battery management systems (BMSs). An accurate model is needed to describe the dynamic behavior of the battery to evaluate the fundamental quantities, such as the state of charge (SOC) or the state of health (SOH). This paper presents an overview of the most commonly used battery models, the equivalent electrical circuits, and data-driven ones, discussing the importance of battery modeling and the various approaches used to model lithium batteries. In particular, it provides a detailed analysis of the electrical circuit models commonly used for lithium batteries, including equivalent circuit and thermal models. Furthermore, a comprehensive overview of data-driven approaches is presented. The advantages and limitations of each type of model are discussed. Finally, the paper concludes with a discussion of current research trends and future directions in the field of battery modeling.

Keywords: equivalent circuit battery models; battery management systems; Li-ion battery (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/23/7807/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/23/7807/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:23:p:7807-:d:1288765

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().