Next-generation battery management systems: dynamic reconfiguration
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Abstract
Batteries are widely applied to the energy storage and power supply in portable electronics, transportation, power systems, communication networks, etc. They are particularly demanded in the emerging technologies of vehicle electrification and renewable energy integration for a green and sustainable society. To meet various voltage, power, and energy requirements in large-scale applications, multiple battery cells have to be connected in series and/or parallel. While battery technology has advanced significantly in the past decade, existing battery management systems (BMSs) mainly focus on state monitoring and control of battery systems packed in fixed configurations. In fixed configurations, though, the battery system performance is in principle limited by the weakest cells, which can leave large parts severely underutilized. Allowing dynamic reconfiguration of battery cells, on the other hand, allows individual and flexible manipulation of the battery system at cell, module, and pack levels, which may open up a new paradigm for battery management. Following this trend, this paper provides an overview of next-generation BMSs featuring dynamic reconfiguration. Motivated by numerous potential benefits of reconfigurable battery systems (RBSs), the hardware designs, management principles, and optimization algorithms for RBSs are sequentially and systematically discussed. Theoretical and practical challenges during the design and implementation of RBSs are highlighted in the end to stimulate future research and development.
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Current SOC estimation methods often lack the flexibility to address different battery types and configurations, limiting their universal application.
“Current methods often lack the flexibility to address different battery types and configurations, limiting their universal application (Han et al., 2020).”
From State-of-charge estimation of commercial electric vehicles by using battery-aware transformer network algorithms (2025) · cites this paper as Han et al., 2020
The “Modeling of RBSs” section discusses SoC estimation and explains why a fixed-configuration pack model must change for reconfigurable systems (page unavailable). The “Coordinating Batteries of Different Age or Chemistry” section discusses managing different chemistries, but neither section says that current SoC estimation methods generally lack flexibility across battery types and configurations or have limited universal application. Searches for those limitations found no such passage. (LLM, conf=0.72)
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References 55 · Cited by 173
Research works printed but not linked: 2
- B. Lawson, "A software configurable battery," in 26th Int. Battery, Hybrid Fuel Cell Electr. Veh. Symp., May 2012, pp. 252-263.
- J. Andersson, "Lifetime estimation of lithium-ion batteries for stationary energy storage systems," M.S. thesis, KTH Royal Institute of Technology, Stockholm, Sweden, June 2017.
- Authors
- Han, W., Wik, T., Kersten, A., Dong, G., & Zou, C.
- Affiliations
- University of Connecticut (US)
- Chalmers University of Technology (SE)
- The University of Melbourne (AU)
- Venue
- IEEE Industrial Electronics Magazine
- Published
- 2020-12
- Volume
- 14
- Issue
- 4
- Pages
- 20-31
- ISSN
- 1932-4529 (ISSN-L)
- 1941-0115
- OpenAlex
- W3044039637
- Cited by
- 173
- References
- 55
- Citations by year
- 2026: 27 · 2025: 36 · 2024: 40 · 2023: 20 · 2022: 23 · 2021: 22 · 2020: 5
- FWCI
- 6.47
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- IEEE Industrial Electronics Magazine (publishedVersion)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- Funders
- Stiftelsen för Miljöstrategisk Forskning (MI23-19.03)
- Area of Advance Transport Chalmers University of Technology (32610511)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Photovoltaic System Optimization Techniques
- Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
- Keywords
- battery management systems, dynamic reconfiguration, battery state monitoring, vehicle electrification, renewable energy storage
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