Journal
ENERGIES
Volume 14, Issue 11, Pages -Publisher
MDPI
DOI: 10.3390/en14113284
Keywords
lithium-ion battery; state-of-charge; modelling; battery management systems
Categories
Funding
- ENERSENSE research initiative, NTNU, Norway
- Freyr Battery AS, NTNU [90492503]
- EIT Innoenergy SE [02-2019-IP172-FREYR]
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Energy storage systems (ESSs) are crucial for the future of electric vehicles, but their safety and management need improvement. State-of-charge (SoC) has become a significant research area for lithium-ion batteries (LIBs) in recent years, yet faces challenges in accurate modeling and assessment of internal environments.
Energy storage systems (ESSs) are critically important for the future of electric vehicles. Despite this, the safety and management of ESSs require improvement. Battery management systems (BMSs) are vital components in ESS systems for Lithium-ion batteries (LIBs). One parameter that is included in the BMS is the state-of-charge (SoC) of the battery. SoC has become an active research area in recent years for battery electric vehicle (BEV) LIBs, yet there are some challenges: the LIB configuration is nonlinear, making it hard to model correctly; it is difficult to assess internal environments of a LIB (and this can be different in laboratory conditions compared to real-world conditions); and these discrepancies can lead to raising the instability of the LIB. Therefore, further advancement is required in order to have higher accuracy in SoC estimation in BEV LIBs. SoC estimation is a key BMS feature, and precise modeling and state estimation will improve stable operation. This review discusses current methods use in BEV LIB SoC modelling and estimation. The review culminates in a brief discussion of challenges in BEV LIB SoC prediction analysis.
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