Optimizing Lithium-Ion Battery SOC Estimation Under Safe Dynamic Conditions : Modeling and Performance Comparison
Year: 2026
Type: conference-paper
Abstract: Recently, several methods have been widely reviewed and investigated to estimate the lithium-Ion state of charge due to their high efficiency in terms of improving estimation accuracy. However, we still encounter significant thermal management challenges as they represent one of the main limitations for multiple applications of Li-ion batteries. This study presents a comprehensive comparative evaluation of state-of-the-art – State-of-Charge (SoC) estimation methods for lithium-ion Battery Management Systems (BMS), essential for electric vehicle performance and safety. An accurate SoC estimation is crucial for efficient and robust BMS, guaranteeing precise range prediction, preventing thermal runaway risks, and maximizing battery lifespan under real-world operating conditions.
Institutions: Université Hassan 1er, Cadi Ayyad University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7204117269