An improved variable forgetting factor sliding window recursive least square-chaotic firefly optimization method for key dynamic parameters identification of lithium-ion batteries with hybrid electrochemical empirical and circuit modeling
Puntos clave
Dynamic parameter identification of lithium-ion batteries enhances modeling precision using recursive least square.
The method integrates chaotic firefly optimization for more efficient prediction of battery behavior.
Assessment of electrochemical and circuit modeling highlights potential advancements in battery management systems.
Highlights the need for further research to validate improvements in real-world applications for battery technologies.
An improved variable forgetting factor sliding window recursive least square-chaotic firefly optimization method for key dynamic parameters identification of lithium-ion batteries with hybrid electrochemical empirical and circuit modeling | Synapse