SOC Estimation of Vanadium Redox Flow Batteries Based on the ISCSO-ELM Algorithm
Dong Xiao, Boyan Li, Jiawei Shan, Zelin Yan, Jie Huang
Abstract
This study focuses on the stage of charge (SOC) estimation for vanadium redox flow batteries (VFBs), establishing an electrochemical model that provides parameters, including ion concentration. Second, considering the capacity decay of VFBs, an extreme learning machine (ELM) combined with an improved sand cat swarm optimization algorithm, named ISCSO-ELM, is integrated with SOC estimation to predict the battery's SOC more effectively.
Topics & Concepts
VanadiumFlow batteryRedoxState of chargeExtreme learning machineComputer scienceBattery (electricity)ElectrochemistrySwarm behaviourAlgorithmMaterials scienceChemistryArtificial intelligenceElectrodeMetallurgyPower (physics)PhysicsPhysical chemistryQuantum mechanicsArtificial neural networkAdvanced Battery Technologies ResearchAdvanced battery technologies researchAdvancements in Battery Materials