SOC - SOH Estimation and Balance Control Based on Event-Triggered Distributed Optimal Kalman Consensus Filter

Xiaohan Fang, Moran Xu and Yuan Fan ()
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Xiaohan Fang: Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
Moran Xu: Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
Yuan Fan: Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China

Energies, 2024, vol. 17, issue 3, 1-19

Abstract: The inconsistency in state-of-charge ( SOC ) for electric vehicle batteries will cause component damage and lifespan reduction of batteries. Meanwhile, the consistency in the state-of-health ( SOH ) also negatively influences the consensus of SOC . To ensure the consensuses of SOC and SOH simultaneously, this paper introduces an innovative distributed optimal Kalman consensus filter (KCF) approach to battery management systems. In addition, at the stage where sensors transmit information to each other, a new event-triggering mechanism (ETM) based on dynamic information is proposed to reduce communication overhead effectively. Theoretical analysis verifies the optimality of the algorithm. By numerical simulations, the proposed event-triggered distributed optimal KCF (ET-DOKCF) method can improve the performance of SOC - SOH estimation and save communication resources.

Keywords: state-of-charge; state-of-health; Kalman filter; consensus; event-triggered (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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