In the last years, the drift toward electric mobility and the need for renewable energy penetration placed the batteries and their control in a prominent position. A critical parameter for the battery management system (BMS) is the state of charge (SOC) of the battery pack. This paper gives an overview of the trends of the last 5 years of SOC estimation, using data-driven estimation methods. Due to the evolution of electronic materials and the abundance of available data, data-driven methods became popular and advantageous.

An Overview of Data-Driven Methods for the Online State of Charge Estimation

Eleftheriadis P.;Dolara A.;Leva S.
2022-01-01

Abstract

In the last years, the drift toward electric mobility and the need for renewable energy penetration placed the batteries and their control in a prominent position. A critical parameter for the battery management system (BMS) is the state of charge (SOC) of the battery pack. This paper gives an overview of the trends of the last 5 years of SOC estimation, using data-driven estimation methods. Due to the evolution of electronic materials and the abundance of available data, data-driven methods became popular and advantageous.
2022
2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe)
978-1-6654-8537-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1223594
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