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      Review on the Selection of Health Indicator for Lithium Ion Batteries

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      Machines
      MDPI AG

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          Abstract

          Scientifically and accurately predicting the state of health (SOH) and remaining useful life (RUL) of batteries is the key technology of automotive battery management systems. The selection of the health indicator (HI) that characterizes battery aging affects the accuracy of the prediction model construction, which in turn affects the accuracy of SOH and RUL estimation. Therefore, this paper analyzes the current status of HI selection for lithium-ion batteries by systematically reviewing the existing literature on the selection of HIs. According to the relationship between HI and battery aging, battery HI can be divided into two categories: direct HI and indirect HI. The capacity and internal resistance of the battery can directly represent the aging degree of the battery and are the direct HIs of the battery. Indirect HIs refer to characteristic parameters extracted from battery charge and discharge data that can characterize the degree of battery aging. This paper analyzes and summarizes the advantages and disadvantages of various HIs and indirect HIs commonly used in current research, providing useful support and reference for future researchers in selecting HIs to characterize battery aging. Finally, in view of the capacity regeneration phenomenon in the aging process of the battery, the selection direction of future HI is proposed.

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          Most cited references83

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          A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve

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            Towards a smarter battery management system: A critical review on battery state of health monitoring methods

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              Modeling and Applications of Electrochemical Impedance Spectroscopy (EIS) for Lithium-ion Batteries

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                MACHCV
                Machines
                Machines
                MDPI AG
                2075-1702
                July 2022
                June 24 2022
                : 10
                : 7
                : 512
                Article
                10.3390/machines10070512
                b7e51f0a-a3b7-441a-b3d7-507c03ca307f
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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