2023
DOI: 10.3390/su15065014
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Review of State Estimation and Remaining Useful Life Prediction Methods for Lithium–Ion Batteries

Abstract: The accurate estimation of the state of charge, the state of health and the prediction of remaining useful life of lithium–ion batteries is an important component of battery management. It is of great significance to prolong battery life and ensure the reliability of the battery system. Many researchers have completed a large amount of work on battery state evaluation and RUL prediction methods and proposed a variety of methods. This paper first introduces the definition of the SOC, the SOH and the existing es… Show more

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Cited by 37 publications
(5 citation statements)
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“…Accurate capacity prediction not only ensures the safe operation of the battery but also extends its service life [9]. To this end, researchers have proposed various prediction methods, including traditional modelling methods [10], data-driven methods [11], and deep learning methods [12].…”
Section: Introductionmentioning
confidence: 99%
“…Accurate capacity prediction not only ensures the safe operation of the battery but also extends its service life [9]. To this end, researchers have proposed various prediction methods, including traditional modelling methods [10], data-driven methods [11], and deep learning methods [12].…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, the state of charge of a battery at a given time, i.e., SOC(t), is defined as the ratio between the remaining charge in the battery at a given time, i.e., Q remaining (t), expressed in Coulombs [C], and the reference charge of a fresh battery (usually given by the cell manufacturer), i.e., Q ref [25], as follows:…”
Section: Methodsmentioning
confidence: 99%
“…In addition, there are the Kalman filter (KF) and its derivative algorithms, including the extended Kalman filter (EKF) [8], CDKF [9], H-infinity filter [10], adaptive Kalman filter [11,12] and other algorithms. The KF can better resist noise interference and has low dependence on the initial value [13], so the KF is recognized as the most widely employed method in SOC estimation.…”
Section: Introductionmentioning
confidence: 99%