2021
DOI: 10.1049/stg2.12013
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Smooth particle filter‐based likelihood approximations for remaining useful life prediction of Lithium‐ion batteries

Abstract: Accurate prediction of the remaining useful life (RUL) in Lithium-ion batteries (LiBs) is a key aspect of managing its health, in order to promote reliable and secure systems, and to reduce the need for unscheduled maintenance and costs. Recent work on RUL prediction has largely focused on refining the accuracy and reliability of the RUL prediction. The author introduces a new online RUL prediction for LiB using smooth particle filter (SPF)-based likelihood approximation method. The proposed algorithm can accu… Show more

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Cited by 8 publications
(2 citation statements)
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References 34 publications
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“…Papers [1–3] of this Special Issue are in this category. Paper [1] by Daniel Morales et al., introduces a model‐based observer for the calculation of the SoC of water‐based Thermal Energy Storage system for district heating and cooling systems (DHCS) that acts as a buffer between supply and demand schedules.…”
Section: Technology‐related Aspects Of Energy Storage Systemsmentioning
confidence: 99%
See 1 more Smart Citation
“…Papers [1–3] of this Special Issue are in this category. Paper [1] by Daniel Morales et al., introduces a model‐based observer for the calculation of the SoC of water‐based Thermal Energy Storage system for district heating and cooling systems (DHCS) that acts as a buffer between supply and demand schedules.…”
Section: Technology‐related Aspects Of Energy Storage Systemsmentioning
confidence: 99%
“…Paper [3] by El‐Dalahmeh, et al., proposes a new and interesting method on estimating the Remaining Useful Life of Lithium‐Ion Batteries based on a Smooth Particle Filter. This method appears to be more effective than traditional methods like Particle Filter Unscented Particle Filter.…”
Section: Technology‐related Aspects Of Energy Storage Systemsmentioning
confidence: 99%