Review of Fusion Prognostics for Lithium-Ion Batteries - Current State and Future Challenges

Nneka Daniel, Stoyan Stoyanov, Christopher Bailey, David Flynn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


The rapid increase in deployment of Lithium-ion (Li-ion) batteries across a wide range of applications such as automotive, robotics, energy networks and consumer products, present specific challenges to the optimal performance and reliability of Li-ion batteries. Charge-discharge cycles are the main factors degrading Li-ion battery capacity, thus directly affecting their lifetime. Studies on prognostic approaches for predicting state of health (SOH) and remaining useful life (RUL) of batteries aim at supporting their optimal operation and well-managed usage. This paper presents a review of state-of-the-art hybrid/fusion prognostics methods for assessing the SOH/RUL of Li-ion batteries, aiming to leverage the advantage of each to achieve a more accurate and/or more computationally efficient model. The respective underpinning fusion prognostics methods and algorithms for predicting SOH/RUL of Li-ion battery are outlined and discussed. A comparative analysis outlines their capabilities with respect to critical criteria, such as error and uncertainty handling capacity. The benefits and challenges of using these approaches are highlighted, as well as opportunities for continuing research into fusion prognostics approaches for Li-ion batteries posed by emerging applications.
Original languageEnglish
Title of host publication2021 44th International Spring Seminar on Electronics Technology (ISSE)
ISBN (Electronic)9781665414777
ISBN (Print)9781665430616
Publication statusPublished - 1 Jul 2021
Event44th International Spring Seminar on Electronics Technology 2021 - Bautzen, Germany
Duration: 5 May 20219 May 2021


Conference44th International Spring Seminar on Electronics Technology 2021
Abbreviated titleISSE 2021


  • Prognostics
  • Lithium-ion batteries
  • uncertainty analysis
  • Computational efficiency
  • Prediction algorithms
  • Computational modeling

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Electrical and Electronic Engineering


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