Advanced filtering technique for battery failure prognostics

Sara Kohtz, Pingfeng Wang

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


Prognostics and health management (PHM) has become a prominent field with an emphasis on the analysis of dynamic system degradation, with the objective of enhancing decision making for contingency improvement. The fusion of data-driven and model-based approaches have caused applications of PHM to require extensive concentration in forecasting and filtering techniques. In recent studies, the combination of dynamic system modeling and filtering methods have shown to be extremely effective for PHM applications. Moreover, methods utilizing artificial intelligence (AI) for system modeling, combined with a filtering method for estimation, have shown promising results. This study aims to provide insight to the optimal method of modeling and estimation particularly for PHM concentrations and develop a general prognostics platform using advanced filtering techniques coupled with artificial intelligence based dynamic system modelers. The specific application is a battery dynamic system, with the parameters of interest being state of charge (SOC) and state of health (SOH).

Original languageEnglish (US)
Title of host publicationProceedings of the 2020 IISE Annual Conference
EditorsL. Cromarty, R. Shirwaiker, P. Wang
PublisherInstitute of Industrial and Systems Engineers, IISE
Number of pages6
ISBN (Electronic)9781713827818
StatePublished - 2020
Event2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020 - Virtual, Online, United States
Duration: Nov 1 2020Nov 3 2020

Publication series

NameProceedings of the 2020 IISE Annual Conference


Conference2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020
Country/TerritoryUnited States
CityVirtual, Online


  • Battery
  • Filter
  • Prognostics
  • State of Charge
  • State of Health

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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