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Model Based Change Detection Approach For Sensor Fault Identification in Battery Packs

  • Luis Herrera
  • , Anthony Frierson
  • , Bang Hung Tsao
  • , Gregory Horrocks
  • , Joseph Fellner
  • University of Dayton
  • Air Force Research Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, a model based sensor fault detection strategy is proposed for series connected Li-Ion cells. A state space model of the equivalent circuit of each cell is first derived and a Luenberger observer is designed for residual generation, which plays a crucial role in the fault detection process. Since the residual is influenced by the fault's magnitude, it may result in subtle changes that are challenging to identify. Therefore, a Quickest Change Detection (QCD) approach is presented to further process the residual and ensure sensor malfunctions are not missed. The Cumulative Sum algorithm is then used to solve the QCD problem. Simulation results are then presented to verify the feasibility of the proposed method.

Original languageEnglish
Title of host publicationNAECON 2023 - IEEE National Aerospace and Electronics Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9798350338782
DOIs
StatePublished - 2023
Event2023 IEEE National Aerospace and Electronics Conference, NAECON 2023 - Dayton, United States
Duration: Aug 28 2023Aug 31 2023

Publication series

NameProceedings of the IEEE National Aerospace Electronics Conference, NAECON
ISSN (Print)0547-3578
ISSN (Electronic)2379-2027

Conference

Conference2023 IEEE National Aerospace and Electronics Conference, NAECON 2023
Country/TerritoryUnited States
CityDayton
Period08/28/2308/31/23

Keywords

  • Fault detection and identification
  • Luenberger observer
  • Quickest Change Detection
  • Residual generation

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