Sensor Fault Detection, Isolation, and Estimation in Lithium-Ion Batteries

Satadru Dey, Sara Mohon, Pierluigi Pisu, Beshah Ayalew

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

In battery management systems (BMSs), real-time diagnosis of sensor faults is critical for ensuring the safety and reliability of the battery. For example, a current sensor fault leads to erroneous estimates of state of charge and other parameters, which in turn affects the control actions in the BMS. A temperature sensor fault may lead to ineffective thermal management. In this brief, a model-based diagnostic scheme is presented that uses sliding mode observers designed based on the electrical and thermal dynamics of the battery. It is analytically shown how the extraction of the equivalent output error injection signals on the sliding manifolds enables the detection, the isolation, as well as the estimation of the temperature, voltage, and current sensor faults. This brief includes simulation and experimental studies to demonstrate and evaluate the effectiveness of the proposed scheme. Discussions are also included on the effects of uncertainty and on threshold design.

Original languageEnglish (US)
Article number7437404
Pages (from-to)2141-2149
Number of pages9
JournalIEEE Transactions on Control Systems Technology
Volume24
Issue number6
DOIs
StatePublished - Nov 2016

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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