Model-Based Adaptive Fault Diagnosis in Lithium Ion Batteries: A Comparison of Linear and Nonlinear Approaches

Paper #:
  • 2017-01-1192

Published:
  • 2017-03-28
DOI:
  • 10.4271/2017-01-1192
Citation:
Sidhu, A., Izadian, A., and Anwar, S., "Model-Based Adaptive Fault Diagnosis in Lithium Ion Batteries: A Comparison of Linear and Nonlinear Approaches," SAE Technical Paper 2017-01-1192, 2017, doi:10.4271/2017-01-1192.
Pages:
8
Abstract:
In this paper, multiple-model adaptive estimation techniques have been successfully applied to fault detection and identification in lithium-ion batteries. The diagnostic performance of a battery depends greatly on the modeling technique used in representing the system and the associated faults under investigation. Here, both linear and non-linear battery modeling techniques are evaluated and the effects of battery model and noise estimation on the over-charge and over-discharge fault diagnosis performance are studied. Based on the experimental data obtained under the same fault scenarios for a single cell, the non-linear model based detection method is found to perform much better in accurately detecting the faults in real time when compared to those using linear model based method.
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