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Model-Based Adaptive Fault Diagnosis in Lithium Ion Batteries: A Comparison of Linear and Nonlinear Approaches
Technical Paper
2017-01-1192
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
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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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, https://doi.org/10.4271/2017-01-1192.Data Sets - Support Documents
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