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

2017-01-1192

03/28/2017

Features
Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
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.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-1192
Pages
8
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.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-1192
Content Type
Technical Paper
Language
English