Adaptive Nonlinear Model-Based Fault Diagnosis of Li-Ion Batteries

Autor:	Sohel Anwar, Amardeep Sidhu, Afshin Izadian
Rok vydání:	2015
Předmět:	Battery (electricity) Engineering business.industry Hardware_PERFORMANCEANDRELIABILITY Kalman filter Fault (power engineering) Residual Signature (logic) Stuck-at fault Nonlinear system Control and Systems Engineering Control theory Equivalent circuit Electrical and Electronic Engineering business
Zdroj:	IEEE Transactions on Industrial Electronics. 62:1002-1011
ISSN:	1557-9948 0278-0046
DOI:	10.1109/tie.2014.2336599
Popis:	In this paper, an adaptive fault diagnosis technique is used in Li-ion batteries. The diagnosis process consists of multiple nonlinear models representing signature faults, such as overcharge and overdischarge, causing significant model parameter variation. The impedance spectroscopy of a Li-ion $(\hbox{LiFePO}_{4})$ cell is used, along with the equivalent circuit methodology, to construct nonlinear battery signature-fault models. Extended Kalman filters are utilized to estimate the terminal voltage of each model and to generate residual signals. The residual signals are used in the multiple-model adaptive estimation technique to generate probabilities that determine the signature faults. It can be seen that, by using this method, signature faults can be detected accurately, thus providing an effective way of diagnosing Li-ion battery failure.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d9e606a19de3a426cc0947c4c74b4b8b https://doi.org/10.1109/tie.2014.2336599 Zobrazit plný text záznamu