@inproceedings{486c1a8667fc4d7aa74dd4d039a73970,
title = "Review on sensors fault diagnosis and fault-tolerant techniques for lithium ion batteries in electric vehicles",
abstract = "Lithium ion batteries have been widely used in electric vehicles (EVs) due to their high power density, high energy density and long cycle life. Lithium ion battery systems in EVs require high voltage to meet power and energy demand. They consist of a large number of cells connected in series or parallel combination of both. A battery management system (BMS) is used to ensure safe and reliable operation of EV battery systems. The normal operation of the BMS highly depends on the installed sensors which provide the BMS the information of current, voltage and temperature for maintaining the battery systems in the safe working condition. Thus, it is critical for the BMS to diagnose these sensor faults and take measures to mitigate the influences of these sensor faults on the operation of EVs in real time. This paper will comprehensively review recent techniques for sensors fault diagnosis and tolerance for lithium ion batteries in EVs from the perspectives of model-based approaches.",
keywords = "electric vehicles, fault tolerance, lithium ion batteries, sensors fault diagnosis",
author = "Rui Xiong and Quanqing Yu and Weixiang Shen",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018 ; Conference date: 31-05-2018 Through 02-06-2018",
year = "2018",
month = jun,
day = "26",
doi = "10.1109/ICIEA.2018.8397751",
language = "English",
series = "Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "406--410",
booktitle = "Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018",
address = "United States",
}
