文章基本信息

标题：Clustering-based Sensor Placement for Thermal Fault Diagnostics in Large-Format Batteries ⁎
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作者：Sara Sattarzadeh ; Tanushree Roy ; Satadru Dey 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：20
页码：381-386
DOI：10.1016/j.ifacol.2021.11.203
语种：English
出版社：Elsevier
摘要：AbstractFault detectability and isolability are essential for realizing online diagnostic algorithms in large format batteries used in safety-critical applications. As sensor locations determine such detectability and isolability, sensor placement becomes a crucial task to enable diagnostics. Limited sensing availability in battery systems makes this issue even more challenging. In this setting, we propose an offline sensor placement framework to maximize the fault detectability and isolability based on limited number of given sensors. Within this framework, we combine physics-based thermal model, fault-to-output transfer functions, and data-driven Evidential C-means (ECM) clustering to determine the essential sensor locations. The performance of the proposed framework is demonstrated via simulation studies on a pouch type battery.
关键词：KeywordsBatteriesThermal faultSensor placementFault detectabilityFault isolability