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http://dx.doi.org/10.3795/KSME-B.2017.41.11.735

Model - Based Sensor Fault Detection and Isolation for a Fuel Cell in an Automotive Application  

Han, Jaeyoung (Dept. of Mechanical Engineering, Chungnam Nat'l Univ.)
Kim, Younghyeon (Dept. of Mechanical Engineering, Chungnam Nat'l Univ.)
Yu, Sangseok (Dept. of Mechanical Engineering, Chungnam Nat'l Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers B / v.41, no.11, 2017 , pp. 735-742 More about this Journal
Abstract
In this study, an effective model-based sensor fault detection methodology that can detect and isolate PEM temperature sensors fault is introduced. In fuel cell vehicle operation process, the stack temperature affects durability of a fuel cell. Thus, it is important for fault algorithm to detect the fault signals. The major objective of sensor fault detection is to guarantee the healthy operations of the fuel cell system and to prevent the stack from high temperature and low temperature. For the residual implementation, parity equation based on the state space is used to detect the sensors fault as stack temperature and coolant inlet temperature, and residual is compared with the healthy temperature signals. Then the residuals are evaluated by various fault scenarios that detect the presence of the sensor fault. In the result, the designed in this study fault algorithm can detect the fault signal.
Keywords
Fuel Cell; Model-Based; Sensor Fault; Fault Detection; Residual; Controller;
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