DocumentCode
46147
Title
Adaptive Fault Diagnosis Algorithm for Controller Area Network
Author
Kelkar, Supriya ; Kamal, Raj
Author_Institution
Comput. Eng. Dept., Cummins Coll. of Eng. for Women, Pune, India
Volume
61
Issue
10
fYear
2014
fDate
Oct. 2014
Firstpage
5527
Lastpage
5537
Abstract
A controller area network (CAN)-based distributed system may develop faults at run-time. These faults need to be detected and diagnosed. This paper proposes a new algorithm named adaptive fault diagnosis algorithm for CAN (AFDCAN). It is designed for low-cost resource-constrained distributed embedded systems. The proposed algorithm detects all faulty nodes on the CAN. It allows new node entry and reentry of repaired faulty nodes during a diagnostic cycle. AFDCAN is found to provide high fault tolerance and to ensure reliable communication. It uses single-channel communication deploying the bus-based standard CAN protocol. A hardware implementation of the proposed algorithm has been used to obtain the results. The results show that the proposed algorithm diagnoses all faults in the system. Analysis of the proposed algorithm proves that the algorithm uses a definite and bounded number of testing rounds and messages to complete one diagnostic cycle.
Keywords
controller area networks; embedded systems; fault diagnosis; protocols; AFDCAN algorithm; CAN-based distributed system; adaptive fault diagnosis algorithm; bus-based standard CAN protocol; controller area network; diagnostic cycle; fault tolerance; low-cost resource-constrained distributed embedded systems; node entry; node reentry; Adaptive systems; Algorithm design and analysis; Automotive engineering; Fault detection; Fault diagnosis; Principal component analysis; Protocols; Adaptive algorithms; automotive applications; controller area network (CAN) protocol; distributed networks; distributed systems; fault diagnosis; real-time systems;
fLanguage
English
Journal_Title
Industrial Electronics, IEEE Transactions on
Publisher
ieee
ISSN
0278-0046
Type
jour
DOI
10.1109/TIE.2013.2297296
Filename
6701172
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