Distributed Node Fault Detection and Tolerance Algorithm for Controller Area Networks

Nath, Nithish N.; Pillay, V. Radhamani; Saisuriyaa, G.

doi:10.1007/978-3-319-23258-4_22

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…Initially, recognising the origins of CAN failure helps to better understand the system‐level diagnosis aims and challenges. The authors in [32, 60, 62, 87] drew attention to several fault sources. In particular, Suwatthikul et al [88] classified these sources into peripheral (wiring and connecters faults) and internal (ECUs faults).…”

Section: Can System‐level Diagnosismentioning

confidence: 99%

“…A comparator circuit was charged to trigger alerts once a difference was detected in controller outputs. In an attempt to avoid its high cost, Nath et al [87] limited the material redundancy application to critical CAN nodes.…”

Section: Can System‐level Diagnosismentioning

confidence: 99%

“…When a feedback is not received in a definite time from a node, it is considered as damaged. Nath et al [87] aimed to reduce the number of detection cycles performed by CDD. Nodes judged as fault‐free are exonerated from checking in the next cycle.…”

Section: Can System‐level Diagnosismentioning

confidence: 99%

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Controller area network reliability: overview of design challenges and safety related perspectives of future transportation systems

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The in‐vehicular networked control system is among the most critical embedded processes. The controller area network (CAN) has prevailed intra‐vehicle communication for decades. Meanwhile, requirements of future transportation systems are expected to emphasise the in‐vehicle communication complexity, which endangers the reliability/safety of the intelligent navigation. At first, this study reviews the recent solutions proposed to overcome the CAN expanding complexity. Challenges that tomorrow's intelligent vehicles may raise for CAN reliability are investigated. The comprehensive coverage of current research efforts to remove the impact of these challenges is presented. Further, the in‐vehicle system reliability of future automated vehicles is also related to the fault diagnosis performances. Hence, different classes of system‐level diagnosis strategies are compared relatively to the requirements of automotive embedded networks. Furthermore, to thoroughly cover CAN reliability engineering issues, focus is given to the automotive validation techniques. The hardware in the loop, real‐time analysis and computer‐aided‐design tools intervene in various phases along the in‐vehicular network life cycle. Parameters that stand behind the efficiency and accuracy of these techniques in validating the new generation of vehicles are analysed. The authors finally draw some deductive predictions about the future directions related to the reliability of the intelligent transportation system in‐vehicular communication.

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