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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2200592


Availability evaluation of controller area network under the Influence of intermittent connection fault


Author(s):  Longkai WANG, Leiming ZHANG, Yong LEI

Affiliation(s):  State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   lkwang@zju.edu.cn, smezlm2010@126.com, ylei@zju.edu.cn

Key Words:  Controller area network, Intermittent connection fault, Arrival rate, DSPN, Availability evaluation


Longkai WANG, Leiming ZHANG, Yong LEI. Availability evaluation of controller area network under the Influence of intermittent connection fault[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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Abstract: 
controller area networks (CANs), as one of the widely used fieldbuses in the industry, has been extended to the automation field with strict standards for safety and reliability. In practice, factors such as fatigue and insulation wear of the cables can cause intermittent connection (IC) faults to occur frequently in the CAN, which will affect the dynamic behavior and the safety of the system. Hence, quantitatively evaluating the performance of the CAN under the influence of IC faults is crucial to real-time health monitoring of the system. In this paper, a novel methodology for real-time quantitative evaluation of CAN availability when considering IC faults is proposed, which calculates the system availability parameter based on the network states transition model. First, the causal relationship between IC fault and network error response is constructed, based on which the IC fault arrival rate is estimated. Second, the states of the network considering IC faults are analyzed and the Deterministic and Stochastic Petri Net (DSPN) model is applied to describe the transition relationship of the states. Then, the parameters of the DSPN model are determined and the availability of the system is calculated based on the probability distribution and physical meaning of markings in the DSPN model. A testbed is constructed and case studies are conducted to verify the proposed methodology under various experimental setups. Experimental results show that the estimation results using the proposed method agree well with the actual values.

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