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Abstract: controller area networks (CANs), as one of the widely used fieldbuses in the industry, have 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 is proposed for real-time quantitative evaluation of CAN availability when considering IC faults, with the system availability parameter being calculated based on the network state 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 obtained using the proposed method agree well with the actual values.

间歇性连接故障影响下的控制器局域网可用性评估

[1]Bosch R, 1991. CAN Specification Version 2.0. Technical Report. Robert Bousch GmbH, Postfach, Gerlingen, Germany.

[2]Chen JX, Luo F, Sun ZC, 2006. Reliability analysis of CAN nodes under electromagnetic interference. IEEE Int Conf on Vehicular Electronics and Safety, p.367-371.

[3]Choi H, Kulkarni VG, Trivedi KS, 1993. Transient analysis of deterministic and stochastic Petri nets. Proc 14^th Int Conf on Application and Theory of Petri Nets, p.166-185.

[4]Choi H, Kulkarni VG, Trivedi KS, 1994. Markov regenerative stochastic Petri nets. Perform Eval, 20(1-3):337-357.

[5]Dos Santos Roque A, Jazdi N, De Freitas EP, et al., 2022. A fault modeling based runtime diagnostic mechanism for vehicular distributed control systems. IEEE Trans Intell Transp Syst, 23(7):7220-7232.

[6]Gaujal B, Navet N, 2005. Fault confinement mechanisms on CAN: analysis and improvements. IEEE Trans Veh Technol, 54(3):1103-1113.

[7]Gujarati A, Brandenburg BB, 2015. When is CAN the weakest link? A bound on failures-in-time in CAN-based real-time systems. IEEE Real-Time Systems Symp, p.249-260.

[8]Hansson HA, Nolte T, Norstrom C, et al., 2002. Integrating reliability and timing analysis of CAN-based systems. IEEE Trans Ind Electron, 49(6):1240-1250.

[9]Herpel T, Hielscher KS, Klehmet U, et al., 2009. Stochastic and deterministic performance evaluation of automotive CAN communication. Comput Netw, 53(8):1171-1185.

[10]Lei Y, Djurdjanovic D, Ni J, 2010. DeviceNet reliability assessment using physical and data link layer parameters. Qual Reliab Eng Int, 26(7):703-715.

[11]Mary GI, Alex ZC, Jenkins L, 2013. Reliability analysis of controller area network based systems—a review. Int J Commun Netw Syst Sci, 6(4):155-166.

[12]Murata T, 1989. Petri nets: properties, analysis and applications. Proc IEEE, 77(4):541-580.

[13]Navet N, Song YQ, 2001. Validation of in-vehicle real-time applications. Comput Ind, 46(2):107-122.

[14]Navet N, Song YQ, Simonot F, 2000. Worst-case deadline failure probability in real-time applications distributed over controller area network. J Syst Archit, 46(7):607-617.

[15]Pohren DH, dos Santos Roque A, Kranz TAI, et al., 2020. An analysis of the impact of transient faults on the performance of the CAN-FD protocol. IEEE Trans Ind Electron, 67(3):2440-2449.

[16]Sun YC, Yang F, Lei Y, 2015. Message response time distribution analysis for controller area network containing errors. Chinese Automation Congress, p.1052-1057.

[17]Syed WA, Khan S, Phillips P, et al., 2013. Intermittent fault finding strategies. Proc CIRP, 11:74-79.

[18]Wang ZY, Guo XS, Yu CQ, 2010. Research of fault-tolerant redundancy and fault diagnosis technology based on CAN. 2^nd Int Conf on Advanced Computer Control, p.287-291.

[19]Zago GM, de Freitas EP, 2018. A quantitative performance study on CAN and CAN FD vehicular networks. IEEE Trans Ind Electron, 65(5):4413-4422.

[20]Zhang LM, Tang LH, Yang F, et al., 2015. CAN node reliability assessment using segmented discrete time Markov chains. IEEE Int Conf on Automation Science and Engineering, p.231-236.

[21]Zhang LM, Tang LH, Lei Y, 2017a. Controller area network node reliability assessment based on observable node information. Front Inform Technol Electron Eng, 18(5):615-626.

[22]Zhang LM, Yuan Y, Lei Y, 2017b. Data driven CAN node reliability assessment for manufacturing system. Chin J Mech Eng, 30(1):190-199.

[23]Zhang LM, Sun YC, Lei Y, 2019. Message delay time distribution analysis for controller area network under errors. Front Inform Technol Electron Eng, 20(6):760-772.