Message delay time distribution analysis for controller area network under errors

Controller area network (CAN) is a widely used fieldbus protocol in various industrial applications. To understand the network behavior under errors for the optimal design of networked control systems, the message response time of the CAN network needs to be analyzed. In this study, a novel delay time distribution analysis method for the response messages is proposed when considering errors. In this method the complex message queues are decomposed into typical message patterns and cases. First, a stochastic fault model is developed, and the probability factor is defined to calculate the error distribution. Then the message delay time distribution for the single slave node configuration is analyzed based on the error distribution. Next, based on the delay time distribution analysis of typical patterns and cases, an analysis framework of message delay time distribution for the master/slave configuration is developed. The testbed is constructed and case studies are conducted to demonstrate the proposed methodology under different network configurations. Experimental results show that the delay time distributions calculated by the proposed method agree well with the actual observations

[1]  Manuel Barbosa,et al.  An overview of controller area network , 1999 .

[2]  Robert I. Davis,et al.  Controller area network (CAN) schedulability analysis for messages with arbitrary deadlines in FIFO and work-conserving queues , 2012, 2012 9th IEEE International Workshop on Factory Communication Systems.

[3]  Alberto L. Sangiovanni-Vincentelli,et al.  Using Statistical Methods to Compute the Probability Distribution of Message Response Time in Controller Area Network , 2010, IEEE Transactions on Industrial Informatics.

[4]  Robert I. Davis,et al.  Schedulability analysis for Controller Area Network (CAN) with FIFO queues priority queues and gateways , 2012, Real-Time Systems.

[5]  Alan Burns,et al.  Analysis of hard real-time communications , 1995, Real-Time Systems.

[6]  Liu Lu-yuan Modeling and Analysis of Response Time of CAN Bus Based on Queueing Theory , 2012 .

[7]  Alan Burns,et al.  An extendible approach for analyzing fixed priority hard real-time tasks , 1994, Real-Time Systems.

[8]  Robert I. Davis,et al.  Controller Area Network (CAN) Schedulability Analysis with FIFO Queues , 2011, 2011 23rd Euromicro Conference on Real-Time Systems.

[9]  Qing Chang,et al.  Fault Location for the Intermittent Connection Problems on CAN Networks , 2015, IEEE Transactions on Industrial Electronics.

[10]  Alan Burns,et al.  Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised , 2007, Real-Time Systems.

[11]  Jukka Mäki-Turja,et al.  Integrating mixed transmission and practical limitations with the worst-case response-time analysis for Controller Area Network , 2015, J. Syst. Softw..

[12]  Jukka Mäki-Turja,et al.  Extending Worst Case Response-Time Analysis for Mixed Messages in Controller Area Network With Priority and FIFO Queues , 2014, IEEE Access.

[13]  Alan Burns,et al.  Calculating controller area network (can) message response times , 1994 .

[14]  Thomas Nolte,et al.  Integrating reliability and timing analysis of CAN-based systems , 2002, IEEE Trans. Ind. Electron..

[15]  Robert I. Davis,et al.  Controller Area Network (CAN): Response time analysis with offsets , 2012, 2012 9th IEEE International Workshop on Factory Communication Systems.

[16]  Yeqiong Song,et al.  Worst-case deadline failure probability in real-time applications distributed over controller area network , 2000, J. Syst. Archit..

[17]  Alan Burns,et al.  Timing Analysis of Real-Time Communication Under Electromagnetic Interference , 2005, Real-Time Systems.

[18]  Yong Lei,et al.  Model-Based Detection and Monitoring of the Intermittent Connections for CAN Networks , 2014, IEEE Transactions on Industrial Electronics.