CLC number: TP277
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-06-11
Cited: 0
Clicked: 6682
Lei-ming ZHANG, Yi-chao SUN, Yong LEI. Message delay time distribution analysis for controller area network under errors[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 760-772.
@article{title="Message delay time distribution analysis for controller area network under errors",
author="Lei-ming ZHANG, Yi-chao SUN, Yong LEI",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="20",
number="6",
pages="760-772",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700815"
}
%0 Journal Article
%T Message delay time distribution analysis for controller area network under errors
%A Lei-ming ZHANG
%A Yi-chao SUN
%A Yong LEI
%J Frontiers of Information Technology & Electronic Engineering
%V 20
%N 6
%P 760-772
%@ 2095-9184
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700815
TY - JOUR
T1 - Message delay time distribution analysis for controller area network under errors
A1 - Lei-ming ZHANG
A1 - Yi-chao SUN
A1 - Yong LEI
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 6
SP - 760
EP - 772
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1700815
Abstract: 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.
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