Collecting Big Data from Automotive ECUs beyond the CAN Bandwidth for Fault Visualization
Joint Authors
Lee, Jeong-Woo
Choi, Ki-Yong
Lee, Jung-Won
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Telecommunications Engineering
Abstract EN
A hardware-in-the-loop (HiL) test is performed to verify the software functions mounted on automotive electronic control units (ECUs).
However, the characteristics of HiL test limit the usage of common debugging techniques.
Meanwhile, the logs of how the program uses memory can be utilized as debugging information collected by the controller area network (CAN).
However, when the 32 KB memory is observed with 10 ms period, about 96% of the data on each cycle is lost, since the CAN only can transfer 1.25 KB of data at each cycle.
Therefore, to overcome the above limitations, in this study, the memory is divided into multiple regions to transmit generated data via CAN.
Next, the simulation is repeated for the each divided regions to obtain the different areas in each simulation.
The collected data can be visualized as update information in each cycle and the cumulative number of updates.
Through the proposed method, the ECU memory information during the HiL test was successfully collected using the CAN; the transmission is completed without any loss of data.
In addition, the data was visualized in images containing the update information of the memory.
These images contribute to shortening the debugging time for developers and testers.
American Psychological Association (APA)
Lee, Jeong-Woo& Choi, Ki-Yong& Lee, Jung-Won. 2017. Collecting Big Data from Automotive ECUs beyond the CAN Bandwidth for Fault Visualization. Mobile Information Systems،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1189059
Modern Language Association (MLA)
Lee, Jeong-Woo…[et al.]. Collecting Big Data from Automotive ECUs beyond the CAN Bandwidth for Fault Visualization. Mobile Information Systems No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1189059
American Medical Association (AMA)
Lee, Jeong-Woo& Choi, Ki-Yong& Lee, Jung-Won. Collecting Big Data from Automotive ECUs beyond the CAN Bandwidth for Fault Visualization. Mobile Information Systems. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1189059
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189059