Back close

Fuzzy logic based fault detection of controller area network using microautobox – II

Publication Type : Conference Paper

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics,

Source : 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Institute of Electrical and Electronics Engineers Inc., Volume 2017-January, p.1290-1295 (2017)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042771711&doi=10.1109%2fICACCI.2017.8126019&partnerID=40&md5=b142a03132a81ab3943db72828c283fa

ISBN : 9781509063673

Keywords : Automobile electronic equipment, Automotive industry, Computer circuits, control system synthesis, Controller area network, Controllers, Diagnostic Trouble Codes, Error frames, Fault detection, Fuzzy inference, Fuzzy inference systems, Fuzzy logic, Fuzzy systems, MicroAutoBox - II, Process control

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Mechanical Engineering

Year : 2017

Abstract : In automotive industry the role of electronic system becomes phenomenal. The complexity of the system increases to a larger extend now a days, and hence the diagnostics is also very much essential. The diagnostics can be mainly done in sensors/actuators, processors and on communication medium. Here, we have presented a fault detection system using fuzzy logic for the CAN (Controller Area Network). Whenever a fault occurred in the CAN, a Diagnostic Trouble Code (DTC) corresponding to that fault is recorded in an ECU (Electronic Controlled Unit) which is capable of detecting distinct faults only. In this paper we have proposed a prototype of an ECU using MicroAutoBox ' II hardware, with a CAN interface to detect faults induced into the network. Fuzzy engine within the ECU is capable of identifying the faults based on the number of error frames (Ef), ranges from 0-80 as well as change in differential bus resistance (Rdiff(total)). The validation is done based on the rule created in the fuzzy system.

Cite this Research Publication : A. Tamrakar, Adasrh, S., and Dr. K. I. Ramachandran, “Fuzzy logic based fault detection of controller area network using microautobox - II”, in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, 2017, vol. 2017-January, pp. 1290-1295.

Admissions Apply Now