• DocumentCode
    3588951
  • Title

    Hybrid ARQ for DC-DC Converter Noise in Controller Area Networks

  • Author

    Nakamura, Muneyuki ; Ohara, Mamoru ; Saysanasongkham, Aromhack ; Arai, Masayuki ; Sakai, Kazuya ; Fukumoto, Satoshi

  • Author_Institution
    Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Hino, Japan
  • fYear
    2014
  • Firstpage
    375
  • Lastpage
    379
  • Abstract
    Controller area networks (CANs) are primarily used for communications among electronic devices in an automobile. The noise resistance mechanism defined by the CAN standard accommodates frame/bits errors caused by relatively small noise. However, when it comes to the modern electronic vehicles (EVs) and hybrid vehicles (HVs), the noise level caused by high voltage switching in DC-DC converters could be very large. This significantly reduces the performance of the CAN protocol. To tackle this issue, we first perform noise injection experiments to characterize noise patterns generated by a DC-DC converter. The experiments show that the noise level caused by voltage switching varies from time to time. Therefore, in this paper, we propose an application layer-based hybrid ARQ protocol, which consists of the automatic repeat request (ARQ), forward error correction (FEC), and HALT modes. Depending on the noise level, the proposed protocol selects an appropriate mode. The first prototype implemented on a real CAN node show that our protocol can adaptively switch its mode according to the noise level.
  • Keywords
    DC-DC power convertors; automatic repeat request; controller area networks; forward error correction; protocols; CAN; DC-DC converter noise; FEC; HALT modes; automatic repeat request; controller area networks; forward error correction; hybrid ARQ protocol; noise level; Automatic repeat request; DC-DC power converters; Forward error correction; Noise; Noise level; Protocols; Switches; CANs; DC-DC converter noise; hybrid ARQ;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing Workshops (ICCPW), 2014 43rd International Conference on
  • ISSN
    1530-2016
  • Type

    conf

  • DOI
    10.1109/ICPPW.2014.56
  • Filename
    7103474