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Title: A PCGL-based data loading algorithm for electrical vehicle time-triggered CAN

Authors: Yingji Liu; Shuju Wang; Chen Ding; Yu Yao; Hongwen Xia; Jie Xia

Addresses: Key Laboratory of Operation Safety Technology on Transport Vehicles, Ministry of Transport, Beijing, China ' School of Mechanical Engineering, Liaoning Technical University, Fuxin, China ' Department of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing, China ' Key Laboratory of Operation Safety Technology on Transport Vehicles, Ministry of Transport, Beijing, China ' Key Laboratory of Operation Safety Technology on Transport Vehicles, Ministry of Transport, Beijing, China ' Department of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing, China

Abstract: In this paper, a period correlative group loading (PCGL)-based algorithm is proposed specifically for the real-time communication of random messages in electrical vehicle TTCAN networks. By compressing the bandwidth radio of the synchronous phase, the real-time response of event-triggered messages is accelerated. The PCGL-based scheduling approach will be detailed and described. The proposed method is tested on the scheduling for SAE electrical vehicle message standard and the results show that, on the premise of guaranteeing the real-time efficiency of time-triggered messages, the real-time efficiency of event-triggered messages is significantly improved.

Keywords: data loading; electrical vehicle; time-triggered CAN; period correlative group.

DOI: 10.1504/IJMNDI.2018.090152

International Journal of Mobile Network Design and Innovation, 2018 Vol.8 No.1, pp.1 - 6

Available online: 20 Feb 2018 *

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