Download PDFOpen PDF in browser

Autonomous vehicle traction subsystem modeling and diagnosis using BG-PCs

16 pagesPublished: January 6, 2018

Abstract

Fault diagnosis is an essential part in the Health Management of autonomous vehicles. Within these vehicles the traction subsystem is a critical component, especially in those exploring planetary surfaces. Recent advances in brushless DC motors has raised the interest in new models and control configurations to integrate them in those vehicles due to their low energy consumption high torque/- mass ratio and low maintenance requirements. In this work we develop a full Bond Graph model of this subsystem, including the brushless motor and the control blocks needed for proper and efficient operation. These models will allow us to perform fault diagnosis with Bond Graph Possible Conflicts as the unifying formalism. We derive the Bond Graph-Possible Conflicts of the system, discussing the viability of the proposal.

Keyphrases: autonomous vehicle, bond graph models, fault diagnosis, lunar rover model, Possible Conflicts, system decomposition methods

In: Marina Zanella, Ingo Pill and Alessandro Cimatti (editors). 28th International Workshop on Principles of Diagnosis (DX'17), vol 4, pages 94--109

Links:
BibTeX entry
@inproceedings{DX'17:Autonomous_vehicle_traction_subsystem,
  author    = {Carlos Alonso-Gonz\textbackslash{}'alez and Anibal Bregon and Belarmino Pulido and Mat\textbackslash{}'ias Nacusse and Sergio Junco},
  title     = {Autonomous vehicle traction subsystem modeling and diagnosis using BG-PCs},
  booktitle = {28th International Workshop on Principles of Diagnosis (DX'17)},
  editor    = {Marina Zanella and Ingo Pill and Alessandro Cimatti},
  series    = {Kalpa Publications in Computing},
  volume    = {4},
  pages     = {94--109},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, http://www.easychair.org},
  issn      = {2515-1762},
  url       = {https://easychair.org/publications/paper/dNM7},
  doi       = {10.29007/qj7v}}
Download PDFOpen PDF in browser