Optimization of Hybrid Electric Cars by Neuro-Fuzzy Networks

  • Authors:
  • Fabio Massimo Frattale Mascioli;Antonello Rizzi;Massimo Panella;Claudia Bettiol

  • Affiliations:
  • INFO-COM Dpt., University of Rome "La Sapienza", Via Eudossiana 18, 00184 Rome, Italy;INFO-COM Dpt., University of Rome "La Sapienza", Via Eudossiana 18, 00184 Rome, Italy;INFO-COM Dpt., University of Rome "La Sapienza", Via Eudossiana 18, 00184 Rome, Italy;University of Rome "Tor Vergata", Via della Ricerca Scientifica 1, 00133 Rome, Italy

  • Venue:
  • WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
  • Year:
  • 2007

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Abstract

In this paper, the problem of the optimization of energetic flows in hybrid electric vehicles is faced. We consider a hybrid electric vehicle equipped with batteries, a thermal engine (or fuel cells), ultracapacitors and an electric engine. The energetic flows are optimized by using a control strategy based on the prediction of short-term and medium-term vehicle states (energy consumption, vehicle load, current route, traffic flow, etc.). The prediction will be performed by a neuro-fuzzy control unit, where the predictive model exploits the robustness of fuzzy logic in managing the said uncertainties and the neural approach as a data driven tool for non-linear control modeling.