Selection of Control Algorithms for Hybrid Electric Vehicle

DOI

10.2991/aime-17.2017.116How to use a DOI?

Keywords

hybrid electric vehicle, series hybrid, power installation, control strategy, neural network, fuel consumption

Abstract

In the paper the main problems of power control strategies in series hybrid electric vehicles are discussed. Classical regulators are compared with neural networks, their advantages and disadvantages are shown. Experimental data sources for training neural networks and proofing results are suggested and limitations of their application scope have been considered. It is shown that improving the quality of the regulation of electric drives by using a neural network controller can lead to an increase in the reliability of regulatory systems, which subsequently leads to the saving of electricity and resources. Using the experimental data it makes possible to construction and synthesis of a neural regulator. Thus the following research directions are evaluation of optimal neural network structure and modeling its performance

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - V. N. Anosov
AU  - S. A. Saidov
AU  - M. V. Yaroslavcev
PY  - 2017/07
DA  - 2017/07
TI  - Selection of Control Algorithms for Hybrid Electric Vehicle
BT  - Proceedings of the International Conference "Actual Issues of Mechanical Engineering" 2017 (AIME 2017)
PB  - Atlantis Press
SP  - 715
EP  - 719
SN  - 2352-5401
UR  - https://doi.org/10.2991/aime-17.2017.116
DO  - 10.2991/aime-17.2017.116
ID  - Anosov2017/07
ER  -