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/).
Cite this article
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 -