Optimal Control for Energy Management of Connected Hybrid Electrical Vehicles - Predictive Connectivity Compared to an Adaptive Algorithm

Hamza Idrissi Hassani Azami, Stéphane Caux, Frederic Messine, Mariano Sans

2018

Abstract

For fuel consumption andCO2 emissions reduction, an optimal predictive control strategy for connected hybrid electrical vehicles is proposed, and evaluated through a comparison to an adaptive strategy. The predictive strategy relies on the future driving conditions that can be predicted by intelligent navigation systems with realtime connectivity. The theory proposed for such real-time optimal predictive algorithm is based on Pontryagin minimum principle, a mathematical principle that provides general solutions for dynamic systems optimization with integral criteria, under given constraints. In this work, the energy management problem is mathematically modeled as an optimal control one, and optimal solutions are synthesized. The predictive optimal real-time algorithm is confronted to the adaptive method. Both control strategies are simulated on different driving cycles. The simulation results show the interest of predictive approaches for hybrid electrical vehicles energy management.

Paper Citation

in Harvard Style

Idrissi Hassani Azami H., Caux S., Messine F. and Sans M. (2018). Optimal Control for Energy Management of Connected Hybrid Electrical Vehicles - Predictive Connectivity Compared to an Adaptive Algorithm.In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-293-6, pages 261-268. DOI: 10.5220/0006668302610268

in Bibtex Style

@conference{vehits18,
author={Hamza Idrissi Hassani Azami and Stéphane Caux and Frederic Messine and Mariano Sans},
title={Optimal Control for Energy Management of Connected Hybrid Electrical Vehicles - Predictive Connectivity Compared to an Adaptive Algorithm},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2018},
pages={261-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006668302610268},
isbn={978-989-758-293-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Optimal Control for Energy Management of Connected Hybrid Electrical Vehicles - Predictive Connectivity Compared to an Adaptive Algorithm
SN - 978-989-758-293-6
AU - Idrissi Hassani Azami H.
AU - Caux S.
AU - Messine F.
AU - Sans M.
PY - 2018
SP - 261
EP - 268
DO - 10.5220/0006668302610268