Authors:
Hamza Idrissi Hassani Azami
1
;
Stéphane Caux
2
;
Frederic Messine
2
and
Mariano Sans
3
Affiliations:
1
University of Toulouse and French Environment and Energy Management Agency (ADEME), France
;
2
University of Toulouse, France
;
3
Continental Automotive SaS, France
Keyword(s):
Energy Management, Hybrid Electrical Vehicle, Optimal Control, Pontryagin Minimum Principle, Shooting Algorithms.
Related
Ontology
Subjects/Areas/Topics:
Power Management
;
Sensor Networks
;
Wireless Information Networks
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
ma
nagement.
(More)