Authors:
Yacine Gaoua
1
;
Stéphane Caux
2
and
Pierre Lopez
3
Affiliations:
1
INPT, UPS, CNRS and Univ de Toulouse, France
;
2
INPT and UPS, France
;
3
CNRS and Univ de Toulouse, France
Keyword(s):
Energy Management, Modeling, Combinatorial Optimization, Off-line Optimization, Dynamic Programming, Quasi-Newton Method, Branch-and-Cut Method, Operating Point, Energy Losses, Linearization.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Energy and Environment
;
Industrial Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Pattern Recognition
;
Software Engineering
;
Symbolic Systems
Abstract:
Minimizing the consumption of hydrogen by a fuel cell system in a hybrid vehicle can reduce its environmental impact and increase its autonomy. However an intelligent management of power distribution is essential to meet the demand of the powertrain. The characteristics of the sources constituting the energy chain of the hybrid vehicle (efficiency and energy losses) make the mathematical model nonlinear. Solution methods such as Dynamic Programming and Quasi-Newton which have so far been developed in previous works give satisfactory results but with very large computation times. In this paper, a new combinatorial model is proposed and a Branch-and-Cut method is developed to solve the problem to optimality. This approach leads to drastically reduced computation times.