Treffer: Component sizing of a plug-in hybrid electric powertrain via convex optimization

Title:
Component sizing of a plug-in hybrid electric powertrain via convex optimization
Authors:
MURGOVSKI, Nikolce, JOHANNESSON, Lars, SJÖBERG, Jonas, EGARDT, Bo
Source:
Mechatronics (Oxford). 22(1):106-120
Publisher Information:
Oxford: Elsevier, 2012.
Publication Year:
2012
Physical Description:
print, 48 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Mechanical engineering, Génie mécanique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Programmation mathématique, Mathematical programming, Genie mecanique. Construction mecanique, Mechanical engineering. Machine design, Transmissions, Drives, Arbres, accouplements, embrayages, freins, Shafts, couplings, clutches, brakes, Transports terrestres, transports aeriens, transports maritimes, constructions navales, Ground, air and sea transportation, marine construction, Transports et trafic routiers, Road transportation and traffic, Accumulateur électrochimique, Secondary cell, Acumulador electroquímico, Autobus, Bus, Batterie, Battery, Batería, Commande moteur, Engine control, Control motor, Coût exploitation, Operating cost, Costo explotación, Dimensionnement, Dimensioning, Dimensionamiento, Effet non linéaire, Non linear effect, Efecto no lineal, Gestion énergie, Energy management, Gestión energía, Infrastructure transport, Transportation infrastructure, Infraestructura transporte, Machine électrique, Electric machine, Máquina eléctrica, Modélisation, Modeling, Modelización, Méthode heuristique, Heuristic method, Método heurístico, Programmation convexe, Convex programming, Programación convexa, Programmation dynamique, Dynamic programming, Programación dinámica, Programmation non convexe, Non convex programming, Programación no convexa, Programmation partiellement en nombres entiers, Mixed integer programming, Programación mixta entera, Recharge accumulateur, Accumulator recharge, Recarga acumulador, Temps calcul, Computation time, Tiempo computación, Transmission mécanique, Mechanical drive, Transmisión mecánica, Véhicule hybride, Hybrid vehicle, Vehículo híbrido, Battery sizing, Convex optimization, Plug-in hybrid electric vehicle, Power management, Slide-in electric vehicle
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Signals and Systems, Charmers University of Technology, 41296 Gothenburg, Sweden
Viktoria Institute, 41756 Gothenburg, Sweden
ISSN:
0957-4158
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=25595556
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Building. Public works. Transport. Civil engineering

Mechanical engineering. Mechanical construction. Handling

Operational research. Management
Accession Number:
edscal.25595556
Database:
PASCAL Archive

Weitere Informationen

This paper presents a novel convex modeling approach which allows for a simultaneous optimization of battery size and energy management of a plug-in hybrid powertrain by solving a semidefinite convex problem. The studied powertrain belongs to a city bus which is driven along a perfectly known bus line with fixed charging infrastructure. The purpose of the paper is to present the convexifying methodology and validate the necessary approximations by comparing with results obtained by Dynamic Programming when using the original nonlinear, non-convex, mixed-integer models. The comparison clearly shows the importance of the gear and engine on/off decisions, and it also shows that the convex optimization and Dynamic Programming point toward similar battery size and operating cost when the same gear and engine on/off heuristics are used. The main conclusion in the paper is that due to the low computation time, the convex modeling approach enables optimization of problems with two or more state variables, e.g. allowing for thermal models of the components; or to include more sizing variables, e.g. sizing of the engine and the electric machine simultaneously.