Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen: http://dx.doi.org/10.25673/35095
Titel: Multiphase mixed-integer nonlinear optimal control of hybrid electric vehicles
Autor(en): Robuschi, Nicolò
Zeile, Clemens
Sager, SebastianIn der Gemeinsamen Normdatei der DNB nachschlagen
Braghin, FrancescoIn der Gemeinsamen Normdatei der DNB nachschlagen
Erscheinungsdatum: 2020
Umfang: 1 Online-Ressource (10 Seiten)
Art: Artikel
Sprache: Englisch
Herausgeber: Elsevier, Amsterdam
URN: urn:nbn:de:gbv:ma9:1-1981185920-352983
Schlagwörter: Hybrid electric vehicles
Hybrid powertrains
Energy management
Nonlinear programming
Mixed-integer nonlinear optimal control
Zusammenfassung: This study considers the problem of computing a non-causal minimum-fuel energy management strategy for a hybrid electric vehicle on a given driving cycle. Specifically, we address the multiphase mixed-integer nonlinear optimal control problem that arises when the optimal gear choice, torque split and engine on/off controls are sought in off-line evaluations. We propose an efficient model by introducing vanishing constraints and a phase specific right-hand side function that accounts for the different powertrain operating modes. The gearbox and driveability requirements translate into combinatorial constraints. These constraints have not been included in previous research; however, they are part of the algorithmic framework for this investigation. We devise a tailored algorithm to solve this problem by extending the combinatorial integral approximation (CIA) technique that breaks down the original mixed-integer nonlinear program into a sequence of nonlinear programs and mixed-integer linear programs, followed by a discussion of its approximation error. Finally, numerical results illustrate the proposed algorithm in terms of solution quality and run time.
URI: https://opendata.uni-halle.de//handle/1981185920/35298
http://dx.doi.org/10.25673/35095
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY 4.0) Creative Commons Namensnennung 4.0 International(CC BY 4.0) Creative Commons Namensnennung 4.0 International
Journal Titel: Automatica
Verlag: Elsevier
Verlagsort: Amsterdam
Band: 123
Heft: 2021
Originalveröffentlichung: 10.1016/j.automatica.2020.109325
Seitenanfang: 1
Seitenende: 10
Enthalten in den Sammlungen:Fakultät für Mathematik (OA)

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
Sager_et al._Automatica_2020.pdfZweitveröffentlichung1.5 MBAdobe PDFMiniaturbild
Öffnen/Anzeigen