Article | Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017 | Nonlinear Model Predictive Control of a Thermal Management System for Electrified Vehicles using FMI
Göm menyn

Title:
Nonlinear Model Predictive Control of a Thermal Management System for Electrified Vehicles using FMI
Author:
Torben Fischer: Fraunhofer Institute for Chemical Technology (ICT), Project Group New Drive Systems, Germany Tom Kraus: Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany Christian Kirches: Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany Frank Gauterin: Institute of Vehicle System Technology, Karlsruhe Institute of Technology (KIT), Germany
DOI:
10.3384/ecp17132255
Download:
Full text (pdf)
Year:
2017
Conference:
Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017
Issue:
132
Article no.:
027
Pages:
255-264
No. of pages:
10
Publication type:
Abstract and Fulltext
Published:
2017-07-04
ISBN:
978-91-7685-575-1
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


Export in BibTex, RIS or text

Energy-efficient thermal management systems for Emobility help to decrease energy consumption and increase range. Due to transient external conditions and the increasing system complexity, optimization-based control approaches are required in order to harness the full potential of such systems. In (Fischer et al., 11th Int. Modelica Conf, 2015), we have presented a model-based development cycle for a thermal management system in Emobility to this end. In this article, we build upon this work to describe the use of this model within a nonlinear model predictive control (NMPC) approach. The main benefits of using an advanced optimization-based control system in this application are a) the ability to control the battery temperature and the cabin temperature simultaneously, b) the increased energy efficiency achieved by exploiting the predictive character of the optimizationbased control approach, c) the possibility to include operational limits as constraints in the optimization problems and d) the fast reaction to disturbances or model parameter changes. We evaluate the merit of the proposed advanced control system by way of a comparison to conventional PID controller.

Keywords: e-mobility thermal management system nonlinear model predictive control Functional Mock-up Interface

Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Author:
Torben Fischer, Tom Kraus, Christian Kirches, Frank Gauterin
Title:
Nonlinear Model Predictive Control of a Thermal Management System for Electrified Vehicles using FMI
DOI:
http://dx.doi.org/10.3384/ecp17132255
References:
No references available

Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Author:
Torben Fischer, Tom Kraus, Christian Kirches, Frank Gauterin
Title:
Nonlinear Model Predictive Control of a Thermal Management System for Electrified Vehicles using FMI
DOI:
http://dx.doi.org/10.3384/ecp17132255
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment


Responsible for this page: Peter Berkesand
Last updated: 2017-02-21