dc.contributor.author | Taghavipour, Amir | |
dc.contributor.author | Azad, Nasser L. | |
dc.contributor.author | McPhee, John | |
dc.date.accessioned | 2018-06-20 14:40:21 (GMT) | |
dc.date.available | 2018-06-20 14:40:21 (GMT) | |
dc.date.issued | 2015-08-01 | |
dc.identifier.uri | https://dx.doi.org/10.1016/j.mechatronics.2015.04.020 | |
dc.identifier.uri | http://hdl.handle.net/10012/13423 | |
dc.description | The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.mechatronics.2015.04.020 © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
dc.description.abstract | Model predictive control is a promising approach to exploit the potentials of modern concepts and to fulfill the automotive requirements. Since, it is able to handle constrained multi-input multi-output optimal control problems. However, when it comes to implementation, the MPC computational effort may cause a concern for real-time applications. To maintain the advantage of a predictive control approach and improve its implementation speed, we can solve the problem parametrically. In this paper, we design a power management strategy for a Toyota Prius plug-in hybrid powertrain (PHEV) using explicit model predictive control (eMPC) based on a new control-oriented model to improve the real-time implementation performance. By implementing the controller to a PHEV model through model and hardware-in-the-loop simulation, we get promising fuel economy as well as real-time simulation speed. | en |
dc.description.sponsorship | NSERC | en |
dc.description.sponsorship | Toyota | en |
dc.description.sponsorship | Maplesoft Industrial Research Chair program | en |
dc.language.iso | en | en |
dc.publisher | Elsevier | en |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Automotive powertrain | en |
dc.subject | Explicit model predictive control | en |
dc.subject | Plug-in hybrid electric vehicle | en |
dc.subject | Power management | en |
dc.title | Real-time predictive control strategy for a plug-in hybrid electric powertrain | en |
dc.type | Article | en |
dcterms.bibliographicCitation | Taghavipour, A., Azad, N. L., & McPhee, J. (2015). Real-time predictive control strategy for a plug-in hybrid electric powertrain. Mechatronics, 29, 13–27. doi:10.1016/j.mechatronics.2015.04.020 | en |
uws.contributor.affiliation1 | Faculty of Engineering | en |
uws.contributor.affiliation2 | Systems Design Engineering | en |
uws.typeOfResource | Text | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Reviewed | en |
uws.scholarLevel | Faculty | en |