dc.contributor.author | Taghavipour, Amir | |
dc.contributor.author | Vajedi, Mahyar | |
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 | 2015-07-29 | |
dc.identifier.uri | https://dx.doi.org/10.1002/asjc.1191 | |
dc.identifier.uri | http://hdl.handle.net/10012/13422 | |
dc.description | This is the peer reviewed version of the following article: Taghavipour, A., Vajedi, M., Azad, N. L., & McPhee, J. (2015). A Comparative Analysis of Route-Based Energy Management Systems for Phevs. Asian Journal of Control, 18(1), 29–39, which has been published in final form at https://dx.doi.org/10.1002/asjc.1191. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. | en |
dc.description.abstract | Plug-in hybrid electric vehicle (PHEV) development seems to be essential step on the path to widespread deployment of electric vehicles (EVs) as the zero-emission solution for the future of transportation. Because of their larger battery pack in comparison to conventional hybrid electic vehicles (HEVs), they offer longer electric range which leads to a superior fuel economy performance. Advanced energy management systems (EMSs) use vehicle trip information to enhance a PHEV's performance. In this study, the performance of two optimal control approaches, model predictive control (MPC) and adaptive equivalent consumption minimization strategy (A-ECMS), for designing an EMS for different levels of trip information are compared. The resulting EMSs are fine-tuned for the Toyota Prius plug-in hybrid powertrain and their performances are evaluated by using a high-fidelity simulation model in the Autonomie software. The results of simulation show that both MPC and A-ECMS can approximately improve fuel economy up to 10% compared to the baseline Autonomie controller for EPA urban and highway drive cycles. Although both EMSs can be implemented in real time, A-ECMS is 15% faster than MPC. Moreover, it is shown that the engine operating points are more sensitive to the battery depletion pattern than to different driving schedules. | en |
dc.language.iso | en | en |
dc.publisher | Wiley | en |
dc.subject | adaptive equivalent consumption minimization strategy | en |
dc.subject | energy management system | en |
dc.subject | model predictive control | en |
dc.subject | Plug-in hybrid electric vehicle | en |
dc.title | A Comparative Analysis of Route-Based Energy Management Systems for Phevs | en |
dc.type | Article | en |
dcterms.bibliographicCitation | Taghavipour, A., Vajedi, M., Azad, N. L., & McPhee, J. (2015). A Comparative Analysis of Route-Based Energy Management Systems for Phevs. Asian Journal of Control, 18(1), 29–39. doi:10.1002/asjc.1191 | 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 |