Feed-forward modelling and fuzzy logic based control strategy for powertrain efficiency improvement in a parallel hybrid electric vehicle
Meisam Amiri,
Vahid Esfahanian,
Mohammad Reza Hairi-Yazdi,
Mohsen Esfahanian,
Amir Mohammad Fazeli and
Ali Nabi
Mathematical and Computer Modelling of Dynamical Systems, 2008, vol. 15, issue 2, 191-207
Abstract:
With the stricter limitations on both fuel consumption and air pollution, the advantages of a hybrid electric vehicle are becoming more evident than ever. In the present study, an energy management system for a hybrid electric vehicle is developed. Because the plant under consideration is nonlinear, multi-domain, time-varying, has multiple uncertainties and, in addition, the designed control strategy must be able to obey the driver's commands and achieve the par-internship for a new generation of vehicle regulations, the fuzzy logic approach is chosen. A feed-forward hybrid vehicle simulation model is used to demonstrate the validity and the convenience of the current approach and its results have been compared with the other parallel hybrid electric vehicle control strategies. Simulation results show considerable improvement in the efficiency of the internal combustion engine and, consequently, fuel consumption and acceleration performances.
Date: 2008
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/13873950802532294 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:15:y:2008:i:2:p:191-207
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20
DOI: 10.1080/13873950802532294
Access Statistics for this article
Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch
More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().