Look-ahead intelligent energy management of a parallel hybrid electric vehicle

Ganji, Behnam, Kouzani, Abbas Z. and Khayyam, Hamid 2011, Look-ahead intelligent energy management of a parallel hybrid electric vehicle, in FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy Systems, IEEE, [Taipei, Taiwan], pp. 2335-2341.

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Title Look-ahead intelligent energy management of a parallel hybrid electric vehicle
Author(s) Ganji, Behnam
Kouzani, Abbas Z.ORCID iD for Kouzani, Abbas Z. orcid.org/0000-0002-6292-1214
Khayyam, Hamid
Conference name IEEE International Conference on Fuzzy Systems (2011 : Taipei, Taiwan)
Conference location Taipei, Taiwan
Conference dates 27-30 Jun. 2011
Title of proceedings FUZZ 2011 : Proceedings of the IEEE 2011 International Conference on Fuzzy Systems
Editor(s) [Unknown]
Publication date 2011
Conference series IEEE International Conference on Fuzzy Systems
Start page 2335
End page 2341
Total pages 7
Publisher IEEE
Place of publication [Taipei, Taiwan]
Keyword(s) hybrid electric vehicles
backward modeling
look-ahead fuzzy control system
fuel efficiency
Summary Improving fuel efficiency in vehicles can reduce the energy consumption concerns associated with operating the vehicles. This paper presents a model for a parallel hybrid electric vehicle. In the model, the flow of energy starts from wheels and spreads toward engine and electric motor. A fuzzy logic based control strategy is implemented for the vehicle. The controller manages the energy flow from the engine and the electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines the vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. It then determines the best values for continuous variable transmission ratio, speed, and torque. A slope window method is formed that takes into account the look-ahead slope information, and determines the best vehicle speed. The developed model and control strategy are simulated using real highway data relating to Nowra-Bateman Bay in Australia, and SAE Highway Fuel Economy Driving Schedule. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces the fuel consumption of the vehicle.
ISBN 1424473160
ISSN 1098-7584
Language eng
Field of Research 090602 Control Systems, Robotics and Automation
Socio Economic Objective 850702 Energy Conservation and Efficiency in Transport
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2011
Copyright notice ©2011, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30042378

Document type: Conference Paper
Collection: School of Engineering
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