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Simultaneous Reduction of Fuel Consumption and NOx Emissions through Hybridization of a Long Haulage Truck
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-8646-8998
2017 (English)In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2017, Vol. 50, no 1, p. 8927-8932Conference paper, Published paper (Refereed)
Abstract [en]

Hybridization is a promising and obvious way of reducing fuel consumption in automotive applications, however, its ability to reduce emissions in long haulage trucks is not so obvious. The complexity of the powertrain is also increased which makes well designed control systems needed to fully utilize the potential benefits of the hybridization. In this paper, a control strategy that takes advantage of the complex structure of the powertrain in a hybrid electric long haulage truck is developed and evaluated. The control system is based on equivalent consumption minimization strategy where an equivalence factor is used to compare fuel and battery power so that an optimal distribution of power between the components in the powertrain can be calculated. The proposed control system is evaluated in a driving scenario using a model of a complete hybrid electric truck, including an aftertreatment system, and the results are compared with a conventional, non-hybrid, vehicle. The hybridization leads to 31 % lower NOx emissions, primarily due to better thermal conditions in the exhaust system during braking, and at the same time, the fuel consumption was reduced by 3.8 % compared to the non-hybrid vehicle. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2017. Vol. 50, no 1, p. 8927-8932
Series
IFAC PAPERSONLINE, E-ISSN 2405-8963
Keyword [en]
Hybrid Electric Truck; Automotive Emissions; Powertrain Control; Aftertreatment System; Energy Management; Optimal Control
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-145852DOI: 10.1016/j.ifacol.2017.08.1295ISI: 000423964900473OAI: oai:DiVA.org:liu-145852DiVA, id: diva2:1192130
Conference
20th World Congress of the International-Federation-of-Automatic-Control (IFAC)
Available from: 2018-03-21 Created: 2018-03-21 Last updated: 2018-03-21

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Citation style
  • apa
  • harvard1
  • ieee
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  • de-DE
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