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One-step prediction for improving gear changing control of HEVs
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-3626-6367
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0001-5703-5923
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.ORCID iD: 0000-0002-7550-3134
2014 (English)In: Journal of Robotics and Mechatronics, ISSN 0915-3942, Vol. 26, no 6, 799-807 p.Article in journal (Refereed) Published
Abstract [en]

Decreasing fuel consumption and emissions in automobiles continues to be an active research problem. A promising technology is powertrain hybridization. Study in this area usually focuses on the development of optimal power management control methods. The equivalent consumption minimization strategy (ECMS) is a widely used real-time control method used for determining the optimal trajectory of the power split between the engine and motor. Reports also cover applying ECMS to find an optimal gear changing strategy, but results are not always satisfactory in fuel economy and drivability. One possible reason for this is that gearbox dynamics are slow, but ECMS is based on instant optimization and neglects this time delay. This paper proposes a simple prediction strategy for improving ECMS performance used with gear changing control. The proposed controller improves fuel efficiency and drivability without the need of adding extra sensors to the automobile. The proposed method’s simplicity makes it suitable for implementation.

Place, publisher, year, edition, pages
2014. Vol. 26, no 6, 799-807 p.
Keyword [en]
Drivability, ECMS, Fuel efficiency, Hybrid electric vehicle, Prediction
National Category
Energy Engineering
URN: urn:nbn:se:kth:diva-161050ScopusID: 2-s2.0-84919427220OAI: diva2:793776

QC 20150309

Available from: 2015-03-09 Created: 2015-03-06 Last updated: 2016-01-28Bibliographically approved
In thesis
1. Improving Fuel Efficiency of Commercial Vehicles through Optimal Control of Energy Buffers
Open this publication in new window or tab >>Improving Fuel Efficiency of Commercial Vehicles through Optimal Control of Energy Buffers
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Fuel consumption reduction is one of the main challenges in the automotiveindustry due to its economical and environmental impacts as well as legalregulations. While fuel consumption reduction is important for all vehicles,it has larger benefits for commercial ones due to their long operational timesand much higher fuel consumption.

Optimal control of multiple energy buffers within the vehicle proves aneffective approach for reducing energy consumption. Energy is temporarilystored in a buffer when its cost is small and released when it is relativelyexpensive. An example of an energy buffer is the vehicle body. Before goingup a hill, the vehicle can accelerate to increase its kinetic energy, which canthen be consumed on the uphill stretch to reduce the engine load. The simplestrategy proves effective for reducing fuel consumption.

The thesis generalizes the energy buffer concept to various vehicular componentswith distinct physical disciplines so that they share the same modelstructure reflecting energy flow. The thesis furthermore improves widely appliedcontrol methods and apply them to new applications.

The contribution of the thesis can be summarized as follows:

• Developing a new function to make the equivalent consumption minimizationstrategy (ECMS) controller (which is one of the well-knownoptimal energy management methods in hybrid electric vehicles (HEVs))more robust.

• Developing an integrated controller to optimize torque split and gearnumber simultaneously for both reducing fuel consumption and improvingdrivability of HEVs.

• Developing a one-step prediction control method for improving the gearchanging decision.

• Studying the potential fuel efficiency improvement of using electromechanicalbrake (EMB) on a hybrid electric city bus.

• Evaluating the potential improvement of fuel economy of the electricallyactuated engine cooling system through the off-line global optimizationmethod.

• Developing a linear time variant model predictive controller (LTV-MPC)for the real-time control of the electric engine cooling system of heavytrucks and implementing it on a real truck.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. xviii, 71 p.
TRITA-MMK, ISSN 1400-1179 ; 2016:01
Energy buffer, Optimal control, Hybrid electric vehicle, Engine cooling system, Equivalent consumption minimization strategy, Model predictive control
National Category
Mechanical Engineering Control Engineering Energy Engineering
Research subject
Machine Design
urn:nbn:se:kth:diva-181071 (URN)978-91-7595-850-7 (ISBN)
Public defence
2016-02-18, F3, Lindstedtsvägen 26, KTH, Stockholm, 13:00 (English)

QC 20160128

Available from: 2016-01-28 Created: 2016-01-28 Last updated: 2016-01-28Bibliographically approved

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