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Improving Fuel Economy and Robustness of an Improved ECMS Method
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
2013 (English)In: 2013 10th IEEE International Conference on Control and Automation  (ICCA), IEEE , 2013, 598-603 p.Conference paper (Refereed)
Abstract [en]

Hybrid electric vehicles have shown significant improvement for both fuel efficiency and emission reduction, and attracted many researchers. Paramount for the fuel efficiency of HEVs is the energy management control strategies. ECMS (equivalent consumption minimization strategy) is one of the well-known real time power management strategies and has been used extensively in different works; however, its intrinsic difficulty is to find the optimal equivalent factor, which in theory is determined by the a priori knowledge of the complete driving cycle. Different methods have been proposed to solve this issue, but each one has its own pros. and cons. Especially, the applicability of each method for different cycles as well as the computation overhead are two main concerns in the methods presented so far. In this paper, a new method is presented for calculating equivalent factor in the ECMS method. The method does not rely on any prediction nor the a priori knowledge of driving cycles. Its robustness is demonstrated through different driving cycles with distinct characteristics. Our new method will improve the effectiveness and robustness of the ECMS method.

Place, publisher, year, edition, pages
IEEE , 2013. 598-603 p.
, IEEE International Conference on Control and Automation ICCA, ISSN 1948-3449
Keyword [en]
Computation overheads, Driving cycle, Emission reduction, Energy management control strategies, Fuel efficiency, Priori knowledge, Real-time power managements
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-132220DOI: 10.1109/ICCA.2013.6564946ISI: 000324335200108ScopusID: 2-s2.0-84882308395ISBN: 978-1-4673-4708-2OAI: diva2:659100
2013 10th IEEE International Conference on Control and Automation, ICCA 2013; Hangzhou; China; 12 June 2013 through 14 June 2013

QC 20131024

Available from: 2013-10-24 Created: 2013-10-24 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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