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Fuel Saving Potential of Optimal Engine Cooling System
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)Conference paper (Refereed)
Abstract [en]

The engine cooling system in trucks is one of the main sources of parasite load. Thus optimal control of the engine thermal management system with the objective of minimizing energy consumption can substantially improve fuel efficiency. Existing methods on the engine thermal control system concentrate mainly on regulating the engine coolant temperature within a safety range. This paper explicitly calculates the energy consumption of the cooling system using the optimal control methods to decide the trajectories of the control values of the cooling system. During the optimal operation, the engine cooling system serves as another energy buffer to balance the engine workload in conventional trucks. To expose the maximal fuel saving potential of the optimal engine thermal control system, we apply dynamic programming in the investigation and the results are compared with a simple state feedback controller.

Place, publisher, year, edition, pages
Society of Automotive Engineers, 2014.
Keyword [en]
Energy efficient vehicles
National Category
Mechanical Engineering
URN: urn:nbn:se:kth:diva-170378OAI: diva2:828093
AVEC 2014 International symposium on advanced vehicle control, September 22-26, 2014

QC 20150715

Available from: 2015-06-29 Created: 2015-06-29 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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