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Predictive control of the engine cooling system for fuel efficiency improvement
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: Automation Science and Engineering (CASE), 2014 IEEE International Conference on, IEEE conference proceedings, 2014, 61-66 p.Conference paper (Refereed)
Abstract [en]

The engine cooling system in trucks is one of the main sources of parasite load. Thus fuel efficiency can be improved by optimal control of engine thermal management system considering fuel consumption minimization as the objective. Although several optimal control methods have been proposed for the engine cooling system, their main emphasize is on regulating engine and coolant temperature in an acceptable range rather than minimizing fuel consumption. In contrast, this paper investigates the fuel saving potential of predictive optimal control methods for the engine cooling system of conventional trucks. Our method exploits the idea of energy buffers in the automotive system, where the engine cooling system and the battery serve as energy buffers. The advantages of this approach are the recovery of brake energy and the balance of energy sources so that the total energy loss is minimized. A model predictive controller is used as the real time controller, and the results are compared with a simple state feedback controller and a global optimal solution obtained by dynamic programming. The results show limited but notable improvement in fuel efficiency. The results also construct a base for ongoing research on energy buffer control in conventional heavy trucks.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 61-66 p.
National Category
Mechanical Engineering
Research subject
Vehicle and Maritime Engineering; Energy Technology
URN: urn:nbn:se:kth:diva-170377DOI: 10.1109/CoASE.2014.6899305OAI: diva2:828079
IEEE International Conference on Automation Science and Engineering (CASE), 18-22 Aug. 2014,Taipei

QC 20150716

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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