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Publications (10 of 36) Show all publications
Zhang, X., Song, X., Feng, L., Chen, L. & Törngren, M. (2017). A Case Study on Achieving Fair Data Age Distribution in Vehicular Communications. In: Parmer, G (Ed.), PROCEEDINGS OF THE 23RD IEEE REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS 2017): . Paper presented at 23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), APR 18-21, 2017, Pittsburgh, PA (pp. 307-317). IEEE.
Open this publication in new window or tab >>A Case Study on Achieving Fair Data Age Distribution in Vehicular Communications
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2017 (English)In: PROCEEDINGS OF THE 23RD IEEE REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS 2017) / [ed] Parmer, G, IEEE , 2017, 307-317 p.Conference paper, Published paper (Refereed)
Abstract [en]

In vehicular communication protocol stacks, received messages may not always be decoded successfully due to the complexity of the decoding functions, the uncertainty of the communication load and the limited computation resources. Even worse, an improper implementation of the protocol stack may cause an unfair data age distribution among all the communicating vehicles (the receiving bias problem). In such cases, some vehicles are almost locked out of the vehicular communication, causing potential safety risk in scenarios such as intersection passing. To our knowledge, this problem has not been systematically studied in the fields of vehicular communication and intelligent transport systems (ITS). This paper analyzes the root of the receiving bias problem and proposes architectural solutions to balance data age distribution. Simulation studies based on commercial devices demonstrate the effectiveness of these solutions. In addition, our system has been successfully applied during the Grand Cooperative Driving Challenge, where complicated scenarios involving platooning maneuvering and intersection coordination were conducted.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Real-Time and Embedded Technology and Applications Symposium, ISSN 1545-3421
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-215487 (URN)10.1109/RTAS.2017.7 (DOI)000411195100034 ()2-s2.0-85021802444 (Scopus ID)978-1-5090-5269-1 (ISBN)
Conference
23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), APR 18-21, 2017, Pittsburgh, PA
Note

QC 20171013

Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2017-10-23Bibliographically approved
Khodabakhshian, M., Feng, L., Börjesson, S., Lindgärde, O. & Wikander, J. (2017). Reducing Auxiliary Energy Consumption of Heavy Trucks by Onboard Prediction and Real-time Optimization. Applied Energy, 188, 652-671.
Open this publication in new window or tab >>Reducing Auxiliary Energy Consumption of Heavy Trucks by Onboard Prediction and Real-time Optimization
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2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 188, 652-671 p.Article in journal (Refereed) Published
Abstract [en]

The electric engine cooling system, where the coolant pump and the radiator fan are driven by electric motors, admits advanced control methods to decrease auxiliary energy consumption. Recent publications show the fuel saving potential of optimal control strategies for the electric cooling system through offline simulations. These strategies often assume full knowledge of the drive cycle and compute the optimal control sequence by expensive global optimization methods. In reality, the full drive cycle is unknown during driving and global optimization not directly applicable on resource-constrained truck electronic control units. This paper reports state-of-the-art engineering achievements of exploiting vehicular onboard prediction for a limited time horizon and minimizing the auxiliary energy consumption of the electric cooling system through real-time optimization. The prediction and optimization are integrated into a model predictive controller (MPC), which is implemented on a dSPACE MicroAutoBox and tested on a truck on a public road. Systematic simulations show that the new method reduces fuel consumption of a 40-tonne truck by 0.36% and a 60-tonne truck by 0.69% in a real drive cycle compared to a base-line controller. The reductions on auxiliary fuel consumption for the 40-tonne and 60-tonne trucks are about 26% and 38%, respectively. Truck experiments validate the consistency between simulations and experiments and confirm the real-time feasibility of the MPC controller. © 2016 Elsevier Ltd

Place, publisher, year, edition, pages
Elsevier, 2017
Keyword
Engine cooling system; Model predictive control (MPC); Parasitic load reduction; Quadratic programming (QP)
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-181077 (URN)10.1016/j.apenergy.2016.11.118 (DOI)000393003100053 ()2-s2.0-85007038221 (Scopus ID)
Projects
CONVENIENT
Funder
EU, FP7, Seventh Framework Programme, 312314
Note

QC 20170111

Available from: 2016-01-28 Created: 2016-01-28 Last updated: 2017-05-22Bibliographically approved
Liu, J., Feng, L. & Li, Z. (2017). The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption. Energies, 10(5), Article ID 700.
Open this publication in new window or tab >>The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption
2017 (English)In: Energies, ISSN 1996-1073, E-ISSN 1996-1073, Vol. 10, no 5, 700Article in journal (Refereed) Published
Abstract [en]

Reducing energy consumption of ground vehicles is a paramount pursuit in academia and industry. Even though the road infrastructural has a significant influence on vehicular fuel consumption, the majority of the R&D efforts are dedicated to improving vehicles. Little investigation has been made in the optimal design of the road infrastructure to minimize the total fuel consumption of all vehicles running on it. This paper focuses on this overlooked design problem and the design parameters of the optimal road infrastructure is the profile of road grade angle between two fixed points. We assume that all vehicles on the road follow a given acceleration profile between the two given points. The mean value of the energy consumptions of all vehicles running on the road is defined as the objective function. The optimization problem is solved both analytically by Pontryagin's minimum principle and numerically by dynamic programming. The two solutions agree well. A large number of Monte Carlo simulations show that the vehicles driving on the road with the optimal road grade consume up to 31.7% less energy than on a flat road. Finally, a rough cost analysis justifies the economic advantage of building the optimal road profile.

Place, publisher, year, edition, pages
MDPI AG, 2017
Keyword
optimal control, road grade design, analytical solution, Pontryagin's minimum principle, dynamic programming
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-210379 (URN)10.3390/en10050700 (DOI)000403048400119 ()2-s2.0-85036459521 (Scopus ID)
Funder
XPRES - Initiative for excellence in production research
Note

QC 20170704

Available from: 2017-07-04 Created: 2017-07-04 Last updated: 2017-12-15Bibliographically approved
Li, Y., Duan, A., Gratner, A. & Feng, L. (2016). A Geometric Programming Approach to the Optimization of Mechatronic Systems in Early Design Stages. In: 2016 IEEE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM): . Paper presented at IEEE International Conference on Advanced Intelligent Mechatronics (AIM), JUL 12-15, 2016, Banff, CANADA (pp. 1351-1356). IEEE conference proceedings.
Open this publication in new window or tab >>A Geometric Programming Approach to the Optimization of Mechatronic Systems in Early Design Stages
2016 (English)In: 2016 IEEE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM), IEEE conference proceedings, 2016, 1351-1356 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper evaluates geometric programming as a solver to optimize mechatronic system design in a holistic manner to aid early design decisions. Mechatronic systems design optimization requires complex and often non-convex functions as design objectives and constraints. Currently the solutions are primarily based on randomized search methods, e.g., genetic algorithms, and they are time-consuming. This paper converts complex constraints and objectives into approximate posynomial forms, which can then be used with disciplined convex optimization to significantly reduce the computation time for optimization. The approach is compared to the previous research using a mechatronic servo system design case study consisting of a motor, a shaft, two planetary gears and a rotational load. The result confirms that the geometric programming approach improves both computation speed and accuracy.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
Series
IEEE ASME International Conference on Advanced Intelligent Mechatronics, ISSN 2159-6255
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-197804 (URN)10.1109/AIM.2016.7576958 (DOI)000387100300220 ()2-s2.0-84992415342 (Scopus ID)978-1-5090-2065-2 (ISBN)
Conference
IEEE International Conference on Advanced Intelligent Mechatronics (AIM), JUL 12-15, 2016, Banff, CANADA
Note

QC 20161227

Available from: 2016-12-27 Created: 2016-12-08 Last updated: 2017-01-17Bibliographically approved
Zhang, X., Feng, L., Törngren, M. & Chen, D. (2016). Formulating Customized Specifications for Resource Allocation Problem of Distributed Embedded Systems. In: 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD): . Paper presented at 35th IEEE/ACM International Conference on Computer-Aided Design (ICCAD), NOV 07-10, 2016, Austin, TX. Institute of Electrical and Electronics Engineers (IEEE).
Open this publication in new window or tab >>Formulating Customized Specifications for Resource Allocation Problem of Distributed Embedded Systems
2016 (English)In: 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), Institute of Electrical and Electronics Engineers (IEEE), 2016Conference paper, Published paper (Refereed)
Abstract [en]

There are plentiful attempts for increasing the efficiency, generality and optimality of the Design Space Exploration (DSE) algorithms for resource allocation problems of distributed embedded systems. Most contemporary approaches formulate DSE as an optimization or SAT problem, based on a set of predefined constraints. In this way, the end users lose the flexibility to guide and customize the exploration based on specifics of their actual problem. Besides, during the design of the DSE algorithms, manual formulation is time consuming and error-prone. To solve these problems, 1) a formal representation is defined for capturing customized architectural constraints based on a combination of propositional logic and Pseudo-Boolean (PB) formulas; 2) A process is designed to automatically translate these architectural constrains into corresponding Integer Linear Programming (ILP) constraints, commonly used for DSE. The translation process is also optimized to create ILP formulation with less introduced variables so as to reduce computation time. The results show that the generated constraints correctly reflect the corresponding specification with decent efficiency.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Series
ICCAD-IEEE ACM International Conference on Computer-Aided Design, ISSN 1933-7760
Keyword
DSE, Resource Allocation and Constraint Language
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-199778 (URN)10.1145/2966986.2967042 (DOI)000390297800076 ()2-s2.0-85000916308 (Scopus ID)978-1-4503-4466-1 (ISBN)
Conference
35th IEEE/ACM International Conference on Computer-Aided Design (ICCAD), NOV 07-10, 2016, Austin, TX
Note

QC 20170120

Available from: 2017-01-20 Created: 2017-01-16 Last updated: 2018-01-13Bibliographically approved
Zhang, X., Feng, L., Chen, D.-J. & Törngren, M. (2015). Design-Space Reduction for Architectural Optimization of Automotive Embedded Systems. In: High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on: . Paper presented at IEEE 12th International Conference on Embedded Softwareand Systems (ICESS), New York, August 24-26 (pp. 1103-1109). IEEE Computer Society.
Open this publication in new window or tab >>Design-Space Reduction for Architectural Optimization of Automotive Embedded Systems
2015 (English)In: High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on, IEEE Computer Society, 2015, , 7 p.1103-1109 p.Conference paper, Published paper (Refereed)
Abstract [en]

A key decision for the synthesis of automotiveembedded systems is the allocation of application softwarecomponents to ECUs. Design Space Exploration (DSE) supportsthe decision by automatically characterizing and evaluating alarge number of possible design alternatives, and thereby suggestingthe optimal ones. A primary challenge for applying DSEmethods to support this decision is to reduce the computationtime of the DSE process while maintaining the generality andoptimality. This paper exploits legacy system architectures andthe AUTOSAR standard to preemptively reduce the design space,because both artifacts limit the flexibility of certain designvariables. A new DES formulation incorporating the constraintsof the legacy system architectures and the AUTOSAR standardis proposed in this paper. Computation result shows a largereduction of the computation time comparing to traditionalmodeling and formulations. The scalability of our method is alsoanalyzed by testing it on a set of random problem instances.

Place, publisher, year, edition, pages
IEEE Computer Society, 2015. 7 p.
National Category
Embedded Systems
Research subject
Industrial Engineering and Management
Identifiers
urn:nbn:se:kth:diva-177585 (URN)10.1109/HPCC-CSS-ICESS.2015.298 (DOI)000380408100182 ()2-s2.0-84961717465 (Scopus ID)
External cooperation:
Conference
IEEE 12th International Conference on Embedded Softwareand Systems (ICESS), New York, August 24-26
Note

QC 20151201

Available from: 2015-11-24 Created: 2015-11-24 Last updated: 2016-09-05Bibliographically approved
Lindgärde, O., Feng, L., Tenstam, A. & Soderman, M. (2015). Optimal Vehicle Control for Fuel Efficiency. SAE International Journal of Commercial Vehicles, 8(2), 682-694.
Open this publication in new window or tab >>Optimal Vehicle Control for Fuel Efficiency
2015 (English)In: SAE International Journal of Commercial Vehicles, ISSN 1946-391X, E-ISSN 1946-3928, Vol. 8, no 2, 682-694 p.Article in journal (Refereed) Published
Abstract [en]

CONVENIENT is a project where prediction and integrated control are applied on several subsystems with electrified actuators. The technologies developed in this project are applied to a long-haul tractor and semi-trailer combination. A Volvo truck meeting the Eu6 emission standard is rebuilt with a number of controllable electrified actuators. An e-Horizon system collects information about future road topography and speed limits. Controllable aerodynamic wind deflectors reduce the wind drag. The tractor is also equipped with a full digital cluster for human machine interface development. A primary project goal is to develop a model-based optimal controller that uses predictive information from the e-Horizon system in order to minimize fuel consumption. Several energy buffers are controlled in an integrated and optimal way using model predictive control. Several buffers are considered, such as the cooling system, the battery, and the vehicle kinetic energy. This paper presents details on the model predictive controller of the battery system and of the cooling system. Another project goal is to reduce fuel consumption by using adaptive aerodynamics. Controllers are developed that automatically sets an optimal roof deflector angle and the optimal side deflector angle. The results presented in this paper are encouraging. A third focus is the human machine interface and especially the communication between the driver and the control system during driving. This project develops a driver interface that encourages the driver to use the adaptive cruise controller when appropriate. The CONVENIENT project will be finalized this year. This paper presents the main project findings.

Place, publisher, year, edition, pages
SAE International, 2015
Keyword
Actuators, Adaptive cruise control, Aerodynamic drag, Aerodynamics, Automobile cooling systems, Control system synthesis, Cooling systems, Electric batteries, Fuels, Kinetic energy, Kinetics, Man machine systems, Model predictive control, Printing machinery, Secondary batteries, Thermoelectric equipment, Tractors (truck), Truck transportation, Trucks, Adaptive cruise controllers, Driver interface, Emission standard, Human Machine Interface, Model predictive controllers, Optimal controller, Optimal vehicles, Predictive information, Controllers
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-181245 (URN)10.4271/2015-01-2875 (DOI)2-s2.0-84945118923 (Scopus ID)
Projects
CONVENIENT
Funder
EU, FP7, Seventh Framework Programme, 312314
Note

QC 20160210

Available from: 2016-02-10 Created: 2016-01-29 Last updated: 2017-11-30Bibliographically approved
Khodabakhshian, M., Feng, L. & Wikander, J. (2014). Fuel Saving Potential of Optimal Engine Cooling System. In: : . Paper presented at AVEC 2014 International symposium on advanced vehicle control, September 22-26, 2014. Society of Automotive Engineers.
Open this publication in new window or tab >>Fuel Saving Potential of Optimal Engine Cooling System
2014 (English)Conference paper, Published 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
Energy efficient vehicles
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-170378 (URN)
Conference
AVEC 2014 International symposium on advanced vehicle control, September 22-26, 2014
Note

QC 20150715

Available from: 2015-06-29 Created: 2015-06-29 Last updated: 2016-01-28Bibliographically approved
Shoaei, M. R., Feng, L. & Lennartson, B. (2014). On the computation of natural observers for extended finite automata. In: IFAC Proceedings Volumes (IFAC-PapersOnline): . Paper presented at 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014, 24 August 2014 through 29 August 2014 (pp. 2448-2455). .
Open this publication in new window or tab >>On the computation of natural observers for extended finite automata
2014 (English)In: IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, 2448-2455 p.Conference paper, Published paper (Refereed)
Abstract [en]

Compared to finite automata, Extended Finite Automata (EFAs) allows us to efficiently represent discrete-event systems that involve non-trivial data manipulation. However, the complexity of designing supervisors for such systems is still a challenge. In our previous works, we have studied model abstraction for EFAs using natural projections with observer property on events as well as data. In this paper, we provide sufficient conditions for verifying the observer properties and further enhance the EFAs when the property does not hold. To this end, we introduce symbolic simplification techniques for data and generalize existing algorithms in the literature for the events to compute natural observers for EFAs. The importance of this combined abstraction and symbolic simplification method is demonstrated by synthesis of a nonblocking controller for an industrial manufacturing system.

Keyword
Discrete-event systems, Hierarchical control, Supervisory control theory
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-175130 (URN)2-s2.0-84929832940 (Scopus ID)9783902823625 (ISBN)
Conference
19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014, 24 August 2014 through 29 August 2014
Note

QC 20151016

Available from: 2015-10-16 Created: 2015-10-09 Last updated: 2015-10-16Bibliographically approved
Khodabakhshian, M., Feng, L. & Wikander, J. (2014). One-step prediction for improving gear changing control of HEVs. Journal of Robotics and Mechatronics, 26(6), 799-807.
Open this publication in new window or tab >>One-step prediction for improving gear changing control of HEVs
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
Fuji Technology Press, 2014
Keyword
Drivability, ECMS, Fuel efficiency, Hybrid electric vehicle, Prediction
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-161050 (URN)2-s2.0-84919427220 (Scopus ID)
Projects
CONENIENT
Funder
EU, FP7, Seventh Framework Programme, 312314
Note

QC 20150309

Available from: 2015-03-09 Created: 2015-03-06 Last updated: 2017-01-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5703-5923

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