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  • 1.
    Albrektsson, Jörgen
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Optimisation of Off-Road Transport Missions2018Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Mines, construction sites, road construction and quarries are examples of applications where construction equipment are used. In a production chain consisting of several construction machines working together, the work needs to be optimised and coordinated to achieve an environmental friendly, energy efficient and productive production. Recent rapid development within positioning services, telematics and human machine interfaces (HMI) opens up for control of individual machines and optimisation of transport missions where several construction machines co-operate.

    The production chain on a work site can be split up in different sub-tasks of which some can be transport missions. Taking off in a transport mission where one wheel loader ("loader" hereinafter) and two articulated haulers ("haulers" hereinafter) co-operate to transport material at a set production rate [ton/h], a method for fuel optimal control is developed. On the mission level, optimal cycle times for individual sub-tasks such as wheel loader loading, hauler transport and hauler return, are established through the usage of Pareto fronts.

    The haulers Pareto fronts are built through the development of a Dynamic Programming (DP) algorithm that trades fuel consumption versus cycle time for a road stretch by means of a time penalty constant. Through varying the time penalty constant n number of times, discrete fuel consumption - cycle time values can be achieved, forming the Pareto front. At a later stage, the same DP algorithm is used to generate fuel optimal vehicle speed and gear trajectories that are used as control signals for the haulers. Input to the DP algorithm is the distance to be travelled, road inclination, rolling resistance coefficient and a max speed limit to avoid unrealistic optimisation results.

    Thus, a method to describe the road and detect the road related data is needed to enable the optimisation. A map module is built utilising an extended Kalman Filter, Rauch-Tung-Striebel smoother and sensor fusion to merge data and estimate parameters not observable by sensors. The map module uses a model of the vehicle, sensor signals from a GPS or GNSS sensor and machine sensors to establish a map of the road.

    The wheel loader Pareto front is based on data developed in previous research combined with Volvo in-house data. The developed optimisation algorithms are implemented on a PC and in an interactive computer tablet based system. A human machine interface is created for the tablet, guiding the operators to follow the optimal control signals, which is speed for the haulers and cycle time for the loader. To evaluate the performance of the system it is tested in real working conditions.

    The contributions develop algorithms, set up a demo mission control system and carry out experiments. Altogether rendering in a platform that can be used as a base for a future design of an off-road transport mission control system.

    List of papers
    1. Road estimation and fuel optimal control of an off-road vehicle
    Open this publication in new window or tab >>Road estimation and fuel optimal control of an off-road vehicle
    2017 (English)In: Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems, SciTePress, 2017, p. 58-67Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    SciTePress, 2017
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-142731 (URN)10.5220/0006247200580067 (DOI)978-989-758-242-4 (ISBN)
    Conference
    3rd International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2017, April 22-24, 2017, in Porto, Portugal
    Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2018-11-22
    2. Fuel Optimal Control of an Articulated Hauler Utilising a Human Machine Interface
    Open this publication in new window or tab >>Fuel Optimal Control of an Articulated Hauler Utilising a Human Machine Interface
    2019 (English)In: Smart Cities, Green Technologies, and Intelligent Transport Systems / [ed] Donnellan, Brian; Klein, Cornel; Helfert, Markus; Gusikhin, Oleg; Pascoal, António, Springer International Publishing , 2019, p. 190-208Conference paper, Published paper (Refereed)
    Abstract [en]

    Utilising optimal control presents an opportunity to increase the fuel efficiency in an off-road transport mission conducted by an articulated hauler. A human machine interface (HMI) instructing the hauler operator to follow the fuel optimal vehicle speed trajectory has been developed and tested in real working conditions. The HMI implementation includes a Dynamic Programming based method to calculate the optimal vehicle speed and gear shift trajectories. Input to the optimisation algorithm is road related data such as distance, road inclination and rolling resistance. The road related data is estimated in a map module utilising an Extended Kalman Filter (EKF), a Rauch-Tung-Striebel smoother and a data fusion algorithm. Two test modes were compared: (1) The hauler operator tried to follow the optimal vehicle speed trajectory as presented in the HMI and (2) the operator was given a constant target speed to follow. The objective of the second test mode is to achieve an approximately equal cycle time as for the optimally controlled transport mission, hence, with similar productivity. A small fuel efficiency improvement was found when the human machine interface was used.

    Place, publisher, year, edition, pages
    Springer International Publishing, 2019
    Series
    Communications in Computer and Information Science book series (CCIS), ISSN 1865-0929, E-ISSN 1865-0937 ; 921
    Keywords
    Off-road, Construction equipment, Human machine interface, Optimal control, Dynamic programming, Kalman filters
    National Category
    Vehicle Engineering
    Identifiers
    urn:nbn:se:liu:diva-153311 (URN)10.1007/978-3-030-02907-4_10 (DOI)978-3-030-02906-7 (ISBN)978-3-030-02907-4 (ISBN)
    Conference
    6th International Conference, SMARTGREENS 2017 and Third International Conference, VEHITS 2017, Porto, Portugal, April 22–24, 2017
    Available from: 2018-12-12 Created: 2018-12-12 Last updated: 2018-12-12
    3. Fuel optimal control of an off-road transport mission
    Open this publication in new window or tab >>Fuel optimal control of an off-road transport mission
    2018 (English)In: 2018 IEEE International Conference on Industrial Technology (ICIT), 2018, p. 175-180Conference paper, Published paper (Refereed)
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-151856 (URN)10.1109/ICIT.2018.8352172 (DOI)978-1-5090-5949-2 (ISBN)
    Conference
    2018 IEEE International Conference on Industrial Technology (ICIT), 19-22 Feb.,Lyon, France
    Available from: 2018-10-06 Created: 2018-10-06 Last updated: 2018-11-22
  • 2.
    Albrektsson, Jörgen
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering. Volvo Construction Equipment, Eskilstuna, Sweden.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Fuel Optimal Control of an Articulated Hauler Utilising a Human Machine Interface2019In: Smart Cities, Green Technologies, and Intelligent Transport Systems / [ed] Donnellan, Brian; Klein, Cornel; Helfert, Markus; Gusikhin, Oleg; Pascoal, António, Springer International Publishing , 2019, p. 190-208Conference paper (Refereed)
    Abstract [en]

    Utilising optimal control presents an opportunity to increase the fuel efficiency in an off-road transport mission conducted by an articulated hauler. A human machine interface (HMI) instructing the hauler operator to follow the fuel optimal vehicle speed trajectory has been developed and tested in real working conditions. The HMI implementation includes a Dynamic Programming based method to calculate the optimal vehicle speed and gear shift trajectories. Input to the optimisation algorithm is road related data such as distance, road inclination and rolling resistance. The road related data is estimated in a map module utilising an Extended Kalman Filter (EKF), a Rauch-Tung-Striebel smoother and a data fusion algorithm. Two test modes were compared: (1) The hauler operator tried to follow the optimal vehicle speed trajectory as presented in the HMI and (2) the operator was given a constant target speed to follow. The objective of the second test mode is to achieve an approximately equal cycle time as for the optimally controlled transport mission, hence, with similar productivity. A small fuel efficiency improvement was found when the human machine interface was used.

  • 3.
    Albrektsson, Jörgen
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Fuel optimal control of an off-road transport mission2018In: 2018 IEEE International Conference on Industrial Technology (ICIT), 2018, p. 175-180Conference paper (Refereed)
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  • harvard1
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  • modern-language-association-8th-edition
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  • de-DE
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