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Embedded System for Learning Smooth and Energy-Efficient Tram Driving Techniques

Author

Listed:
  • Adam Konieczka

    (Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

  • Dorota Stachowiak

    (Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

  • Szymon Feliński

    (Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

  • Maciej Dworzański

    (Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

Abstract

Driving a tram in city traffic is a challenging task. It is especially difficult to drive smoothly (without unnecessary jerks) when the route runs through streets with many other vehicles, pedestrians, and traffic lights. A smooth driving style of the tram driver not only has a significant impact on the comfort of passengers being transported, but also affects the energy consumption of the tram. The paper focuses on the analysis of the tram driver’s way of driving and the resulting energy savings. The energy consumption of the tram was measured depending on the driver’s driving technique. For the analysis of the driving technique, an innovative electronic device was proposed to be installed on the tram. It detects jerks in the lateral and longitudinal directions. Based on vibration analysis, it evaluates the driver’s driving technique on an ongoing basis and displays the result of this assessment. The device is cheap and uses a popular minicomputer, a GPS system receiver, an IMU accelerometer, and a screen. It is independent of the electronic systems of the tram. Due to this, it is possible to increase passenger comfort and reduce electricity consumption. It can be useful when learning to drive a tram. Preliminary tests of this device were carried out on a real tram during rides with passengers in city traffic. Tests have confirmed its effectiveness.

Suggested Citation

  • Adam Konieczka & Dorota Stachowiak & Szymon Feliński & Maciej Dworzański, 2023. "Embedded System for Learning Smooth and Energy-Efficient Tram Driving Techniques," Energies, MDPI, vol. 16(19), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6881-:d:1250658
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    References listed on IDEAS

    as
    1. Davide Maria Bruno & Guido Musante & Fabio Dacarro, 2022. "Smart Trams : A Design Proposal for a City of Interrelation," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    2. Jitka Fialová & Dastan Bamwesigye & Jan Łukaszkiewicz & Beata Fortuna-Antoszkiewicz, 2021. "Smart Cities Landscape and Urban Planning for Sustainability in Brno City," Land, MDPI, vol. 10(8), pages 1-17, August.
    3. Krystian Pietrzak & Oliwia Pietrzak, 2022. "Tram System as a Challenge for Smart and Sustainable Urban Public Transport: Effects of Applying Bi-Directional Trams," Energies, MDPI, vol. 15(15), pages 1-29, August.
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