IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2018i1p27-d192619.html
   My bibliography  Save this article

Energy Modeling and Power Measurement for Mobile Robots

Author

Listed:
  • Linfei Hou

    (School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China)

  • Liang Zhang

    (School of Mechanical, Electrical and Information Engineering, Shandong University (Weihai), Weihai 264209, China)

  • Jongwon Kim

    (Department of Electromechanical Convergence Engineering, Korea University of Technology and Education, Cheonan 31253, Korea)

Abstract

To improve the energy efficiency of a mobile robot, a novel energy modeling method for mobile robots is proposed in this paper. The robot can calculate and predict energy consumption through the energy model, which provides a guide to facilitate energy-efficient strategies. The energy consumption of the mobile robot is first modeled by considering three major factors: the sensor system, control system, and motion system. The relationship between the three systems is elaborated by formulas. Then, the model is utilized and experimentally tested in a four-wheeled Mecanum mobile robot. Furthermore, the power measurement methods are discussed. The energy consumption of the sensor system and control system was at the milliwatt level, and a Monsoon power monitor was used to accurately measure the electrical power of the systems. The experimental results showed that the proposed energy model can be used to predict the energy consumption of the robot movement processes in addition to being able to efficiently support the analysis of the energy consumption characteristics of mobile robots.

Suggested Citation

  • Linfei Hou & Liang Zhang & Jongwon Kim, 2018. "Energy Modeling and Power Measurement for Mobile Robots," Energies, MDPI, vol. 12(1), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:27-:d:192619
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/1/27/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/1/27/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marojahan Tampubolon & Laskar Pamungkas & Huang-Jen Chiu & Yu-Chen Liu & Yao-Ching Hsieh, 2018. "Dynamic Wireless Power Transfer for Logistic Robots," Energies, MDPI, vol. 11(3), pages 1-13, February.
    2. Saidur, R., 2010. "A review on electrical motors energy use and energy savings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 877-898, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenji Jia & Guilin Yang & Chongchong Wang & Chi Zhang & Chinyin Chen & Zaojun Fang, 2019. "Energy-Efficient Torque Distribution Optimization for an Omnidirectional Mobile Robot with Powered Caster Wheels," Energies, MDPI, vol. 12(23), pages 1-19, November.
    2. Krystian Góra & Mateusz Kujawinski & Damian Wroński & Grzegorz Granosik, 2021. "Comparison of Energy Prediction Algorithms for Differential and Skid-Steer Drive Mobile Robots on Different Ground Surfaces," Energies, MDPI, vol. 14(20), pages 1-16, October.
    3. Reda, Francesco & Fatima, Zarrin, 2019. "Northern European nearly zero energy building concepts for apartment buildings using integrated solar technologies and dynamic occupancy profile: Focus on Finland and other Northern European countries," Applied Energy, Elsevier, vol. 237(C), pages 598-617.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Primitivo Díaz & Marco Pérez-Cisneros & Erik Cuevas & Omar Avalos & Jorge Gálvez & Salvador Hinojosa & Daniel Zaldivar, 2018. "An Improved Crow Search Algorithm Applied to Energy Problems," Energies, MDPI, vol. 11(3), pages 1-22, March.
    2. Sauer, Ildo L. & Tatizawa, Hédio & Salotti, Francisco A.M. & Mercedes, Sonia S., 2015. "A comparative assessment of Brazilian electric motors performance with minimum efficiency standards," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 308-318.
    3. Yoon, Hae-Sung & Kim, Eun-Seob & Kim, Min-Soo & Lee, Jang-Yeob & Lee, Gyu-Bong & Ahn, Sung-Hoon, 2015. "Towards greener machine tools – A review on energy saving strategies and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 870-891.
    4. Louback, Eduardo & Biswas, Atriya & Machado, Fabricio & Emadi, Ali, 2024. "A review of the design process of energy management systems for dual-motor battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    5. Miguel Castro Oliveira & Muriel Iten & Pedro L. Cruz & Helena Monteiro, 2020. "Review on Energy Efficiency Progresses, Technologies and Strategies in the Ceramic Sector Focusing on Waste Heat Recovery," Energies, MDPI, vol. 13(22), pages 1-24, November.
    6. Md Junayed Hasan & Jong-Myon Kim, 2019. "Fault Detection of a Spherical Tank Using a Genetic Algorithm-Based Hybrid Feature Pool and k-Nearest Neighbor Algorithm," Energies, MDPI, vol. 12(6), pages 1-14, March.
    7. Nogueira Vilanova, Mateus Ricardo & Perrella Balestieri, José Antônio, 2014. "Energy and hydraulic efficiency in conventional water supply systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 701-714.
    8. Ibrahem Hussein & Zakariya Al-Hamouz & M. A. Abido & Abdulaziz Milhem, 2018. "On the Mathematical Modeling of Line-Start Permanent Magnet Synchronous Motors under Static Eccentricity," Energies, MDPI, vol. 11(1), pages 1-17, January.
    9. Madlool, N.A. & Saidur, R. & Rahim, N.A. & Kamalisarvestani, M., 2013. "An overview of energy savings measures for cement industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 18-29.
    10. Yilmaz, Murat, 2015. "Limitations/capabilities of electric machine technologies and modeling approaches for electric motor design and analysis in plug-in electric vehicle applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 80-99.
    11. Mekhilef, S. & Saidur, R. & Safari, A., 2011. "A review on solar energy use in industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1777-1790, May.
    12. Osamu Shimizu & Sakahisa Nagai & Toshiyuki Fujita & Hiroshi Fujimoto, 2020. "Potential for CO 2 Reduction by Dynamic Wireless Power Transfer for Passenger Vehicles in Japan," Energies, MDPI, vol. 13(13), pages 1-16, June.
    13. Firth, Anton & Zhang, Bo & Yang, Aidong, 2019. "Quantification of global waste heat and its environmental effects," Applied Energy, Elsevier, vol. 235(C), pages 1314-1334.
    14. Thirugnanasambandam, M. & Hasanuzzaman, M. & Saidur, R. & Ali, M.B. & Rajakarunakaran, S. & Devaraj, D. & Rahim, N.A., 2011. "Analysis of electrical motors load factors and energy savings in an Indian cement industry," Energy, Elsevier, vol. 36(7), pages 4307-4314.
    15. Rashmi R. Mohanty & A. Subash Babu, 2022. "Quality management in a fractional horsepower electrical motor industry: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2764-2789, October.
    16. Diao, Kaikai & Sun, Xiaodong & Bramerdorfer, Gerd & Cai, Yingfeng & Lei, Gang & Chen, Long, 2022. "Design optimization of switched reluctance machines for performance and reliability enhancements: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    17. Ahamed, J.U. & Madlool, N.A. & Saidur, R. & Shahinuddin, M.I. & Kamyar, A. & Masjuki, H.H., 2012. "Assessment of energy and exergy efficiencies of a grate clinker cooling system through the optimization of its operational parameters," Energy, Elsevier, vol. 46(1), pages 664-674.
    18. Wang, Zanxin & Wei, Wei, 2017. "External cost of photovoltaic oriented silicon production: A case in China," Energy Policy, Elsevier, vol. 107(C), pages 437-447.
    19. Paramonova, Svetlana & Nehler, Therese & Thollander, Patrik, 2021. "Technological change or process innovation – An empirical study of implemented energy efficiency measures from a Swedish industrial voluntary agreements program," Energy Policy, Elsevier, vol. 156(C).
    20. Saidur, R. & Hossain, M.S. & Islam, M.R. & Fayaz, H. & Mohammed, H.A., 2011. "A review on kiln system modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2487-2500, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:27-:d:192619. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.