IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i5p700-d98794.html
   My bibliography  Save this article

The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption

Author

Listed:
  • Junhui Liu

    (School of Electro-Mechanical Engineering, Xidian University, Xi’an 710071, China
    Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xi’an 710071, China)

  • Lei Feng

    (Department of Machine Design, KTH Royal Institute of Technology, Stockholm SE-10044, Sweden)

  • Zhiwu Li

    (School of Electro-Mechanical Engineering, Xidian University, Xi’an 710071, China
    Institute of Systems Engineering, Macau University of Science and Technology, Taipa 999078, Macau)

Abstract

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.

Suggested Citation

  • Junhui Liu & Lei Feng & Zhiwu Li, 2017. "The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption," Energies, MDPI, vol. 10(5), pages 1-31, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:700-:d:98794
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/5/700/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/5/700/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khodabakhshian, Mohammad & Feng, Lei & Börjesson, Stefan & Lindgärde, Olof & Wikander, Jan, 2017. "Reducing auxiliary energy consumption of heavy trucks by onboard prediction and real-time optimization," Applied Energy, Elsevier, vol. 188(C), pages 652-671.
    2. Francesco Bottiglione & Stefano De Pinto & Giacomo Mantriota & Aldo Sorniotti, 2014. "Energy Consumption of a Battery Electric Vehicle with Infinitely Variable Transmission," Energies, MDPI, vol. 7(12), pages 1-21, December.
    3. Fengqi Zhang & Haiou Liu & Yuhui Hu & Junqiang Xi, 2016. "A Supervisory Control Algorithm of Hybrid Electric Vehicle Based on Adaptive Equivalent Consumption Minimization Strategy with Fuzzy PI," Energies, MDPI, vol. 9(11), pages 1-26, November.
    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. Adriano Ceschia & Toufik Azib & Olivier Bethoux & Francisco Alves, 2022. "Multi-Criteria Optimal Design for FUEL Cell Hybrid Power Sources," Energies, MDPI, vol. 15(9), pages 1-18, May.
    2. Adriano Ceschia & Toufik Azib & Olivier Bethoux & Francisco Alves, 2020. "Optimal Sizing of Fuel Cell Hybrid Power Sources with Reliability Consideration," Energies, MDPI, vol. 13(13), pages 1-18, July.

    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. Stefano De Pinto & Pablo Camocardi & Christoforos Chatzikomis & Aldo Sorniotti & Francesco Bottiglione & Giacomo Mantriota & Pietro Perlo, 2020. "On the Comparison of 2- and 4-Wheel-Drive Electric Vehicle Layouts with Central Motors and Single- and 2-Speed Transmission Systems," Energies, MDPI, vol. 13(13), pages 1-24, June.
    2. Milan Perkušić & Damir Jelaska & Srdjan Podrug & Vjekoslav Tvrdić, 2017. "On the Feasibility of Independently Controllable Transmissions," Energies, MDPI, vol. 10(11), pages 1-13, November.
    3. Ruan, Jiageng & Walker, Paul & Zhang, Nong, 2016. "A comparative study energy consumption and costs of battery electric vehicle transmissions," Applied Energy, Elsevier, vol. 165(C), pages 119-134.
    4. Ruan, Jiageng & Walker, Paul D. & Watterson, Peter A. & Zhang, Nong, 2016. "The dynamic performance and economic benefit of a blended braking system in a multi-speed battery electric vehicle," Applied Energy, Elsevier, vol. 183(C), pages 1240-1258.
    5. Polychronis Spanoudakis & Nikolaos C. Tsourveloudis & Lefteris Doitsidis & Emmanuel S. Karapidakis, 2019. "Experimental Research of Transmissions on Electric Vehicles’ Energy Consumption," Energies, MDPI, vol. 12(3), pages 1-15, January.
    6. Fengqi Zhang & Lihua Wang & Serdar Coskun & Hui Pang & Yahui Cui & Junqiang Xi, 2020. "Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook," Energies, MDPI, vol. 13(13), pages 1-35, June.
    7. Massimiliano Passalacqua & Mauro Carpita & Serge Gavin & Mario Marchesoni & Matteo Repetto & Luis Vaccaro & Sébastien Wasterlain, 2019. "Supercapacitor Storage Sizing Analysis for a Series Hybrid Vehicle," Energies, MDPI, vol. 12(9), pages 1-15, May.
    8. Xie, Shaobo & Hu, Xiaosong & Qi, Shanwei & Lang, Kun, 2018. "An artificial neural network-enhanced energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 163(C), pages 837-848.
    9. Qixiang Yan & Ibrahim Adamu Tasiu & Hong Chen & Yuting Zhang & Siqi Wu & Zhigang Liu, 2019. "Design and Hardware-in-the-Loop Implementation of Fuzzy-Based Proportional-Integral Control for the Traction Line-Side Converter of a High-Speed Train," Energies, MDPI, vol. 12(21), pages 1-24, October.
    10. Polychronis Spanoudakis & Gerasimos Moschopoulos & Theodoros Stefanoulis & Nikolaos Sarantinoudis & Eftichios Papadokokolakis & Ioannis Ioannou & Savvas Piperidis & Lefteris Doitsidis & Nikolaos C. Ts, 2020. "Efficient Gear Ratio Selection of a Single-Speed Drivetrain for Improved Electric Vehicle Energy Consumption," Sustainability, MDPI, vol. 12(21), pages 1-19, November.
    11. Wei, Zhichen & Calautit, John Kaiser, 2024. "Field experiment testing of a low-cost model predictive controller (MPC) for building heating systems and analysis of phase change material (PCM) integration," Applied Energy, Elsevier, vol. 360(C).
    12. Antti Ritari & Jari Vepsäläinen & Klaus Kivekäs & Kari Tammi & Heikki Laitinen, 2020. "Energy Consumption and Lifecycle Cost Analysis of Electric City Buses with Multispeed Gearboxes," Energies, MDPI, vol. 13(8), pages 1-21, April.
    13. Jarosław Mamala & Michał Śmieja & Krzysztof Prażnowski, 2021. "Analysis of the Total Unit Energy Consumption of a Car with a Hybrid Drive System in Real Operating Conditions," Energies, MDPI, vol. 14(13), pages 1-16, July.
    14. Pengyu Lu & Qing Gao & Liang Lv & Xiaoye Xue & Yan Wang, 2019. "Numerical Calculation Method of Model Predictive Control for Integrated Vehicle Thermal Management Based on Underhood Coupling Thermal Transmission," Energies, MDPI, vol. 12(2), pages 1-27, January.
    15. Wang, Bin & Ma, Guangliang & Xu, Dan & Zhang, Le & Zhou, Jiahui, 2018. "Switching sliding-mode control strategy based on multi-type restrictive condition for voltage control of buck converter in auxiliary energy source," Applied Energy, Elsevier, vol. 228(C), pages 1373-1384.
    16. Shaobo Xie & Huiling Li & Zongke Xin & Tong Liu & Lang Wei, 2017. "A Pontryagin Minimum Principle-Based Adaptive Equivalent Consumption Minimum Strategy for a Plug-in Hybrid Electric Bus on a Fixed Route," Energies, MDPI, vol. 10(9), pages 1-22, September.
    17. Yuping Zeng & Yang Cai & Guiyue Kou & Wei Gao & Datong Qin, 2018. "Energy Management for Plug-In Hybrid Electric Vehicle Based on Adaptive Simplified-ECMS," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
    18. Guo, Hongqiang & Lu, Silong & Hui, Hongzhong & Bao, Chunjiang & Shangguan, Jinyong, 2019. "Receding horizon control-based energy management for plug-in hybrid electric buses using a predictive model of terminal SOC constraint in consideration of stochastic vehicle mass," Energy, Elsevier, vol. 176(C), pages 292-308.
    19. Xing, Yang & Lv, Chen & Cao, Dongpu & Lu, Chao, 2020. "Energy oriented driving behavior analysis and personalized prediction of vehicle states with joint time series modeling," Applied Energy, Elsevier, vol. 261(C).
    20. Graba, M. & Mamala, J. & Bieniek, A. & Sroka, Z., 2021. "Impact of the acceleration intensity of a passenger car in a road test on energy consumption," Energy, Elsevier, vol. 226(C).

    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:10:y:2017:i:5:p:700-:d:98794. 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.