IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i16p3170-d258702.html
   My bibliography  Save this article

Vehicle Optimal Control Design to Meet the 1.5 °C Target: A Control Design Framework for Vehicle Subsystems

Author

Listed:
  • Xu Hu

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Yisong Chen

    (School of Automobile, Chang’an University, Xi’an 710064, China)

  • Zhensen Ding

    (Automotive Engineering Institute, Guangzhou Automobile Group Co., Ltd., Guangzhou 511434, China)

  • Liang Gu

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

Abstract

Current studies have achieved energy savings of vehicle subsystems through various control strategies, but these control strategies lack a benchmark to measure whether these energy savings are sufficient. This work proposes a control design framework that uses the 1.5 °C target in the Paris Agreement as a benchmark to measure the adequacy of energy savings of vehicle subsystems. This control design framework involves two points. One is the conversion of the 1.5 °C target into a constraint on the energy consumption of a vehicle subsystem. The other is the optimal control design of the vehicle subsystem under this constraint. To describe the specific application of this control design framework, we conduct a case study concerning the control design of active suspension in a battery electric light-duty vehicle. By comparison with a widely used linear quadratic regulator (LQR) method, we find that this control design framework can both ensure the performance comparable to the LQR method and help to meet the 1.5 °C target in the Paris Climate Agreement. In addition, a sensitivity analysis shows that the control effect is hardly changed by battery electric vehicle market share and electricity CO 2 intensity. This work might provide insight on ways that the automotive industry could contribute to the Paris Agreement.

Suggested Citation

  • Xu Hu & Yisong Chen & Zhensen Ding & Liang Gu, 2019. "Vehicle Optimal Control Design to Meet the 1.5 °C Target: A Control Design Framework for Vehicle Subsystems," Energies, MDPI, vol. 12(16), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3170-:d:258702
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/16/3170/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/16/3170/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huang, Yanjun & Khajepour, Amir & Ding, Haitao & Bagheri, Farshid & Bahrami, Majid, 2017. "An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 188(C), pages 576-585.
    2. 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.
    3. Guoqing Geng & Qingyuan Shen & Haobin Jiang, 2019. "ANFTS Mode Control for an Electronically Controlled Hydraulic Power Steering System on a Permanent Magnet Slip Clutch," Energies, MDPI, vol. 12(9), pages 1-22, May.
    4. Abu Hanifah, Rabiatuladawiyah & Toha, Siti Fauziah & Hassan, Mohd Khair & Ahmad, Salmiah, 2016. "Power reduction optimization with swarm based technique in electric power assist steering system," Energy, Elsevier, vol. 102(C), pages 444-452.
    5. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    6. Hao, Han & Geng, Yong & Sarkis, Joseph, 2016. "Carbon footprint of global passenger cars: Scenarios through 2050," Energy, Elsevier, vol. 101(C), pages 121-131.
    7. Gambhir, Ajay & Tse, Lawrence K.C. & Tong, Danlu & Martinez-Botas, Ricardo, 2015. "Reducing China’s road transport sector CO2 emissions to 2050: Technologies, costs and decomposition analysis," Applied Energy, Elsevier, vol. 157(C), pages 905-917.
    8. Camilo Mora & Randi L. Rollins & Katie Taladay & Michael B. Kantar & Mason K. Chock & Mio Shimada & Erik C. Franklin, 2018. "Bitcoin emissions alone could push global warming above 2°C," Nature Climate Change, Nature, vol. 8(11), pages 931-933, November.
    9. Han, Zhongliang & Xu, Nan & Chen, Hong & Huang, Yanjun & Zhao, Bin, 2018. "Energy-efficient control of electric vehicles based on linear quadratic regulator and phase plane analysis," Applied Energy, Elsevier, vol. 213(C), pages 639-657.
    10. Li, Liang & Li, Xujian & Wang, Xiangyu & Song, Jian & He, Kai & Li, Chenfeng, 2016. "Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking," Applied Energy, Elsevier, vol. 176(C), pages 125-137.
    Full references (including those not matched with items on IDEAS)

    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. Muhammad Khalid, 2019. "A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids," Energies, MDPI, vol. 12(23), pages 1-34, November.
    2. Han, Zhongliang & Xu, Nan & Chen, Hong & Huang, Yanjun & Zhao, Bin, 2018. "Energy-efficient control of electric vehicles based on linear quadratic regulator and phase plane analysis," Applied Energy, Elsevier, vol. 213(C), pages 639-657.
    3. Jiangbo Wang & Kai Liu & Toshiyuki Yamamoto, 2017. "Improving Electricity Consumption Estimation for Electric Vehicles Based on Sparse GPS Observations," Energies, MDPI, vol. 10(1), pages 1-12, January.
    4. Liu, Yang & Zhang, Qi & Lyu, Cheng & Liu, Zhiyuan, 2021. "Modelling the energy consumption of electric vehicles under uncertain and small data conditions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 313-328.
    5. Antonia Tamborrino & Claudio Perone & Filippo Catalano & Giacomo Squeo & Francesco Caponio & Biagio Bianchi, 2019. "Modelling Energy Consumption and Energy-Saving in High-Quality Olive Oil Decanter Centrifuge: Numerical Study and Experimental Validation," Energies, MDPI, vol. 12(13), pages 1-20, July.
    6. Huang, Xianghui & Li, Kuining & Xie, Yi & Liu, Bin & Liu, Jiangyan & Liu, Zhaoming & Mou, Lunjie, 2022. "A novel multistage constant compressor speed control strategy of electric vehicle air conditioning system based on genetic algorithm," Energy, Elsevier, vol. 241(C).
    7. Fang, Kai & Li, Chenglin & Tang, Yiqi & He, Jianjian & Song, Junnian, 2022. "China’s pathways to peak carbon emissions: New insights from various industrial sectors," Applied Energy, Elsevier, vol. 306(PA).
    8. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2016. "Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 1351-1360.
    9. Cui, Taowen & Zhao, Wanzhong & Wang, Chunyan, 2019. "Design optimization of vehicle EHPS system based on multi-objective genetic algorithm," Energy, Elsevier, vol. 179(C), pages 100-110.
    10. Zhang, Yuxin & Chen, Hong & Guo, Konghui & Zhang, Xinjie & Eben Li, Shengbo, 2017. "Electro-hydraulic damper for energy harvesting suspension: Modeling, prototyping and experimental validation," Applied Energy, Elsevier, vol. 199(C), pages 1-12.
    11. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2018. "Exploring the interactive effects of ambient temperature and vehicle auxiliary loads on electric vehicle energy consumption," Applied Energy, Elsevier, vol. 227(C), pages 324-331.
    12. Xie, Yunkun & Li, Yangyang & Zhao, Zhichao & Dong, Hao & Wang, Shuqian & Liu, Jingping & Guan, Jinhuan & Duan, Xiongbo, 2020. "Microsimulation of electric vehicle energy consumption and driving range," Applied Energy, Elsevier, vol. 267(C).
    13. Yashraj Tripathy & Andrew McGordon & Anup Barai, 2020. "Improving Accessible Capacity Tracking at Low Ambient Temperatures for Range Estimation of Battery Electric Vehicles," Energies, MDPI, vol. 13(8), pages 1-18, April.
    14. K. S. Reddy & S. Aravindhan & Tapas K. Mallick, 2017. "Techno-Economic Investigation of Solar Powered Electric Auto-Rickshaw for a Sustainable Transport System," Energies, MDPI, vol. 10(6), pages 1-15, May.
    15. Li, Xi & Yu, Biying, 2019. "Peaking CO2 emissions for China's urban passenger transport sector," Energy Policy, Elsevier, vol. 133(C).
    16. 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.
    17. Lin William Cong & Zhiguo He & Jiasun Li & Wei Jiang, 2021. "Decentralized Mining in Centralized Pools [Concentrating on the fall of the labor share]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1191-1235.
    18. Boyi Xiao & Huazhong Lu & Hailin Wang & Jiageng Ruan & Nong Zhang, 2017. "Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis," Energies, MDPI, vol. 10(11), pages 1-19, November.
    19. Nan, Sirui & Tu, Ran & Li, Tiezhu & Sun, Jian & Chen, Haibo, 2022. "From driving behavior to energy consumption: A novel method to predict the energy consumption of electric bus," Energy, Elsevier, vol. 261(PA).
    20. Tattini, Jacopo & Ramea, Kalai & Gargiulo, Maurizio & Yang, Christopher & Mulholland, Eamonn & Yeh, Sonia & Karlsson, Kenneth, 2018. "Improving the representation of modal choice into bottom-up optimization energy system models – The MoCho-TIMES model," Applied Energy, Elsevier, vol. 212(C), pages 265-282.

    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:2019:i:16:p:3170-:d:258702. 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.