IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i8p2103-d163458.html
   My bibliography  Save this article

A Study on the Fuel Economy Potential of Parallel and Power Split Type Hybrid Electric Vehicles

Author

Listed:
  • Hyunhwa Kim

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon-si 16419, Korea)

  • Junbeom Wi

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon-si 16419, Korea)

  • Jiho Yoo

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon-si 16419, Korea)

  • Hanho Son

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon-si 16419, Korea)

  • Chiman Park

    (Eco-Vehicle R&D Division, Hyundai Powertech, Hwaseong-si 18583, Korea)

  • Hyunsoo Kim

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon-si 16419, Korea)

Abstract

What is the best number of gear steps for parallel type hybrid electric vehicles (HEVs) and what are the pros and cons of the power split type HEV compared to the parallel type have been interesting issues in the development of HEVs. In this study, a comparative analysis was performed to evaluate the fuel economy potential of a parallel HEV and a power split type HEV. First, the fuel economy potential of the parallel HEV was investigated for the number of gear steps. Four-speed, six-speed, and eight-speed automatic transmissions (ATs) and a continuously variable transmission (CVT) were selected, and their drivetrain losses were considered in the dynamic programming (DP). It was found from DP results that the power electronics system (PE) loss decreased because the magnitude of the motor load leveling power decreased as the number of gear steps increased. On the other hand, the drivetrain losses including the electric oil pump (EOP) loss increased with increasing gear step. The improvement rate from the 4-speed to the 6-speed was the greatest, while it decreased for the higher gear step. The fuel economy of the CVT HEV was rather low due to the large EOP loss in spite of the reduced PE loss. In addition, the powertrain characteristics of the parallel HEV were compared with the power split type HEV. In the power split type HEV, the PE loss was almost double compared to that of the parallel HEV because two large capacity motor-generators were used. However, the drivetrain loss and EOP loss of the power split type HEV were found to be much smaller due to its relatively simple architecture. It is expected that the power characteristics of the parallel and power split type HEVs obtained from the DP results can be used in the development of HEV systems.

Suggested Citation

  • Hyunhwa Kim & Junbeom Wi & Jiho Yoo & Hanho Son & Chiman Park & Hyunsoo Kim, 2018. "A Study on the Fuel Economy Potential of Parallel and Power Split Type Hybrid Electric Vehicles," Energies, MDPI, vol. 11(8), pages 1-19, August.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2103-:d:163458
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/8/2103/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/8/2103/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hanho Son & Kyusik Park & Sungho Hwang & Hyunsoo Kim, 2017. "Design Methodology of a Power Split Type Plug-In Hybrid Electric Vehicle Considering Drivetrain Losses," Energies, MDPI, vol. 10(4), pages 1-18, March.
    2. Yang, Yalian & Hu, Xiaosong & Pei, Huanxin & Peng, Zhiyuan, 2016. "Comparison of power-split and parallel hybrid powertrain architectures with a single electric machine: Dynamic programming approach," Applied Energy, Elsevier, vol. 168(C), pages 683-690.
    3. Hanho Son & Hyunsoo Kim, 2016. "Development of Near Optimal Rule-Based Control for Plug-In Hybrid Electric Vehicles Taking into Account Drivetrain Component Losses," Energies, MDPI, vol. 9(6), pages 1-18, May.
    4. Ximing Wang & Hongwen He & Fengchun Sun & Jieli Zhang, 2015. "Application Study on the Dynamic Programming Algorithm for Energy Management of Plug-in Hybrid Electric Vehicles," Energies, MDPI, vol. 8(4), pages 1-20, 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. Keun-Young Yoon & Soo-Whang Baek, 2019. "Robust Design Optimization with Penalty Function for Electric Oil Pumps with BLDC Motors," Energies, MDPI, vol. 12(1), pages 1-14, January.
    2. Branimir Škugor & Joško Petrić, 2018. "Optimization of Control Variables and Design of Management Strategy for Hybrid Hydraulic Vehicle," Energies, MDPI, vol. 11(10), pages 1-24, October.
    3. Bảo-Huy Nguyễn & João Pedro F. Trovão & Ronan German & Alain Bouscayrol, 2020. "Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation," Energies, MDPI, vol. 13(21), pages 1-19, October.
    4. Md Ragib Ahssan & Mehran Ektesabi & Saman Gorji, 2020. "Gear Ratio Optimization along with a Novel Gearshift Scheduling Strategy for a Two-Speed Transmission System in Electric Vehicle," Energies, MDPI, vol. 13(19), pages 1-24, September.
    5. Matteo Repetto & Massimiliano Passalacqua & Luis Vaccaro & Mario Marchesoni & Alessandro Pini Prato, 2020. "Turbocompound Power Unit Modelling for a Supercapacitor-Based Series Hybrid Vehicle Application," Energies, MDPI, vol. 13(2), pages 1-20, January.

    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. Jing Lian & Shuang Liu & Linhui Li & Xuanzuo Liu & Yafu Zhou & Fan Yang & Lushan Yuan, 2017. "A Mixed Logical Dynamical-Model Predictive Control (MLD-MPC) Energy Management Control Strategy for Plug-in Hybrid Electric Vehicles (PHEVs)," Energies, MDPI, vol. 10(1), pages 1-18, January.
    2. Wang, Yue & Zeng, Xiaohua & Song, Dafeng & Yang, Nannan, 2019. "Optimal rule design methodology for energy management strategy of a power-split hybrid electric bus," Energy, Elsevier, vol. 185(C), pages 1086-1099.
    3. Hanho Son & Kyusik Park & Sungho Hwang & Hyunsoo Kim, 2017. "Design Methodology of a Power Split Type Plug-In Hybrid Electric Vehicle Considering Drivetrain Losses," Energies, MDPI, vol. 10(4), pages 1-18, March.
    4. Xu, Nan & Kong, Yan & Zhang, Yuanjian & Yue, Fenglai & Sui, Yan & Li, Xiaohan & Liu, Heng & Xu, Zhe, 2022. "Determination of vehicle working modes for global optimization energy management and evaluation of the economic performance for a certain control strategy," Energy, Elsevier, vol. 251(C).
    5. Hanho Son & Hyunhwa Kim & Sungho Hwang & Hyunsoo Kim, 2018. "Development of an Advanced Rule-Based Control Strategy for a PHEV Using Machine Learning," Energies, MDPI, vol. 11(1), pages 1-15, January.
    6. Yongjian Zhou & Rong Yang & Song Zhang & Kejun Lan & Wei Huang, 2023. "Optimization of Power-System Parameters and Energy-Management Strategy Research on Hybrid Heavy-Duty Trucks," Energies, MDPI, vol. 16(17), pages 1-21, August.
    7. Wang, Bin & Xu, Jun & Cao, Binggang & Ning, Bo, 2017. "Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 596-608.
    8. Du, Jiuyu & Chen, Jingfu & Song, Ziyou & Gao, Mingming & Ouyang, Minggao, 2017. "Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness," Energy, Elsevier, vol. 121(C), pages 32-42.
    9. 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.
    10. Anselma, Pier Giuseppe, 2022. "Computationally efficient evaluation of fuel and electrical energy economy of plug-in hybrid electric vehicles with smooth driving constraints," Applied Energy, Elsevier, vol. 307(C).
    11. Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2020. "Comparison of four-wheel-drive hybrid powertrain configurations," Energy, Elsevier, vol. 209(C).
    12. Hanho Son & Hyunsoo Kim, 2016. "Development of Near Optimal Rule-Based Control for Plug-In Hybrid Electric Vehicles Taking into Account Drivetrain Component Losses," Energies, MDPI, vol. 9(6), pages 1-18, May.
    13. Singh, Somendra Pratap & Hanif, Athar & Ahmed, Qadeer & Meijer, Maarten & Lahti, John, 2022. "Optimal management of electric hotel loads in mild hybrid heavy duty truck," Applied Energy, Elsevier, vol. 326(C).
    14. Jacek Pielecha & Kinga Skobiej & Przemyslaw Kubiak & Marek Wozniak & Krzysztof Siczek, 2022. "Exhaust Emissions from Plug-in and HEV Vehicles in Type-Approval Tests and Real Driving Cycles," Energies, MDPI, vol. 15(7), pages 1-38, March.
    15. Xiangyang Xu & Xiaoxiao Wu & Mick Jordan & Peng Dong & Yang Liu, 2018. "Coordinated Engine-Start Control of Single-Motor P2 Hybrid Electric Vehicles with Respect to Different Driving Situations," Energies, MDPI, vol. 11(1), pages 1-23, January.
    16. Pan, Haihong & Lü, Zhiqiang & Lin, Weilong & Li, Junzi & Chen, Lin, 2017. "State of charge estimation of lithium-ion batteries using a grey extended Kalman filter and a novel open-circuit voltage model," Energy, Elsevier, vol. 138(C), pages 764-775.
    17. Song, Ziyou & Li, Jianqiu & Hou, Jun & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "The battery-supercapacitor hybrid energy storage system in electric vehicle applications: A case study," Energy, Elsevier, vol. 154(C), pages 433-441.
    18. Zhuang, Weichao & Zhang, Xiaowu & Li, Daofei & Wang, Liangmo & Yin, Guodong, 2017. "Mode shift map design and integrated energy management control of a multi-mode hybrid electric vehicle," Applied Energy, Elsevier, vol. 204(C), pages 476-488.
    19. Pei, Huanxin & Hu, Xiaosong & Yang, Yalian & Tang, Xiaolin & Hou, Cong & Cao, Dongpu, 2018. "Configuration optimization for improving fuel efficiency of power split hybrid powertrains with a single planetary gear," Applied Energy, Elsevier, vol. 214(C), pages 103-116.
    20. 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.

    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:11:y:2018:i:8:p:2103-:d:163458. 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.