IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i2p725-d1028688.html
   My bibliography  Save this article

Configurations and Control Strategies of Hybrid Powertrain Systems

Author

Listed:
  • Huijun Yue

    (Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China)

  • Jinyu Lin

    (Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China)

  • Peng Dong

    (Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing 100191, China)

  • Zhinan Chen

    (Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China)

  • Xiangyang Xu

    (Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing 100191, China)

Abstract

The configuration and control strategy of hybrid powertrain systems are significant for the development of hybrid electric vehicles (HEV) because they significantly affect their comprehensive performance. In this paper, the types, features, and applications of the mainstream hybrid powertrain configurations on the market in recent years are summarized and the effects of different configurations on the comprehensive performance of HEVs are compared. Moreover, the technical routes for each hybrid configuration are highlighted, as configuration optimization methods have become a technical difficulty. In addition, the technological advances in the steady-state energy management strategy and dynamic coordinated control strategy for hybrid powertrain systems are studied. The optimization of the steady-state energy management strategy mainly involves assigning the working point and working range of each power source reasonably. However, with the increase in the complexity of optimization algorithms, real-time control of HEVs still needs to be improved. The optimization of the dynamic coordinated control strategy mainly focuses on the stability and smoothness of the dynamic process involving switching and shifting the working mode. The optimization of the dynamic control process for the system remains to be further improved. It is pointed out that the configurations and strategies should be optimized jointly to obtain a comprehensive improvement in the system performance. This paper provides an informative basis and technical support for the design and optimization of a hybrid powertrain system.

Suggested Citation

  • Huijun Yue & Jinyu Lin & Peng Dong & Zhinan Chen & Xiangyang Xu, 2023. "Configurations and Control Strategies of Hybrid Powertrain Systems," Energies, MDPI, vol. 16(2), pages 1-18, January.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:725-:d:1028688
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/2/725/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/2/725/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Yalian & Li, Pengshuai & Pei, Huanxin & Zou, Yunge, 2022. "Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory," Energy, Elsevier, vol. 242(C).
    2. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    3. Chen, Syuan-Yi & Wu, Chien-Hsun & Hung, Yi-Hsuan & Chung, Cheng-Ta, 2018. "Optimal strategies of energy management integrated with transmission control for a hybrid electric vehicle using dynamic particle swarm optimization," Energy, Elsevier, vol. 160(C), pages 154-170.
    4. Weichao Zhuang & Xiaowu Zhang & Huei Peng & Liangmo Wang, 2016. "Simultaneous Optimization of Topology and Component Sizes for Double Planetary Gear Hybrid Powertrains," Energies, MDPI, vol. 9(6), pages 1-17, May.
    5. Wei Wang & Zhenjiang Cai & Shaofei Liu, 2021. "Design of Real-Time Control Based on DP and ECMS for PHEVs," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, February.
    6. Yongbing Xiang & Xiaomin Yang, 2021. "An ECMS for Multi-Objective Energy Management Strategy of Parallel Diesel Electric Hybrid Ship Based on Ant Colony Optimization Algorithm," Energies, MDPI, vol. 14(4), pages 1-21, February.
    7. 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.
    8. Jing Sun & Guojing Xing & Chenghui Zhang, 2017. "Data-Driven Predictive Torque Coordination Control during Mode Transition Process of Hybrid Electric Vehicles," Energies, MDPI, vol. 10(4), pages 1-21, April.
    9. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    10. Woong Lee & Tacksu Kim & Jongryeol Jeong & Jaewoo Chung & Deokjin Kim & Beomho Lee & Namwook Kim, 2020. "Control Analysis of a Real-World P2 Hybrid Electric Vehicle Based on Test Data," Energies, MDPI, vol. 13(16), pages 1-15, August.
    11. Yang, Yalian & Pei, Huanxin & Hu, Xiaosong & Liu, Yonggang & Hou, Cong & Cao, Dongpu, 2019. "Fuel economy optimization of power split hybrid vehicles: A rapid dynamic programming approach," Energy, Elsevier, vol. 166(C), pages 929-938.
    12. Yang Yang & Chao Wang & Quanrang Zhang & Xiaolong He, 2017. "Torque Coordination Control during Braking Mode Switch for a Plug-in Hybrid Electric Vehicle," Energies, MDPI, vol. 10(11), pages 1-16, October.
    13. Liu, Hongxiang & Han, Ling & Cao, Yue, 2020. "Improving transmission efficiency and reducing energy consumption with automotive continuously variable transmission: A model prediction comprehensive optimization approach," Applied Energy, Elsevier, vol. 274(C).
    14. Qin, Zhaobo & Luo, Yugong & Zhuang, Weichao & Pan, Ziheng & Li, Keqiang & Peng, Huei, 2018. "Simultaneous optimization of topology, control and size for multi-mode hybrid tracked vehicles," Applied Energy, Elsevier, vol. 212(C), pages 1627-1641.
    15. 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.
    16. Tobias Nüesch & Philipp Elbert & Michael Flankl & Christopher Onder & Lino Guzzella, 2014. "Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs," Energies, MDPI, vol. 7(2), pages 1-23, February.
    17. Hassanzadeh, Mojtaba & Rahmani, Zahra, 2022. "A predictive controller for real-time energy management of plug-in hybrid electric vehicles," Energy, Elsevier, vol. 249(C).
    18. 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.
    19. Teng Liu & Yuan Zou & Dexing Liu & Fengchun Sun, 2015. "Reinforcement Learning–Based Energy Management Strategy for a Hybrid Electric Tracked Vehicle," Energies, MDPI, vol. 8(7), pages 1-18, July.
    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. Francesco Mocera & Aurelio Somà & Salvatore Martelli & Valerio Martini, 2023. "Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications," Energies, MDPI, vol. 16(18), pages 1-36, September.

    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. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    2. Zhou, Xingyu & Sun, Chao & Sun, Fengchun & Zhang, Chuntao, 2023. "Commuting-pattern-oriented stochastic optimization of electric powertrains for revealing contributions of topology modifications to the powertrain energy efficiency," Applied Energy, Elsevier, vol. 344(C).
    3. 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).
    4. Ju, Fei & Zhuang, Weichao & Wang, Liangmo & Zhang, Zhe, 2020. "Comparison of four-wheel-drive hybrid powertrain configurations," Energy, Elsevier, vol. 209(C).
    5. Yang, Yalian & Li, Pengshuai & Pei, Huanxin & Zou, Yunge, 2022. "Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory," Energy, Elsevier, vol. 242(C).
    6. Wang, Yue & Zeng, Xiaohua & Song, Dafeng, 2020. "Hierarchical optimal intelligent energy management strategy for a power-split hybrid electric bus based on driving information," Energy, Elsevier, vol. 199(C).
    7. Yang, Yalian & Pei, Huanxin & Hu, Xiaosong & Liu, Yonggang & Hou, Cong & Cao, Dongpu, 2019. "Fuel economy optimization of power split hybrid vehicles: A rapid dynamic programming approach," Energy, Elsevier, vol. 166(C), pages 929-938.
    8. Anselma, Pier Giuseppe & Biswas, Atriya & Belingardi, Giovanni & Emadi, Ali, 2020. "Rapid assessment of the fuel economy capability of parallel and series-parallel hybrid electric vehicles," Applied Energy, Elsevier, vol. 275(C).
    9. Anselma, Pier Giuseppe, 2022. "Electrified powertrain sizing for vehicle fleets of car makers considering total ownership costs and CO2 emission legislation scenarios," Applied Energy, Elsevier, vol. 314(C).
    10. Geng, Wenran & Lou, Diming & Wang, Chen & Zhang, Tong, 2020. "A cascaded energy management optimization method of multimode power-split hybrid electric vehicles," Energy, Elsevier, vol. 199(C).
    11. Rajput, Daizy & Herreros, Jose M. & Innocente, Mauro S. & Bryans, Jeremy & Schaub, Joschka & Dizqah, Arash M., 2022. "Impact of the number of planetary gears on the energy efficiency of electrified powertrains," Applied Energy, Elsevier, vol. 323(C).
    12. Zhou, Xingyu & Qin, Datong & Hu, Jianjun, 2017. "Multi-objective optimization design and performance evaluation for plug-in hybrid electric vehicle powertrains," Applied Energy, Elsevier, vol. 208(C), pages 1608-1625.
    13. Liu, Teng & Tan, Wenhao & Tang, Xiaolin & Zhang, Jinwei & Xing, Yang & Cao, Dongpu, 2021. "Driving conditions-driven energy management strategies for hybrid electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    14. 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.
    15. Du, Guodong & Zou, Yuan & Zhang, Xudong & Kong, Zehui & Wu, Jinlong & He, Dingbo, 2019. "Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. 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.
    17. 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.
    18. 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.
    19. Wu, Changcheng & Ruan, Jiageng & Cui, Hanghang & Zhang, Bin & Li, Tongyang & Zhang, Kaixuan, 2023. "The application of machine learning based energy management strategy in multi-mode plug-in hybrid electric vehicle, part I: Twin Delayed Deep Deterministic Policy Gradient algorithm design for hybrid ," Energy, Elsevier, vol. 262(PB).
    20. Hu, Jiayi & Li, Jianqiu & Hu, Zunyan & Xu, Liangfei & Ouyang, Minggao, 2021. "Power distribution strategy of a dual-engine system for heavy-duty hybrid electric vehicles using dynamic programming," Energy, Elsevier, vol. 215(PA).

    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:16:y:2023:i:2:p:725-:d:1028688. 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.