IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i20p5355-d427914.html
   My bibliography  Save this article

A Comprehensive Review on Classification, Energy Management Strategy, and Control Algorithm for Hybrid Electric Vehicles

Author

Listed:
  • Qicheng Xue

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Xin Zhang

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Teng Teng

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Jibao Zhang

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Zhiyuan Feng

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Qinyang Lv

    (Beijing Key Laboratory of Powertrain for New Energy Vehicle, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China)

Abstract

The energy management strategy (EMS) and control algorithm of a hybrid electric vehicle (HEV) directly determine its energy efficiency, control effect, and system reliability. For a certain configuration of an HEV powertrain, the challenge is to develop an efficient EMS and an appropriate control algorithm to satisfy a variety of development objectives while not reducing vehicle performance. In this research, a comprehensive, multi-level classification for HEVs is introduced in detail from the aspects of the degree of hybridization (DoH), the position of the motor, the components and configurations of the powertrain, and whether or not the HEV is charged by external power. The principle and research status of EMSs for each type of HEV are summarized and reviewed. Additionally, the EMSs and control algorithms of HEVs are compared and analyzed from the perspectives of characteristics, applications, real-time abilities, and historical development. Finally, some discussions about potential directions and challenges for future research on the energy management systems of HEVs are presented. This review is expected to bring contribution to the development of efficient, intelligent, and advanced EMSs for future HEV energy management systems.

Suggested Citation

  • Qicheng Xue & Xin Zhang & Teng Teng & Jibao Zhang & Zhiyuan Feng & Qinyang Lv, 2020. "A Comprehensive Review on Classification, Energy Management Strategy, and Control Algorithm for Hybrid Electric Vehicles," Energies, MDPI, vol. 13(20), pages 1-30, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5355-:d:427914
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/20/5355/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/20/5355/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Chao & Li, Liang & You, Sixiong & Yan, Bingjie & Du, Xian, 2017. "Cloud computing-based energy optimization control framework for plug-in hybrid electric bus," Energy, Elsevier, vol. 125(C), pages 11-26.
    2. Wei, Zhen & Xu, John & Halim, Dunant, 2017. "HEV power management control strategy for urban driving," Applied Energy, Elsevier, vol. 194(C), pages 705-714.
    3. Jiankun Peng & Hao Fan & Hongwen He & Deng Pan, 2015. "A Rule-Based Energy Management Strategy for a Plug-in Hybrid School Bus Based on a Controller Area Network Bus," Energies, MDPI, vol. 8(6), pages 1-21, June.
    4. Lu Han & Xiaohong Jiao & Zhao Zhang, 2020. "Recurrent Neural Network-Based Adaptive Energy Management Control Strategy of Plug-In Hybrid Electric Vehicles Considering Battery Aging," Energies, MDPI, vol. 13(1), pages 1-22, January.
    5. Khayyam, Hamid & Bab-Hadiashar, Alireza, 2014. "Adaptive intelligent energy management system of plug-in hybrid electric vehicle," Energy, Elsevier, vol. 69(C), pages 319-335.
    6. Benmouna, Amel & Becherif, Mohamed & Depernet, Daniel & Ebrahim, Mohamed A., 2018. "Novel Energy Management Technique for Hybrid Electric Vehicle via Interconnection and Damping Assignment Passivity Based Control," Renewable Energy, Elsevier, vol. 119(C), pages 116-128.
    7. Chen, Bo-Chiuan & Wu, Yuh-Yih & Tsai, Hsien-Chi, 2014. "Design and analysis of power management strategy for range extended electric vehicle using dynamic programming," Applied Energy, Elsevier, vol. 113(C), pages 1764-1774.
    8. Hui-Long Yu & Jun-Qiang Xi & Feng-qi Zhang & Yu-hui Hu, 2014. "Research on Gear Shifting Process without Disengaging Clutch for a Parallel Hybrid Electric Vehicle Equipped with AMT," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-12, February.
    9. Zhang, Pei & Yan, Fuwu & Du, Changqing, 2015. "A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 88-104.
    10. Yuan Qiao & Yizhou Song & Kaisheng Huang, 2019. "A Novel Control Algorithm Design for Hybrid Electric Vehicles Considering Energy Consumption and Emission Performance," Energies, MDPI, vol. 12(14), pages 1-28, July.
    11. Zeyu Chen & Jiahuan Lu & Bo Liu & Nan Zhou & Shijie Li, 2020. "Optimal Energy Management of Plug-In Hybrid Electric Vehicles Concerning the Entire Lifespan of Lithium-Ion Batteries," Energies, MDPI, vol. 13(10), pages 1-15, May.
    12. M. Sabri, M.F. & Danapalasingam, K.A. & Rahmat, M.F., 2016. "A review on hybrid electric vehicles architecture and energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1433-1442.
    13. Zou, Yuan & Liu, Teng & Liu, Dexing & Sun, Fengchun, 2016. "Reinforcement learning-based real-time energy management for a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 171(C), pages 372-382.
    14. Tie, Siang Fui & Tan, Chee Wei, 2013. "A review of energy sources and energy management system in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 82-102.
    15. Xu Chen & Guangdi Hu & Feng Guo & Mengqi Ye & Jingyuan Huang, 2020. "Switched Energy Management Strategy for Fuel Cell Hybrid Vehicle Based on Switch Network," Energies, MDPI, vol. 13(1), pages 1-23, January.
    16. Sun, Zhendong & Wang, Yujie & Chen, Zonghai & Li, Xiyun, 2020. "Min-max game based energy management strategy for fuel cell/supercapacitor hybrid electric vehicles," Applied Energy, Elsevier, vol. 267(C).
    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. Md. Sazal Miah & Molla Shahadat Hossain Lipu & Sheikh Tanzim Meraj & Kamrul Hasan & Shaheer Ansari & Taskin Jamal & Hasan Masrur & Rajvikram Madurai Elavarasan & Aini Hussain, 2021. "Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends," Sustainability, MDPI, vol. 13(22), pages 1-38, November.
    2. Pierpaolo Polverino & Ivan Arsie & Cesare Pianese, 2021. "Optimal Energy Management for Hybrid Electric Vehicles Based on Dynamic Programming and Receding Horizon," Energies, MDPI, vol. 14(12), pages 1-11, June.
    3. Hegazy Rezk & Mohammad Ali Abdelkareem & Samah Ibrahim Alshathri & Enas Taha Sayed & Mohamad Ramadan & Abdul Ghani Olabi, 2023. "Fuel Economy Energy Management of Electric Vehicles Using Harris Hawks Optimization," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    4. Muhyaddin Rawa & Prem P & Jagabar Sathik Mohamed Ali & Marif Daula Siddique & Saad Mekhilef & Addy Wahyudie & Mehdi Seyedmahmoudian & Alex Stojcevski, 2021. "A New Multilevel Inverter Topology with Reduced DC Sources," Energies, MDPI, vol. 14(15), pages 1-21, August.
    5. Alberto Broatch & Pablo Olmeda & Benjamín Plá & Amin Dreif, 2022. "Novel Energy Management Control Strategy for Improving Efficiency in Hybrid Powertrains," Energies, MDPI, vol. 16(1), pages 1-21, December.
    6. Pier Giuseppe Anselma, 2022. "Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health," Energies, MDPI, vol. 15(5), pages 1-25, February.
    7. Seydali Ferahtia & Hegazy Rezk & Rania M. Ghoniem & Ahmed Fathy & Reem Alkanhel & Mohamed M. Ghonem, 2023. "Optimal Energy Management for Hydrogen Economy in a Hybrid Electric Vehicle," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    8. Danijel Pavković & Mihael Cipek & Filip Plavac & Juraj Karlušić & Matija Krznar, 2022. "Internal Combustion Engine Starting and Torque Boosting Control System Design with Vibration Active Damping Features for a P0 Mild Hybrid Vehicle Configuration," Energies, MDPI, vol. 15(4), pages 1-24, February.
    9. 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.
    10. Da Huo & Peter Meckl, 2022. "Power Management of a Plug-in Hybrid Electric Vehicle Using Neural Networks with Comparison to Other Approaches," Energies, MDPI, vol. 15(15), pages 1-19, August.
    11. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    12. Enas Taha Sayed & Abdul Ghani Olabi & Abdul Hai Alami & Ali Radwan & Ayman Mdallal & Ahmed Rezk & Mohammad Ali Abdelkareem, 2023. "Renewable Energy and Energy Storage Systems," Energies, MDPI, vol. 16(3), pages 1-26, February.
    13. Hyungkwan Jang & Hyunwoo Kim & Huai-Cong Liu & Ho-Joon Lee & Ju Lee, 2021. "Investigation on the Torque Ripple Reduction Method of a Hybrid Electric Vehicle Motor," Energies, MDPI, vol. 14(5), pages 1-13, March.
    14. Dongwei Yao & Xinwei Lu & Xiangyun Chao & Yongguang Zhang & Junhao Shen & Fanlong Zeng & Ziyan Zhang & Feng Wu, 2023. "Adaptive Equivalent Fuel Consumption Minimization Based Energy Management Strategy for Extended-Range Electric Vehicle," Sustainability, MDPI, vol. 15(5), pages 1-18, March.
    15. Zhen Huang & Xuechun Xiao & Yuan Gao & Yonghong Xia & Tomislav Dragičević & Pat Wheeler, 2023. "Emerging Information Technologies for the Energy Management of Onboard Microgrids in Transportation Applications," Energies, MDPI, vol. 16(17), pages 1-26, August.

    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. López-Ibarra, Jon Ander & Gaztañaga, Haizea & Saez-de-Ibarra, Andoni & Camblong, Haritza, 2020. "Plug-in hybrid electric buses total cost of ownership optimization at fleet level based on battery aging," Applied Energy, Elsevier, vol. 280(C).
    2. Fan, Likang & Wang, Yufei & Wei, Hongqian & Zhang, Youtong & Zheng, Pengyu & Huang, Tianyi & Li, Wei, 2022. "A GA-based online real-time optimized energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 241(C).
    3. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    4. 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).
    5. Peng, Jiankun & He, Hongwen & Xiong, Rui, 2017. "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming," Applied Energy, Elsevier, vol. 185(P2), pages 1633-1643.
    6. Chen, Z. & Liu, Y. & Ye, M. & Zhang, Y. & Chen, Z. & Li, G., 2021. "A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    7. Farzaneh, Alireza & Farjah, Ebrahim, 2018. "Analysis of Road Curvature’s Effects on Electric Motorcycle Energy Consumption," Energy, Elsevier, vol. 151(C), pages 160-166.
    8. Kong, Yan & Xu, Nan & Zhang, Yuanjian & Sui, Yan & Ju, Hao & Liu, Heng & Xu, Zhe, 2021. "Acquisition of full-factor trip information for global optimization energy management in multi-energy source vehicles and the measure of the amount of information to be transmitted," Energy, Elsevier, vol. 236(C).
    9. Xiao, B. & Ruan, J. & Yang, W. & Walker, P.D. & Zhang, N., 2021. "A review of pivotal energy management strategies for extended range electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    10. İnci, Mustafa & Büyük, Mehmet & Demir, Mehmet Hakan & İlbey, Göktürk, 2021. "A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    11. Du, Guodong & Zou, Yuan & Zhang, Xudong & Guo, Lingxiong & Guo, Ningyuan, 2022. "Energy management for a hybrid electric vehicle based on prioritized deep reinforcement learning framework," Energy, Elsevier, vol. 241(C).
    12. Yan Wang & Qing Gao & Tianshi Zhang & Guohua Wang & Zhipeng Jiang & Yunxia Li, 2017. "Advances in Integrated Vehicle Thermal Management and Numerical Simulation," Energies, MDPI, vol. 10(10), pages 1-30, October.
    13. Ahmed M. Ali & Dirk Söffker, 2018. "Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions," Energies, MDPI, vol. 11(3), pages 1-24, February.
    14. Feiyan Qin & Guoqing Xu & Yue Hu & Kun Xu & Weimin Li, 2017. "Stochastic Optimal Control of Parallel Hybrid Electric Vehicles," Energies, MDPI, vol. 10(2), pages 1-16, February.
    15. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
    16. Liu, Teng & Wang, Bo & Yang, Chenglang, 2018. "Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning," Energy, Elsevier, vol. 160(C), pages 544-555.
    17. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    18. Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M., 2017. "Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 268-291.
    19. 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.
    20. 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.

    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:13:y:2020:i:20:p:5355-:d:427914. 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.