IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v227y2018icp239-248.html
   My bibliography  Save this article

Tolerance analysis of electrified vehicles on the motor demagnetization fault: From an energy perspective

Author

Listed:
  • He, Hongwen
  • Zhou, Nana
  • Guo, Jinquan
  • Zhang, Zheng
  • Lu, Bing
  • Sun, Chao

Abstract

Due to possible overheat, abrasion or mechanical vibrations, demagnetization fault is inevitable in permanent magnet synchronous motors (PMSMs), which could greatly decrease the motor’s efficiency and hence an electrified vehicle’s performance. This paper, from an energy efficiency point of view, proposes to analyze the tolerance ability of different electrified vehicles on motor demagnetization faults, via PMSM flux density degradation modeling, efficiency estimation and dynamic programming (DP) based powertrain energy management. The relationship between different demagnetization levels and resultant motor efficiencies is obtained, and analyzed according to the motor operation area. Demagnetized PMSM is adopted in a pure electric vehicle (PEV), a hybrid electric vehicle (HEV) and a plug-in hybrid electric vehicle (PHEV) for energy efficiency analysis. Tolerance analysis indicates that the powertrain efficiency decrease caused by motor demagnetization is more severe under urban driving conditions, especially with PEV and PHEV configurations compared with HEV. A demagnetization threshold investigation is also given in this paper.

Suggested Citation

  • He, Hongwen & Zhou, Nana & Guo, Jinquan & Zhang, Zheng & Lu, Bing & Sun, Chao, 2018. "Tolerance analysis of electrified vehicles on the motor demagnetization fault: From an energy perspective," Applied Energy, Elsevier, vol. 227(C), pages 239-248.
    • Handle: RePEc:eee:appene:v:227:y:2018:i:c:p:239-248
    DOI: 10.1016/j.apenergy.2017.08.226
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191731259X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.08.226?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sun, Chao & Sun, Fengchun & He, Hongwen, 2017. "Investigating adaptive-ECMS with velocity forecast ability for hybrid electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1644-1653.
    2. 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.
    3. Zhang, Shuo & Xiong, Rui & Cao, Jiayi, 2016. "Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system," Applied Energy, Elsevier, vol. 179(C), pages 316-328.
    4. Xiong, Rui & Yu, Quanqing & Wang, Le Yi & Lin, Cheng, 2017. "A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter," Applied Energy, Elsevier, vol. 207(C), pages 346-353.
    5. Wang, Hong & Huang, Yanjun & Khajepour, Amir & Song, Qiang, 2016. "Model predictive control-based energy management strategy for a series hybrid electric tracked vehicle," Applied Energy, Elsevier, vol. 182(C), pages 105-114.
    6. Torres, J.L. & Gonzalez, R. & Gimenez, A. & Lopez, J., 2014. "Energy management strategy for plug-in hybrid electric vehicles. A comparative study," Applied Energy, Elsevier, vol. 113(C), pages 816-824.
    7. Xiong, Rui & Tian, Jinpeng & Mu, Hao & Wang, Chun, 2017. "A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries," Applied Energy, Elsevier, vol. 207(C), pages 372-383.
    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. Chen, Shi-An & Jiang, Xu-Dong & Yao, Ming & Jiang, Shun-Ming & Chen, Jinzhou & Wang, Ya-Xiong, 2020. "A dual vibration reduction structure-based self-powered active suspension system with PMSM-ball screw actuator via an improved H2/H∞ control," Energy, Elsevier, vol. 201(C).
    2. Zhu, Xiaoyong & Fan, Deyang & Xiang, Zixuan & Quan, Li & Hua, Wei & Cheng, Ming, 2019. "Systematic multi-level optimization design and dynamic control of less-rare-earth hybrid permanent magnet motor for all-climatic electric vehicles," Applied Energy, Elsevier, vol. 253(C), pages 1-1.

    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. Yang, Dongpo & Liu, Tong & Song, Dafeng & Zhang, Xuanming & Zeng, Xiaohua, 2023. "A real time multi-objective optimization Guided-MPC strategy for power-split hybrid electric bus based on velocity prediction," Energy, Elsevier, vol. 276(C).
    2. He, Hongwen & Guo, Xiaoguang, 2018. "Multi-objective optimization research on the start condition for a parallel hybrid electric vehicle," Applied Energy, Elsevier, vol. 227(C), pages 294-303.
    3. Mingjie Zhao & Junhui Shi & Cheng Lin & Junzhi Zhang, 2018. "Application-Oriented Optimal Shift Schedule Extraction for a Dual-Motor Electric Bus with Automated Manual Transmission," Energies, MDPI, vol. 11(2), pages 1-16, February.
    4. Xiong, Rui & Duan, Yanzhou & Cao, Jiayi & Yu, Quanqing, 2018. "Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle," Applied Energy, Elsevier, vol. 217(C), pages 153-165.
    5. Aijuan Li & Wanzhong Zhao & Xibo Wang & Xuyun Qiu, 2018. "ACT-R Cognitive Model Based Trajectory Planning Method Study for Electric Vehicle’s Active Obstacle Avoidance System," Energies, MDPI, vol. 11(1), pages 1-21, January.
    6. 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.
    7. Li, Jianwei & Xiong, Rui & Mu, Hao & Cornélusse, Bertrand & Vanderbemden, Philippe & Ernst, Damien & Yuan, Weijia, 2018. "Design and real-time test of a hybrid energy storage system in the microgrid with the benefit of improving the battery lifetime," Applied Energy, Elsevier, vol. 218(C), pages 470-478.
    8. Yang, Ruixin & Xiong, Rui & He, Hongwen & Mu, Hao & Wang, Chun, 2017. "A novel method on estimating the degradation and state of charge of lithium-ion batteries used for electrical vehicles," Applied Energy, Elsevier, vol. 207(C), pages 336-345.
    9. Xiaogang Wu & Siyu Lv & Jizhong Chen, 2017. "Determination of the Optimum Heat Transfer Coefficient and Temperature Rise Analysis for a Lithium-Ion Battery under the Conditions of Harbin City Bus Driving Cycles," Energies, MDPI, vol. 10(11), pages 1-17, October.
    10. 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).
    11. Xiaogang Wu & Wenwen Shi & Jiuyu Du, 2017. "Multi-Objective Optimal Charging Method for Lithium-Ion Batteries," Energies, MDPI, vol. 10(9), pages 1-18, August.
    12. Lin, Cheng & Yu, Quanqing & Xiong, Rui & Wang, Le Yi, 2017. "A study on the impact of open circuit voltage tests on state of charge estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 205(C), pages 892-902.
    13. Gong, Jun & Zhang, Daqing & Guo, yong & Liu, Changsheng & Zhao, Yuming & Hu, Peng & Quan, weicai, 2019. "Power control strategy and performance evaluation of a novel electro-hydraulic energy-saving system," Applied Energy, Elsevier, vol. 233, pages 724-734.
    14. Li, Guozhen & Zhang, Zhenyu & Shi, Wankai & Li, Wenyong, 2023. "Energy management strategy and simulation analysis of a hybrid train based on a comprehensive efficiency optimization," Applied Energy, Elsevier, vol. 349(C).
    15. Xu, Nan & Kong, Yan & Yan, Jinyue & Zhang, Yuanjian & Sui, Yan & Ju, Hao & Liu, Heng & Xu, Zhe, 2022. "Global optimization energy management for multi-energy source vehicles based on “Information layer - Physical layer - Energy layer - Dynamic programming” (IPE-DP)," Applied Energy, Elsevier, vol. 312(C).
    16. Mu, Hao & Xiong, Rui & Zheng, Hongfei & Chang, Yuhua & Chen, Zeyu, 2017. "A novel fractional order model based state-of-charge estimation method for lithium-ion battery," Applied Energy, Elsevier, vol. 207(C), pages 384-393.
    17. Hong Zhang & Hang Zhang & Zhuo Wang, 2017. "Effect on Vehicle Turbocharger Exhaust Gas Energy Utilization for the Performance of Centrifugal Compressors under Plateau Conditions," Energies, MDPI, vol. 10(12), pages 1-18, December.
    18. Yan Bao & Yu Luo & Weige Zhang & Mei Huang & Le Yi Wang & Jiuchun Jiang, 2018. "A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System," Energies, MDPI, vol. 11(1), pages 1-21, January.
    19. Yang, Lin & Cai, Yishan & Yang, Yixin & Deng, Zhongwei, 2020. "Supervisory long-term prediction of state of available power for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 257(C).
    20. Chen, Zeyu & Xiong, Rui & Lu, Jiahuan & Li, Xinggang, 2018. "Temperature rise prediction of lithium-ion battery suffering external short circuit for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 213(C), pages 375-383.

    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:eee:appene:v:227:y:2018:i:c:p:239-248. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.