IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i20p7090-d1259619.html
   My bibliography  Save this article

Real-Time Implementation of Sensorless DTC-SVM Applied to 4WDEV Using the MRAS Estimator

Author

Listed:
  • Abdelhak Boudallaa

    (Laboratoire des Sciences et Techniques Pour l’Ingénieur (LASTI), National School of Applied Sciences (ENSA), Université Sultan Moulay Slimane, Khouribga 25000, Morocco)

  • Ahmed Belkhadir

    (Laboratoire des Systèmes Electriques, Efficacité Energétique et Télécommunications (LSEEET), Faculty of Sciences and Technologies, Université Cadi Ayyad, P.O. Box 549, Marrakech 40000, Morocco
    Laboratoire Systèmes Electrotechniques et Environnement (LSEE), Université Artois, UR 4025, F-62400 Béthune, France)

  • Mohammed Chennani

    (Laboratoire des Systèmes Electriques, Efficacité Energétique et Télécommunications (LSEEET), Faculty of Sciences and Technologies, Université Cadi Ayyad, P.O. Box 549, Marrakech 40000, Morocco)

  • Driss Belkhayat

    (Laboratoire des Systèmes Electriques, Efficacité Energétique et Télécommunications (LSEEET), Faculty of Sciences and Technologies, Université Cadi Ayyad, P.O. Box 549, Marrakech 40000, Morocco)

  • Youssef Zidani

    (Laboratoire des Systèmes Electriques, Efficacité Energétique et Télécommunications (LSEEET), Faculty of Sciences and Technologies, Université Cadi Ayyad, P.O. Box 549, Marrakech 40000, Morocco)

  • Karim Rhofir

    (Laboratoire des Sciences et Techniques Pour l’Ingénieur (LASTI), National School of Applied Sciences (ENSA), Université Sultan Moulay Slimane, Khouribga 25000, Morocco)

Abstract

This article presents the DTC-SVM approach for controlling a sensorless speed induction motor. To implement this approach, a practical prototype is built using a microcontroller, an embedded GPS module, and a memory card to collect real-time data during the driving route, such as road geographical data, speed, and time. These data are then utilized in the laboratory to implement the control law (DTC-SVM) on the electric vehicle. The d-q model of the induction motor is first presented to explain the requirements for calculating the rotor speed. Then, an adaptive model reference system speed estimator is developed based on the rotor flux, along with a controller and DTC-SVM strategy, which are implemented using the dSpace 1104 board to achieve the desired performance. The simulation results demonstrate satisfactory speed regulation with the proposed system. In this study too, an electronic differential system is modeled for the four wheels of an electric vehicle equipped with an integrated motor, all controlled by the DTC-SVM strategy. Vehicle speed and electrical vehicle steering angle variations, as well as wheel speeds estimated by code system, are verified using MATLAB/Simulink simulations.

Suggested Citation

  • Abdelhak Boudallaa & Ahmed Belkhadir & Mohammed Chennani & Driss Belkhayat & Youssef Zidani & Karim Rhofir, 2023. "Real-Time Implementation of Sensorless DTC-SVM Applied to 4WDEV Using the MRAS Estimator," Energies, MDPI, vol. 16(20), pages 1-23, October.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7090-:d:1259619
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/20/7090/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/20/7090/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mahmoud A. Mossa & Hamdi Echeikh & Ahmed A. Zaki Diab & Hassan Haes Alhelou & Pierluigi Siano, 2021. "Comparative Study of Hysteresis Controller, Resonant Controller and Direct Torque Control of Five-Phase IM under Open-Phase Fault Operation," Energies, MDPI, vol. 14(5), pages 1-23, February.
    2. Sofiane Bacha & Ramzi Saadi & Mohamed Yacine Ayad & Mohamed Sahraoui & Khaled Laadjal & Antonio J. Marques Cardoso, 2023. "Autonomous Electric-Vehicle Control Using Speed Planning Algorithm and Back-Stepping Approach," Energies, MDPI, vol. 16(5), pages 1-26, March.
    3. Zhihao Yu & Ruituo Huai & Linjing Xiao, 2015. "State-of-Charge Estimation for Lithium-Ion Batteries Using a Kalman Filter Based on Local Linearization," Energies, MDPI, vol. 8(8), pages 1-20, July.
    4. Tomas Esparza Sola & Huang-Jen Chiu & Yu-Chen Liu & Arief Noor Rahman, 2022. "Extending DC Bus Utilization for Induction Motors with Stator Flux Oriented Direct Torque Control," Energies, MDPI, vol. 15(1), pages 1-22, January.
    5. Usha Sengamalai & T. M. Thamizh Thentral & Palanisamy Ramasamy & Mohit Bajaj & Syed Sabir Hussain Bukhari & Ehab E. Elattar & Ahmed Althobaiti & Salah Kamel, 2022. "Mitigation of Circulating Bearing Current in Induction Motor Drive Using Modified ANN Based MRAS for Traction Application," Mathematics, MDPI, vol. 10(8), pages 1-24, April.
    6. 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.
    7. Yashar Farajpour & Mohamad Alzayed & Hicham Chaoui & Sousso Kelouwani, 2020. "A Novel Switching Table for a Modified Three-Level Inverter-Fed DTC Drive with Torque and Flux Ripple Minimization," Energies, MDPI, vol. 13(18), pages 1-19, September.
    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. Habib Benbouhenni & Nicu Bizon, 2021. "Improved Rotor Flux and Torque Control Based on the Third-Order Sliding Mode Scheme Applied to the Asynchronous Generator for the Single-Rotor Wind Turbine," Mathematics, MDPI, vol. 9(18), pages 1-16, September.
    2. Sofiane Bacha & Ramzi Saadi & Mohamed Yacine Ayad & Mohamed Sahraoui & Khaled Laadjal & Antonio J. Marques Cardoso, 2023. "Autonomous Electric-Vehicle Control Using Speed Planning Algorithm and Back-Stepping Approach," Energies, MDPI, vol. 16(5), pages 1-26, March.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. Abderrazek Saoudi & Saber Krim & Mohamed Faouzi Mimouni, 2021. "Enhanced Intelligent Closed Loop Direct Torque and Flux Control of Induction Motor for Standalone Photovoltaic Water Pumping System," Energies, MDPI, vol. 14(24), pages 1-21, December.
    9. Huang, Hai-chao & He, Hong-di & Peng, Zhong-ren, 2024. "Urban-scale estimation model of carbon emissions for ride-hailing electric vehicles during operational phase," Energy, Elsevier, vol. 293(C).
    10. 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.
    11. Soulios, V. & Loonen, R.C.G.M. & Metavitsiadis, V. & Hensen, J.L.M., 2018. "Computational performance analysis of overheating mitigation measures in parked vehicles," Applied Energy, Elsevier, vol. 231(C), pages 635-644.
    12. Li, Hai & Zheng, Peng & Zhang, Tingsheng & Zou, Yingquan & Pan, Yajia & Zhang, Zutao & Azam, Ali, 2021. "A high-efficiency energy regenerative shock absorber for powering auxiliary devices of new energy driverless buses," Applied Energy, Elsevier, vol. 295(C).
    13. Kapetanović, Marko & Núñez, Alfredo & van Oort, Niels & Goverde, Rob M.P., 2021. "Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains," Applied Energy, Elsevier, vol. 294(C).
    14. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2020. "Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 30-46.
    15. Ibrahim M. Safwat & Weilin Li & Xiaohua Wu, 2017. "A Novel Methodology for Estimating State-Of-Charge of Li-Ion Batteries Using Advanced Parameters Estimation," Energies, MDPI, vol. 10(11), pages 1-16, November.
    16. Yuan, Xinmei & Zhang, Chuanpu & Hong, Guokai & Huang, Xueqi & Li, Lili, 2017. "Method for evaluating the real-world driving energy consumptions of electric vehicles," Energy, Elsevier, vol. 141(C), pages 1955-1968.
    17. Sun, Xilei & Fu, Jianqin, 2024. "Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature," Energy, Elsevier, vol. 288(C).
    18. Guo, Qiangqiang & Ban, Xuegang (Jeff), 2023. "A multi-scale control framework for urban traffic control with connected and automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).
    19. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
    20. Kyoungho Ahn & Hesham A. Rakha, 2022. "Developing a Hydrogen Fuel Cell Vehicle (HFCV) Energy Consumption Model for Transportation Applications," Energies, MDPI, vol. 15(2), pages 1-15, January.

    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:20:p:7090-:d:1259619. 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.