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Development and Verification of a Simulation Model for 120 kW Class Electric AWD (All-Wheel-Drive) Tractor during Driving Operation

Author

Listed:
  • Seung-Yun Baek

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea
    Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea)

  • Yeon-Soo Kim

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea
    Convergence Agricultural Machinery Group, Korea Institute of Industrial Technology (KITECH), Gimje 54325, Korea)

  • Wan-Soo Kim

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea
    Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea)

  • Seung-Min Baek

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea
    Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea)

  • Yong-Joo Kim

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea
    Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea)

Abstract

This study was conducted to develop a simulation model of a 120 kW class electric all-wheel-drive (AWD) tractor and verify the model by comparing the measurement and simulation results. The platform was developed based on the power transmission system, including batteries, electric motors, reducers, wheels, and a charging system composed of a generator, an AC/DC converter, and chargers on each axle. The data measurement system was installed on the platform, consisting of an analog (current) and a digital part (rotational speed of electric motors and voltage and SOC (state of charge) level of batteries) by a CAN (controller area network) bus. The axle torque was calculated using the current and torque curves of the electric motor. The simulation model was developed by 1D simulation software and used axle torque and vehicle velocity data to create the simulation conditions. To compare the results of the simulation, a driving test using the platform was performed at a ground speed of 10 km/h in off- and on-road conditions. The similarities between the results were analyzed using statistical software and we found no significant difference in axle torque data. The simulation model was considered to be highly reliable given the change rate and average value of the SOC level. Using the simulation model, the workable time of driving operation was estimated to be about six hours and the workable time of plow tillage was estimated to be about 2.4 h. The results showed that the capacity of the battery is slightly low for plow tillage. However, in future studies, the electric AWD tractor performance could be improved through battery optimization through simulation under various conditions.

Suggested Citation

  • Seung-Yun Baek & Yeon-Soo Kim & Wan-Soo Kim & Seung-Min Baek & Yong-Joo Kim, 2020. "Development and Verification of a Simulation Model for 120 kW Class Electric AWD (All-Wheel-Drive) Tractor during Driving Operation," Energies, MDPI, vol. 13(10), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2422-:d:357125
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    References listed on IDEAS

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    1. Guoqing Xu & Weimin Li & Kun Xu & Zhibin Song, 2011. "An Intelligent Regenerative Braking Strategy for Electric Vehicles," Energies, MDPI, vol. 4(9), pages 1-17, September.
    2. Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang, 2018. "State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles," Energies, MDPI, vol. 11(7), pages 1-36, July.
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    2. Yi Du & Jiayan Zhou & Zhuofan He & Yandong Sun & Ming Kong, 2022. "A Dual-Harmonic Pole-Changing Motor with Split Permanent Magnet Pole," Energies, MDPI, vol. 15(20), pages 1-14, October.
    3. Thanh Vo-Duy & Minh C. Ta & Bảo-Huy Nguyễn & João Pedro F. Trovão, 2020. "Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles," Energies, MDPI, vol. 13(23), pages 1-28, December.
    4. Francesco Mocera & Valerio Martini & Aurelio Somà, 2022. "Comparative Analysis of Hybrid Electric Architectures for Specialized Agricultural Tractors," Energies, MDPI, vol. 15(5), pages 1-22, March.
    5. 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.

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