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Conducted EMI Prediction and Mitigation Strategy Based on Transfer Function for a High-Low Voltage DC-DC Converter in Electric Vehicle

Author

Listed:
  • Li Zhai

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Tao Zhang

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Yu Cao

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Sipeng Yang

    (R&D Department for New Energy Automobile, Zhengzhou YuTong Bus Co., Ltd., Zhengzhou 450061, China)

  • Steven Kavuma

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Huiyuan Feng

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

Abstract

The high d v /d t and d i /d t outputs from power devices in a high-low voltage DC-DC converter on electric vehicles (EVs) can always introduce the unwanted conducted electromagnetic interference (EMI) emissions. A conducted EMI prediction and mitigation strategy that is based on transfer function for the high-low voltage DC-DC converter in EVs are proposed. A complete test for the DC-DC converter is conducted to obtain the conducted EMI from DC power cables in the frequency band of 150 kHz-108 MHz. The equivalent circuit with high-frequency parasitic parameters of the DC-DC converter is built`1 based on the measurement results to acquire the characteristics of the conducted EMI of the DC power cables. The common mode (CM) and differential mode (DM) propagation coupling paths are determined, and the corresponding transfer functions of the DM interference and CM interference are established. The simulation results of the conducted EMI can be obtained by software Matlab and Computer Simulation Technology (CST). By analyzing the transfer functions and the simulation results, the dominated interference is the CM interference, which is the main factor of the conducted EMI. A mitigation strategy for the design of the CM interference filter based on the dominated CM interference is proposed. Finally, the mitigation strategy of the conducted EMI is verified by performing the conducted voltage experiment. From the experiment results, the conducted voltage of the DC power cables is decreased, respectively, by 58 dBμV, 55 dBμV, 65 dBμV, 53 dBμV, and 54 dBμV at frequency 200 kHz, 400 kHz, 600 kHz, 1.4 MHz, and 50 MHz. The conduced voltage in the frequency band of 150 kHz–108 MHz can be mitigated by adding the CM interference filters, and the values are lower than the limit level-3 of CISPR25 standard (GB/T 18655-2010).

Suggested Citation

  • Li Zhai & Tao Zhang & Yu Cao & Sipeng Yang & Steven Kavuma & Huiyuan Feng, 2018. "Conducted EMI Prediction and Mitigation Strategy Based on Transfer Function for a High-Low Voltage DC-DC Converter in Electric Vehicle," Energies, MDPI, vol. 11(5), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1028-:d:142829
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    References listed on IDEAS

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    1. Li Zhai & Liwen Lin & Xinyu Zhang & Chao Song, 2016. "The Effect of Distributed Parameters on Conducted EMI from DC-Fed Motor Drive Systems in Electric Vehicles," Energies, MDPI, vol. 10(1), pages 1-17, December.
    2. Li Zhai & Xinyu Zhang & Natalia Bondarenko & David Loken & Thomas P. Van Doren & Daryl G. Beetner, 2016. "Mitigation Emission Strategy Based on Resonances from a Power Inverter System in Electric Vehicles," Energies, MDPI, vol. 9(6), pages 1-17, May.
    3. Ferrero, Enrico & Alessandrini, Stefano & Balanzino, Alessia, 2016. "Impact of the electric vehicles on the air pollution from a highway," Applied Energy, Elsevier, vol. 169(C), pages 450-459.
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    Cited by:

    1. Kyunghwan Choi & Kyung-Soo Kim & Seok-Kyoon Kim, 2019. "Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer," Energies, MDPI, vol. 12(8), pages 1-14, April.
    2. Chaiyan Jettanasen & Atthapol Ngaopitakkul, 2019. "The Conducted Emission Attenuation of Micro-Inverters for Nanogrid Systems," Sustainability, MDPI, vol. 12(1), pages 1-31, December.
    3. Feng Wang & Yutao Luo & Hongluo Li & Xiaotong Xu, 2019. "Switching Characteristics Optimization of Two-Phase Interleaved Bidirectional DC/DC for Electric Vehicles," Energies, MDPI, vol. 12(3), pages 1-14, January.
    4. Seok-Kyoon Kim, 2018. "Passivity-Based Robust Output Voltage Tracking Control of DC/DC Boost Converter for Wind Power Systems," Energies, MDPI, vol. 11(6), pages 1-13, June.

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