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Identifying Technology Opportunities for Electric Motors of Railway Vehicles with Patent Analysis

Author

Listed:
  • Yunkoo Cho

    (Adam International Patent & Law Office, 1313, 127 Beobwon-ro, Songpa-gu, Seoul 05836, Korea)

  • Young Jae Han

    (Railroad Test & Certification Division, Korea Railroad Research Institute, 176 Cheoldobangmulgwan-ro, Uiwang-si 16105, Gyeonggi-do, Korea)

  • Jumi Hwang

    (Department of Industrial Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Korea)

  • Jiwon Yu

    (Department of Industrial Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Korea)

  • Sangbaek Kim

    (Department of Packaging, Yonsei University, 1, Yeonsedae-gil, Heungeop-myeon, Wonju-si 26493, Gangwon-do, Korea)

  • Chulung Lee

    (School of Industrial and Management Engineering, Korea University, 145 Anam-ro, Seongbuk, Seoul 02841, Korea)

  • Sugil Lee

    (Smart Electrical & Signaling Division, Korea Railroad Research Institute, 176 Cheoldobangmulgwan-ro, Uiwang-si 16105, Gyeonggi-do, Korea)

  • Kyung Pyo Yi

    (Smart Electrical & Signaling Division, Korea Railroad Research Institute, 176 Cheoldobangmulgwan-ro, Uiwang-si 16105, Gyeonggi-do, Korea)

Abstract

An electric motor is a device that changes electrical energy into mechanical energy for railway vehicles. When developing the electric motor, it used to be developed simply for structures or control methods of the motor itself without considering convergence with other devices or technologies. However, as the railway vehicles become more advanced, technology development through convergence with other devices or technologies is spreading. Therefore, based on patent data related to the electric motors applied to the railway vehicles, this research aims to carry out technical forecasting for establishing research and development (R and D) direction for new technologies by predicting vacant technologies from the point of view of technology convergence. In other words, we studied how to find the vacant technologies in a field of convergence technology for the electric motor of the railway vehicles by analyzing the patent data. More specifically, we search the patents data associated with the electric motor of the railway vehicle that contain multiple IPC codes, and use multiple IPC codes to determine the field of convergence technology. In addition, we extract keywords from the patents data related to each of the determined convergence technologies and define the vacant technologies by interpreting the field of convergence technology and the extracted keywords.

Suggested Citation

  • Yunkoo Cho & Young Jae Han & Jumi Hwang & Jiwon Yu & Sangbaek Kim & Chulung Lee & Sugil Lee & Kyung Pyo Yi, 2021. "Identifying Technology Opportunities for Electric Motors of Railway Vehicles with Patent Analysis," Sustainability, MDPI, vol. 13(5), pages 1-13, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2424-:d:504751
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    References listed on IDEAS

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    Cited by:

    1. Liu, Zhenfeng & Feng, Jian & Uden, Lorna, 2023. "Technology opportunity analysis using hierarchical semantic networks and dual link prediction," Technovation, Elsevier, vol. 128(C).
    2. Worasak Klongthong & Veera Muangsin & Chupun Gowanit & Nongnuj Muangsin, 2021. "A Patent Analysis to Identify Emergent Topics and Convergence Fields: A Case Study of Chitosan," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    3. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Sangyun Han & Soo Kyung Park & Kyu Tae Kwak, 2021. "Workforce Composition of Public R&D and Performance: Evidence from Korean Government-Funded Research Institutes," Sustainability, MDPI, vol. 13(7), pages 1-17, March.
    5. Koopo Kwon & Sungchan Jun & Yong-Jae Lee & Sanghei Choi & Chulung Lee, 2022. "Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    6. Yong-Jae Lee & Young Jae Han & Sang-Soo Kim & Chulung Lee, 2022. "Patent Data Analytics for Technology Forecasting of the Railway Main Transformer," Sustainability, MDPI, vol. 15(1), pages 1-25, December.

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