MERL - Mitsubishi Electric Research Laboratories

Electric Systems

Modeling & optimization of power systems and electromagnetic machines.

Our research in this area includes flexible and resilient power system design and operational optimization; modeling and analysis of electric machines for applications such as fault detection of motors, power efficiency improvement and design complexity reduction.

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  • Researchers

  • Awards

    •  AWARD    Best paper award at PHMAP 2023
      Date: September 14, 2023
      Awarded to: Dehong Liu, Anantaram Varatharajan, and Abraham Goldsmith
      MERL Contacts: Abraham Goldsmith; Dehong Liu
      Research Areas: Electric Systems, Signal Processing
      Brief
      • MERL researchers Dehong Liu, Anantaram Varatharajan, and Abraham Goldsmith were awarded one of three best paper awards at Asia Pacific Conference of the Prognostics and Health Management Society 2023 (PHMAP23) held in Tokyo from September 11th to 14th, 2023, for their co-authored paper titled 'Extracting Broken-Rotor-Bar Fault Signature of Varying-Speed Induction Motors.'

        PHMAP is a biennial international conference specialized in prognostics and health management. PHMAP23 attracted more than 300 attendees from worldwide and published more than 160 regular papers from academia and industry including aerospace, production, civil engineering, electronics, and so on.
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    •  AWARD    MERL receives 33rd ARIB Radio Achievement Award
      Date: June 28, 2022
      Awarded to: Yukimasa Nagai, Jianlin Guo, Shoichi Kitazawa, Kazuto Yano.
      MERL Contacts: Jianlin Guo; Philip V. Orlik
      Research Areas: Communications, Electric Systems
      Brief
      • Mitsubishi Electric Corporation (Yukimasa Nagai), MERL (Jianlin Guo), Muroran Institute of Technology (Shoichi Kitazawa) and Advanced Telecommunications Research Institute International (Kazuto Yano) jointly won the 33rd ARIB Radio Achievement Award with "IEEE 802.19.3 Standardization and Development for Sub-1 GHz Wireless Frequency Coexistence". The ARIB is an organization similar to the FCC in the U.S. It is responsible for setting standards for all radio communications in Japan at the request of the Ministry of Internal Affairs and Communications (MIC). In order to promote the effective use of radio waves, the "Radio Achievement Award" is given annually to an individual or organization that has made a special achievement in the effective use of radio waves. This award is the most prestigious award in the field of wireless communications in Japan.
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    •  AWARD    Best conference paper of IEEE PES-GM 2020
      Date: June 18, 2020
      Awarded to: Tong Huang, Hongbo Sun, K.J. Kim, Daniel Nikovski, Le Xie
      MERL Contacts: Daniel N. Nikovski; Hongbo Sun
      Research Areas: Data Analytics, Electric Systems, Optimization
      Brief
      • A paper on A Holistic Framework for Parameter Coordination of Interconnected Microgrids Against Natural Disasters, written by Tong Huang, a former MERL intern from Texas A&M University, has been selected as one of the Best Conference Papers at the 2020 Power and Energy Society General Meeting (PES-GM). IEEE PES-GM is the flagship conference for the IEEE Power and Energy Society. The work was done in collaboration with Hongbo Sun, K. J. Kim, and Daniel Nikovski from MERL, and Tong's advisor, Prof. Le Xie from Texas A&M University.
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  • News & Events


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  • Internships

    • EA1891: Electric machine monitoring technologies

      MERL is looking for a self-motivated intern to work on electric machine monitoring, fault detection, and predictive maintenance. The ideal candidate would be a Ph.D. candidate in electrical engineering or computer science with solid research background in electric machines, signal processing, and machine learning. Proficiency in MATLAB and Simulink is necessary. The intern is expected to collaborate with MERL researchers to perform simulations, analyze experimental data, and prepare manuscripts for scientific publications. The total duration is anticipated to be 3 months and the start date is flexible. This internship requires work that can only be done at MERL.

    • EA2045: Speed-sensorless Control of Electrical Machines

      MERL is seeking a highly motivated and qualified individual to conduct research/development in speed-sensorless control of electrical machines.



      The ideal candidate should have solid backgrounds in electrical machines, sensorless drives control, dynamical system analysis, signal processing, state estimation, and parameter identification. Demonstrated knowledge of the state-of-the-art sensorless drives control and experience on using dSPACE for real-time HIL experimentation is necessary. Proven record of publishing results in leading conferences/journals is a plus.



      Senior Ph.D. students in electrical engineering, control, and related areas are encouraged to apply. Start date for this internship is as soon as possible and the duration is about 3-6 months.


    See All Internships for Electric Systems

  • Openings


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  • Recent Publications

    •  Liu, D., Anantaram, V., Goldsmith, A., "Extracting Broken-Rotor-Bar Fault Signature of Varying-Speed Induction Motors", Asia Pacific Conference of the Prognostics and Health Management Society, September 2023.
      BibTeX TR2023-115 PDF
      • @inproceedings{Liu2023sep,
      • author = {Liu, Dehong and Anantaram, Varatharajan and Goldsmith, Abraham},
      • title = {Extracting Broken-Rotor-Bar Fault Signature of Varying-Speed Induction Motors},
      • booktitle = {Asia Pacific Conference of the Prognostics and Health Management Society},
      • year = 2023,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2023-115}
      • }
    •  Wang, B., Zhang, S., Inoue, H., Kanemaru, M., "Semi-Supervised Machine Learning for Motor Eccentricity Fault Diagnosis", Asia Pacific Conference of the Prognostics and Health Management Society, September 2023.
      BibTeX TR2023-117 PDF
      • @inproceedings{Wang2023sep,
      • author = {Wang, Bingnan and Zhang, Shen and Inoue, Hiroshi and Kanemaru, Makoto},
      • title = {Semi-Supervised Machine Learning for Motor Eccentricity Fault Diagnosis},
      • booktitle = {Asia Pacific Conference of the Prognostics and Health Management Society},
      • year = 2023,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2023-117}
      • }
    •  Wang, B., Inoue, H., Kanemaru, M., "Motor Eccentricity Fault Detection: Physics-Based and Data-Driven Approaches", IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED), August 2023.
      BibTeX TR2023-107 PDF
      • @inproceedings{Wang2023aug,
      • author = {Wang, Bingnan and Inoue, Hiroshi and Kanemaru, Makoto},
      • title = {Motor Eccentricity Fault Detection: Physics-Based and Data-Driven Approaches},
      • booktitle = {IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)},
      • year = 2023,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2023-107}
      • }
    •  Khan, I., Sun, H., Kim, K.J., Guo, J., Nikovski, D.N., "Combined Detection and Localization Model for High Impedance Fault under Noisy Condition", IEEE PES General Meeting, July 2023.
      BibTeX TR2023-093 PDF
      • @inproceedings{Khan2023jul,
      • author = {Khan, Imtiaj and Sun, Hongbo and Kim, Kyeong Jin and Guo, Jianlin and Nikovski, Daniel N.},
      • title = {Combined Detection and Localization Model for High Impedance Fault under Noisy Condition},
      • booktitle = {IEEE PES General Meeting},
      • year = 2023,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2023-093}
      • }
    •  Hu, H., Menner, M., Wang, Y., Fang, H., Sun, D., Takegami, T., "Simulator-based Mission Optimization for Conceptual Aircraft Design with Turboelectric Propulsion", AIAA/IEEE Electric Aircraft Technologies Symposium (EATS), DOI: 10.2514/​6.2023-3872, June 2023, pp. 3872.
      BibTeX TR2023-069 PDF
      • @inproceedings{Hu2023jun,
      • author = {Hu, Hanyao and Menner, Marcel and Wang, Yebin and Fang, Huazhen and Sun, Dengfeng and Takegami, Tomoki},
      • title = {Simulator-based Mission Optimization for Conceptual Aircraft Design with Turboelectric Propulsion},
      • booktitle = {AIAA/IEEE Electric Aircraft Technologies Symposium (EATS)},
      • year = 2023,
      • pages = 3872,
      • month = jun,
      • doi = {10.2514/6.2023-3872},
      • url = {https://www.merl.com/publications/TR2023-069}
      • }
    •  Farakhor, A., Wang, Y., Wu, D., Fang, H., "Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach", American Control Conference (ACC), DOI: 10.23919/​ACC55779.2023.10156008, May 2023.
      BibTeX TR2023-054 PDF
      • @inproceedings{Farakhor2023may,
      • author = {Farakhor, Amir and Wang, Yebin and Wu, Di and Fang, Huazhen},
      • title = {Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach},
      • booktitle = {American Control Conference (ACC)},
      • year = 2023,
      • month = may,
      • publisher = {IEEE},
      • doi = {10.23919/ACC55779.2023.10156008},
      • issn = {2378-5861},
      • url = {https://www.merl.com/publications/TR2023-054}
      • }
    •  Sakamoto, Y., Xu, Y., Wang, B., Yamamoto, T., Nishimura, Y., "Electric Motor Surrogate Model Combining Subdomain Method and Neural Network", Conference on the Computation of Electromagnetic Fields (COMPUMAG), May 2023.
      BibTeX TR2023-041 PDF
      • @inproceedings{Sakamoto2023may2,
      • author = {Sakamoto, Yusuke and Xu, Yihao and Wang, Bingnan and Yamamoto, Tatsuya and Nishimura, Yuki},
      • title = {Electric Motor Surrogate Model Combining Subdomain Method and Neural Network},
      • booktitle = {Conference on the Computation of Electromagnetic Fields (COMPUMAG)},
      • year = 2023,
      • month = may,
      • url = {https://www.merl.com/publications/TR2023-041}
      • }
    •  Xu, Y., Wang, B., Sakamoto, Y., Yamamoto, T., Nishimura, Y., "Comparison of Learning-based Surrogate Models for Electric Motors", Conference on the Computation of Electromagnetic Fields (COMPUMAG), May 2023.
      BibTeX TR2023-042 PDF
      • @inproceedings{Xu2023may,
      • author = {Xu, Yihao and Wang, Bingnan and Sakamoto, Yusuke and Yamamoto, Tatsuya and Nishimura, Yuki},
      • title = {Comparison of Learning-based Surrogate Models for Electric Motors},
      • booktitle = {Conference on the Computation of Electromagnetic Fields (COMPUMAG)},
      • year = 2023,
      • month = may,
      • url = {https://www.merl.com/publications/TR2023-042}
      • }
    See All Publications for Electric Systems

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