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

    • EA0069: Internship - PWM inverter switching loss reduction

      MERL is looking for a self-motivated intern to work on PWM inverter simulation and design. The ideal candidate would be a Ph.D. candidate in electrical engineering with solid research background in power electronics, control, and optimization. Experience in switching loss reduction modulation is desired. The intern is expected to collaborate with MERL researchers to carry out simulations, optimize design, analyze results, and prepare manuscripts for scientific publications. The total duration is 3 months.

      Required Specific Experience

      • Experience with simulation tools for PWM inverter design.

    • EA0073: Internship - Fault Detection for Electric Machines

      MERL is seeking a motivated and qualified individual to conduct research on electric machine fault analysis and detection methods. Ideal candidates should be Ph.D. students with a solid background and publication record in one more research area on electric machines: electric and magnetic modeling, machine design and prototyping, harmonic analysis, fault detection, and predictive maintenance. Knowledge on data analysis and machine learning algorithms, and strong programming skills using Python/PyTorch are expected. Research experience on modeling and analysis of electric machines and fault diagnosis is desired. Senior Ph.D. students in related expertise, such as electrical engineering, mechanical engineering, and applied physics are encouraged to apply. Start date for this internship is flexible and the duration is 3 months.

    • EA0070: Internship - Multi-modal sensor fusion

      MERL is looking for a self-motivated intern to work on multi-modal sensor fusion for health condition monitoring and predictive maintenance of motor drive systems. The ideal candidate would be a Ph.D. candidate in electrical engineering or computer science with solid research background in signal processing and machine learning. Experience in motor drive system is a plus. The intern is expected to collaborate with MERL researchers to collect data, explore multi-modal data relationship, and prepare manuscripts for publications. The total duration is anticipated to be 3 months and the start date is flexible.

      Required Specific Experience

      • Experience with multi-modal sensor fusion.


    See All Internships for Electric Systems

  • Openings


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  • Recent Publications

    •  Liu, D., Wang, Y., Shinya, T., "A Sparsity-Driven Method to Iteratively Extract Motor Fault Signatures in Varying-Speed Operations", International Conference on Electrical Machines and Systems (ICEMS), November 2024.
      BibTeX TR2024-162 PDF
      • @inproceedings{Liu2024nov,
      • author = {Liu, Dehong and Wang, Yebin and Shinya, Tsurutashin}},
      • title = {A Sparsity-Driven Method to Iteratively Extract Motor Fault Signatures in Varying-Speed Operations},
      • booktitle = {International Conference on Electrical Machines and Systems (ICEMS)},
      • year = 2024,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2024-162}
      • }
    •  Sun, H., Kosanic, M., Kawano, S., Raghunathan, A., Kitamura, S., Takaguchi, Y., "Proactive Sequential Phase Swapping Scheduling for Distribution Systems with a Finite Horizon", IEEE PES Asia-Pacific Power and Energy Engineering Conference, October 2024.
      BibTeX TR2024-149 PDF
      • @inproceedings{Sun2024oct,
      • author = {Sun, Hongbo and Kosanic, Miroslav and Kawano, Shunsuke and Raghunathan, Arvind and Kitamura, Shoichi and Takaguchi, Yusuke}},
      • title = {Proactive Sequential Phase Swapping Scheduling for Distribution Systems with a Finite Horizon},
      • booktitle = {IEEE PES Asia-Pacific Power and Energy Engineering Conference},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-149}
      • }
    •  Wang, B., "Induction Motor Fault Classification with Topological Data Analysis", IEEE Energy Conversion Congress and Exposition (ECCE), October 2024.
      BibTeX TR2024-145 PDF
      • @inproceedings{Wang2024oct,
      • author = {Wang, Bingnan}},
      • title = {Induction Motor Fault Classification with Topological Data Analysis},
      • booktitle = {IEEE Energy Conversion Congress and Exposition (ECCE)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-145}
      • }
    •  Kosanic, M., Sun, H., Kawano, S., Raghunathan, A., Kitamura, S., "Sequentially Pruning Phase Rebalance Schedule: Load Profile Learning Approach", IEEE PES Innovative Smart Grid Technologies Conference - Europe (ISGT Europe), October 2024.
      BibTeX TR2024-143 PDF
      • @inproceedings{Kosanic2024oct,
      • author = {Kosanic, Miroslav and Sun, Hongbo and Kawano, Shunsuke and Raghunathan, Arvind and Kitamura, Shoichi}},
      • title = {Sequentially Pruning Phase Rebalance Schedule: Load Profile Learning Approach},
      • booktitle = {IEEE PES Innovative Smart Grid Technologies Conference - Europe (ISGT Europe)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-143}
      • }
    •  Liu, D., Shinya, T., "ROBUST SLOT HARMONIC EXTRACTION IN VARYING SPEED OPERATIONS", 26TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES ICEM 2024, DOI: 10.1109/​ICEM60801.2024.10700540, September 2024.
      BibTeX TR2024-119 PDF
      • @inproceedings{Liu2024sep,
      • author = {Liu, Dehong and Shinya, Tsurutashin}},
      • title = {ROBUST SLOT HARMONIC EXTRACTION IN VARYING SPEED OPERATIONS},
      • booktitle = {26TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES ICEM 2024},
      • year = 2024,
      • month = sep,
      • publisher = {IEEE},
      • doi = {10.1109/ICEM60801.2024.10700540},
      • issn = {2473-2087},
      • isbn = {979-8-3503-7060-7},
      • url = {https://www.merl.com/publications/TR2024-119}
      • }
    •  Zhang, H., Wang, B., "Supervised Contrastive Learning for Electric Motor Bearing Fault Detection", International Conference on Electrical Machines (ICEM), September 2024.
      BibTeX TR2024-120 PDF
      • @inproceedings{Zhang2024sep,
      • author = {Zhang, Hengrui and Wang, Bingnan}},
      • title = {Supervised Contrastive Learning for Electric Motor Bearing Fault Detection},
      • booktitle = {International Conference on Electrical Machines (ICEM)},
      • year = 2024,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2024-120}
      • }
    •  Park, S., Wang, Y., Qiao, H., Sakamoto, Y., Wang, B., Liu, D., "Control Co-Design for Electric Vehicles with Driving Cycle Synthesis Encoding Road Traffic and Driver Characteristics", IEEE Conference on Control Technology and Applications (CCTA) 2024, DOI: 10.1109/​CCTA60707.2024.10666575, August 2024.
      BibTeX TR2024-114 PDF
      • @inproceedings{Park2024aug,
      • author = {Park, Seho and Wang, Yebin and Qiao, Hongtao and Sakamoto, Yusuke and Wang, Bingnan and Liu, Dehong}},
      • title = {Control Co-Design for Electric Vehicles with Driving Cycle Synthesis Encoding Road Traffic and Driver Characteristics},
      • booktitle = {IEEE Conference on Control Technology and Applications (CCTA) 2024},
      • year = 2024,
      • month = aug,
      • doi = {10.1109/CCTA60707.2024.10666575},
      • url = {https://www.merl.com/publications/TR2024-114}
      • }
    •  Vanfretti, L., Laughman, C.R., "Power System Modeling for Identification and Control Applications using Modelica and OpenIPSL", Conference on Control Technology and Applications (CCTA), August 2024.
      BibTeX TR2024-112 PDF
      • @inproceedings{Vanfretti2024aug,
      • author = {{Vanfretti, Luigi and Laughman, Christopher R.}},
      • title = {Power System Modeling for Identification and Control Applications using Modelica and OpenIPSL},
      • booktitle = {Conference on Control Technology and Applications (CCTA)},
      • year = 2024,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2024-112}
      • }
    See All Publications for Electric Systems

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