MERL - Mitsubishi Electric Research Laboratories

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Multi-Physical Modeling

Optimal design & robust control through multi-physical modeling.

Our work involves the development of state-of-art modeling and simulation tools for complex, heterogeneous systems. We apply these models for the optimal design and robust control of a variety of systems including HVAC systems, zero-energy buildings, automobiles, and robotic systems.

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  • News & Events

    •  NEWS   Scott Bortoff gave Mercer Distinguished Lecture at Rensselaer Polytechnic Institute
      Date: September 25, 2019
      Where: Rensselaer Polytechnic Institute (RPI), Troy, NY
      MERL Contact: Scott Bortoff
      Research Areas: Control, Multi-Physical Modeling
      Brief
      • The seminar, entitled “HVAC System Control and Optimization,” was part of the Mercer Distinguished Lecture Series in the Electrical, Computer and Systems Engineering Department at Rensselaer Polytechnic Institute (RPI), Troy, NY. Given on Wednesday September 25, 2019, it focused on the systems engineering and control issues associated with highly integrated Heating, Ventilation and Air Conditioning Systems for low and zero energy buildings.
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    •  NEWS   The Ab Initio paper selected as "HOT Physical Chemistry Chemical Physics article" and is made free to access the end of July 2019
      Date: June 12, 2019
      Where: Physical Chemistry Chemical Physics – Published 22 Feb 2019
      MERL Contact: Chungwei Lin
      Research Areas: Applied Physics, Multi-Physical Modeling
      Brief
      • The journal "Physical Chemistry Chemical Physics (PCCP)" selects a few well-received articles highlighted as HOT by the handling editor or referees. The following paper "Band Alignment in Quantum Wells from Automatically Tuned DFT+U" with MERL authors Grigory Kolesov, Chungwei Lin, Andrew Knyazev, Keisuke Kojima, Joseph Katz has been selected as a 2019 HOT Physical Chemistry Chemical Physics article, and is made free to access until the end of July 2019. This paper provides a semi-empirical methodology to compute the lattice and electronic structures of systems composed of 400+ atoms. The efficiency of this method allows for realistic simulations of interfaces between semiconductors, which is nearly impossible using the existing methods due to the extremely large degrees of freedom involved. The formalism is tested against a few established band alignments and then applied to determine the band gaps of quantum wells; the agreement is within the experimental uncertainty.
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  • Internships

    • MP1381: Electric Motor Design

      MERL is seeking a motivated and qualified individual to conduct research in design, modeling, and simulation of electrical machines. The ideal candidate should have solid backgrounds in modeling (including model reduction)/co-simulation of electromagnetics and thermal dynamics of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and real-time control experiments involving motor drives is a strong plus. Senior Ph.D. students in electrical or mechanical engineering are encouraged to apply. Start date for this internship is flexible and the duration is about 3-6 months.

    • MP1443: Numerical optimization of thermal fluid systems

      MERL is seeking a motivated and qualified individual to conduct research in numerical modeling and optimization of thermal fluid systems. A solid background in numerical simulation of fluid dynamics and heat transfer is required. Skills in numerical optimization in partial differential equations are expected and experiences with OpenFOAM are highly desirable. Senior Ph.D. students in applied mathematics, chemical/mechanical engineering and other related areas are encouraged to apply. The duration of the internship is about 3 months.

    • MP1406: Numerical Analysis of Electric Machines

      MERL is seeking a motivated and qualified intern to conduct research in the design, modeling and optimization of electrical machines. The ideal candidate should have solid backgrounds in electromagnetic theory, electric machine design, and numerical modeling techniques (including model reduction), research experiences in electric, magnetic, and thermal modeling and analysis of electrical machines, and demonstrated capability to publish results in leading conferences/journals. Experience with ANSYS, COMSOL, and optimization techniques is a strong plus. Senior Ph.D. students in electrical or mechanical engineering with related expertise are encouraged to apply. Start date for this internship is flexible and the duration is 3-6 months.


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  • Openings


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  • Recent Publications

    •  Teo, K.H., "Report on ISPSD 2019," Tech. Rep. TR2019-161, Mitsubishi Electric Research Laboratories, December 2019.
      BibTeX Download PDFAbout TR2019-161
      • @techreport{Teo2019dec,
      • author = {Teo, Koo Hoo},
      • title = {Report on ISPSD 2019},
      • institution = {Mitsubishi Electric Research Laboratories},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-161}
      • }
    •  Garcia, J., Danielson, C., Limon, D., Bortoff, S.A., Di Cairano, S., "Steady-State Analysis of HVAC Performance using Indoor Fans in Control Design", IEEE Conference on Decision and Control (CDC), December 2019.
      BibTeX Download PDFAbout TR2019-143
      • @inproceedings{Garcia2019dec,
      • author = {Garcia, Joaquin and Danielson, Claus and Limon, Daniel and Bortoff, Scott A. and Di Cairano, Stefano},
      • title = {Steady-State Analysis of HVAC Performance using Indoor Fans in Control Design},
      • booktitle = {IEEE Conference on Decision and Control (CDC)},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-143}
      • }
    •  Ma, T., Komatsu, T., Wang, B., Wang, Y., Lin, C., "Observer Designs for Simultaneous Temperature and Loss Estimation for Electric Motors: A Comparative Study", Annual Conference of the IEEE Industrial Electronics Society (IES), DOI: 10.1109/IECON.2019.8927182, ISSN: 1553-572X, October 2019, pp. 1234-1241.
      BibTeX Download PDFAbout TR2019-122
      • @inproceedings{Ma2019oct,
      • author = {Ma, Tong and Komatsu, Taiga and Wang, Bingnan and Wang, Yebin and Lin, Chungwei},
      • title = {Observer Designs for Simultaneous Temperature and Loss Estimation for Electric Motors: A Comparative Study},
      • booktitle = {IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society},
      • year = 2019,
      • pages = {1234--1241},
      • month = oct,
      • doi = {10.1109/IECON.2019.8927182},
      • issn = {1553-572X},
      • url = {https://www.merl.com/publications/TR2019-122}
      • }
    •  Laughman, C.R., Mackey, C., Bortoff, S.A., Qiao, H., "Modeling and Control of Radiant, Convective, and Ventilation Systems for Multizone Residences", Building Simulation, September 2019.
      BibTeX Download PDFAbout TR2019-093
      • @article{Laughman2019sep,
      • author = {Laughman, Christopher R. and Mackey, Chris and Bortoff, Scott A. and Qiao, Hongtao},
      • title = {Modeling and Control of Radiant, Convective, and Ventilation Systems for Multizone Residences},
      • journal = {Building Simulation},
      • year = 2019,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2019-093}
      • }
    •  Zhang, S., Zhang, S., Wang, B., Habetler, T., "Deep Learning Algorithms for Bearing Fault Diagnostics – A Review", Symposium on Diagnostics for Electric Machines, Power Electronic and Drives (SDEMPED), August 2019.
      BibTeX Download PDFAbout TR2019-084
      • @inproceedings{Zhang2019aug,
      • author = {Zhang, Shen and Zhang, Shibo and Wang, Bingnan and Habetler, Thomas},
      • title = {Deep Learning Algorithms for Bearing Fault Diagnostics – A Review},
      • booktitle = {Symposium on Diagnostics for Electric Machines, Power Electronic and Drives (SDEMPED)},
      • year = 2019,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2019-084}
      • }
    •  Qiao, H., Nabi, S., Laughman, C.R., "Performance Evaluation of HVAC Systems via Coupled Simulation between Modelica and OpenFOAM", International Conference on Compressor and Refrigeration, July 2019.
      BibTeX Download PDFAbout TR2019-073
      • @inproceedings{Hongtao2019jul,
      • author = {Qiao, Hongtao and Nabi, Saleh and Laughman, Christopher R.},
      • title = {Performance Evaluation of HVAC Systems via Coupled Simulation between Modelica and OpenFOAM},
      • booktitle = {International Conference on Compressor and Refrigeration},
      • year = 2019,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2019-073}
      • }
    •  Krupa, P., Danielson, C., Laughman, C.R., Bortoff, S.A., Burns, D.J., Di Cairano, S., Limon, D., "Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump", European Control Conference (ECC), June 2019.
      BibTeX Download PDFAbout TR2019-056
      • @inproceedings{Krupa2019jun,
      • author = {Krupa, Pablo and Danielson, Claus and Laughman, Christopher R. and Bortoff, Scott A. and Burns, Daniel J. and Di Cairano, Stefano and Limon, Daniel},
      • title = {Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump},
      • booktitle = {European Control Conference (ECC)},
      • year = 2019,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2019-056}
      • }
    •  Ploskas, N., Laughman, C.R., Raghunathan, A., Sahinidis, N.V., "Heat Exchanger Circuitry Design by Decision Diagrams", International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, DOI: 10.1007/978-3-030-19212-9_30, June 2019, vol. 11494, pp. 467-471.
      BibTeX Download PDFAbout TR2019-038
      • @inproceedings{Ploskas2019jun,
      • author = {Ploskas, Nikolaos and Laughman, Christopher R. and Raghunathan, Arvind and Sahinidis, Nikolaos V.},
      • title = {Heat Exchanger Circuitry Design by Decision Diagrams},
      • booktitle = {International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research},
      • year = 2019,
      • volume = 11494,
      • pages = {467--471},
      • month = jun,
      • doi = {10.1007/978-3-030-19212-9_30},
      • url = {https://www.merl.com/publications/TR2019-038}
      • }
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