Mahdi Shahbakhti

Mahdi Shahbakhti


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  • Associate Professor, Mechanical Engineering–Engineering Mechanics
  • Affiliated Associate Professor, Electrical and Computer Engineering
  • PhD, Mechanical Engineering, University of Alberta, Canada


Dr. Shahbakhti joined MTU in August of 2012. Prior to this appointment, he was a post-doctoral scholar for two years in the Mechanical Engineering Department at the University of California, Berkeley. He worked in the automotive industry for 3.5 years on R&D of powertrain management systems for gasoline and natural gas vehicles. Some of his past academic and industrial research experience includes system identification, physical modeling and control of dynamic systems including combustion engines, vehicle emission aftertreatment systems, hybrid electric vehicles, and HVAC systems.

His research at Michigan Tech focuses on increasing efficiency of energy systems through utilization of advanced control techniques. His current research involves the transportation and building sectors which account for 68% of total consumed energy in the United States. Dr. Shahbakhti's research to optimize efficiency of energy systems centers on developing and incorporating the following research areas: thermo-kinetic physical modeling, model order reduction, grey-box modeling, adaptive parameter estimation, model-based and nonlinear controls.

 Shahbakhti is an active member of ASME Dynamic Systems & Control Division (DSCD), serving as the vice-chair of the Energy Systems (ES) technical committee and secretary of the Automotive Transportation Systems (ATS) technical committee, chairing and co-organizing sessions in the areas of modeling, fault diagnosis, and control of automotive systems, and building energy systems.

Links of Interest

Areas of Expertise

  • Dynamic Systems Modeling and Control
  • Powertrain/Vehicle Control
  • Internal Combustion Engines
  • Vehicular Emissions and Aftertreatment Systems
  • Building Energy Controls

Research Interests

  • Modeling and Control of Energy Systems
  • Hybrid Electric Vehicles
  • Connected Vehicles
  • Advanced Combustion Engines
  • Energy Control of Buildings in a Smart Grid

Recent Publications

  • B. Bahri, M. Shahbakhti, A.A. Aziz, "Real-time Modeling of Ringing in HCCI Engines using Artificial Neural Networks," Energy, Volume 125, Pages 509–518, 2017. Read More
  • M. R. Amini, M. Shahbakhti, S. Pan, J. K. Hedrick, "Bridging the Gap Between Designed and Implemented Controllers via Adaptive Robust Discrete Sliding Control," Control Engineering Practice, Vol. 59, pages 1-15, 2017. Read More
  • A. Solouk, M. Shakiba, M. Shahbakhti, "Analysis and Control of a Torque Blended Hybrid Electric Powertrain with a Multi-Mode LTC-SI Engine," SAE Int. J. of Alternative Powertrains, 15 pages, 6(1):2017, doi:10.4271/2017-01-1153, 2017. Read More
  • B. M. Singalandapuram, J. H. Johnson and M. Shahbakhti, "Predicting Pressure Drop, Temperature and Particulate Matter Distribution of a Catalyzed Diesel Particulate Filter using a Multi-zone Model including Cake Permeability," Emission Control Science & Technology, pages 1-31, doi:10.1007/s40825-017-0062-6, 2017. Read More
  • M. Razmara, G. Bharati, M. Shahbakhti, S. Paudyal, R. Robinett, "Bilevel Optimization Framework for Smart Building-to-Grid Systems," 12 pages, IEEE Transactions on Smart Grid, Issue 99, 2016. Read More
  • A. Solouk, M. Shahbakhti, "Energy Optimization and Fuel Economy Investigation of Series Hybrid Electric Vehicle Integrated with Diesel/RCCI Engines," Energies, 9(12), pages 1-23, 1020; 2016. Read More
  • M. Razmara, M. Bidarvatan, M. Shahbakhti, R. Robinett III, "Optimal Exergy-based Control of Internal Combustion Engines," Applied Energy, Vol. 183, pages 1389-1403, 2016. Read More
  • K. Khodadadi Sadabadi, M. Shahbakhti, A. N. Bharath and R. D. Reitz, "Modeling of Combustion Phasing of a Reactivity-Controlled Compression Ignition Engine for Control Applications," Int. J. of Engine Research, Vol. 17, Issue 4, Pages 421-435, 2016. Read More

Recent Research Projects

NEXTCAR: Connected and Automated Control for Vehicle Dynamics and Powertrain Operation on a Light-Duty Multi-Mode Hybrid Electric Vehicle

Principal Investigator: Jeffrey Naber
Co-PI: Bo Chen
Co-PI: Darrell Robinette
Co-PI: Mahdi Shahbakhti
Co-PI: Kuilin Zhang
College/School: College of Engineering
Department(s): Mechanical Engineering-Engineering Mechanics

Center/Institute: Advanced Power Systems Research Center (APSRC)