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Engineering and Technology

D-Index
37
Citations
5646
World Ranking
8381
National Ranking
2321

Overview

Mahdi Shahbakhti is affiliated with Michigan Technological University in the United States. Their research spans multiple areas within Engineering and Chemical Engineering, with extensive work in subfields including Automotive Engineering, Fluid Flow and Transfer Processes, Control and Systems Engineering, Mechanical Engineering, and Materials Chemistry.

Their scholarly output reflects focus on several main topics of study, such as:

  • Advanced Combustion Engine Technologies
  • Vehicle emissions and performance
  • Combustion and flame dynamics
  • Electric and Hybrid Vehicle Technologies
  • Catalytic Processes in Materials Science
  • Advanced Control Systems Optimization
  • Advancements in Solid Oxide Fuel Cells

Some of Shahbakhti's recent publications, indicating areas of applied research and collaboration, include:

  • Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions (2021), published in Progress in Energy and Combustion Science
  • A green hydrogen energy storage concept based on parabolic trough collector and proton exchange membrane electrolyzer/fuel cell: Thermodynamic and exergoeconomic analyses with multi-objective optimization (2022), published in International Journal of Hydrogen Energy
  • Design, thermodynamic, and economic analyses of a green hydrogen storage concept based on solid oxide electrolyzer/fuel cells and heliostat solar field (2023), published in Renewable Energy
  • Integrating Machine Learning and Model Predictive Control for automotive applications: A review and future directions (2023), published in Engineering Applications of Artificial Intelligence
  • Integrated cabin heating and powertrain thermal energy management for a connected hybrid electric vehicle (2020), published in Applied Energy

The frequent co-authors in Shahbakhti's work include:

  • Charles Robert Koch
  • Jeffrey Naber
  • Saeid Shahpouri
  • Armin Norouzi
  • Gordon McTaggart-Cowan

The primary publication venues for Shahbakhti's research are notable for their relevance to control systems, energy, and engineering applications:

  • IFAC-PapersOnLine
  • Energies
  • Control Engineering Practice
  • SSRN Electronic Journal
  • SAE technical papers on CD-ROM/SAE technical paper series

Shahbakhti's multidisciplinary research ranges from theoretical machine learning applications in engine control to practical thermodynamic and economic analyses of green hydrogen energy systems. This body of work reflects integration of advanced combustion engine technologies with emerging sustainable energy solutions and control optimization techniques.

Best Publications

  • A green hydrogen energy storage concept based on parabolic trough collector and proton exchange membrane electrolyzer/fuel cell: Thermodynamic and exergoeconomic analyses with multi-objective optimization

    Unknown

  • Handling model uncertainty in model predictive control for energy efficient buildings

    M. Maasoumy;M. Razmara;M. Shahbakhti;A. Sangiovanni Vincentelli

  • Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions

    Masoud Aliramezani;Charles Robert Koch;Mahdi Shahbakhti

  • Design, thermodynamic, and economic analyses of a green hydrogen storage concept based on solid oxide electrolyzer/fuel cells and heliostat solar field

    Unknown

  • Performance prediction of HCCI engines with oxygenated fuels using artificial neural networks

    Javad Rezaei;Mahdi Shahbakhti;Bahram Bahri;Azhar Abdul Aziz

  • Modeling and analysis of fuel injection parameters for combustion and performance of an RCCI engine

    M. Nazemi;M. Shahbakhti

  • Building-to-grid predictive power flow control for demand response and demand flexibility programs

    Meysam Razmara;Guna Bharati;Drew Hanover;Mahdi Shahbakhti

  • Optimal exergy control of building HVAC system

    M. Razmara;M. Maasoumy;M. Shahbakhti;R.D. Robinett

  • Bilevel Optimization Framework for Smart Building-to-Grid Systems

    Meysam Razmara;Guna R. Bharati;Mahdi Shahbakhti;Sumit Paudyal

  • Integrating Machine Learning and Model Predictive Control for automotive applications: A review and future directions

    Unknown

  • Understanding and detecting misfire in an HCCI engine fuelled with ethanol

    Bahram Bahri;Azhar Abdul Aziz;Mahdi Shahbakhti;Mohd Farid Muhamad Said

  • Characterizing the cyclic variability of ignition timing in a homogeneous charge compression ignition engine fuelled with n-heptane/iso-octane blend fuels:

    M Shahbakhti;C R Koch

  • Modeling and controller design architecture for cycle-by-cycle combustion control of homogeneous charge compression ignition (HCCI) engines – A comprehensive review

    Morteza Fathi;Omid Jahanian;Mahdi Shahbakhti

  • Optimal exergy-based control of internal combustion engines

    M. Razmara;M. Bidarvatan;M. Shahbakhti;R.D. Robinett

  • Predicting Start of Combustion Using a Modified Knock Integral Method for an HCCI Engine

    Kevin Swan;Mahdi Shahbakhti;Charles Robert Koch

  • Integrated cabin heating and powertrain thermal energy management for a connected hybrid electric vehicle

    S. Hemmati;N. Doshi;D. Hanover;C. Morgan

  • Reactivity controlled compression ignition engine: Pathways towards commercial viability

    Amin Paykani;Antonio Garcia;Mahdi Shahbakhti;Pourya Rahnama

  • Model Predictive Control of Internal Combustion Engines: A Review and Future Directions

    Armin Norouzi;Hamed Heidarifar;Mahdi Shahbakhti;Charles Robert Koch

  • Deep learning based model predictive control for compression ignition engines

    Unknown

  • Optimization of performance and operational cost for a dual mode diesel-natural gas RCCI and diesel combustion engine

    Ehsan Ansari;Mahdi Shahbakhti;Jeffrey D. Naber

  • Cycle-to-cycle modeling and sliding mode control of blended-fuel HCCI engine

    M. Bidarvatan;M. Shahbakhti;S.A. Jazayeri;C.R. Koch

  • Physics Based Control Oriented Model for HCCI Combustion Timing

    Mahdi Shahbakhti;Charles Robert Koch

  • Online Simultaneous State Estimation and Parameter Adaptation for Building Predictive Control

    Mehdi Maasoumy;Barzin Moridian;Meysam Razmara;Mahdi Shahbakhti

  • Modeling and experimental study of an HCCI engine for combustion timing control

    Mahdi Shahbakhti

  • Modeling of combustion phasing of a reactivity-controlled compression ignition engine for control applications:

    Kaveh Khodadadi Sadabadi;Mahdi Shahbakhti;Anand N Bharath;Rolf D Reitz

  • A SKELETAL KINETIC MECHANISM FOR PRF COMBUSTION IN HCCI ENGINES

    Patrick Kirchen;Mahdi Shahbakhti;Charles Robert Koch

Frequent Co-Authors

Jeffrey Naber
Jeffrey Naber Michigan Technological University
J. Karl Hedrick
J. Karl Hedrick University of California, Berkeley
John H. Johnson
John H. Johnson Michigan Technological University
Aria Alasty
Aria Alasty Sharif University of Technology
Jing Sun
Jing Sun University of Michigan–Ann Arbor
Rolf D. Reitz
Rolf D. Reitz University of Wisconsin–Madison
Gordon G. Parker
Gordon G. Parker Michigan Technological University
Alberto Sangiovanni-Vincentelli
Alberto Sangiovanni-Vincentelli University of California, Berkeley
Antonio García
Antonio García Universitat Politècnica de València

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