World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
33
Citations
4877
World Ranking
2999
National Ranking
128

Research.com Recognitions

  • 2015 - Fellow of the American Society of Mechanical Engineers

Overview

Saeid Habibi is affiliated with McMaster University in Canada and focuses on research primarily within the field of Engineering. Their work spans several key subfields including Control and Systems Engineering, Automotive Engineering, Electrical and Electronic Engineering, Mechanical Engineering, and Artificial Intelligence.

Their research topics cover a range of areas such as:

  • Fault Detection and Control Systems
  • Advanced Battery Technologies Research
  • Advancements in Battery Materials
  • Machine Fault Diagnosis Techniques
  • Additive Manufacturing Materials and Processes
  • Additive Manufacturing and 3D Printing Technologies
  • Video Surveillance and Tracking Methods

Prominent venues where Saeid Habibi has published research include:

  • IEEE Access
  • Energies
  • Additive manufacturing
  • Journal of Power Sources
  • Sustainable Energy Technologies and Assessments

The following are some of Saeid Habibi's recent publications:

  • Estimating battery state of health using electrochemical impedance spectroscopy and the relaxation effect (2021), Journal of Energy Storage
  • Review of the Li-Ion Battery, Thermal Management, and AI-Based Battery Management System for EV Application (2022), Energies
  • Reduced-Coupling Coestimation of SOC and SOH for Lithium-Ion Batteries Based on Convex Optimization (2020), IEEE Transactions on Power Electronics
  • Unraveling the low thermal conductivity of the LPBF fabricated pure Al, AlSi12, and AlSi10Mg alloys through substrate preheating (2022), Additive manufacturing
  • Interacting Multiple Model Strategy for Electric Vehicle Batteries State of Charge/Health/ Power Estimation (2021), IEEE Access

Saeid Habibi frequently collaborates with several co-authors, including:

  • Ryan Ahmed
  • Yixin Huangfu
  • Peyman Setoodeh
  • Martin v. Mohrenschildt
  • Ali Ghasemi

In recognition of contributions to the field, Saeid Habibi was named a Fellow of the American Society of Mechanical Engineers in 2015.

Best Publications

  • Design of a new high performance electrohydraulic actuator

    S. Habibi;A. Goldenberg

  • Design of a new high-performance electrohydraulic actuator

    S. Habibi;A. Goldenberg

  • The Smooth Variable Structure Filter

    S. Habibi

  • Gaussian filters for parameter and state estimation

    H.H. Afshari;S.A. Gadsden;S. Habibi

  • Automotive Internal-Combustion-Engine Fault Detection and Classification Using Artificial Neural Network Techniques

    Ryan Ahmed;Mohammed El Sayed;S. Andrew Gadsden;Jimi Tjong

  • Reduced-Order Electrochemical Model Parameters Identification and SOC Estimation for Healthy and Aged Li-Ion Batteries Part I: Parameterization Model Development for Healthy Batteries

    Ryan Ahmed;Mohammed El Sayed;Ienkaran Arasaratnam;Jimi Tjong

  • The Variable Structure Filter

    S. R. Habibi;R. Burton

  • Combined electrochemical, heat generation, and thermal model for large prismatic lithium-ion batteries in real-time applications

    Mohammed Farag;Haitham Sweity;Haitham Sweity;Matthias Fleckenstein;Saeid Habibi

  • Estimating battery state of health using electrochemical impedance spectroscopy and the relaxation effect

    Marvin Messing;Tina Shoa;Saeid Habibi

  • Model-Based Parameter Identification of Healthy and Aged Li-ion Batteries for Electric Vehicle Applications

    Ryan Ahmed;Javier Gazzarri;Simona Onori;Saeid Habibi

  • Novel Model-Based Estimators for the Purposes of Fault Detection and Diagnosis

    S. Andrew Gadsden;Yu Song;Saeid R. Habibi

  • Kalman and smooth variable structure filters for robust estimation

    Stephen Andrew Gadsden;Saeid R. Habibi;Thia Kirubarajan

  • Combined cubature Kalman and smooth variable structure filtering: A robust nonlinear estimation strategy

    S. A. Gadsden;M. Al-Shabi;I. Arasaratnam;S. R. Habibi

  • Reduced-Order Electrochemical Model Parameters Identification and State of Charge Estimation for Healthy and Aged Li-Ion Batteries—Part II: Aged Battery Model and State of Charge Estimation

    Ryan Ahmed;Mohammed El Sayed;Ienkaran Arasaratnam;Jimi Tjong

  • Review of the Li-Ion Battery, Thermal Management, and AI-Based Battery Management System for EV Application

    Unknown

  • Kalman filtering strategies utilizing the chattering effects of the smooth variable structure filter

    M. Al-Shabi;S. A. Gadsden;S. R. Habibi

  • Parameter Identification for a High-Performance Hydrostatic Actuation System Using the Variable Structure Filter Concept

    S. R. Habibi;R. Burton

  • A new form of the smooth variable structure filter with a covariance derivation

    S. Andrew Gadsden;Saeid R. Habibi

  • Reduced-Coupling Coestimation of SOC and SOH for Lithium-Ion Batteries Based on Convex Optimization

    Dianxun Xiao;Gaoliang Fang;Sheng Liu;Shaoyi Yuan

  • A New Robust Filtering Strategy for Linear Systems

    S. A. Gadsden;S. R. Habibi

  • Battery state of charge estimation using an Artificial Neural Network

    Mahmoud Ismail;Rioch Dlyma;Ahmed Elrakaybi;Ryan Ahmed

  • Failure monitoring in a high performance hydrostatic actuation system using the extended Kalman filter

    Y. Chinniah;R. Burton;S. Habibi

Frequent Co-Authors

Andrew A. Goldenberg
Andrew A. Goldenberg University of Toronto
Ali Emadi
Ali Emadi McMaster University
Thiagalingam Kirubarajan
Thiagalingam Kirubarajan McMaster University
Narayan C. Kar
Narayan C. Kar University of Windsor
Simona Onori
Simona Onori Stanford University
Danil V. Prokhorov
Danil V. Prokhorov Toyota Motor Corporation (Japan)
Mohamed A. Elbestawi
Mohamed A. Elbestawi McMaster University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Students pursuing Mechanical and Aerospace Engineering often explore complementary fields and accelerated learning options to enhance their career prospects. For those interested in interdisciplinary skills, online degrees such as speech pathology offer flexible education opportunities. Understanding the speech pathology online program cost can help prospective students budget effectively when considering dual careers or additional certifications.

Veterans seeking to transition into engineering or allied health professions may find tailored support through specialized programs. Resources discussing speech pathology degree online for veterans highlight benefits such as VA education benefits, making it worthwhile to explore these options alongside aerospace studies.

For accelerated pathways, programs like the 5 year accelerated speech pathology programs serve as a model for how students can fast-track degree completion, a concept increasingly relevant in rigorous engineering curricula as well.

Additionally, those blending technical expertise with analytical and investigative skills might explore career paths such as profiling within federal agencies. Understanding the required education, salary, and job outlook detailed in profiler job resources can inspire engineers to consider diversified roles.

Best Scientists Citing Saeid Habibi

Trending Scientists

Recently Published Articles