About
Centre for Mechatronics and Hybrid Technologies
Research Areas
- Fault detection, diagnosis and prognosis
- Hybrid/electric powertrain development
- Electric battery testing, modeling and characterization
- Autonomous driving: tracking & control
- Estimation and cognitive control
- Signal processing and filtering
- Fluid power and hydraulics
- Internal combustion engine modelling
- Electric motor testing and characterization
- Optimization and trade-off analysis
CMHT – Research Facilities
CMHT’s research utilizes the state of the art testing facilities located at McMaster Automotive Resource Centre (MARC). Specializing in collaborative research projects with automotive OEM’s and Tier One’s, CMHT’s researchers work at CMHT and in our partners’ facilities.
Test Laboratories
AVL DynoTK 250 Dynamometer
- 250kW Max Power
- 500Nm Max Torque
- 22,000 rpm Max Speed
- Maximum Acceleration 60,000 rpm/sec
AVL Puma Open Control System
- CAN communication up to 1000 Hz
- EMCON 400 Test rig controller
- Torque Measurement (up to 1kN, 0.05% accuracy)
- 16 high voltage analog inputs (1000V)
- 32 general purpose analog inputs (10V, 20mA, Thermocouple, RTD…)
AVL In-motion Simulation System
DC power up to 1000V, up to 800A
Various test inverters available to support custom E-motors
20kW fluid conditioning system
Horiba Dynas3 HT 250 Dynamometer
- 250kW Max Power
- 718 Nm Max Torque
- 10,000 rpm Max Speed
Horiba STARS Control System
- CAN communication up to 1000 Hz
- SPARCe Test rig controller
- Torque Measurement (up to 2kN, 0.05% accuracy)
- 32 general purpose analog inputs (10V, 20mA, Thermocouple, RTD…)
- 16 general purpose pressure inputs (various ranges)
Emissions Bench
Engine Coolant Temperature Conditioning System (200kW)
Engine Oil Temperature Conditioning System (40kW)
Miriam LFE intake airflow measurement system
Positive displacement volumetric fuel measurement system with on-line density meter
Mustang Dynamometer Chassis Dynamometer
- Duel 218 mm (8.575”) Roller
- Max speed 100 mph, 125mph transient
- Max 268 hp absorption
- 30” to 100” track width
- 6000 lb max axle weight
- 2000 lb mechanical inertia

- Maximum Speed: 8000 RPM
- Maximum Torque: 1003 Nm (0 to 2000 RPM)
- Maximum Power: 210 kW (2000 to 8000 RPM)
- Overload capability
D&V BCT-150
- Full automatic switching between 3 test modules:
Cycler Module, High Frequency Signal Module and Coulombic Efficiency Module - 200KHz High Frequency Signal Module
- Expandable system, up to 16 Cycler Modules
Cycler:
- 1-6 V
- Current ranges: 5 A/25A/ 100A
- Expandable up to 16 100A Cycler Modules, allowing for testing one battery up to 1600 Amps or 16 batteries at
100A.
EIS:
- 1-6V
- Current: 5 A
- Electrochemical Impedance Spectroscopy testing (EIS) can be performed within a shorter period of time,
because we can automatically switch between the 3 test modules – 100 A Cycler Module, High Frequency Signal
Module and Coulombic Efficiency Module
Columbic:
- 1-6V
- Current ranges: 2 A/5A
- measurement reading up to 10ppm
D&V Electronics BST 240 Battery Pack Tester
2 Independent Channels
- Max Current 400A/channel
- Max Voltage 600V/channel
- Max Power 120kW/channel
Two Channels in Parallel
- Max current 800A
- Max Voltage 600V
- Max Power 240kW
Two Channels in Series
- Max current 400A
- Max Voltage 1000V
- Max Power 240kW
HIgh speed switch mode – channel switching in ~100usec
- Max current 400A
- Max Voltage 600V
- Max Power 120kW
One 8 cubic feet Thermal Chamber -63 to +177°C
One 16 cubic feet Thermal Chamber -30 to 177°C
Thermotron SE3000 Environmental Chamber
- 3000l (100 cubic feet) capacity
- 70°C to +180°C (-94°F to +365°F)
Dual Servo-motor/pumps
Dual piston hydraulic cylinder with linear encoder
Simulation for leakage and friction faults
Yokogawa WT1800 Power Meter
General purpose scopes, meters etc.
Vehicle hoist
Service Tools
Snap-on SOLUS ULTRA scan tool
dSPACE Micro Auto Box
Intrepid Controls NeoVI Fire/Vehicle Spy CAN Interface
Velodyne HDL32E Lidar
Delphi Electronically Scanning Radar
Princeton Applied Research Potentiostat/Galvanostat
CMHT – Research
The Centre for Mechatronics and Hybrid Technologies (CMHT) is one of the most advanced research labs in the field of electrified powertrain testing, prognosis, and Fault Detection and Diagnosis (FDD) in Canada and internationally. CMHT has state-of-the-art equipment obtained through multi-million dollar grants secured from the Canadian Foundation for Innovation, NSERC equipment grants, and Ontario Research Fund-Research Excellence (ORF-RE) awards.
Information Box Group
The Centre’s activities fall into six main areas:
Fault Detection and Diagnosis
The ability to detect and diagnose faults is essential for the safe and reliable control of mechanical and electrical systems. In the presence of a fault, the system behaviour may become unpredictable, resulting in a loss of control which can cause unwanted downtime as well as damage to the system. There are two main types of methods to detect and diagnose faults: signal-based and model-based. Signal-based fault detection methods typically use thresholds to extract information from available measurements. This information is then used to determine if a fault is present. Model-based methods, as the name suggests, makes use of faults which can be modelled, typically through system identification. This type of fault detection and diagnosis is popular when well-defined models can be created and utilized. A number of fault detection and identification (FDI) methods are being implemented and developed by our research group. For example, one area of research involves developing a new neural network strategy to be used determining and predicting the presence of faults in engines. Another area of research involves the development of an interacting multiple-model approach, in an effort to correctly identify the presence of faults in an electrohydrostatic actuator (EHA).
Hybrid/Electric Powertrain Development
Testing E-Axles, Electric Motors, Inverters:
- Efficiency Mapping
- Performance Characterization
- Fault Detection, Diagnosis and Prognosis
CMHT has state of the art facilities for testing the e-axles, motors and inverters used in electric and hybrid vehicles. This test equipment is used for advanced research in the areas of performance testing, test optimization, integration testing and with the advanced fault detection and prognostics software, we are able to provide unprecedented insight into e-mobility research.
Electric Battery Testing, Modelling and Characterization
CMHT is researching with major suppliers and users, battery cells, packs and battery management systems.
CMHT has unique testing capabilities with specialized testing equipment from Digatron and D&V Electronics. These resources allow CMHT to provide deep research into batteries, cells and the software running these systems.
Research areas include:
- EIS Model Fitting and Analysis
- State of Charge/ State of Health Estimation
- Li-Ion Battery Modelling
Case Studies:
State and Parameter Estimation Theory
Estimation theory plays an important role in a variety of fields – ranging from astronomy to commerce, and biochemistry to mechanics. It involves determining a value of some parameter of interest, typically by extraction from noisy observations. In engineering, one is usually concerned with the system states of a mechanical or electrical system. Quite often, the states are representative of the dynamics of the system. For example, one may be interested in the position, velocity, and acceleration of an actuator piston. Knowledge of these states is important for the successful control of the actuating device. The states are observed or measured by the use of sensors in the environment. However, measurements typically contain unwanted information such as system and measurement noise. It is the role of a filter to extract the useful information from the measurements, while minimizing the effects of noise and other unwanted disturbances. The smooth variable structure filter (SVSF) is a relatively new (2007) estimation strategy based on sliding mode theory, and has been shown to be robust to modeling uncertainties. It is a predictor-corrector method that makes use of an existence subspace and of a smoothing boundary layer to keep the estimates bounded within a region of the true state trajectory. This creates an inherently stable estimation process. This area of research involves advancing the development of the filter, and working on implementations (simulated and experimental) of the SVSF.
Automotive Tracking Systems
Automotive tracking systems are integral part of any autonomous driving system. A generic automotive tracking system performs several functions. The environment is perceived using sensors such as LiDAR, radar, vision sensor, ultrasonic sensor, and infrared camera. The acquired information is processed for detection and classification of objects of interest. Artificial intelligence and machine learning techniques are among pioneering approaches to tackle this issue. The noisy information about the objects are later employed to estimate the quantities of interest such as position, direction, velocity, acceleration, shape, size, etc. for each object. This information is essential for decision making process for autonomous driving functionalities. In CMHT we have developed our in-house car detection and tracking technology, which has led to a number of publications, and an experimental setup for on-road driving, data collection, and real-time detection and tracking. We aim to use information from different sensors and sensor fusion methods to extend the scope of the project.
Control of Mechatronic Systems
Mechatronics is a multidisciplinary subject, involving mechanical, electrical, computer, control, and systems design engineering. In our research group, mechatronics engineering is used to unite the principles of mechanics, electronics, and computing to generate a simpler, more economical and reliable system. Recently, a novel electrohydrostatic actuator (EHA) prototype was created by combining a computer controlled servomotor with a hydraulic actuator circuit. An EHA is an emerging type of actuator typically used in the aerospace industry, and are self-contained units comprised of their own pump, hydraulic circuit, and actuating cylinder. The main components of an EHA include a variable speed motor, an external gear pump, an accumulator, inner circuitry check valves, a double-rod double-acting cylinder, and a bi-directional pressure relief mechanism. The objective of the design was to provide an efficient and accurate method of actuating heavy loads. A variety of control strategies were studied and implemented on the system in an effort to enhance the system performance. For example, strategies such as fuzzy logic, PID, feedforward, and sliding mode control were implemented. The results of this research have led to a number of conference and journal publications.
CMHT – People
Our world-class researchers.
Information Box Group
Research Team
Peyman Setoodeh, Research Associate
Biography: Dr. Peyman Setoodeh received his B.Sc. and M.Sc. degrees (Hons.) in electrical engineering from Shiraz University, and his Ph.D. in computational engineering and science from McMaster University. He was the Harrison McCain visiting professor with the Marine Additive Manufacturing Centre of Excellence (MAMCE), University of New Brunswick, and an associate professor with the School of Electrical and Computer Engineering, Shiraz University. Previously, he was a senior research engineer with Huawei Noah’s Ark Lab, and a lecturer with the Department of Electrical and Computer Engineering, McMaster University. Dr. Setoodeh was the recipient of the Monbukagakusho Scholarship from the Ministry of Education, Culture, Sports, Science, and Technology in Japan. He has coauthored two books: “Fundamentals of Cognitive Radio” and “Nonlinear Filters: Theory and Applications”. He is a coauthor of a paper on “Cognitive Control”, which was featured as the cover story of the Proceedings of the IEEE in the December issue of the centennial year. Dr. Setoodeh is a senior member of the IEEE.
Research Interests: Artificial Intelligence, Deep learning and deep reinforcement learning, Cognitive systems (integration of perception, memory, attention, learning, planning and action), Industry 4.0 (cyber-physical systems, IoT, Ios, smart factory), battery management sytsems, nonlinear estimation.
Ryan Ahmed, Postdoctoral Fellow

Yixin (Elliott) Huangfu, Postdoctoral Fellow
Yixin (Elliott) Huangfu, Postdoctoral Fellow
Salman Akhtar, Ph.D. Student
Farzaneh Ebrahimizonouz, Ph.D. Student
Biography: Farzaneh holds a B.Sc. from Tabriz University in Electrical Engineering (2015) and a M.A.Sc. in Control Engineering from Shahid Beheshti University (2019). She is currently a Ph.D. student with the department of Mechanical Engineering at McMaster University since May 2022. Farzaneh joined CMHT as part of the battery group working specializing in Battery Mangaement Systems.
Hosna Geraei, Ph.D. Student
Ash (Chang) Liu, Ph.D. Student
Ehsan Majma, Ph.D. Student
Ahsan Saeedzadeh, Ph.D. Student
Lesley Wheat, Ph.D. Student
Wenlin Zhang, Ph.D. Student
Yu (Joe) Zhang, Ph.D. Student
Reza Hosseininejad, M.A.Sc. Student
Biography: Reza is a CMHT member who received a Bachelor of Bio-electronics Engineering from Azad University of Esfahan in 2020. He was awarded as the first academic student in his cohort of the Faculty of Computer and Electrical Engineering in both 2019 and 2020. He has a strong interest and expertise in microprocessor, embedded system, battery management systems, control theory, and estimation theory. He is currently a member of the battery group of CMHT at McMaster University, where he is gaining valuable research experience in the area of battery management systems and battery characterization. His academic achievements demonstrate his potential to make significant contributions in the field of engineering.
Research Interests: microprocessor, embedded system, battery management systems, control theory, and estimation theory

Christian Brice Tongkoua Bangmi, M.A.Sc. Student
Christian Brice Tongkoua Bangmi, M.A.Sc. Student
Biography: Christian holds a B.Eng (Hons) degree in Mechanical Engineering from Coventry University in the United Kingdom. He has over 3 years of industry experience on High Horse Power Diesel and Natural Gas engines manufactured by Cummins and Jenbacher respectively. He joined the Centre of Mechatronics and Hybrid Technologies (CMHT) in September 2022 and is working on his M.A.Sc degree under the supervision of Dr. Habibi. His Masters research focuses on Fault Detection and Diagnostics of internal combustion engines.
Linnea Campbell, M.A.Sc. Student
Biography: Linnea received her B.Tech in Automotive Engineering from McMaster University in 2021. She joined CMHT as part of the Autonomous team in May 2022. Linnea is a M.A.Sc student under the supervision of Dr. Habibi. Her research focuses on the application of radar and vision systems for object detection and scenario identification.

Edgar Armando Vazquez Rodrigez, Ph.D. Student
Edgar Armando Vazquez Rodrigez, Ph.D. Student
Bao Ming (Brian) Ding, M.A.Sc. Student
Adrian Sochaniwsky, M.A.Sc. Student
Jonathan Wong, M.A.Sc. Student
Former Graduate Students
Ruiwen Chen, M.A.Sc. (2022), Thesis Title: Battery Pack Design of Cylindrical Lithium-Ion Cells and Modelling of Prismatic Lithium-Ion Battery Based on Characterization Tests
Ahmed Salem, Ph.D. (2022), Thesis Title: On the Topology and Control of Six-Phase Current-Source Inverter (CSI) for the Powertrain of Heavy-Duty EVs
Sara Rahimifard, Ph.D. (2022), Thesis Title: Advanced State Estimation for Electric Vehicle Batteries
Yixin Huangfu, Ph.D. (2022), Thesis Title: Log Data Analysis for Software Diagnosis: The Machine Learning Theories and Applications
Marvin Messing, Ph.D. (2021), Thesis Title: Advanced Characterization of Battery Cell Dynamics
Yujie Hu, M.A.Sc. (2021), Thesis Title: Camera Based Deep Learning Algorithms with Transfer Learning in Object Perception
Jiahong Dong, M.A.Sc. (2021), Thesis Title: Machine Learning and Deep Learning Algorithms in Thermal Imagining Vehicle Perception Systems
Essam Seddik, Ph.D. (2021), Thesis Title: Advanced Pre-processing Techniques for Cloud-based Degradation Detection using Artificial Intelligence (AI)
Doyi Joo, M.A.Sc (2020), Thesis Title:Feature Extraction and Machine Learning Classifier Development for Fault Detection and Diagnosis
Abdel Rahman Tawakol, M.A.Sc (2020), Thesis Title: Performance Characterization and Modelling of a Lithium-Ion Cell using Electrochemical Impedance Spectroscopy
Rioch Dlyma, M.A.Sc (2020), Thesis Title: A Software Development Framework for Complete Battery Characterization: Testing, Modelling & Parameterization
Christina Riczu, M.A.Sc (2020), Thesis Title: Modeling and Implementation of a Hardware Efficient Low-Voltage-to-Cell Battery Balancing Circuit for Electric Vehicle Range Extension
Mehdi Sadeghkazemi, M. A. Sc. (2019), Thesis Title: Evaluation of Spark Plug Technologies in Spark Ignition Engines by Pareto Front Optimization
Benjamin Miethig, M.A.Sc. (2019), Thesis Title: Convolutional Neural Network Detection and Classification System Using an Infrared Camera and Image Detection Uncertainty Estimation
Ahmed Doghri, M.A.Sc. (2019), Thesis Title: A Real Time Fault Detection and Diagnosis System for Automotive Applications
Mahmoud Ismail, Ph.D. (2018), Thesis Title: Practical Deep Learning Algorithms Using Estimation Theory
Zhongzhen Luo, Ph.D. (2017), Thesis Title: LiDAR Based Perception System: Pioneer Technology for Safety Driving
Min Xu, M.A.Sc. (2017), Thesis Title: Hybrid Electric Vehicle Powertrain Laboratory
Sean Hodgins, M.A.Sc. (2017), Thesis Title: A Wireless Sensor for Fault Detection and Diagnosis of Internal Combustion Engines
Mohammed Farag, Ph.D. (2017), Thesis Title: Thermal-Electrochemical Modeling and State of Charge Estimation for Lithium-Ion Batteries in Real-Time Applications
Essam Seddik, M.A.Sc. (2016), Thesis Title: Fault Detection and Identification of Vehicle Starters and Alternators Using Machine Learning Techniques
Mohammad Zeiaee, M.A.Sc. (2016), Thesis Title: An Intelligent Cell-Level Battery/Ultracapacitor Hybrid
Mina Attari, Ph.D. (2016), Thesis Title: SVSF (Smooth Variable Structure Filter) Estimation for Target Tracking with Measurement Origin Uncertainty
Ali Delbari, M.A.Sc. (2016), Thesis Title: Design and Implementation of a Lithium-ion Cell Tester Capable of Obtaining High Frequency Characteristics
Yifei Feng, M.A.Sc. (2016), Thesis Title: Fault Detection and Diagnosis of an Internal Combustion Engine
Xiang Hu, M.A.Sc. (2015), Thesis Title : Electro-Hydrostatic Actuator (EHA) Position Tracking and Correction
Mahmoud Ismail, M.A.Sc. (2015), Thesis Title: Industrial Extended Multi-Scale Principle Components Analysis for Fault Detection and Diagnosis of Car Alternators and Starters
Ryan Ahmed, Ph.D. (2014), Thesis Title: Modeling and State of Charge Estimation of Electric Vehicle Batteries
Hamed Afshari, Ph.D. (2014), Thesis Title: The 2nd-Order Smooth Variable Structure Filter (2nd-SVSF) for State Estimation: Theory and Applications
Mohammed Farag, M.A.Sc. (2013), Thesis Title: Lithium-Ion Batteries: Modelling and State of Charge Estimation
Seyyed Reza Haqshenas, M.A.Sc. (2013), Thesis Title : Multiresolution-Multivariable Analysis of Vibration Signals; Applications in Fault Diagnosis of Internal Combustion Engines
Dhafar Al-Ani, Ph.D. (2012), Thesis Title: Energy Optimization Strategy for System-Operational Problems
Yu Song, M.A.Sc. (2012), Thesis Title : Electro-hydrostatic Actuator Fault Detection and Diagnosis
Mohammed El-Sayed, Ph.D. (2012), Thesis Title : Multiple Inner-Loop Control of an Electro-Hydrostatic Actuator
Wanlin Zhang, M.A.Sc. (2012), Thesis Title : A Fault Detection and Diagnosis Strategy for Permanent Magnet Brushless DC Motor
Shenjin Zhu, M.A.Sc. (2011), Thesis Title: Modeling, System Identification and Control of A Belt Drive System
Andrew Gadsden, Ph.D. (2011), Thesis Title: Smooth Variable Structure Filtering: Theory and Application
Jeffrey Sylvester, M.A.Sc. (2011), Thesis Title: Characterization and Modeling of Rubbing Friction in a Motored Four-Cylinder Internal Combustion Engine
Kevin McCullough, M.A.Sc. (2011), Thesis Title: Design and Characterization of a Dual Electro-Hydrostatic Actuator
Mohammad Al-Shabi, Ph.D. (2011), Thesis Title: The General Toeplitz/Observability Smooth Variable Structure Filter
Ryan Ahmed, M.A.Sc. (2011), Thesis Title: Training of Neural Networks Using the Smooth Variable Structure Filter with Application to Fault Detection
CMHT – Publications
Journal Papers
- Z. Luo, M. V. Mohrenschildt and S. Habibi, A Probability Occupancy Grid Based Approach for Real-Time LiDAR Ground Segmentation, in IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 3, pp. 998-1010, March 2020
- Z. Luo, M. Attari, S. Habibi and M. V. Mohrenschildt, Online Multiple Maneuvering Vehicle Tracking System Based on Multi-Model Smooth Variable Structure Filter, in IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 2, pp. 603-616, Feb. 2020
- K. P. Divakarla, A Emadi, S. Razavi, S. Habibi and F. Yan., A Review of Autonomous Vehicle Technology Landscape, International Journal Electric and Hybrid Vehicles, Vol. 11, no. 4, pp. 320-345, Sept. 2019
- H. Afshari, S. A. Gadsden, and S. Habibi, A Nonlinear Second-Order Filtering Strategy for State Estimation of Uncertain Systems. Signal Processing. 155, pp. 182-192, Spet. 2018
- H. Afshari, M. Attari, R. Ahmed, A. Delbari, S. Habibi, T.Shoa, Reliable State of Charge and State of Health Estimation Using the Smooth Variable Structure Filter, Control Engineering Practice, Vol. 77, pp 1-14, Aug. 2018
- M. Farag, M. Attari, S. A. Gadsden, and S. Habibi, Lithium-Ion Battery State of Charge Estimation Using One State Hysteresis Model with Nonlinear Estimation Strategies, International Journal of Materials and Metallurgical Engineering, Vol. 11, no. 3, pp. 237-241, 2017.
- M. Attari, S. A. Gadsden and S. Habibi, Target Tracking Formulation of the SVSF with Data Association Techniques, IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 1, pp. 12-25, Feb 2017.
- M. Attari, Z. Luo, and S. Habibi, An SVSF-Based Generalized Robust Strategy for Target Tracking in Clutter, IEEE Transactions on Intelligent Transportation, Vol. 17, no. 5, pp. 1381-1392, May 2016.
- H. H. Afshari, D. Al-Ani, and S. Habibi, A New Adaptive Control Scheme Based on the Interacting Multiple Model (IMM) Estimation, Journal of Mechanical Science and Technology Springer Publications, Vol. 30, No. 6, 2759-2767, 2016.
- R. Ahmed, M. El Sayed, S. A. Gadsden, S. Habibi, and J. Tjong, Artificial Neural Network Training Utilizing the Smooth Variable Structure Filter Estimation Strategy, Neural Comput & Applic (2016) 27: 537. doi:10.1007/s00521-015-1875-2.
- R. Ahmed, M. El-Sayed, S. A. Gadsden, J. Tjong, and S. Habibi, Automotive internal-combustion-engine fault detection and classification using artificial neural network techniques, IEEE Transactions of Vehicular Technology, Vol 64, No. 1, 2015.
- R. Ahmed, J. Gazzarri, S. Onori, S. Habibi et al., Model-Based Parameter Identification of Healthy and Aged Li-ion Batteries for Electric Vehicle Applications, SAE Int. J. Alt. Power. 4(2):233-247, 2015, doi:10.4271/2015-01-0252.
- H. H. Afshari, S. A. Gadsden, and S. Habibi, Robust Fault Diagnosis of an Electro-Hydrostatic Actuator Using the Novel Optimal Second-Order SVSF and IMM Strategies, International Journal of Fluid Power, Vol. 15, No. 3, 181-196, 2014.
- R. Ahmed, M. El Sayed, I. Arasaratnam, J. Tjong, and S. Habibi, Reduced-Order Electrochemical Model Parameters Identification and SOC Estimation for Healthy and Aged Li-Ion Batteries. Part I: Parameterization Model Development for Healthy Batteries, IEEE Journal of Emerging Technologies, Special Issue on Transportation and Electrification, Vol.2, No. 3, 2014.
- R. Ahmed, El Sayed, I. Arasaratnam, J. Tjong, and S. Habibi, Reduced-Order Electrochemical Model Parameters Identification and SOC Estimation for Healthy and Aged Li-Ion Batteries. Part II: Aged Battery Model and State of Charge Estimation, IEEE Journal of Emerging Technologies, Special Issue on Transportation and Electrification, Vol.2, No. 3, 2014.
- S. A. Gadsden, S. Habibi, and T. Kirubarajan, Kalman and Smooth Variable Structure Filters for Robust Estimation, IEEE Transactions on Aerospace and Electronic Systems, Vol. 50, No. 2, April 2014.
- S. A. Gadsden, M. Al-Shabi, I. Arasaratnam, and S. Habibi, Combined Cubature Kalman and Smooth Variable Structure Filtering: A Robust Estimation Strategy, Signal Processing, Vol. 96, Part B, March 2014.
- S. A. Gadsden, Y. Song, and S. Habibi, Novel Model-Based Estimators for the Purposes of Fault Detection and Diagnosis, IEEE/ASME Transactions on Mechatronics, Vol. 18, No. 4, August 2013.
- S. A. Gadsden and S. Habibi, Model-Based Fault Detection of a Battery System in a Hybrid Electric Vehicle, Journal of Energy and Power Engineering, Vol. 7, No. 7, July 2013.
- M. Al-Shabi, S. A. Gadsden, and S. Habibi, Kalman Filtering Strategies Utilizing the Chattering Effects of the Smooth Variable Structure Filter, Signal Processing, Vol. 93, No. 2, February 2013.
- S. A. Gadsden and S. Habibi, A New Robust Filtering Strategy for Linear Systems, ASME Journal of Dynamic Systems, Measurements and Control, Vol. 135, No. 1, January 2013.
- S. A. Gadsden, D. Dunne, S. Habibi, and T. Kirubarajan, Nonlinear Estimation Techniques Applied on Target Tracking Problems, ASME Journal of Dynamic Systems, Measurements and Control, Vol. 134, No. 5, September 2012.
- S. A. Gadsden, S. Habibi, and T. Kirubarajan, The Smooth Particle Variable Structure Filter, Transactions of the Canadian Society for Mechanical Engineering, Vol. 36, No. 2, June 2012.
- S. A. Gadsden, M. Al-Shabi, and S. Habibi, Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle, ISRN Signal Processing, February 2011.
- M. El Sayed and S. R. Habibi, Inner-Loop Control for Electro-Hydraulic Actuation (EHA) Systems, ASME Journal of Dynamic Systems, Measurement and Control, Vol. 134, No. 1, 2011.
- M. Al-Shabi and S. R. Habibi, Iterative Smooth Variable Structure Filter for Parameter Estimation, ISRN Signal Processing, Vol. 2011, Article ID 725108, 2011.
Conference Papers
- M. Messing, T. Shoa and S. Habibi, Lithium-Ion Battery Relaxation Effects, 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, MI, pp. 1-6, June 2019
- B. Miethig, A. Liu, S. Habibi, M. Von Mohrenschildt, Leveraging Thermal Imaging for Autonomous Driving, 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, MI, pp. 1-5, June 2019.
Data Set: Labelled Thermal Data - C. Riczu and J. Bauman, Modeling and Control of a Hardware Efficient Low-Voltage-to-Cell Battery Balancing Circuit for Electric Vehicle Range Extension, 2019 IEEE Transportation Electrification Conference and Expo (ITEC),pp. 1-7, Detroit, USA, June 2019.
- C. Riczu, S. Habibi and J. Bauman, Design and Optimization of An Electric Vehicle with Two Battery Cell Chemistries, 2018 IEEE Transportation Electrification Conference and Expo (ITEC), 2018, pp. 506-512, California, USA, June 2018
- M. Ismail, R. Dlyma, A. Elrakaybi, R. Ahmed, and S. Habibi, Battery State of Charge Estimation Using an Artificial Neural Network, 2017 IEEE Transportation Electrification Conference and Expo (ITEC), Chicago, IL, pp. 342-349, 2017.
- H. H. Afshari, R. Ahmed, M. Farag, and S. Habibi, Dynamic Analysis of a Li-Iron Phosphate Cell Using the Electro-Chemical Modelling Approach, 2016 ITEC/IEEE Transportation Electrification Conference and Expo, Dearborn, Michigan, USA, June 2016.
- H. H. Afshari, M. Attari, R. Ahmed, S. Habibi, Modeling, Parameterization, and State of Charge Estimation of Li-Ion Cells Using a Circuit Model, 2016 ITEC/IEEE Transportation Electrification Conference and Expo, Dearborn, Michigan, USA, June 2016.
- S. A. Gadsden, H. H. Afshari, and S. Habibi, Development of a Sliding Mode Controller and Higher-Order Structure-Based Estimator, 2016 ITEC/IEEE Transportation Electrification Conference and Expo, Dearborn, Michigan, USA, June 2016.
- H. H. Afshari, S. A. Gadsden, R. Ahmed, and S. Habibi, State of Charge Estimation of Li-Ion Batteries Using the Dynamic 2nd Order Smooth Variable Structure Filter, 25th Canadian Congress of Applied Mechanics (CANCAM 2015) London, Ontario, Canada, 2015.
- H. H. Afshari, S. A. Gadsden, and S. Habibi, Condition Monitoring of an Electro-Hydrostatic Actuator Using the Dynamic 2nd-order Smooth Variable Structure Filter, ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, DETC2015-47436, Boston, Massachusetts, USA, 2015.
- M. Attari, H. H. Afshari, and S. Habibi, Maneuvering Car Tracking Using the Interacting Multiple Model and the Dynamic 2nd-order SVSF Method, ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, DETC2015-47375, Boston, Massachusetts, USA, 2015.
- H. H. Afshari, and S. Habibi, Robustness Analysis of Some State Estimation Methods with an Explicit Consideration of Modeling Uncertainties, 28th IEEE Canadian Conference on Electrical and Computer Engineering, Halifax, Canada, 2015.
- H. H. Afshari, D. Al-Ani, and S. Habibi, State Estimation of a Faulty Actuator Using the Second-Order Smooth Variable Structure Filter (the 2nd-order SVSF), 28th IEEE Canadian Conference on Electrical and Computer Engineering, Halifax, Canada, 2015.
- H. H. Afshari, D. Al-Ani, and S. Habibi, Fault Prognosis of Roller Bearings Using the Adaptive Auto-Step Reinforcement Learning Technique, ASME 2014 International Mechanical Engineering Congress & Exposition, IMECE2014-36052, Montreal, Quebec, Canada, 2014.
- M. Attari, and S. Habibi, Automotive Tracking Techniques Using a New IMM based PDA-SVSF, International Mechanical Engineering Congress and Exposition (IMECE), Montreal, QC, November 14-20, 2014.
- M. Attari, S. A. Gadsden, S. Habibi, A Multi-Target Tracking Formulation of the SVSF with the Joint Probabilistic Data Association Technique, ASME 2014 Dynamic Systems and Control Conference (DSCC), San Antonio, TX, October 22-24, 2014.
- M. Attari, S. A. Gadsden, S. Habibi, Target Tracking Formulation of the SVSF as a Probabilistic Data Association Algorithm, American Control Conference (ACC2013), Washington D.C., June 17-19, 2013.
- I. Arasaratnam, J. Tjong, R. Ahmed, and S. Habibi, Adaptive Temperature Monitoring for Battery Thermal Management, SAE World Congress, Detroit, MI, USA, 2013.
- I. Arasaratnam, R. Ahmed, El-Sayed,M., S. Habibi, and J. Tjong, Li-Ion Battery SOC Estimation Using a Bayesian Tracker, SAE World Congress and Exhibition, Detroit, MI, USA, 2013.
- W. Zhang, S. A. Gadsden, and S. R. Habibi, A Wavelet-Based Smooth Variable Structure Filter, ASME Dynamic Systems and Control Conference (DSCC), Ft. Lauderdale, Florida, 2012.
- Y. Song, S. A. Gadsden, S. A. Delbari, and S. R. Habibi, System Modelling and Bulk Modulus Estimation of an Electrohydrostatic Actuator, Bath/ASME Symposium on Fluid Power and Motion Control (FPMC), Bath, England, 2012.
- M. A. El Sayed, S. A. Gadsden, and S. R. Habibi, A Sliding Mode Controller Based on the Interacting Multiple Model Strategy, Bath/ASME Symposium on Fluid Power and Motion Control (FPMC), Bath, England, 2012.
- M. Farag, R. Ahmed, S. A. Gadsden, S. R. Habibi, and J. Tjong, A Comparative Study of Li-ion Battery Models and Nonlinear Dual Estimation Strategies, IEEE Transportation Electrification Conference and Expo (ITEC), Dearborn, Michigan, USA, 2012.
- R. M. Ahmed, S. A. Gadsden, M. A. El Sayed, S. R. Habibi, and J. Tjong, A Signal-Based Fault Detection and Classification Strategy with Application to an Internal Combustion Engine, IEEE Transportation Electrification Conference and Expo (ITEC), Dearborn, Michigan, USA, 2012.
- S. A. Gadsden, Y. Song, and S. R. Habibi, Mathematical Modeling and Fault Detection and Diagnosis of an Electrohydrostatic Actuator, 2012 American Control Conference, Montreal, Quebec, Canada, 2012.
- S. A. Gadsden, Y. Song, K. R. McCullough, and S. R. Habibi, Friction Fault Detection of an Electrohydrostatic Actuator, ASME Dynamic Systems and Control Conference (DSCC) and the Bath/ASME Symposium on Fluid Power and Motion Control (FPMC), Washington D.C., 2011.
- S. A. Gadsden, D. Dunne, S. R. Habibi, and T. Kirubarajan, Combined Particle and Smooth Variable Structure Filtering for Nonlinear Estimation Problems, 14th International Conference on Information Fusion, Chicago, Illinois, 2011.
- S. A. Gadsden and S. R. Habibi, Model-Based Fault Detection of a Battery System in a Hybrid Electric Vehicle, IEEE Vehicle Power and Propulsion Conference (VPPC), Chicago, Illinois, 2011.
- S. A. Gadsden, M. El Sayed, and S. R. Habibi, The Continuous-Time Smooth Variable Structure Filter, 23rd Canadian Congress of Applied Mechanics (CANCAM), Vancouver, British Columbia, 2011.
- R. M. Ahmed, S. A. Gadsden, M. El Sayed, and S. R. Habibi, Fault Detection and Classification of an Electrohydrostatic Actuator Using a Neural Network Trained by the Smooth Variable Structure Filter, 23rd Canadian Congress of Applied Mechanics (CANCAM), Vancouver, British Columbia, 2011.
- S. A. Gadsden, M. El Sayed, and S. R. Habibi, Derivation of an Optimal Boundary Layer Width for the Smooth Variable Structure Filter, 2011 American Control Conference, San Francisco, California, USA, 2011.
- S. A. Gadsden, K. McCullough, and S. R. Habibi, Fault Detection and Diagnosis of an Electrohydrostatic Actuator Using a Novel Interacting Multiple Model Approach, 2011 American Control Conference, San Francisco, California, USA, 2011.
- S. A. Gadsden, D. Dunne, R. Tharmarasa, S. R. Habibi, and T. Kirubarajan, Application of the Smooth Variable Structure Filter to a Multi-Target Tracking Problem, Signal Processing, Sensor Fusion, and Target Recognition, Society of Photo-Optical Instrumentation Engineers (SPIE), Orlando, Florida, 2011.
- S. A. Gadsden and S. R. Habibi, Derivation of the Smooth Variable Structure Information Filter, International Mechanical Engineering Congress and Exposition (IMECE), American Society of Mechanical Engineers, Vancouver, British Columbia, 2010.
- S. A. Gadsden, M. Al-Shabi, and S. R. Habibi, Estimation of an Electrohydrostatic Actuator Using a Combined Cubature Kalman and Smooth Variable Structure Filter, International Mechanical Engineering Congress and Exposition (IMECE), American Society of Mechanical Engineers, Vancouver, British Columbia, 2010.
- S. A. Gadsden, and S. R. Habibi, A New Form of the Smooth Variable Structure Filter with a Covariance Derivation, IEEE Conference on Decision and Control (CDC), Atlanta, Georgia, 2010.
- M. El Sayed and S. R. Habibi, Multiple Sliding Mode Control for an Electrohydraulic Actuator System, Bath/ASME Symposium on Fluid Power and Motion Control (FPMC 2010), Bath, UK, 2010.
- S. A. Gadsden, S. R. Habibi, and T. Kirubarajan, A Novel Interacting Multiple Model Method for Target Tracking, 13th International Conference on Information Fusion, Edinburgh, UK, 2010.
- V. Jouppila, S. A. Gadsden, and A. Ellman, Modeling and Identification of a Pneumatic Muscle Actuator System Controlled by an On/Off Solenoid Valve, 7th International Fluid Power Conference (IFP), Aachen, Germany, 2010.
- S. A. Gadsden and S. R. Habibi, Target Tracking Using the Smooth Variable Structure Filter, Dynamic Systems and Control Conference (DSCC), American Society of Mechanical Engineers, Hollywood, California, 2009.
- M. El Sayed and S. R. Habibi, Inner-Loop Control for Electro-Hydraulic Actuation (EHA) Systems, Dynamic Systems and Control Conference (DSCC), American Society of Mechanical Engineers, Hollywood, California, 2009.
- S. A. Gadsden, D. Dunne, S. R. Habibi, and T. Kirubarajan, Comparison of Extended and Unscented Kalman, Particle, and Smooth Variable Structure Filters on a Bearing-Only Target Tracking Problem, Signal and Data Processing of Small Targets, Society of Photo-Optical Instrumentation Engineers (SPIE), San Diego, California, 2009.
- V. Jouppila, S. A. Gadsden, G. Bone, A. Ellman and S. R. Habibi, Sliding Mode Controller and Filter Applied to a Pneumatic McKibben Muscle Actuator, International Mechanical Engineering Congress and Exposition (IMECE), American Society of Mechanical Engineers, Lake Buena Vista, Florida, 2009.
- S. A. Gadsden, D. Mohammed, and M. Al-Shabi, Regularized Least Squares: A Useful (Forgotten) Tool for Supervised and Semi-Supervised Learning, The 13th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI), Orlando, Florida, 2009.
- S. A. Gadsden and S. R. Habibi, The Future of Automobiles: Cognitive Cars, 22nd Canadian Congress of Applied Mechanics (CANCAM), Halifax, Nova Scotia, 2009.
- S. A. Gadsden and S. R. Habibi, Aircraft Tracking Using a Radar and the Smooth Variable Structure Filter, 22nd Canadian Congress of Applied Mechanics (CANCAM), Halifax, Nova Scotia, 2009.
- S. A. Gadsden and S. R. Habibi, Aerodynamic Flutter and Flight Surface Actuation, International Mechanical Engineering Congress and Exposition (IMECE), American Society of Mechanical Engineers, Seattle, Washington, 2007.
- S. A. Gadsden, A Brief History and Philosophy of Mechanics, 21st Canadian Congress of Applied Mechanics (CANCAM), Toronto, Ontario, 2007.
- S. A. Gadsden and S. R. Habibi, Effects of Aerodynamic Flutter on a Flight Surface Actuator, 21st Canadian Congress of Applied Mechanics (CANCAM), Toronto, Ontario, 2007.
Posters
EECOMOBILITY (ORF) and HEVPD&D Create Conference 2019
- Fault Detection and Diagnosis for Internal Combustion Engines by Ahmed Doghri
- Neural Network-based Sensor Fusion for Vehicle Perception by Ash (Chang) Liu
- Multiphase Drives for EV Applications by Ahmed Salem
- Battery Impedance Mapping and Characterization by Abdel Rahman Tawakol
- Classification and Detection Considerations for Thermal Imaging by Ben Miethig
- Alternative Cathode Substrates for the Na-Air Battery by C. Franko, H. Yadegari, A. Sun, Y. Abu-Lebdeh, G. Goward
- Low-Voltage-to-Cell Battery Management System by Christina Riczu
- Fault Detection and Diagnosis of Internal Combustion Engines by Doyi Joo
- Log Data Analysis and Software Diagnosis by Elliott (Yixin) Hangfu
- Advanced Fault Detection and Diagnosis by Mahmoud Ismail
- Battery Relaxation Effects by Marvin Messing
- Performance Evaluation of Spark Plugs in Gasoline Engines by Mehdi Sadeghkazemi
- Battery Pack Design and Thermal Management by Raven Chen
- Modeling and State of Charge Estimation of Electric Vehicle Batteries by Sara Rahimifard
- Dual High-Resolution Radar Tracking by Viktor Smirnov
EECOMOBILITY (ORF) and HEVPD&D Create Conference 2018
- Battery Impedance Mapping and Characterization by Abdel Rahman Tawakol
- Fault Detection and Diagnosis for Internal Combustion Engines by Ahmed Doghri
- Advanced Vehicle Perception System by Ash (Chang) Liu
- Detection Considerations for Thermal Imaging by Ben Miethig
- Relating Structure and Dynamics to Performance of Na-ion Battery Cathodes by Chelsey Hurst, Kristopher J. Harris, and Gillian R. Goward
- Alternative Cathode Substrates for the Na-Air Battery by Christopher Franko, Hossein Yadegari, Andy Sun, Gillian Goward
- Dual-Chemistry Battery Pack by Christina Riczu
- Fault Detection and Diagnosis of Internal Combustion Engines by Doyi Joo
- Battery Failure Prediction by Essam Seddik
- Advanced Fault Detection and Diagnosis by Mahmoud Ismail
- Injection Optimization of Spark Ignition (SI) Engines by Mehdi Sadeghazemi
- Model Based Fault Detection and Diagnosis on Alternators by Nicholas D’Aquila
- Advanced Lane Detection for Autonomous Driving by Paolo Cudrano
- Integrated Battery Testing Solution by Rioch D’lyma
CMHT – Contact Us
Mailing Address:
Centre for Mechatronics & Hybrid Technologies
McMaster Automotive Resource Centre (MARC)
200 Longwood Road South, Unit 224,
Hamilton, Ontario
Canada L8P 0A6
Phone Number:
1-289-674-0250
Contact Us:
CMHT – Partners



