Mechatronics Systems Engineering - Theses, Dissertations, and other Required Graduate Degree Essays

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Assessment and development of mitigation strategies for membrane durability in fuel cells

Author: 
Date created: 
2021-07-22
Abstract: 

Fuel cell membranes undergo simultaneous or individual chemical and mechanical degradation under dynamic fuel cell operating conditions. This combined stress development effect compromises the functionality of the membrane and ultimately, the overall durability of the fuel cell system. Therefore, it is critical to understand the underlying degradation mechanisms and failure modes under operational conditions. In this thesis, an extensive research methodology including accelerated stress tests, visualization techniques, and finite element modeling is adopted in order to understand and mitigate membrane degradation. The membrane characterization is facilitated using a non-invasive laboratory-based X-ray computed tomography (XCT) system for 3D visualization of membrane damage progression over the lifetime of the fuel cell. The 3D XCT approach is first applied to understand the degradation mechanism responsible for combined chemical and mechanical membrane degradation. The XCT approach is further expanded to 4D in situ visualisation through periodic same location tracking within a miniature operational fuel cell. Fuel cell membranes with mechanical reinforcements and chemical additives are tested as existing mitigation strategies for the isolated degradation stressors. Under pure chemical degradation, the chemically and mechanically reinforced membrane does not show membrane thinning or shorting sites and exceeds the lifetime of the non-reinforced membrane by 2x. The reinforced membrane also mitigated/delayed the crack development during pure mechanical degradation as compared to the non-reinforced membrane. However, significant membrane degradation is still observed and attributed to buckling and delamination mechanisms within the membrane electrode assembly (MEA). Mitigation of these mechanisms is demonstrated through two novel approaches proposed in this thesis: i) reduced surface roughness gas diffusion layers (GDLs); and ii) bonded MEAs. Both mitigation strategies are tested using the same experimental workflow and shown to provide substantial mitigation against fatigue driven mechanical membrane degradation via reduced membrane buckling, resulting in a doubling of the test lifetime in each case. Complementary finite element simulations corroborate the experimental findings and further estimate the critical GDL void sizes to prevent membrane buckling and the required interfacial MEA adhesion quality to stabilize the MEA for improved membrane durability.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Erik Kjeang
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Control system development for energy-efficient lighting in greenhouses

Author: 
Date created: 
2020-08-20
Abstract: 

This thesis focuses on the development and implementation of feedback control with application to an energy-efficient lighting system for potential application in a greenhouse environment. The proposed control system was developed and implemented in four stages. First, the lighting model for the red and blue lights was identified separately to ensure uniform light distribution at plant canopies. Subsequently, a daylight environment was constructed using the MATLAB/Simulink environment. The performance of the system was evaluated on a proof of concept system through a series of simulations to verify the control performance. In the second stage, the proposed concept was implemented to regulate the intensity of dimmable multi-spectrum LED fixtures for achieving desired spectral irradiance levels and color ratios while utilizing daylight harvesting to enhance energy-efficiency. To ensure the stability and performance, a Smith predictor was utilized to compensate for the delay introduced into the system by the communication hardware. Implementation of the proposed system with a smooth transient response ensured lower energy consumption for the LED panels. In the third stage, a testbed with environment monitoring and intelligent LED lighting control system was implemented with potential utilization in an Internet of Things (IoT) smart greenhouse environment. The performance of the LED control system was verified through conducting plant experiments in the proposed testbed. It was shown that the proposed testbed is capable of achieving the desired light requirement for the tested plant while maintaining satisfactory plant growth results. Finally, in the fourth stage, the proposed concept was extended to a small-scale plant growth and implemented on a Raspbian operating system with the IoT technology. The system was utilized to implement lighting control and environmental monitoring applications for greenhouses in remote areas. Results show potential for prominent energy savings when the proposed lighting system is utilized to grow kale microgreens, which further resulted in improved plant quality due to uniform lighting conditions achieved through feedback control.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Mehrdad Moallem
Jason Wang
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Converter based electrochemical impedance spectroscopy for fuel cell stacks

Author: 
Date created: 
2021-03-19
Abstract: 

Fuel cells are important devices in a hydrogen-based chain of energy conversion. They have distinctive advantages over batteries with their higher energy density and faster refueling speed, which make them attractive in stationary power supplies and heavy-duty vehicles. However, the high cost and low durability associated with modern fuel cells are still hindering their wider commercialization. Besides developing more reliable and lower cost materials and advanced assemblies of cells and stacks, a practical and effective diagnostic tool is highly needed for fuel cells to identify any abnormal internal conditions and assist with maintenance scheduling or application of on-board mitigating schemes. Conventionally, linear instruments were used for fuel cell EIS, however, limited to single cells or short stacks only as a laboratory testing method. With recent developments, EIS enabled by switching power converters are capable of being applied to a high-power stack directly. This approach has the potential for practical field applications such as a servicing tool for fuel cell manufacturers or an on-board diagnostic tool of a moving vehicle. Previous works on converter based EIS have made a few different attempts at conceptually realizing this solution while several significant issues were not well recognized and resolved yet. As such, this thesis explores further on this topic to address the flexibility of EIS perturbation generation, the perturbation frequency range, and the linkage between fuel cell EIS requirements and the converter design to push for its readiness for practical implementations. Several new solutions are proposed and discussed in detail, including a total software approach for existing high-power converters to enable wide-frequency-range EIS, a redesign of the main dc/dc converter enabling wide-frequency-range perturbations, and a separate auxiliary converter as a standalone module for EIS operation. A detailed analysis of oscillations brought by converter based EIS in powertrains is also presented.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Jiacheng Wang
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Functional impairment following axonal injury

Date created: 
2021-01-18
Abstract: 

Following trauma or other neurological disorders, a series of events happen that cause axonal dysfunction or ultimately lead to axonal death. Computational modeling of the nervous system facilitates systematic study of the effects of each injury parameter on the output. The overall goal of this research was to develop a new method of simulating axon damage in a biophysical model and quantify the effects of structural damage on signal conduction. To achieve this, three objectives were addressed 1) quantify the effects of normal morphological variation and demyelination on axonal conduction characteristics, 2) develop a new computationally efficient method for modeling damage in axons, and 3) characterize the structure changes observed in human axons and quantify the relationship between these observed changes and axonal function. Biophysical computational models developed in NEURON were employed to characterize morphological changes in damaged axons and study the effects of some of the most common axonal injuries such as myelin damage and spheroid formation on signal propagation in axons with different calibers. To facilitate efficient computational simulation, a new approach for increasing geometrical resolution in NEURON was developed and assessed. To investigate the effects of axonal swelling on action potential conduction in myelinated axons, the morphological properties of axonal spheroids were characterized by analyzing a series of confocal images captured from post-mortem human brain samples of patients with MS and infarction. Our results indicate that subtle abnormalities in nodal, paranodal and juxtaparanodal regions may have sizable effects on action potential amplitude and velocity and more targeted treatments need to be developed that focus on these regions. In addition, the results of our histopathological and computational studies suggest that axons with different diameters may respond differently to injuries and diseases. Therefore, it is important to perform experimental injury models across a wide range of axons to get a more comprehensive understanding of the relationship between axonal morphological features, injury parameters and functional responses. We expect this research to lay the quantitative foundation for finding new potential functional markers of white matter tissue damage and provide further insights into how myelin damage and axonal spheroids may affect function.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Carolyn Sparrey
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Strategies for impure hydrogen use in polymer electrolyte fuel cell systems

Author: 
Date created: 
2020-10-29
Abstract: 

Availability of high purity H2 for low temperature polymer electrolyte fuel cell (PEFC) technology is a necessity for optimum performance and durability. H2 purity depends on the production process as well as post purification measures, which may increase the final pump outlet cost of H2 fuel and operating cost of PEFC applications. Low cost H2 is produced in refineries and other reforming processes. Presence of certain contaminants such as methane, carbon dioxide and carbon monoxide in this H2 may however cause performance degradation in fuel cells. The aim of this thesis is to investigate strategies to mitigate and overcome the fuel cell performance losses resulting from the use of impure H2. Firstly, stack level testing on H2 with isolated contaminants of known concentration are conducted to assess performance losses. These studies are expanded in a single cell for comparison with stack results as well as in devising strategic mitigation techniques. CO, being a major contaminant, is extensively studied with variation of operating current density and CO concentration. Performance losses are partially rectified through application of a CO tolerant electrocatalyst, Pt-Ru/C instead of Pt/C. Two more techniques of air-bleeding and pulsed oxidation are also investigated alongside Pt-Ru/C electrocatalyst for performance recovery through CO oxidation. Parametric studies of pulsed oxidation are undertaken with 80 ppm CO containing H2 fuel for performance recovery and energy efficiency comparison with respect to pure H2 efficiencies. Up to 95% recovery in performance is observed at 0.5 A cm-2 with strategic application of pulsed oxidation when using a threshold cell potential for activation. These studies are further extended to long term pulsing operation of up to 4000 cycles to gauge the robustness and effectiveness of the pulsing process. These studies demonstrate cell potential recovery over extended pulse cycles without any significant decay of fuel cell performance through monitoring of droptime and peak potential values. Lastly, a zero-dimensional model is developed to study the transient surface coverage of different species present at the anode during CO poisoning and predict cell potential losses. It is extended to cover the pulsed oxidation effect and provide overall efficiency of the fuel cell with change of anodic flow parameters. The cost effectiveness of pure and impure H2 fuel used with mitigation techniques are compared and discussed for the interest of commercialization of such processes for the practical use of impure H2 in PEFC systems.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Erik Kjeang
Steven Holdcroft
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Gas diffusion layer characterization and microstructural modeling in polymer electrolyte fuel cells

Date created: 
2021-04-13
Abstract: 

Polymer electrolyte fuel cells (PEFCs), as promising clean energy power sources, are potential substitutes not only for stationary power generation but also for mobile applications specifically in transportation due to their high power density and performance as well as lack of pollutants. PEFC vehicles are at the dawn of commercialization, but still, cost, performance, and durability of current PEFCs need to be further improved to facilitate vast market integration especially under high current density conditions. Pursuant to this goal, comprehensive multidisciplinary understanding of multiphase transport of mass, heat, and electricity in the PEFC constituents including the gas diffusion layer (GDL), as the centerpiece of this thesis, will help to make progress towards material optimization and subsequently fuel cell performance improvements. The GDL transport capability is determined by its effective transport properties which are strongly dependent on its morphological, microstructural, and physical characteristics. Therefore, accurate knowledge regarding the correlation between the GDL microstructure and its transport properties is essential for improving the performance and durability of PEFCs as well as for material optimization, fuel cell design, and prototyping in the area of fuel cell development and manufacturing. In this context, this thesis aims to develop a fast and cost-effective design tool for GDL microstructural modeling and transport properties simulation. Given the limitations of experimental, analytical, and tomographic techniques, stochastic microstructural model development to retrieve the heterogeneous GDL microstructure is a more reliable and flexible tool for GDL material design and prototyping assignments to reduce cost and time of the design cycle. Inspired by the randomness of the GDL porous media structure and its fabrication process, the GDL microstructure is virtually reconstructed as a collection of stochastic processes to provide a robust representation of the structure. The technique of stochastic microstructural reconstruction relies on statistical correlation functions which describe the probabilities of the porous media constituents’ distribution and aim to encompass all the details of the porous media. The obtained 3D digitized realizations of the stochastic model are then used as a domain for numerical computation of transport properties. In this thesis, a unique stochastic GDL microstructural modeling framework inspired by manufacturing information and characterization data is developed in which all GDL substrate and MPL components are resolved, and thoroughly validated with literature and measured data for a variety of MPL-coated GDLs. The effects of PTFE loading and liquid water saturation on the GDL substrate anisotropic transport properties for both gas and liquid phases are found to be highly coupled and are therefore simulated and analyzed jointly. Furthermore, a parametric study is conducted to investigate the effect of MPL pore morphology composition on the MPL and MPL-coated GDL transport properties. The validated stochastic design tool can be used as a fast and accurate framework for reconstructing GDL porous materials and understanding the correlation between the GDL morphology and transport properties. This paves the way for development of improved GDL materials with desired transport properties in modern PEFCs.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Erik Kjeang
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Novel Design of Energy Control Algorithm used in Solar Powered Batteryless Energy Harvesting System to power Wireless Sensor Node

Author: 
Date created: 
2019-11-28
Abstract: 

'Internet of Things' (IoT) technology is becoming one of the most important driving forces in human productivity in recent years.  New generation of 'super sensors', in the form of wireless sensor nodes (WSN) are the most important components in IoT. Powering these devices using traditional batteries creates a tough battery longevity problem, where the rigorous demands on the batteries require them to be replaced once every few years. This is further worsened by the huge number of devices in a typical IoT application, with their demand in power becoming a serious issue.   It is commonly considered that one of the best ways to power these wireless sensor nodes is to use energy harvesters with solar energy harvesting. Due to the unpredictable nature of solar irradiation, a problem to be solved is how a wireless sensor node powered by a solar energy harvester can have continual operation while simultaneously deliver the highest possible service duty.   This thesis presents a new energy control algorithm that addresses this bottleneck problem. Firstly, the analysis of past research using PID Control, Fuzzy Logic, and Adaptive Dynamic algorithm is provided, which reveals significant shortfalls.  The use of a solar irradiation prediction model by one group of researchers results in significant system shutdown (“dead time”) when actual solar irradiation deviates from the prediction model.  Another group of researchers maintain the terminal voltage of the supercapacitor at a certain set point but this approach is not able to avoid system shut down, and it demands an unacceptable operating condition in which certain amount of light must be present for the system to operate. After analysis of these past projects, the design deficits and imprecise design objectives in these researches are elaborated. Secondly, a proposal of a new energy control algorithm with the use of a precise two branch equivalent model is presented, with the employment of Model Predictive Control (MPC) theories to compute important control parameters. An augmented MPC control algorithm is designed based on three new principles, in order to handle the two mingled system input variables of system operating current and system sleep mode current of the WSN. Thirdly, the resulting new energy control algorithm is implemented in a self designed wireless sensor node embedded system. The purpose of this self designed system is to conduct comprehensive field tests to validate the performance and the robustness of the energy control algorithm. Finally, detail results with analysis of the four field tests is presented. The four field tests include the first test with normal operating condition, the second test as a stress test with an obstructed solar panel, the third as an additional stress test with a defective supercapacitor, and the fourth field test under abnormally adverse operating conditions. Except for the third field test which exhibits some time duration (2.8% of the total testing duration) with non-maximized WSN operation, all other field tests demonstrate full fulfillment of the new energy control algorithm’s design objectives. The last part of this thesis summarizes the conclusion of the research. And the research contribution in the field of IoT as well as in other numerous application areas are interpreted.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Zoë Druick
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) M.A.Sc.

A Kinematic Rating System for evaluating helmet performance

Author: 
Date created: 
2019-12-05
Abstract: 

Adopting a helmet has been very helpful in reducing the risk of head injury in activities with a high risk of impact to the head. However, the main focus of most helmet standards is protecting the head against skull fracture through a pass or fail criterion that only measures the linear acceleration of the head during impact. Yet, it is known that most impacts result in both linear and rotational acceleration to the head. A pass-or-fail criterion does not inform the consumers how well a helmet performs. In recent years, Virginia Tech Summation of Tests for the Analysis of Risk (STAR) rating system was introduced to provide more insight into a helmet performance. The STAR rating system quantifies the risk of concussion based on the linear and rotational performance of a helmet. However, the science behind concussion is not fully understood, and in addition to helmet performance, the risk of concussion is closely related to other factors such as age, sex, genetic, the direction of an impact, and previous head trauma. The STAR rating also does not include all crucial factors in assessing a helmet performance, and therefore, it may not provide an accurate performance or risk of injury assessment for a given helmet. In this work, a Kinematic Rating System (KRS) was developed to evaluate helmet performance based on how well a helmet reduces crucial factors such as linear acceleration, rotational acceleration, and rotational velocity. KRS is an effective tool that provides an accurate assessment of the performance of a helmet compared to when the head is not protected by a helmet. KRS requires the helmet of interest to be tested against a 45º anvil at 6.5 m/s impact speed. Various football, hockey, and cycling helmets were tested according to the KRS, and the results were compared with the STAR rating system. In some cases, the performance reported by the STAR rating system were found to have significant discrepancies with the results obtained by the KRS. This is because the STAR rating system does not consider all the crucial factors while evaluating a helmet, such as the magnitude and duration of the acceleration pulse.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Farid Golnaraghi
Gary Wang
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) M.A.Sc.

Soft Gripper Driven by a Solenoid Actuator

Date created: 
2019-11-28
Abstract: 

In the past thirty years, robotics technology has become well-established in the manufacturing industry for reducing worker ergonomic stress and workload by performing operations such as picking and placing objects from a location to another, quickly, repetitively, and accurately. As we continue to integrate robots as versatile aids for industry, it is important to develop mechanisms that facilitate seamless cooperation between humans and robot assistants (RAs). Contributions of this thesis include the design and development of a more advanced, yet simple and cost-effective soft industrial robotic gripper that is scalable, and can be mounted on a wide range of commonly used robotic arms. The finished gripper prototype uses inexpensive components, and thus, would be economical to produce while addressing the needs of industry. Depending on the application, the developed gripper can outperform the state of the art in many “pick and place” tasks and is capable of picking up a wide variety of objects in size, weight, geometry and texture. To be applicable to current industrial warehouse environments, a series of tests were conducted to evaluate the effectiveness of the gripper in picking up and placing a set of items commonly available. The developed gripper in this work was mounted on a KUKA arm, and was tested for gripping objects from delicate ones such as a light bulb to heavier ones such as a 23 cm x 14 cm x 12 cm pack of eight cans of soda, weighing around 3 kg with a measured speed of 0.88 m/s.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Carlo Menon
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) M.A.Sc.

Motion generation of a wearable hip exoskeleton robot using machine learning-based estimation of ground reaction forces and moments

Date created: 
2019-09-11
Abstract: 

Statistical data acquired from US citizens in 2013 showed that the overall percentage of all disabilities for all ages in this country was around 12.6%, in which the “ambulatory disabilities” had the highest prevalence rate (7.1 %). This amount is estimated around 7.2% for all Canadian adults, which corresponds to more than 2.5 million people. In order to improve the quality of life of those with ambulatory disabilities (e.g., paraplegic people), wearable robotic exoskeleton is being developed in our lab. In this project, Ground Reaction Forces and Moments (GRF/M), which are important data for closed-loop control of an exoskeleton, is estimated based on lower limb motion of a wearable hip exoskeleton user. This method can reduce manufacturing cost and design complications of these types of robots. In order to model GRF/M, Neural Network, Random Forest and Support Vector Machine algorithms are utilized. Afterward, the achieved results from the three algorithms are compared with each other and some of the most recent similar studies. In the next step, the trained models are employed in an online control loop for assisting a healthy exoskeleton user to walk easier. The device applies forces on the user’s upper thigh, which reduces the required torque of the hip flexion-extension joint for the user. Finally, the exoskeleton’s performance is compared experimentally with the cases when the device is not powered or it is simply following the user’s motion based on the inverse kinematics. The results demonstrate that the presented algorithm can help the exoskeleton user to walk easier.

Document type: 
Thesis
File(s): 
Supervisor(s): 
Siamak Arzanpour
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) M.A.Sc.