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

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Thermal contact resistance between ceramic and metallic surfaces with applications in power electronics

Date created: 
2018-11-29
Abstract: 

In power electronic systems, aluminum oxide (alumina) is frequently used to electrically isolate high voltage devices mounted onto touch safe heat sinks for cooling. The thermal contact resistance (TCR) developed between the aluminum oxide and the metallic surfaces may significantly increase the thermal resistance between the heat generating device and the heat sink. In this thesis, the thermal contact resistance between ceramics and metals is explored analytically and experimentally. The TCR between polished ceramics and bead-blasted metals was first measured under uniform contact pressures (0.25 – 1.5 MPa) in both atmospheric and vacuum conditions. These results are compared with existing metallic surface TCR models to validate their use with metallic-ceramic surfaces. TCR measurements of as-fired, lapped and polished aluminum oxide in contact with machined, cast and anodized extruded aluminum surfaces with thermal interface materials (TIMs) are also presented.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Majid Bahrami
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) M.A.Sc.

Heat and electron conduction in microporous catalyst layers of polymer electrolyte membrane fuel cells

Author: 
Date created: 
2018-11-28
Abstract: 

Recent movement toward zero-emission mobility has propelled significant technological advancements in commercialization of polymer electrolyte membrane fuel cells (PEMFCs). PEMFCs provide electricity by reacting hydrogen with oxygen through two half-reactions occurring inside two respective anodic/cathodic microporous catalyst layers (CLs) with thicknesses of ~2-8 µm. Other products of the overall reaction include water and waste heat. All the electricity generation/consumption and most of the heat generation modes occur inside the CLs through a set of highly coupled multi-physics phenomena (a coupling between the electrochemical reactions, transport of species, electron conduction, and heat conduction). This necessitates knowing thermal and electronic conductivities of CLs for optimizing the fuel cell performance in various operating conditions. In this thesis, novel procedures are developed to measure thermal and electronic conductivities of CLs at low error rates. The procedures are based on novel methods to increase the amount of catalyst in the testbeds for enhancing the signal to noise ratio while ensuring complete deconvolution of the CL bulk signal. Further, a comprehensive platform is developed to characterize microstructure of CLs from different aspects, including a complete scheme for characterizing cracks for the first time. Separate measurements of in-plane and through-plane electronic conductivities, for the first time, uncovers anisotropic microstructure of CLs. CL designs with various compositions and structures are made and characterized. Observed trends in the conductivity data are linked to various structural properties of the CLs to understand structure-property correlations. A complete set of closed-form multi-scale structural models are developed for the conductivities in different directions to understand the underlying physics and provide tools for development of CLs with desired conductivities. The developed models agree well with the experimental data and precisely predict the structural trends. The models also explain and predict effects of different operating conditions. Using the developed tools, design guidelines are proposed for fabricating CLs with desired thermal and electronic conductivities, whose proof of concepts were made and successfully tested in the experimental phase of this research. Order of magnitude analyses show significant potentials for enhancing the fuel cell performance by tuning the conductivities through engineering the microstructure.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Majid Bahrami
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Gas diffusion in thin porous catalyst layers of PEM fuel cells

Author: 
Date created: 
2018-10-30
Abstract: 

Oxygen molecules reach the reaction sites in the cathode catalyst layer (CL) of PEM fuel cells through diffusion, and the water vapor produced at the cathode leaves the reaction sites through diffusion. Therefore, the gas diffusivity of CL influences fuel cell performance. Uniform oxygen delivery to the Pt particles is one of the primary parameters ensuring high activity level of Pt particles and prolonging the CL lifetime. A sufficient supply of oxygen to the CL is required to achieve high current densities. Therefore, to reach high power outputs with low Pt loading, it is vital to understand the mechanism and improve the oxygen diffusion rate within CL and investigate the effects of different operating conditions on its performance. To investigate the effect of different CL designs and operating conditions on gas diffusivity, a modified Loschmidt cell was used to measure the gas diffusivity of CL. Also, the pore size distribution of CL was measured with N2 adsorption porosimetry. Moreover, the structure of CL was modeled through considering a packed-sphere model for carbon particles within agglomerates, and a network of overlapped spherical agglomerates forming the CL. The gas diffusion problem was solved analytically for the CL structure considering both Knudsen and molecular mechanisms. The results show that decreasing the ionomer content of CL from an ionomer to carbon weight ratio of 1.5 to 0.5 increases the relative diffusivity by 400%. Dry milling the catalyst powders for 48 hours led to 50% drop in the relative diffusivities of CL. Drying the catalyst ink on the support substrate at elevated temperatures improved gas diffusivity in some cases. The CL effective diffusivity is higher in higher operating temperature; however, its relative gas diffusivity is lower. High compressive loads (30 MPa or 50 MPa) reduces the CL diffusivity; however, in range of fuel cell operating condition (<5 MPa) the effect is negligible. The effect of gas relative humidity on the relative diffusivity of CL is negligible. On the other hand, liquid water reduces CL relative diffusivity. For example, a 25 wt. % water content in CL results in a 25% drop in relative diffusivity.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Majid Bahrami
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Development of hardware and algorithms for a multi-functional capacitive proximity sensing system

Author: 
Date created: 
2018-11-05
Abstract: 

This thesis focuses on the development of a multi-functional capacitive proximity sensor to improve the worker safety during the industrial human-robot interactions. The sensor is to be mounted on the worker and used to maintain a safe distance between the worker and robot or the parts moved by the robot. The response of a capacitive proximity sensor is a function of the actual distance as well as the geometry of the approaching object. This uncertainty can lead to a wrong estimation of distance or possibly a missed detection. The proposed sensing system in this work aims to solve this issue. Three sensing capabilities, namely distance measurement, surface profile recognition, and parallel motion tracking are implemented in a single platform. These capabilities are achieved by a capacitive sensing element coupled to reprogrammable interface electronics. The sensing element features a 4×4 matrix of electrodes that can be reconfigured to different arrangements at run-time to obtain information on the desired parameters of interest (i.e., distance, shape, and trajectory). The control modules are mapped on a field programmable gate array while the capacitance generated by each configuration of electrodes is measured and quantized by a capacitance-to-digital chipset. Digital filters are used to pre-process the raw capacitive data in order to compensate for random walk and environmental interferences such as temperature and humidity variations. Statistical learning methodologies are applied to classify objects and calculate distance values. Quantitative regression models are built to seek out distance values while classification tools including K nearest neighbors, neural network, and support vector machine are employed to recognize the surface profiles. The performance of the sensing modalities is experimentally assessed with lab equipment as well as on an industrial robot. The system can detect objects and classify their geometries at distances up to about 20 cm with high accuracy. Three different surface profiles can be recognized by all the classifiers. Recognizing the shape of the object improved the regression models and reduced the close-distance measurement error by a factor of five compared to methods that did not take the geometry into account. The capability of tracking the parallel motion is demonstrated by combining the capacitive responses from different electrode connection configurations. The breakthroughs made through this work will make capacitive sensing a viable low-cost alternative to existing technologies for proximity detection in robotics and other fields.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Behraad Bahreyni
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

A monitoring system for honey bee colonies

Author: 
Date created: 
2018-09-28
Abstract: 

In the recent decades, there has been an alarming rate of loss of honey bee colonies. Considering the important role that honey bee colonies play in crop pollination and preserving the environment, it is crucial to monitor the health of managed colonies. There is an increasing interest in continuous monitoring systems that can detect events in the colony, such as death or loss of the queen bee, the death of colony, etc. The purpose of this research is to design and implement a continuous monitoring system for honey bee colonies. Considering factors such as the effectiveness, cost, sensor placement, and known physiological behaviour of honey bees, a sensor array consisting of the following was developed: temperature, relative humidity, and sound. Furthermore, an algorithm is developed to process and analyse the collected data. The collective information gathered from these sensors and the ambient conditions are used to observe the state of the colony.

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

Angular rate sensing using nonlinear microresonators actuated by 2:1 internal resonance

Author: 
Date created: 
2018-09-28
Abstract: 

The goal of this research is to introduce nonlinear microresonator designs that utilize nonlinear modal interaction for application in angular rate sensing. This dissertation specifically looks at the application of nonlinear 2:1 internal resonance, as an actuation mechanism, in micro-electro-mechanical (MEMS) gyroscopes to measure angular input rate. Many MEMS Coriolis vibratory gyroscopes work based on matching the drive- and sense-mode frequencies. The mode-tuning condition cannot be preserved without sophisticated control electronics, due to inevitable fabrication defects and fluctuations in drive parameters. The proposed principle of operation can eliminate the mode-matching requirement in conventional MEMS gyroscopes, and widen the operational frequency region with, ultimately, high flat-top signals. Moreover, it reduces the common problem in MEMS gyroscopes known as cross-coupling by moving the drive mode away from the sense mode of operation. In this thesis, we suggest and develop two microresonator designs in form of frame-shaped and H-shaped microdevices. The proposed microresonators resembled the nonlinear dynamics of spring-pendulum mechanism with forced and 2:1 internal resonances. The reduced-order modeling software was employed to design and characterize the nonlinear microresonators through comprehensive transient simulations. The simulation results revealed the sensitivity of the microresonators to the angular input rate while probing the 2:1 internal resonance. The designed microresonators were fabricated in a foundary process and tested to investigate the nonlinear modal interaction between the vibrational modes. The lumped mass-spring-damper models of the microdevice with electrostatic actuation and detection mechanism were derived and studied via two-variable expansion perturbation technique. Qualitative agreement between experiments and simulations was confirmed for both microresonators with distinct frequency ratios. Finally, the H-shaped microresonator, with closer frequency ratio to 2:1 and better nonlinear features, was mounted on the rate table for the performance evaluation. The experimental findings implied a full-scale range of sensitivity between 0 to 220 deg sec-1. This work as a proof of concept showed that the output voltage of the microresonator linearly changed with an increase in the applied angular rates. This research proposed an alternative actuation mechanism that can provide new avenues to develop the next generation of nonlinear MEMS gyroscopes.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Farid Golnaraghi
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Practical advances in microfluidic electrochemical energy conversion

Author: 
Date created: 
2018-08-10
Abstract: 

Micro-fabrication technologies has enabled the inexpensive production of microchannels which has been utilized in electrochemical flow cells like fuel cells and flow batteries. These offer simplicity and cost benefits as they utilize co-laminar flow for flowing streams separation rather than a physical separator or membrane. This thesis aims to identify practical applications for viable utility of microfluidic flow cells and suggests their potential use for analytical platforms, disposable power sources or combined electrolyte functionalities such as cooling and powering of electronics. All advances reported in this work leverage microfluidic cell architectures with flow-through porous electrodes to achieve competitive performance with simplified, inexpensive device solutions. A previously reported microfluidic redox battery design is modified to form an analytical cell that is applied throughout this dissertation. The analytical cell designs have two separate cell portions which, when connected in parallel, enable in-situ characterization of the dual-pass design, allowing deeper understanding of the reactant conversion and crossover. When the two portions are connected in series, quantifying possible losses in flow cell arrays, such as shunt current, is allowed. The technology is also applied to explore flow cells with non-aqueous electrolytes, which generally enable higher cell voltages but have limited performance from high membrane resistance. The proposed membrane-less cell with non-aqueous electrolytes shows comparable performance with aqueous vanadium electrolytes. Moreover, a chemistry evaluation framework is applied to assess redox reactants and supporting electrolytes selection for biodegradable primary batteries. The selected quinone redox chemistry is demonstrated in a novel 1 V paper-based capillary flow cell, with flow-through porous electrodes, that is proven to be powerful, cheap, scalable and biodegradable and demonstrated to directly substitute a coin cell battery for powering a water quality sensor. This new class of batteries thus holds great promise to radically change the portable battery paradigm; from considering it a harmful waste to a source of biodegradable materials that could even nurture the environment by enriching soil and water beyond its life cycle. Lastly, a scaled co-laminar flow cell is shown for the first time and embedded in a printed circuit board for the application of simultaneous thermal and power management of mounted electronics. This demonstration has advantages in future high-density computers and enables new perspectives for near-term adoption.

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

Identification of intoxicated driving using steering wheel signals and improving lateral control in semi-autonomous and autonomous vehicles

Author: 
Date created: 
2018-08-22
Abstract: 

The studies reported in this thesis focus on specific problems in detection of intoxicated driving, improving the performance of the vehicle when an intoxicated driver is controlling the vehicle, and designing autonomous lateral controllers. In the first phase of this study, we apply system identification techniques on the steering wheel control behavior of the driver to present two models to describe the behaviors of sober and drunk drivers. Then we use these models and online identification methods to detect intoxicated driving from steering wheel data and vehicle lateral position. In the second part of this thesis, we present the idea of improving the steering action of intoxicated drivers by adding serial and parallel controllers to the system while the driver is in the loop. In the first proposed algorithm, the steering signal coming from the steering wheel is fed to a serial controller. The output of the controller becomes the actual steering of the car. In the second suggested algorithm, the output of an independent lateral controller is added to the control signal generated by the human driver. In the third phase, several look-ahead lateral controllers are designed to maintain the vehicle in the center of the lane when the driver is removed from the system. Among the designed controllers are a novel, simple fused neural-network controller, introduced by our group, and a recently introduced robust adaptive controller which applies L_1 adaptive control theory on vehicles for the first time. The designed controllers are tested in challenging scenarios including wind gusts, road banking, icy roads, vehicle parameter uncertainties, and measurement noise, all present at the same time. Finally, longitudinal controllers are studied, designed, and combined with the previously designed lateral controllers to complete the control subsystem of autonomous vehicles.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Ahmad Rad
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) Ph.D.

Large-scale design optimization methods for problems with expensive objectives and constraints

Date created: 
2018-04-23
Abstract: 

With the increasing adoption of complex simulations in engineering design involving finite element analysis (FEA) and computational fluid dynamics (CFD), design optimization problems are increasingly high-dimensional, computationally expensive, and black-box (HEB). In addition, computationally expensive constraints are commonly seen in real-world engineering optimization problems, which pose challenges for existing optimizers. Surrogates, or metamodels, are mathematical functions that are used to approximate computationally expensive models. Use of surrogates in metamodel-based design optimization (MBDO) methods has shown promise in the literature for optimization of expensive and black-box problems. However, current MBDO approaches are often not suitable for high-dimensional problems and often do not support expensive constraints. The goal of this work is to develop surrogate-based methods suitable for efficient single and multi-objective optimization of HEB problems with expensive inequality constraints. This work integrated the concept of trust regions with the Mode Pursuing Sampling (MPS) MBDO method to create the Trust Region-based MPS (TRMPS) optimizer, which dramatically improved performance and efficiency for single-objective high-dimensional problems with inexpensive constraints. To address expensive constraints, an adaptive aggregation-based constraint handling strategy is proposed by hybridizing a function aggregation method with surrogate modeling. The strategy, called the Situational Adaptive Kreisselmeier and Steinhauser (SAKS) method, formed the basis for two new optimizers for solving single and multi-objective HEB problems with expensive constraints. The new methods, called SAKS-Trust Region Optimizer (SAKS-TRO) and SAKS-Multiobjective Trust Region Optimizer (SAKS-MTRO), demonstrated significant performance improvement when benchmarked against other optimizers. SAKS-TRO and SAKS-MTRO were successfully applied to two real engineering design applications: multi-objective optimization of a semiconductor substrate, and single and multi-objective optimization of a recessed impeller for slurry pumps.

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

7-degree-of-freedom hybrid-manipulator exoskeleton for lower-limb motion capture

Date created: 
2018-04-06
Abstract: 

Lower-limb exoskeletons are wearable robotic systems with a kinematic structure closely matching that of the human leg. In part, this technology can be used to provide clinical assessment and improved independent-walking competency for people living with the effects of stroke, spinal cord injury, Parkinson’s disease, multiple sclerosis, and sarcopenia. Individually, these demographics represent approximately: 405 thousand, 100 thousand, 67.5 thousand, 100 thousand, and 5.9 million Canadians, respectively. Key shortcomings in the current state-of-the-art are: restriction on several of the human leg’s primary joint movements, coaxial joint alignments at the exoskeleton-human interface, and exclusion of well-suited parallel manipulator components. A novel exoskeleton design is thus formulated to address these issues while maintaining large ranges of joint motion. Ultimately, a single-leg unactuated prototype is constructed for seven degree-of-freedom joint angle measurements; it achieves an extent of motion-capture accuracy comparable to a commercial inertial-based system during three levels of human mobility testing.

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