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Diesel engines are widely used in automotive sector due to their high fuel efficiency, distinguished durability and great reliability. However, NOx and particulate matters (PM) are main concerns of the Diesel engines due to their lean burn conditions. To reduce these emissions, Diesel engines are usually coupled with state-of-the-art Diesel aftertreatment systems including a Diesel Oxidation Catalyst (DOC), a Diesel Particulate Filter (DPF), and a Selective Catalytic Reduction system (SCR). With increasingly stringent regulations, the estimation and control strategies of Diesel after-treatment systems for NOx and PM reduction are becoming more and more critical and challenging, especially under transient conditions with unknown system dynamics including disturbances and model uncertainties. To address these problems, this thesis focuses on advanced strategies based on disturbance estimation and compensation for improving the performance of Diesel after-treatment systems. Urea injection and ammonia storage ratio are critical for the SCR system to achieve high NOx reduction efficiency and low NH3 slip. Nevertheless, unknown system dynamics including input (urea injection) disturbances and model uncertainties of SCR system make it challenging to achieve high NOx reduction efficiency and low NH3 slip. To deal with these obstacles, Paper 1, Paper 2 and Paper 3 (Chapter 2, 3, and 4 respectively) proposed active disturbance estimation and compensation methods for enhancing the SCR performance. Paper 1 (Chapter 2) introduces two different methods to accurately detect urea injection and correct for urea dosing control. Paper 2 (Chapter 3) depicts a robust Nonlinear Disturbance Observer (robust NDO) to effectively estimate the ammonia storage ratio in a cost-effective way. Paper 3 (Chapter 4) presents a compound control strategies based on active disturbance rejection control (ADRC) to precisely keep NH3 slip low and achieve high NOx reduction efficiency. DOC thermal management is critical to effectively burn the soot during DPF regeneration (PM reduction). But unknown system dynamics including DOC inlet emissions and model uncertainties make it difficult for DOC mean temperature estimation and DOC outlet temperature control during DPF regeneration. To deal with these challenges, Paper 4 and Paper 5 (Chapter 5 and 6 respectively) developed active disturbance estimation and compensation strategies for improving DOC thermal management during DPF regeneration. Paper 4 (Chapter 5) introduces a robust filter based on Smooth Variable Structure Filter (SVSF) with augmented disturbance states to estimate the mean temperature of DOC. Paper 5 (Chapter 6) presents a composite controller combining a feedforward controller and an modified Active Disturbance Rejection Controller (mADRC) with time delay compensation for the DOC outlet temperature control. The proposed methods in the 5 papers are either validated by the calibrated GT-power model or experiments with Diesel after-treatment systems. / Thesis / Doctor of Philosophy (PhD)

This thesis examines factors that influence the daily number of trip departures and arrivals at over 100 hubs comprising Hamilton, Ontario’s (Canada) bike share program – SoBi (Social Bicycles) Hamilton. SoBi operates all year, and during its first year of operation (April 1, 2015 to March 31, 2016), over 200,000 trips were generated on SoBi bikes. The study utilizes data from SoBi Hamilton, the 2011 Canadian Census, the 2011 Transportation Tomorrow Survey, Environment Canada, and Hamilton’s Open Source Data initiative. From these master files, daily trips, meteorological data, temporal variables, socio-demographic and built environment attributes were obtained to generate a comprehensive suite of explanatory variables to explain the daily trips at each hub. A multilevel regression approach was used to understand the associations between bike share usage at each hub and each suite of explanatory variables at two temporal scales: total daily trips at hubs and total daily trips across four time periods of the day. Findings demonstrate that weather and temporal attributes play a significant role in trip departures and arrivals. In addition, hub attributes vary in significance throughout different times of the day for trip departures and arrivals. Overall, the methodology and findings allow us to identify factors that increase SoBi usage, which can also benefit city planners and engineers who are implementing a bike share system with the goal of maximizing bike share activity in urban centers. / Thesis / Master of Science (MSc)

Location-based services have experienced substantial growth in the last decade. However, despite extensive research efforts, sub-meter location accuracy with low-cost infrastructure continues to be elusive. Comparing with infrastructure-based solutions, infrastructure-free indoor localization has the major advantage of avoiding extra cost for infrastructure deployment. There are two typical types of infrastructure-free indoor localization solutions, i.e., Pedestrian Dead Reckoning (PDR)-based and fingerprint-based. PDR-based solutions rely on inertial measurement units to estimate the user's relative location. Despite the effort, many issues still remain in PDR systems. For example, any deployed smartphone-based PDR system needs to cope with the changing orientation of smartphone that the phone might be putting in a pocket, or being taken out to use, etc. In addition, the outputs of Micro Electro-Mechanical Systems (MEMS) sensors on smart devices vary over time which results in rapidly accumulated localization errors without external references. Fingerprint-based solutions utilize different types of location dependent parameters to estimate user's absolute location. Although fingerprint-based solutions are usually more practical than PDR-based, they suffer from laborious site survey process. In this dissertation, we aim to mitigate these challenges. First of all, illumination intensity is introduced as a new type of fingerprints to provide location references for PDR-based indoor localization. We propose IDyLL -- an indoor localization system using inertial measurement units (IMU) and photodiode sensors on smartphones. Using a novel illumination peak detection algorithm, IDyLL augments IMU-based pedestrian dead reckoning with location fixes. Moreover, we devise a burned-out detection algorithm for simultaneous luminary-assisted IPS and burned-out luminary detection. Experimental study using data collected from smartphones shows that IDyLL is able to achieve high localization accuracy at low costs. As for fingerprint collection, several frameworks are proposed to ease the laborious site survey process, without compromising fingerprint quality. We propose TuRF, a path-based fingerprint collection mechanism for site survey. MobiBee, a treasure hunt game, is further designed to take advantage of gamification and incentive models for fast fingerprint collection. Motivated by applying mobile crowdsensing for fingerprint collection, we propose ALSense, a distributed active learning framework, for budgeted mobile crowdsensing applications. Novel stream-based active learning strategies are developed to orchestrate queries of annotation data and the upload of unlabeled data from mobile devices. Extensive experiments demonstrate that ALSense can indeed achieve higher classification accuracy given fixed data acquisition budgets. Facing malicious behaviors, three types of location-related attacks and their corresponding detection algorithms are investigated. Experiments on both crowdsensed and emulated dataset show that the proposed algorithms can detect all three types of attacks with high accuracy. / Thesis / Doctor of Philosophy (PhD)

This thesis focuses on the problem of underwater target tracking with consideration for realistic conditions using active sonar. This thesis addresses the following specific problems: 1) underwater detection in three dimensional (3D) space using multipath detections and an uncertain sound speed profile in heavy clutter, 2) tracking a group of divers whose motion is dependent on each other using sonar detections corrupted by unknown structured background clutter, 3) extended target tracking (ETT) with a high-resolution sonar in the presence of multipath detection and measurement origin uncertainty. Unrealistic assumptions about the environmental conditions may degrade the performance of underwater tracking algorithms. Hence, underwater target tracking with realistic conditions is addressed by integrating the environment-induced uncertainties or constraints into the trackers. First, an iterated Bayesian framework is formulated using the ray-tracing model and an extension of the Maximum Likelihood Probabilistic Data Association (ML-PDA) algorithm to make use of multipath information. With the ray-tracing model, the algorithm can handle more realistic sound speed profile (SSP) instead of using the commonly-assumed constant velocity model or isogradient SSP. Also, by using the iterated framework, we can simultaneously estimate the SSP and target state in uncertain multipath environments. Second, a new diver dynamic motion (DDM) model is integrated into the Probability Hypothesis Density (PHD) to track the dependent motion diver targets. The algorithm is implemented with Gaussian Mixtures (GM) to ensure low computational complexity. The DDM model not only includes inter-target interactions but also the environmental influences (e.g., water flow). Furthermore, a log-Gaussian Cox process (LGCP) model is seamlessly integrated into the proposed filter to distinguish the target-originated measurement and false alarms. The final topic of interest is to address the ETT problem with multipath detections and clutter, which is practically relevant but barely addressed in the literature. An improved filter, namely MP-ET-PDA, with the classical probabilistic data association (PDA) filter and random matrices (RM) is proposed. The optimal estimates can be provided by MP-ET-PDA filter by considering all possible association events. To deal with the high computational load resulting from the data association, a Variational Bayesian (VB) clustering-aided MP-ET-PDA is proposed to provide near real-time processing capability. The traditional Cramer-Rao Lower Bound (CRLB), which is the inverse of the Fisher information matrix (FIM), quantifies the best achievable accuracy of the estimates. For the estimation problems, the corresponding theoretical bounds are derived for performance evaluation under realistic underwater conditions. / Thesis / Doctor of Philosophy (PhD)

A long aspect ratio synthetic jet is produced through an axial slit along part of the length of a cylinder. The jet is excited acoustically by a pair of loudspeakers mounted at the cylinder terminations. The study compares between the performance of two different slits with aspect ratios of 273 and 773. The comparison is based on the spanwise distribution of the mean jet velocity and phase between the jet velocity fluctuations and the excitation signal. Three different frequencies and amplitudes are used to excite the speakers covering the range of frequencies used in the control application. For both cases studied the mean centerline velocity of the jet increases with increasing the amplitude of the exciting signal, but decreases with increasing its frequency. Moreover, velocity deficits of up to 30% are evident as the midspan of the cylinder is approached from either end. Similar trends are also observed for the centerline phase distributions of the velocity fluctuations, with deficits of up to 130°. However, it is observed that for the long slit case the deficits in both the velocity and phase distributions are much larger than those for the short one. The synthetic jet is then mounted in the upstream cylinder of a tandem cylinder arrangement to be used as a control actuator for controlling the vibrations of the downstream cylinder. A simple feedback control mechanism is used at a Reynolds number of about 6.3x104. This Reynolds number corresponds to the case' where the downstream cylinder’s response is dominated with two frequency components, one at the resonance frequency of the cylinder, which is excited by broadband turbulence in the flow, and the other at the vortex shedding frequency. Both slits studied for the characterization experiments are used to compare their performance as control actuators. Both jets produce comparable reductions in the vibration of the downstream cylinder. A reduction of about 20% in the total RMS amplitude of the vibrations signal is achieved. This amounts to a reduction of about 50% in the resonant peak and an average value of about 40% in the vortex shedding peak. The optimal values of gain and time lag of the controller are then used to investigate the effect of the jet on the flow. It is found that the short slit jet produced an effect that was traced up to 1.875 diameters downstream, while the effect of the long slit jet dropped dramatically very close to the upstream cylinder. / Thesis / Master of Applied Science (MASc)