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Driver assistance for steering while reversing long combination vehicles
No full textLong combination vehicles, such as A-double configurations, pose significant challenges during low-speed reversing
due to their length and multiple articulation points, which increase the risk of instability and jackknifing.
This project investigates a driver-assist approach for reverse steering of such vehicles, aiming to improve controllability
during low-speed manoeuvres.
A desktop simulation framework was developed using TruckMaker for vehicle modelling and MATLAB/Simulink
for control implementation and visualisation. The reversing behaviour was described using a kinematic singletrack
model for articulated vehicles, and an LQR-based feedback controller was designed to stabilise articulation
angles and regulate the reversing trajectory. Driver input is provided through a knob-based interface specifying
the desired turning radius, which is used to calculate steering commands for the tractor and the rear trailer.
The system was evaluated in simulation through multiple reversing scenarios, including straight-line, constantradius,
and misaligned initial conditions, demonstrating stable reversing behaviour without jackknifing and
consistent path tracking under the tested conditions. In addition, a CAN communication framework was
implemented to explore real-vehicle integration. While vehicle state signals were successfully received in real
time, steering command transmission could not yet be validated due to gateway limitations. The project
establishes a simulation and HIL-ready framework for future refinement and real-vehicle validation
Deep learning-based methods for segmentation and labelling of clay
No full textRecent advancements in x-ray technology have enabled non destructive 3D sub-micron
imaging of clay. In this work, a 3D tomography of kaolinite particles is analysed.
Conventional segmentation algorithms are used along with a deep learning-aided
method, which brings novelty to the clay research area. The clay image is segmented
to acquire morphological properties of the material, intended to be used to inform
continuum models for clay used at the engineering scale. Imaging clay is especially
challenging because of its small particle size and thin aggregated platelets. A small
clay dataset will be developed to evaluate the performance of segmentation techniques
and to train a machine learning-model called the Segment Anything Model 2 (SAM
2). Advanced contemporary studies in biomedical segmentation show compelling
results using SAM 2 and this study is proposing to bring this technique into the area
of geomechanics. This study aims to lay a path for future research to strengthen
the link between physical relationships and observed clay behaviour by providing
information of clay micro-structures
The big car dilemma exploring consumer attitudes toward vehicle size and the barriers to downsizing
No full textHome Energy Management System Optimization with Stochastic Programming
No full textThis thesis explores the optimization of Home Energy Management Systems (HEMS)
with a focus on battery electric vehicle (BEV) charging, using two different methods:
Linear Programming (LP) and Stochastic Programming. The BEV is modeled with
vehicle-to-everything (V2X) functionality, allowing it to both charge and discharge
energy to support the household or grid.
The primary aim is to incorporate uncertainty into the optimization process, acknowledging
that in real-world scenarios, exact information about the vehicle’s arrival
time and current state of energy (SOE) is rarely known in advance. We begin
by examining uncertainty in both arrival time and SOE, then narrow the focus to
uncertainty in SOE alone. In the final part of the thesis, we investigate the impact of
power tariffs to determine whether incorporating them into the optimization yields
meaningful benefits for households.
Our results show that stochastic optimization introduces a small increase in computational
cost while significantly reducing the risk of unwanted outcomes caused by
uncertainty. While the cost difference per vehicle is fractional, the impact becomes
substantial when scaled across many BEVs. The benefits extend beyond cost savings,
by optimizing charging to occur during low spot price hours, we also reduce
the environmental footprint, as electricity is typically greener during these periods.
In addition, the ability to sell back energy to the grid when it is not needed helps
balance demand and supports grid stability.
Therefore, assuming perfect foresight and relying solely on LP is not representative
of real-world conditions. We conclude that accounting for uncertainty through
stochastic methods is a cost-effective and scalable improvement for future energy
management systems
A study of the Gothenburg tramways system with a focus on crisis preparedness and risk management: Ensuring compliance with NIS2 and CER directives through procurement and supplier relationships
No full textThis thesis examines how the City of Gothenburg’s tramway procurement and sup plier relationships can be organized to ensure compliance with the EU’s NIS2 and
CER directives. Using a qualitative case study approach with semi-structured in terviews of key municipal and supplier stakeholders, the study identifies gaps in
awareness, governance, supplier readiness, contract design, and leadership engage ment. Findings indicate that effective implementation requires formal governance
structures, role-specific training, procurement criteria aligned with criticality levels,
flexible contractual clauses, clear information classification, and sustained leader ship. The study proposes actionable recommendations and outlines opportunities
for future research, including longitudinal effects, SME-adaptability, and frameworks
for sensitive data protection
Investigating the economical impact of smart charging strategies at a fully electric truck depot
No full textDesigning a prototype acoustic leaky wave antenna
No full textAcoustic direction finding is a useful tool for navigational applications. Current techniques
for achieving this rely on the use of many electro-acoustic components, which are expensive
to produce and consume a lot of power. Acoustic Leaky Wave Antennas (ALWAs) offer a
potential for a low-cost alternative, using much fewer electro-acoustic components and the
inherent directionality of the geometrical structure to produce a similar effect. ALWAs
possess a directionality which changes with frequency due to their dispersive properties,
hence allowing for frequency scanning. Natural material ALWAs can scan angles from
broadside (perpendicular to the length of the antenna) to endfire (parallel to the length
of the antenna). Metamaterials may be used to extend the range to backfire (180◦
from endfire).
This thesis focuses on deriving a model for a rectangular natural material ALWA with
either a long slit or a series of periodically spaced circular holes. The theoretical model
was tested using Finite Element Method (FEM) simulations in Comsol and experimental
measurements of a physical prototype. First, the theoretical model was tested with Comsol
simulations. When the model was verified by the simulations, two particular designs
with circular holes were chosen for the manufacture of physical prototypes. The directivity of
the prototypes was measured using a rotating table and a microphone. Monopole
and dipole sources were used to investigate different modes of the ALWA.
The results obtained for the ALWA with holes showed good agreement between the theoretical
model, the FEM simulation and the experimental measurements. For the slit ALWA, the
results were also satisfactory. However, the model may be improved, particularly at lower frequencies
Screen Space Global Illumination Using Radiance Cascades in 3D Video Games
No full textAchieving accurate Global Illumination (GI) is essential for creating visually compelling and photorealistic imagery in computer graphics. Recent advancements in GI typically require temporal accumulation or reuse of samples in order to achieve real-time performance at a good quality. However, interactive video games may require GI solutions that respond quickly to user interaction and rapidly changing lighting conditions. We develop a lighting method for video games, specifically designed for the constraints present in the game As We Descend by Box Dragon, where the camera has limited movement and all relevant parts of the scene are on screen at all times, contains many short lasting emissive visual effects, with a budget of a few milliseconds per frame on modern hardware. To create a method for these conditions, we make use of ideas first presented by Alexander Sannikov for use in Path of Exile 2, Radiance Cascades (RC), which is an efficient data structure for representing a lightfield [Ale23]. We make use of a recent screen-space lighting technique, Visibility Bitmask Global Illumination (VBGI) [TLG23] combined with RC, by placing probes in screen-space. We detail many of the optimizations and adjustments needed to combine these techniques, and allowing them to run in real-time.
During evaluation, we go over various parameters that allow scaling the method to various performance levels, allowing it to run at down to 2ms at the lowest settings, 6 milliseconds at medium settings, and 26 milliseconds on high settings, with a
memory usage ranging from 0.03GiB to 3.9GiB depending on the settings. At this performance, it can achieve one bounce screen-space global illumination along with emissive lighting, with a radius that covers the entire screen. The method has no high-frequency noise without the use of a separate denoising pass, and does not use temporal accumulation or reuse which would otherwise lead to temporal artifacts. The method is not without issue, as there are many limitations and artifacts, and is an approximation of ground truth GI. Firstly, anything that is off-screen cannot contribute or occlude lighting, the chosen screen-space tracing method causes over-brightening of the background, and upscaling radiance data causes artifacts at especially lower settings. Worst is that the method is prone to flickering during even small movements, especially at lower settings, significantly worsening any artifacts present as artifacts become flickery
The Design and Performance Evaluation of a Double-three-phase Inverter - DC-Link Thermal Evaluation and Lifetime Estimation
No full textThis thesis presents the design, implementation, and experimental evaluation of a double–three–phase traction inverter based on silicon carbide (SiC) power modules for heavyduty
electric vehicle applications. The work focuses on achieving high power density and robust thermal performance through co-design of the DC-link capacitor bank and laminated busbar structure. Two alternative DC-link layouts were investigated: Case I, with capacitors mounted above the busbar, and Case II, with capacitors in direct contact with the housing.
A comprehensive methodology combining analytical modeling, MATLAB/Simulink simulations, and laboratory testing was employed. Open-loop SVPWM tests validated inverter
functionality, while thermal performance was assessed under RMS ripple currents of 156 Arms and 300 Arms at 10 kHz under 2 thermal conditions: with and without liquid cooling.
Results show that liquid cooling significantly reduces busbar temperatures (up to 67% in Case I), whereas capacitor hot-spot remain dominated by internal thermal paths, limiting
improvements to 18–21%. Lifetime analysis, based on datasheet models, experimental data, and MATLAB/Simulink model, indicates that capacitor lifetime is highly sensitive to temperature. Under ideal assumptions, the lifetime at 55 ◦C ambient was estimated at 24.8 years, whereas experimentally adjusted scenarios ranged from 8.7 to 13.1 years. Liquid cooling improved lifetime by up to 50% at high ripple currents compared to the worst case, emphasizing the importance of accurate thermal modeling and integrated cooling strategies for next-generation traction inverters. The findings underscore the importance of integrated electro–thermal design for reliability in high-power SiC-based traction inverters. Future work includes closed-loop control implementation, and EMI/EMC characterization
Genetic Algorithm and Simulated Annealing for Flexible Job Shop Scheduling Problem with Time Constraints
No full textIn this work, we investigate the Scheduling for Laboratory Automation in Biology (S-LAB) problem, which arises in time-sensitive laboratory workflows. S-LAB is an extension of the Flexible Job Shop Scheduling Problem (FJSP) with Time Constraints
by Mutual Boundaries (TCMB). We proposed a hybrid Genetic Algorithm- Simulated Annealing (GASA) approach that combines the global exploration capabilities of genetic algorithms with the local refinement strength of simulated annealing. The genetic algorithm component employed a novel triple encoding scheme incorporating Operation Sequence, Machine Selection, and Operation Delay to effectively represent scheduling solutions under strict time constraints. We conducted comprehensive experiments on multiple realistic laboratory protocol datasets to compare the performance of GASA with those of the Branch and Bound (B&B) and SAGAS algorithms. The results demonstrated that GASA achieved optimal solutions in simpler scenarios and near-optimal results in complex cases with significantly reduced computational time compared to B&B. On the most complex dataset (qPCR-RNAseq×5), GASA reduced execution time by more than 96% while incurring only a 10.1% increase in makespan relative to the optimum. The proposed approach provides an effective balance between solution quality and computational efficiency, making it particularly suitable for time-sensitive laboratory automation applications