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Senast publicerade

Integrated Fast Battery Charger Using an Electrically Excited Synchronous Machine-Based Drive System
(2026) Ma, Xinyu
This thesis investigates an integrated off-board fast battery charging system utilizing an Electrically Excited Synchronous Machine (EESM)-based drive topology. The aim is to reuse the existing traction inverter and machine windings as part of a DC/DC boost converter, thereby reducing system cost, volume, and component redundancy. To achieve this goal, three levels of simulation were carried out. First, an excitation-based Finite Element Analysis (FEA) in ANSYS Maxwell was per formed to determine losses and inductances of the EESM under various operating conditions. Second, a system-level co-simulation between Maxwell and ANSYS Simplorer/Simulink was conducted, in which the electromagnetic model of the machine interacted dynamically with the converter and control system. This enabled real time calculation of inductances and losses under variations in both shift angle and rotor position. Finally, a Simulink-based system simulation was carried out to analyze current ripple, torque generation, and efficiency across different frequencies. The results show that phase-shift modulation predominantly affects the current waveform and ripple behavior, while the magnetic coupling and inductance remain almost constant. Increasing the switching frequency reduces stator core losses but has minimal impact on copper losses. Overall, the proposed integrated EESM-based fast charger demonstrates high feasibility and efficiency. It achieves compact system integration, stable electromagnetic performance, and effective control of current ripple and core losses - offering a sustainable approach for future electric vehicle charging architectures.
Our future through a film lens: A speculative exploration of the future’s architecture based on today’s development plans & films
(2025) Lennartsson, Nadja
The future city consists of tightly built high buildings, so the sky is barely visible. People will no longer eat food, but rather take pills, and the traffic will be moved to the air. Everywhere you go, there will be some sort of technology, and society relies on AI. Natural disasters are more common with greater effects and more problems in the utopia arise. The dream people once had has turned into a nightmare. The thesis speculated and explored the future of Gothenburg, which was shown in a final film. Today, architects don’t use the art of storytelling, but rather technical drawings to communicate their ideas, and the images they create are seldom emotionally affecting. On the other hand, films communicate a range of emotions that affect the viewers. In this thesis, storytelling and communicating emotions through hand drawings, aquarelle colouring and film in architecture is explored. By inspiration from films, architects can communicate emotions in architecture and enhance the experience of spaces. They can also take inspiration from films and other media to design buildings or reflect on our society’s architecture. How do film and museums communicate and portray dystopia and anxiety? What will Gothenburg look like every 25th year from today to 2125, based on the architectural developments happening today? Rosenlundsverket is a deteriorating building in Gothenburg with many layers that contribute to a dystopian appearance. By an analysis of five films, this thesis discovers how time, colour, light and shadow can communicate emotions and how those strategies can be applied to buildings. That results in a reconstructed version of the building that metaphorically is our distorted future. The analysis consisted of watching films, choosing particularly emotional scenes, sketching them and placing them on a timeline. They were then analysed to determine how they portrayed and evoked emotions such as anxiety. Based on the analyses and research about utopia, dystopia and filmmaking, perspectives of the Rosenlundsverket’s rooms were painted. The perspectives of the utopian and dystopian rooms were then assembled into a film. The tools learned from the explorations were then used when creating and materialising my personal view of the future Gothenburg city, which was lastly shown in a film.
Introducing the ModularML Framework - A transparent and modular machine learning framework made as a tool for research and education
(2025) Norland, William; Bremer, Måns; Sättemo, Gabriel; Carlsson, Sander; Nilsson, Elias; Carlsson, Tim
This thesis explores the process of creating a highly modular machine learning framework in C++, without performance compromises. The framework can parse ONNX models into dynamic C++ objects, modify the implementation of core computational functions (like GEMM), and use the models to perform inference. The framework reproduces results achieved in peer frameworks like PyTorch and TensorFlow. The usefulness of this framework stems from its pure C++ implementation, with no API layers to compiled modules or other black-box functionality. This makes it highly suitable for use in education and research, where debuggability, modularity, and ease of use are paramount.
Software Quality Evaluation of AI/ML-Based Neuroimaging Tools - A Simulation Study Using BRAPH 2
(2025) Guo, Yuxin
The increasing integration of artificial intelligence (AI) and machine learning (ML) into neuroimaging research has amplified concerns regarding the quality, reproducibility, and trustworthiness of such software systems. Existing evaluation practices often lack standardized and systematic frameworks, limiting their ability to test software quality, especially for AI/ML-based neuroimaging software system. This study addresses this gap by developing and applying a simulation-based framework to evaluate key quality attributes—transparency, functional correctness, and robustness— in AI/ML-based brain imaging analysis pipelines. The framework leverages the Watts–Strogatz network model to generate controlled, simulated brain connectivity datasets, enabling rigorous and repeatable testing. Two analysis pipelines within BRAPH 2 (Brain Analysis using Graph Theory 2), an open-source MATLABbased neuroimaging software for brain network analysis, are tested: a graph theory– based pipeline and a deep learning–based analysis pipeline. Both pipelines are evaluated against simulated datasets, successfully identifying the predefined salient brain regions and maintaining stable performance across repeated runs and random noise situations. Transparency was further enhanced through a graphical user interface and visualization modules that allow inspection of intermediate and final outputs. These results demonstrate that the proposed framework can effectively verify critical quality attributes in a controlled environment. The established methodology provides a robust and accessible foundation for extending validation to real-world neuroimaging datasets and for guiding future st andards in the quality evaluation of AI/ML-based neuroscience software.
Household Resilience to Power Outages
(2026) Kock, Tobias; Quesada, Daniel
The purpose of this study is to investigate the resilience capabilities of house holds in case of power shortages/outages and their ability to adapt to these situations and to find out how long a villa district can maintain power with basic living conditions from an electric power supply point of view. By using Matlab, an artificial test environment was created in order to simulate how much power consumption behavior affects the overall consumption, specifically focusing on the heat pump and the electrical water heater. Using data from monthly generated solar power in Stockholm Sweden and the power storage capabilities of electric vehicles in order to prolong the resilience time of the households in these situations. The results of implementing the combination of solar panels and vehicle to grid technologies has shown that with some changes to daily life power consumption, the residential area can potentially provide sufficient energy locally for up to 65% of the year without grid support, given weather conditions do not stay dark for longer periods of time.