Examensarbeten för masterexamen
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- PostShape Optimization of High Voltage Electrodes(2024) Shema, Junior; Chalmers tekniska högskola / Institutionen för elektroteknik; Serdyuk, Yurijy; Doedens, EspenAbstract Electrostatic screens and electrodes used in high voltage apparatuses and in test setups in high voltage laboratories are essential for proper operation of the equipment and for performing high voltage withstand tests. Electrostatic fields generated on their surfaces must be minimized to prevent parasitic discharges in surrounding air especially under conditions of limited space. To realize this, shape of the electrodes can be optimized in a way that the maximum electric field strength is kept below the critical level corresponding to the initiation of breakdown in air. In the thesis, the optimization methods provided in COMSOL Multiphysics software were examined and shape optimization was employed in the electrostatic problem for minimizing the maximum field strength. Several 2D study cases reflecting typical electrode shapes providing different field enhancement factors were implemented. The effects of various parameters in the optimization algorithms on the shapes of the electrodes and respective reductions of the maximum field were analyzed. The influence of the proximity of the boundaries to the energized electrodes was also investigated and best practices for selecting numerical parameters for the optimization were established. Furthermore, 3D scanning of the real 400 kV high voltage divider equipped with a toroidal electrostatic screen was performed using Scaniverse software installed on iPhone. The obtained scan was cleaned up and imported into COMSOL Multiphysics for conducting electrostatic field calculations. The procedure developed with the 2D study cases was used for shape optimization of the 3D high voltage divider to demonstrate the validity of the method for real scale high voltage devices.
- PostAn equivalent circuit model for swelling in Prismatic Lithium-ion cells(2023) Gingsjö, Erik; Harish , Poshith; Chalmers tekniska högskola / Institutionen för elektroteknik; Thiringer, Torbjörn; Thiringer, TorbjörnAbstract In this thesis, the expansion behavior of a Prismatic Lithium-ion cell is investigated via its external pressure changes. Experiments were done for 0% to 100% state-of-charge for both charge and discharge at various charging rates from 0.05C to 1.2C. An equivalent circuit with a single resistance was used to model the pressure behavior during charging, where the modeled resistance can be understood as a mechanical resistance of the cell casing to expand. It was shown to exhibit a clear trend for charging rate as well as state-of-charge, with values becoming bigger with both increasing charging rate and state-of-charge up to 0.5C. The model was evaluated for 0.3C with the absolute relative error between the modeled and experimental result being around 1% after 5% to 100% state-of-charge. Data from two research articles with similar pressure change experiments were used to validate the model. The first, [1], used charging rates comparable to those used in this thesis, and the other, [2], used charging rates above 1C. For the former, the modeled resistance values showed similar trends as presented here. For the latter however, the resistance values instead decreased with both state-of- charge and increasing charging rate, which was assumed to be due to lithium plating at higher state-of-charge at the higher charging rates as well as due to thermal effects.
- PostEfficient Grid-Less Target Detection Algorithms(2024) Mumtaz, Zubia; Abdullah, Usama; Chalmers tekniska högskola / Institutionen för elektroteknik; Mckelvey, Tomas
- PostFault Tracing Bot in Electric Drive Software Using Machine Learning(2023) Jai Prakash, Soundarya; Gopinath, Hariharan; Chalmers tekniska högskola / Institutionen för elektroteknik; Eriksson, Thomas; Farsi, MohammadThe Electric Drive Software Continuous Deployment (EDCD) team at Volvo Car Corporation is working towards figuring out the automation of the analysis of the build log data obtained as a result of the continuous software integration for Electronic Control Unit (ECUs) using Machine Learning. Machine Learning is expected to be used in building a fault tracing bot, whose main goal is to analyse the provided log data and find the underlying meaning or information through it with minimum or zero human interaction. As this is an ongoing process and the creation of such log data will never really end, this project could make it easier for the analysis of big projects in getting instant data. At first, we are working on the data cleaning and the preprocessing of the big unstructured log data, followed by the labeling of the data by the clustering process. Lastly, the machine learning algorithm is used to predict the classification of the newly fed data. Many different machine learning algorithms have been implied to compare and get the best accuracy predicting algorithm among them.
- PostHuman detection and pose estimation using ceiling mounted cameras(2023) Ravi, Harish; Madhavan, Harish; Chalmers tekniska högskola / Institutionen för elektroteknik; Åkesson, Knut