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Voltage support in open pit mining power systems using electric drill rigs

(2025) Gomez Arguello, Juan Pablo; Pardo Galvis, Jaime Andres

The electrification of mining operations presents significant challenges in power quality, particularly in remote open-pit mines where limited grid connectivity results in reduced short-circuit capacity and increased susceptibility to voltage instability. High-power induction motor startups in drilling equipment frequently generate significant voltage sags, that compromise operational continuity and compliance with power quality standards. This thesis examines different configurations of the motor and drive system for electric drilling units and their impact on voltage profiles in mining grids. The study aims to determine how electric drillers can provide voltage support to improve grid voltage stability. A comprehensive electrical distribution grid model was developed in MATLAB/Simulink, incorporating typical mining environment loads. Critical scenarios were identified through parametric sweeps across different grid strengths to assess voltage sag depth, duration, and reactive power demand under multiple operational scenarios. Simulation results demonstrate that Active Front End (AFE) drives significantly reduce the severity of voltage sag, improve steady-state voltage profiles, and maintain system stability under weak grid conditions. When AFE control is modified to provide dynamic reactive power compensation, additional voltage support is achieved, further mitigating voltage sags and enabling stable operation under even weaker grid conditions while maintaining voltage performance comparable to full AFE implementation. A key contribution of this work is to demonstrate that a single AFE-equipped driller with compensation capability can effectively support multiple Direct-On-Line (DOL) drillers during simultaneous operation, keeping Point-of-Common Coupling (PCC) voltages within acceptable limits without requiring full fleet AFE conversion. This selective deployment approach represents a technically robust and operationally viable solution to enhance power quality and resilience in mining electrical systems.

Resurshantering och arbetsplanering inom Barnintensivvården

(2025) Borg, August; Nyström, Hugo

Syftet med denna studie är att undersöka organisatoriska utmaningar och förbättringsmöjligheter på intensivvårdsavdelning barn på Sahlgrenska Universitetssjukhuset. Avdelningen har komplexa bemanningsbehov på grund av varierande vårdnivåer och ett patientflöde som består av både planerade operationer och akuta inläggningar. Schemaläggningen är i dagsläget till stor del manuell och påverkas av begränsad digitalisering, bristande standardisering samt ett fragmenterat informationsflöde. Genom en kombination av observationer, intervjuer och dataanalys har flera problemområden identifierats: ineffektiv schemaläggning, brist på standardiserade rutiner, outnyttjade data om förväntad vårdtid och begränsad användning av vårdtyngd i resursplanering. Studien föreslår ett antal förbättringsåtgärder, såsom AI-baserad schemaplanering, standardisering enligt Lean-principer, visuell styrning för ökad informationsöversikt och införande av Fast track-rutiner för förutsägbara patientgrupper. Syftet med dessa förslag är att minska administrativ belastning, effektivisera resursanvändningen, förbättra både arbetsmiljö och vårdkvalitet samt förbättra patientflödet. Resultaten visar på vikten av att utveckla avdelningen mot en lärande organisation där både tyst och explicit kunskap tas tillvara i det kontinuerliga förbättringsarbetet TEKNIKENS EKONOMI OCH ORGANISATION Avdelning för Supply and Operations Management CHALMERS TEKNISKA HÖGSKOLA Göteborg, Sverige 2025 Resurshantering och arbetsplanering inom Barnintensivvården August Borg Hugo Nyström © August Borg, 2025 © Hugo Nyström, 2025 Teknikens ekonomi och organisation Chalmers tekniska högskola 412 96 Göteborg Sverige Telefon + 46 (0)31-772 1000 Göteborg, Sverige 2025 Göteborg, Sverige 2025 Resurshantering och arbetsplanering inom Barnintensivvården August Borg Hugo Nyström Institutionen för Teknikens ekonomi och organisation Chalmers tekniska högskola Syftet med denna studie är att undersöka organisatoriska utmaningar och förbättringsmöjligheter på intensivvårdsavdelning barn på Sahlgrenska Universitetssjukhuset. Avdelningen har komplexa bemanningsbehov på grund av varierande vårdnivåer och ett patientflöde som består av både planerade operationer och akuta inläggningar. Schemaläggningen är i dagsläget till stor del manuell och påverkas av begränsad digitalisering, bristande standardisering samt ett fragmenterat informationsflöde. Genom en kombination av observationer, intervjuer och dataanalys har flera problemområden identifierats: ineffektiv schemaläggning, brist på standardiserade rutiner, outnyttjade data om förväntad vårdtid och begränsad användning av vårdtyngd i resursplanering. Studien föreslår ett antal förbättringsåtgärder, såsom AI-baserad schemaplanering, standardisering enligt Lean-principer, visuell styrning för ökad informationsöversikt och införande av Fast track-rutiner för förutsägbara patientgrupper. Syftet med dessa förslag är att minska administrativ belastning, effektivisera resursanvändningen, förbättra både arbetsmiljö och vårdkvalitet samt förbättra patientflödet. Resultaten visar på vikten av att utveckla avdelningen mot en lärande organisation där både tyst och explicit kunskap tas tillvara i det kontinuerliga förbättringsarbetet.

Building a Motor Test Bench Prototype

(2025) Andersson, Elin; Nilsson, Felix

In modern production machines, numerous electrical motors are used, and failures are common. To reduce downtime and improve reliability, anomaly detection by sensors can be used. The anomaly detection algorithms can discover abnormal patterns in the motor’s performance and thus, give an early indication when failure is underway. An issue with this, however, is that the subject is complicated to study, as real-life production machines are difficult to test with different failure scenarios. The purpose of this project was to set up a test bench with two DC motors and sensors that could be used for studying anomaly detection algorithms. A test bench was built with an MDF board as the base. On the board, two 3D-printed motor holders for the DC motors were attached along with two axis holders to mount an axis between the motors. An Arduino Mega was connected to control the motors and adjust the speed with a potentiometer. Additionally, a temperature sensor and a 3-axis accelerometer sensor were applied to the motor and connected to the Arduino Mega. In conclusion, a prototype of a test bench for further development was created.

Shaping Rewards with Temporal Information to Guide Reinforcement Learning

(2025) Lundgren, Linus

Reinforcement learning (RL) methods that apply pretrained Vision-Language Models (VLMs) to compute rewards typically use a single observation of the environment to do so. This is problematic because any information emerging from the sequential nature of RL, i.e. temporal information, is therefore disregarded. This thesis explored how temporal information can be incorporated into the VLM reward computation, by first distinguishing between fixed and adaptive temporal information. In fixed temporal information, additional inputs are provided to describe the environment’s progression through time, but these inputs remain unchanging throughout each episode. In contrast, adaptive temporal methods take additional inputs that can change as the episode progresses. Positional and directional rewards were defined to take advantage of fixed and adaptive temporal information respectively, along with new supervised finetuning methods for the directional reward functions. Evaluated with a sample efficiency metric over 6 robotic manipulation tasks, the best new positional rewards performed 18.4% better than previous methods, while directional rewards performed 23.0% better. Combining positional and directional rewards showed a 25.4% improvement, which was the best performance achieved by any method in this thesis.

Modeling and Evaluation of the Olshammar engine. A simulation based approach of a five-stroke turbocharged engine using Siemens Amesim.

(2025) Hansson, Wilhelm; Åberg, Fredrik

Internal combustion engines (ICEs) have been used since the 19th century and remain relevant as of 2025, although the field faces major challenges. The future of ICEs will heavily rely on new inventions and technological advancements. This thesis addresses one such invention: the Olshammar engine, a five-stroke engine concept featuring a lowpressure exhaust cylinder. The purpose of this study is to examine how the Olshammar engine performs in comparison to a conventional four-stroke engine. There are several software tools available for modeling and simulating ICEs, and in this study, Siemens Amesim was used. Initially, a two-cylinder petrol baseline engine was modeled and optimized, providing the reference for modeling the Olshammar engine. The results show that the Olshammar engine reduces brake-specific fuel consumption (BSFC) across the operating range of 2000–5000 rpm, with the largest improvement at 3000 rpm, where BSFC is reduced by approximately 4 %. This corresponds to a fuel conversion efficiency of ηf = 35.2% compared to ηf = 33.7% for the baseline engine. Furthermore, the simulations indicate that the improvement in BSFC can be attributed to the power contribution from the exhaust cylinder, resulting from the recovery of expansion work. Additional assessment of key parameters contributing to performance improvements suggests that tuning the exhaust cylinder offset relative to the combustion cylinders, as well as adjusting the bore-to-stroke ratio, can further enhance overall performance. Siemens Amesim proved to be a well-suited tool for ICE modeling, to the extent that it could replace GTPower in the ICE course at Chalmers in the future. Finally, the findings of this study demonstrate how the design and optimization of the Olshammar engine contribute to improved fuel efficiency compared to conventional four-stroke designs.