Chalmers Open Digital Repository

Välkommen till Chalmers öppna digitala arkiv!

Här hittar du:

Studentarbeten utgivna på lärosätet, såväl kandidatarbeten som examensarbeten på grund- och masternivå
Digitala specialsamlingar, som t ex Chalmers modellkammare
Utvalda projektrapporter

Forskningspublikationer, rapporter och avhandlingar hittar du i research.chalmers.se

Enheter i Chalmers ODR

Välj en enhet för att se alla samlingar.

Visar 1 - 2 av 2

Senast publicerade

Virtual Multi-Cylinder Engine. Experimental and simulation data "in loop" towards a "virtual multi-cylinder engine" for pre-mixed hydrogen combustion
(2026) Karattuthodi, Mohammad Rusail; Repinz, Theodore Pierce
This project introduces an integrated methodology and tool set that couples experimental data from a single-cylinder engine (SCE) with a 0D/1D Three-Pressure- Analysis (TPA) model and a multi-cylinder engine (MCE) simulation in GT-Suite. The system developed utilizes measured data from a SCE and uses this to compute an apparent burn rate in a TPA model. This apparent burn rate, along with other operational data is extracted from the SCE and imposed onto a 0D/1D MCE simulation environment where the feedback is a set of boundary conditions corresponding to the inlet and exhaust manifold of the MCE. These boundary conditions are then used to adjust actuators on the SCE - enabling the continuation of a closed loop system until boundary condition convergence criteria have been met. This concept addressed the two main shortcomings of SCE testing and 0D/1D simulation, respectively. In SCE testing, the entire engine system is decoupled, and each subsystem can be controlled independently for a specific load point. This implies that only steady state operation is possible, while the data that is collected is high fidelity measurement directly from the engine. A 0D/1D MCE simulation can model the system-level engine response, however in the context of premixed hydrogen engines, the combustion models are not mature enough to accurately represent in-cylinder combustion events. The integration of a TPA-derived burn rate into the 0D/1D MCE model allowed the gap to be bridged between simplified simulation and experimental reality. A symbiotic looped workflow was established, and this paper shows that there exists potential to optimize the design quality and time of high-performance MCE concepts for future powertrain development. A data sampling and averaging study was conducted to understand how the output of the simulation components reacted to cyclic variations. The study showed that key performance parameters are not significantly affected by the sample size when compared to a 200-cycle average; however are more sensitive to the sampling window - suggesting a sensitivity to cyclic variations. A minimum of 50 averaged cycles is required for accurate system results. Furthermore, the output of an initial loop iteration of the ’virtual MCE’ simulation tool is compared to a similar experimental MCE as a means to understand the system’s initial conditions and validate the concept. This investigation was inconclusive, and hardware discrepancies were found to be evident in the test setups. The continuation of loop iterations was halted by the lack of access to a dedicated SCE test bed. The initial iteration found absolute inlet manifold boundary condition errors of 7.14% for pressure, and 82.4% for temperature. While the absolute exhaust manifold back pressure error was found to be 3.98%. The overarching research question was found to be inconclusive. However, this report sets the foundation for future work and discusses how further research can be conducted to aid in realizing its successful outcome. This thesis offers a set of recommendations for continued progression in realizing this as an industry tool. The thesis was therefore written in a manner to aid in future work and can be used as reference for configuring simulation models, addressing errors in future studies and is useful reference for relevant theory.
Dynamic Line Rating Based on Phasor Measurements: An Uncertainty Analysis
(2026) Olsson-Lalor, Karl
Rising electricity demand from energy-intensive technologies has heightened the need for reliable power transmission. Conventional static line ratings, based on conservative seasonal assumptions, often underutilize available capacity. Dynamic Line Rating (DLR) overcomes this by estimating ampacity from real-time conditions, but most implementations rely on extensive weather monitoring that limits scalability. Phasor-based DLR offers a scalable alternative by using synchronized voltage and current measurements to infer conductor temperature and power losses, enabling higher utilization without additional infrastructure. This thesis investigates the theoretical performance of phasor-based DLR for short 130 kV overhead lines, with a focus on error propagation. Statistical inference methods are used to estimate conductor temperature from synthetic measurements while accounting for sensor accuracy. The impact of multiple measurements on estimating both static and dynamic estimation line parameters is examined. The results show that single-measurement temperature estimates are fundamentally limited by amplified uncertainty in power loss calculations, requiring measurement accuracy improvements of at least two orders of magnitude over current standards. Multiple measurements improve accuracy and precision but require 103 -105 samples, depending on prior assumptions and sensor quality. Dynamic methods perform well under most conditions, achieving RMSEs of 0.8-2.6 °C for high-accuracy measurements, but abrupt current changes degrade accuracy while maintaining high model confidence, indicating model over-confidence. These findings suggest that phasor-based DLR can reach accuracy levels comparable to weather-based approaches under ideal conditions, but practical deployment is constrained by measurement uncertainty, inference assumptions, and fundamental information limits. Further development of phasor-based DLR will require more robust uncertainty modelling, and stronger integration of physical priors in both static and dynamic estimation frameworks.
Elektrifiering av regionala lastbilstransporter Drivkrafter, hinder och möjligheter
(2026) Hauge, Thias
Klimatförändringar beskrivs ofta som en av vår tids största globala utmaningar. För att skapa en grönare framtid behöver vi anpassa och förändra de industrier som skadar vår planet. För att bekämpa klimatförändringarna har Europeiska unionen introducerat paketet ”Fit for 55”, med målet att minska nettoutsläppen med minst 55% till år 2030. Transportsektorn är en av de största bovarna bakom den globala uppvärmningen och står för en stor andel av växthusgasutsläppen. Detta innebär att sättet vi transporterar varor över världen på måste förändras på flera sätt. Genom intressentanalys och kvalitativa intervjuer syftar denna studie till att ge en bild av hur olika intressenter är beroende av varandra. Studien fokuserar på problemen, för- och nackdelarna med elektrifiering av regionala tunga lastbilstransporter. Höga investeringskostnader, brist på laddinfrastruktur och osäkerhet kring framtiden leder till en ovilja att investera i ellastbilar. Resultaten visar att även om intresset för elektrifiering av lastbilar är stort och tekniken har utvecklats långt, saknas i dagsläget incitament för de enskilda aktörerna att investera.
Optimized Internal Logistics for Non-Standard Parts
(2026) Arkavazi, Mohamed; Kitevski, Filip
This report focuses on optimizing internal logistics for non-standard parts in Volvo Trucks’ production plant in Tuve. More specifically, the customer adapted (CA) materials are emphasized. The thesis aims to identify the issues in the current logistics flow and propose solutions to improve material availability, reduce lead times, and support production goals. Furthermore, the research covers the challenges induced by having a logistics flow with low-volume and customer specific components. By analyzing the root causes of delays, errors, and poor coordination, the study identifies areas for improvement, such as better information flow, system support, and quality control measures. Key findings suggest that addressing underlying issues like unclear material specifications, manual handling, and weak communication between departments can significantly improve the robustness of the CA material flow, leading to improved performance and better customer satisfaction. The proposed solutions include implementing real-time scanning systems, enhancing buffer management, and improving coordination across departments. This report shows the importance of adapting logistics systems to handle a high variability and ensure on-time deliveries of non-standard parts in a complex manufacturing environment.
Analyzing Order-to-Cash Using Process Mining A Case Study in Collaboration with Paulig
(2026) Adolfsson, Jens; Saleh, Dilan
Organizations increasingly rely on digital data to understand and improve their business processes. Process Mining is a data-driven approach that uses event logs from information systems to visualize actual process behavior and identify inefficiencies. This thesis investigates how Process Mining can be applied in practice to analyze the Order-to-Cash process, with a particular focus on the use of pre-defined reference process models and backward-looking analytical techniques. The study is conducted as a case study in collaboration with Paulig, using Infor’s Process Mining solution integrated with the ERP system M3. Through a combination of Process Mining analysis, interviews, workshops and shadowing sessions, the thesis evaluates how well a pre-defined industry-specific process model reflects an organization’s actual Order-to-Cash process and how inefficiencies and bottlenecks can be identified. The reference process model proved to be a strong baseline for understanding the overall process structure, while the analysis revealed bottlenecks related to master data issues that cause unnecessary manual interventions and longer cycle times. The results demonstrate that Process Mining can support improvements in both administrative processes and physical logistics flows by revealing systematic issues that are difficult to detect through traditional qualitative methods alone. The study also highlights the importance of combining Process Mining insights with domain knowledge and stakeholder involvement to correctly interpret results.