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Now showing 1 - 2 of 2

Recent Submissions

Vibration Condition Monitoring of an Electric Drive Unit
(2026) Nalawade, Aditya
The increasing competition and rapid development in electromobility are driving accelerated product development, higher drivetrain performance, and consequently greater mechanical stress on components. Ensuring reliability and safety therefore requires effective condition monitoring during testing. Vibration-based condition monitoring is widely used for this purpose; however, the effectiveness of such monitoring strongly depends on the measurement setup, particularly sensor placement. In practice, sensor positioning is often performed without a structured approach, which could lead to inconsistent and potentially unreliable results. This study focuses on developing a standardized procedure for vibration measurement setup during drivetrain testing. Multiple real-time measurements were conducted and analysed using various evaluation metrics to assess the influence of sensor placement and operating conditions. The results demonstrate that sensor placement must be carefully optimised for different machine configurations. In addition, the classification of load cases requires refinement to support a consistent and standardized testing methodology. The proposed approach contributes to improved reliability and comparability of condition monitoring results.
Design and Optimization of a Wideband Feed Antenna for the Onsala 20-m Telescope
(2026) Valsan, Abhijith
Wideband feed antennas are an essential part of reflector antenna systems, as they affect the radiation characteristics and, in turn, the reflector performance, which is the focus of the present thesis. A wideband quad-ridge horn feed was designed and optimized for the Onsala Cassegrain reflector system. The main objective of this work was to achieve a narrow radiation beam that satisfies the required edge taper while providing acceptable impedance matching and antenna efficiency. The antenna geometry is determined and studied by means of electromagnetic simulation. The ridge profile, horn geometry, and backshort, as well as antenna dimensions and radiation characteristics, were studied in detail. The 3D spline-based approach was used to design the ridge profile, providing flexibility in controlling the antenna geometry. Several geometric configurations and scaling factors were investigated to study their influence on radiation beamwidth and efficiency. The scaled design of 1.8 has shown approximately a 12-degree beam width at -12 dB point at 4 GHz and has retained a narrow beam with the increase of frequency and better antenna efficiency. The efficiency of the antenna has been assessed through simulated reflection coefficient, radiation patterns, spillover efficiency, illumination efficiency and combined aperture efficiency as measuring parameters. Although the target beamwidth could be achieved or closely approached, the overall efficiency remained below the target value of 60%. The results indicate that modifying the geometry and scaling of a wideband quad ridge horn provides significant control over its radiation pattern. Nevertheless, further optimization and validation are required to improve the overall efficiency while maintaining the required beam characteristics.
Assessing Sustainability Strategic Alignment in Automotive Product Development Decision-Making
(2026) Premmert, Lea
The integration of environmental considerations into product development has been discussed in literature with particular attention to approaches related to Life Cycle Assessment (LCA). While these approaches aim to inform more sustainable products and business, a particular gap is the alignment between corporate sustainability strategies and operational decision-making. This study investigates how sustainability goals are operationalized in practice by assessing the strategic alignment between corporate targets and decision-maker priorities, exemplified by a Volvo Cars case study. This study applies the Analytic Network Process (ANP), a Multi-Criteria Decision Analysis (MCDA) method, to two decision cases involving polymeric automotive parts. Six criteria were evaluated: cradle-to-gate carbon footprint, end-of-life circularity, recycled content, biobased content, weight and cost. Data from 79 decision-makers in product development were used to quantify priorities, enabling assessment of strategic alignment. These findings were complemented with interviews with company sustainability experts and participating decision-makers to enable triangulation between strategic ambitions and operational practices, complemented with literature to assess the integration efforts in the case company and synthesize complementary improvement actions. The findings indicated several instances of internal and external misalignment, and misalignment between decision maker preferences and sustainability targets. The integration of environmental considerations into product development decision making was found to be relatively poor, with environmental aspects generally not viewed as an integral part of product development activities. Supplementary interviews and observations revealed that integration efforts from central sustainability functions addressed many of the prescriptions in literature, subsequently addressing much of the identified misalignment. However, a need was identified for top management support and allocation of resources, as well as the creation of dedicated collaboration spaces, to complement central sustainability efforts and to effectively motivate product development staff taking ownership of environmental considerations This study is a relevant example of current challenges present in environmental work and green product development, with a particular focus in the automotive industry. It also demonstrates how a quantitative method like ANP can be combined with qualitative analysis and an extended scope of respondents to assess misalignment between sustainability strategy and decision-making practices in complex industrial contexts.
Edge-Optimized Deep Learning for Real-Time State of Health Estimation of Lithium-Ion Batteries in Embedded Systems
(2026) Hanumaraddi, Krishna; Fu, Xuqi
Accurate State of Health (SoH) estimation is critical for lithium-ion battery management. While deep learning models like Long Short-Term Memory (LSTM) networks offer superior predictive capabilities, their computational complexity and memory footprints prohibit direct deployment on resource-constrained Battery Management System (BMS) microcontrollers. This thesis addresses this bottleneck by proposing an edge-optimized deep learning framework for real-time SoH estimation. Utilizing features extracted from early-cycle operational data (the first 10 cycles), we develop a Physics-Informed Long Short-Term Memory (PINN-LSTM) architecture as the fullprecision teacher model. To achieve embedded compatibility, we introduce a model compression pipeline integrating Physics-Informed Neural Network Knowledge Distillation (PINN-KD), structural pruning, and W8A32 dynamic quantization, where the knowledge of the PINN-LSTM teacher is transferred to a lightweight LSTM student model. The optimization workflow compiles the models from PyTorch into bare-metal C applications using the Apache TVM stack and Relax Virtual Machine, enabling static memory allocation and Flash-aligned weight storage. Software-inthe- Loop (SIL) on Infineon TC4D7 and Processor-in-the-Loop (PIL) evaluations on NXP MCXN947 microcontrollers validate the system’s real-time performance and concurrent asynchronous data handling. Results demonstrate a massive memory reduction, with Flash storage shrinking from 127.13 KB (full-precision PINN-LSTM teacher) to merely 1.25 KB (quantized LSTM student). Crucially, the W8A32 quantized student model maintains exceptional mathematical fidelity, exhibiting a Mean Absolute Error (MAE) of 3.32×10−8 against the corresponding full-precision LSTM student model. Finally, the study identifies gradient dominance as a fundamental challenge in developing chemistry-agnostic models across mixed LFP, NMC, and NCA datasets, highlighting avenues for future domain-adaptation research.
Multi-functional Microneedle Patches for Chronic Wound Infections
(2026) Eriksson, Caroline; Ramér, Elin
Bacterial infections can persist as biofilms in wounds, exacerbating infection and potentially causing it to become chronic. Biofilms are difficult to treat because of their robust protective structure that limits antibiotic delivery, while their microenvironment can promotes the spread of antibiotic resistance. Because antibiotics often fail to eradicate established biofilms, removal typically requires surgical debridement, which is costly, time-consuming, and invasive. New treatment strategies are therefore needed to effectively disrupt established biofilms, kill planktonic bacteria, and enable minimally invasive drug delivery. Microneedle patches (MNs) are promising drug delivery systems due to their biocompatibility, tunable mechanical properties, and swelling capacity. Loaded with therapeutics, MNs combine needle penetration with swelling to release of therapeutics deeper into infected tissue. This study assesses the therapeutic effect of two MN designs, NaBIL@MN and MV-ZnO@DMN, on methicillin-resistant Staphylococcus aureus (MRSA) biofilms. Both MNs were successfully fabricated with therapeutic incorporation, sufficient thermal stability and mechanical strength for skin penetration. The MNs showed two distinct hydration behaviours. NaBIL@MN demonstrated swelling behaviour with potential for controlled drug release, while MV-ZnO@DMN rapidly dissolved, likely resulting in burst release. Biological testing demonstrated antibiofilm activity of membrane vesicles (MVs) against MRSA both free form and loaded into the DMN system. ZnO nanoparticles (ZnO NPs) exhibited a minimum inhibitory concentration (MIC) of 100 μg/ml against MRSA, but were cytotoxic at concentrations above 25 μg/ml. Consequently, although MV-ZnO@DMN showed antibiofilm activity, its antimicrobial effect was insufficient to kill bacteria remaining in the biofilm. NaBIL@MN prevented biofilm formation and showed potential dispersive activity against mature biofilms. However, despite significant antimicrobial activity against planktonic MRSA, it did not significantly reduce the viability or growth of bacteria remaining in the biofilm after dispersion. Furthermore, although NaBIL@MN showed clinically acceptable cell viability above 70 %, compromised cell morphology and cell number, together with hemolytic activity exceeding clinical standards, suggest limited biocompatibility. Nevertheless, these findings demonstrate the potential of NaBIL@MN and MV-ZnO@DMN as drug delivery systems against MRSA biofilms while highlighting the challenge of balancing antimicrobial efficacy and cytocompatibility.