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Physics-Informed Neural Networks for Vehicle Lateral Dynamics Modeling
No full textAccurate estimation of vehicle lateral dynamics is important for advanced driver
assistance systems (ADAS) and autonomous driving applications. This thesis proposes
a Physics-informed Neural Network (PINN) framework that combines fundamental
vehicle dynamics, based on simplified single-track models and Pacejka tire
formulations, with data-driven recurrent neural networks that incorporate attention
mechanisms. By embedding physical constraints within the learning process, the hybrid
model aims to improve interpretability, robustness, and real-time performance
without relying on additional sensor inputs. Evaluations using high-fidelity simulations
and real-world datasets suggest that the model can estimate latent states,
such as lateral velocity, with promising accuracy. While the approach generalizes
well across a variety of simulated driving scenarios, it faces challenges in maintaining
comparable performance on real-world data mainly due to modeling uncertainties
and measurement noise. These limitations highlight the need for further investigation
into robustness and domain adaptation techniques. Future work will explore
on-board deployment, adaptation to individual vehicle characteristics, and the integration
of more detailed physical models. These developments could enhance the
model’s reliability and utility in practical applications, contributing to improved
vehicle safety and operational efficiency
Comparative Analysis of Lithium-Ion Batteries and Supercapacitors for Smart Grid Energy Storage
No full textAbstract
This thesis presents a comparative analysis of lithium-ion batteries and supercapacitors as energy storage technologies in smart grids. The analysis is based on five parameters: energy density, power density, life cycle, cost and environmental impact. The results reveal that lithium-ion batteries are more appropriate for long-term storage in smart grids. This is due to their exceptionally high energy density and benefits connected to costs. By comparison, supercapacitors offer higher power density, life cycle and lower environmental impact. Making them suitable for smart grid processes like high-frequency peak shaving. A potential hybrid solution that consists of both lithium-ion batteries and supercapacitors were also explored. These hybrid solutions have shown to address a number of the individual concerns faced by both technologies. However, there needs to be more development focusing on the hybrid solution within smart grid infrastructures. While limited by a lack of real-world studies, this thesis offers a valuable framework that could be used in future studies and practical applications in smart grids
Circular Economy: Design for Recycling and Data Exchange for Plastic Packaging
No full textCircular economy is becoming a key way of addressing use of limited resources and environmental impact, but currently the use of plastic packaging is far from circular.
One of the challenges that hinder a circular flow of plastic for packaging is that the packaging is not always designed to work with existing recycling infrastructure.
Together with a literature review of recent scientific findings and policy documents, interviews were used to fulfil the aim of analysing the state-of-the-art and current data exchange practices
of the plastic packaging value chain. Semi-structured interviews were conducted with 19 companies that produce and sell products with plastic packaging (product producers), and
10 complementary interviews were conducted to cover a larger part of the value chain. With the recently introduced EU Packaging and Packaging Waste Regulation (PPWR), the industry has an increasing focus in
Design for Recycling (DfR). The main tool that product producers use for DfR today is DfR guidelines, but the study show that these can diverge in their assessments of products. The industry currently only have a
small focus on traceability, but the PPWR will bring more focus to this as requirements for ensuring recycling at scale comes into affect. DfR and differentiated fees is a start but increased data exchange in the industry
has the potential to improve circularity to a new level
Airship diffusion in Swedish agriculture Sociotechnical barriers and opportunities
No full textAgriculture is under increasing pressure to adapt to climate change while reducing
its environmental impact. One of the challenges is to maintain or increase food production
without intensifying soil degradation, emissions, or fossil dependency. This
thesis applies the Technological Innovation Systems (TIS) framework in combination
with scenario analysis to explore the potential for implementing lighter-than-air
technology in Swedish agriculture. Semi-structured interviews were complemented
by literature research and a bibliometric analysis. The study examines the current
state of the Swedish agricultural system and the emerging airship market by identifying
possible configurations for market integration. Findings show that airships
have potential applications such as lifting heavy objects, transporting, spraying pesticides,
and monitoring. Key drivers and barriers were identified, focusing on the
capabilities and willingness of various societal actors to adopt lighter-than-air technology
in agriculture. Diffusion is currently constrained by financial and human
resource mobilisation, critical components, regulations and limited legitimation and
collaborations. Four future scenarios were developed, covering different ownership
models and degrees of functionality of airships. The thesis discusses policy measures
that could facilitate the diffusion of LTA technology within the Swedish agricultural
sector
Impact of ionic doping on the normal and superconducting properties of YBCO thin films and nanowires
No full textDespite almost 40 years of intense research, high-temperature superconductivity in
cuprates remains one of the most intriguing unsolved problems in condensed matter
physics. The phase diagram of these materials, which describes how their properties
vary with temperature and doping, is extremely complex: even the normal state
above the superconducting critical temperature is characterized by multiple regions
and symmetry-breaking orders associated with charge, magnetic, lattice, and orbital
excitations. The interplay and competition among these orders, which may be at the
origin of the pairing mechanism, are still far from being fully understood.
In this thesis, to shed light on these phenomena and gain a clearer picture of normalstate
orders and of their competition with superconductivity, we focus on YBa2Cu3O7−δ
(YBCO), where doping is controlled by oxygen content, and we introduce a small fraction
of Zn atoms substituting Cu. This chemical substitution modifies the CuO2 planes,
which constitute the core of both the superconducting and normal-state properties of
this family of materials. In particular, I optimized the growth of Zn-doped YBCO
thin films on STO substrates via pulsed laser deposition. The partial substitution of
Cu with non-magnetic Zn atoms effectively suppresses superconductivity, revealing the
underlying normal-state properties hidden beneath the superconducting dome.
To explore different regions of the phase diagram and understand the effect of
Zn, films were grown across a range of oxygen dopings, from underdoped to strongly
overdoped regimes, and for two different Zn concentrations. The structure, morphology,
and transport properties of these films were characterized: these measurements allowed
me to precisely determine the doping and build the complete phase diagrams for both
Zn levels. Our results reveal a clear suppression of Tc, an expansion of the insulating
region, and a relative invariance of the pseudogap temperature. Finally, the films were
patterned into Hall bars and nanowires to investigate transport properties via currentvoltage
characterization and transport measurements down to the nanoscale, providing
information about material homogeneity at the nanodomain level.
This work contributes to the broader effort of disentangling the mechanisms behind
unconventional superconductivity by accessing the normal state through chemical doping.
Moreover, it establishes a new material platform that paves the way for future
investigations in both transport and spectroscopic experiments