Degree project

Explore the Future of Autonomous Flight: Drone Swarm Coordination with Real-World Experiments (master's thesis)

Description

In this project, we consider a team of drones working together like a flock of birds—searching for missing people, monitoring forests, inspecting bridges, or surveying farmland—all without human intervention. In particular, we dive into the world of drone swarms, where multiple autonomous drones collaborate to complete complex tasks in dynamic and unpredictable environments. You will explore how to make these swarms intelligent, adaptable, and efficient by contributing to one or more of the following areas, depending on your background: designing decentralized control or signal processing algorithms, developing inter-agent communication or sensing protocols, and implementing robust coordination strategies.

Unlike purely theoretical work, this project emphasizes hands-on experimentation with real drones, giving you the opportunity to test your ideas in both indoor and outdoor settings. You'll work with cutting-edge platforms and tools such as ROS, PX4, and motion capture systems to bring your algorithms to life. The goal is to enable collaborative behaviors like formation flying, area coverage, and target tracking, while ensuring each drone can safely avoid collisions with obstacles and other drones.

Through this project, you'll gain valuable experience at the intersection of robotics, AI, control theory, and embedded systems, preparing you for careers in research, industry, or entrepreneurship. If you're passionate about autonomous systems and want to contribute to technologies that can make a real-world impact, this is your chance to be part of the future of intelligent robotics.

Background

We will offer multiple thesis focusing on different aspects of drone swarms. Background information about a few examples of aspects we would like to focus can be found here:

- Darbari et al, “Dynamic Motion Planning for Aerial Surveillance on a Fixed-Wing UAV“, IEEE International Conference on Unmanned Aircraft Systems, 2017.

- Lamberti et al, “A Sim-to-Real Deep Learning-Based Framework for Autonomous Nano-Drone Racing”, IEEE Robotics and Automation Letters, 2024.

- Loianno et al, “Estimation, Control, and Planning for Aggressive Flight With a Small Quadrotor With a Single Camera and IMU”, IEEE Robotics and Automation Letters, 2017.

Prerequisites

Applicants should demonstrate a strong academic and/or professional background, with solid expertise in at least one of the following areas: Automatic control, Signal processing, Programming (Matlab/Python/C++), Embedded systems (ROS), Experience with UAV platforms, Machine Learning, Communication systems

Supervisors

Christos Verginis –email: christos.verginis@angstrom.uu.se

Ayca Özcelikkale – email : ayca.ozcelikkale@angstrom.uu.se

Roland Hostettler – email: roland.hostettler@angstrom.uu.se

Please submit your interest by sending to the emails above: 1) a short letter describing yourself, why you are applying for the position, and relevant experience, 2) your CV, 3) a certificate of registration and a transcript of records.

Thesis project in Robot motion planning (30 credits)

Description

This project considers the motion-planning problem of single- or multi-robot systems. Motion planning is one of the most important problems in robotic systems. It consists of navigating a robot (or a multi-robot) safely from a start to a goal position while avoiding collisions with obstacles (and/or between each other in a multi-robot team). Significant challenges consist of potential uncertainty in the dynamic motion model of the robot(s) and local minima configurations – where conflicting objectives of navigating to the goal and avoiding obstacles renders the robot immobile. Furthermore, when multi-robot systems are concerned, it is of high importance to develop decentralized control and decision-making algorithms in order to guarantee scalability to large robot teams. Decentralized operation implies that each robot determines its own control action by communicating with the rest of the robots, without relying on a central control unit. This could further impose connectivity-maintenance specifications.

This project will investigate safety-constrained planning and control algorithms for single- or multi-robot systems. The central concept lies in the integration of planning methods with adaptive-control techniques that accommodate dynamic uncertainty. While target navigation will be the primary objective, other tasks can be also considered (such as establishing a geometric formation for multiple robots). Extensive studies using computer simulations and possibly robot hardware are planned.

Related literature

• Pan et al, “Robust and safe task-driven planning and navigation for heterogeneous multi-robot teams with uncertain dynamics”, https://www.kavrakilab.org/publications/pan2024-iros.pdf
• Verginis et al, “Adaptive robot navigation with collision avoidance subject to 2nd-order dynamics“, https://arxiv.org/pdf/2005.12599

Prerequisites

Good knowledge of automatic control, mathematics (differential equations), and programming using Matlab/Python/C++. Motion planning methods will be useful.

Supervisor and contact

Contact and apply to supervisor Christos Verginis by e-mail: christos.verginis@angstrom.uu.se

Your application should contain an official transcript of study records with information on your programme, courses and grades.

Thesis project in Robust control of robotic manipulators (30 credits)

Description

The rapid advancement of technology has led to the increasing development and use of intelligent robotic systems in industry but also everyday life. A major component of such systems is the ability to design control algorithms that make them successfully perform a task such as navigate to a point or track a time-varying trajectory. Nevertheless, successful control of robotic systems often entails difficulties due to a large variety of reasons. In particular, robots often evolve subject to uncertain nonlinear dynamics, such as the case of robotic manipulators. The complex articulated structure of such robots creates many nonlinearities in the system dynamics. Further, many parameters (geometric or dynamic) that cannot accurately identified could lead to large degrees of uncertainty in these dynamics. Nevertheless, satisfactory performance of robots requires their successful control regardless of such nonlinearities and uncertainties.

This project will investigate adaptive-control methodologies for controlling robotic manipulators. Adaptive control entails control algorithms that adapt in real-time to the underlying dynamic uncertainties, implicitly compensating for them. A key element that will be used is that of integrators, traditionally used in PID control in order to yield zero steady-state errors. The developed algorithms will be tested in simulation environments (MATLAB of Python) and in real experiments on a robotic manipulator.

Related literature

• Siciliano et al, ”Robotics: Modelling, Planning, and Control”, Chapters 1-3, 7, 8.
• Verginis, “Barrier Integral Control for Global Asymptotic Stabilization of Uncertain Nonlinear Systems under Smooth Feedback and Transient Constraints“, https://arxiv.org/pdf/2409.04767

Prerequisites

Good knowledge of automatic control (with a focus on nonlinear control), mathematics (differential equations), and programming using Matlab/Python/C++.

Supervisor and contact

Contact and apply to supervisor Christos Verginis by e-mail: christos.verginis@angstrom.uu.se

Your application should contain an official transcript of study records with information on your programme, courses and grades.

Thesis project in Constrained control of mobile robots (30 credits)

Description

The rapid advancement of technology has led to the increasing development and use of intelligent robotic systems in industry but also everyday life. Mobile robots (ground/aerial) constitute a large part of robotic systems and are widely used for a large variety of applications. A major component of such systems is the ability to design control algorithms that make them successfully perform a task such as navigate to a point or track a time-varying trajectory. Nevertheless, many of these robots evolve subject to different constraints, such as non-holonomic constraints (inability for lateral motion), underactuation (fewer states than control inputs), or Ackermann-steering kinematics. These constraints often make the control-design procedure tedious and cumbersome.

This project will investigate control algorithms for tracking and regulation by mobile robots while handling the aforementioned constraints, which will be primarily done using nonlinear control methodologies. The developed algorithms will be tested in simulation environments (MATLAB of Python) and in real experiments on a ground vehicle.

Related literature

• Khalil, ”Nonlinear Systems”, Chapters 4, 12, 13.
• Franch et al, “Control and trajectory generation of an Ackerman vehicle by dynamic linearization“, https://ieeexplore.ieee.org/document/7075182/

Prerequisites

Good knowledge of automatic control (with a focus on nonlinear control), mathematics (differential equations), and programming using Matlab/Python/C++.

Supervisor and contact

Contact and apply to supervisor Christos Verginis by e-mail: christos.verginis@angstrom.uu.se

Your application should contain an official transcript of study records with information on your programme, courses and grades.

User Optimized Electric Vehicle Energy Services (master thesis project)

This project focuses on developing an optimization model for Electric Vehicles (xEVs) to utilize their batteries as flexible energy resources for grid services, buildings, and households, aiming to generate revenue for the owner. The core goal is to maximize the financial return from services like V2X (charging/discharging) and energy trading while strictly ensuring the vehicle is charged for the user's needs. The main challenge is integrating the complex financial optimization of these services with user-centric functionality that makes participation easy and beneficial, all while managing battery degradation and different use locations.

The thesis is conducted in the framework of the Dansmästaren research project at the Division of Electricity and it is supervised by the partner company Zeeker Tech EU.

Supervisor: Niklas Legnedahl, Architect - Energy Management

Starting date: January 2026

Last application date: 2025-11-06

Do you want to know more and apply?

Read more and apply now (link to Zeekr's website)

Powering sustainable urban mobility: How energy-efficient Off-Street Mobility Hubs can balance the grid and enable new value chains (master thesis project)

To explore how Off-Street Mobility Hubs (OSMHs) can evolve from passive energy consumers into active, energy-efficient system nodes that enable new business models, enhance grid resilience, and reduce carbon impact in urban areas.

The Urban Mobility Resilience Roadmap* identifies as one of the research recommendations with regards to enabling resilient mobility systems the following: “Explore and test tools to integrate energy infrastructure in urban mobility planning to guarantee critical energy supply in unforeseen crisis situations, and to systematically integrate energy considerations in the set-up of new mobility services.” The statement proposes a proactive and integrated approach to urban mobility planning that centralizes energy infrastructure to ensure resilience and sustainability. An important objective will then be to embed energy efficiency and grid impact considerations from the ground up when developing and deploying new urban transport solutions, considering also the growing urban electric transportation. This means moving beyond treating energy as an afterthought and making it a core design parameter.

The thesis work is conducted in collaboration with Mobility Hub Partners, infrastructure and real estate developers contributing to sustainable urban mobility and more livable urban spaces.

The project aims at:

1) Conducting a literature review of MHs in Sweden and Europe that focus also on the Energy layer of such hubs. The key elements of each energy system (e.g., generation, storage, energy management system, etc.) will be described and compared.

2) Generating an Energy Impact Assessment Tool, to develop metrics/processes to quantify the total energy supply and consumption (including charging infrastructure needs) and the potential strain on the local electrical grid before a new OSMH is launched. Energy needs, capacity and benefits both internal and external stakeholders of the OSMH will be considered.

3) Optimizing charging of EVs to smoothen out the MH consumption during peak hours/critical days. Evaluation of the economic benefits that this optimization has from the view point of the MH. Evaluate what new income streams can emerge from these new energy flows? (e.g., EV charging, energy trading, flexibility as a service, EV fleet optimization, neighborhood energy services).

4) Identifying a case study with the help of UU and MHP to apply the tool, and a holistic financial business case with the support of MHP. Evaluate the performance of the OSMH and identify possible changes in the configuration elements which may result in better financial revenues.

5) Evaluating the impact of discharging EVs, so that essential mobility services remain operational during “unforeseen crisis” scenarios (interruptions from the power grid, natural or political disasters…).

The thesis can be conducted by 1-2 students (30 hp each). The description on the thesis proposal might be updated based on that.

Reading material

* https://www.ertrac.org/wp-content/uploads/2022/07/ERTRAC-Urban-Mobility-Resilicience-Roadmap-V3.pdf

https://link.springer.com/chapter/10.1007/978-3-031-35664-3_14

https://infrasweden.nu/wp-content/uploads/2024/07/RISE-Arup_Mobility_hubs_report_FINAL.pdf

https://www.diva-portal.org/smash/get/diva2:1894907/FULLTEXT02.pdf

Contact

Contact Valeria Castellucci for application and questions

Deadline for application the 13th of November.

The research group on Ionic and Optoelectronic Sensors (FTE-IONS) at the Division of Solid-State Electronics have several openings for master thesis. The topics include:

1. Multiplexed electrokinetic sensor for surface protein profiling of EVs
2. Single vesicle protein profiling
3. Electrokinetic chip and fluidic integration
4. Microfluidic mixer for electrokinetic sensor
5. AFM and Electron microscopy for size-based EV profiling

For further details, please contact Apurba.dev@angstrom.uu.se

Read more about our research

We are offering the following thesis subjects within the research area of microwaves in medical engineering. The projects are conducted within the MMG research group at the Division of Solid-State Electronics (Department of Electrical Engineering).

If you have any questions you are very welcome to contact: robin.augustine@angstrom.uu.se

Read more about MMG's research

(På engelska) Modeling and Optimization of Eddy-current Damper Power-Take-Off for Wave Energy Application

Antoine Dupuis, Jens Engström, Jan Isberg
Division of Electricity, Uppsala University

This project is suited for one or two master students in the field of electrical engineering or physics, interested in electromagnetism modeling and renewable energy. If you are interested, please contact the project author (Antoine Dupuis, antoine.dupuis@angstrom.uu.se).

Introduction

Despite the ever-growing demand for renewable energy, the reliability and economic viability of wave energy harnessing have not yet reached a consensus. It is estimated that, if fully harnessed, wave energy resources could provide up to 10% of the world’s electricity consumption. However, two key challenges hinder the industrialization of this technology: the maximization of power absorption and the reliability and survivability of wave energy converters (WECs). Systematically, research efforts focused on these challenges require scaled experiments in controlled environments, such as wave tanks, to validate concepts and results before full-scale deployment in the open sea.

The reliability of scaled experiments for WECs largely depends on the design of the power take-off (PTO) system, which is responsible for converting the buoy’s motion into useful energy. The PTO must faithfully reproduce the dynamics of the full-scale version. Depending on the type of WEC, the most common PTOs include linear motors, small generators, and friction blocks. However, these PTOs suffer from several drawbacks, such as cogging, static friction, temperature dependency and other non-linear unwanted effects. These effects lead to reduced reliability when extrapolating results to full-scale systems.

Eddy-current brake or damper PTOs are a promising alternative due to their robustness, reliability, and low friction. In these systems, when a conductive aluminum rod moves through a permanent magnetic field, eddy currents are induced in the rod, following Faraday’s law of induction. These currents generate a magnetic field that opposes the initial magnetic field, resulting in a damping force applied to the rod. Uppsala University has tested various designs of eddy current PTOs in both dry tests and wave tank experiments over the past eight years. Their most recent work featured a simple linear eddy current brake PTO using permanent magnets and showed promising potential despite its rudimentary design.

This project proposal aims to further develop the eddy-current PTO concept by advancing it from a proof-of-concept stage to a numerical model that can serve as the foundation for future designs and optimizations.

Figure 1: (a) Experimental setup and (b) linear eddy current brake PTO jpg, 74 kB.

Methodology

PTO Modeling

This project main aims is to develop a linear eddy current PTO model. The model entails two main components: the external magnetic source and the conductive material. The external magnetic source could be electromagnets or permanent magnets. The modeling is thought to be developed using finite element software (such as COMSOL, ANSYS, etc.), but analytical approach could also be considered given the simplicity of the geometry. The model should incorporate the key components of the PTO as input variables, such as the aluminum rod’s dimensions, the air gap, magnetic flux density of the magnetic source and the spacing between magnets. Depending on the approach, the model should, given as set of input variable, provide either the eddy current density, damping force or damping coefficient as an output. The model should eventually be validated against experimental data.

Damping Optimization

The second part of the project is associated with the damping maximization oriented design of the PTO using the model developed in the first part. Depending on the remaining time allocated for the project, the objective can go from a simple quantitative description of the impact of each of the model’s variables, to an optimization and design of the PTO before manufacturing stage. Different optimization methods could be considered depending on the type of model and results obtained in part one.

Expected Deliverables

The expected deliverables are, by order of priority, given below:

• A ready-to-use, model of a linear eddy current damper PTO
• A comparison between the numerical model and experimental data
• A PTO design for damping coefficient maximization.

Research Group and Supervision

The proposed project is closely connected to the wave energy group research at the division of Electricity in Uppsala University. The student(s) will be supervised by:

• Antoine Dupuis, PhD student in wave energy
• Jens Engström, Docent in the field of wave energy
• Jan Isberg, Professor at the division of Electricity

Requirements

The students should have knowledge and associated course credit on electromagnetism theory. Experience and associated course credit on FEM software may be mandatory.

Finally, knowledge on optimization is beneficial.

One MSc thesis project available at the Division of Solid-State Electronics, Department of Electrical Engineering, The Ångström Laboratory

Understand electroosmotic flow in nanopore systems

Background

Electroosmotic flow (EOF) is a common phenomenon in nanofluidic systems, such as nanopore sensors, ion channels, and other ionic devices. It arises from the movement of ions attracted to surface charges at the electrolyte-solid interface. For example, as illustrated in Fig. 1a, when a surface carries a negative charge, it attracts cations from the electrolyte. Under an external electric field, these cations move and drag the surrounding water with them, creating what is known as EOF. In nanopores under different conditions, EOF can manifest in various patterns, such as vortices or reversed flow (Fig. 1b and 1c). EOF is a critical electrohydrodynamic process that affects ion transport and molecule translocation through nanopores or nanochannels, and consequently influences the performance of these ionic devices, including nanopore single biomolecule sensors, concentration gradient power generators, and iontronic devices. Figure 1. (a) Origin of EOF; (b) EOF in a cylindrical nanopore; (c) EOF vortex in a truncated conical nanopore.

Figure 1. (a) Origin of EOF; (b) EOF in a cylindrical nanopore; (c) EOF vortex in a truncated conical nanopore jpg, 85 kB.

Task

In this project, we will investigate electroosmotic flow (EOF) in nanopore systems primarily through COMSOL simulations and theoretical modeling. Unlike EOF in infinitely long tubes, the finite length of a nanopore can significantly alter the EOF distribution due to boundary conditions. We will theoretically describe the EOF distribution within a nanopore under various boundary conditions and verify these models through simulations.

Plan

We will implement this project in three major steps:

1. Understand the mechanism of EOF and traditional EOF models.
2. Establish numerical simulation platform of EOF in nanopores based on COMSOL. Interpret the simulation results.
3. Develop theoretical models to describe the EOF distribution in a nanopore with different boundary conditions.

Goal

Through this project, the students will gain the knowledge of electrokinetics and electrohydrodynamics in nanopore systems, nanofluidics, and ionic devices based on nanopores. The students will also gain practical skills of theorical modelling and numerical simulation.

When: As soon as possible, upon mutual agreement.

Duration: 6 months

Your background: Physics, engineering physics, physical chemistry, chemical engineering, electronics, electrical engineering

Supervisor: Dr. Chenyu Wen (chenyu.wen@angstrom.uu.se)

Master Thesis Project: Real-Time RF Mapping with Analog Backscatter Tags

This project focuses on developing an innovative system for real-time mapping of ambient RF transmitters using signal strength measurements collected by a custom-built analog backscatter tag. Inspired by recent advancements like RFIMap, it aims to address key limitations such as the lack of real-time updates and the extensive calibration required by current methods.

The project will involve:

• Testing backscatter tags for efficient RF signal sensing.
• Designing machine learning models to tackle noisy data, sparse measurements, and dynamic environments.
• Validating the system through real-world experimental testing.

This thesis is ideal for students passionate about wireless communication, signal processing, and machine learning, offering practical experience with RF sensing, backscatter technology, and real-time ML techniques.

Contact

If you have any questions contact Padmal by e-mail at madhushanka.padmal@angstrom.uu.se or directly apply by sending your CV + an official transcript of your study records.

Two MSc thesis projects available at the Division of Solid-State Electronics, Department of Electrical Engineering, The Ångström Laboratory

Silicon neurons and synapses: Electronic circuit design, simulation, and realization

Background

Neuromorphic computing is an innovative field that aims to replicate the architecture and functionality of the human brain using electronic systems. Unlike the traditional von Neumann architecture that relies on binary logic and sequential processing, neuromorphic systems emulate the brain’s neural networks by using electrical spikes to transmit information. This approach allows for parallel processing and more efficient data analysis (Fig. 1a). Neuromorphic computing holds the potential to perform complex tasks, particularly those requiring real-time processing and learning capabilities. It could revolutionize areas such as artificial intelligence, robotics, and sensory processing by offering more efficient computing with lower energy consumption. A key method for realizing neuromorphic systems involves artificial neurons based on electronic circuits and corresponding components, as illustrated in Fig. 1b and 1c for two typical examples of artificial neurons and synapses implemented through electronic circuits. Figure 1. (a) spike signal generation and transmission between neurons and a simple neuron network structure; An example of artificial (b) neuron and (c) synapse realized by electronic circuits.

Figure 1. (a) spike signal generation and transmission between neurons and a simple neuron network structure; An example of artificial (b) neuron and (c) synapse realized by electronic circuits jpg, 65 kB.

Task

In this project, we will design and build artificial silicon neurons and synapses using electronic components such as transistors, resistors, and capacitors. We will develop various neuron and synapse circuits, analyze their properties, simulate their behaviors, and ultimately realize them in physical form.

Plan

The development of silicon neuromorphic circuits will be divided into three main stages:

1. Initial Development: We will begin with a simple version of silicon neurons and synapses. Through circuit simulation and construction, we will gain a thorough understanding of the circuits by identifying core components, supportive elements, and the parameters that influence their performance.
2. Module Enhancement: Next, we will enhance the modules by adding functions that emulate more detailed behaviors of neurons and synapses, such as adaptation and short-term plasticity. We will also design sensory neurons capable of responding to optical, acoustic, and thermal stimuli.
3. System Integration: Finally, we will design small-scale neuromorphic circuits by interconnecting the neuron and synapse modules to achieve simple system functions, such as classification. These circuits will be physically realized using PCBs, and we will demonstrate their functionality.

Goals

Our goal is to develop 2-3 different silicon neurons and synapses using electronic devices and integrate them into small-scale neuromorphic circuits for simple functions. Through this project, you will gain knowledge of the working principles of neuromorphic systems, silicon neuron and synapse circuits, analog circuit design, signal processing, and system dynamics. Additionally, you will develop practical skills in circuit design and debugging, circuit simulation, PCB design, and the characterization of electronic devices and circuits.

When: As soon as possible, upon mutual agreement.

Duration: 6 months

Your background: Engineering physics, electrical engineering, computer science. Experience in circuit and system design, FPGA/MCU development is a merit.

Supervisor: Dr. Chenyu Wen (chenyu.wen@angstrom.uu.se)

The Thin Film of Advanced Electronic Materials (FTE-TF) group has the following master thesis projects available.

Read more about us and our research on our website

Underwater communication for wave power parks

Project description
Due to a large potential of ocean waves [1], wave energy has a potential to contribute to a future renewable electricity production. Many researchers and engineers across the globe are striving to find an efficient way to convert the energy of waves to a useful electric energy. At the Division of Electricity of Uppsala University, wave power research started in 2002. The concept developed, studied and tested experimentally at Uppsala University consists of a buoy resting of the sea water surface and connected to the translator of a linear generator moored on the seafloor.

In the experimental setup it is often required a reliable communication between the measurement system installed on the buoy with the measurement system placed next to the generator. Since the direct communication through the wire is not possible due to complex motion of the buoy and the risk of a quick rupture and damage of the communication cable and due to the hostile saline environment the radio communication underwater is not possible, a new communication system should be suggested and tested. The new communication system will be based on sonar principles using piezoelectric transducers similar to that in submarine communication [2].

Goal
The goal with the master thesis project is to develop, build and test system for underwater multi nodal communication between buoy and generator: for the data transmission above / below the sea water and synchronization of digital clocks of both measurement systems of the buoy and generator.

References

[1] T. W. Thorpe, “An overview of wave energy technologies: status, performance and costs - moving towards commercial viability,” IMECHE Seminar, London, UK, no. 30 November, pp. 1–16, 1999.
[2] Ali, Mohammad & Jayakody, Dushantha Nalin & Perera, Tharindu & Sharma, Abhishek & Srinivasan, Kathiravan & Krikidis, Ioannis. (2019). Underwater Communications: Recent Advances.

Supervisors and contact:

Robin Augustine (Robin.Augustine@angstrom.uu.se)

Irina Temiz (Irina.Temiz@angstrom.uu.se)

Thesis Project: Development of a BEM Model for the Aerodynamics of a CRAFT Turbine in MATLAB

Background

CRAFT turbines (Counter Rotating Axis Floating Tilted Turbine) are an innovative type of wind turbine for floating offshore wind power. To optimize the performance and efficiency of these turbines, accurate simulations of their aerodynamics are required. BEM theory (Blade Element Momentum) is a well-established method for modelling the aerodynamics of rotating blades, making it suitable for analyzing CRAFT turbines.

Purpose

The purpose of this thesis project is to develop a detailed BEM model to simulate the aerodynamics of a specific CRAFT turbine. The model will be implemented in MATLAB, allowing for flexibility and adaptation to different turbine configurations.

Tasks

1. Literature Study: Conduct a comprehensive literature study on BEM theory, wind turbine aerodynamics, and the specific characteristics of CRAFT turbines.
2. Model Development: Develop a detailed BEM model in MATLAB, including the following components:
   • Blade element geometry
   • Airflow calculations
   • Force calculations
   • Performance calculations: i.e., forces in the vertical direction (lift), wind direction (thrust), and side forces; moments; and power
3. Model Validation: Validate the model by comparing simulation results with experimental data or other existing models.
4. Parametric Study: Perform a parametric study to investigate how different parameters (wind speed, blade angle, turbine geometry) affect the turbine's performance.

Expected Results

• A well-documented MATLAB code for BEM simulation of CRAFT turbines.
• Detailed simulation results, including force curves, power curves, and other relevant parameters.
• An understanding of the flow around the turbine calculated using the BEM method.

Project Benefits

• Relevance: The project is directly linked to current research in renewable energy and contributes to the development of more efficient floating wind turbines.
• Development: The student will have the opportunity to develop their skills in modeling, simulation, and optimization.
• Collaboration: The student will collaborate with experienced researchers and engineers in the field.

Possible Extensions

• Incorporation of Dynamic Effects: Extend the model to include dynamic effects such as resonance phenomena (e.g., blade flutter) and torsional vibrations in the drivetrain.
• Integration with Other Simulation Programs: Link the BEM model to other simulation programs to analyze the entire power plant system.

Application and contact

Contact Hans.Bernhoff@angstrom.uu.se for more information or apply directly by sending your CV and an official transcript of study records.

Thesis project: Deployable Disaster Wind Power System: Electrical Control and Power Management for a Novel Hyperlight Concept (30 credits)

Department: Electrical Engineering, Uppsala University

Abstract:
This diploma work focuses on the investigation and development of a novel deployable wind power system designed for disaster relief scenarios. The project emphasizes the electrical control system and power management strategies for a novel hyperlight wind turbine concept capable of mobile autonomous deployment.

Scope: Work with a novel hyperlightweight, portable wind turbine system optimized for rapid deployment in disaster-affected areas.

Objectives:

1. Electrical Control System:Develop an advanced control system to ensure efficient and stable operation under varying wind conditions.
2. Power Management:Study and develop a robust power management techniques including local energy storage, ensuring reliable power supply for critical applications.
3. Performance Evaluation:Conduct evaluation and possibly testing a real system to validate the system's performance, efficiency, and reliability in real-world disaster scenarios.

Methodology:

• Literature Review:Conduct a comprehensive review of existing deployable wind power systems and their applications in disaster relief.
• System Design:Utilize CAD software to design electrical system for the hyperlight wind turbine.
• Control System Development:Develop and simulate the electrical control system using MATLAB.
• Prototype Construction:Build/assemble a functional prototype control/power management setup for the wind turbine system.
• Analysis:Simulate and perhaps perform field tests to evaluate the system's performance and make necessary adjustments.

Expected Outcomes:

• Concept for electrical system of a fully functional deployable hyperlight wind power system.
• Study efficient electrical control systems tailored for disaster relief applications.
• Comprehensive documentation of the design, development, and testing processes.

Significance:
This project aims to contribute to sustainable disaster relief efforts by providing a reliable, renewable energy source. The innovative hyperlight concept and advanced control systems developed in this work have the potential to significantly enhance the efficiency and effectiveness of disaster response operations.

Application and contact

Contact Hans.Bernhoff@angstrom.uu.se for more information or apply directly by sending your CV and an official transcript of study records.