Bakgrunn og aktiviteter

Project proposals for ITK 2017-2018 (Molinas)

1. Flying a Drone with your Mind

2. The Augmented Human: actuation of devices with biological signals

3. Revolve NTNU: Battery Study for Electric Race Car

4. Cardiac arrhythmia detection from instantaneous frequency estimation of ECG signals

5. Low frequency detection in blood pressure with Hilbert Huang Transform

6. Smart Meters Hackathon

7. Smart Energy for People: into the Smart Meters of TrønderEnergi

8. Synchronization and Stability: a microgrid investigation

9. Non Stationary signal analysis of stochastic processes

10. Instantaneous frequency analyzer in a Suitcase

11. Collaboration strategies between main and emergency power systems for marine vessels 

12. Identification of Instantaneous Frequency in maritime power systems

13. Suitcase for electrical signal analysis in ships, offshore structures and microgrids

14. Stability analysis of DC distribution systems for electric ships

15. Stability Characterization of Solar Microgrids

16. Smart grid online identification and stability analysis

17. Resonances and oscillatory phenomena in power electronics systems: Power Quality characterization

18. Resonances and oscillatory phenomena in wind farms: Stability characterization

19. Model Predictive Control in Power Electronics Systems

20. Harmonics Management through data analysis, identification and control

21. Control of wireless power transfer systems for marine applications

22. Resonant wireless power transfer in subsea applications

23. Impact of controllers in the stability of a Modular Multilevel Converter (MMC)

24. Development of converter for electric composite motors to be used in high payload industrial drones. 

1. Flying a Drone with your Mind

This project is about an experimentation on actuation of unmanned vehicles with direct signals from the mind. The direct mind actuation will be done through the use of an open source Electroencephalography (EEG) headset that records brain activity and translates it by means of a computer interface into signals that can be analyzed and used for actuation in real-time. 

The task of this project will consist of developing a Brain Computer Interface (BCI)  that can directly give commands from the brain to the drone for flying. The EEG headset that will be used is the one based on Open BCI concept (http://www.openbci.com/) that records brain waves based on EEG and then sends the information wirelessly to a smartphone or computer from where the commands are actuated to the drone. Motor imagery will be used as command to the drone. Using this command, this project will fly a drone and develop a trajectory control directly from the motor imagery commands without using any manual actuation system in between.

The student can choose the software development platform among Android, iOS, Mac, Linux and Windows Platforms. The students in this project will have access to the open-source softwares, EEG headset and BCI already developed within this task by previous year students. 

This project is suitable for two students to work in a team.

This project is in collaboration with former Director of NASA Goddard Institute of Data Analysis Norden Huang.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Geir Kulia, geir.kulia@signalanalysislab.com

2. The Augmented Human: actuation of devices with biological signals

This project will work on the design of actuation signals based on the use of Event Related Potential (ERP) in the viusal cortex of the brain. The students will work on the classification of electroencephalograph (EEG) signals produced by the random visual exposure of primary colours i.e. red and green to a number of subjects while sitting in a dark room. The signals obtained as a consequence of these exposures will be analysed by using time-frequency analysis to extract the frequency modes specifically associated with the instant of exposure to the red and green colours. These specific modes will be used as features for support vector machine (SVM) in order to classify them. The main objective will be to classify the EEG signals in Red and Green classes from groups of data among all the subjects.

NTNU ITK Supervisor: Marta Molinas, marta.molinas@ntnu.no  

Co-supervisor: NTNU Dept. of Electronics, Lars Lundheim, lars.lundheim@ntnu.no

3. Revolve NTNU: Battery Study for Electric Race Car

The battery management system (BMS) is one of the most important parts of an electric vehicle power system, which may comprise hundreds of cells, and the health of batteries is essential to the life and safety of the whole vehicle system. In order to protect and diagnose the battery pack better, many kinds of battery state parameters, such as the state of charge (SOC), state of health (SOH), internal resistance, capacity, polarization capacitance, polarization resistance, self-discharge resistance, etc., are usually needed to be measured, estimated and displayed in the BMS. This project will continue the ongoing research on Kalman Filter based SOC estimation developed by a previous student in this project. The idea is to advance the research into the State of Health and Impedance identification and measurements by utilizing other identification methods that will cope with tha limitations of Kalman Filter. 

Kalman Filter (KF) and its extension based methods, i.e., the Extended Kalman Filter (EKF) [1]-[2] and the Unscented Kalman Filter (UKF) are widely used for SOC estimation. Other techniques that are utilized for SOC estimation include the fuzzy logic based methods, the neural network (NN) based methods, etc. The Kalman Filter based methods require that the noise in the system should be Gaussian distributed and the fuzzy logic and NN based methods need to train the system first and lots of train data are needed. The Particle Filter (PF) approach uses weighted random samples (particles) that are sampled by the Monte Carlo method to approximate the post priority density of the whole system. The PF can be used for state estimation of nonlinear systems with a non-Gaussian distribution and it is not sensitive to the dimension of the system and it has shown promising results for battery SOC estimation.

This project will apply Particle Filter to the battery SOC estimation dedicated to the Revolve NTNU race car, looking at the battery as a nonlinear dynamic system.

[1] Gao, M., et al., Battery State of Charge online Estimation based on Particle Filter, Proceeding of the 4th International Congress on Image and Signal Processing, pp. 2233-2236, 2011.

[2] Ørjan Gjengedal, Preben Joakim Svela Vie, Marta Molinas, Battery Modeling and Kalman Filter-based State-of-Charge Estimation for a Race Car Application, 14th IEEE International Conference on Networking, Sensing and Control, May 16-18, 2017, Calabria, Southern Italy

This project is in collaboration with Revolve NTNU

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Revolve contact person, Maria Dyrseth, maria.dyrseth@revolve.no,

Project webpage: www.revolve.no

4. Cardiac arrhythmia detection from instantaneous frequency estimation of ECG signals

Preliminary detection and classification of cardiac arrhythmia is one of the most important problems in biomedical signal analysis. This project will work on the estimation of instantaneous frequency (IF) of ECG signals (from patients of Saint Olav Hospital in Trondheim) as a method for carrying out detection of cardiac disorder. Based on IF estimates, a classifier will be designed to differentiate an abnormal signal from a normal one. The project will aim at training, testing and validation of the classifier using signals from Arrhythmia databases.

This project is in collaboration with Saint Olav Hospital, Department of Circulation and Medical Imaging.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Nils Kristian Skjærvold, nils.k.skjervold@ntnu.no  

5. Low frequency detection in blood pressure with Hilbert Huang Transform

Measurements of blood pressure will be analyzed in this project to detect low-frequency oscillatory components by using Instantaneous Frequency detection methods. In human studies, low-frequency oscillatory components in blood pressure are associated to: 

- the respiratory rate interval which is considered a good marker of sympathetic activity

- low-frequency oscillations that emanate from a different end organ, arterial smooth muscle, known as Mayer waves

It is known that low-frequency components increase with tilt, mental stress, physical exercise, moderate hypotension, and coronary artery occlusion.  In this project, low-frequency component of systolic Blood Pressure Variability (BPV), will be used as a marker of sympathetic activity. Sympathetic activity is involved in the pathogenesis of hypertension, coronary artery disease or heart failure and this is well known and proved. However, although these methods are introduced into scientific research of Sympathetic Nervous System evaluation, they are not commonly used in the clinical practice. This project will aim at opening the path to its use in clinical practice through a collaboration with Saint Olav Hospital. 

This project is in collaboration with Saint Olav Hospital, Department of Circulation and Medical Imaging. 

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Nils Kristian Skjærvold, nils.k.skjervold@ntnu.no  

6. Smart Meters Hackathon

This project will consist on the analysis of the hardware and the software emebeded in a smart meter (Smart meter of TrønderEnergi) to understand the way it works and the fundamentals behind the measurement of voltages and currents. Based on this assesment, new functionalities for monitoring and control will be explored for the design of a Home Energy Management System.

This project is in collaboration with the TrønderEnergi (https://tronderenerginett.no/english/new-meter-ams ) and Technical University of Bucharest.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

7. Smart Energy for People: into the Smart Meters of TrønderEnergi

The smart meter from Trønderenergi will be analyzed to assess the algorithms that are implemented in the meter for the estimation of measurements of voltage and currents. Based on the findings, the work will consist of exploring the opportunities for real-time actuation of loads inside the home, by exploiting the features of the smart meter. 

This project will be in close collaboration with TrønderEnergi (https://tronderenerginett.no/english/new-meter-ams) and Technical University of Bucharest. 

Supervisor: Marta Molinas, marta.molinas@ntnu.no

8. Synchronization and Stability: a microgrid investigation

An electric power system is a non-linear oscillator. A stand-alone microgrid can be considered as composed by coupled oscillators which would spontaneously synchronize when coupled through an underlying electrical network (Huygens synchronization of two clocks). This project will implement different versions of controlling a stand-alone microgrid based on the emulation of the dynamics of non-linear oscillators and will compare them with the widely-used Phase Locked Loop based synchronisation, to understand the underlying mechanism behind synchronisation. The impact of these different implementations of synchronisations on the stability of the microgrid will be explored.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Prof. Jon Are Suul, jon.are.suul@ntnu.no  

9. Non Stationary signal analysis of stochastic processes

A non-stationary stochastic signal is a signal whose statistical structure changes as a function of time, e.g., the mean, variance, correlation (covariance), etc., may change as time evolves. This project will examine several techniques for data analysis, by implementing, using real data from various processes and systems, time-frequency analysis methods and spectral analysis. Examples of implementation will use Short-Time Fourier Transform, Wavelet Transforms, Wigner-Ville Distribution, Hilbert-Huang Transform, Bayesian methods, Kalman filtering. etc. The focus will be to identify the limitations and advantages of established methods for the selected stochastic signals chosen for this project (Brain signals, speech signals, blood pressure, heart beat, microgrid signals, etc)

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Dr. Maximiliano Bueno Lopez, maximiliano.bueno@ntnu.no 

10. Instantaneous frequency analyzer in a Suitcase

This project will consist on the design of a data analysis tool that will include the following:

- In-house development of a data acquisition system for on-site measurement acquisition

- Development of a flexible module for data analysis with high resolution for monitoring load variation, production variation, voltage and frequency signals

- Development of a power quality module using instantaneous power calculations

The students in this project will be part of a team that has already started the development of some modules of the above described device.

This project is in collaboration with the Start-up Company "Signal Analysis Lab" 

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Geir Kulia, geir.kulia@signalanalysislab.com

11. Collaboration strategies between main and emergency power systems for marine vessels

Maritime power systems with variable configurations and non-linear loads will need collaboration strategies between the different power sources for efficient operation, ensuring overall stability and control of harmonic level. The use of a stored energy source with active conditioning functions can be designed as part of the function of an emergency system with the purpose of increasing power systems resilience and efficiency by using collaboration strategies with the main power system.

This project will be in close collaboration with ULSTEIN Power & Control. 

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-Supervisor: Egil Rødskar, egil.rodskar@ulstein.com, Prof. Jon Are Suul, jon.are.suul@ntnu.no 

12. Identification of Instantaneous Frequency in maritime power systems

The project objective will be to compare Kalman Filter based frequency estimators with time-frequency analysis methods such as Wavelet based, Fourier based, Wigner distribution and Hilbert Huang Transform-based.

Since the waveforms of electrical signals in marine microgrid systems (marine vessels) are strongly influenced by the dynamic loads in the system, the distributed and dispersed nature of sources and loads and the presence of power electronics components, a real-time estimation of the dominant modes of oscillations is necessary. Several signal analysis and identification methods will be tested in the presence of dynamic loads and potential non-stationarity. Non-linear filters will be explored in this project and compared to the classical linear filters and Fourier-based techniques applied to real data from a marine vessel.

NTNU Supervisors: Marta Molinas, marta.molinas@ntnu.no,

Co-supervisor: Lars Lundheim, lars.lundheim@ntnu.no 

Contact person in Ulstein: Espen Skjong, espen.skjong@ulstein.com

13. Suitcase for electric signal analysis in ships, offshore structures and microgrids

A portable integrated hardware/software interface based on FPGA/DSP platform for data acquisition and software interface for data analysis will be developed with the purpose of applying it to the analysis of electrical waveform distortions in diesel electric ships power systems, offshore structures and microgrids in general. Current and voltage waveforms in isolated electrical systems like those in ships can be severely distorted, field measurements showing not only high levels of distortions but also non-linear and non-stationary characteristics. The methods and tools used today to analyse these distortions are not suited for dealing with simultaneously non-linear, non-stationary signals. This project will develop an "in-house" both hardware and software tools that will accurately extract meaningful data from the observed waveforms without loss of relevant information and at relatively low cost. The instantaneous frequency concept presented in [1], will be at the core of the implementation of this portable integrated hardware/software tool.

[1] N.E. Huang, Z.Wu, S.R. Long, K.C. Arnold, X. Chen and K. Blank, "On Instantaneous Frequency," in Advances in Adaptive Data Analysis, Theory and Applications, World Scientific Publishing Company, vol.1, no. 2, April 2009.

This project is in collaboration with former Director of NASA Goddard Institute of Data Analysis Norden Huang.

The project is also part of an ongoing Master project that has already advanced the development of the data acquisition module. The student in this project will collaborate with further development of the device.

Supervisor: Prof. Marta Molinas, marta.molinas@ntnu.no

Co-supervisors: Bjorn B. Larsen, Lars Lundheim (dept. of Electronics), Geir Kulia, geir.kulia@signalanalysislab.com

14. Stability analysis of DC distribution system for electric ships

Direct Current (DC) electrical distribution systems are an option for future low emission and fuel-efficient electric ships. Future ships require reliable energy systems with improved fuel economy, and reduced emission. Shipboard hybrid electric power systems have become attractive solution to meet the mentioned requirements. With penetration of power electronic converters into power systems, shipboard DC distribution systems offer further advantages, such as reduced space and weight of the components. However, modelling and stability analysis are essential tools to enable design and optimization of the system.

In this project, the electrical model of the hybrid electric ship, with a power electronics based DC system, will be studied based on small signal stability tools. Then, the influence of control design on the stability of the electrical system will be investigated. This project will be done in three steps; first, designing a simple DC power system for ship electrification, and tuning converter controllers; second, deriving state-space model of the system; third, establishing the small signal stability method and evaluating the stability margin. The control parameters will be studied with respect to the system stability and the system response. The system model will be implemented in MATLAB.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor:  Prof. Jon Are Suul, jon.are.suul@ntnu.no 

15. Stability Characterization of Solar Microgrids

The impedance based stability analysis method and the Nyquist criteria will be implemetned and applied to estimate the stability of a solar microgrid. The work will consist of analysis, modelling, control design of a solar microgrid on a simulation platform (e. g. Matlab). A method for estimating the stability margin will be explored.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

16. Smart Grid on-line identification and stability analysis

The SmartGrid is an electrical grid (e. g. microgrid, marine vessel grid, solar farm, wind farm) where several different components interact depending on the control actions and information flow available. It is a complex system especially when the scale grows (e.g. wind farm), with several model uncertainties and unknown dynamics. A mathematical model that describes accurately the physical behavior can be a challenging task when the scale grows. As an alternative to high fidelity modeling, this project will work with on-line identification techniques based on limited measurement availability (Kalman Filter, Least-Squares, Bayesian Filter, Particle Filter, Non-linear observers) that can characterize the Smart Grid under investigation. The purpose of this work is to perform an online stability analysis of the system based on the identification of critical parameters. The project will consist of modeling, simulation work (Matlab/Simulink), system identification, signal analysis and impedance estimation. The work will be a mixture of control and stability theory, signal processing and power system analysis.

Supervisor: Prof. Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: PhD candidate Atle Rygg Årdal, atle.rygg.ardal@itk.ntnu.no

17. Resonances and oscillatory phenomena in power electronics systems: Power Quality characterization

Harmonic pollution is a serious problem in many power distribution grids (and micro grids), and can cause instability as well as increased losses undermining a green environment philosophy. The measurement Total Harmonic Distortion (THD) is used for measuring the harmonic content in a grid, and class entities such as DNV and ABS provides a regulatory framework for maximum allowed THD in a marine vessel relative to the vessel’s operation and classification. This project will work on the assessment of the power quality indexes in use today by the Standard Organization and evaluate their validity for the current transformation the system is undergoing. The project will include estimators (Kalman filters / Observers) for providing estimates of measurements which are not possible to extract due to the grid’s physical layout or distribution. Field measurements from a marine vessel will be provided to test the algorithms and industrial grade measurement devices will be used for comparing performances. 

This project is in collaboration with Ulstein Power & Control

Supervisor: Prof. Marta Molinas, marta.molinas@ntnu.no;

Co-supervisor: Espen Skjong (UPC), espen.skjong@ulstein.com

18. Resonances and oscillatory phenomena in wind farms: Stability characterization

Harmonic and subharmonic resonances have been reported in wind farms interconnections with high voltage direct current (HVDC) systems. Those harmonics resonances propagate through the HVDC system posing risks of security of power delivery, representing severe losses of power and contributing to the decay and deterioration of equipment when undetected.  The underlying mechanism behind those resonances has not yet been clearly identified. The objective of this project is to identify the root-cause of those resonances in order to explore possible solutions to cope with them. This project will be anchored on an ongoing PhD research focused on the development of methods and tools for identifying and correcting stability problems related to resonances in electrical grids. This PhD research has already identified the impact of the control systems design in the presence and suppression of these resonances. However, the mechanism at the root of these resonances depends on the particular configuration of the interconnected system and the interaction between its components. In order to understand this mechanism, a wind farm connected through an HVDC system will be used as a basis for the investigation. Modelling, analysis and simulations of the system will target at mapping the impedances for identifying the source of the resonance and the role and impact of the control system in stabilizing the oscillations.  Matlab will be used as platform for the simulations. This project is part of an ongoing collaboration with Shanghai Jiao Tong University (SJTU) where several students from NTNU and SJTU are engaged in the research of the resonance at the Nanao Offshore grid where 20 Hz oscillations between the wind farm and the Multi-terminal HVDC were detected.

Supervisor: Prof. Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: PhD candidate Atle Rygg Årdal, atle.rygg.ardal@itk.ntnu.no

19. Model Predictive Control in Power Electronics Systems

Hybrid constrained optimal control methodologies such as Model Predictive Control (MPC) is an excellent candidate control for power electronics systems. From the control point of view, power electronics circuits and systems constitute examples of hybrid systems, since the discrete switch positions are associated with different continuous-time dynamics with physical and safety constraints. Power electronics circuits and systems have traditionally been controlled in industry using linear controllers combined with non-linear procedures like Pulse Width Modulation (PWM). The models used for controller design are a result of simplifications that include averaging the behavior of the system over time (to avoid modelling the switching) and linearizing around a specific operating point disregarding all constraints. The derived controller usually performs well only in a neighbourhood around the operating point disregarding all constraints. To enable reliable operation for the entire operating range, the control circuit is usually supplemented by a number of heuristic add-ons. This procedure requires large development times and lacks theoretically backed guarantees for the operation of the system. Today’s available computational power and the theoretical advances in the control of hybrid systems make possible to revisit the control issues associated with power electronics applications and explore the application of MPC. In this project, MPC, as an example of hybrid constrained optimal control, will be applied to a selected case of power electronics application depending on the interests (Harmonic current filtering, reactive power compensation, active front end converter, etc). Non-linear and linear models will be tested and compared and a real-time implementation will be implemented. A two-level voltage source converter (.VSC) will be used as example of application.  The challenges to real-time implementation will be identified by first developing a simulation model to be further implemented in a prototype VSC. 

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Atle Rygg Årdal, atle.rygg.ardal@itk.ntnu.no

20. Harmonics Management through data analysis, identification and control

Electrical grids (e. g. microgrid, marine vessel grid, offshore platforms, solar farm, wind farm) where several new type of components (power electronics converters) interact, are becoming prone to harmonics pollution. A mathematical model that describes accurately the physical behavior can be a challenging task. Even if a detailed mathematical model is available, such model can be of high order leading to a complex controller whose implementation may be costly and whose operation may not be well understood. As an alternative to high fidelity modeling, this project will work with data analysis and on-line identification techniques based available measurements (Kalman Filter, Least-Squares, Bayesian Filter, Particle Filter) that can characterize the grid under investigation. The purpose of the characterization is to understand the harmonic propagation and its impact on the electrical stability of the grid. The project will have two parts: 1) a theoretical part where data analysis methods will be compared according to their suitability to the purpose of the investigation using synthetic data, 2) the practical part of the project will evaluate measured data from the field (data can be chosen from marine vessels and an isolated solar microgrid). Once the measurements are characterized, possible solutions to manage harmonics will be explored. The specific grid case for investigation will be decided depending on the interests (e.g. wind farm, marine vessel microgrid, solar microgrid, etc). Matlab will be used as platform for the investigation.

Supervisor: Prof. Marta Molinas, marta.molinas@ntnu.no

21. Control of wireless power transfer systems for marine applications

Inductive, wireless power transfer is a safe, efficient and reliable way of transferring power without any physical contact between a sending circuit and a pick-up circuit. Inductive charging has proved its feasibility in multiple fields, ranging from low power biomedical sensors to applications in the kW range for material handling in industrial environments. One major challenge in wireless charging lies in the capability of precisely controlling the power flow, while keeping the transfer efficiency as high as possible.

Possible misalignment between sending and pickup coils is one of the key factors influencing the transfer efficiency and/or the size of the system. Precise relative positioning of sending and pickup structures is therefore of utmost importance, especially in applications where space and cost constraints are very stringent.

The task of the student will be to show how precise positioning control can affect relevant system quantities (current and voltage stresses) compared to the base-case of freely moving structures.

It will be also possible to:

  • Experimentally verify the real control performance on a scaled prototype of inductive charging system available at NTNU/SINTEF laboratory. The experimental verification of obtained results can be part of the MSc project to be developed starting from spring 2017.

The specialization project will be developed in collaboration with SINTEF Energy.

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Dr Giuseppe Guidi, giuseppe.guidi@sintef.no

22. Resonant wireless power transfer in subsea applications

Wireless power transfer can enable truly autonomous long-duration underwater vehicles (AUVs) allowing them to embark in longer missions in deeper and more difficult environments. Resonant wireless power transfer through air is a relatively mature technology, with several commercial systems emerging, especially for charging of EVs, rated for up to several kW and allowing for power transmission over several tenths of centimetres. (www.witricity.comwww.qualcomm.com/products/halo).

In principle, the same concept can enable wireless power transfer through a variety of materials, including saltwater. This project will explore this possibility and identify the challenges in saltwater by building first a simulation model based on the principle of resonant wireless transfer. This model will be used as basis to identify the parameters that will strongly affect the efficiency of the power transfer under saltwater conditions (resonant frequency, coil geometry, magnetic field strength, etc). After critical parameters have been identified, a small scale prototype will be designed and built to test the performance. System efficiency, as well as configuration of the electromagnetic field will be measured, assessing the potential for scalability. 

This project is in collaboration with SINTEF Energy

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisor: Prof. Jon Are Suul, jon.are.suul@ntnu.no 

Co-supervisor: Dr Giuseppe Guidi, Giuseppe.guidi@sintef.no

23. Impact of controllers in the stability of a Modular Multilevel Converter (MMC)

Different controllers have different impacts on the stability of power electronics converters. Much research is available today on the stability of power electronics converters whose controllers are design based on the Field Oriented Control concept. This project will design several other controllers based on non-linear approaches and will evaluate the stability of the converter unit under each controller. Based on the comparative study of the stability of these controllers, critical factors and/or inherent properties of these controllers affecting the stability will be identified. Impedance based stability analysis will be the starting point of the investigation. 

Supervisor: Marta Molinas, marta.molinas@ntnu.no

Co-supervisors: Morten Hovd, morten.hovd@itk.ntnu.no

                          Dr Jing Lyu, jing.lyu@ntnu.no 

24. Development of converter for electric composite motors to be used in high payload industrial drones. 

A new electric motor will be developed in cooperation with the drone manufacturer, Dronera. The drone will be utilized by hospitals to transport blood bags and medicine. A new production method, developed by students at NTNU, will enable cheaper and lighter electric motors with high efficiency. As a student, you will work closely with a multidisciplinary team, and be co-supervised by an experienced motor designer. The main focus of the master thesis is to develop a custom control system (converter) for the electric motor. During the project, you will be challenged to investigate new areas and come up with creative novel solutions. A job opportunity will be available after the project period. 

Supervisor: Marta Molinas, marta.molinas@ntnu.no 

Co-Supervisor: Dr Ravindra Ummanenis, Alva Industries AS, ravindrababuu@gmail.com 

Contact person: Jørgen Selnes (91598175), CEO, Alva Industries AS

 

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