Bakgrunn og aktiviteter

Project proposals for ITK 2018-2019 (Molinas)

1. David and Goliath: a new concept of dry single-channel EEG for brain health monitoring

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

3. Flying a Drone with your Mind

4. Revolve NTNU: Battery Study for Electric Race Car

5. Optimal design and operation of H2 fuel cell powered passenger ferry

6. Battery systems data analysis

7. Prognostic system framework for battery operations

8. Synchronization and Stability in Network of Inverters

9. Non-Stationary signal analysis of stochastic processes

10. Instantaneous frequency analyzer in a Suitcase

11. Energy for PEACE: Microgrid Energy Management System for a remote area in Colombia

12. Identification of Instantaneous Frequency in maritime power systems

13. Suitcase for electrical signal analysis in ships and microgrids

14. Application of EMD to Power Quality Analysis in Power Systems

15. Smart grid online identification and stability analysis

16. Resonances and oscillatory phenomena in network of inverters

17. Xsens project acustic or doppler

18. Wave energy control based on instantaneous frequency tracking

19. Harmonics Management by data analysis, identification and control

20. Control of wireless power transfer systems for marine applications

21. Resonant wireless power transfer in subsea applications

22. Siemens project on BEMS in ships

23. Control of BLDC motors for high payload industrial drones

24. Electrically Actuated Safety Valves

25. Stability Characterization of Solar Microgrids

26. Encoder Initialization of Elasticaclly Locked Rotor

1. David and Goliath: a new concept of dry single-channel EEG for brain health monitoring

This project is part of a larger project with 3 PhD students and one Post Doc under the NTNU Enabling Technologies Strategic Area. The project is in collaboration with the Department of Electronics Systems, Developmental Neuroscience Laboratory and the Department of Circulation and Medical Imaging of NTNU.

Traditionally EEG signals are recorded by several electrodes placed in a regular pattern on the scalp. To ensure stable and reliable readings a type of gel is usually applied to the scalp. The resulting procedure is both time consuming, expensive and uncomfortable for the patient.

As an alternative to the traditional method, single-channel EEG with single, dry, wireless, electrodes has been suggested. This simplified approach requires advanced electronics, signal processing and system identification competences. A team working towards such solutions is being built up, and Master students with background in electronics, signal processing, embedded technologies are required.

 The research task will include: 

  • Development of an “in-house” single wireless dry electrode EEG system that can overcome the low SNR of dry sensors.
  • A main result of the study will be specifications for an ASIC (application specific integrated circuit) for optimized readout and digital transformation of the EEG sensor signal including wireless communication.

Supervisor: Marta Molinas,

Co-supervisors: Lars Lundheim, Trond Ytterdal, Audrey Van Der Meer, Nils Kristian Sjkaervold

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,  

Co-supervisor: NTNU Dept. of Electronics, Lars Lundheim,

3. 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 ( 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,

Co-supervisor: Geir Kulia,

4. 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,

Revolve contact person, Maria Dyrseth,,

Project webpage:

5. Optimal Design and Operation of H2 Fuell Cell Powered Passanger Ferry

High speed passenger ferries are an important mode of transport for the coastal communities in Norway, however it is also the mode that has the highest GHG emissions per passenger km. The hydrogen fuel cell is the only feasible zero emission energy source in the near future for high speed passenger ferries that need to travel any significant distance.

In this project, the electrical energy system on the ship, with a hybrid configuration of fuel cells and batteries, will be modelled. Then the model will be used to optimize the system design (dimensioning of components) and optimize the operation of the energy management system to minimize operational costs. The system model will be implemented in MATLAB Simulink.

This project will be in collaboration with IFE, and will be part of several similar ongoing projects at IFE. A summer job relevant to the topic will be offered at the IFE Kjeller campus.

There is possibility for a summer job at IFE.

Supervisor: Marta Molinas

Co-supervisors: Mehdi Zadeh, Fredrik Aarskog, Mohsen Vatani (IFE)

6. Battery Systems Data Analysis

As focus is shifting from automation to autonomous in various applications, it is essential to understand the behavior of battery systems under various operating scenarios. In addition, the performance batteries change as the number of cycles increase and the change is also dependent on the type of application (depth of discharge per cycle and variation of environmental conditions etc.).
There are lot of sources available for collecting cell/battery related data: data sheets, test data, online resources etc. This work focuses on collecting, analyzing and quantifying the cell/battery behavior and develop a framework to use the data for further utilization in autonomous operations.
1. Review of data sources and types of data
2. Framework for data categorization of data types
3. Quantifying the cell behavior (variation with age, cell type, type of application, temperature etc. ) with equivalent circuit/empirical models

Supervisor: Marta Molinas

Co-supervisors: Rambabu Kandepu, 

7. Prognostic System Framework for Battery Operations

The main objective of this work is to propose a prognostic system framework for energy storage system, in particular, battery system.
• Review of prognostics system approaches with focus on battery systems
o Modeling: Physics-based, data-driven
o Diagnostics approaches
o Prediction methods

Supervisor: Marta Molinas

Co-supervisors: Rambabu Kandepu, 

8. Synchronization and Stability in Network of Inverters

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,

Co-supervisor: Dr. Zhang Chen, Prof. Jon Are Suul,  

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,

Co-supervisor: Dr. Maximiliano Bueno Lopez, 

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,

Co-supervisor: Geir Kulia,

11. Energy for PEACE: Microgrid Energy Management System for a remote area in Colombia

After the PEACE agreement has been signed in Colombia in 2016, different energy projects have been developed in the rural sector in Colombia. The projects’ goal is to provide clean technologies to people in remote areas in order to increase their productive capacities and improve their quality of  life. Production processes in these areas stimulate economic growth, generating new income alternatives that result in social well-being. Some of the main challenges of these projects are the Social Appropriation of Knowledge and Technology Transfer to ensure  Project Sustainability. How can we make the members of the communities where the projects are developed understand the functioning of the generation systems? An alternative to this is to design and implement monitoring interfaces that allow a clear visualization of the system's performance. In this project, the students will design, implement and deploy on-site the technologies needed to build an interface that is both affordable and easy to implement in a rural context in Colombia, taking into account the limitations that could exist in real applications.

This project can be in collaboration with Engineers Witout Borders - IUG Norway  and the volunteer organization ren-PEACE

Supervisor: Marta Molinas,

Co-supervisor: Dr. Maximiliano Bueno Lopez, , Prof. Jon Are Suul

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.

Supervisor: Marta Molinas,,

Co-supervisors: Prof. Mehdi Zadeh, Dr Zhang Chen 

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.

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,

14. Application of EMD to Power Quality Analysis in Power Systems: Detection of flicker source in power system

In recent years, the proliferation of nonlinear load in the electricity network introduced new forms of power quality issues that are a concern for both consumers and utilities. One important power quality issue is flicker. Detection of flicker source’s place is the first step to mitigate flicker in power systems. Empirical Mode decomposition (EMD) is a new nonlinear decomposition method that breaks an input signal into different frequency modes. This project will focus on detecting flicker sources by using EMD and compare with typical tools used for the same purpose. The work will be a mix of power quality of power system and signal analysis.

Supervisor: Marta Molinas,,

Co-supervisors: Olav Fosso, Jalal Khodaparast 

15. 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,

Co-supervisor: Dr. Jalal Khodaparast

16. Resonances and Oscillatory Phenomena in Network of Inverters

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. 

Supervisor: Prof. Marta Molinas,;

Co-supervisor: Mehdi Zadeh, Jon Are Suul

17. Xsens project acustic or doppler

Supervisor: Prof. Marta Molinas,;


18. Wave Energy Control based on Instantaneous Frequency Tracking

Wave energy converters (WECs) are usually designed to match their frequency responses to the predominant wave spectrum, or sea state, of an installation site. Since real ocean waves are non-stationary by nature, and wave profiles with different spectral characteristics occur over time, control systems are employed to improve the energy conversion performance of the WEC for sea states other than the design sea state. In this framework, a number of control strategies rely on tuning the parameters of the power take-off system to the frequency of waves.  Thus, the frequency that best characterizes the incident non-stationary wave field should be determined. This project will investigate several frequency identification methods to answer the question "which frequency best characterizes the wave field for a given WEC and sea setting?". The Hilbert-Huang transform (HHT), Kalman Filter variants, Wavelet, and Frequency locked loops among others will be implemented and their respective energy yield will be assessed. The HHT is an analysis method that calculates the instantaneous frequency of nonlinear and non-stationary signals [1].

[1] Paula Garcia Rosa, Geir Kulia, John Ringwood, Marta Molinas, Real-Time Passive Control of Wave Energy Converters Using the Hilbert-Huang Transform, IFAC-PapersOnLine,Volume 50, Issue 1, July 2017, Pages 14705-14710

Supervisor: Prof. Marta Molinas,

Co-supervisors: Olav Fosso (, Paula Garcia Rosa (

19. 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, passive components) interact, are becoming prone to harmonics pollution. A mathematical model that describes accurately the physical behavior can be a challenging task in a large scale system. 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 (Bayesian Filters: Kalman Filters, Least-Squares, Particle Filter, Prony Analysis) 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 or isolated solar microgrids). 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,

Co-supervisors: Jalal Khodaparast,; Olav Fosso,

20. 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: Prof. Jon Are Suul, 

Co-supervisors: Marta Molinas,, Dr Giuseppe Guidi,

21. 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. (

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: Prof. Jon Are Suul, 

Co-supervisors: Marta Molinas,, Dr Giuseppe Guidi,

22. 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,

Co-supervisor:  Prof. Mehdi Zadeh, Prof. Jon Are Suul, 

23. Control of BLDC Motors for High Payload Industrial Drones

Alva Motor Solutions (Alva Industries AS) is a spin-off company from NTNU developing a new production method for electric composite motors. The motors have lower weight, higher efficiency and higher precision than conventional electrical machines, and can be produced more flexible and at a lower cost. In certain segments, recent tests already show a preliminary +20% torque increment and -76% cost decrement, compared to state-of-the-art. Alva has received 2.3MNOK in funding and currently consists of 6 full-time employees. The beach head market is industrial UAV's, with an estimated market entry in 2020. Alva can offer the following:

  • Working with an interdisciplinary team at NTNU Gløshaugen.
  • A larger budget for materials and resoruces
  • Involvement in customer meetings, strategic decisions, etc.
  • Cooperation with other master students and post docs completing their theses for Alva.
  • Shares of the company

Slotless permanent magnet brushless DC (BLDC) machines are very much suitable in applications like drone vehicles due to its simple stator construction, light weight, and high efficiency due to less losses.

Generally, there are two motor types used for the light weight drone applications.  Those are Permanent Magnet Synchronous motor and Brushless DC machine. The main purpose of the thesis is developing the three-phase inverter and control system for the propulsion application like drones. The tasks include understanding the principal of BLDC motors and study different control techniques based on both sensor and sensor-less methods by developing the Simulink model of BLDC drive.  By comparing different control techniques, the student should select the suitable control system for Alva's slotless BLDC motor.

To summarise, the main aim of the thesis is development and testing of Ironless drive system.

  • Development of suitable controller for different type of electrical machines (ironless) used for propulsion market.
  • Development of control algorithms for Ironless electrical machines using matlab/Simulink
  • Software implementation for DSP or other
  • Hardware implementation and development of test bench
  • Testing and verification
  • Documentation

Supervisor: Marta Molinas, 

Co-Supervisor: Dr Ravindra Ummanenis, Alva Industries AS, 

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

24. Electrically Actuated Safety Valves

A solution for electrically actuated safety valves will be analysed, designed and simulated. The task is part of a larger project that is developing an all-electric solution for subsea production in collaboration with industry.

Supervisor: Marta Molinas and post-doc to be hired

Contact person: Stig Moen,

25. 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,

26. Encoder initialization of elastically locked rotor

The main motivation for the project is to solve encoder initialization problems with hanging loads , e.g. for winches.

Incremental encoder provides (if it is connected correctly and pulse count is set correctly) a relative position to the rotor, i.e., real rotor position plus a constant. This constant is new every time voltage is applied, as opposed to an absolute decoder that gives the same constant until it is replaced. Encoder initialization consists in finding this constant. Traditional free-rotor encoder initialization is done by setting out a constant current vector in the stator. Given some friction, rotor will eventually adjust after this, and one now knows the constant offset. Another variant is to send voltage pulses or the like to try to find the current position after the response to the power pulses, but these depend on motor design and often that the rotor is at standstill (high inertia).  

The new method invented by Rolls-Royce in Trondheim helps to solve the above problems. The project implies implementing and testing the new method using a Vacon frequency drive for driving a winch. The project will require a bit of programming/PLC experience.

Supervisor: Prof. Marta Molinas,

Co-supervisors: Dr. Tore Skjellnes,, Rolls-Royce Marine AS

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