https://www.mdu.se/

Cyber Physical Systems (CPS) bridge the cyber-world of computing and communications with the physical world and require development of secure and reliable software. It asserts a big challenge not only on testing and verifying the correctness of all physical and cyber components of such big systems, but also on integration of these components. This paper develops a categorization of multiple levels of testing required to test CPS and makes a comparison of these levels with the levels of software testing based on the V-model. It presents a detailed state-of-the-art survey on the testing approaches performed on the CPS. Further, it provides challenges in CPS testing.

In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97 dB and 0.02 respectively and a significantly higher correlation coefficient (p < 0.05).

Safety in human-robot interaction can be divided into physical safety and perceived safety, where the latter is still under-addressed in the literature. Investigating perceived safety in human-robot interaction requires a multidisciplinary perspective. Indeed, perceived safety is often considered as being associated with several common factors studied in other disciplines, i.e., comfort, predictability, sense of control, and trust. In this paper, we investigated the relationship between these factors and perceived safety in human-robot interaction using subjective and objective measures. We conducted a two-by-five mixed-subjects design experiment. There were two between-subjects conditions: the faulty robot was experienced at the beginning or the end of the interaction. The five within-subjects conditions correspond to (1) baseline, and the manipulations of robot behaviors to stimulate: (2) discomfort, (3) decreased perceived safety, (4) decreased sense of control and (5) distrust. The idea of triggering a deprivation of these factors was motivated by the definition of safety in the literature where safety is often defined by the absence of it. Twenty-seven young adult participants took part in the experiments. Participants were asked to answer questionnaires that measure the manipulated factors after within-subjects conditions. Besides questionnaire data, we collected objective measures such as videos and physiological data. The questionnaire results show a correlation between comfort, sense of control, trust, and perceived safety. Since these factors are the main factors that influence perceived safety, they should be considered in human-robot interaction design decisions. We also discuss the effect of individual human characteristics (such as personality and gender) that they could be predictors of perceived safety. We used the physiological signal data and facial affect from videos for estimating perceived safety where participants’ subjective ratings were utilized as labels. The data from objective measures revealed that the prediction rate was higher from physiological signal data. This paper can play an important role in the goal of better understanding perceived safety in human-robot interaction.

This paper deals with a way to probabilistically guarantee reliable packet delivery in WirelessHART based networks suitable for industrial control systems. We propose a new scheduling scheme, called Iterative Probabilistic Scheduling with Adaptive Relaying (IPS-AR), which consists of a static part (IPS) and a dynamic part (AR). IPS takes into account the channel characteristics and exploits relaying to achieve a minimum reliability threshold as requested by the supported industrial application. In the AR part, each relay node decides the packet to be sent based on online assessment of both the number of consecutive errors experienced by previous packets belonging to the same flow, as well as the number of copies of the packet currently available at the other relay nodes. This enables IPS-AR to achieve the desired reliability level while using the available re-sources in terms of time and bandwidth more efficiently.

This paper covers a method for operator decision support, where physical simulation models are used to connect different physical variables to each other. By comparing energy and material balances for a larger process area inconsistencies in single process parts and sensor measurements can be detected, by following the development between single measurements and values predicted from the simulations. This information then can be used as input to e.g. a BN, Bayesian Network, for decision support. The application has been for a CFB boiler at Mälarenergi AB. The simulators have been made in Modelica respectively a more advanced model in APROS.

Software design for automotive systems is highly complex due to the presence of strict data age constraints for event chains in addition to task specific requirements. These age constraints define the maximum time for the propagation of data through an event chain consisting of independently triggered tasks. Tasks in event chains can have different periods, introducing over- and under-sampling effects, which additionally aggravates their timing analysis. Furthermore, different functionality in these systems, is developed by different suppliers before the final system integration on the ECU. The software itself is developed in a hardware agnostic manner and this uncertainty and limited information at the early design phases may not allow effective analysis of end-to-end delays during that phase. In this paper, we present a method to compute end-to-end delays given the information available in the design phases, thereby enabling timing analysis throughout the development process. The presented methods are evaluated with extensive experiments where the decreasing pessimism with increasing system information is shown.

The work presented in this paper is about the development of a collision avoidance systemfor a mobile telepresence robot developed by the company Gira technologies AB.The robot is designed to extend the length of time elderly can stay in their homes beforerequiring full-time staed care. The collision avoidance system is needed to help the userto avoid running in to objects or down a stairway. The design must be capable of beingimplemented at low cost, and should not look overtly "robotic" as this would not resultin an appealing industrial design.

Herein, dierent techniques are presented and analyzed to nd the best suitable solutionfor the robot. In particular a lot of work is done in taking measurements to nd theright characteristics for the sensors according dierent mounting angles, dierent objectsand distances. A solution is chosen and calculations are made to nd the best positionsto place the sensors to get the best results.

A complete solution is presented and implemented in the current system and testedto work as expected.

In Model-Driven Engineering bidirectional model transformations emerged as an important ingredient to cope with scenarios such as change propagation, synchronization and to keep consistent system views whenever changes occurring on some view have to be propagated over the others. However, bidirectional mappings open a number of intricate issues that have been only partially solved by research.

This master thesis identifies a set of features characterizing bidirectional transformations and validates them against two existing approaches. In particular, a benchmark based on the UML2RDBMS transformation and consisting of two different configurations is implemented by means of two different approaches, such as Triple Graph Grammars and the Janus Transformation Language, for understanding bidirectional transformations with respect to the elicited features.

Large penetration of distributed generation from variable renewable energy sources, increased consumption flexibility on the demand side and the electrification of transportation pose great challenges to existing and future electric distribution networks. This thesis studies the roles of several actors involved in electric distribution systems through electricity consumption data analysis and simulation models. Results show that real-time electricity pricing adoption in the residential sector offers economic benefits for end consumers. This occurs even without the adoption of demand-side management strategies, while real-time pricing also brings new opportunities for increasing consumption flexibility. This flexibility will play a critical role in the electrification of transportation, where scheduled charging will be required to allow large penetration of EVs without compromising the network's reliability and to minimize upgrades on the existing grid. All these issues add significant complexity to the existing infrastructure and conventional passive components are no longer sufficient to guarantee safe and reliable network operation. Active distribution networks are therefore required, and consequently robust and flexible modelling and simulation computational tools are needed for their optimal design and control. The modelling approach presented in this thesis offers a viable solution by using an equation-based object-oriented language that allows developing open source network component models that can be shared and used unambiguously across different simulation environments. 

Global smart metering market growth has increased significantly over the past few years and the trend is expected to continue. Smart metering technology enables energy consumption feedback and the adoption of dynamic pricing mechanisms that encourages users to shift power consumption from peak-use times to lower-use times, in order to help balance the load in the power system. In Sweden particularly, the introduction of the new legislation and adoption of remote meters in 2009, in combination with more flexible pricing schemes, offer a great opportunity for users to reduce energy consumption during peak times, increase their energy efficiency and therefore reduce their overall cost. More recently, in 2012, Swedish energy providers started offering hourly spot-based electricity price to homeowners in order give them access to pricing mechanisms that are closer to the real cost of electricity supply. Additionally to hourly pricing, other dynamic pricing contracts are available for consumers all across the country; however, conventional agreements that use fixed-rates for electricity are still the most common. This paper analyzes the economic impact for consumers, if dynamic pricing, enabled through smart metering technologies, is adopted. To achieve this, electricity costs from a large group of households were calculated, using users’ hourly consumption data with both conventional fixed rates and real time pricing, in order to understand their impact on customers’ bills. Obtained results suggest that real time pricing has great savings potential, especially for years where summer rainfall and winter conditions are within average. However, in order to increase savings and have them consistent year after year, changes in user time-of-use consumption profile are required. Moreover, this research work leads to further analysis on dynamic pricing combined with demand response in order to optimize electricity costs.

Nowadays stress is a frequent problem in the society. Stress level could be important in order torecognise health problems later.Electrocardiogram technics allows to supervise the heart condition and the detection ofanomalies about the patient.Sometimes data collection systems by sensors placed on the patient restrict his mobility.Therefore the elimination of wires is a good solution for this trouble. Then the Bluetooth protocol ischosen as way for transmitting and receiving data between stations. There are three ECG sensorsplaced on the right hand, the left hand and the right leg. It is possible to measure the heart signalwith this technique. Besides there is an extra sensor in order to measure the temperature of thepatient. Depending of the value of these parameters is possible to recognise stress levels. Allsensors are connected to a special box with a microcontroller which treats every signal. Thismodule has a Bluetooth part that transmitts wireless the new digital signal to the receiver. This onewill be a dongle connected to the computer by Serial Port.A program in the computer has been implemented in order to receive the Bluetooth Datasent from the box and saving the data in a file for subsequent activities.

Elvabrott och reaktiv effekt är två faktorer som förorsakar stora överkostnader vid samtliga elbolag. Dessa kostnader överförs i sinom tid till kunderna.Samtidigt mer och mer regler och normer kräver större tillsynt för kundernas fördel. Kostnaderna bör optimeras och information bli tillgängligare. Installationen av de nya fjärravläsningssystemen öppnar nya möjligheter för att förbättra dessa processer.Syftet med detta arbete är att undersöka och analysera processer och procedurer i tre elbolag för att hantera reaktiv effekt hos privatkunder och elavbrott.Resultatet visar att elbolagen är mycket konservativa med sina processer och fortfarande finns utrymme för flera förbättringar. Reaktiv effekt tas inte i beaktande och underskattas ordentligt av elbolag hos vanliga hushåll. Trots detta några försök att börja arbeta med den har redan införts. Däremot reaktiv effekt hos stora konsumenter och industri är med i detta arbete endast som ett exempel därför att där finns det omfattande kontroller och kompenseringar. Fokus i vårt fall ligger på hushåll.Angående elavbrott finns väl bestämda mekanismer. Analysen visar att det finns möjlighet att förbättra dessa processer genom att utnyttja de nya fjärravläsningsmätarna, GIS- och GPS-system.Det presenteras några lösningar där det anses vara nödvändigt men inte i den stora hela. Målet är att undersöka och beskriva processer inför framtida arbeten.

Software in modern industrial systems may have complex data dependencies. As a result of this, it can be hard for system developers to understand the system’s behavior, if they cannot explicitly see these dependencies. This thesis addresses this problem, with an emphasis on dependencies among data in systems built using the IEC 61499 standard. An analysis method was developed, with which we are able to extract data dependency information from basic and composite function blocks. The first step of handling this problem is to investigate how the data dependencies occur in IEC 61499. The second step is to create a formal definition of IEC 61499 elements that were needed in order to formulate the analysis method. Next, we define a dependency matrix, in which we store the information regarding dependencies between input and output data ports. Later, we formulate the necessary algorithms for data dependency analysis in basic and composite function blocks. Finally, the last piece of the puzzle is to develop a plug-in for Framework for Distributed Industrial Automation and Control – Integrated Development Environment. This plug-in is used to show that the analysis method is efficient and that the proposed analysis is applicable to IEC 61499 systems.

In Malardalen, Sweden a work is on-going to drive the region towards becoming fossil fuel free. To get rid of coal a decision has been made to build a waste combustion plant. The plant will have a fuel capacity of 200 MW thermal. There are also a number of biogas plants. One is recycling all the organic waste in the region, and combining with crop residues from the farmers. With planned expansions we will produce some 7 million Nm3/y, corresponding to some 9-10 MW HHV. This would make a total of some 500 GWh/y. Today the total consumption of fuels for vehicles is 2 TWh. With new technologies for cars and other vehicles we could take the consumption down to at least some 1 TWh/y. The methane then would cover 50% of the need. To this we add some 0.25 TWh extra electricity for cars used primarily in cities. Possibilities to reduce energy consumption and build renewable power like wind and solar power for both Sweden and EU27 is also discussed, where a special emphasis is made on possibilities to reduce energy consumption in process industries like metal, pulp and paper and cement. This includes increasing production efficiency by using on-line applications of simulation models. This also includes power plants. The conclusion is that it is possible to reach a balance in Malardalen region including Stockholm, and with a total of 3 million people, but also all Sweden.

The rapid growth of electric vehicles (EVs) is likely to endanger the current power system. Forecasting the demand for charging stations is one of the critical issues while mitigating challenges caused by the increased penetration of EVs. Uncovering load-affecting features of the charging station can be beneficial for improving forecasting accuracy. Existing studies mostly forecast electricity demand of charging stations based on load profiling. It is difficult for public EV charging stations to obtain features for load profiling. This paper examines the power demand of two workplace charging stations to address the above-mentioned issue. Eight different types of load-affecting features are discussed in this study without compromising user privacy. We found that the workplace EV charging station exhibits opposite characteristics to the public EV charging station for some factors. Later, the features are used to design the forecasting model. The average accuracy improvement with these features is 42.73% in terms of RMSE. Moreover, the experiments found that summer days are more predictable than winter days. Finally, a state-of-the-art interpretable machine learning technique has been used to identify top contributing features. As the study is conducted on a publicly available dataset and analyzes the root cause of demand change, it can be used as baseline for future research.

21st Century education and professional practice require novel engagement with ideas, technologies and toolsets. Virtual Reality (VR) and similar technologies are advancing rapidly, and protocols to understand, implement and measure the new values for design education which need to be further elaborated on. This paper discusses the impact of VR on craft and design in a university design class. A pilot was conducted to study students’ experiences and opinions around VR in craft and design in an advanced CAD design course. The findings indicate improvement in design and communication from the students’ perspective. This study suggests that VR can be an effective design tool integrated into design education.

The explosive development of wireless communication services creates a demand for more flexible and cost-effective communication systems that offer higher data rates. The obvious trend towards small-size and ultra low power systems, in combination with the ever increasing number of applications integrated in a single portable device, tightens the design constraints at hardware and software level. The integration of current mobile systems with the third generation systems exemplifies and emphasizes the need of monolithic multi-band transceivers. A long term goal is a software defined radio, where several communication standards and applications are embedded and reconfigured by software. This motivates the need for highly flexible and reconfigurable analog radio frequency (RF) circuits that can be fully integrated in standard low-cost complementary metal-oxide-semiconductor (CMOS) technologies.

In this thesis, the Voltage-Controlled Oscillator (VCO), one of the main challenging RF circuits within a transceiver, is investigated for today’s and future communication systems. The contributions from this work may be divided into two parts. The first part exploits the possibility and design related issues of wide-band reconfigurable integrated VCOs in CMOS technologies. Aspects such as frequency tuning, power dissipation and phase noise performance are studied and design oriented techniques for wide-band circuit solutions are proposed. For demonstration of these investigations several fully functional wide-band multi-GHz VCOs are implemented and characterized in a 0.18µm CMOS technology.

The second part of the thesis concerns theoretical analysis of phase noise in VCOs. Due to the complex process of conversion from component noise to phase noise, computer aided methods or advanced circuit simulators are usually used for evaluation and prediction of phase noise. As a consequence, the fundamental properties of different noise sources and their impact on phase noise in commonly adopted VCO topologies have so far not been completely described. This in turn makes the optimization process of integrated VCOs a very complex task. To aid the design and to provide a deeper understanding of the phase noise mechanism, a new approach based on a linear time-variant model is proposed in this work. The theory allows for derivation of analytic expressions for phase noise, thereby, providing excellent insight on how to minimize and optimize phase noise in oscillators as a function of circuit related parameters. Moreover, it enables a fair performance comparison of different oscillator topologies in order to ascertain which structure is most suitable depending on the application of interest. The proposed method is verified with very good agreement against both advanced circuit simulations and measurements in CMOS and bipolar technologies. As a final contribution, using the knowledge gained from the theoretical analysis, a fully integrated 0.35µm CMOS VCO with superior phase noise performance and power dissipation is demonstrated.

The significance of overload in power system has increased substantially due to of consumption and ambient temperature rise. An important consideration when evaluating the impact of overload is their on power system ambient tem-and load. Transformers are major components in power systems. The increase useful lifetime and hence abnormal temperature rise. Existing standards give a procedure to determine the capability of an existing transformers subject to overload problem and ambient temperature rise based on conservative assumptions .in addition, the temperature oil rise of power transformer due to overloading and ambient temperature are estimated based on power and cooling system, and the average daily or monthly temperatures to which a transformer would be subjected while in service. it is the purpose of this research of this effort to quantify the decreased life time due to overloading and the corresponding temperature rise in transformers. This is accomplished using a 2-D FEMLAB Model adapted for cooling simulation in power transformers.

Koldioxid är en central parameter för metabolismen i alla levande varelser. Hos människan regleras koldioxidhalten främst genom andningen. Därför är det viktigt att kunna mäta och övervaka koldioxidhalten i fysiologiska applikationer så väl inom sportmedicin som inom vården, till exempel på intensivvårdsavdelningar. Dessa mätningar kräver adekvat mätutrustning.

Syftet med denna avhandling är att kritiskt granska föreslagna metoder för övervakning av andningsaktiviteten, att föreslå och utveckla förbättringar, samt att föreslå och utveckla nya applikationer för mätning av koldioxidhalten i utandningsluften med hjälp av en elektroakustisk sensor.

Mätning av koldioxid i utandningsluften har den fördelen över andra föreslagna metoder för andningsövervakning att den även ger information om förhållandet i arteriellt blod då partialtrycket för koldioxid i slutet av ett andetag är lika stort som i artärblod hos lungfriska personer.

Den föreslagna tekniken bygger på en elektroakustisk sensor som kan registrera och mäta koldioxidhalten i utandningsluften om fukt- och temperaturvariationer utjämnas med hjälp av filter. Den elektroakustiska sensorn består av en ultraljudssändare och en reflektor placerade i varsin ände av ett perforerat rör. Den elektriska impedansen i sensorn representerar molekylvikten inne i sensorkaviteten. Molekylmassan har ett linjärt förhållande till koldioxidhalten så länge övriga gaser hålls konstanta.

Det faktum att partialtrycket av koldioxid i slutet av ett andetag kan mätas med den elektroakustiska sensorn gör den användbar i flera kliniska situationer om andra gaser inte kan påverka mätningarna.

Partialtrycket av koldioxid i slutet av ett andetag har visat sig vara användbar som en indikator för mjölksyratröskeln då personens individuella mjölksyratröskel infaller då partialtrycket av koldioxid i slutet av ett andetag börjar minska. Det ger en ny applikation inom sportmedicin. På det sättet är det möjligt för en idrottare att mäta variationerna i sin mjölksyratröskel, i sin egen sport på daglig basis, vilket kan användas för att optimera arbetsintensiteten under träning och tävling. Trots att det elektroakustiska sensorsystemet inte är selektivt för koldioxid och därför påverkas även av förändringar i syre i utandningsluften har det visat sig fungera i denna applikation.

På bilar med insprutningsmotorer behövs oftast någon typ av justering av bränsletryck då olika typer av belastning behöver olika mycket bränsle. Mängden bränsle motorn får styrs till viss del av spridarnas öppentider samt storleken på spridarmunstyckena. Men öppentiderna kan inte vara hur långa som helst samt storleken på spridarmunstyckena kan inte vara allt för stor heller då man bara har en viss tid på sig att trycka in bränsle under insugstakten[1] samt att man inte vill trycka in allt för mycket bränsle heller beroende på belastningen på motorn. Just för den anledningen används oftasten bränsletrycksregulator för sänka bränsletrycket när belastningen är låg och höja bränsletrycket när belastningen är hög. De flesta bränsletrycksregulatorer som sitter som standard på bilar är inte justerbara utan har oftast bara ett fast arbetsområde som styrs med hjälp av vakuum. Börjar man ta ut mer effekt ur en motor kommer det att behövas mer bränsle och ett sätt att få in mer bränsle men ändå behålla spridare och bränslepump är att byta ut den fasta bränsletrycksregulatorn mot en justerbar vilket innebär att man kan ändra arbetsområdet för bränsletrycket och därigenom få in mer bränsle under samma öppentid på spridare, vilket kan behövas vid t.ex överladdning. Den här rapporten kommer gå igenom hur ett trådlöst övervakningssystem för kontroll av bränsletryck kan konstrueras.

The proliferation of Electric Vehicles (EVs) poses new challenges for the Distribution System Operator (DSO). For example, the rectifiers that are used for charging EV batteries could significantly influence Power Quality (PQ), in terms of harmonic distortion. The emissions from individual EV, are well regulated by current harmonic emission standards. But what the aggregation of multiple EV loads will look like is still uncertain and the research being made in this area is still in its early stage. 

The DSO responsibilities include ensuring grid code compliance confirmed by PQ metering.  In general, 10 minute RMS values are sufficient. However, the large scale integration of non-linear loads, like EVs, could lead to new dynamic phenomena, possibly lost in the process of time aggregation.

In this thesis PQ and, in more detail, the concept of harmonics, and how this is related to EVs, is presented. A current-harmonic load model using power exponential functions and built from actual measurement data during the individual charging of four different fully electric vehicles was constructed. The model was based on individual emitted current harmonics as a function of state of charge (SOC), and was used to deterministically simulate the simultaneous charging of six vehicles fed from the same bus. The aggregation of current harmonics up to the 11th was simulated while randomizing battery SOC, the start of charging, and the kind of vehicle. Additionally, an investigation of the impact on aggregation in time was conducted.

The analysis clearly shows the importance of phase angle information, its correlation to SOC, and how the aggregation of EV loads is influenced by these factors. The analysis also shows that 10 minute RMS aggregation could lead to significant deviations from the “actual” (200ms) data.  This indicates that 10 minute value monitoring could lead to information losses.

This paper presents an aggregate current-harmonic load model using power exponential functions and built from actual measurement data during the individual charging of four dierent fully electric vehicles. The model is based on individual emitted current harmonics as a function of state of charge (SOC), and was used to deterministically simulate the simultaneous charging of six vehicles fed from the same bus. The aggregation of current harmonics up to the 11th was simulated in order to find the circumstances when maximal current-harmonic magnitude occurs, and the phase-angle location. The number of possible identical vehicles was set to four, while battery SOC, the start of charging, and the kind of vehicle were randomized. The results are presented in tables, graphs, and polar plots. Even though simulations did not consider the surrounding harmonics, supply-voltage variation, or network impedance, this paper presents an innovative modeling approach that gives valuable information on the individual current-harmonic contribution of aggregated electric-vehicle loads. With the future implementation of vehicle-to-grid technology, this way of modeling presents new opportunities to predict the harmonic outcome of multiple electric vehicles charging. 

Conservation voltage reduction (CVR) is based onthe premise that conserving energy by reducing voltage levels of the electrical system will lead to reduced electrical energy consumption. In this work a comparison-based method has been applied for assessing CVR effects in a distribution grid. The reference voltage on the secondary side of the primary substation was manually altered according to a predefined schedule during 6 months, that is, perform CVR on a substation and apply “normal” voltage to the same substation with a 2-week interval between the changes. Measurements (1 second RMS-values for voltages, active powers and reactive powers) and analysis were made at the 11 kV side of a 130/11 kV transformer of a primary substation, on outgoing feeders and at the 400 V side of 11/0.4 kV distribution transformers downstream of the primary substation as well as on downstream single rural and industrial customers. Active power at different reference voltage levels versus 24 hours divided into 10 minute intervals for reoccurring days of the week were plotted and analysed.

This work confirms the difficulties in obtaining predictable loads over time and to accurately analyse the load composition on all grid levels. Each are needed in order to quantify the effects of CVR and by extension optimising the grid operations without violating the power quality.

Mobile communication systems are experiencing a huge growth. While traditional communication paradigms deal with fixed networks, mobility raises a new set of questions, techniques, and solutions. This work focuses on wireless sensor networks (WSNs) where each node is a mobile device. The main objectives of this thesis have been to develop algorithms and protocols enabling WSNs with a special interest in overcoming mobility support limitations of standards such as Bluetooth and Zigbee. The contributions of this work may be divided in four major parts related to mobility support. The first part describes the implementation of local positioning services in Bluetooth since local positioning is not supported in Bluetooth v1.1. The obtained results are used in later implemented handover algorithms in terms of deciding when to perform the handover. Moreover local positioning information may be used in further developed routing protocols. The second part deals with handover as a solution to overcome the getting out of range problem. Algorithms for handover have been implemented enabling mobility in Bluetooth infrastructure networks. The principal achievement in this part is the significant reduction of handover latency since sensor cost and quality of service are directly affected by this parameter. The third part solves the routing problems originated with handovers. The main contribution of this part is the impact of the Bluetooth scatternet formation and routing protocols, for multi-hop data transmissions, in the system quality of service. The final part is a comparison between Bluetooth and Zigbee in terms of mobility support. The main outcome of this comparison resides on the conclusions, which can be used as a technology election guide.

The main scientific contribution relies on the implementation of a mobile WSN with Bluetooth v1.1 inside the scope of the ”Multi Monitoring Medical Chip (M3C) for Homecare Applications” European Union project (Sixth Framework Program (FP6) Reference: 508291) offering multi-hop routing support and improvements in handover latencies with aid of local positioning services.

This report is a master degree thesis in electronics that examines if weak relations can be used in TracFeed. TracFeed is a simulation tool designed to aid in the dimensioning of the power supply

system for electrical railroads. The program was originally developed by Adtranz and is today further enhanced by Balfour Beatty Rail AB.

When using weak relations there will be fewer truncations of the steps and therefore the response time will decrease. The purpose of this thesis is to study how much time that can be gained in

different types of simulations and in which way the result is effected because of weak relations. The theoretical part explains the fundamentals concerning electrical trains and how trains are

modelled in TracFeed. The calculation kernel used by TracFeed is called SIMPOW and it is described as well as the modelling language which is used to create the train models.

Weak relations are tested in two simulations. The result from those simulations shows that if a displacement in simulated time of the output is acceptable and there are many trains active

simultaneously weak relations are an interesting alternative.

In this article, a novel implementation of a widely used pseudo-two-dimensional (P2D) model for lithium-ion battery simulation is presented with a transmission line circuit structure. This implementation represents an interplay between physical and equivalent circuit models. The discharge processes of an LiNi0.33Mn0.33Co0.33O2-graphite lithium-ion battery under different currents are simulated, and it is seen the results from the circuit model agree well with the results obtained from a physical simulation carried out in COMSOL Multiphysics, including both terminal voltage and concentration distributions. Finally we demonstrated how the circuit model can contribute to the understanding of the cell electrochemistry, exemplified by an analysis of the overpotential contributions by various processes. 

Electric propulsion system in trains has the highest efficiency compared to other propulsion systems (i.e. steam and diesel). Still, electric trains are not used on all the routes, due to the high setup and maintenance cost of the catenary system. Energy storage technologies and the battery driven trains however, make it possible to have the electric trains on the non-electrified routes as well. High energy consumption of the electric trains, makes the energy management of such trains crucial to get the best use of the energy storage device. This paper suggests an algorithm for the optimal control of the catenary free operation of an electric train equipped with an onboard energy storage device. The algorithm is based on the discrete dynamic programming and Bellman’s backward approach. The objective function is to minimize the energy consumption, i.e. having the maximum battery level left at the end of the trip. The constraints are the trip time, battery capacity, local speed limits and limitations on the traction motor. Time is the independent variable and distance, velocity and battery level are the state variables. All of the four variables are discretized which results in some inaccuracy in the calculations, which is discussed in the paper. The train model and the algorithm are based on the equations of motion which makes the model adjustable for all sorts of electric trains and energy storage devices. Moreover, any type of electrical constraints such as the ones regarding the voltage output of the energy storage device or the power output can be enforced easily, due to the nature of the dynamic programming. 

This paper offers a solution for the optimal EMU train (Electric Multiple Unit) operation with the aim of minimizing the energy consumption. EMU is an electric train with traction motors in more than one carriage. The algorithm is based on dynamic programming and the Hamilton-Jacobi-Bellman equation. To model the train, real data has been used, which was provided by experts from Bombardier Transportation Västerås. To evaluate the model, some experiments have been done on the energy saving in exchange for the increase in the trip time. Moreover a simple accuracy factor is introduced to evaluate the accuracy of the model. The final goal is to use this approach as a base for a driver advisory system, therefore it is important to have the amount of calculations as minimum as possible. The paper also includes the studies done on the calculation time. The solution can be used for driverless trains as well as normal trains. It should be mentioned that this paper is a part of a research which is still in progress and the final model will also be used by Bombardier Transportation Västerås as an evaluation tool for the propulsions systems and trains.

Problem of optimal train control with the aim of minimizing energy consumption is one of the old optimal control problems. During last decades different solutions have been suggested based on different optimization techniques, each including a certain number of constraints or different train configurations, one being the control on the tractive effort available from traction motor. The problem is previously solved using dynamic programming for trains with continuous tractive effort, in which velocity was assumed to be the control variable. The paper at hand presents a solution based on dynamic programming for solving the problem for trains with discrete tractive effort. In this approach, tractive effort is assumed to be the control variable. Moreover a short comparison is made between two approaches regarding accuracy and ease of application in a driver advisory system.

Locally repairable codes (LRCs) have gained significant interest for the design of large distributed storage systems as they allow a small number of erased nodes to be recovered by accessing only a few others. Several works have thus been carried out to understand the optimal rate-distance tradeoff, but only recently the size of the alphabet has been taken into account. In this paper, a novel definition of locality is proposed to keep track of the precise number of nodes required for a local repair when the repair sets do not yield MDS codes. Then, a new alphabet-dependent bound is derived, which applies both to the new definition and the initial definition of locality. The new bound is based on consecutive residual codes and intrinsically uses the Griesmer bound. A special case of the bound yields both the extension of the Cadambe-Mazumdar bound and the Singleton-type bound for codes with locality (r, delta), implying that the new bound is at least as good as these bounds. Furthermore, an upper bound on the asymptotic rate-distance tradeoff of LRCs is derived, and yields the tightest known upper bound for large relative minimum distances. Achievability results are also provided by deriving the locality of the family of Simplex codes together with a few examples of optimal codes.

Microwave imaging is an efficient diagnostic modality for non-invasively visualizing dielectric contrasts of non-metallic bodies. An increasing interest of this field has been observed during the last decades. Many application areas in biomedicine have been issued, recently the breast tumor detection application using microwave imaging.

Many groups are working in the field at the moment for several reasons. Breast cancer is a major health problem globally for women, while it is the second most common cancer form for women causing 0.3 % of the yearly female death in Sweden. Medical imaging is considered as the most effective way of diagnostic breast tumors, where X-ray mammography is the dominating technique. However, this imaging modality still suffers from some limitations. Many women, mostly young ones, have radiographically dense breasts, which means that the breast tissues containing high rates of fibroglandular tissues. In this case the density is very similar to the breast tumor and the diagnosis is very difficult. In this case alternative modalities like Magnetic Resonance Imaging (MRI) with contrast enhancement and Ultrasound imaging are used, however those are not suitable for large scale screening program.Another limitation is the false-negative and false-positive rate using mammography, in general 5–15 % of the tumors are not detected and many cases have to go though a breast biopsy to verify a tumor diagnosis. At last the mammography using breast compression sometimes painful, and utilizing ionizing X-rays. The big potential in microwave imaging is the reported high contrast of complex permittivity between fibroglandular tissues and tumor tissues in breasts and that it is a non-ionizing method which probably will be rather inexpensive.

The goal with this work is to develop a microwave imaging system able to reconstruct quantitative images of a female breast. In the frame of this goal this Licentiate thesis contains a brief review of the ongoing research in the field of microwave imaging of biological tissues, with the major focus on the breast tumor application. Both imaging algorithms and experimental setups are included. A feasibility study is performed to analyze what response levels could be expected, in signal properties, in a breast tumor detection application. Also, the usability of a 3D microwave propagation simulator, (QW3D), in the setup development is investigated. This is done by using a simple antenna setup with a breast phantom with different tumor positions. From those results it is clear that strong responses are obtained by a tumor presence and the diffracted responses gives strong information about inhomogeneities inside the breast. The second part of this Licentiate thesis is done in collaboration between Mälardalen University and Supélec. Using the existing planar 2.45 GHz microwave camera and the iterative non-linear Newton Kantorovich code, developed at Département de Recherches en Electromagnétisme (DRE) at Supélec, as a starting point, a new platform for both real-time qualitative imaging and quantitative images of inhomogeneous objects are investigated. The focusing is related to breast tumor detection. For the moment the tomographic performance of the planar camera is verified in simulations through a comparison with other setups. Good calibration is observed, but still experimental work concerning phantom development etc. is needed before experimental results on breast tumor detection may be obtained.

Testing is a key activity in industry to verify and validate products before they reach end customers. In hardwarein- the-loop system-level verification of automotive systems, testing is often performed using sequential execution of test scripts, each containing a mix of stimuli and assertions. In this paper, we propose and study an alternative approach for automated system-level testing automotive systems. In our approach, assertion-only test scripts and one (or several) stimulionly script(s), execute concurrently on the test driver. By separating the stimuli from the assertions, with each assertion independently determining when the system under test shall be verified, we seek to achieve three things: 1) tests that better represent real-world handling of the product, 2) reduced test execution time, and 3) increased defect detection. In addition to describing our proposed approach in detail, we provide experimental results from an industrial case study evaluating the approach in an automotive system test environment.

Microwave imaging is an efficient technique to non-invasively visualizing dielectricproperties of non-metallic bodies. One potential of the technique is the high contrast in dielectricproperties between biological tissues. In the 80’s, Supélec developed a 2.45 GHz planarmicrowave camera, in the 90’s the group developed algorithms for quantitative microwaveimaging. The purpose of this study is to investigate the capability of these existing materials, oran extended version of them, in terms of quantitative imaging of high-contrast inhomogeneousobject for application of breast cancer detection. A two-dimensional formalization is consideredto be followed up with future three-dimensional investigations.

This dissertation presents a contribution to quantitative microwave imaging for breast tumor detection. The study made in the frame of a joint supervision Ph.D. thesis between University Paris-SUD 11 (France) and Mälardalen University (Sweden), has been conducted through two experimental microwave imaging setups, the existing 2.45 GHz planar camera (France) and the multi-frequency flexible robotic system, (Sweden), under development. In this context a 2D scalar flexible numerical tool based on a Newton-Kantorovich (NK) scheme, has been developed.

Quantitative microwave imaging is a three dimensional vectorial nonlinear inverse scattering problem, where the complex permittivity of an object is reconstructed from the measured scattered field, produced by the object. The NK scheme is used in order to deal with the nonlinearity and the ill-posed nature of this problem. A TM polarization and a two dimensional medium configuration have been considered in order to avoid its vectorial aspect. The solution is found iteratively by minimizing the square norm of the error with respect to the scattered field data. Consequently, the convergence of such iterative process requires, at least two conditions. First, an efficient calibration of the experimental system has to be associated to the minimization of model errors. Second, the mean square difference of the scattered field introduced by the presence of the tumor has to be large enough, according to the sensitivity of the imaging system.

The existing planar camera associated to a flexible 2D scalar NK code, are considered as an experimental platform for quantitative breast imaging. A preliminary numerical study shows that the multi-view planar system is quite efficient for realistic breast tumor phantoms, according to its characteristics (frequency, planar geometry and water as a coupling medium), as long as realistic noisy data are considered. Furthermore, a multi-incidence planar system, more appropriate in term of antenna-array arrangement, is proposed and its concept is numerically validated.

On the other hand, an experimental work which includes a new fluid-mixture for the realization of a narrow band cylindrical breast phantom, a deep investigation in the calibration process and model error minimization, is presented. This conducts to the first quantitative reconstruction of a realistic breast phantom by using multi-view data from the planar camera. Next, both the qualitative and quantitative reconstruction of 3D inclusions into the cylindrical breast phantom, by using data from all the retina, are shown and discussed. Finally, the extended work towards the flexible robotic system is presented.

Microwave imaging is recognized as an efficient diagnostic modality for no invasively visualizingdielectric contrasts in non metallic bodies. The usefulness of this modality results from the existingcorrelation between dielectric properties and quantities of practical relevance for industrial orbiomedical applications. At the beginning of the 80’s, Supélec developed a 2.45 GHz planarmicrowave camera, in the 90’s the group developed algorithms for quantitative microwave imaging.The purpose of this study is to investigate the capability of these existing materials, or an extendedversion of it, in terms of quantitative imaging of high contrast inhomogeneous object for application ofbreast cancer detection.

Microwave imaging is recognized as a potentialcandidate for biomedical applications, such as breast tumordetection. In this context a planar microwave camera isinvestigated for quantitative imaging of inhomogeneous objects.Promising simulation results indicates that the planar geometryis suitable for quantitative imaging, as long as the signal to noiseratio is higher than 40 dB. Different calibration techniques arediscussed with several proposed model improvements and thefirst reconstructed quantitative image of an inhomogeneous 2Dobject is obtained by using experimental data from the camera.

This paper deals with the breast tumor detectionability of a planar microwave imaging system. Indeed, microwaveimaging seems to have a significant potential in such a biomedicalapplication. By means of a numerical model based upon electricfield volume integral equations, we investigate the influence ofseveral parameters, such as the respective sizes of the breastand the tumor, the operating frequency and the electromagneticproperties of the different media, on the detection ability. Thelatter is estimated by comparing the scattered fields observed inthe presence and in the absence of tumor and by accounting forthe signal to noise ratio available with the experimental setupdeveloped at the laboratory.

Breast cancer is a global health problem, needing cheep and effective alternative diagnosis methods in order to minimize the mortality. This experimental study is performed in the context of an ongoing collaborative project towards a future planar three-dimensional microwave breast mammography system. Herein the first quantitative image of an inhomogeneous breast tumor phantom, composed by different Triton X-100/water/salt mixtures, is obtained by using the existing planar 2.45 GHz microwave camera.

Monitoring stress in real-time, in a non-laboratory environment can be benecial in several applications. One of these, which have been the motivation for this thesis, is to to perform this measurement during Attention decit hyperactivity disorder (ADHD) diagnosis. Monitoring several physiological responses to internal or external stimuli in a single soft-real-time system is nota solution widely used in an application like this. The thesis starts by studying several stress related responses in detail. Sensors for all of the responses are not implemented nor is it possible toimplement in to the desired system. After the study is was decided to implement two measurement modules. The first a Photo-plethysmogrophy (PPG) measurement module to measure heart rate and also estimate breathing. This module is prepared for estimating arterial blood oxygen levels but the calculation or verification have not been done. The second is Skin Conductance (SC) measurement module and in to both ofthese add a temperature sensor to measure the temperature of the skin. Time constraints limit the SC module to only be presented in theory. The PPG module on the other hand have been realisedin a prototype. This prototype performs the measurement in transmissive mode on the left earlobe, which leaves the hands free and it does not affect the hearing on that ear. The prototype giveout acceptable signal quality when good contact with the measurement site is achieved. The signalinterpretation, such as performing the signal analysis to count the beats per minute, is outside thescope of this thesis and will therefore not be presented but the signals can be seen in figures.

The advancement of Artificial Intelligence technologies has paved the way for the increasing use of autonomous systems in various fields, including air, land, and sea. Maritime is an important domain for applying autonomous systems, as collisions at sea can result in significant losses. How- ever, the development of autonomous systems in the maritime domain involves the collection of vast amounts of data from sensors on vehicles, which poses significant challenges in understanding the types of data collected from vehicle sensors and the corresponding data system requirements due to the large amount of data collected. To address this issue, this thesis proposes the use of Oper- ational Design Domain (ODD), inspired by the autonomous car domain, to structure and manage the data. An ODD taxonomy was designed with the help of BSI PAS 1883 and ASAM OpenODD concepts. This thesis presents an initial draft of the ODD taxonomy for the maritime domain, followed by the implementation of ODD samples on actual data. The work involved converting unstructured data into ODD-friendly data. The results of this thesis include an ODD taxonomy, a framework, and a use case demonstrating the application of these concepts to actual data. These results provide an example of how to manage large amounts of data in the autonomous maritime environment and facilitate further testing of autonomous systems in this domain. 

The task for this thesis was to develop, construct and evaluate a multi‐bus communication system,connected to a PC via USB and capable of communicating in CAN, I2C and SPI and develop drivers for itin National Instruments LabVIEW.In the beginning a study was made of the communication buses followed by an investigation of whattype of hardware that could accomplish this task. A microcontroller unit was selected andprogrammed in MikroElektronika MikroC Pro v.3.2 to act as the interface between the communicationbusses and PC. A PCB prototype of the system was constructed by using Eagle Cad software v.5.6.0. General drivers for this system where created in LabVIEW v.8.6.1 so the end‐user simply can createtheir own applications and control the compatible hardware depending on their type of purposes. Thesystem was tested on criteria’s such as: speed, power consumption, burst performance andtransmission length depending on which communication bus was used.

The harsh operating environment in a wastewater treatment process (WWTP) makes sensor faults commonplace. Detecting these faults can be challenging due to the complex process dynamics, unknown inputs, and general noise in the process and measurements. Comparing sensor readings against predictions from a physics-based or data-driven model of the WWTP is a common strategy for detecting such faults. In this work sensor measurements are directly modelled using Gaussian process (GP) regression, a data-driven multivariate approach. These GP sensor models are, with a generalised product of experts, combined into a dedicated fault isolation scheme resembling traditional observer bank methods. The residuals are monitored with a multivariate exponentially weighted moving average chart which is used for fault detection and isolation. The method is evaluated using simulated data generated with the Benchmark Simulation Model No. 1 WWTP. Fault detection performance is reported using several standard metrics such as false alarms, missed detections, time to detection, and successful fault isolations, with emphasis on reporting across a wide range of sensors and faults to provide a point of comparison for future studies. The proposed approach performs well across these metrics. Given sufficient data representative of normal operation, this approach can easily be adapted across a wide variety of plant configurations and can be used to create operatorfriendly diagnostics resembling classical control charts.

To prioritise which faults should be detected in a biological wastewater treatment process, and with what level of urgency, it is necessary to understand the effect that they have on the process. Using the Benchmark Simulation Model No. 1 and 2. (BSM1 and BSM2), several process and sensor faults were considered and their impacts on various cost, quality, and controller performance evaluation metrics analysed. Both the cost of treating the wastewater and the quality of the effluent were impacted in varying degrees of severity by the faults tested. The most influential faults in both models were decreases to autotrophic and heterotrophic growth rates, decreases to the heterotrophic death rate, and the inhabitation fault. It was shown that only larger fault sizes were significant, and the required speed of detection is dependent on the fault profile. Prioritising detection of the most influential faults was shown to have significant effects on monitoring requirements for fault detection and the subsequent complexity required of a fault detection system. A valuable takeaway was the similarity of results from BSM1 and BSM2; the consistency of the influential process faults suggests that systems that can be described by these models are likely affected by the same faults.

HF analysis of a horizontal dipole antenna buried in lossy ground has been performed in this paper. The soil is treated as a homogenous half-space of known electrical parameters. The authors compare the range of applicability of two forms of transmission line model , a hybrid circuit method, and a point-matching method in such analysis.

The purpose of this project is to analyze the economic parameters that affects the profits from a roof mounted solar cell installation for an agriculture company in Sweden. To analyze the different production type and the impact of the fraction self- used electricity is calculated with respect to the direction of the installation. The parameters that are affecting the profit are the yearly electricity production, the investment cost, the fraction self-used, the price of bought and sold electricity and any subsidies. The conclusion is that the type of production does not affect the self use as much and an installation facing south still have a higher self use due to the higher total electricity production. The most important factor for profit is the subsides, without subsidies the investment does not give a positive yield rate. In second place comes the orientation and the total investment cost. Two of the three companies studied would get 1-3% inflation compensated interest rate with 20% subsidies and the third, relatively located far up north, reached 1-2% inflation compensated interest rate with the same subsides. The lower interest rate comes from the lower yearly electricity production. Another 2 percentage interest rate can be added if the subsides of 40% is granted for all three of the studied companies. As complement to the already existent feeder cable a solar plant combined with a battery storage can support a new house on the property during summer. As a backup for a power outage, a solar plant and a battery costs more and does less than a tractor driven electric generator.

In this thesis we discuss and analyze aspects and methods for low-speed poeration, startup, and particularly rotational reversal for sensorless control of non-salient permanent-magnet synchronous motors (PMSMs), i.e., stabilization in the low-speed region. Furtermore, a speed and position estimation algorithm for speed-sensorless control of electrically excited synchronous machines (EESMs) with damper windings is developed. For EESM drives, an initial rotor position estimation algorithm is also developed. Regarding the PMSM drives, it is shown that the sensorless drive synchronizes from any initial rotor position, recovers from initial rotation in the wrong direction, and also reverses rotation without lockup or instability phenomena.

The result regarding sensorless control and preformance in the low-speed region are simulated and experimentally verified, which indicates that the proposed estimator is effective. An additional subject in this thesis is control traction converters. One major problem is that trains with pulse-width-modulation (PWM) converters have active input impedance; thus the phase shift between the input current and voltage is greater than +90 degrees or less than -90 degrees for a certain ferquency region. This may result in poor damping and in worst case unstable operation. Here, it is shown that via sophisticated current control and improved feed-forward, one may stabilize the system with respect to passivity.

An analytically extended function based on power-exponential functions is used in this paper for approxi- mation of electrostatic discharge (ESD) currents and their derivatives. The Marquardt least-squares method (MLSM) is applied for obtaining nonlinear function parameters. IEC 61000-4-2 Standard ESD current is approximated, as well as some measured ESD currents' wave shapes. Power-exponential terms are extended at the local maxima and minima of the represented wave shape, so that this approximation is done from peak to peak. ESD current derivative is approxi- mated using the same procedure in order to obtain the continuous second order derivative of the current, as all piecewise functions are of differentiability class C¹L . Currents and their derivatives are often measured in ESD experiments so that their analytical representation is needed for simulation of ESD phenomena, better definition of standard requirements, and computation of the transient fields and induced effects.