Electrical Engineering

This introductory semiconductor course is specifically designed for interdisciplinary learners. Leveraging professors from STEM (engineering, science, engineering, electrical engineering, and computer science) backgrounds, the course utilizes unit-based thematic teaching to help students understand semiconductor terminology, principles, and forward-looking applications, while also developing their ability to plan for further learning. The course features a holistic overview and does not emphasize related mathematical theories; therefore, it also serves as a general introductory course in contemporary materials science, suitable for students of all backgrounds and academic levels (including graduate students) interested in semiconductor technology. As an introductory course for interdisciplinary learners, this course first provides an overview of the current semiconductor world and how self-learners can modularly understand semiconductor technology. It then explores forward-looking chip applications and AI development to help students understand the importance of semiconductors for future societal development and even human civilization, and why undergraduate and graduate students should study semiconductor general knowledge. The course then progresses through basic solid-state physics and chemistry, materials and components, process equipment, and smart manufacturing modules, concluding with a comprehensive reflection on chip globalization and AI development. There are no exams for this course. Students  integrate the knowledge they have acquired and explore a personalized learning map by submitting handwritten study notes, group discussion assignments, and final forum poster activities.

This course gives students an overview of how to create projects in electronics. The course covers a basic overview of electronics, solder skills, use of computer chips (“microcontrollers”) to make sound, control lights, and move things, use Arduino and other easy/fun microcontroller development boards, modify (“hack”) existing programs for controlling electronics with microcontrollers, basics of how to make sound with microcontrollers (“Digital Signal Processing”), read a schematic diagram, use solderless breadboards (to quickly make electronic projects), use some tools for debugging projects, design solder boards (“Printed Circuit Boards”) using software (using KiCad), principals of Open Source, patents, project names, and Intellectual Property, skills to manufacture projects (both small-scale and mass-production), basics of starting one’s own small business, and principals of entrepreneurial thinking and hacker’s mindset. The course uses, as an example, a project called “TV-B-Gone universal remote control”, which was invented by the course instructor. With the ideas learned through the TV-B-Gone project, students are then in an excellent position to apply the lessons learned to come up with their own project ideas, and implement them in small groups and with their own projects, and present them at the end of the class.

This course provides the knowledge needed to participate in development and control of drivetrain in modern electric vehicles and in wind power generation. Lectures and arithmetic exercises include the following: Modulation and Current Control methods for power electronic circuits. This is a repetition of required prior knowledge built in the preceding course EIENnn “Power Electronic Control and Design Project”. EV drivetrains design based on vehicle performance requirements. Battery voltage level, Power electronic switching frequency, Maximum vehicle speed, Acceleration requirements, hill climbing requirements, Size requirements, Number of gears. Wind turbine design based on performance requirements. Turbine Size and rotor speed range, mechanical and electrical transmission, power optimization dependent on wind speed, ancillary services requirements. Modelling of electrical machines. Torque map, flux map, voltage limitation, current limitations, optimal operating points. Applications on both EV drives and Wind power generation. Control of electrical machines. Optimal operating points, Torque control, Magnetic flux limitations, Field weakening control, Applications on both EV drives and Wind turbines. Simulation tasks and laboratory work include electric machine (PMSM) in a vehicle drive system and electrical machine (PMSM) in a wind power system. These labs are prepared through simulation work, which is reported as a homework before the lab. After the laboratory, a report is written where simulations and measurements are compared. Assumed prior knowledge: EIENnn Power Electronic Control and Design Project, ESSF01 Analogue Circuits, ESS030/ESSF20 Physics of Devices, ESSF15 Electrical Engineering (EE, WE), MIE012/EIEF35 Electrical Engineering, basic course (ME)or EITF90 Electromagnetics and Electronics (FE) and FRT010/FRTF05 Automatic Control, Basic Course.

The widespread adoption of deep learning methods has been largely driven by the availability of easy-to-use systems such as PyTorch and TensorFlow. However, it is less common for users to explore the internals of the libraries and understand how they function, as well as how to optimize the high-level code for hardware systems. When deep learning algorithms are deployed into custom hardware, they are often modified to run faster and more efficiently. This course provides students with the basic concepts and principles of modern deep learning systems, and it explores how optimizations can be applied from both the software and hardware aspects of the system stack.

This course gives a fundamental understanding and an experimental experience of ultrasound and gain insight in an expanding research area. Topics covered include ultrasound physics, transducer technology, diagnostic equipment technology, doppler, bio-acoustics, field characterization, airborne ultrasound, diagnostic application, non-destructive testing, sonar, and research projects at the department. Assumed prior knowledge: First Course in Physics

This course introduces the calculation methods and experience of manufacturing options used by engineers to design electromagnetic devices such as transformers, actuators, and electric machines. The aim of the design of an electromagnetic device is the desired function, integration, and rational manufacturing method, and thus this course develops the related and relevant skills and experience. The course provides theoretical knowledge though lectures, and the acquisition of modelling skills and experience through assignments and course projects. Assumed prior knowledge: EIEF15 Electrical Engineering (EE), ETE055, EITF85 Electromagnetic Field Theory (PhyE), MIE012, EIEF35 Electrical Engineering, basic course (ME), ETEF01 Electromagnetic Field Theory (MathE).

This course is driven by time series perspectives and short term statistical behavior, underpinned by digital signal processing and machine learning, which is appropriate for cash assets (stocks, bonds, currencies, portfolios) and futures. It therefore answers the needs of the rapidly changing global financial system which requires financial models to be adaptively inferred from the data. Students gain hands-on experience through structured Python assignments based upon time series models, robust estimators, subspace techniques, portfolio optimization, and data analytics on graphs. There are no particular prerequisites, although knowledge of estimation theory and statistics would be useful. 

The course providers the knowledge, skills, and experience from taking part in an industrially based mechatronic development project, which is conducted up to a working prototype. The principal design of the product has been formed in the course Applied Mechatronics. It is essential that the work is done in a team with competences from various fields. The project is done during two study periods. The course participants should develop the mechatronic parts of those projects or other purely mechatronic products. The development process starts with extensive information search, brainstorming, and evaluation, activities which often encompass 30-40% of the total workload. This has been done in the course EIEN65 Applied Mechatronics. Then follows in this course selection of concept, constructive design of the product idea, ordering of components, building, testing, and adjustments. The course concludes with the official presentation of the designed products, where representatives from industry, course leaders, and the press take part. Assumed prior knowledge: Applied Mechatronics.

The course covers how solar cells and photovoltaic systems technology work in different applications, especially when integrated into the built environment. In developing countries where many live outside the electric grid, standalone PV systems are also of great interest. The ability to design and optimize the performance of PV systems through computer simulations is an important part of the course. The course covers: energy knowledge and the problems connected to the use of energy; radiation physics, the annual irradiance distribution and the climatic conditions for using solar energy in Sweden; calculation of solar angels and the irradiance on different surfaces; the PN-junction and Solar cell physics and construction and function of a PV-module; function and performance of the components in the PV-system; batteries, power point tracker, DC-AC inverter, charge regulator; system design of standalone and grid connected systems; building integration of PV-system; hand calculation of economic profitability of PV-systems; calculations of climate impact of solar cells in carbon dioxide emissions; use of simulation programs; laborations and computer simulations; and studievisits to PV installations.  Assumed prior knowledge: Basic courses in electricity and electronics. Experience from the use of calculation program like Matlab and Excel.

This course provides knowledge about the most important power electronic circuit configurations, including both power semiconductors and passive components like inductors and capacitors in addition to how modulation and current control is done in the most relevant circuits. The course includes a project to design a power electronic circuit with a specific set of functional specifications. Participants develop and verify (electrically and thermally) a power electronic converter for a low power application like an electric scooter or bicycle motor drive. The battery supply and the motor are given, but the power electronic converter with its modulation and control are developed as a part of the course. Topics include diodes, transistors (BJT, IGBT, MOSFET), materials (silicon, silicon carbide), inductors, capacitors, sensors (current, voltage). Function, mechanical and thermal design, aging, drive and protection circuits, various bridges such as 1Q, 2Q and 3-phase 2- and multi-level converters, parasitic components, load currents, and earth currents, carrier modulation, sampled current control, tolerance band control of current, voltage control, switching power supplies, motor drive systems for DC and AC motors, solar cell converters, electric vehicle chargers, "Unified Power Flow Controllers" (UPFC), active power filters, and high voltage direct current (HVDC). Assumed prior knowledge: ESSF01 Analogue Circuits, ESS030, ESSF20 Physics of Devices, ESSF15 Electrical Engineering (EE) or MIE012, EIEF35 Electrical Engineering, basic course (ME) and FRT010, FRTF05 Automatic Control, Basic Course.