COURSE DESCRIPTION
The course goal is to understand the energy storage units of different batteries and fuel cells when used in electric vehicles. The choice of energy storage system, or the type or generation of battery or fuel cell, will ultimately control the performance. A careful selection of materials and components is necessary to implement optimal functionalities of the electrochemical cells. Of similar importance is the integration of the storage component within the vehicle and how it is monitored during use. Thereby, ageing can be mitigated, energy losses kept at a minimum, safety be assured, and health maintained.
Energy Storage for Electrification is a module of the larger course Learning Electromobility developed by the Swedish Electromobility Centre in collaboration with five leading Swedish universities. Designed for engineers and professionals in the transport and energy sectors, the course supports lifelong learning by offering in-depth knowledge of the technologies and systems that underpin the transition to electric mobility. To apply for the full course, click here: https://learning4professionals.se/showCourse/536/Learning_electromobility.
You can choose which modules to attend, allowing for a tailored learning experience based on your interests and professional needs. Each module includes preparatory materials, three interactive teaching sessions, and assignments that reinforce learning through real-world applications. When you have completed a module, you will receive a certificate indicating your achievements.
The course Energy Storage is divided into three parts:
Part 1: Principles of electrochemical energy storage.
This seminar will focus on operating principles and pros and cons of supercapacitors, batteries and fuel cells. Basic electrochemistry of supercapacitors, batteries and fuel cells. Cell components: anodes, cathodes, electrolytes, separators, current collectors. Summary of basic concepts and relevant properties of electrochemical energy storage devices.
Part 2: Batteries.
This seminar will focus on the lithium-ion and next generation batteries. Battery components and materials. Cells, modules and packs and cell formats. Cell and pack behaviour during different charge and discharge protocols. Battery ageing, diagnostics and safety. Next-generation batteries, including sodium-ion batteries and solid-state batteries. Battery cooling and auxiliary systems. Battery management systems. Vehicle integration.
Part 3: Fuel cells.
This seminar will focus on fuel cells. Principles of proton exchange membrane fuel cells (PEMFC). Fuel cell components, including gas diffusion electrodes, and fuel cell systems. Efficiency and thermal management. Ageing of fuel cells. Fuel cell vehicles and vehicle integration. Hydrogen generation and storage.
There are 3 live sessions: Monday and Thursday in week 43, and Wednesday in week 45. You will be invited to an introductory lecture in week 39.
Each session will be between 13:00-15:00, except the very first session that will be between 13:00-16:00, since it includes an introduction to the full Learning Electromobility course.
This course will take you about 15 hours to complete.
The learning outcomes of the course are:
This course is designed for professionals in the engineering and technology sectors.
This course makes you acquainted with the concept of systems-of-systems (SoS), which means that independent systems are collaborating. It gives you an understanding why SoS is an important topic in the current digitalisation and provides a theoretical and practical foundation for understanding important characteristics of SoS. It also gives you a deeper knowledge in a number of key concerns that need to be considered when engineering SoS. This is a course with a flexible start: If you are admitted, you may join the course any time between the course start in September 2025 until the beginning of October. With the recommended study pace of 25%, the course will take approximately seven calendar weeks to complete. Higher or lower study pace is possible as long as the course is finished no later than the end of the autumn semester.
The purpose is to give the students an overview of issues and methods for development and assurance of safety-critical software, including details of selected technologies, methods and tools. The course includes four modules: Introduction to functional safety; knowledge that give increased understanding of the relationship between Embedded systems / safety-critical system / accidents / complexity / development models (development lifecycle models) / certification / “the safety case”. Analysis and modelling methods; review of analysis and modelling techniques for the development of safety-critical systems. Verification and validation of safety critical software, methods and activities to perform verification and validation. Architectures for safety critical systems. Safety as a design constraint.
The aim of the course is to introduce the participants into methods and tools for verifying systems that need to react to external stimuli. The methods use system models with precise formal semantics and will span model-checking as well as deductive verification. A set of simple examples as well as real-world applications will be used throughout the course to illustrate the methods and their tool support. The objective of the course is to understand the underpinning theories of formal verification, and learn how to apply tool support in order to verify system models.
The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. About the course Smart Healthcare with Applications, 4 credits Who is this course for?The course suits you with any Bachelor’s degree (equivalent of 180 Swedish credit points / ECTS credits at an accredited university) who have an interest in applying Artificial Intelligence (specifically Machine Learning) to healthcare. Leadership/management experience in health-related organization/industry OR a Bachelor degree in computer science is advantageous. What will you learn from this course?Healthcare as a sector together with other health-related sources of data (municipalities, home sensors, etc.), is now in a place and can take advantage of what data science, Artificial Intelligence (AI), and machine learning (ML) have to offer. Information-driven care has the potential to build smart solutions based on the collected health data in order to achieve a holistic fact-based picture of healthcare, from an individual to system perspective. This course aims to provide a general introduction to information-driven care, challenges, applications, and opportunities. Students will get introduced to artificial intelligence and machine learning in specific, as well as some use cases of information-driven care, and gain practice on how a real-world evidence project within information-driven care is investigated. What is the format for this course?Instruction type: The lectures, announcements, and assignments of this course will be fully online via a learning management system and presented in English. Each lecture is delivered through a video conference tool with a set of presentation slides displayed online during each class session. Online practical labs (pre-written Python notebooks) are also provided in the lectures.
The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. About the course Critical design and practical ethics for AI, 3 credits Who is this course for? Artificial Intelligence (AI) is being increasingly implemented and used in society today. It has already proven to have an impact on the individual, organization and society, and this impact will most likely only increase. Therefore, it is important to understand the ethical issues that may arise from use of AI, as well as to adopt a critical stance to the technology’s impact. The course introduces critical and ethical issues surrounding data and society, to train the student to problematize and reason about artificial intelligence (AI). You are most likely a designer, innovator, or product manager that works with digital services and products. What will you learn from this course? The course deals with different perspectives on AI and its real and potential effect on organizations and society. The course is based on five different perspectives on AI: accountability, surveillance capitalism, power and bias, sustainability, and trust. The course material consists of recent and relevant literature on the impact of, and critical perspectives on AI. Active discussions founded in different ethical perspectives are also an important part of the course. What is the format of this course? This course is primarily self-paced, with a few synchronous meetings. Most activities are based on the student’s having consumed specified material beforehand, such as video lectures, podcasts, articles, and books. Active discussions, both in online forums and during synchronous meetings, are an important part of the course.
Do you want to learn the basics of Industry 4.0, at your own pace, whenever you want? Then the MOOC (Massive Open Online Course) Introduction to Industry 4.0 is for you. You will learn basic terminology and theory while gaining insight and understanding of the fourth industrial revolution and how it affects us. The MOOC: Introduction to Industry 4.0 is part of MDU's investment in smart production. The course is divided into ten modules, each of which describes different technologies in Industry 4.0. We estimate that it will take about 40 hours to complete the course and it is in English. The MOOC can also give you eligibility to apply for these 3 university courses at Mälardalen University: Internet of things for industrial applications, 5 credits Simulation of production system, 5 credits Big data for industrial applications, 5 credits