Projects

The project aims to advance Electric Propulsion Drive System (EPDS) Digital Twin (DT) technology for Software Defined Electric Vehicles (SDEVs), with a focus on achieving DT adaptive and intelligent levels. It addresses the need for efficient testing and evaluation of electric propulsion systems in line with EU clean energy transition goals. Leveraging the rapid development of DT technology, the project seeks to contribute to SDV technology through enhanced modeling, data gathering, IoT integration, and system optimization. Key challenges include lifecycle management, data processing, and real-time communication between physical and virtual systems. The project encompasses advanced modeling, data gathering, IoT, and communication infrastructure, system integration, optimization, and technology demonstration.

The CROSS project aims to strengthen the European Research Area by developing innovative tools to mainstream the new Charters´ principles, fostering organisational change and career interoperability. Key outputs include a Self-Assessment Competence Tool, a comprehensive Roadmap for transversal skills training, a Mentoring Handbook, a Roadmap for career counseling, an Intersectoral Collaboration Handbook, and an HRS4R Repository. These form a comprehensive set of career management services, which will be piloted and implemented across four intersectoral networks. The development of these resources will follow a co-creative process, engaging stakeholders across Europe, facilitated through the creation of our ResearchComp Community of Practice. This approach ensures their adaptability to diverse European ecosystems. A key component of CROSS is the creation of a platform designed to support institutions in obtaining the HRS4R award. This platform can also serve as a shared resource for all projects funded under this call, ensuring their continued use and expansion beyond the project’s lifecycle. By promoting organisational change, CROSS will benefit research-performing organisations and researchers at all career stages, significantly improving career prospects and delivering broader societal impact.

This project aims at enhancing expert workforce and digitalization in the field of fault diagnosis, condition- based maintenance of wind turbines and related components in the partner institutions by bringing innovation in higher education teaching and learning methods in wind energy and applied artificial intelligence for maintenance decisions, increasing its relevance for the labour market and the society as a whole. The project will help partners in Vietnam and Thailand to produce in-house human resources in the field of condition-based maintenance of wind energy, making both the countries independent of external consultants. The main objective of the project is to implement real problem-based teaching and learning methods in the curriculum of higher education institutions (HEIs) of the partner countries. The expertise and know- how of the EU partner universities and their long- term teaching and research in this field would make this project objective achievable. Moreover, this project will build the capacity to produce graduates with independent, global insight, interdisciplinary expertise, competence in wind energy, and intercultural expertise. The project will also help the EU partners to renew their education in renewable energy and build a sustainable flow of students in both directions.

Advancing education of engineers through AI for cyber-sustainable and energy-efficient union involves a collaborative ENERGYCOM network of Baltic, Scandinavic and Nordic institutions, including Kaunas University of Technology, Vilnius Gediminas Technical University, Riga Technical University, Tallinn University of Technology, University of Tartu, University of Vaasa and UiT The Arctic University of Norway. This network aims to address engineering education, focusing on cyber-sustainability and energy efficiency by integrating advanced AI-powered teaching and learning methods. Within this project, ENERGYCOM introduces AI-powered assistants into the learning ecosystem, preparing engineers to tackle global challenges in sustainability and cybersecurity while adhering to ethical principles. Key activities include workshops, express mobility programs, and academic exchanges covering fields such as like mechatronics, power systems, robotics, cybersecurity, artificial intelligence, and human-centric information systems. By integrating AI-driven tools into education, the initiative aims to prepare students and educators to think critically, solve complex problems, and develop sustainable and energy-efficient solutions. The network builds on the EU's strategic initiatives, such as the Digital Education Action Plan, Coordinated Plan on Artificial Intelligence and Cybersecurity Strategy, to strengthen digital competencies and promote sustainability.

Autonomous driving is no longer just an idea of technology vision, instead a real technical trend all over the world. The continuing development to a further level of autonomy requires more from energy optimization. The optimization of electric propulsion drive systems of self-driving electric vehicles by using autonomous and monitoring sensors are not often discussed. The goal of the proposal is to develop a specialized unsupervised prognosis and control platform for such energy system performance estimation. This goal requires the development of several test platforms and digital twins. A digital twin is composed of three components – the physical entities in the real world, their virtual models, and the connected data/view that ties the two worlds together.

Project goals Taking into account the relatively low automation and robotization of the traditional fossil fuels industry, a significant retraining is necessary for the workforce in transition to modern technological industrial sectors. This has to be done, in order for the potentially available workforce to meet the needs and requirements set by the modern mechatronics oriented industry, which actively implements the Industry 4.0 ideology. To meet those requirements, the project proposes retraining courses for the soon-to-be-available workforce. The topics covered by the retraining are electrical drives, automation, robotics, power electronics, and condition monitoring of industrial systems. These separate fields are strongly interconnected and overlapping, and together with the connection point of IT technologies, they can be considered the main technological pillars of modern mechatronics oriented industry.

The objective of the EEV5040 Industrial Automation and Drives activity is to introduce students to the importance of industrial automation and electric drives and the latest trends in these fields (including IoT). As a result of the development activities, students will acquire in-depth knowledge of electric drive management, model-based design methodology and IoT applications in industrial automation in the future. They are able to create, adapt and analyse electric motor control systems and solve real problems in this field. These results influence the quality of industry-specific ICT teaching, providing students with the practical skills and knowledge essential to today's industrial automation. Within the framework of the development project, the subject EEM0040 Machine vision is also amended, where the traditional machine vision curriculum is added to it by adding the hyperspectral technology component. The aim of the development activity is to combine concepts of machine vision with hyperspectral data processing. Within the subject, students will develop practical skills in the use of hyperspectral cameras, from camera setup to processing of various hyperspectral images. They acquire knowledge of the specifics of hyperspectral data, such as the wavelength spectrum and its relationship to the properties of materials. In addition, they learn the methods of machine vision, which allow to identify different objects and characteristics from hyperspectral images.

The project is primarily aimed at counteracting the negative impact of the COVID-19 pandemic on the academic education process at technical universities. In accordance with the restrictions and with an aim to prevent spread of the virus many universities made a decision to transfer all studies, including practical classes, at fully online from. Due to that fact that practical classes were either not implemented at all or were carried out in a very narrow and simplified (impractical) manner. The goal of the RELABEMA project will be the development of a set of laboratory exercises in mechatronics and electric drive and their integration into a commonly used e-learning tool, which is the Moodle platform.

This project is a side project of the superior research project that has been supported by the Estonian Research Council under grant PSG453, "Digital twin for propulsion drive of an autonomous electric vehicle". It is conducted by the TalTech Mechatronics and Autonomous Systems Research Group. So far, the vehicle's drive but not the wheels' properties have been considered for the development of the digital twin. The task of this sub-project is the development of a test bench for wheels with the associated simulation. The influence of the different properties of wheels on the entire vehicle should be simulated as realistically as possible. Additionally, this project includes knowledge exchange and laboratory visits both in Germany and Estonia. The aim is to popularize knowledge among young people, introducing digital twins to aspiring engineers.