Anton Rassõlkin

Professor Anton Rassõlkini töö keskendub elektriajamite, mehatroonika ja autonoomsete süsteemide valdkonnale. Ta on lõpetanud Tallinna Tehnikaülikooli (TalTech) bakalaureuse-, magistri- ja doktorikraadiga elektriajamite ja jõuelektroonika erialal, ning omandas diplomeeritud inseneri kraadi automaatikas Saksamaal Giessen-Friedbergi rakenduskõrgkoolis.

Professor Anton Rassõlkin on Tallinna Tehnikaülikooli (TalTech-i) elektroenergeetika ja mehhatroonika instituudi professor ning mehhatroonika ja autonoomsete süsteemide uurimisrühma juht. Ta on ka TalTechi elektrotehnika ja mehhatroonika magistriõppekava programmijuht. Tema teadustöö keskendub elektriajamitele, mehatroonikale, elektrisõidukitele ja digitaalsete kaksikute (Digital Twin) arendamisele tarkvarapõhiste elektrisõidukite kontekstis.

Ta kuulub mitmesse teadusorganisatsiooni, sealhulgas IEEE-sse, kus ta on vanemliige ning täidab IEEE Estonia VTS (Vehicular Technology Society) sektsiooni esimehe rolli. Samuti on ta aktiivne liige Eesti Moritz Hermann Jacobi Seltsis. Professor Rassõlkin on aktiivselt osalenud mitmetes rahvusvahelistes teadusprojektides ning on pälvinud tunnustust nii Eestis kui ka rahvusvaheliselt. Tema publitseerimisportfell sisaldab üle 200 teadusartikli rahvusvahelistes eelretsenseeritavates teadusajakirjades ja konverentsikogumikes. Tema töid on korduvalt tsiteeritud ning ta on kuulunud Stanfordi Ülikooli ja Elsevieri koostatud maailma 2% kõige mõjukamate teadlaste nimekirja.

Mehhatroonika ja autonoomsete süsteemide uurimisrühma teadus- ja arendustegevus on suunatud nutikate lahenduste väljatöötamisele, integreerides omavahel tipptasemel autonoomsete süsteemide tehnoloogiaid. Lisaks teadusuuringute arendusele on oluline teadmiste ja lahenduste ülekandmine praktilistesse rakendustesse, edendades seeläbi valdkonna jätkusuutlikku kasvu ja arengut ka väljaspool ülikooli. Tänapäeval pööratakse tehnikavaldkondades suurt tähelepanu energiatõhususe ja efektiivsuse optimeerimisele erinevates kõrgtehnoloogilistes süsteemides. Ühe olulise näitena võib tuua töötleva tööstuse, kus automatiseerimine ja autonoomsed süsteemid mängivad võtmerolli tootmisprotsesside tõhusamaks muutmisel. Autonoomsete süsteemide põhieesmärk seisneb tihti tootlikkuse suurendamises, vähendades seejuures inimressursi kasutamise vajadust. Tööstuse automatiseerimine võimaldab täpsemat ressursside planeerimist ning energiakasutuse efektiivsemat kontrolli, aidates seeläbi kaasa keskkonnamõju vähendamisele. Seega ei tähenda protsesside automatiseerimine ainult majanduslikku kasu ettevõtetele, vaid toetab ka säästliku ja keskkonnasõbraliku tootmise initsiatiivi. Autonoomsete süsteemide arendamine on seetõttu oluline samm suunas, kus tehnoloogiline areng ja keskkonnasäästlikkus käivad käsikäes.
Mehhatroonika ja autonoomsete süsteemide uurimisrühma fookuses on autonoomsete süsteemide loomine ja rakendamine, elektrisõidukite alamsüsteemide uurimine, riist- ja tarkvara loomine, tajusüsteemide ning masinnägemise rakenduste väljatöötamine ning elektrimasinate arendamine ja diagnostikameetodid. Uurimisrühm pakub erialaseid ekspertiise, konsultatsioone, koolitusi ning teaduspartnerlust.

Projects and applications

Advanced Digital Tools to Accelerate the Development of Software-Defined Electric Vehicles
Team: Rolando Antonio Gilbert Zequera, Assem Reda Abdelhafez Fahim Meghawer, Mahmoud Ibrahim Hassanin Mohamed, Mahmoud Ibrahim Hassanin Mohamed, Diana Belolipetskaja, Hadi Ashraf Raja, Daniil Valme, Ojaswi bahadur Lakhey, Rolando Antonio Gilbert Zequera, Tiina Loit-Oidsalu, Anton Rassõlkin, Martin Võip
Year: 2025 - 2029
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.
Career Management Services for European Talents
Team: Tiina Loit-Oidsalu, Anton Rassõlkin, Ilona Oja Açik, Marju-Triin Pilt, Toomas Vaimann, Kaire Kaljuvee
Year: 2025 - 2028
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.
Enhancing Capacity in Condition-based Maintenance of Wind Energy
Team: Toomas Vaimann, Martin Sarap, Muhammad Usman Sardar, Hadi Ashraf Raja, Ants Kallaste, Tiina Loit-Oidsalu, Anton Rassõlkin
Year: 2025 - 2027
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.
Artificial intelligence–based adaptive drive control system
Team: Mahmoud Ibrahim Hassanin Mohamed, Anton Rassõlkin, Ekaterina Demiankova
Year: 2025 - 2026
The project will develop a smart, adaptive electric drive that increases the energy efficiency and reliability of electric vehicles. The innovative solution combines artificial intelligence-based control with advanced sensor technology, allowing the drive to adapt in real-time to changes in traffic and road conditions. The project will produce a laboratory prototype, a user-friendly software solution for data processing, and comprehensive documentation that will simplify the implementation of the system.
Advancing the Education of Engineers Through AI for Cyber-Sustainable and Energy-Efficient Union
Team: Anton Rassõlkin
Year: 2025 - 2026
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.
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