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Project detail
Duration: 01.05.2021 — 28.02.2025
Funding resources
Ministerstvo školství, mládeže a tělovýchovy ČR - Společná technologická iniciativa ECSEL
- whole funder (2021-11-01 - 2024-11-30)Evropská unie - Horizon 2020
- whole funder (2021-05-01 - 2024-04-30)
On the project
AI4CSM rewrite the auto industry’s competitive rules. Today, software, large computing power and advanced sensors,increasingly step into that role; they enable most modern innovations, from efficiency to connectivity, from autonomousdriving to electrification and new mobility solutions. The AI4CSM project aims at developing the new ECS architecture forelectric, connected and automated vehicles for the future mass market, enabled by embedded intelligence and functionalintegration for connected shared Mobility. AI4CSM will drive technology developments in the field of integrating newintelligent solutions in the propulsion, energy, perception, connectivity and brain domains of vehicles. Through this, AI4CSM will reinforce the user acceptance, affordability by convenience and services for the major transition to a diverse mobility.The outcome of AI4CSM is incorporating all the 4 major trends (electrification, standardization, automatization anddigitalization) which foster the progress and define the transition of the automotive industry and mobility. The climateneutrality, zero pollution Europe, sustainable transport and circular economy will be driven by the outcome of AI4CSM.
Mark
101007326/8A21013
Default language
English
People responsible
Bartík Ondřej, Ing. - fellow researcherBeneš Petr, doc. Ing., Ph.D. - fellow researcherBuchta Luděk, Ing., Ph.D. - fellow researcherCihlář Miloš, Ing. - fellow researcherDokoupil Jakub, Ing., Ph.D. - fellow researcherDoseděl Martin, Ing. - fellow researcherFialka Jiří, Ing., Ph.D. - fellow researcherGábrlík Petr, Ing., Ph.D. - fellow researcherHnidka Jakub, Ing., Ph.D. - fellow researcherHoreličan Tomáš, Ing. - fellow researcherChromý Adam, Ing., Ph.D. - fellow researcherJílek Tomáš, Ing., Ph.D. - fellow researcherKlusáček Stanislav, Ing., Ph.D. - fellow researcherKopečný Ladislav, Ing. - fellow researcherKozovský Matúš, Ing., Ph.D. - fellow researcherKozubík Michal, Ing. - fellow researcherLázna Tomáš, Ing., Ph.D. - fellow researcherOtava Lukáš, Ing., Ph.D. - fellow researcherPohl Lukáš, Ing., Ph.D. - fellow researcherSkalský Michal, Ing. - fellow researcherSvědiroh Stanislav, Ing. - fellow researcherVeselý Libor, Ing., Ph.D. - fellow researcherZezula Lukáš, Ing. et Ing. - fellow researcherVáclavek Pavel, prof. Ing., Ph.D. - principal person responsible
Units
Cybernetics and Robotics- beneficiary (2021-06-01 - 2024-05-31)Cybernetics in Material Science- responsible department (2020-04-16 - 2021-02-16)
Results
KOZOVSKÝ, M.; BUCHTA, L.; BLAHA, P. Implementation of ANN for PMSM interturn short-circuit detection in the embedded system. In IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. Singapur: IEEE, 2023. p. 1-6. ISBN: 979-8-3503-3182-0.Detail
SVĚDIROH, S.; ŽALUD, L. Atlas Fusion 2.0 - A ROS2 Based Real-Time Sensor Fusion Framework. In Lecture Notes in Computer Science. 14615. Springer Nature, 2024. p. 1-13. ISBN: 3031713966.Detail
ZEZULA, L.; BLAHA, P. Discrete-Time Modeling of PMSM for Parametric Estimation and Model Predictive Control Tasks. In IECON 2023: 49th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2023. ISBN: 979-8-3503-3182-0.Detail
BARTÍK, O. Parameter Estimation and Control Structure Synthesis for Oscillatory Mechanical Two-Mass Systems. IEEE Access, 2024, vol. 12, no. May, p. 77764-77773. ISSN: 2169-3536.Detail
BUCHTA, L.; KOZOVSKÝ, M.;. Online neural network application for compensation of the VSI voltage nonlinearities. In IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. Singapur: IEEE, 2023. p. 1-6. ISBN: 979-8-3503-3182-0.Detail
ZEZULA, L.; KOZOVSKÝ, M.; BLAHA, P. Diagnostics of Interturn Short Circuits in PMSMs With Online Fault Indicators Estimation. IEEE Transactions on Industrial Electronics, 2024, vol. 71, no. 11, p. 15001-15011. ISSN: 0278-0046.Detail
HAVRÁNEK, Z.; KOPEČNÝ, L.; DOSEDĚL, M.; HNIDKA, J.: HYBRID-ELDIAG; Module for detection of electrical fault in the propulsion using mechanical and acoustical quantities. Brno University of Technology Central European Institute of Technology Laboratory B1.04 Purkynova 656/123 612 00 Brno. URL: http://ai4csm.ceitec.cz/vysledky. (software)Detail
KRATOCHVÍLA, L.; ZEMČÍK, T.; BILÍK, Š.; CHROMÝ, A.: ASGARD-CLASS; System for detection and classification of obstacles through data-fusion of lidar and RGB cameras (ASGARD-CLASS). CEITEC, Purkyňova 123, B1.08. URL: https://ai4csm.ceitec.cz/vysledky. (software)Detail