Project detail

AI4CSM - Automotive Intelligence for/at Connected Shared Mobility

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 researcher
Beneš Petr, doc. Ing., Ph.D. - fellow researcher
Buchta Luděk, Ing., Ph.D. - fellow researcher
Cihlář Miloš, Ing. - fellow researcher
Dokoupil Jakub, Ing., Ph.D. - fellow researcher
Doseděl Martin, Ing. - fellow researcher
Fialka Jiří, Ing., Ph.D. - fellow researcher
Gábrlík Petr, Ing., Ph.D. - fellow researcher
Hnidka Jakub, Ing., Ph.D. - fellow researcher
Horeličan Tomáš, Ing. - fellow researcher
Chromý Adam, Ing., Ph.D. - fellow researcher
Jílek Tomáš, Ing., Ph.D. - fellow researcher
Klusáček Stanislav, Ing., Ph.D. - fellow researcher
Kopečný Ladislav, Ing. - fellow researcher
Kozovský Matúš, Ing., Ph.D. - fellow researcher
Kozubík Michal, Ing. - fellow researcher
Lázna Tomáš, Ing., Ph.D. - fellow researcher
Otava Lukáš, Ing., Ph.D. - fellow researcher
Pohl Lukáš, Ing., Ph.D. - fellow researcher
Skalský Michal, Ing., Ph.D. - fellow researcher
Svědiroh Stanislav, Ing. - fellow researcher
Veselý Libor, Ing., Ph.D. - fellow researcher
Zezula Lukáš, Ing. et Ing. - fellow researcher
Václavek 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

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

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

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

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

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

SVĚDIROH, S.; CHROMÝ, A.; ŽALUD, L.: ASGARD-RTFMAP; System for building an object-based 3D map of surroundings and its sharing among vehicles in the real-time (ASGARD-RTFMAP). CEITEC, Purkyňova 123, B1.08. URL: https://ai4csm.ceitec.cz/vysledky/. (software)
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