SmartCorners | User-centred Optimal Design of Electric Vehicle with Smart E-Corners

Summary
In-wheel motors (IWMs) have become a mature technology that is well-suited for new user-centric electric vehicles (EVs). IWMs can be integrated in multi-functional and controllable modules consisting of the electric powertrain, friction brake and suspension/steering actuation. By combining several vehicle functionalities in a compact solution, the modules offer substantial opportunities to enhance the design and the operation of EVs. This is the starting point of the SmartCorners project. Using machine learning and AI, an adaptive multilayer control strategy will be implemented with historical and current data from the vehicle, its environment, and users, including relevant EV fleets. This approach will pave the way toward software-defined vehicles, ena-bling rightsizing, holistic optimisation, innovative fault mitigation and actuator allocation strategies as well as more efficient, adaptive, predictive, and personalised system operation. SmartCorners will bring a so far un-explored authority level over: i) vehicle design, through skateboard-like chassis configurations; ii) energy management aspects, covering pre-conditioning and predictive thermal management during EV operation; iii) comfort and functional aspects, in terms of user-centric cabin thermal management, and pre-emptive vehicle body control; and iv) dismantling process and recycling of the vehicle. The development and industrialization of the project outcomes will be accelerated by comprehensive and integrated simulation, design and validation methodologies to decrease development time and cost, and support the uptake of AI-based solutions. In con-clusion, SmartCorners will provide a significant competitive advantage of the European industry and contrib-ute to achieve key strategic orientations C and A of the EU Strategic Plan.
Results, demos, etc. Show all and search (1)
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101138110
Start date: 01-01-2024
End date: 31-12-2026
Total budget - Public funding: 6 317 719,99 Euro - 4 575 719,00 Euro
Cordis data

Original description

In-wheel motors (IWMs) have become a mature technology that is well-suited for new user-centric electric vehicles (EVs). IWMs can be integrated in multi-functional and controllable modules consisting of the electric powertrain, friction brake and suspension/steering actuation. By combining several vehicle functionalities in a compact solution, the modules offer substantial opportunities to enhance the design and the operation of EVs. This is the starting point of the SmartCorners project. Using machine learning and AI, an adaptive multilayer control strategy will be implemented with historical and current data from the vehicle, its environment, and users, including relevant EV fleets. This approach will pave the way toward software-defined vehicles, ena-bling rightsizing, holistic optimisation, innovative fault mitigation and actuator allocation strategies as well as more efficient, adaptive, predictive, and personalised system operation. SmartCorners will bring a so far un-explored authority level over: i) vehicle design, through skateboard-like chassis configurations; ii) energy management aspects, covering pre-conditioning and predictive thermal management during EV operation; iii) comfort and functional aspects, in terms of user-centric cabin thermal management, and pre-emptive vehicle body control; and iv) dismantling process and recycling of the vehicle. The development and industrialization of the project outcomes will be accelerated by comprehensive and integrated simulation, design and validation methodologies to decrease development time and cost, and support the uptake of AI-based solutions. In con-clusion, SmartCorners will provide a significant competitive advantage of the European industry and contrib-ute to achieve key strategic orientations C and A of the EU Strategic Plan.

Status

SIGNED

Call topic

HORIZON-CL5-2023-D5-01-01

Update Date

12-03-2024
Images
No images available.
Geographical location(s)