Diana Belolipetskaja

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 purpose of this project is to address the problems related to expert workforce in the field of diagnosis, monitoring, and maintenance of the power systems and related components in the partner countries by bringing innovation in higher education teaching and learning methods in order to fill the expertise gap and enhance its relevance for the labour market and the society as a whole. The project will help Nepal and Bhutan to produce in-house human resources in the field of condition monitoring of power equipment 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 HEIs of the partner countries. This is possible thanks to the expertise and know how of the EU partner Universities and their long term teaching in this field. The project will also help the EU partners to renew their education in this field and build a sustainable flow of students in both directions

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.