Framtida elektriska drivlinor för eMobility
- Diarienummer
- SM19-0036
- Start- och slutdatum
- 200101-240630
- Beviljat belopp
- 248 963 kr
- Förvaltande organisation
- ABB Power Grids Research
- Forskningsområde
- Informations-, kommunikations- och systemteknik
Summary
A formal long-term alliance has been signed in 2013 between CHALMERS and ABB covering both research and education in the areas of engineering sectors essential for developing Sweden’s future competitiveness. One of the research areas identified for mutual collaboration is eMobility Powertrains considering ABB’s strength with motor drive systems and CHALMERS expertise in vehicle powertrains. The individual mobility planned through this project proposal is to research into digital drive assisted predictive diagnostics for electric drivetrains using digital twins’ framework. Digital twins have potential use in the situations where predictive analysis is limited due to non-availability of data during abnormal operation. The mobility will include practical aspects of creating framework for digital twins, model-building for physical and accurate representation of the drivetrains and explore on advanced AI analytics for predicting potential failure diagnostics for better maintenance scheduling. The second objective of mobility is to define collaborative research framework for supervising PhD and post-doctoral students at CHALMERS with the high potential to integrate the research outcome into next generation ABB technologies. The applicant, Rahul Kanchan, is working as a principal scientist at ABB Corporate Research and brings a lot of domain competence in the field of advanced power electronics drives technology and electrical machines control.
Populärvetenskaplig beskrivning
The automotive industry has been continuously encouraged to move away from traditional fossil-based combustion vehicles to more environment friendly vehicles. Both off-road as well as on-road vehicles based on electric drivetrains are seen to be one of the best solutions, and this spurred the introduction of electric mobility – or e-Mobility – technologies. With the rapid demand and development of more electric vehicles, there is a critical need to assess and prepare for the impact of these technologies on vehicle drivetrains. The demand to reduce the cost and performance enhancement of the electric vehicles, most manufacturers are looking at various forms of electrical machine technologies with highly integrated power electronics converters. At the same time, the increased interconnectivity of electrical drives and various sensing technologies are opening up further possibilities for advanced predictive diagnostics for electric drivetrains using digital twins framework. The project aims at innovative e-drive trains solutions consisting of highly integrated machine-power electronic converters, assisted by revolutionary control and diagnostics solution to predict drivetrain failure modes for smart maintenance scheduling. The project plans to leverage on disruptive potential various options for integrated machine drive solutions and associated control solutions. Overall, the project should address critical issues of reliability and availability of e-Mobility solutions where the cost and ease of manufacturing are dominant factors over efficiency of the overall solution. In addition, the project aims to leverage on small sensing and industrial digitization technologies coming up in other technology areas and adapt them to e-Mobility solutions for advanced drivetrain monitoring and failure mode diagnostics. The research into digital twins will include practical aspects of creating infrastructural framework for digital twins, model-building for physical and accurate representation of the drivetrains and explore on advanced AI analytics for predicting potential failure diagnostics for better maintenance planning and support services