smartCAST – digital castings with condition monitoring for autonomous vehicles

In the course of the "smartCAST" project, piezoresistive sensors are being developed for direct embedding in safety-relevant aluminum components in autonomous vehicles. The integrated sensors are intended to monitor critical loads and identify imminent component failure at an early stage.


Project Description

The increasing spread of autonomous vehicles on the road is placing new challenges on vehicle safety. The physical separation of the steering wheel from the driver in autonomous driving means that in the future the driver will leave control, and therefore risk, entirely to the vehicle. The problem is further aggravated by the continuing trend toward car sharing services and the resulting decline in sense of responsibility toward a vehicle. Any damage that occurs - and with it an increased safety risk - is transferred directly to the subsequent driver. As a result, there is a significant demand for intelligent automotive components that can self-monitor thermal and mechanical state by means of integrated sensors.

In this project, new combinations of techniques and materials are being researched at IMSAS to enable the production of sensors that can withstand the contsraints of the manufacturing process of the host component. In this context, embedding the sensor in the aluminum casting is one of the greatest challenges of material-integrated sensor technology. During in-process integration, the sensor that is to be integrated is exposed to the high thermal and mechanical stress of the harsh and hot casting environment. At the same time, the embedded sensor acts like a foreign object in the component and has a direct influence on the mechanical stability and thermal conductivity, both of which must be mitigated and reduced.

As part of the DFG-funded project "SINA", initial principles for the direct casting of load sensors based on thick-film technology in aluminum castings were developed. The principle of the piezoresistive sensor allows real-time data acquisition both during the operating phase and during commissioning. This means that it is possible to carry out checks for deformation or damage to the casting at any time. In this project, these fundamental findings will be transferred with regard to practical application scenarios and castings for autonomous vehicles and completed for a future series application together with the research partner IFAM and the two industrial partners KSM Casting Group GmbH and MAGMA Giessereitechnologie GmbH.



Prof.. Dr.-Ing. habil. Matthias Busse, Fraunhofer-Institut für Fertigungstechnik und Angewandte Materialforschung IFAM

Dipl.-Wi.-Ing. Christoph Pille, Fraunhofer-Institut für Fertigungstechnik und Angewandte Materialforschung IFAM

Dr.-Ing. Dirk Lehmhus, Fraunhofer-Institut für Fertigungstechnik und Angewandte Materialforschung IFAM

Dipl.-Ing. Olaf Middelmann, KSM Castings Group GmbH

Dr.-Ing. Götz Hartmann, MAGMA Gießereitechnologie GmbH


Contact IMSAS

M.Sc Aynur Klatt
Universität Bremen
IMSAS, NW1, Room O2050
Tel.: +49 421 218 62619
E-mail: aklattprotect me ?!imsas.uni-bremenprotect me ?!.de

Prof.. Dr.-Ing. Walter Lang
Universität Bremen
IMSAS, NW1, Room O2120
Tel.: +49 421 218 62602
E-mail: wlangprotect me ?!imsas.uni-bremenprotect me ?!.de


The project is funded by the DFG - German Research Foundation since 2020 under project number 440971991 over three years.

DFG - GEPRIS - smartCAST – digital castings with condition monitoring for autonomous vehicles


back to projects group Lang