Subproject A03

Sensitive road surface layer: Detection of wheel loads with high temporal and spatial resolution

In subproject A03, a sensitive surface layer will be developed of which function is based on piezoresistivity. The resistance of the conductive material changes by strain induction. The resulting change in resistance forms a signal that is used to determine area-wide load positions and load variables of vehicles (tyres) and to record condition data.

A comprehensive literature study on the preparation of polymer-based materials with nanoparticles forms the first milestone of the subproject. Based on this, an experimental parameter study, accompanied by the development of numerical methods, will be conducted with the aim of identifying an optimal design of a conductive material. The aim is to balance the homogeneity, miscibility, strength and conductivity of the material.

An experimental characterisation of the mechanical and piezoresistive properties of the identified optimal material is then carried out, in which the mechanical and tribological performance of the sensitive surface layer is tested and further developed.

Another part of subproject A03 involves the development of a multi-physical model that maps the mechanical-electrical interaction of the piezoresistive material on the nano, micro and meso scales. After iterative improvement of the material properties, the integration of the material into the context of the digital twin takes place. In this step, the implementation of the wheel load and position estimation as well as the approaches for self-diagnosis are advanced. The surface layer is applied in sections to asphalt or concrete pavements and is an essential component of the digital twin road envisaged in SFB/TRR 339. In addition, in this subproject, initial research will start to develop the approaches for generation of electrical energy using piezoelectric energy harvester, transmission of the signals derived from the sensitive surface layer to the communication systems.

Multiscale view of the sensitive top layer (size ratios between partition and CNT distorted for display reasons, partitions have dimensions of approx. 5 x 5 cm, the nanoparticles have a length of approx. 50 nm).

Project Participants

Prof. Dr.-Ing. habil.
Markus Oeser
Subproject Manager
Dr.-Ing.
Pengfei Liu
Subproject Manager
Dr.-Ing.
Quentin Félix Adam
Scientific Researcher
M.Sc.
Lei Luo
Associated Member
M.Sc.
Tiangling Wang
Associated Member

Publications of the Subprojects

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