ePredict (ePredict)
The objectives of the project are the development of fundamental digital methods for monitoring and increasing the reliability of highly integrated mechatronic systems that can be transferred to other engineering problems. The methods are to be developed within the framework of the project using the electric bicycle as an example, always with a view to the transferability and utilization of the research results to other vehicles with electric drives. These methods are a prerequisite for new business models of system providers that link product, application and service.
This project is open access and publicly accessible.
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eBike measurements for fatigue monitoring and maneuver identification tasks [1]
This dataset provides acceleration and strain measurements from a sensor equipped eBike, which were collected for the development of new methods for fatigue damage monitoring and maneuver identification tasks. -
3-component servo-hydraulic test bench measurements for virtual sensing and forward prediction tasks [1]
This dataset was created to provide measurements of a non-linear dynamic system with multiple input and output signal channels for the developement and testing of virtual sensing and forward prediction algorithms. It also ...
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Recent Submissions
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eBike measurements for fatigue monitoring and maneuver identification tasks
(Technische Universität Dresden, 2022)This dataset provides acceleration and strain measurements from a sensor equipped eBike, which were collected for the development of new methods for fatigue damage monitoring and maneuver identification tasks. -
3-component servo-hydraulic test bench measurements for virtual sensing and forward prediction tasks
(Technische Universität Dresden, 2021)This dataset was created to provide measurements of a non-linear dynamic system with multiple input and output signal channels for the developement and testing of virtual sensing and forward prediction algorithms. It also ...
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