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No, Title
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SCD 7.3.Simulation and Virtualization for MultiModal Mobility
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Leader
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AIDIGI+
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Contributing Partners
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AIDIGI+
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Description
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For the software-related tasks, interfaces were developed that can ensure fully automated recording and generation of data records from the vehicle between the hardware components. These data sets were automatically read in a virtual environment for further processing and evaluation. Various approaches from the field of machine learning were used. Based on a research vehicle, in this case an electric vehicle, various parameters were generated and extracted via the On-Board Diagnostic with CANEdge interface. These interfaces can be used to record and store thousands of vehicle parameters during a journey. This data can be further processed retrospectively and used for various evaluations with the help of machine learning approaches.
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Deployment/utilization
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Integration of the On-Board Diagnostic with CANEdge in a Lab Environment and the integration as a prototype to test and sent data from vehicle to a virtual environment. In the project, an On-Board Diagnostic with CANEdge interface was used and further developed that was able to record parameters from various components of an electric vehicle. It was possible to record and store various variables such as voltage, current, state of charge, charging temperature, charging volume and other parameters. In addition, the ambient temperature was determined during real trips with the help of another sensor. This was set in relation to the battery parameters to obtain contextual information.
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Pictures/visuals with titles
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LAB-Pipeline
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