Modeled components for all areas of the vehicle
Alexander Grimm from OTH Regensburg worked on an object-oriented hierarchical model library for electric vehicles based on the Modelica modeling language as part of his master's degree. In the project work of the first semester, he implemented the model of an electric vehicle with generic components. The interfaces between the components are based on a standardized library. This work was submitted as a contribution to the "12th International Modelica" conference 2017 in Prague and won second place with another work at the "Modelica Association" award ceremony.
The modeled components cover all areas of the vehicle: from the energy storage system to the drivetrain to a model of the driver. This makes it possible to make important statements about driving performance and energy consumption at an early design stage and to compare alternative solutions. In the second semester's project work, Alexander Grimm described a key component in more detail: the battery as an energy storage system. Finally, in his master's thesis, he compares the simulation results of his model with real measured values obtained during journeys of the Regensburg electric bus "EMIL" with the support of AVL and Regensburger Verkehrsbetriebe.
The results of the research work were presented at the cluster's annual conference.
The city of Regensburg is consistently expanding its expertise in the field of artificial intelligence. The technology clusters based in the business and science location, which work together in the joint AI initiative AIR Artificial Intelligence Regensburg, play a decisive role in this.
The cluster partnership received 250,000 euros in funding for the cross-cluster project goAIR, which has established a comprehensive range of services for companies in the field of artificial intelligence. The funding for the Regensburg goAIR project came from the "go-cluster" program of the Federal Ministry of Economics and Climate Protection.
The project sponsor is VDI/VDE Innovation + Technik GmbH.
Project duration: 01.10.2021 - 30.09.2022
The aim of the AIR Artificial Intelligence Regensburg AI initiative is to bundle the respective cluster expertise and offer member companies a joint service portfolio for the cross-industry promotion of AI-driven innovations:
About the Data Inventory mobility data concept
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The cross-cluster project goAIR Artificial Intelligence Regensburg involved
In cooperation with the LaS³ (Laboratory for Safe and Secure Systems), the Cluster Mobility & Logistics examined charging stations for their safety functions. The aim was to make a statement about the current level of protection as well as possibilities for improvement.
The charging stations were assessed in terms of their risk for classification into safety integrity levels (SIL). To this end, the possible malfunctions and the resulting hazards for users or the environment were determined. Safety functions were implemented to prevent malfunctions. Certain safety functions have already been implemented in charging stations currently available on the market.
Based on the hazard, the SIL placed requirements on the safety circuit of the overall system with regard to failure rates and usable components. A standard charging station model was examined and evaluated for this purpose. Based on this, the additional requirements for the architecture of charging stations were investigated.
At higher safety integrity levels, requirements also arose for the lifecycle management of the product, i.e. how maintenance is to be carried out and what documentation is required. These steps were also taken into account in the investigation.
In cooperation with the Las3 laboratory at Regensburg University of Applied Sciences, the cluster produced a guide to creating fail-safe software with regard to the functional safety of charging stations in accordance with IEC 61508.
The guideline can be made available to interested parties.