Complexity in todays connected world is increasing every day. Information became accessible and new technologies are emerging with increased speed leading to fast changing customer requirements and growing demand on mobility and transportation concepts. Exactly there VIRTUAL VEHICLE sets the focus and aims to provide a research and development platform for de-risking future rail systems technologies along the value creation for intelligent, affordable and scalable solutions increasing transport capacities of rail systems.
For this reasons, the department RAIL SYSTEMS places their main scientific and research efforts on analysing the rail system as a whole, examining the interaction between vehicles, track, and the environment. In order to understand the complex interactions of vehicles and tracks, and to be able to take effective optimisation measures for the rail system, physical effects are modelled to the necessary level of precision. The VIRTUAL VEHICLE established a broadly diversified network of industrial and scientific partners over the last years. By means of research and technology development with focus on service oriented, modular design and validation digital framework the department empowers the industries and researchers to craft a smarter planet.
Virtual methods coupled with real measured data while integrating the rail vehicles, smart infrastructure, users, environment and disturbances but also other means of transportation are the topics that VIRTUAL VEHICLE focus on. Interacting with smart infrastructure, the cloud, and all types of users is an integral part of future rail vehicle functionality. Connectivity implies broadcasting and consuming real-time data streams, as well as applying virtual sensors, on-board data analytics, learning algorithms and cognitive models in an automated environment.
New approaches and solutions are required for an individualized, customer-centric and flexible use of rail systems interconnecting with other means of transportation as a mobility service. The rail system as a whole must become quieter, more reliable, and more affordable, while safety and performance must be maintained.
Interaction between vehicles, smart infrastructure, and the environment
Develop methodologies to examine the interaction between vehicles, smart tracks, and the environment. Identify the missing links, and connect the dots of an embedded rail system as a mobility service.
Intelligent and accurate Fault Diagnosis
Provide solutions for intelligent and accurate Fault Diagnosis and Identification (FDI), prediction of system behaviour and condition of the vehicle and track to increase rail capacity, reliability while reducing the maintenance costs Conditioned Based Maintenance & Predictive Maintenance
Advanced train operations
Train on demand, individualized, comfortable, flexible and scalable, interconnected, automated train operations
Conditioned based monitoring systems
Development of new approaches combining virtual high fidelity models with measured data describing and predicting of forces while addressing tribological effects transmitted between the wheel and rail under all possible environmental conditions. These concepts will be implemented in traction control systems and condition based monitoring systems of vehicles and track.
Operational and environmentally relevant influences cause impairment of vehicles and track quality over time. Virtual methods are developed to predict and evaluate the behaviour of the track, the conditions and the effects of the track on a railway vehicle and vice a versa providing homologation data to ensure compliance.
Train on demand
New scalable, flexible and autonomous rail systems ensuring a multi-modal interoperability lead to new requirements on the rail system. Integrating of high fidelity models and sensor data, fusion of information incl. machine learning algorithms shall enable the automated train operations (AT O).