Research for an innovative future
The principle of integrating current research results and future-oriented topics into our projects is already deeply ingrained in our company's name - Technisch Wissenschaftlicher Transfer [Technical Scientific Transfer]. With the aim of securing progress today for tomorrow, TWT is involved in numerous national and international research projects. Activities include initiation, management and coordination of consortia, as well as participation in research initiatives.
Our innate drive for improvement aims to stimulate research-based innovations and advance emerging, cutting-edge technologies. Innovation and scientific expertise, coupled with the competence to examine things holistically, have been the cornerstones and driving forces behind TWT's successful research activities since the company was founded.
AINET-Antillas is a sub-project within the European AINET initiative. In various applications, such as Industry 4.0 and connected and autonomous driving, network availability and quality are of utmost importance to implement customer functions properly. AINET-Antillas develops and validates infrastructure elements for applications in highly networked scenarios. Tronis® is to be used for validating automated, connected and autonomous driving functions with regard to network quality; the latter also applies when comparing different network generations.
The acronym KoSi stands for Cooperative Autonomous Driving with Safety Guarantees. This project aims to investigate how the challenge of autonomous driving in complex traffic situations can be mastered through cooperative manoeuvre planning. Here, a particular focus is on mixed traffic scenarios, i.e. with autonomous and non-autonomous road users.
In the newAide project, the partners are researching the use of Artificial Intelligence (AI) methods in highly complex, simulation-based design processes in vehicle development with the aim of accelerating, optimising and partially automating these processes. In addition to improving individual design disciplines through AI approaches, the newAIDE project will use the sub-projects to investigate a fundamental database structure, as well as data structuring that supports and simplifies the use of AI methods in vehicle design. This could provide the base for a widespread introduction of AI approaches in vehicle design and beyond.
ALFRIED – Automated and Connected Driving in Logistics at the FRIEDrichshafen test field – is intended to serve inner-city goods traffic in the future. The overall concept of the hyper-efficient mobility system consists of several mobility users. The project aims to improve the overall traffic situation, especially of vehicles (both connected and non-connected), intelligent infrastructures and control centres. To this end, various technologies are being developed and prepared for use and deployment in real traffic. In the future, the findings from Friedrichshafen should be highly relevant for other cities and regions.
AUTOAKZEPT stands for the elimination of insecurity in understanding human-machine interaction ("Automation Without Insecurity to Increase Acceptance of Automated and Connected Driving"). To improve the user experience, the recommender system selects the most suitable adaptation for the driver with regard to the information provided on the traffic situation or driving style.
LiBAT – Development of a High Voltage Lithium BATtery – aims to develop an ultra-light, highly integrated battery pack for aerospace applications. The LiBAT design meets demanding requirements in terms of weight, energy density and performance and can be used flexibly in various applications. Prior to the LiBAT design being used in electric and hybrid aircraft, prototypical implementations and tests on the ground (TRL4) are being carried out. LiBAT is shaping a new future for aviation.
RABE – Intelligent Rollator for Inpatient Care to Preserve the Autonomy of Residents and to Relieve the Workload of Caregivers – comprises the development of an intelligent rollator designed to increase the user's autonomy and mobility while relieving the workload of caregivers. This is achieved through a range of functions, such as the "Autonomous Driving" mode, an indoor navigation and a pedelec function. The products developed during the project are being tested in a nursing home run by Stiftung Liebenau.
OPsTIMAL – Optimised Processes for Trajectory, Maintenance, Management of Resources and Airline Operations – aims to optimise aviation operations. Data analysis and predictive maintenance of engines help to track the research on these topics.
In the project AIToC – Artificial Intelligence Supported Tool Chain in Manufacturing Engineering – an integrated tool chain for production planning and production systems engineering is being developed to support decision-making at very early stages. This includes the development and adaptation of tools for defining and managing requirements, as well as for creating process plans, equipment models and layouts. For this purpose, a model-based approach is used to define product and production requirements. Tool chain integration focuses on solutions for tool interoperability and plug & play functionality to be flexible in designing the simulation environment. This will have a significant impact on efficiency (cost), quality of models and cycle time for simulations in the industrial context.
iVeSPA – Integrated Verification, Sensors and Positioning for Aircraft Production – is investigating ways to significantly increase the level of digitisation in today's aircraft production. The current level of process step digitisation is rather low. Insofar as the machines used in the process make their sensor data from the undergone process steps available for further use, isolated solutions will emerge at best. A networking of the machines or central storage for simplified access to all data of the manufacturing processes is not widely implemented.
Autonomous driving applications place high demands on mobile communications networks, which naturally have varying qualities of service. SMART is investigating virtual Vehicle-to-X (V2X) applications and their resilience in LTE and 5G scenarios. The project developed a mechanism for negotiating the Quality of Service (QoS). Real-time simulations of V2X-based autonomous driving scenarios in the Tronis® 3D virtual environment were also used to evaluate the mechanism's capabilities to predict stochastic QoS guarantees.
While assistive robots are already well developed in terms of function, they are currently often not yet capable of interpreting human emotions and behaviour correctly and of interacting with the user in a way appropriate to the situation. If assistive robots are to enter our private everyday life, they must be enabled to correctly interpret the user's state and the context of use and to adapt their verbal and non-verbal interaction strategy accordingly.
Scientific engineering and physical questions are often formulated by partial differential equations and solved using the Finite Element Method (FEM). In this method, the given calculation domain is first meshed, i.e. broken down into simple geometric elements, such as triangles or quadrilaterals in case of surface models, or tetrahedra or hexahedra in case of volume models. These elements are used as the basis for defining the solution function, the coefficients of which are to be determined by the FE procedure. Depending on the quality of the resulting mesh, this is followed by a mesh optimisation step, which may be integrated, if applicable, into the mesh generation procedure. Then, taking into account boundary conditions such as loads, fixations, etc., a linear system of equations is set up during the FE simulation process to determine the solution coefficients. Subsequently, the resulting FE system is solved using special numerical methods and the solution of the simulation problem is evaluated.