Research Database: Projects

The majority of work aimed at increasing transportation efficiency is centered around engineering: whether improving the efficiency of motors, the aerodynamics of the vehicle, or reducing the weight of the entire vehicle. Only now we are approaching an era where we can look to the automatic control of the vehicle as another opportunity to reduce fuel use. As a long overlooked area, it appears that even initial advances can have large benefits. In multiple pilot programs, single-day programs training automobile drivers to drive in a more fuel-efficient fashion brought reductions of between 10% and 20% in fuel consumption. For a heavy commercial truck in Europe, each percentage decrease saves nearly 500L of gasoline in a year. By controlling our vehicles not with a few lessons from a course, but with the aid of clever algorithms, we can expect even greater improvements.   

The question of how to produce effective and appropriate physical training plans is of great importance in many areas. For both professional and amateur athletes, getting the most out of every training session and progressing toward a long term fitness goal is of obvious interest. Even more important is the building of physical fitness for the less able-bodied. For cardiovascular patients and those in need of physical rehabilitation, the effectiveness of physical training is a quality of life issue of critical importance. Regardless of the application or goal, it is important to avoid injury or exhaustion due to training, and at the same time achieve the maximum long term performance improvement.

In this project Fraunhofer SCAI uses highly modern molecular midelling for the simulation of octanol-water and membrane-water distribution coefficients. Both of them are important to  rate the toxicity of those chemicals. The octanol-water distribution indicates the affinity of a chemical to biological material. In contrast, the membrane-water distribution shows how fast a chemical can intrude a biological cell. These experiments are not easy to perform due to the extremely low IL-concentrations. Therefore, the simulation is a good and realistic alternative concerning the accuracy and the price. 

The aim of this project is to develop a simulator that is able to simulate the beaviour of blow moulding machines for Kautex Maschinenbau, even before implementation. The vitrual blow moulding machine consists of mechanic, hydraulic and pneumatic components in order to reconstruct realistic conditions. This enables a simulation of the control systems before the machine is constructed. The virtual implementation will partly replace the real implementation, which will lead to time and cost saving. Last but not least, trainings of the personell can be performed much more realistic unsing a simulation program.

With using force field based molecular dynamic simulations it is possible to open up the field of modelling to the engineering sciences for the first time. Based on molecular interactions techniqual systems can now be reliably analysed. For sure the molecular simulation will also have a great impact on industrial development and resource efficiency. Chemical companies will be able to make use of simulations to solve engineering problems efficiently and therefore to replace experiments. To achieve this, it is necessary to reach accuracies comparable to high-level experiments. This requires optimised molecular models as well as overall efficiency. This means coordinated development of models, simulation methods and software.  This goal of this project is to investigate highly parallel molecular dynamics and new methods for highly parallel mathematic optimisation. Special focus will be put on: the prediction of specific properties for pure substances the behaviour of mixed fluid phases the study of nano scaled processes the development of new methods in the field of fluid phase lines and nucleation in reacting systems    

The goal of EWave is: 1. to develop an innovative energy management system 2. to calculate energy efficient operating plans for water distribution systems 3. to coordinate the everchanging offers of energy production facilities and different energy suppliers. 4. to start a pilot application at "Rheinisch-Westfälische Wasserwerksgesellschaft mbH" (RWW)  

The STELLA Efficient Mobility group explores issues in intelligent transportation. Our work centers around the energy-efficient control and design of vehicles, and their relationship with their passengers. Our focus is on bringing state-of-the-art machine learning solutions to traditional transportation problems.  Our experiments are conducted using high-performance electrically assisted velomobiles. These light-weight, aerodynamic vehicles act as a test-bed for ideas about the larger transportation picture. With a weak motor compared to the its weight, the pull of gravity caused by the slope of the road has an outsized influence on the motion of the vehicle. Controllers designed to take advantage of, and compensate for, this effect can yield large savings in energy consumption, and be applied to vehicles which are similarly effected, including some of our most energy hungry vehicles: trains, trucks, and buses.  Creating these controllers requires a deep understanding of how the vehicle behaves in the real world. Designed primarily by hobbyists and small companies, velomobiles lack the sophisticated aerodynamic and motor models produced for traditional vehicles by generations of engineers. We take this as an opportunity to explore innovative techniques for creating these models by taking advantage of new computational tools and advances in machine learning. We are most interested in the use of real world data, rather than data collected in highly controlled environments such as wind tunnels. We believe that modeling techniques which can take into account how vehicles behave as we drive them, not just as the could be driven, will have widespread application. Modeling the vehicle itself is only one aspect of our research. By collecting data from riders as they ride we are building models of how our bodies react to training, in both the long and short term. This allows us to not only support riders with electrical-motor assistance to avoid exhaustion on individual trips, but for long-term training plans to be developed so that riders get the most out of their efforts. Coupled with intelligent motor controllers, a day’s training can be  customized, even without changing routes.  The Stella project is composed of researchers from a variety of backgrounds and disciplines at the Bonn-Rhein-Sieg University of Applied Sciences. Our foremost concern is to bring our work into reality and affect change through innovation. We are always eager to cooperate with those in industry, government, and like-minded academic institutions.

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In the scope of this project an LED Flasher will be developed that enables the controlling of intensity, spectral distribution of energy density, and angle of incidence. This helps the measuring of the situational energy yield in the laboratory. This project is supported by the Germany Federal Ministry for Economic Affairs and Energy within the programm ‚Zentrales Innovationsprogramm Mittelstand‘ (ZIM).

The project is about the idea of a quick retrofit for conventional cars and buses, in order to reduce fuel consumption, related costs and CO2 emissions by using photovoltaic panels on the roof which are connected to the existing vehicle power supply network. This reduces the load on the alternator and leads to a reduction in fuel consumption. Tasks The main task of this project is to find out if the suggested PV system is applicable and profitable particularly with regard to sustainability: Theoretic calculations Experimental tests Analysing the results Impact estimations

Project management at the H-BRS