Browsing by Subject "Kraftstoff"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Publication
    Kraftstoffverbrauch beim Einsatz von Ackerschleppern im besonderen Hinblick auf die CO2-Emissionen
    (2006) Schreiber, Matthias; Kutzbach, Heinz Dieter
    Agricultural tractors are currently almost exclusively driven by diesel engines. By rising fuel prices and growing ecological awareness concerning CO2-emissions and preservation of fossil fuel resources the importance of fuel consumption has been increasing. Generally, the substitution of diesel by alternative fuel based on vegetable oil is possible, however the potential for the substitution is limited by the scarcity of agricultural farmland and categorized as low. The cost savings are not very big due to higher fuel consumption with bio fuel. Therefore, only the reduction of fuel consumption for different agricultural operations and if applicable the reorganisation of the production chains can contribute to a sustained reduction of fuel consumption and costs. In this thesis the basic influencing factors on fuel consumption of tractors are shown. Field tests are only of limited usefulness for the examination of single influencing variables. For those studies a model had to be developed. The presented model is based on the status of science concerning engine and transmission performances as well as tractive performance for agricultural tractors and is combined with the ASAE-Standard 497.4-model for the tractive force needed to pull the implement. As existing tyre-soil-models are only of limited use to predict tractive performance in the field and to deliver these values to the tractor model, an independent traction prediction model was developed. It is based on empirical equations, which were parameterized on the basis of numerous field tests. Furthermore, the influence of the fuel consumption for turning over in the headlands and for transportation work were investigated and considered in the model. The new model was implemented into the software Matlab to determine fuel consumption for different agricultural work and defined parameter variations. The calculated values were compared to the results of field tests with a special equipped tractor at the University of Hohenheim to validate the model. The model was used to investigate the influence of numerous influencing parameters, the effect on fuel consumption was shown and optimization strategies were developed. The saving potential by the optimization of the working process is up to 30 % for different implements, depending on the current state. For this purpose the tractive efficiency must be maximized by the correct weight of the tractor and the correct tyres, tractor and implement must be adjusted ideal, four wheel drive and differential locks must be used if necessary and the transmission ratio must be chosen to run the engine close to the optimum working point with the optimum engine load. Besides the process optimisation it is important to deliver standard values for the fuel consumption for different working operations and production chains for the practical use. For the presented model a large number of parameters has to be determined, thus it is of limited use to calculate standard values. Furthermore, it is too accurate for those calculations. Therefore, the model was used to obtain simplified equations for a quick and simple calculation of fuel consumption values, considering the major criteria of engine, transmission and tractive performance of the tractor as the drawbar pull and the needed PTO-power of the implement. On the basis of these equations, implemented into Microsoft Excel, the required standard values for fuel consumption can be calculated for different tractors with implements of different size and defined soil conditions. However, the required data of some implements are not complete. For the most important agricultural implements these parameters were determined by measurements or collected from KTBL- or FAT-values. The results for different operations and production chains are correlating well with values measured in the field. The effect of the field size or the distance between field and the farm yard on fuel consumption can be shown as well. The saving potential by changing the whole production chain (like zero tillage) is enormous, however, there are horticultural and economical external effects. As those economical effects can hardly be estimated, the conversion of the production chain has to be reviewed for the individual case. In the future the importance of fuel consumption will increase. Different saving strategies will gain in importance in order to optimize agricultural operations with respect to fuel consumption. The approach of this thesis can be used to show saving potentials, to develop optimization strategies and to calculate values for the fuel consumption of different agricultural operations.
  • Thumbnail Image
    Publication
    Screen for collusive behavior : a machine learning approach
    (2024) Bantle, Melissa
    The paper uses a machine learning technique to build up a screen for collusive behavior. Such tools can be applied by competition authorities but also by companies to screen the behavior of their suppliers. The method is applied to the German retail gasoline market to detect anomalous behavior in the price setting of the filling stations. Therefore, the algorithm identifies anomalies in the data-generating process. The results show that various anomalies can be detected with this method. These anomalies in the price setting behavior are then discussed with respect to their implications for the competitiveness of the market.