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Robust and Regularized Algorithms for Vehicle Tractive Force Prediction and Mass Estimation
This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models.
Experimental investigation and process simulation of the compression molding process of Sheet Molding Compound (SMC) with local reinforcements
In this book, a new three-dimensional approach for the process simulation of SMC is developed. This approach takes into account both, the core layer that is dominated by the extensional viscosity and the thin lubrication layer. In order to transfer the information from the process to the structure simulation, a CAE chain is further developed. In addition, a new rheological tool is developed to analyze flow behavior experimentally and to provide the required material parameters.
Simulation of damage mechanisms in weave reinforced materials based on multiscale modeling
A weave reinforced composite material with a thermoplastic matrix is investigated by using a multiscale chain to predict the macroscopic material behavior. A large-strain framework for constitutive modeling with focus on material non-linearities, i.e. plasticity and damage is defined. The ability of the geometric and constitutive models to predict the deformation and failure behavior is demonstrated by means of selected examples.
Numerical prediction of curing and process-induced distortion of composite structures
Fiber-reinforced materials offer a huge potential for lightweight design of load-bearing structures. However, high-volume production of such parts is still a challenge in terms of cost efficiency and competitiveness. Numerical process simulation can be used to analyze underlying mechanisms and to find a suitable process design. In this study, the curing process of the resin is investigated with regard to its influence on RTM mold filling and process-induced distortion.
Road Condition Estimation with Data Mining Methods using Vehicle Based Sensors
The work provides novel methods to process inertial sensor and acoustic sensor data for road condition estimation and monitoring with application in vehicles, which serve as sensor platforms. Furthermore, methods are introduced to combine the results from various vehicles for a more reliable estimation.
Objective Tyre Development : Definition and Analysis of Tyre Characteristics and Quantification of their Conflicts
The present work focuses on tyres for passenger cars, especially on its influence on power loss, lateral dynamics, ride comfort and interior noise. The objective of the work is the quantification of conflicts between four selected requirements considering the physical constraints given by the tyre. The method proposed in the present book is based on a set of functional tyre characteristics, a physical tyre model and a procedure for identifying and quantifying the conflicts.
Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models
This work aims at improving the energy consumption forecast of electric vehicles by enhancing the prediction with a notion of uncertainty. The algorithm itself learns from driver and traffic data in a training set to generate accurate, driver-individual energy consumption forecasts.
Development of a CO2e quantification method and of solutions for reducing the greenhouse gas emissions of construction machines
This work focuses on the development of a quantification method for GHG (CO2e) emissions from construction machines. The method considers CO2e reduction potentials in the time past-present–future, through influencing factors from six pillars: Machine efficiency, process efficiency, energy source, operating efficiency, material efficiency and CCS. In addition, transformation solutions are proposed to reduce GHG emissions from construction machines like liquid methane, fuel cell drive or CCS.
Manufacturing-constrained multi-objective optimization of local patch reinforcements for discontinuous fiber reinforced composite parts
In this work, contributes to the optimization of local continuous fiber reinforcement patches, under consideration of manufacturing constraints. This approach requires specific optimization strategies. Therefore, an multi-objective optimization strategy for the placement of local reinforcement patches, under consideration of manufacturing constraints, has been developed. During the multi objective optimization, structural and process related objectives are considered.
Simulation of the thermoforming process of UD fiber-reinforced thermoplastic tape laminates
In this work, initially, the requirements on a simulation model of the non-isothermal stamp forming process of unidirectional fiber-reinforced, and thermoplastic tape laminates are investigated experimentally. On this basis, different isothermal as well as a fully coupled thermomechanical simulation model under consideration of the crystallization kinetics are developed. For validation, a complex shaped geometry is simulated and compared to experimental forming results.
