A current trend in the commercial vehicle industry are autonomous trucks and tractor-semitrailers which will lead to an increasing automation of functions and autonomous transport processes in the future. In this contribution, we present the IdenT system concept, which has been developed for tractor-semitrailers within the research project of the same name, consisting of an intelligent trailer sensor network, a cloud-based data platform and methods for on- and offline data processing. In this work, we focus on the offline process, by presenting its architecture and main functions. As fundamental elements of the offline process, the digital twin of the trailer, i.e., a detailed multi-body model with current inputs and parameters acquired via the system’s online setup, and the methodology to identify the road profile are presented in detail. We show and discuss results of the offline process for some demonstration cases that illustrate how the simulation of the trailer digital twin with identified road profiles can provide a valuable identification of the trailer’s real system dynamics. Moreover, some expected limits of the approach and results of some representative signals are discussed for the demonstration cases.

The Discrete Element Method (DEM) is broadly used for soil modeling, especially if a realistic prediction of interaction forces with solid materials, i.e. tools is required. While recent enhancements of computing power allow for faster computing times in many fields, DEM-based calculations are still far from real-time, typically by a factor of 100 or more. This is a bottle neck within the design and development processes of agricultural and construction machinery, which are relying on the interaction forces with soils. Finding a decent surrogate model, combining higher computing speeds without loosing accuracy in the prediction of soil-tool interaction forces, would be highly beneficial. Here, we discuss an approach based on recurrent neural networks with the potential of combining real-time capability with accurate soil-tool interaction force prediction.

Soil models coupled with multibody systems are wellestablished in the development process of construction machinery to predict reaction forces in relevant application maneuvers. In order to accommodate the large variety of soils, it is crucial to choose a suitable model complexity and corresponding identifiable parameters to describe the respective soil characteristic. Within this contribution, we present the parametrization of a soil model based on the Discrete Element Method and discuss efficient and robust methods with the help of direct optimization approaches.

In diesem Beitrag präsentieren wir das sog. IdenT-System, welches im Rahmen des gleichnamigen Forschungsprojekts für LKW-Trailer entwickelt wird. Wir betrachten eine spezifische Teilkomponente, nämlich die Online-Identifikation von Straßenprofilen und -rauigkeiten basierend auf Trailer-Messungen, einfachen Modellen und maßgeschneiderten mathematischen Verfahren. Die Rauigkeit des befahrenen Straßensegments wird mithilfe des sog. IRIs (International Roughness Index) aus dem Profil abgeleitet und dient u.a. der Detektion besonders beanspruchender und kritischer Straßensegmente. Für solche wird im IdenT-System u.a. ein Signal ausgelöst, das den auf der Cloud-Plattform befindlichen Offline-Zwilling startet, der für solche Straßenabschnitte höher aufgelöste Informationen generiert. Die basierend auf den identifizierten Straßeneigenschaften gewonnenen Informationen dienen der Überwachung des Trailerzustands und können zukünftig einen Beitrag dazu leisten, Sattelzüge sicherer zu betreiben.

Interactive simulator-based development has a great potential for product development in the automotive and commercial vehicle industry. In particular, test studies and validation steps can be performed during early development phases in a safe and reproducible simulator environment, leading to a decreasing need for real prototype building and testing. Furthermore, it enables engineers to explore features that would require major changes to the current machine generations. In this contribution we report about the simulator-based development of a stability assistance system for excavators. We show the complete toolchain from modeling over interactive simulator studies to a prototype environment and industrialization, closely following the exemplary case of a tip over warning assistant.

AbstractWe consider an efficient, data‐driven approximation approach for the prediction of soil‐tool interaction forces. In a time‐consuming offline phase, we perform a set of Discrete Element Method basis simulations. In each simulation, we consider a different tool state, process the acquired data and save it into a data structure, which we call a Lookup Table. In an online phase, when performing arbitrary tool maneuvers, we obtain tool forces and moments from the Lookup Table, based on the current tool state. In other words, we generate a data base of tool maneuver forces and access it efficiently.

We present a fast, data-based approach to predict soil-tool forces. In an expensive offline phase, we perform time-consuming particle simulations based on the Discrete Element Method (DEM). Relevant tool parameters, more specifically cutting depth, angle of incidence and velocity in longitudinal direction are varied to obtain a significant data range of the tool forces and moments. The data is stored in a structure, which we call a Lookup Table (LUT). In an online phase, we use the tool parameters to access the Lookup Table data and to obtain a meaningful approximation of the soil-tool interaction forces.

We consider prediction strategies in a parallel coupling scheme for modular co-simulation: local extrapolation and a linear-implicit stabilization technique based on model information. That is, concerning local extrapolation, instead of using data points at the macro time points for generating the extrapolation polynomial (as it is done in the conventional global case), we use local data points only within the last macro time step. The linear-implicit stabilization technique predicts coupling quantities based on model information in terms of Jacobian matrices by performing a linear-implicit Euler step forward in time. We introduce and discuss these two prediction strategies and analyze their numerical properties, stability and accuracy, based on a simple test model.

The Discrete Element Method (DEM) is well-established and widely used in soil-tool interaction related applications. As for all simulation tools, a proper calibration of the model parameters is crucial. In this contribution, we present the parametrization procedure of the DEM software GRAnular Physics Engine (GRAPE), developed and implemented at Fraunhofer ITWM, and attempt to use two parametrized soil samples for the simulation of small scale shallow penetration tests. The results are compared to laboratory measurements.

Micro Abstract Modern vehicles are highly complex systems consisting of many subsystems in various physical domains that dynamically interact. In this context, co-simulation strategies are particularly attractive as each subsystem is solved via tailored simulation tools with appropriate numerical methods. Industrial applications induce enormous numerical challenges regarding efficiency, accuracy and stability. We present co-simulation strategies by means of selected application examples in vehicle engineering.

A co-simulation scheme is developed that couples an MBS wheel loader model with the ITWM/DEM code for soil simulation, in order to realize a framework in which different loading maneuvers can be si ...

Modern vehicles are highly complex systems consisting of many subsystems in various physical domains, e.g. electric, electronic, hydraulic and control systems that dynamically interact. For any subsystem, there are tailored simulation tools with specifically developed and adapted numerical solvers. In this context, co‐simulation strategies are particularly attractive, where each submodel is solved with appropriate numerical methods. In industrial applications, one is hereby confronted with enormous numerical challenges with respect to efficiency, accuracy and numerical stability – especially in online applications. In this article, we present co‐simulation strategies by means of selected application examples from the field of vehicle engineering. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

In this chapter we present a parallel modular algorithm to compute all solutions with multiplicities of a given zero-dimensional polynomial system of equations over the rationals. In fact, we compute a triangular decomposition using Möller’s algorithm (Möller, Appl. Algebra Eng. Commun. Comput. 4:217–230, 1993) of the corresponding ideal in the polynomial ring over the rationals using modular methods, and then apply a solver for univariate polynomials.

Given a reduced affine algebra A over a perfect field K, we present parallel algorithms to compute the normalization (A) over bar of A. Our starting point is the algorithm of Greuel et al. (2010), which is an improvement of de Jong's algorithm (de Jong, 1998; Decker et al., 1999). First, we propose to stratify the singular locus Sing(A) in a way which is compatible with normalization, apply a local version of the normalization algorithm at each stratum, and find (A) over bar by putting the local results together. Second, in the case where K = Q is the field of rationals, we propose modular versions of the global and local-to-global algorithms. We have implemented our algorithms in the computer algebra system SINGULAR and compare their performance with that of the algorithm of Greuel et al. (2010). In the case where K = Q, we also discuss the use of modular computations of Grobner bases, radicals, and primary decompositions. We point out that in most examples, the new algorithms outperform the algorithm of Greuel et al. (2010) by far, even if we do not run them in parallel. (C) 2012 Elsevier B.V. All rights reserved.

In this article we present two new algorithms to compute the Gröbner basis of an ideal that is invariant under certain permutations of the ring variables and which are both implemented in Singular (cf. Decker et al., 2012). The first and major algorithm is most performant over finite fields whereas the second algorithm is a probabilistic modification of the modular computation of Gröbner bases based on the articles by Arnold (cf. Arnold, 2003), Idrees, Pfister, Steidel (cf. Idrees et al., 2011) and Noro, Yokoyama (cf. Noro and Yokoyama, in preparation; Yokoyama, 2012). In fact, the first algorithm that mainly uses the given symmetry, improves the necessary modular calculations in positive characteristic in the second algorithm. Particularly, we could, for the first time even though probabilistic, compute the Gröbner basis of the famous ideal of cyclic 9-roots (cf. Björck and Fröberg, 1991) over the rationals with Singular.

The aim of the CIMPA-ICTP-UNESCO-MESR-MICINN-PAKISTAN Research School on Local Analytic Geometry at Abdus Salam School of Mathematical Sciences, GC University Lahore, Pakistan (organized by A. D. Choudary, Alexandru Dimca and Gerhard Pfister) was to introduce the participants to local analytic geometry and related topics. A basis of the course was the book entitled Local Analytic Geometry (cf. [JP00]). An important part of the school was to establish computational methods in local algebra and to provide an introduction to the computer algebra system Singular (cf. [DGPS12]). This article includes the lecture notes corresponding to the lectures held during the school and was edited by Gerhard Pfister and Stefan Steidel.

In this article we describe our experiences with a parallel Singular implementation of the signature of a surface singularity defined by z N + g ( x; y ) = 0.