Open Access

Autonomous race cars, such as in Formula Student Driverless, operate close to their physical handling limits. The resulting highly nonlinear vehicle behavior increases the path tracking complexity, especially on narrow tracks. Model Predictive Control (MPC) is commonly used to address this issue, a method whose performance is closely tied to the accuracy of the underlying prediction model. This paper presents a novel, real-time capable prediction model for autonomous race cars that adjusts to changing conditions by combining information from past runs and the current driving situation. Our model is divided into three consecutive submodels: a nominal Kinematic Bicycle Model, an offline Bayesian Linear Regression (BLR) model, and an online Sparse Gaussian Process Regression (SGPR) model. The proposed approach enables efficient integration of all available data without significantly increasing computational cost, ensuring high prediction accuracy and a quantitative uncertainty assessment right from the start of the run. Compared to existing approaches, an improvement in prediction accuracy of up to 57 % was achieved. Further, we successfully demonstrated the practical applicability of the model within an MPC-based path tracking controller on a real Formula Student race car.

The perception of comfort in seminar rooms signifi cantly affects the performance, concentration, and productivity of its users. This research investigates the impact of the ventilation system, natural ventilation or mechanical ventilation, on user comfort in seminar rooms. Six indoor climate parameters were recorded in identical rooms with natural and mechanical ventilation and were subsequently evaluated from the users’ perspective. A statistical analysis was conducted to compare objective measurement data with subjective perceptions of the indoor climate among the target population. This study aims to determine whether mechanical and natural ventilation systems provide equivalent comfort levels or lead to signifi cant differences in user perceptions. The results from this research provide valuable insights into the impact of ventilation systems on perceived comfort and the mutual interactions between individual factors. Both mechanical and natural ventilation systems created comparable indoor climate conditions in the seminar rooms under consideration. Furthermore, the comfort levels were found to be equivalent for both ventilation systems from the users’ point of view. However, users in rooms with natural ventilation reported higher air velocities to be more pleasant than those in mechanically ventilated spaces. These fi ndings can be used to optimize seminar rooms in terms of perceived comfort, potentially enhancing the performance, concentration and productivity of students.

The integration of collaborative robots into manufacturing has significantly transformed industry dynamics by enhancing the effectiveness and adaptability of production processes. This study investigates the potential of mixed reality (MR) technology to revolutionize employee training through immersive and interactive environments that seamlessly merge digital and physical realities. We introduce an MR training system for human–robot collaborative assembly tasks and evaluate its effectiveness as a training tool. The evaluation applies the following metrics: User Experience, Interaction Effectiveness, Affective-Cognitive Response, Technology Readiness, and Task Completion Time. Sixty-three participants with varied technical backgrounds, experience levels, and job roles completed a collaborative assembly task using the MR system. Our analysis includes (1) the overall effectiveness of the MR system on an absolute scale, and (2) the difference in effectiveness given the participants’ backgrounds. For the latter, participants were split into two MR-Affinity groups. Our results suggest that the MR system can effectively train people to jointly work with robots. Secondly, no significant difference between the two MR-Affinity groups was found except for the Task Completion Time. Both results together indicate that MR-based training for human–robot collaboration is generally useful and applicable to users from varied backgrounds.

According to parasitic effects, unwanted resonant circuits occur in electric applications. In power electronic systems, resonances might be excited. Modulation methods are decisive for the frequency dependent voltage excitation generated by power electronic components. In this paper a delta-sigma modulated voltage source inverter is considered with the aim of reducing common mode disturbances. Simulative and experimental results are discussed in order to state out advantages and disadvantages in comparison to a pulse width modulation. Especially significant peaks in voltage spectra can be reduced with a delta-sigma modulated inverter.

An Edgeworth expansion of first order is established for general linear rank statistics under the null hypothesis. Furthermore, corresponding results for the second order are formulated, but not proved here. The proof for the first order is based on Stein's method and on an extension of the combinatorial method of Bolthausen. It is also shown that conditions of van Zwet imply up to a small factor our conditions for the validity of Edgeworth expansions. Moreover, our proof for the first order also provides us with a result about Edgeworth expansions for smooth functions.

Accurately predicting the energy demand of Computerized Numeric Control (CNC) machining processes before production enables the assessment of a product’s CO₂ footprint, the identification of optimization opportunities, and the implementation of energy-aware scheduling strategies. However, forecasting the energy consumption of CNC machines equipped with regenerative drives presents unique challenges, as the energy demand of a given G-command is influenced by the preceding operation. This study investigates the application of time-series Machine Learning (ML) models to better capture these temporal dependencies and improve energy consumption accuracy. A significant variance in repeated measurements was observed during the experimental phase, prompting a comparative analysis of using raw versus averaged energy values as input data. Multiple time-series model architectures, including Long Short-Term Memory (LSTM) and Temporal Convolutional Networks (TCNs), are evaluated for their ability to learn sequential patterns in a 5-axis machining process. The results reveal that while ensemble methods such as LightGBM and Random Forest achieve the highest accuracy and efficiency on the test dataset, sequence-based models demonstrate greater robustness on unseen validation data. Incorporating a small portion of validation data into training further improves ensemble performance, highlighting the trade-off between robustness and efficiency in energy demand prediction.

Die International Financial Reporting Standards prägen heute die Bilanzierungspraxis börsennotierter Unternehmen weltweit. Diese neue Auflage vermittelt die komplexen Regelwerke systematisch und praxisnah – mit der bewährten fallorientierten Methodik, die bereits Tausende von Studierenden zum Erfolg geführt hat. Aus dem Inhalt: – Rechnungslegung und Abschluss nach IFRS – verbundene und kapitalmarktorientierte Unternehmen – Erstbewertung und Folgebewertung – Bilanzierung von Aktiva und Passiva – Finanzinstrumente und Leasingverhältnisse Ob Klausurvorbereitung oder berufliche Weiterbildung – dieses Lehrbuch bietet das fundierte Rüstzeug für den sicheren Umgang mit der internationalen Rechnungslegung. Verständlich erklärt, systematisch aufgebaut, praxisorientiert angewendet.

In dieser Arbeit wird das Mikroimpulsschweißverfahren der Firma Lampert Werktechnik GmbH (Micro Arc Welder) zur Verbindung dünnwandiger Titanbleche (Ti-6Al-4V, 1 mm) untersucht. Ziel ist es, den Einfluss des reduzierten Wärmeeintrags auf Festigkeit und Duktilität zu bewerten. Die Ergeb-nisse zeigen, dass die Zugfestigkeit und Bruchdehnung der Schweißverbindungen signifikant gegenüber dem Grundmaterial reduziert sind (-50 % Festigkeit, -93 % Dehnung). Mit Zusatzmaterial durchge-schweißte Proben zeigen bessere mechanische Eigenschaften als stumpf verschweißte. Trotz der sprö-den Gefüge weisen durchgeschweißte Proben im Biegeversuch eine höhere Maximalkraft vor dem Bruch auf als Referenzbleche, was Potenzial für spezielle Anwendungen mit begrenztem Wärmeeintrag bietet.

Die vorliegende Studie fasst die wesentlichen Ergebnisse des Workshops „Steigerung der Studierendenzahlen in ingenieurwissenschaftlichen Studiengängen an bayerischen HAW/TH“ zusammen. Es wurden neun Handlungsfelder identifiziert, die bei verschiedenen Zielgruppen ansetzen (Schülerinnen und Schülern, Frauen, internationale Studierende), die Bedarfe von MINT-Studierenden adressieren (Stärkung mathematischer Kompetenzen, strukturierte Studieneingangsphase, aktivierende Lernformate, individualisierte Lernpfade) und bestimmte Studienformate (duales Studium) in den Blick nehmen. Die Vorstellung von Good-Practices an bayerischen HAW/TH zeigt, wie vielfältig der Gestaltungsspielraum der Hochschulen ist, um neue Zielgruppen zu gewinnen und auf die Bedarfe von Studierenden im Student-Life-Cycle zu reagieren. Die Ergebnisse der thematischen Workshops unterstreichen, welche Potenziale für die Weiterentwicklung der Angebote bestehen. Diese können von den Hochschulen jedoch nur im Austausch mit Schulen, Unternehmen und Medien als gesamtgesellschaftliche Herausforderung bewältigt werden. Diese Publikation als Dokumentation der Veranstaltung soll den Hochschulen und Lehrenden Anregungen und Good-Practice-Beispiele zur Attraktivitätssteigerung der ingenieurswissenschaftlichen Studiengänge an die Hand geben. Workshop und Publikation sind der Ausgangspunkt für einen Prozess, den die Hochschulen und Lehrenden nun aktiv weitergestalten sollten, wobei IHF und BayZiel weiterhin beratend zur Seite stehen.

(English) When using voltage source converters (VSC) to control the load flow between the DC voltage circuit and n-phase AC consumers/generators, distortion currents/voltages occur due to the principle involved. These describe the deviation of the real, measurable signal from its ideal, desired course. The distortion voltages occurring at the AC-side connection points of the VSC correspond to the deviation from the specified set voltage. At the DC-side connection point strong distortion currents are superimposed on the direct current emitted or absorbed by the VSC. Within the scope of this work, the emergence of the DC-side distortion currents, caused by the switching mode of operation of the VSC, based on corresponding literature sources, is discussed. The consideration here is limited to the differential mode components of the currents mentioned, a common mode consideration is not carried out. Criteria for describing the DC-side distortion currents and factors for influencing these criteria are derived from the results of the investigations carried out. For a given system and operating range, the distortion current stress caused by the VSC can be varied by adapting the control method used. For this purpose, different control methods found in the literature are selected and the operating point-dependent distortion current stress caused by them is determined analytically. To verify the results, a simulation model is developed and tests are carried out on an experimental test setup. The VSC is operated with a modulator-based control method as well as with a direct current control method. The results are compared regarding the DC-side distortion current. Namely, the control methods used are Space Vector Modulation (SVM) and Scalar Hysteresis Control (SHC). The latter was developed at the Technical University of Applied Sciences Wuerzburg-Schweinfurt. If the DC-side distortion current stress caused by the VSC is known, a filter can be designed that reduces the interference emission of the VSC to a specified level. As a level for the remaining interference emission, the remaining voltage ripple at the DC-side connection point of the filter is usually used in regulative specifications. Passive filters consisting of one or more capacitors of the same or different type are usually used for this purpose. This filter structure is described below as conventional structure. The different variants are presented accordingly and the filter capacitor is designed analytically/numerically on a concrete example for the DUT operated with SHC as well as SVM. Concepts known from literature for reducing the passive filter effort are presented and their effects on the DC-side distortion current load are described analytically. The concepts presented are divided into the categories of horizontal and vertical extension of the VSC as well as extension by downstream active components. In the second part of the work, a non-linear hybrid filter consisting of an actively controlled four-quadrant controller and two passive filter stages is designed and a methodology for the design of the components is developed. Furthermore, a modulation scheme with superimposed control for the use of the four-quadrant controller as an active filter is developed. The methodology for designing the filter is applied to the DUT used in this work as an example. The verification of the calculated results is carried out using a simulation model and an experimental test setup. Finally, the presented and more detailed passive filter variants as well as the developed non-linear hybrid filter are compared with each other in terms of construction volume and interference immunity. This shows that the presented non-linear hybrid filter has a significantly better interference immunity and a lower tendency to oscillate compared to passive filters. As a result, a more stable filter effect can be expected, especially when used in dynamic systems or systems with unknown dynamic behaviour.

In speed control of permanent magnet synchronous motors, the measured position signal is usually used for motor commutation and speed calculation. Since the position and speed signals are fed back to the controller, a sensor fault during operation is a severe problem. This contribution proposes a simple linear estimation method that reconstructs rotor position and speed. A comparison between measured signals and estimates allows to detect faults during operation. Furthermore, the estimated signals are used for reconfiguration after the occurrence of a fault. The fault detection logic is based on an adaptive threshold facilitating an operating point-dependent compromise between robustness against uncertainties and sensitivity to faults. Measurement results show that no faults are detected during fault-free operation, whereas the proposed algorithm instantly recognizes the sudden supply voltage outage of the used incremental encoder. The investigated reconfiguration mechanism allows for the control of the motor at medium and high speeds after the detection of a fault. This can be used to decelerate the motor in a controlled manner.

Laser powder bed fusion of metal has emerged as a key technology in additive manufacturing, enabling the production of intricate, high-performance metal components directly from digital designs. However, challenges such as dimensional inaccuracies and internal defects continue to hinder its broader industrial application. Addressing these limitations requires enhanced process monitoring and control strategies. This study introduces an innovative process monitoring system, designed to improve defect detection and process control. By employing a dual scan head configuration, enabling precise and independent path planning of the laser and the measurement field of an infrared camera, the Synchronized Path Infrared Thermography (SPIT) setup utilizes the principle of exploiting differences in cooling behavior to identify subsurface defects. Pre-printed samples with embedded cylindrical defects ranging from 300 to 1000 μm in diameter are used and an additional layer of powder is applied and fused within the experimental setup. The volumetric energy density and scanning speed are varied to analyze their influence on process monitoring reliability. The sensor scan head is synchronized with the laser scan head’s movements, while the infrared camera captures thermal radiation at 1904 fps. The results demonstrate the system’s capability to detect subsurface defects with a minimum size of 356 µm.