Robustness Measures and Numerical Approximation of the Cumulative Density Function of Response Surfaces

Robust design optimization is used to examine the effect of variations in the design variables, for example production tolerances, on the response variables. This article presents a new approach for uncertainty propagation, supplemented by a comparativestudy of various methods. These are design of experiments in combination with quantile and kernel density estimation to approximate the cumulative density function of the response. The accuracy and efficiency of the novel methods in comparison to the standard method of determining, which is the empirical distribution function is investigated by means of mathematical analyses and a numerical study proving the suitability of the proposed proceeding. The article also discusses different robustness measures and their suitability in engineering. A new one based on quantiles is introduced

Model – Based Approach to investigate the Influences of different Load States to the Vehicle Dynamics of Light Electric Vehicles

The need to find alternative urban mobility solutions for delivery and transporthas led mobility companies to devote enormous resources for researchbasedsolutions to increase vehicle safety. This paper documents a virtual approachto investigate the influences of different load states to the vehicle dynamicof light electric vehicle. A model basing on a three-dimensional multibody system was used, which consists of five bodies. By applying methods of multibody modelling the generalized equations of motion were generated. To include the behavior within the contact point between road and vehicle a simplified tire models was added. The implementation of the equations allowed a first validation of the model via simulations. In a final modeling step the simulation results were interpreted in respect of plausibility. Afterwards,the model was simulated numerically to investigate different load states of the vehicle, by applying constant steering stimuli and variable velocities. In sum,the investigated model approach is useful to identify safety relevant parameters and shows the effects of load states to the vehicle dynamics. Furthermore, it behaves plausibly regarding general vehicle dynamics. These results prove the general usability of the model for the development controllers and estimators in driver assistances systems

Methodical Approach to the Development of a Radar Sensor Model for the Detection of Urban Traffic Participants Using a Virtual Reality Engine

New approaches for testing of autonomous driving functions are using VirtualReality (VR) to analyze the behavior of automated vehicles in variousscenarios. The real time simulation of the environment sensors is still a challenge.In this paper, the conception, development and validation of an automotiveradar raw data sensor model is shown. For the implementation, theUnreal VR engine developed by Epic Games is used. The model consists of asending antenna, a propagation and a receiving antenna model. The microwavefield propagation is simulated by a raytracing approach. It uses the methodof shooting and bouncing rays to cover the field. A diffused scatteringmodel is implemented to simulate the influence of rough structures on thereflection of rays. To parameterize the model, simple reflectors are used. Thevalidation is done by a comparison of the measured radar patterns of pedestriansand cyclists with simulated values. The outcome is that the developedmodel shows valid results, even if it still has deficits in the context of performance.It shows that the bouncing of diffuse scattered field can only be doneonce. This produces inadequacies in some scenarios. In summary, the papershows a high potential for real time simulation of radar sensors by using raytracing in a virtual reality

Development and Analysis of a Detail Model for Steer-by-Wire Systems

Steer-by-wire systems represent a key technology for highly automated and autonomous driving. In this context, robust steering control is a fundamental precondition for automated vehicle lateral control. However, there is a need for improvement due to degrees of freedom, signal delays, and nonlinear characteristics of the plant which are unconsidered in the design models for the design of current steering controls. To be able to design an extremely robust steering control, suitable optimal models of a steer-by-wire system are required. Therefore, this paper presents an innovative nonlinear detail model of a steer-by-wire system. The detail model represents all characteristics of a real steer-by-wire system. In the context of a dominance analysis of the detail model, all dominant characteristics of a steer-by-wire system, including parameter dependencies, are identified. Through model reduction, a reduced model of the steer-by-wire system is then developed that can be used for a subsequent robust control design. Furthermore, this paper compares the steer-by-wire system with a conventional electromechanical power steering and shows similarities as well as differences

Leveraging Robust Artificial Intelligence for Mechatronic Product Development : A Literature Review

Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed

Künstliche Intelligenz als Co-Pilot: Warum Unternehmen im Fahrersitz bleiben müssen

In der heutigen digitalen Ära erleben wir eine Revolution durch die fortschreitende Entwicklung und die Integration von Künstlicher Intelligenz (KI) in alle Lebensbereiche. Der vorliegende Beitrag beleuchtet diese Transformation, indem er auf die bemerkenswerten Fortschritte und die zunehmende Bedeutung von KI für Gesellschaft und Wirtschaft eingeht, aber auch Optionen zur Bewältigung der damit einhergehenden Risiken aufzeigt. Der Artikel ist in mehrere Kapitel unterteilt, die verschiedene Dimensionen der KI-Einbindung in die Gesellschaft und Wirtschaft beleuchten. Zunächst wird erarbeitet, dass KI erstens nicht nur Produktivitätssteigerungen und Effizienzgewinne ermöglicht, sondern auch die Basis für Innovationen bietet, die unseren Alltag erleichtern können. Die intelligente Automatisierung von Routineaufgaben gibt Menschen den Freiraum, sich kreativeren und anspruchsvolleren Tätigkeiten zu widmen. Gleichzeitig kann KI auch schöpferische Prozesse unterstützen und inspirieren. Beides trägt zu einer Steigerung von Lebensqualität und Wohlstand bei. Bei der Betrachtung der erfolgreichen Einführung von KI in Unternehmen wird hervorgehoben, dass zweitens eine durchdachte KI-Strategie notwendig ist, um die Technologie effektiv zu nutzen: Unternehmen müssen nicht nur in die entsprechende Technik investieren, sondern auch in die Ausbildung ihrer Mitarbeiter. Eine umfassende KI-Kompetenz innerhalb der Belegschaft ist entscheidend, um innovative Lösungen zu entwickeln und die Potenziale von KI voll auszuschöpfen. Die Entwicklung von Personal und Kompetenzen stellt daher - drittens - ein weiteres wichtiges Kapitel dar. Die Arbeitswelt wird sich durch KI wandeln, wodurch neue Anforderungen an die Fähigkeiten der Arbeitnehmer gestellt werden. Lebenslanges Lernen und die stetige Weiterbildung in digitalen Kompetenzen sind unerlässlich, um mit dem rasanten technologischen Fortschritt Schritt halten zu können. Gleichzeitig müssen Bildungseinrichtungen in der allgemeinen wie beruflichen Bildung ihre Curricula anpassen, um die nächste Generation auf eine Zukunft vorzubereiten, in der KI eine zentrale Rolle spielt. Basierend auf den Erkenntnissen der getätigten Analysen werden Handlungsoptionen zum Umgang mit KI abgeleitet. Durch regulatorische Rahmenbedingungen und die Sensibilisierung für die Beachtung von ethischen Richtlinien kann sichergestellt werden, dass die Weiterentwicklung und Nutzung von KI im Einklang mit gesellschaftlichen Werten und Normen erfolgt. Der Mensch sollte dabei stets im Mittelpunkt stehen, wobei die Technologie als Unterstützung dient, die menschliches Handeln ergänzt und erweitert, jedoch nicht ersetzt. KI stellt eine doppelte Herausforderung dar: Einerseits bietet sie unglaubliche Chancen für Innovation und Wohlstand, andererseits erfordert sie eine sorgfältige Steuerung und Anpassung auf individueller, unternehmerischer und gesellschaftlicher Ebene. Durch die Entwicklung kritischer KI-Kompetenzen und eine verantwortungsvolle Nutzung verbinden wir beide Aufgaben: das volle Potenzial von Künstlicher Intelligenz auszuschöpfen und gleichzeitig potenzielle Risiken zu minimieren. KI ist in diesem dynamischen Umfeld als Co-Pilot zu begreifen. Eine solche Haltung ist der Schlüssel, um die Weichen für eine Zukunft zu stellen, in der Technologie und Mensch bestmöglich zum gegenseitigen Nutzen zusammenarbeiten.In today's digital era, we are witnessing a revolution driven by the progressive development and integration of Artificial Intelligence (AI) into all aspects of life. This article sheds light on this transformation by highlighting the remarkable advancements and the growing significance of AI for society and economy. The article is divided into several chapters that illuminate various dimensions of AI integration in society and economy. Firstly, the article elaborates that AI enables not only productivity enhancements and efficiency gains but also serves as the foundation for innovations that can simplify our daily lives. The intelligent automation of routine tasks provides people with the freedom to engage in more creative and challenging activities, contributing to an improvement in quality of life and prosperity. Secondly, when examining the successful implementation of AI in companies, the article emphasiszes that a well-thought-out AI strategy is necessary to effectively utilize the technology: businesses must invest not only in the relevant tools but also in the training of their employees. Comprehensive AI competence within the workforce is crucial for developing innovative solutions and fully harnessing the potential of AI. Thirdly, the development of personnel and competencies represents another essential chapter. The world of work will transform due to AI, leading to new skill requirements for employees. Lifelong learning and continuous training in digital competencies are essential to keep pace with rapid technological advancements. Simultaneously, educational institutions must adapt their curricula to prepare the next generation for a future where AI plays a central role. Based on the insights from conducted analyses, actionable options regarding AI are derived. Regulatory frameworks and ethical guidelines ensure that the advancement and utilization of AI align with societal values and norms. Human-centricity remains paramount, with technology serving as a complement to human actions, enhancing and extending them, but not replacing them. AI presents a dual challenge: On one hand, it offers incredible opportunities for innovation and prosperity; on the other hand, it requires careful control and adaptation at individual, entrepreneurial, and societal levels. By developing critical AI competencies and practicing responsible use, we can fully harness the potential of AI while minimizing potential risks. Understanding AI as a co-pilot in this dynamic environment is the key to setting the course for a future where technology and humans collaborate harmoniously for mutual benefit

Development and Analysis of a Detail Model for Steer-by-Wire Systems

Steer-by-wire systems represent a key technology for highly automated and autonomous driving. In this context, robust steering control is a fundamental precondition for automated vehicle lateral control. However, there is a need for improvement due to degrees of freedom, signal delays, and nonlinear characteristics of the plant which are unconsidered in the design models for the design of current steering controls. To be able to design an extremely robust steering control, suitable optimal models of a steer-by-wire system are required. Therefore, this paper presents an innovative nonlinear detail model of a steer-by-wire system. The detail model represents all characteristics of a real steer-by-wire system. In the context of a dominance analysis of the detail model, all dominant characteristics of a steer-by-wire system, including parameter dependencies, are identified. Through model reduction, a reduced model of the steer-by-wire system is then developed that can be used for a subsequent robust control design. Furthermore, this paper compares the steer-by-wire system with a conventional electromechanical power steering and shows similarities as well as differences