TY - CHAP A1 - Reindl, Andrea A1 - Lausser, Florian A1 - Eriksson, Lars A1 - Park, Sangyoung A1 - Niemetz, Michael A1 - Meier, Hans ED - Pinker, Jiří T1 - Control Oriented Mathematical Modeling of a Bidirectional DC-DC Converter - Part 1: Buck Mode T2 - 28th International Conference on Applied Electronics (AE) 2023, Pilsen, 6-7 September 2023 N2 - Parallel connection of different batteries equipped with bidirectional DC-DC converters offers an increase of the total storage capacity, the provision of higher currents and an improvement of reliability and system availability. To share the load current among the DC-DC converters while maintaining the safe operating range of the batteries, appropriate controllers are needed. The basis for the design of these control approaches requires knowledge of both the static and dynamic characteristics of the DC-DC converter used. In this paper, the small signal analysis of a DC-DC converter in buck mode is shown using the circuit averaging technique. The paper gives an overview of all required transfer functions:. The control and line to output transfer functions for CCM and DCM relevant for average current mode control as well as for voltage control are derived and their poles and zeros are determined. This provides the basis for stability consideration, analysis of the overall control structure and controller design. KW - Analytical models KW - Average modeling KW - Batteries KW - bidirectional dc-dc converter KW - buck mode KW - circuit-averaging technique KW - continuous conduction mode KW - DC-DC power converters KW - derivation of transfer functions KW - discontinuous conduction mode KW - half-bridge KW - Mathematical models KW - Reliability KW - Signal analysis KW - small signal analysis KW - Stability analysis Y1 - 2023 SN - 979-8-3503-3554-5 U6 - https://doi.org/10.1109/AE58099.2023.10274168 SP - 1 EP - 7 PB - University of West Bohemia CY - Pilsen ER - TY - CHAP A1 - Fuhrmann, Thomas A1 - Niemetz, Michael T1 - Analysis and Improvement of Engineering Exams Toward Competence Orientation by Using an AI Chatbot T2 - Towards a Hybrid, Flexible and Socially Engaged Higher Education: Proceedings of the 26th International Conference on Interactive Collaborative Learning (ICL2023), Volume 1 N2 - ChatGPT is currently one of the most advanced general chatbots. This development leads to diverse challenges in higher education, like new forms of teaching and learning, additional exam methods, new possibilities for plagiarism, and many more topics. On the other side with the development of advanced AI tools, pure knowledge will be less and less important, and demands from industry will change toward graduates with higher competencies. Education has therefore to be changed from knowledge-centered toward competence centered. The goal of this article is to use ChatGPT for analyzing and improving the competence orientation of exams in engineering education. The authors use ChatGPT to analyze exams from different engineering subjects to evaluate the performance of this chatbot and draw conclusions about the competence orientation of the tested exams. The obtained information is used to develop ideas for increasing the competence orientation of exams. From this analysis, it is visible that ChatGPT gives good performance mainly where knowledge is tested. It has, however, much more problems with transfer questions or tasks where students need creativity or complex insights for finding new solutions. Based on this result, exams and also lectures can be optimized toward competence orientation. KW - Engineering education KW - Competence orientation KW - Exam analysis KW - AI chatbot KW - ChatGPT Y1 - 2024 SN - 9783031519789 U6 - https://doi.org/10.1007/978-3-031-51979-6_42 SN - 2367-3370 SP - 403 EP - 411 PB - Springer Nature CY - Cham ER -