@phdthesis{58756,
  abstract     = {{Der Permanentmagnet-Synchronmotor (PMSM) ist aufgrund seiner hohen Leistungs- und Drehmomentdichte bezogen auf Volumen und Gewicht ein häufig verwendeter Traktionsmotor in Automobilanwendungen. Jene Charakteristika werden jedoch maßgeblich durch Temperaturhöchstwerte begrenzt. Hinzu kommt, dass die Temperatur wichtiger Rotorkomponenten nicht wirtschaftlich messbar ist. Temperaturschätzverfahren wie modellbasierte Ansätze sind potentiell in der Lage, das Problem der fehlenden Temperaturinformation zu relativieren, ohne zusätzliche Geräte zu erfordern. Diese Arbeit stellt ein Portfolio von thermischen Modellen aus dem Bereich des maschinellen Lernens zusammen. Die Untersuchung basiert auf einem PMSM-Datensatz, der auf einem Prüfstand aufgezeichnet wurde. Neben dem durchschnittlichen Schätzfehler diktiert die erforderliche Anzahl von Modellparametern zahlreiche Auslegungsentscheidungen. Der gesamte Entwurfsprozess eines Modells aus dem maschinellen Lernen wird beleuchtet und für verschiedene lineare, sowie baumbasierte Modelle; vorschiebende, rekurrente und faltende neuronale Netze als auch für verschiedene hybride Modellierungsansätze durchgeführt. Desweiteren wird der hybride Modellierungsansatz über thermische neuronale Netze besonders hervorgehoben. Sie setzen sich aus neuronalen Netzen und einem thermischen Ersatzschaltbild zusammen und wurden erstmals vom Autor dieser Arbeit veröffentlicht. Schließlich wird ein von Experten entworfenes, datengetriebenes thermisches Netz mit konzentrierten Parametern über verschiedene Algorithmen optimiert und als Stand der Technik herangezogen.}},
  author       = {{Kirchgässner, Wilhelm}},
  publisher    = {{LibreCat University}},
  title        = {{{Data-driven thermal modeling of a permanent magnet synchronous motor with machine learning}}},
  doi          = {{10.17619/UNIPB/1-2068}},
  year         = {{2024}},
}

@phdthesis{58757,
  abstract     = {{On-bord DC-DC-Konverter sind das Bindeglied zwischen der Traktionsbatterie und der Hilfsbatterie und versorgen wichtige Komponenten des Elektrofahrzeugs. Diese Arbeit adressiert den weiten Spannungsbereich des Wandlers, der eine Folge der variierenden Spannungen der Batterien ist. Als potentielle Topologien werden der LLC Resonanzwandler, der aktiv geklemmte Flusswandler und der isolierte Vollbrücken-Konverter untersucht.Zunächst wird hierbei der LLC untersucht und verschiedene Modulationstechniken zur Abdeckung des weiten Spannungsbereichs gegenübergestellt, um zu zeigen, dass die Frequenzverdoppler-Modulation und die alternierende Phasenverschiebungsmodulation die maximale Temperatur der Halbleiter deutlich senken. Zum Wechsel zwischen Voll- und Halbbrückenmodulation wird eine Modulationstechnik vorgeschlagen, welche den transienten Magnetisierungsfluss um über 70 % respektive des konventionellen Konzept senkt. Für den aktiv geklemmten Flusswandler wird ein verbessertes Modell vorgestellt, das die Blockierspannung sehr genau modelliert. Zudem wird eine Snubber-Schaltung vorgeschlagen, welche die sekundärseitige transiente Blockierspannung deutlich reduziert. Für den isolierten Vollbrücken-Konverter werden hart- und weichschaltende Modulationstechniken analysiert und eine hartschaltende Frequenz-Verdoppler-Modulationstechnik vorgeschlagen, welche die maximale Schaltertemperatur deutlich reduziert und eine Modulationstechnik mit Beschaltung vorgestellt, um zwischen dem Voll- und Halbbrückenmodus zu wechseln. Die zuvor erarbeiteten Konverter werden unter Anwendung einer vorgestellten Designmethodik verglichen und messtechnisch evaluiert.}},
  author       = {{Rehlaender, Philipp}},
  publisher    = {{LibreCat University}},
  title        = {{{Single-stage DC-DC converters for a wide input & output voltage range}}},
  doi          = {{10.17619/UNIPB/1-2148}},
  year         = {{2024}},
}

@phdthesis{58682,
  author       = {{Brosch, Anian}},
  title        = {{{Time-optimal control of synchronous machines in the whole modulation range considering current and torque constraints }}},
  doi          = {{10.17619/UNIPB/1-2064}},
  year         = {{2024}},
}

@article{48059,
  author       = {{Winkel, Fabian and Wallscheid, Oliver and Scholz, Peter and Böcker, Joachim}},
  issn         = {{2644-1284}},
  journal      = {{IEEE Open Journal of the Industrial Electronics Society}},
  keywords     = {{Electrical and Electronic Engineering, Industrial and Manufacturing Engineering, Control and Systems Engineering}},
  pages        = {{1--14}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Pseudo-Labeling Machine Learning Algorithm for Predictive Maintenance of Relays}}},
  doi          = {{10.1109/ojies.2023.3323870}},
  year         = {{2023}},
}

@article{48058,
  author       = {{Winkel, Fabian and Deuse-Kleinsteuber, Johannes and Böcker, Joachim}},
  issn         = {{0018-9529}},
  journal      = {{IEEE Transactions on Reliability}},
  keywords     = {{Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality}},
  pages        = {{1--14}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Run-to-Failure Relay Dataset for Predictive Maintenance Research With Machine Learning}}},
  doi          = {{10.1109/tr.2023.3255786}},
  year         = {{2023}},
}

@inproceedings{48352,
  abstract     = {{Star-connected cascaded H-bridge Converters require large DC-link capacitors to buffer the second-order harmonic voltage ripple. First, it is analytically proven that the DC-link voltage ripple is proportional to the apparent converter power and does not depend on the power factor for nominal operation with sinusoidal reference arm voltages and currents. A third-harmonic zero-sequence voltage injection with an optimal amplitude and phase angle transforms the 2nd harmonic to a 4th harmonic DC-link voltage ripple. This reduces the voltage ripple by exactly 50% for all power factors at steady-state at balanced conditions. However, this requires 54% additional modules for unity power factor operation and even 100% for pure reactive power operation to account for the increased reference arm voltages due to the large amplitude of the optimal third-harmonic injection. If not enough modules are available, an adaptive discontinuous PWM is utilized to still minimize the voltage ripple for the given number of modules and power factor. With a very limited number of modules (modulation index is 1.15), the proposed method still reduces the DC-link voltage ripple by 24.4% for unity power factor operation. It requires the same number of modules as the commonly utilized 3rd harmonic injection with 1/6 of the grid voltage amplitude and achieves superior results. Simulations of a 10 kV/1 MVA system confirm the analysis.}},
  author       = {{Unruh, Roland and Böcker, Joachim and Schafmeister, Frank}},
  booktitle    = {{2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe)}},
  isbn         = {{979-8-3503-1678-0}},
  keywords     = {{Cascaded H-Bridge, Solid-State Transformer, Capacitor voltage ripple, Zero sequence voltage, Third harmonic injection}},
  location     = {{Aalborg, Denmark}},
  publisher    = {{IEEE}},
  title        = {{{An Optimized Third-Harmonic Injection Reduces DC-Link Voltage Ripple in Cascaded H-Bridge Converters up to 50% for all Power Factors}}},
  doi          = {{10.23919/epe23ecceeurope58414.2023.10264313}},
  year         = {{2023}},
}

@inproceedings{48093,
  author       = {{Pena, Mario and Meyer, Michael and Wallscheid, Oliver and Böcker, Joachim}},
  booktitle    = {{2023 IEEE International Electric Machines and Drives Conference (IEMDC)}},
  location     = {{San Francisco}},
  publisher    = {{IEEE}},
  title        = {{{Fade-Over Strategy for use of Model Predictive Direct Self-Control with Field-Oriented Control}}},
  doi          = {{10.1109/iemdc55163.2023.10239056}},
  year         = {{2023}},
}

@article{48092,
  author       = {{Pena, Mario and Meyer, Michael and Wallscheid, Oliver and Böcker, Joachim}},
  issn         = {{0885-8993}},
  journal      = {{IEEE Transactions on Power Electronics}},
  keywords     = {{Electrical and Electronic Engineering}},
  number       = {{10}},
  pages        = {{12416--12429}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Model Predictive Direct Self-Control for Six-Step Operation of Permanent-Magnet Synchronous Machines}}},
  doi          = {{10.1109/tpel.2023.3286713}},
  volume       = {{38}},
  year         = {{2023}},
}

@article{49760,
  author       = {{Jakobeit, Darius and Schenke, Maximilian and Wallscheid, Oliver}},
  issn         = {{0885-8993}},
  journal      = {{IEEE Transactions on Power Electronics}},
  keywords     = {{Electrical and Electronic Engineering}},
  number       = {{7}},
  pages        = {{8062--8074}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Meta-Reinforcement-Learning-Based Current Control of Permanent Magnet Synchronous Motor Drives for a Wide Range of Power Classes}}},
  doi          = {{10.1109/tpel.2023.3256424}},
  volume       = {{38}},
  year         = {{2023}},
}

@inproceedings{53310,
  author       = {{Gedlu, Emebet Gebeyehu and Wallscheid, Oliver and Böcker, Joachim and Nelles, Oliver}},
  booktitle    = {{2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)}},
  publisher    = {{IEEE}},
  title        = {{{Online system identification and excitation for thermal monitoring of electric machines using machine learning and model predictive control}}},
  doi          = {{10.1109/sdemped54949.2023.10271427}},
  year         = {{2023}},
}

@article{53543,
  author       = {{Winkel, Fabian and Scholz, Peter and Wallscheid, Oliver and Böcker, Joachim}},
  issn         = {{1545-5955}},
  journal      = {{IEEE Transactions on Automation Science and Engineering}},
  keywords     = {{Electrical and Electronic Engineering, Control and Systems Engineering}},
  pages        = {{1--11}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Reducing Contact Bouncing of a Relay by Optimizing the Switch Signal During Run-Time}}},
  doi          = {{10.1109/tase.2023.3322762}},
  year         = {{2023}},
}

@inproceedings{54352,
  author       = {{Urbaneck, Daniel and Böcker, Joachim and Schafmeister, Frank}},
  booktitle    = {{PCIM Europe 2023; IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management }},
  isbn         = {{978-3-8007-6091-6}},
  location     = {{Nuremberg}},
  title        = {{{Advanced Synchronous Rectification for an IGBT-Based ZCS LLC Converter with High Output Currents for a 2 kW Automotive DC-DC Stage}}},
  year         = {{2023}},
}

@inproceedings{54838,
  author       = {{Boshoff, Septimus and Stenner, Jan and Weber, Daniel and Meyer, Marvin and Chidananda, Vikas and Peitz, Sebastian and Wallscheid, Oliver}},
  booktitle    = {{IEEE Power and Energy Student Summit (PESS)}},
  isbn         = {{978-3-8007-6318-4}},
  pages        = {{124--129}},
  publisher    = {{VDE}},
  title        = {{{Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches}}},
  year         = {{2023}},
}

@inproceedings{54839,
  author       = {{Meyer, Marvin and Weber, Daniel and Chidananda, Vikas and Schweins, Oliver and Stenner, Jan and Boshoff, Septimus and Peitz, Sebastian and Wallscheid, Oliver}},
  booktitle    = {{IEEE Power and Energy Student Summit (PESS)}},
  isbn         = {{978-3-8007-6318-4}},
  pages        = {{112--117}},
  publisher    = {{VDE}},
  title        = {{{ElectricGrid.jl – Automated modeling of decentralized electrical energy grids}}},
  year         = {{2023}},
}

@book{41369,
  author       = {{Böcker, Joachim}},
  publisher    = {{Paderborn University}},
  title        = {{{Mechatronik und elektrische Antriebe / Mechatronics and electrical drives}}},
  doi          = {{10.17619/UNIPB/1-1640}},
  year         = {{2023}},
}

@article{43456,
  author       = {{Brosch, Anian and Wallscheid, Oliver and Böcker, Joachim}},
  issn         = {{0885-8993}},
  journal      = {{IEEE Transactions on Power Electronics}},
  keywords     = {{Electrical and Electronic Engineering}},
  pages        = {{1--14}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Time-Optimal Model Predictive Control of Permanent Magnet Synchronous Motors Considering Current and Torque Constraints}}},
  doi          = {{10.1109/tpel.2023.3265705}},
  year         = {{2023}},
}

@article{46147,
  author       = {{Brosch, Anian and Tinazzi, Fabio and Wallscheid, Oliver and Zigliotto, Mauro and Böcker, Joachim}},
  issn         = {{0885-8993}},
  journal      = {{IEEE Transactions on Power Electronics}},
  keywords     = {{Electrical and Electronic Engineering}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Finite Set Sensorless Control With Minimum a Priori Knowledge and Tuning Effort for Interior Permanent Magnet Synchronous Motors}}},
  doi          = {{10.1109/tpel.2023.3294557}},
  year         = {{2023}},
}

@article{46213,
  author       = {{Weber, Daniel and Schenke, Maximilian and Wallscheid, Oliver}},
  issn         = {{2169-3536}},
  journal      = {{IEEE Access}},
  keywords     = {{General Engineering, General Materials Science, General Computer Science, Electrical and Electronic Engineering}},
  pages        = {{76524--76536}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Steady-State Error Compensation for Reinforcement Learning-Based Control of Power Electronic Systems}}},
  doi          = {{10.1109/access.2023.3297274}},
  volume       = {{11}},
  year         = {{2023}},
}

@inproceedings{46212,
  author       = {{Weber, Daniel and Schenke, Maximilian and Wallscheid, Oliver}},
  booktitle    = {{2023 International Conference on Future Energy Solutions (FES)}},
  publisher    = {{IEEE}},
  title        = {{{Safe Reinforcement Learning-Based Control in Power Electronic Systems}}},
  doi          = {{10.1109/fes57669.2023.10182718}},
  year         = {{2023}},
}

@article{46784,
  author       = {{Wallscheid, Oliver and Peitz, Sebastian and Stenner, Jan and Weber, Daniel and Boshoff, Septimus and Meyer, Marvin and Chidananda, Vikas and Schweins, Oliver}},
  issn         = {{2475-9066}},
  journal      = {{Journal of Open Source Software}},
  keywords     = {{General Earth and Planetary Sciences, General Environmental Science}},
  number       = {{89}},
  publisher    = {{The Open Journal}},
  title        = {{{ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids}}},
  doi          = {{10.21105/joss.05616}},
  volume       = {{8}},
  year         = {{2023}},
}