@article{WendelKaramanakosGebhardtetal.2021, author = {Wendel, Sebastian and Karamanakos, Petros and Gebhardt, Philipp and Dietz, Armin and Kennel, Ralph}, title = {Flux Linkage-Based Direct Model Predictive Current Control for Synchronous Machines}, series = {IEEE Transactions on Power Electronics}, volume = {36}, journal = {IEEE Transactions on Power Electronics}, number = {12}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, issn = {0885-8993}, doi = {10.1109/tpel.2021.3083657}, pages = {14237 -- 14256}, year = {2021}, abstract = {This article presents a flux linkage-based direct model predictive current control approach that achieves favorable performance both during steady-state and transient operation. The former is achieved by computing the optimal time instants at which a new switch position is applied to the converter. To this end, the future current behavior is not computed based on the machine inductances or inductance look-up tables; instead, flux linkage maps are utilized to predict the trajectory of the magnetic flux linkage, and subsequently of the current. This is advantageous for electric drives with noticeable magnetic nonlinearity in terms of saturation and/or cross-coupling effects. Hence, by using flux linkage maps in the prediction process, the evolution of the stator current can be calculated more accurately, enabling the controller to make better switching decisions. Moreover, the discussed predictive controller exhibits excellent dynamic performance owing to its direct control nature, i.e., the control and modulation tasks are performed in one computational stage rendering a dedicated modulation stage redundant. Three different drive systems based on permanent magnet synchronous motors are examined to demonstrate the effectiveness of the presented control approach.}, language = {en} } @article{DietzDiTommasoMarignettietal.2020, author = {Dietz, Armin and Di Tommaso, Antonino Oscar and Marignetti, Fabrizio and Miceli, Rosario and Nevoloso, Claudio}, title = {Enhanced Flexible Algorithm for the Optimization of Slot Filling Factors in Electrical Machines}, series = {Energies}, volume = {13}, journal = {Energies}, number = {5}, publisher = {MDPI AG}, issn = {1996-1073}, doi = {10.3390/en13051041}, pages = {21}, year = {2020}, abstract = {The continuous development in the field of industrial automation and electric mobility has led to the need for more efficient electrical machines with a high power density. The improvement of electrical machines' slot filling factors is one of the measures to satisfy these requirements. In recent years, this topic has aroused greater interest in the industrial sector, since the evolution of the winding technological manufacturing processes allows an economically sustainable realization of ordered winding arrangements, rather than random ones. Moreover, the manufacture of electrical machines' windings must be preceded by an accurate design phase in which it is possible to evaluate the maximum slot filling factor obtainable for a given wire shape and for its dimensions. For this purpose, this paper presents an algorithmic approach for the evaluation of maximum slot filling factors in electrical machines under an ideal geometric premise. In particular, this algorithm has a greater degree of flexibility with respect to the algorithm approaches found in the literature, since the study has been extended to round, rectangular and hexagonal wire sections. Furthermore, the slot filling factor calculation was carried out both for standard and non-standard slots. The algorithmic approach proposed can be considered as an additional useful tool for the fast design of electrical machine windings.}, language = {en} } @inproceedings{GumpertVamboltSchmidtetal.2024, author = {Gumpert, Fabian and Vambolt, Eugen and Schmidt, Michael and Fromme, Lars and Dietz, Armin and Lohbreier, Jan}, title = {Physics-Informed Neural Networks to predict the Power Transmission of Electric Road Systems}, series = {2024 1st International Conference on Production Technologies and Systems for E-Mobility (EPTS)}, booktitle = {2024 1st International Conference on Production Technologies and Systems for E-Mobility (EPTS)}, publisher = {IEEE}, doi = {10.1109/EPTS61482.2024.10586741}, pages = {1 -- 7}, year = {2024}, language = {en} } @inproceedings{GerstnerMaerzDietz2020, author = {Gerstner, Michael and Maerz, Martin and Dietz, Armin}, title = {Design of a Wide Input Voltage Range Current-Fed DC/DC Converter Within a Reduced Duty-Cycle Range}, series = {2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe)}, booktitle = {2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe)}, publisher = {IEEE}, doi = {10.23919/epe20ecceeurope43536.2020.9215825}, pages = {10}, year = {2020}, abstract = {A design of a current-fed push-pull converter for wide input voltage ranges within a reduced duty-cycle range is presented. Based on the converter conversion ratios of three different clamping configurations, the potential of the input clamping is shown analytical, simulative and by measurements. A differentiation is made between the four possible operating modes, which can be distinguished in the control of the semiconductors and the magnetomotive force in the reactor. By optimizing the turn ratios of both transformers, the wide input voltage range capability of the input clamped current-fed push-pull converter was improved, which has been proved by measurements on a real prototype.}, language = {en} } @inproceedings{RabensteinDietzParspour2020, author = {Rabenstein, Lukas and Dietz, Armin and Parspour, Nejila}, title = {Design Concept of a Wound Field Transverse Flux Machine using Soft Magnetic Composite Claw-Poles}, series = {2020 10th International Electric Drives Production Conference (EDPC)}, booktitle = {2020 10th International Electric Drives Production Conference (EDPC)}, publisher = {IEEE}, doi = {10.1109/edpc51184.2020.9388176}, pages = {5}, year = {2020}, abstract = {This paper presents the machine concept of a wound field transverse flux machine (WFTFM). In contrast to permanent magnet transverse flux machines (PMTFM), here the magneto motive force (mmf) of the rotor is generated by a current. The magnetic circuit of the WFTFM is made of soft magnetic composite (SMC) and is designed as claw-poles. Thus the magnetic circuit consists of only a few components. Together with the simple ring coils in stator and rotor, the WFTFM offers advantages in the production of electrical machines. The basic structure of the machine and a first design is described here. The results generated by numerical three-dimensional finite element analysis (FEA) are compared with those of conventional machines.}, language = {en} } @inproceedings{BroghammerHufnagelSchindleretal.2023, author = {Broghammer, Lara and Hufnagel, Dennis and Schindler, Tobias and Hoerner, Michael and Karamanakos, Petros and Dietz, Armin and Kennel, Ralph}, title = {Reinforcement Learning Control of Six-Phase Permanent Magnet Synchronous Machines}, series = {2023 13th International Electric Drives Production Conference (EDPC)}, booktitle = {2023 13th International Electric Drives Production Conference (EDPC)}, publisher = {IEEE}, isbn = {979-8-3503-7049-2}, doi = {10.1109/edpc60603.2023.10372153}, pages = {8}, year = {2023}, abstract = {Control of multi-phase machines is a challenging topic due to the high number of controlled variables. Conventional control methods, such as field-oriented control (FOC), address this issue by introducing more control loops. This, however, increases the controller design complexity, while the tuning process can become cumbersome. To tackle the above, this paper proposes a deep deterministic policy gradient algorithm based controller that fulfills all the control objectives in one computational stage. More specifically, the proposed approach aims to learn a suitable current control policy for six-phase permanent magnet synchronous machines to simplify the commissioning of the drive system. In doing so, physical limitations of the drive system can be accounted for, while the compensation of imbalances between the two three-phase subsystems is rendered possible. After validating the training results in a controller-in-the-loop environment, test bench measurements are provided to demonstrate the effectiveness of the proposed controller. As shown, favorable steady-state and dynamic performance is achieved that is comparable to that of FOC. Therefore, as indicated by the presented results, reinforcement learning-based control approaches for multi-phase machines is a promising research area.}, language = {en} } @inproceedings{SchindlerBroghammerKaramanakosetal.2023, author = {Schindler, Tobias and Broghammer, Lara and Karamanakos, Petros and Dietz, Armin and Kennel, Ralph}, title = {Deep Reinforcement Learning Current Control of Permanent Magnet Synchronous Machines}, series = {2023 IEEE International Electric Machines \& Drives Conference (IEMDC)}, booktitle = {2023 IEEE International Electric Machines \& Drives Conference (IEMDC)}, publisher = {IEEE}, isbn = {979-8-3503-9899-1}, doi = {10.1109/IEMDC55163.2023.10238988}, pages = {7}, year = {2023}, abstract = {This paper presents a current control approach for permanent magnet synchronous machines (PMSMs) using the deep reinforcement learning algorithm deep deterministic policy gradient (DDPG). The proposed method is designed by examining different training setups regarding the reward function, the observation vector, and the actor neural network. In doing so, the impact of the different design factors on the steady-state and dynamic behavior of the system is assessed, thus facilitating the selection of the setup that results in the most favorable performance. Moreover, to provide the necessary insight into the controller design, the entire path from training the agent in simulation, through testing the control in a controller-in-the-loop (CIL) environment, to deployment on the test bench is described. Subsequently, experimental results are provided, which show the efficacy of the presented algorithm over a wide range of operating points. Finally, in an attempt to promote open science and expedite the use of deep reinforcement learning in power electronic systems, the trained agents, including the CIL model, are rendered openly available and accessible such that reproducibility of the presented approach is possible.}, language = {en} } @inproceedings{WendelGeigerLiegmannetal.2019, author = {Wendel, Sebastian and Geiger, Andreas and Liegmann, Eyke and Arancibia, David and Duran, Esteban and Kreppel, Thomas and Rojas, Felix and Popp-Nowak, Flaviu and Diaz, Matias and Dietz, Armin and Kennel, Ralph and Wagner, Bernhard}, title = {UltraZohm - a Powerful Real-Time Computation Platform for MPC and Multi-Level Inverters}, series = {2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)}, booktitle = {2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)}, publisher = {IEEE}, doi = {10.1109/PRECEDE.2019.8753306}, pages = {6}, year = {2019}, abstract = {This paper presents the hardware design, software architecture and workflow for rapid control prototyping intended for a wide-range of power electronics based systems. The proposed system is especially useful for computationally intensive algorithms and applications with high demands on the number of required measurements and gate signals. The focus is on a heterogeneous system architecture with minimized latency and jitter as well as a high signal integrity. The software architecture enables a simple, fast and performance driven implementation. A combination of carrier board and exchangeable interfacing adapter boards allows to control a wide range of power electronics applications and converters, i.e., starting with a single switching device, converters with one or several voltage levels and one or several phase legs, up to large modular multilevel converters for grid-tied connection or variable speed drives.}, language = {en} } @inproceedings{WendelKaramanakosDietzetal.2020, author = {Wendel, Sebastian and Karamanakos, Petros and Dietz, Armin and Kennel, Ralph}, title = {Flux Linkage-Based Model Predictive Current Control for Nonlinear PMSM Drives}, series = {IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society}, booktitle = {IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society}, publisher = {IEEE}, doi = {10.1109/iecon43393.2020.9254484}, year = {2020}, abstract = {In this paper, a flux linkage-based direct model predictive current control approach is presented for small permanent magnet synchronous motor (PMSM) drives. The method aims to minimize the current ripples at steady state by deciding on the optimal switching instant, while exhibiting fast dynamic behavior during transients. To this end, the future trajectory of the stator current is not computed based on the machine inductances or inductance look-up tables, but on the changes of the magnetic flux linkage by utilizing flux linkage maps. As shown, the proposed method can be particularly advantageous for electric drives with a noticeable nonlinearity in terms of saturation and/or cross-coupling effects since it allows for a significantly increased prediction accuracy, which leads to an improved steady-state performance as indicated by the reduced current distortions.}, language = {en} } @inproceedings{DietzdiTommasoMicelietal.2021, author = {Dietz, Armin and di Tommaso, A. O. and Miceli, R. and Nevoloso, C. and Schettino, G.}, title = {Enhanced Modelling for Extended Performance Analysis of Interior Permanent Magnet Synchronous Machine Drive fed with Cascaded H-Bridges Multilevel Inverter}, series = {2021 Sixteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)}, booktitle = {2021 Sixteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)}, publisher = {IEEE}, doi = {10.1109/ever52347.2021.9456635}, pages = {9}, year = {2021}, abstract = {This paper presents a comparative simulation analysis of an Interior Permanent Magnet Synchronous Machine (IPMSM) performance once fed by a traditional three-phase two-level inverter and then using a three-phase five-level Cascaded H-Bridges Multilevel Inverter (CHBMI). For this purpose, an enhanced mathematical model of the IPMSM, that take into account simultaneously saturation, cross-coupling, spatial harmonics and iron loss effects, has been employed. Furthermore, two different PWM modulation strategies have been considered. The study was conducted for several working conditions, evaluating the impact of CHBMI adoption on the IPMSM performance in terms of improved efficiency and torque ripple reduction.}, language = {en} } @inproceedings{DietzCarusoDiTommasoetal.2020, author = {Dietz, Armin and Caruso, M. and Di Tommaso, A. O. and Miceli, R. and Nevoloso, C.}, title = {Enhanced Mathematical Modelling of Interior Permanent Magnet Synchronous Machine Considering Saturation, Cross-Coupling and Spatial Harmonics effects}, series = {2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)}, booktitle = {2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)}, publisher = {IEEE}, doi = {10.1109/ever48776.2020.9243003}, pages = {9}, year = {2020}, abstract = {The Interior Permanent Magnet Synchronous machine (IPMSM) conventional mathematical model is generally employed to investigate and simulate the IPMSM control and drive system behaviour. However, magnetic nonlinearities and spatial harmonics have a substantial influence on the IPMSM electromagnetic behaviour and performances. In order to simulate the IPMSM real electromagnetic behaviour, this paper describes an enhanced mathematical model that takes into account the saturation, cross-coupling and spatial harmonics effects. This model has been implemented in Matlab®/Simulink environment where the electric and magnetic parameters are derived from FEA investigations and implemented by the use of lookup tables. The high fidelity of the proposed IPMSM Simulink model is validated by the results of the FEA investigations carried out.}, language = {en} } @inproceedings{GerstnerMaerzDietz2021, author = {Gerstner, Michael and Maerz, Martin and Dietz, Armin}, title = {Review-based Selection Recommendation for Galvanically Isolated DC/DC Converters Designed For a Wide Input Voltage Range}, series = {2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC)}, booktitle = {2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC)}, publisher = {IEEE}, doi = {10.1109/pemc48073.2021.9432537}, pages = {167 -- 172}, year = {2021}, abstract = {Depending on the application range, there are various recommendations in the literature which converter topology should be used. These are mostly based on experience or more or less deeper considerations. For DC/DC converters, which are operated over a wide input voltage range, such recommendations rarely exist. Therefore, this contribution shows the evolution of two input voltage dependent selection matrices, which should facilitate the selection of future topologies based on known publications and basic considerations. The focus here lies on converters for λ = V i_max /V i_min ≥ 3 with galvanic isolation. First, the data set is introduced, where a distinction is made between flyback converters, forward converters and other 1stage or 2stage converters before the evolution of the novel input voltage dependent matrices is carried out. These two matrices support the selection of a suitable topology and whether the energy transfer should be done by one or two stages.}, language = {en} } @inproceedings{LiegmannSchindlerKaramanakosetal.2021, author = {Liegmann, Eyke and Schindler, Tobias and Karamanakos, Petros and Dietz, Armin and Kennel, Ralph}, title = {UltraZohm — An Open-Source Rapid Control Prototyping Platform for Power Electronic Systems}, series = {2021 International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) \& 2021 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM)}, booktitle = {2021 International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) \& 2021 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM)}, publisher = {IEEE}, issn = {1842-0133}, doi = {10.1109/optim-acemp50812.2021.9590016}, pages = {6}, year = {2021}, abstract = {This paper presents two rapid control prototyping (RCP) use cases facilitated by the open-source platform UltraZohm. The openly available UltraZohm development frame- work eases the transition from simulation to the test bench. The framework offers the integration of automatic code generation for field-programmable gate arrays (FPGAs), either by using Simulink models based on the HDL Coder, or by synthesizing C++ code into VHDL via the Vivado high-level synthesis tool. The first use case focuses on the implementation details of an on-chip controller-in-the-loop setup, where a permanent magnetsynchronous machine is emulated in the FPGA with a sampling frequency of 2 MHz. The second use case presents an efficient real-time implemen-tation of the sphere decoding algorithm employed to solve the long-horizon finite control set model predictive control problem for a three-level neutral point clamped inverter driving an induction machine. Experimental results based on a small-scale prototype confirm that the algorithm can be executed in real time on the FPGA, with an execution time of a few tens of microseconds. Both use cases highlight the benefits of using a high-performance RCP platform for research in power electronics and their control.}, language = {en} }