Modular multilevel converters are being researched more and more due to the large number of possible applications. In addition to physical experiments, simulations also provide important insights. To make this possible, it is necessary to be able to take advantage of high-performance simulations. This paper introduces a framework to simulate a system consisting of a Permanent magnet synchronous motor (PMSM) and three phases, each with a full-bridge converter and a Battery Modular Multilevel Management (BM3) converter. This framework allows it to simulate up to at least 140 BM3 modules per phase. In experiments, it was shown that it is possible to simulate 10 modules per phase in 1.43 s per uptime second.

Transcranial magnetic stimulation is widely used in clinical treatment and scientific research. It is facilitated through magnetic air coils, mostly built from copper high-frequency Litz wire. The magnetic stimulation coil induces a focused electrical field in the targeted tissue region of interest to trigger neuromodulation. The coil built-up, as well as its exact electrical properties, are important for the behavior of the triggered stimulation as well as the understanding of how to theoretically model and simulate such a system. This paper investigates the impedance behavior of two commercially available figure-of-eights shaped coils over a wide frequency range (up to 100 kHz) and compares the results to a custom-built round coil. All coils show similar electrical characteristics and, thus, these can be interchanged between stimulation devices without major adjustments. Moreover, the obtained results can be used for further theoretical investigations.

The technology of transcranial magnetic stimulation (TMS) enables to break new ground in medical research. It is suitable for different diagnostics, as well as therapeutic purposes, such as the treatment of depression or epilepsy, which are not fully explored yet. TMS devices that are currently available on the market offer a limited possibility for a targeted stimulation, due to their predefined voltage pulse shape. This paper presents a novel TMS device based on a multilevel inverter technology. Utilizing several cascaded sub-modules (built as H-bridges), arbitrary output waveforms can be discretely generated. At first, a theoretical part discusses how the energy efficiency of such a device can be increased by applying suitable control strategies and how it is possible to charge multiple sub-modules with only one auxiliary power supply. In addition, it is shown how to determine the required capacitance rating of a sub-module. Next, in the practical part, a designed prototype is presented and its current and voltage capabilities are verified, conducting 2.3 kA (peak-to-peak). In addition, the influence of different dead-times on the output voltage waveform is investigated. It is shown that the precise adjustment of the dead-time is crucial to ensure the proper switching of the required current without damaging the hardware.

This paper shows two approaches to determine the battery impedance of battery cells or battery modules when used in a reconfigurable battery system (RBS) or in any type of modular multilevel converter (MMC) for electric drive applications. A generic battery model is used and the concepts of the recursive time and frequency-domain parameter extraction, using a current step and an electrochemical impedance spectroscopy, are explained. Thus, it is shown and demonstrated that the balancing current of neighboring cells/modules ,when in parallel operation, can be used, similar to the time-domain parameter extraction utilizing a current step, to determine the battery parameters. Furthermore, it is shown and demonstrated that a part of the inverter can be used as variable AC voltage source to control a sinusoidal current through the motor inductances of the drive train, which can be injected to the inserted battery cells/modules of an adjacent phase to perform an on-board impedance spectroscopy. Using either of the two presented approaches, the individual battery impedances can be easily determined, yielding the state of health (SOH) and the power capability of individual battery cells/modules. Nonetheless, the analyzed approaches were just considered to be applied at machine standstill, which is not suitable for grid-tied applications.

This paper shows a sensorless capacitor voltage balancing control approach for a grid-connected, single-phase hybrid multilevel inverter based on an NPC main stage with a voltage stiff DC-link and an arbitrary number of H-Bridge modules (capacitor modules) with asymmetric capacitor voltages. Using nearest-level control, a model predictive control (MPC) approach with a prediction horizon of one time step is chosen to find an optimal switching-state combination among the redundant switching combinations to balance the capacitor voltages as quick as possible. Using the Lyapunov stability criterion, it is shown that an offline calculated optimal switching-state sequence for each discrete output voltage level can be used to operate the inverter without using any voltage sensors for the capacitor voltages. To validate the stability of the approach, a laboratory inverter with a resistive load is operated with the offline calculated optimal switching-state sequences and it is shown that the capacitor voltages converge to their desired reference voltages.