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- Control Theory, Kalman Filters, Modular Multilevel Converters, Notch Filters (1)
- Control theory , DC-AC Power Converters , Kalman Filter , Modular Multilevel Converter , Notch Filter (1)
- Iterative Learning Control, Repetitive Control, Current Harmonics, PMSM, Motor Control (1)
- Real-time system , control platform , model predictive control , modular multilevel converter , Zynq , SoC FPGA , UltraScale + , heterogeneous system architecture , low latency , low jitter , high signal integrity , power electronics (1)
- externally excited synchronous machine , electric mobility , drive control , trajectory planning , input-output linearization , inductive energy transfer (1)
An advanced control concept for modular multilevel converter using capacitor voltage estimation
(2017)
An advanced control concept for a Modular Multilevel Converter (MMC) is presented in this paper. By using a Notch Filter and a Kalman Filter it is possible to reduce unwanted AC components within circulating currents in the MMC significantly. Subsequently the current stress and the conduction and switching losses in the semiconductors can be minimized. In the second part of this paper, approaches to estimate the capacitor voltages are presented. The observability is inverstigated theoretically and via simulations. A disadvantage of the MMC topology is the need of a complex and expensive communication system. While the submodule voltages are being estimated, the communication effort between the submodules and the main controller hardware is significantly reduced.
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.
The magnitude of current harmonics depends on the design of an electrical machine. By suppressing these harmonics noise can be reduced and efficiency improved. Iterative Learning Control (ILC) has proven effective in reducing harmonics. One of the challenges of working with ILC is operation at varying speeds. Variable speeds are particularly important for applications like automotive drives. The ILC period length changes during the learning process at varying speeds. Due to fixed sample rates, the number of values processed by the ILC varies with motor speed.This paper proposes a method to solve this problem and uses ILC at varying speeds. The ILC used to eliminate the harmonics is based on the inverse system. The usage of a two-dimensional memory array is proposed. This data structure holds rows for specific speeds between which interpolation is performed, enabling the elimination of errors which are periodically cyclic to one electrical rotation. This includes the reduction of the motor current harmonics. To verify the presented method a permanent magnet synchronous motor with distinctive 5th and 7th harmonics is used. In real-time implementations, limitations of memory and computational capacity occur.
Electrical machines generate unwanted flux and current harmonics. Harmonics can be suppressed using various methods. In this paper, the harmonics are significantly reduced using Iterative Learning Control (ILC) and Neural Networks (NNs). The ILC can compensate for the harmonics well for operation at constant speed and current reference values. The NNs are trained with the data from the ILC and help to suppress the harmonics well even in transient operation. The simulation model is based on flux and torque maps, depending on dq-currents and the electrical angle. The maps are generated from FEM simulation of an interior permanent magnet synchronous machine (IPM) and are published with the paper. They are intended to serve other researchers for direct comparison with their own methods. Simulation results in this paper verify that by using ILC and NNs together, current harmonics in transient operation can be eliminated better than without NNs.
Electrical machines exhibit more or less strong current harmonics depending on their physical structure. The more slots are used per strand, the fewer harmonics an electrical machine has [1]. However, the manufacturing costs also increase with the number of slots. In permanent magnet synchronous machines (PMSM), the arrangement of the permanent magnets also influences the amplitude of the harmonics. Current harmonics can lead to increased motor noise and higher power losses. Therefore, it is worthwhile to deal with special controls which suppress these current harmonics. The aim of this work is to find a suitable control strategy for the suppression of current harmonics and to find out which method is suitable for which application. For this purpose, this paper presents and compares three types of control algorithms.
An approach to estimate the submodule capacitor voltages in a Modular Multilevel Converter (MMC) is presented and realized in a hardware test setup. One disadvantage of the MMC topology is the high communication and measurement effort. As the submodule voltages are being estimated, the measurement effort as well as the communication effort between the submodules and the main controller hardware is significantly reduced. Thereby, the reliability of the system also increases. In the hardware test setup, it is verified that using a notch filter in the feedback path of the energy control loop significantly decreases unwanted AC components of the circulating currents within the MMC. Subsequently the current stress as well as the conduction and switching losses in the semiconductors can be minimized. Furthermore, the dynamic performance of the capacitor voltage estimation and control scheme was analyzed via hardware tests.
Electrical machines generate unwanted flux and current harmonics. Harmonics can be suppressed by using various methods. In this paper, the harmonics are reduced by using iterative learning control (ILC) and neural networks (NNs). This paper focuses on the startup behavior of the control system. The ILC can compensate well for the harmonics in operation at constant speed and constant current reference values, but needs multiple rotations to learn. The NNs are trained with the data from the ILC and help to suppress the harmonics well even in transient operation and from the first rotation. The simulation model is based on flux and torque maps, depending on dq-currents and the electrical angle. The methods are also applied on the test bench and measurement results are presented.
An inductive energy transfer system (IETS) for the energy supply of the excitation coil of an externally excited synchronous machine (EESM) has been developed. Due to the removal of the slip rings, it is impossible to measure the excitation current and the rotor resistance on the rotating rotor. Therefore, a nonlinear observer for the EESM with IETS is presented, which estimates the excitation current and the rotor resistance. This observer is designed with the direct method of Lyapunov. Keywords—externally excited synchronous machine; electric mobility; drive control; inductive energy transfer; direct method of Lyapunov; nonlinear observer
Centralized SoC Balancing for Batteries with Droop-Controlled DC/DC Converters for Electric Aircraft
(2025)
In this article, an approach to balance the State of Charge (SoC) of two batteries connected to the DC bus of a fuel cell (FC) electric aircraft by Droop-controlled converters is described. The proposed algorithm is based on shifting the Droop reference voltages and prevents the simultaneous charging and discharging of the batteries. This approach is not only practical but also highly versatile, as it is compatible with all converters as long as the Droop voltage can be changed remotely, and a current measurement is provided to a central controller. No further programming access to the DC/DCs is necessary. There is no need for nonlinear or different-valued Droop resistances for charging and discharging. The balancing approach is validated via simulation in MATLAB/Simulink 2024a.The results show that the proposed approach achieves SoC balancing without degrading the dynamic performance of the grid. The delays added by the slower communication with the central controller have a minimal impact on performance.