Frederick Kieferndorf

Model Predictive Pulse Pattern Control

Industrial applications of medium-voltage drives impose increasingly stringent performance requirements, particularly with regards to harmonic distortions of the phase currents of the controlled electrical machine. An established method to achieve very low current distortions during steady-state operation is to employ offline calculated optimized pulse patterns (OPP). Achieving high dynamic performance, however, proves to be very difficult in a system operated by OPPs. In this paper, we propose a method that combines the optimal steady-state performance of OPPs with the very fast dynamics of trajectory tracking control. A constrained optimal control problem with a receding horizon policy, i.e. model predictive control (MPC), is formulated and solved. Results show that the combination of MPC with OPPs satisfies both the strict steady-state as well as the dynamic performance requirements imposed by the most demanding industrial applications. This is achieved without resorting to complicated structures such as observers of the state variable fundamental components of the electrical machine, which are required by state-of-the-art methods. A further advantage of the MPC method is the use of a receding horizon policy to provide feedback and a high degree of robustness.

Direct Model Predictive Control: A Review of Strategies That Achieve Long Prediction Intervals for Power Electronics

Direct model predictive control (MPC) strategies that achieve long prediction horizons with a modest computational complexity are reviewed in this article, focusing on power electronics applications. In many MPC problems, a long prediction horizon is required to ensure an adequate closed-loop performance in steady state and to avoid stability issues. However, the computational effort of solving the optimization problem underlying MPC problems with long prediction horizons is often very great, making the implementation of such schemes in real time a difficult and challenging task. To overcome this difficulty, three established methodologies are surveyed that yield long prediction horizons with a modest computational burden. Case studies are investigated to substantiate the merits of these schemes. More specifically, for dc?dc boost converters, a move blocking strategy is reviewed, and for ac medium-voltage (MV) drives, both an extrapolation and an event-based horizon strategy are examined.

Power electronic traction transformer technology

Combining modern high-power semiconductor devices with constantly improving magnetic materials opens up the possibility to replace bulky low frequency transformers with a new medium voltage medium frequency conversion structures. While there are still challenges to be addressed related to these so called power electronic transformers, a steadily increasing development effort is evident and considered in various contexts. Traction applications seem to be the first ones where proliferation of these new galvanic isolated power electronic converters is expected. In this particular application field, substantial weight and volume reduction could be achieved while providing additional functionality at the same time. In this paper a survey of recent R&D efforts in this field is presented.

Model predictive pulse pattern control

Industrial applications of medium-voltage drives impose increasingly stringent performance requirements, particularly with regards to harmonic distortions of the phase currents of the controlled electrical machine. An established method to achieve very low current distortions during steady-state operation is to employ offline calculated optimized pulse patterns (OPP). Achieving high dynamic performance, however, proves to be very difficult in a system operated by OPPs. In this paper, we propose a method that combines the optimal steady-state performance of OPPs with the very fast dynamics of trajectory tracking control. A constrained optimal control problem with a receding horizon policy, i.e. model predictive control (MPC), is formulated and solved. Results show that the combination of MPC with OPPs satisfies both the strict steady-state as well as the dynamic performance requirements imposed by the most demanding industrial applications. This is achieved without resorting to complicated structures such as observers of the state variable fundamental components of the electrical machine, which are required by state-of-the-art methods. A further advantage of the MPC method is the use of a receding horizon policy to provide feedback and a high degree of robustness.

Model predictive control of the internal voltages of a five-level active neutral point clamped converter

In this paper, model predictive control (MPC) is introduced to control the internal voltages of an active neutral-point clamped five-level converter (ANPC-5L). The proposed control scheme aims to keep the neutral point and phase capacitors voltages of the converter within given hysteresis bounds while at the same time minimizing the switching frequency. An additional benefit of the controlled voltages is a reduced level of output current distortion. The large number of redundant states that exist in multi-level converters makes it possible for all the objectives to be achieved. A short horizon is employed in order to ensure a manageable level of complexity. At the same time extrapolation is used to bring the performance to the desired level. Simulation results that substantiate the effectiveness of the proposed approach are presented.

Model predictive pulse pattern control for the five-level active neutral point clamped inverter

In this paper, the recently introduced control strategy referred to as model predictive pulse pattern control (MP3C) is adapted to the ACS 2000 five-level power converter of ABB. The drive consists of an induction machine and a five-level active neutral-point clamped (ANPC-5L) inverter. The power inverter is fed with optimized pulse patterns (OPPs) that produce minimum harmonic distortion in the stator winding of the ac machine. An optimal stator flux trajectory is calculated from these OPPs and a trajectory controller tracks it in real-time. In the proposed approach, trajectory tracking is based on model predictive control (MPC): a constrained optimal control problem is formulated and solved in real-time in a time-efficient manner. An event-based prediction horizon is employed in order to ensure fast tracking of the stator flux trajectory. The advantages of the proposed method are optimal steady-state behavior in terms of harmonic distortion and fast torque response. The method was tested on a pilot ACS 2000 power converter coupled to a general-purpose 1.21-MW induction machine. Experimental results were obtained from this industrial setup; they are presented in this paper to demonstrate the high performance of MP3C.

Power Electronic Transformer Technology for Traction Applications - An Overview

Combining modern high-power semiconductor devices with constantly improving magnetic materials opens up the possibility to replace bulky low-frequency transformers with a new medium voltage medium frequency conversion structure. While there are still challenges to be addressed related to these so called power electronic transformers, a steadily increasing development effort is evident and considered in various contexts. Traction applications seem to be the first ones where proliferation of these galvanically isolated power electronic converters is expected. In this application field, substantial weight and volume reduction can be achieved while providing additional functionality at the same time. In this paper a survey of recent R&D efforts in this field is presented.

Modular PET, two-phase air-cooled converter cell design and performance evaluation with 1.7kV IGBTs for MV applications

This paper explores the optimization and design of a medium voltage, modular power electronics transformer based on industrial 1.7 kV IGBTs. The design of the medium frequency transformer is outlined. The thermal management using a two-phase, air-cooled thermosyphon is described. The overall performance of one cell is detailed from measurements on a full-scale laboratory demonstrator. From the data, the impact of converter variables on power throughput and efficiency is illustrated. In addition, the waveforms are analyzed in terms of converter parasitics and circuit configuration.

Weight minimization of LCL filters for high power converters

Weight reduction of the LCL filter is one of the main concerns for high power, grid connected, voltage source converters (VSC) where an LCL filter can weigh hundreds of kilograms. It is a multi-domain optimization issue to find the minimum weight of an LCL filter considering PWM, control, filter design, and magnetic components with given constraints such as harmonic standards, semiconductor power loss, and cooling condition. The comprehensive design procedure and limits of an LCL filter for a 1.2-MVA VSC is provided in this paper.

Model predictive control in power electronics: Strategies to reduce the computational complexity

Model predictive control (MPC) is a control strategy that has been gaining more and more attention in the field of power electronics. However, in many cases the computational requirements of the derived MPC-based algorithms are difficult to meet, even with modern microprocessors that are immensely powerful and capable of executing complex instructions at a faster rate than ever before. To overcome this difficulty, three strategies that can significantly reduce the complexity of computationally demanding MPC schemes are presented in this paper. Three case studies are examined in order to verify the effectiveness of the proposed strategies. These include a move blocking strategy for a dc-dc boost converter and both an extrapolation strategy and an event-based horizon strategy for a dc-ac medium-voltage (MV) drive.