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Nonlinear High-Speed Model Predictive Control with Long Prediction Horizons for Power-Converter Systems

Name: Nonlinear High-Speed Model Predictive Control with Long Prediction Horizons for Power-Converter Systems
Brand: Shaker
SKU: 9783844078503
Price: 16382 HUF
Availability: InStock

Dissertationsschrift

Szerző: Thomas Hausberger

Nyelv:

Kötés: Puha kötésű

Kiadó: Shaker

Elérhetőség: 50 % esély

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16 382 Ft

The utilization of AC/DC- and DC/DC-power converters and their coupling is emerging in the field of...

Információk a könyvről

Szerző

Thomas Hausberger

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2021

oldal

189

EAN

9783844078503

Enbook ID

38548660

Kiadó

Shaker

Súly

284

Méretek

170 x 240

Teljes leírás

The utilization of AC/DC- and DC/DC-power converters and their coupling is emerging in the field of electrified powertrains in the automotive industry or in the renewable energy sector via photovoltaic (PV) cells or wind turbines and in battery systems for energy storage. For all these tasks, highly dynamic, efficient and accurately controlled power converters are needed.This work presents nonlinear high speed model predictive control (MPC) strategies for (interleaved switching) AC/DC- and DC/DC-power converter and coupled power converter systems. Compared to known MPC strategies the proposed approaches allow for longer prediction horizons while keeping the calculation times in the range of a few mis. This is achieved by tailoring the MPC strategies to an efficient implementation on an FPGA, exploiting the inherent parallel computation capabilities of FPGAs. Moreover, the utilization of a numerically efficient envelope model in the MPC is an important building block to reach the desired fast calculation times. The MPC strategies systematically take into account input and state constraints, provide a high dynamic and accurate control performance, exhibit constant switching frequencies and enable an interleaved switching operation. The proposed MPC strategies are tested in detailed simulations and in hardware-in-the-loop (HIL) experiments. An accurate and fast closed-loop dynamics can be achieved, also with respect to unknown fast load variations and parameter uncertainties. It is finally shown that the proposed MPC strategies have the potential to outperform the control performance of existing state-of-the-art control strategies for power converter systems.