Open AccessNon‐linear dynamic behaviours of DC cascaded converters system with multi‐load converters
Author(s) -
Xie Fan,
Zhang Bo,
Qiu Dongyuan,
Jiang Yanwei
Publication year - 2016
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2015.0193
Subject(s) - converters , control theory (sociology) , power (physics) , attractor , voltage , buck converter , eigenvalues and eigenvectors , topology (electrical circuits) , computer science , mathematics , engineering , physics , electrical engineering , mathematical analysis , control (management) , quantum mechanics , artificial intelligence
Non‐linear dynamic behaviours in a single DC–DC converter system have been widely investigated in the past three decades. However, with the increasing popularity of microgrids, renewable energy systems and DC distribution power systems, non‐linear phenomena analysis of DC cascaded converters system with multi‐load converters, which is the most dominant connection among them, is necessitated. Thus, in this study, the complex bifurcation phenomena of one source boost converter (SBC) paralleled with one boost converter and two buck converters are analysed. To stabilise the output voltage in a determinate region, both inner current loop and outer voltage loop controls are used in all sub‐converters. Using simulation and experiment analysis, the SBC has coexisting attractors and enters the coexistence of fast‐scale and slow‐scale instabilities or multi‐period orbits in some parameters condition, but all the load converters work in stable state. To explain these phenomena, the discrete mapping of this DC cascaded converters system is established and the derivation of its eigenvalue is conducted. For simplicity, all of the load converters are considered as constant power loads. By analysing the eigenvalues of period‐1 and period‐2 orbits, the coexisting attractors and the coexisting fast‐scale and slow‐scale instabilities are explained.