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Reduced Order Identification and Stability Analysis of DC-DC Converters

  • Ali, Husan (School of Automation, Northwestern Polytechnical University) ;
  • Zheng, Xiancheng (School of Automation, Northwestern Polytechnical University) ;
  • Wu, Xiaohua (School of Automation, Northwestern Polytechnical University) ;
  • Zaman, Haider (School of Automation, Northwestern Polytechnical University) ;
  • Khan, Shahbaz (School of Automation, Northwestern Polytechnical University)
  • Received : 2016.06.06
  • Accepted : 2017.01.23
  • Published : 2017.03.20

Abstract

This paper discusses the measurement of frequency response functions for various dc-dc converters. The frequency domain identification procedure is applied to the measured frequency responses. The identified transfer functions are primarily used in developing behavioral models for dc-dc converters. Distributed power systems are based upon such converters in cascade, parallel and several other configurations. The system level analysis of a complete system becomes complex when the identified transfer functions are of high order. Therefore, a certain technique needs to be applied for order reduction of the identified transfer functions. During the process of order reduction, it has to be ensured that the system retains the dynamics of the full order system. The technique used here is based on the Hankel singular values of a system. A systematic procedure is given to retain the maximum energy states for the reduced order model. A dynamic analysis is performed for behavioral models based on full and reduced order frequency responses. The close agreement of results validates the effectiveness of the model order reduction. Stability is the key design objective for any system designer. Therefore, the measured frequency responses at the interface of the source and load are also used to predict stability of the system.

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Cited by

  1. Behavioral Modeling for Parallel- and Cascade-Connected dc–dc Converters pp.1793-6454, 2018, https://doi.org/10.1142/S0218126619500580