@inproceedings{294a9f9f19714bf08d8368aa8188e91b,
title = "Performance Limits of Differential Power Processing",
abstract = "This paper explores performance limits of differential power processing (DPP) for large-scale modular dc energy systems with stochastic loads. An analytical stochastic model is developed to estimate the average power loss of a DPP topology under probabilistic load distributions. A scaling factor $\mathcal{S}$ (•) is introduced to describe how power loss scales as the system size or load power variance increases. The average power losses of several example DPP topologies are analyzed and compared against conventional dc-dc converters given the same total switch die area and magnetic volume. The performance limits for various DPP topologies are derived and verified by Monte-Carlo simulations in SPICE, and the results indicate that the ac-coupled DPP converter stands out from all the representative DPP topologies discussed here in terms of the lowest power loss. The paperprovides an analytical framework to evaluate the performance of different DPP topologies in a methodical way, offering insights for the design of DPP systems with large-scale stochastic loads.",
keywords = "Differential power processing (DPP), dc-dc converters, performance limits, stochastic models",
author = "Ping Wang and Pilawa-Podgurski, {Robert C.N.} and Krein, {Philip T.} and Minjie Chen",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 21st IEEE Workshop on Control and Modeling for Power Electronics, COMPEL 2020 ; Conference date: 09-11-2020 Through 12-11-2020",
year = "2020",
month = nov,
day = "9",
doi = "10.1109/COMPEL49091.2020.9265642",
language = "English (US)",
series = "2020 IEEE 21st Workshop on Control and Modeling for Power Electronics, COMPEL 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE 21st Workshop on Control and Modeling for Power Electronics, COMPEL 2020",
address = "United States",
}