Behavioral Switching Loss Modeling of Inverter Modules
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gp-bibliography.bib Revision:1.8051
- @InProceedings{Stoyka:2018:SMACD,
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author = "Kateryna Stoyka and
Ricieri Akihito {Pessinatti Ohashi} and Nicola Femia",
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booktitle = "2018 15th International Conference on Synthesis,
Modeling, Analysis and Simulation Methods and
Applications to Circuit Design (SMACD)",
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title = "Behavioral Switching Loss Modeling of Inverter
Modules",
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year = "2018",
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abstract = "This paper presents a new behavioural model for
switching power loss evaluation in phase-shifted
full-bridge inverter Power Modules (PoMs). The proposed
model has been identified by means of a Genetic
Programming (GP) algorithm combined with a
Multi-Objective Optimization (MOO) technique. A large
set of loss data, evaluated by means of analytical loss
formulas, has been considered for the identification of
a compact behavioural model. the GP-MOO approach
considers the inverter switching frequency, input
voltage, duty-cycle and load resistance as model input
variables, and the MOSFET gate driver voltage and
resistance as parameters influencing the coefficients
values of the identified loss formula. The behavioral
model loss predictions confirm their reliability for a
wide range of operating conditions.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/SMACD.2018.8434850",
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month = jul,
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notes = "Also known as \cite{8434850}",
- }
Genetic Programming entries for
Kateryna Stoyka
Ricieri Akihito Pessinatti Ohashi
Nicola Femia
Citations