This paper presents a new behavioral 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 behavioral 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.
Behavioral Switching Loss Modeling of Inverter Modules
Stoyka, Kateryna;PESSINATTI OHASHI, RICIERI AKIHITO;Femia, Nicola
2018-01-01
Abstract
This paper presents a new behavioral 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 behavioral 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.