Black-Box Behavioral Modeling and Identification of DC-DC Converters With Input Current Control for Fuel Cell Power Conditioning

Fuel cells are a prime candidate for alternative power source of future on-board power distribution systems such as those for the more-electric-aircraft and electric vehicles. These systems are comprised of a large number of power converters, often provided by a variety of manufacturers. Modeling and simulation are powerful tools to evaluate the system-level behavior but, due to confidentiality of manufacturers, black-box behavioral models of the converters are required instead of the conventional ones. This paper proposes a black-box modeling and identification method of dc-dc converters with input current control for fuel-cell power conditioning. The model is simple, requires low computational cost for simulation, and the identification procedure is based on simple experiments. Moreover, the model does not represent the internal structure of the converter, so it can be provided by the manufacturer while protecting confidential data. The method is illustrated in detail and validated by making use of a commercial dc-dc converter specifically designed for fuel-cell power conditioning.

behavioral modeling; black-box modeling; distributed power system; fuel cell; hybrid electric vehicle; model identification; more electric aircraft; system-level analysis

Black-Box Behavioral Modeling and Identification of DC-DC Converters With Input Current Control for Fuel Cell Power Conditioning Articles