HE DESIGN OF POWER ELECTRONICS
systems involves a large number of design
variables and the application of knowledge
from several different engineering fields
(electrical, magnetic, thermal, and mechanical). In order to
simplify the design problem, traditional design procedures
fix a subset of the design variables and introduce assumptions
(simplifications) based on the designer’s understanding
of the problem. These simplifications allow an initial
design to be obtained in a reasonable amount of time, but
further iterations through hardware prototype testing are
usually required. The ability and expertise of the designer
usually lead to good but not optimum designs.
Mathematical optimization techniques offer an organized
and methodical way of approaching the design problem. This
allows the designer to use more design variables and fewer
simplifications. This, in turn, reduces the number of iterations
during the hardware-testing phase. The increasing speed of
computer hardware and the development of faster computational
models allow optimum designs to be obtained in a relatively
short time. Furthermore, the application of the
optimization echniques can provide a better understanding of
the tradeoffs involved in the design and even highlight those
that were initially ignored.
History
HE DESIGN OF POWER ELECTRONICS
systems involves a large number of design
variables and the application of knowledge
from several different engineering fields
(electrical, magnetic, thermal, and mechanical). In order to
simplify the design problem, traditional design procedures
fix a subset of the design variables and introduce assumptions
(simplifications) based on the designer’s understanding
of the problem. These simplifications allow an initial
design to be obtained in a reasonable amount of time, but
further iterations through hardware prototype testing are
usually required. The ability and expertise of the designer
usually lead to good but not optimum designs.
Mathematical optimization techniques offer an organized
and methodical way of approaching the design problem. This
allows the designer to use more design variables and fewer
simplifications. This, in turn, reduces the number of iterations
during the hardware-testing phase. The increasing speed of
computer hardware and the development of faster computational
models allow optimum designs to be obtained in a relatively
short time. Furthermore, the application of the
optimization echniques can provide a better understanding of
the tradeoffs involved in the design and even highlight those
that were initially ignored.
History
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