Open AccessModeling and Optimization Techniques of Electronic Devices Using Genetic Algorithm
Author(s) -
Sherif Michael
Publication year - 2008
Publication title -
cit. journal of computing and information technology/journal of computing and information technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.169
H-Index - 27
eISSN - 1846-3908
pISSN - 1330-1136
DOI - 10.2498/cit.1001399
Subject(s) - computer science , power (physics) , optimal design , genetic algorithm , photovoltaic system , junction temperature , current limiting , process (computing) , series (stratigraphy) , algorithm , current (fluid) , electrical engineering , physics , quantum mechanics , machine learning , engineering , operating system , paleontology , biology
A new method for developing a realistic physical model of any type of solid state device is presented. Application to model advanced multi-junction solar cells; Thermophotovoltaics; sensors; as well as other novel solid state devices are introduced in this presentation. The primary goal of multijunction solar cell design is to maximize the output power for a given solar spectrum [1-4]. The construction of multijunction cells places the individual junction layers in series, thereby limiting the overall output current to that of the junction layer producing the lowest current [5-7]. The solution to optimizing a multijunction design involves both the design of individual junction layers which produce an optimum output power and the design of a series-stacked configuration of these junction layers which yields the highest possible overall output current. This paper demonstrates the use of Genetic Algorithm in a two-part process to refine a given multijunction solar cell design for near-optimal output power for a desired light spectrum. This approach can similarly be utilized to optimize the parameters of any Solid state device to yield any desired performance