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Daily trip distance and end time of the last trip are two essential variables for home based electric vehicle (HBEV) charging load model. A non-parametric Gaussian kernel density estimation method is proposed to build the probability density distributions of these two variables. This method can improve the precision and adaptability of the distributions compared with parametric estimation. A Latin...
We propose a novel parametric macromodeling method for systems described by admittance and impedance representations, which depend on multiple design variables such as geometrical layout or substrate features. It is able to build accurate multivariate macromodels that are stable and passive over the entire design space. Poles and residues are parameterized indirectly. The proposed method is based...
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