A modified MODPEX model for MOSFET and parameter optimization using excel-based genetic algorithm
MODPEX is widely used in industry and universities to produce Pspice model for power semiconductor devices, including MOSFETs. However, the model generated by MODPEX for MOSFETs does not include channel charge at strong inversion condition. This paper presents a modified MODPEX model for MOSFETs, which includes channel charge at strong inversion condition. A process based on genetic algorithm (GA) implemented in Microsoft Office Excel is developed to optimize parameters of the modified MODPEX model. Static and dynamic validation proves that the modified MODPEX model improves simulation accuracy in both switching loss and driver loss.
Application of the Genetic Algorithm in MOSFET Modeling and Parameter Extraction
In this paper, the genetic algorithm is introduced into parameter optimization for MOSFET small-signal model parameter extraction for up to 60 GHz millimeter-wave operations. Initial parameters of the model are extracted by curve fitting and direct parameter extraction method in saturation region approximately, and then fourteen independent parameters of the equivalent circuit model are optimized together. The real and imaginary part of S-parameter are set as the fitting targets simultaneously in this study. With the more convenient genetic algorithm, the model with the optimized parameters gives a better fitting accuracy than the initial parameters without optimization.
Properties of a monopivot centrifugal blood pump manufactured by 3D printing
An impeller the same geometry as the impeller of a commercial monopivot cardiopulmonary bypass pump was manufactured using 3D printing. The 3D-printed impeller was integrated into the pump casing of the commercially available pump to form a 3D-printed pump model. The surface roughness of the impeller, the hydraulic performance, the axial displacement of the rotating impeller, and the hemolytic properties of the 3D-printed model were measured and compared with those of the commercially available model. Although the surface roughness of the 3D-printed model was significantly larger than that of the commercially available model, the hydraulic performance of the two models almost coincided. The hemolysis level of the 3D-printed model roughly coincided with that of the commercially available model under low-pressure head conditions, but increased greatly under high-pressure head conditions, as a result of the narrow gap between the rotating impeller and the pump casing. The gap became narrow under high-pressure head conditions, because the axial thrust applied to the impeller increased with increasing impeller rotational speed. Moreover, the axial displacement of the rotating impeller was twice that of the commercially available model, confirming that the elastic deformation of the 3D-printed impeller was larger than that of the commercially available impeller. These results suggest that trial models manufactured by 3D printing can reproduce the hydraulic performance of the commercial product. However, both the surface roughness and the deformation of the trial models must be considered to precisely evaluate the hemolytic properties of the model.