A design method of line commutated converter (LCC) compensation network for the dynamic wireless power transfer (DWPT) system based on a complex impedance model (Z-model) of the input impedance of the rectifier is proposed in this study. The continuous conduction mode and discontinuous conduction mode (DCM) of the rectifier are analysed to calculate the equivalent input impedance of the rectifier. Based on the proposed model of the input impedance of the rectifier, a design method of LCC compensation network for the DWPT system is presented. Simulation results prove that the Z-model of the rectifier is more accurate than the prevailing resistive model. Experiments show that the DWPT system with the designed LCC network meets the requirement of the average output power with an average DC-DC efficiency over 93%.

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Recent researches on estimation of parameters of gene regulatory networks by differential equations generally based on Kalman Filtering Model, it makes assumptions that the analyzed system is linear. However, gene regulatory networks are obviously non-linear system, so great deviation error will happen. Here we present a method to estimate the parameters and hidden variables of gene regulatory networks based on Unscented Particle Filter. It makes better fitness than Kalman Filtering Model due to free of the premise that the model is linear. By comparison of the estimation result between Unscented Particle Filter and Unscented Kalman Filter on the hidden variables and parameters of Repressilator, advantage of our method on reduction of estimation error is validated. The amount of particles is simultaneously analyzed. Both deficiency and overabundance of particles will weaken the accuracy of estimation, so selection on the moderate amount of particles is significant.