The study uses the green phosphor of Ca2SiO4:Eu2+ to achieve the color constancy for the dual-film remote phosphor white-LED model at low as well as big CCTs. The utilized green phosphor Ca2SiO4:Eu2+ was prepared using the water-soluble-silicon liquid phase precursor method with the doped Eu2+ ion concentration of 3 mol%. The Ca2SiO4:Eu2+ phosphor emits strong green light with emission intensity focused at 502 nm wavelength, and a wide stimulation band of colors of 225 nm – 450 nm. After applying the Ca2SiO4:Eu2+ green phosphor and modifying its concentration, the modified color and luminous performances can be observed. The better color uniformity and higher luminescence efficiency can be obtained by increasing the percentage of Ca2SiO4:Eu2+ in the phosphor configuration. Meanwhile, the color rendering metrics tend to reduce slightly when the concentration of Ca2SiO4:Eu2+ is over 10% wt.

This paper deals with a novel method to achieve the effective performance of the extended Kalman filter (EKF) for the speedy estimate of an induction motor. The real coding genetic algorithm (GA) is used to optimize the components of the covariance matrix in the EKF, thus ensuring the stability and accuracy of the filter in the speed estimation. The advantage of the proposed method is less dependent on the parameters of the induction motor. The content includes the vector control model for induction motor, the speed estimation by modeling the reference frame-model reference adaptive system (RF-MRAS), the current based-model reference adaptive system (CB-MRAS), and the speed estimation with the EKF optimized by genetic algorithm. Simulative studies on the field-oriented controller (FOC) with different operating conditions are performed in Matlab Simulink when the rotor resistance changes in the current speed estimation methods. The simulation results demonstrate the efficiency of the proposed GA-EKF filter compared with other speed estimation methods of induction motors.