Jacobo de Uña Álvarez

Multilevel Multiphase Space Vector PWM Algorithm

In the last few years, interest in multiphase converter technology has increased due to the benefits of using more than three phases in drive applications. Besides, multilevel converter technology permits the achievement of high power ratings with voltage limited devices. Multilevel multiphase technology combines the benefits of both technologies, but new modulation techniques must be developed in order to take advantage of multilevel multiphase converters. In this paper, a novel space vector pulsewidth modulation (SVPWM) algorithm for multilevel multiphase voltage source converters is presented. This algorithm is the result of the two main contributions of this paper: the demonstration that a multilevel multiphase modulator can be realized from a two-level multiphase modulator, and the development of a new two-level multiphase SVPWM algorithm. The multiphase SVPWM algorithm presented in this paper can be applied to most multilevel topologies; it has low computational complexity and it is suitable for hardware implementations. Finally, the algorithm was implemented in a low-cost field-programmable gate array and it was tested in a laboratory with a real prototype using a five-level five-phase inverter.

FPGA implementation of a fuzzy controller for automobile DC-DC converters

The design of synchronous multiphase DC-DC converters for automobile applications is now a very active field, because the automotive industry forecast that future power demands inside a car will oscillate between 2.5 kW and 3.5kW, keeping a dual system of 42/14V batteries. The design of controllers for the optimal behavior of such converters is a very delicate task. In this paper, an optimized fuzzy control algorithm has been developed to control a synchronous multiphase converter of 1.6kW. First, the fuzzy control algorithm is designed and verified, together with a non linear model of the converter power stage, by means of Matlab and Simulink. Then, the fuzzy controller hardware is developed through Xilinx System Generator for Simulink, and implemented in a Spartan 3 FPGA to achieve a real-time controller

Kernel density estimation with doubly truncated data

In some applications with astronomical and survival data, doubly truncated data are sometimes encountered. In this work we introduce kernel-type density estimation for a random variable which is sampled under random double truncation. Two different estimators are considered. As usual, the estimators are defined as a convolution between a kernel function and an estimator of the cumulative distribution function, which may be the NPMLE [2] or a semiparametric estimator [9]. Asymptotic properties of the introduced estimators are explored. Their finite sample behaviour is investigated through simulations. Real data illustration is included. AMS 2000 subject classifications: Primary 62G07; secondary 62N02.