Scott Ragon

Design of a boost power factor correction converter using optimization techniques

This paper presents an approach to continuous variable design optimization of a power electronics converter. The objective of the optimization approach is to minimize the total component cost. The methodology is illustrated with the design of a boost power factor correction front-end converter with an input electromagnetic interference filter. The system design variables are first identified. The relevant system responses and component costs are then expressed as a function of these design variables. Finally, by using mathematical optimization techniques, the design variable values that minimize the total system component cost are obtained, given practical constraints on these design variables and system responses.

A comparison of three algorithms for tracing nonlinear equilibrium paths of structural systems

The relative efficiencies of the Riks/Wempner, Crisfield, and normal flow solution algorithms for tracking nonlinear equilibrium paths of structural systems are compared. It is argued that the normal flow algorithm may be both more computationally efficient and more robust compared to the other two algorithms when tracing the path through severe nonlinearities such as those associated with structural collapse. This is demonstrated qualitatively by comparing the relative behaviors of each algorithm in the vicinity of a severe nonlinearity. Quantitative results are presented for the collapse a blade stiffened panel.

Design optimization of a boost power factor correction converter using genetic algorithms

This paper presents a software tool for designing a low-cost boost power factor correction front-end converter with an input electromagnetic interference filter. A genetic algorithm based discrete optimizer is used to obtain the design. A detailed and experimentally validated model of the system, including second order effects, is considered. A graphical user interface for managing the design specifications and system component databases, controlling and monitoring the optimization process, and analyzing the performance of the top designs found by the optimizer is also described. The results of a design study for a 1.15 kW unit are presented to demonstrate the usefulness of the software tool.

Voltage source inverter

This article presents an EA-based design optimization tool for a three-phase voltage source inverter with diode front-end rectifier used for industrial motor drive power stage considering all major subsystems front-end rectifier, inverter and thermal management system, and EMI filter. Analytical relationships are developed and implemented into three optimizers. Global optimization is achieved by considering the relations between the subsystems. Design examples verified the usefulness and correctness of the design methodology and tool.

Analysis and Design Optimization of Diode Front-End Rectifier Passive Components for Voltage Source Inverters

This paper presents a systematic design optimization approach for inductors and capacitors in diode front-end rectifiers for voltage source inverters. Analytical relationships between various design variables, operating conditions, and performance and physical constraints are established under nominal, overload, and inrush conditions. A new method to analytically calculate the inrush current is developed considering the nonlinear characteristics of the inductor core materials. A design optimization program based on the established analytical relationships and a genetic algorithm is developed. Examples show that the optimization process can lead to a smaller/lower cost inductor and capacitor design. Experiments are conducted to verify key analytical relationships and the optimized design.

Analysis and design optimization of front-end passive components for voltage source inverters

This paper presents a systematic design optimization approach for inductors and capacitors in front-end rectifiers for voltage source inverters. Analytical relationships between various design variables, operating conditions, and performance and physical constraints are established under nominal, overload and inrush conditions. A new method to analytically calculate the inrush current is developed considering the nonlinear characteristics of the inductor core materials. A design optimization program based on the established analytical relationships and a genetic algorithm is developed. Examples show that the optimization process can lead to a smaller/lower-cost inductor and capacitor design.

Design Optimization of Industrial Motor Drive Power Stage Using Genetic Algorithms

A design optimization tool of motor drive power stage has been developed. Through analyzing and modeling three major blocks, including front-end harmonic filters, IGBT inverters, and EMI filters, in a industrial motor drive, optimization programs have been implemented by using genetic algorithm (GA) engine. The optimizer can be used as design and verification tools useful for practicing engineers. The design results obtained from the optimizer have been implemented and tested, and the experimental results have verified the models and programs

Design of a recurve actuator for maximum energy efficiency

In this paper we study the optimal design of recurve arrays. An analytic model of the static response of the recurve actuator with energy flow in the system is derived. Two optimization problems for the recurve array are formulated with material, packaging, and performance constraints. One formulation is based on minimum weight. The second formulation is based on energy efficiency. A genetic algorithm is used to find the optimum designs. Recurve arrays designed for maximum energy conversion efficiency are compared to those designed for minimum weight. Parametric studies are conducted to investigate the effect of the stiffness of the driven structure and the maximum deliverable voltage on the optimized designs. These optimization formulations are effective design tools for a relatively complex actuator.

Combined Design of Recurve Actuators and Drive Electronics for Maximum Energy Efficiency

Smart structures typically consist of many interacting components, which result in a closed loop formed by an actuator, structure, sensors, controller, and drive circuit components. Despite the recognition of component interactions, much of the traditional design approach for such systems is highly compartmentalized and sequential. The primary objective of the present work is to develop a basic understanding of the energy flow and dynamic interaction between the electrical and mechanical subsystems of smart actuators. When operating from portable power sources, a crucial factor in determining the performance of such a smart system is the battery capacity required for the actuator to operate through a given time span along with its life time. The real and reactive power in such a system will determine the battery life and size separately. While the real power is dissipated only in the drive circuit, the reactive power of the circuit and the actuator cannot be calculated individually, where the interaction arises. Multi-objective function optimization problem, which combines the real and reactive power by different weights, will result in a better balanced solution than optimizing either one of them separately. Genetic algorithm is applied for discrete component selection to generate more realistic designs. The optimization result is illustrated in the paper, as well as their relationship with multi-objective functions.