Armando Araújo

Design and implementation of a current controller for the parallel operation of standard UPSs

The parallel operation of static inverters is, in a large amount of cases, the appropriate solution to achieve the high power required by some applications or to improve power system reliability. The limited inverter capacity obliges to parallel the individual units to obtain the nominal load power. In UPS systems, there are situations where a high reliability/availability is required by critical loads. Parallel redundancy appears an immediate solution to satisfy this requirement. This paper presents a control system for parallel operation of nonredundant UPSs based on current control. The relative phase between the inverters is constant. Simulation results as well as experimental studies are presented. The overall control system is implemented on a simple and low cost platform.

A new physics based SPICE model for NPT IGBTs

A physics based, non-punch-through, insulated gate bipolar transistor (NPT-IGBT) model is presented, as well as its porting into available circuit simulator SPICE. Developed model results in a system of ODEs, from which time/space hole/electron distribution is obtained, and is based on solution of ambipolar diffusion equation (ADE) through a variational formulation, with one-dimensional simplex finite elements. Model implementation, in a circuit simulator, is made by means of an electrical analogy with the resulting system of ODEs. Other parts of the devices are modeled using standard methods. Thus, this new hybrid model combines advantages of numerical and mathematical methods, through modeling charge carrier behavior with high accuracy even maintaining low execution times.

Finite-Element Modeling and Optimization-Based Parameter Extraction Algorithm for NPT-IGBT s

A finite-element, physics-based, non-punch-through (NPT) insulated gate bipolar transistor (IGBT) model is presented in this paper. The models core is based on solving the ambipolar diffusion equation through a variational formulation, resulting in a system of ordinary differential equations (ODEs). The approach enables an easy implementation into a standard SPICE circuit simulator. The resulting system of ODEs is solved as a set of (current controlled) RC nets describing charge carrier distribution in a low-doped zone. Other zones of the device are modeled with classical methods. This hybrid approach describes the devices dynamic and static behavior with good accuracy while maintaining low execution times. As physics-based models need a significant number of parameters, an automatic parameter extraction method has been developed. The procedure, based on an optimization algorithm (simulated annealing), enables an efficient extraction of parameters requiring some simple device waveform measurements. Experimental validation is performed. Results prove the usefulness of the proposed methodology for the efficient design of power circuits through simulation.

Modeling Buffer Layer IGBTs with an Efficient Parameter Extraction Method

A finite element physics-based punch-through IGBT model is presented, as well as its porting into standard circuit simulator SPICE. Developed model is based on solving the ambipolar diffusion equation (ADE) trough a variational formulation, resulting in a system of ODEs, from which charge carrier distribution is obtained. Implementing the model in a circuit simulator is made by means of an electrical analogy with the resulting system of ODEs. Other parts of the devices are modeled using conventional methods. The paper also discusses a parameter extraction procedure using an optimisation algorithm in order to get an efficient extraction of large number of parameters needed for physics-based IGBT models. Model is validated comparing experimental and simulated results

Current control in the grid connection of the double-output induction generator linked to a variable speed wind turbine

The output power of present wind turbines is continuously increasing. At high power levels, to limit mechanical stresses and power surges in the grid it is necessary to use speed control systems. The double-output induction generator (DOIG) system is an excellent solution to adjust the speed over a wide range. At present the two converters associated with the DOIG use high power IGBTs with medium switching frequencies in order to optimise the current waveform in the generator and in the grid. The two converters need a high performance control system operating with high sampling frequencies and complex control algorithms. The voltage source IGBT converter connected to the grid controls the active and reactive power supplied and imposes a low level of harmonic distortion. This paper presents the results obtained with such a system.

A modular approach for modeling and simulation of semiconductor power devices

This paper presents a modular approach for the modeling and simulation of power semiconductor devices. The novelty of the method is the accurate description of the carrier distribution in the low doped zone using a modular circuit network. This is achieved through the variational reformulation of the ambipolar diffusion equation (ADE) with posterior approximate solution with a finite element approach. The obtained modular networks are dependent on the physical properties of the device being modeled (element widths, mobilities, lifetimes, dopings). In this manner, the spatial variation of these parameters is easily implemented. Approaches to this modular construction can also be made with several types of finite elements. Modules for the others zones of the devices (emitters, narrow bases, MOS), as well as for the voltage drops, based on known approaches, are also presented. Semiconductor modeling is then made linking these various modules through the boundary conditions of the device. This enables easy construction of efficient circuits for semiconductor simulation. Results of the method for power p-i-n diodes and power bipolar junction transistors are presented.

Parameter Identification of Power Semiconductor Device Models Using Metaheuristics

Parameter extraction procedures for power semiconductor models are a need for researchers working with development of power circuits. It is nowadays recognized that an identification procedure is crucial in order to design power circuits easily through simulation (Allard et al., 2003; Claudio et al., 2002; Kang et al., 2003c; Lauritzen et al., 2001). Complex or inaccurate parameterization often discourages design engineers from attempting to use physics-based semiconductor models in their circuit designs. This issue is particularly relevant for IGBTs because they are characterized by a large number of parameters. Since IGBT models developed in recent years lack an identification procedure, different recent papers in literature address this issue (Allard et al., 2003; Claudio et al., 2002; Hefner & Bouche, 2000; Kang et al., 2003c; Lauritzen et al., 2001). Different approaches have been taken, most of them cumbersome to be solved since they are very complex and require so precise measurements that are not useful for usual needs of simulation. Manual parameter identification is still a hard task and some effort is necessary to match experimental and simulated results. A promising approach is to combine standard extraction methods to get an initial satisfying guess and then use numerical parameter optimization to extract the optimum parameter set (Allard et al., 2003; Bryant et al., 2006; Chibante et al., 2009b). Optimization is carried out by comparing simulated and experimental results from which an error value results. A new parameter set is then generated and iterative process continues until the parameter set converges to the global minimum error. The approach presented in this chapter is based in (Chibante et al., 2009b) and uses an optimization algorithm to perform the parameter extraction: the Simulated Annealing (SA) algorithm. The NPT-IGBT is used as case study (Chibante et al., 2008; Chibante et al., 2009b). In order to make clear what parameters need to be identified the NPT-IGBT model and the related ADE solution will be briefly present in following sections. 1

A model for battery lifetime calculation implementable in circuit simulators

For pure electrical propelled vehicles, PEVs, a proper battery model is critical in order to estimate State of Charge, SOC, therefore enabling predicting performance and ensuring safe battery operation. Present methods can be classified as electrochemical, electrical equivalent circuits, stochastic and analytical, these last ones based on solution of Partial Differential Equations. These methods are somehow computationally intensive, prejudicing their application in Battery Management Systems. Some ones do not accurately predict battery SOC and most of them are not applicable in electrical circuit simulators. This paper presents a model, based on Ficks laws, capable of an accurate prevision of battery lifetime, i.e. time until battery is empty, and implementable in any circuit simulator. Proposed model behaviour is analysed using PSIM and MATLAB and validated with experimental results.

A new FPGA based PMSM torque controller for hybrid and electric vehicles powertrain

This paper presents a new approach to vector PMSM control implemented on a FPGA platform with a soft processor core integration for floating point computation. An advanced vector control is developed, according to PMSM vector control state-of-the-art, where the torque reference is a direct input to the system, dynamically controlling the injection of stator current flux component, in order to direct control of the torque angle. This approach provides a more robust solution for electric and hybrid electric vehicles as the controlled variable is the torque and the controller actuates simultaneously on the flux and torque current components and their angle. State-of-the-art presents two different control methods based on stator current flux component injection and the authors discuss another two methods, considering different relations between air-gap flux, rotor flux and stator current vectors. These methods are described and one is shown as appropriate to electric vehicle powertrain applications, regarding performance, efficiency and motor parameters. Concerning motor position information feedback, a PLL-based sensorless control technique is presented and compared with a solution based on position measurement. A hardware and software prototype based on a Xilinx® Spartan-6 FPGA and an electric vehicle powertrain set up are developed and tested for performance validation and experimental results are presented. The results show a robust controller with a high dynamics response.

A physics-based power diode model optimized through experiment based parameter extraction

This paper presents a physics-based power diode model with parameters established through an extraction procedure validated experimentally. The core of the model is based on a finite element approach that solves for electron/hole concentration in low doped zone of the device. As physical based models need a significant number of parameters an automatic parameter extraction method has been developed. The procedure, based on an optimization algorithm (simulated annealing), enables an efficient extraction of parameters, needed for physics-based semiconductor models, requiring some simple device waveform measurements. Implementation of developed power diode model, in SPICE like simulators, and extraction procedure is presented. Experimental validation is performed.