Amir Masoud Bozorgi

Optimum switching pattern of matrix converter space vector modulation

This paper presents an optimum switching pattern for the space vector modulation (SVM) of matrix converters based on a genetic algorithm. The possibility of choosing the sequence of active duty cycles, and the ability to allocate the duration of the inactive duty cycle to each one of the zero duty cycles in a matrix converter SVM, provide some degrees of freedom in designing of the switching pattern. This leads to an optimization problem. Therefore, a suitable genetic algorithm for solving the switching pattern optimization problem is adopted, and an objective function to minimize the weighted total harmonic distortion (WTHD) and the low-order harmonics of the output voltage is proposed. Simulations in Matlab/Simulink confirm the validity of analytical achievements.

Improved model predictive current control of permanent magnet synchronous machines with fuzzy based duty cycle control

Model predictive current control uses a model of the machine and an appropriate cost function to indirectly control electromagnetic torque and reactive power. However, due to sensitivity of model predictive control (MPC) to system parameters, need for high sampling frequency, and high torque and flux ripples, this method is not employed in a wide variety of commercial drives. Incorporating the concept of duty cycle and applying two voltage vectors during a sampling period can reduce the torque and stator current ripples of a model predicative current controlled synchronous machine. In this paper, duty cycles of the voltage vectors are determined effectively using a fuzzy logic modulator. In addition, a full order Luenberger observer is designed for accurate estimation of motor variables in presence of parameter uncertainties. Matlab and real-time simulation results confirm the effectiveness of the proposed MPC.

Modeling, analysis and design of an undersea storage system

This paper presents the modeling, performance analysis, and design of an undersea storage system (USS). The USS can be employed for conditioning the output power of wave energy converters (WECs) and floating wind turbines (FWTs) at sea or ocean cites. A mathematical model is developed to describe the governing equations of the USS operation. Next, based on the developed model, a storage system is designed for a 3 MW direct drive WEC. Finally, some guidelines and discussions on determining the USS energy capacity, power capacity, optimum size, and installation depth are presented.

Voltage sensorless improved model predictive direct power control for three-phase grid-connected converters

Despite distinctive advantages such as fast dynamic, simple concept and ease of implementation, model predictive direct power control (MPDPC) suffers from some major drawbacks. First, in order to provide sinusoidal currents and low-ripple powers, very high sampling rates are required for MPDPC implementation. Furthermore, this method requires accurate knowledge of system parameters and its performance deteriorates in presence of parameter uncertainties. In this paper, an improved MPDPC is proposed, which features: 1) high current and power quality at low sampling frequencies, 2) less sensitivity to parameter uncertainties, particularly unknown grid inductance, and 3) voltage sensorless operation. The first and second features are achieved by incorporating the concept of switching duty cycles into the conventional MPDPC. In the proposed method, two voltage vectors are applied during a control period and their duty cycles are obtained by a fuzzy logic modulator. The proposed fuzzy logic modulator works based on the real and reactive power errors. Eventually, voltage sensorless operation is accomplished by designing a full-order observer. Thanks to voltage sensorless operation, the system volume and cost can be reduced. Through extensive hardware-in-the-loop tests, the superiority of the proposed MPDPC in comparison with two conventional MPDPCs is demonstrated.

Controller Design Using Ant Colony Algorithm for a Non-inverting Buck-Boost Chopper Based on a Detailed Average Model

Abstract In this article, the non-inverting buck–boost converter and its operation modes are scrutinized. The closed-loop stability of the converter in buck and boost modes is analyzed, and the necessity of using an appropriated controller is demonstrated. Then the application of an adapted ant colony optimization to design a feedback controller is proposed, and a controller based on its existing model is tuned. Simulation and experimental results obtained from the ant colony optimization designed controller are then compared with a controller designed with the classic method. Although the simulation and experimental results prove the efficiency of the proposed control approach, a significant difference between controller behavior in practice and simulation is obvious. Finding these differences, more detailed models, including all parasitic elements, in the buck and boost modes are derived. Applying the proposed model in controller design illustrates that the desired performance of the converter can be guaranteed with a simple proportional-integral (PI) controller. The suggested ant colony-based controller is again tuned based on the more detailed model, which improves the performance of the converter system even more. Furthermore, good agreement between analytical and experimental outputs validates the accuracy of the modeling and simulation.

Novel modulation schemes and switching pattern for Z-Source ultra-sparse matrix converter

The Z-Source networks are recently being employed in the matrix converters (MCs) to overcome their main drawback, which is the low voltage transfer ratio (VTR). In spite of several Z-Source topologies introduced for the direct and indirect matrix converters, some important issues such as their modulation, operational modes, existing challenges in practical implementation, the design of an optimal switching pattern, and so on, have not been fully addressed in the literature. This paper focuses on cascaded Z-Source ultra-sparse matrix converter (ZSUSMC), where the Z-Source network is inserted between the rectifier stage and inverter stage of an ultra-sparse matrix converter. Provided discussions can be extended to other indirect MC topologies, such as sparse and very-sparse MCs, though. Two space vector modulation (SVM) schemes, with and without considering the zero state in the space vector rectification, are proposed, and then, their advantages and disadvantages are discussed. In addition, an optimal switching pattern, which ensures minimum number of changes in the switches states over the entire switching period, is proposed. Hardware-in-the-loop studies are carried out and performance of the converter under the proposed modulation techniques is evaluated. The proposed modulations are compared with a recent study and its superior performance in terms of input and output currents quality is confirmed.

Implementing modulation schemes with three switching transients in a switching period on single DSP: Application to Z-source ultra-sparse matrix converter

Z-source networks have recently been employed with matrix converters (MCs) in order to address their limited voltage transfer ratio (VTR). In this paper, the space vector modulation of cascaded Z-source ultra-sparse matrix converter (ZSUSMC), where the Z-source network is inserted between the rectifier and inverter stages of an ultra-sparse matrix converter (USMC), is investigated. Digital implementation of the already existing space vector modulation (SVM) techniques for Z-source MCs is possible with a field programmable gate array (FPGA) employed along with a digital signal processor (DSP) due to occurrence of three switching transients in one control period. In this paper, an SVM scheme with an optimal switching pattern resulting in minimum number of changes in the switches states is developed. Furthermore, a novel approach for implementation of the developed modulation scheme on a single conventional DSP is proposed. Hardware-in-the-loop studies of the ZSUMC under the developed modulation scheme are carried out to verify the feasibility of the proposed implementation approach on a conventional DSP.

A Time and Energy Efficient Routing Algorithm for Electric Vehicles Based on Historical Driving Data

A routing algorithm that leads to extended driving range and battery longevity of electric vehicles (EV) is proposed. In addition to locating the time and energy efficient routes, the proposed algorithm provides a desired speed profile to be tracked by the driver. Data mining techniques are employed for extracting the desired speed profile for the goal driver from a set of historical driving data. In order to select data with strong analogy to those of the goal drivers vehicle and driving conditions, driving and vehicle attributes are defined. The historical driving data are clustered and the class of the goal driver among clustered data is determined through classification. Eventually, the required travel time and energy consumption corresponding to historical speed profiles are evaluated and the time and/or energy efficient route along with the desired speed profile are determined. The proposed method is tested on a set of data gathered in the Warrigal project, which provides real vehicle state information. Since the consumed energy data are not available in this dataset, a detailed EV model is adopted to estimate the energy consumption. The obtained results verify the effectiveness of the proposed routing algorithm in locating the time and/or energy efficient routes.