Real-time Converter Research Articles

Model Predictive Control Using Artificial Neural Network for Power Converters

There has been an increasing interest in using model predictive control (MPC) for power electronic applications. However, the exponential increase in computational complexity and demand of computing resources hinders the practical adoption of this highly promising control technique. In this article, a new MPC approach using an artificial neural network (termed ANN-MPC) is proposed to overcome these barriers. A power converter with a virtual MPC controller is first designed and operated under a circuit simulation or power hardware-in-the-loop simulation environment. An artificial neural network (ANN) is then trained offline with the input and output data of the virtual MPC controller. Next, an actual FPGA-based MPC controller is designed using the trained ANN instead of relying on heavy-duty mathematical computation to control the actual operation of the power converter in real time. The ANN-MPC approach can significantly reduce the computing need and allow the use of more accurate high-order system models due to the simple mathematical expression of ANN. Furthermore, the ANN-MPC approach can retain the robustness for system parameter uncertainties by flexibly setting the input elements. The basic concept, ANN structure, offline training method, and online operation of ANN-MPC are described in detail. The computing resource requirement of the ANN-MPC and conventional MPC are analyzed and compared. The ANN-MPC concept is validated by both simulation and experimental results on two kW-class flying capacitor multilevel converters. It is demonstrated that the FPGA-based ANN-MPC controller can significantly reduce the FPGA resource requirement (e.g., 2.11 times fewer slice LUTs and 2.06 times fewer DSPs) while offering a control performance same as the conventional MPC.

Implementation of Cuk Converter with dSPACE1103 controller

This paper discusses a simple approach for the implementation of closed loop control of Cuk converter in real time using dSPACE1103 controller. The control algorithm and the proportional integral controller (PI) are constructed in MATLAB simulink with dSPACE blocksets. The converter is designed with a power rating of 18 W with 30 V output voltage for LED driver applications for an input of 12 V DC supply. The Cuk converter and the driver circuits are designed and fabricated in real time. The circuit is tested under different running conditions. Simulation and experimental results are provided to validate the performance of the converter.

Power Distribution Algorithm and Steady-State Operation Analysis of a Modular Multiactive Bridge Converter

Electrical distribution systems comprising different power sources and loads, such as electric vehicles, aircraft electrical distribution systems, and residential microgrids, need new power conversion architectures. Multiport converters are an alternative to conventional multiconverter systems. This work studies a modular multiactive bridge (MMAB) converter, which is a multiport converter based on the connection of active bridges and independent transformers. The converter is bidirectional, fully modular, and scalable. It allows the connection of multiple power sources and loads that may change its power flow direction, allowing hot connection and disconnection of modules. The control of the power flow in each port depends on the relative phase shift among the control pulses of the other active bridges. An iterative algorithm is developed and implemented in a digital device to control the converter in real time. Besides theoretical analysis, the main characteristics of the converter have been validated in a lab prototype with five modules. The experimental results validate the theoretical predictions. Power distribution among the modules has been kept under 9% of error with respect to the desired value, considering an open-loop control.

Fundamental Device Switching Frequency Control of Current-Fed Nine-Level Inverter for Solar Application

The aim of this article is to develop a real-time computational method that determines switching angles of selective harmonic elimination (SHE) for operating nine-level (9 L) current-fed multilevel converter (MLC). The computation algorithm for SHE conventionally requires huge calculation time to identify switching angles of the inverter, and hence, a truth table based modulation is applied for operating the converter in real time. To overcome this, a new analytical method has been proposed in this article that minimizes the computation time to calculate the switching angles. However, these switching angles cannot be directly applied to current-fed MLCs. Unlike voltage fed converters, the current-fed converters have additional operational constraints on the modulation technique. Hence, in this article, a conversion technique has been utilized to convert the unconstraint SHE angles into constraint angles in order to operate current-fed MLCs. A low-power prototype of 9 L current source inverter has been set-up to experiment and validate the proposed real-time calculation method at the fundamental frequency of 50 Hz.

Industrial IoT based condition monitoring for wind energy conversion system

Wind energy has been identified as the second dominating source in the world renewable energy generation after hydropower. Conversion and distribution of wind energy has brought technology revolution by developing the advanced wind energy conversion system (WECS) including multilevel inverters (MLIs). The conventional rectifier produces ripples in their output waveforms while the MLI suffers from voltage balancing issues across the DC-link capacitor. This paper proposes a simplified proportional integral (PI)-based space vector pulse width modulation (SVPWM) to minimize the output waveform ripples, resolve the voltage balancing issue and produce better-quality output waveforms. WECS experiences various types of faults particularly in the DC-link capacitor and switching devices of the power converter. These faults, if not detected and rectified at an early stage, may lead to catastrophic failures to the WECS and continuity of the power supply. This paper proposes a new algorithm embedded in the proposed PI-based SVPWM controller to identify the fault location in the power converter in real time. Since most wind power plants are located in remote areas or offshore, WECS condition monitoring needs to be developed over the internet of things (IoT) to ensure system reliability. In this paper, an industrial IoT algorithm with an associated hardware prototype is proposed to monitor the condition of WECS in the real-time environment.

Design, Architecture, and Real-Time Distributed Coordination DMPPT Algorithm for PV Systems

The large-scale integration of photovoltaic (PV) systems for renewable power generation requires an intelligent and cost-effective solution in the emerging microgrid applications. In this paper, a fast real-time distributed coordination algorithm is proposed to address the challenge of extracting the maximum power from PV systems connected to microgrid under all uncertainties. A series PV string architecture with differential power processing (DPP) dc–dc converters is considered to extract the maximum power from PV systems by using distributed maximum power point tracking (DMPPT) method. A distributed digital controller architecture is developed for controlling the duty ratio of each DPP dc–dc converter in real time. The digital controller architecture consists of a main bus controller (BC) and submodule controller (SMC) for each DPP dc–dc converter. The BC coordinates the control operation of entire string through communication protocol with SMCs. The BC and SMCs are implemented with PIC18F8520 and PIC18F452 microcontrollers, respectively. An experimental prototype of a PV system is developed with six PV modules. The merits of the proposed algorithm are analyzed with respect to the communication protocol, control method, tracking efficiency, and tracking response time under varying operating conditions.

A modified PWM three intervals control for a matrix converter in real time

Abstract In this paper, the application of the proposed control strategy PWM three intervals with 3×5 matrix converter is presented and analyzed. This control strategy is developed for the control of the multi-phases matrix converter, where the main aim is to ensure the waveform quality of the output voltages and the input currents based on the THD evaluation. Simulation results and real time implementation on dSpace 1103 of 3×5 matrix converter under R-L load are presented for the validation of the proposed control strategy and to clarify the main related advantages.

Low cost time to digital converter in real time with ±1 ns resolution

A time to digital converter (TDC) with a time resolution of 1 ns has been designed. The deadtime is T+0.6 μs where T is the measured time. The time range can be preselected between 0.3 between 10 μs. The TDC has one START and three mutually exclusive STOP inputs which accept standard pulses (−16 mA). The time information is presented as a bit binary word, including the activated stop input address. The instrument has been successfully used in μ + SR (muon spin rotation) measurements and has proven itself advantageous over the more common TAC+ADC combination.