Emulation System Research Articles

Power-Electronic-Based Electric Machine Emulator Using Direct Impedance Regulation

Power-electronics-based emulators have been showing promising prospects in advanced testing of various applications of power electronics systems. For electric machine applications, typical machine emulators calculate the references of stator current in response to terminal voltages via mathematical models of the machine system, and then, the current behaviors of emulators are regulated by using feedback controls. However, the dynamic and high-frequency performances of these machine emulators could be distorted by the introduced control loops, thus compromising the emulating performances. In this article, the limits of typical machine emulators are analyzed, and a new approach is proposed for the real-time emulation of permanent magnet synchronous machines (PMSM). A linear regulator without feedback control loop is proposed and designed to reshape the frequency-domain characteristics of the converter and current filter inside the emulation system. Compared with typical solutions, the proposed approach has frequency-domain characteristics closer to the target PMSM. The dynamic performances can be more accurately recreated, and the applicable frequency range for emulation can be extended. Simulations and experimental validations are also conducted to verify the effectiveness of the proposed approach.

Real-Time FPGA-Based HIL Emulator of Power Electronics Controllers Using NI PXI for DFIG Studies

This article presents a high-performance hardware-in-the-loop (HIL) system aimed to assist experts in developing and testing power electronics control board and their logic with real-time (RT) models of both electrical and mechanical components. For demonstrating the effectiveness of this system for HIL testing, a new industrial doubly-fed induction generator (DFIG) control board is tested based on a comprehensive wind energy conversion model developed in MATLAB/Simulink hardware description language (HDL) coder and LabVIEW environment. The interaction between MATLAB/Simulink and LabVIEW is accomplished by National Instrument (NI) intellectual property (IP) integration node, which loads very high-speed integrated circuit hardware description language (VHSIC-HDL or VHDL) codes (that enable those two software exchange RT data). LabVIEW implements a VHDL code of electrical model with fixed-point variables on an R-Series reconfigurable input/output (I/O) field-programmable gate array (FPGA) module on NI-PXIe 7858R installed on NI PXIe 1062Q chassis, and the mechanical models deployed in its PXIe 8133 central processing unit (CPU). Finally, through a uniquely developed interface board, the HIL emulator connects to an external DFIG control board. In FPGA, the model and other communicational and logging components’ step-time in each iteration is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5.0~\mu \text{s}$ </tex-math></inline-formula> . For verifying the results, a comparison is made between the proposed emulator system and Typhoon HIL602+ as a commercially available HIL system. It is proven that there is little or no significant deviation between the outputs of two systems. The proposed HIL emulator does not have the limitation of commercial HIL systems in adding custom-made new components.

A Novel Energy Management Strategy in Electric Vehicle Based on H∞ Self-Gain Scheduled for Linear Parameter Varying Systems

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.

Moral Community and Moral Order

This work aligns James Buchanan’s theory of social contract with the structure of Michael Moehler’s multilevel social contract. Most importantly, this work develops Buchanan’s notions of moral community and moral order. It identifies moral community as the vehicle of escape from moral anarchy, where community is established upon a system of rules akin to James Buchanan’s first-stage social contract. Moral order establishes the baseline treatment of non-members by members of a moral community and also provides a minimum standard for resolving disputes that are not resolved by the more robust social contract shared among community members. This work links the multilevel contract to polycentric social order, noting that polycentric systems may promote development of the moral order by enabling experimentation with and emulation of rules and rule systems made available by overlapping and adjacent institutions.

Robust Model Predictive Control for Dynamics Compensation in Real-Time Hybrid Simulation

Hybrid simulation is an efficient method to obtain the response of an emulated system subjected to dynamic excitation by combining loading-rate-sensitive numerical and physical substructures. In such simulations, the interfaces between physical and numerical substructures are usually implemented using transfer systems, i.e., an arrangement of actuators. To guarantee high fidelity of the simulation outcome, conducting hybrid simulation in hard real-time is required. Albeit attractive, real-time hybrid simulation comes with numerous challenges, such as the inherent dynamics of the transfer system used, along with communication interrupts between numerical and physical substructures, that introduce time delays to the overall hybrid model altering the dynamic response of the system under consideration. Hence, implementation of adequate control techniques to compensate for such delays is necessary. In this study, a novel control strategy is proposed for time delay compensation of actuator dynamics in hard real-time hybrid simulation applications. The method is based on designing a transfer system controller consisting of a robust model predictive controller along with a polynomial extrapolation algorithm and a Kalman filter. This paper presents a proposed tracking controller first, followed by two virtual real-time hybrid simulation parametric case studies, which serve to validate the performance and robustness of the novel control strategy. Real-time hybrid simulation using the proposed control scheme is demonstrated to be effective for structural performance assessment.

Probing criticality in quantum spin chains with neural networks

The numerical emulation of quantum systems often requires an exponential number of degrees of freedom which translates to a computational bottleneck. Methods of machine learning have been used in adjacent fields for effective feature extraction and dimensionality reduction of high-dimensional datasets. Recent studies have revealed that neural networks are further suitable for the determination of macroscopic phases of matter and associated phase transitions as well as efficient quantum state representation. In this work, we address quantum phase transitions in quantum spin chains, namely the transverse field Ising chain and the anisotropic XY chain, and show that even neural networks with no hidden layers can be effectively trained to distinguish between magnetically ordered and disordered phases. Our neural network acts to predict the corresponding crossovers finite-size systems undergo. Our results extend to a wide class of interacting quantum many-body systems and illustrate the wide applicability of neural networks to many-body quantum physics.

Digital PID Control Law Design for Fuel Cell Model Based on FPGA Emulator System

This paper proposes an off-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. The aim of this research is to obtain the best hydrogen partial pressure (PH2) value using FPGA emulator to design and implement a digital PID controller that track the fuel cell output voltage during a variable load current applied. The off-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID controller parameters that improve the dynamic behavior of the closed loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package and FPGA emulator experimental work show the performance of the proposed FPGA-PID controller in terms of voltage error reduction and generating optimal value of the (PH2) control action without oscillation in the output and no saturation state when these results are compared with other control methodology.

AC Grid Emulations for Advanced Testing of Grid-Connected Converters—An Overview

High penetration of distributed generations and active loads have enabled the power electronics converter to become a vital component in the modern power grid system, and the broad employment of grid-connected converters at various power levels is making the grid impedance and characteristics complicated. Consequently, in order to validate more advanced features such as the reliability and stability performances of the grid-connected converters, it is becoming an emerging need to emulate the grid behaviors from more aspects. This article serves to foster and investigate the state-of-the-art techniques in the field of ac grid emulation from the perspective of multiple spatial-scales and multiple time-scales. Four major concepts used for grid emulation with featured principles, including concept I (analog simulation with under-scaled components), concept II (grid characteristics in the real-time simulator), concept III (grid characteristics in the converters structure), and concept IV (grid characteristics in the converters controller), are summarized, respectively, in this article. The practical implementation regarding to the circuit topology and the power supply for the grid emulation system are also discussed. Finally, the future trends and conclusions in the field of ac grid emulation are provided.

Emulation of up-conversion based quantum key distribution scheme using active pump-controlled basis selection and adaptive thresholding

We emulate a method for quantum key distribution (QKD) that employs up-conversion detection. The scheme uses differential quadrature phase shift modulation and actively chooses the measurement basis by applying a dynamic phase-shift on the pump of the up-conversion interaction. The QKD rate of the quantum-hacking resistant system over an emulated 7.5 km marine-like turbulent channel is evaluated including the impact of thresholding the received data so as to ignore signals that are below a tolerable signal-to-noise ratio. The emulated system is well suited to operate over marine free space optical links coupled to single mode fiber.

Improving FPGA-Based Logic Emulation Systems through Machine Learning

We present a machine learning (ML) framework to improve the use of computing resources in the FPGA compilation step of a commercial FPGA-based logic emulation flow. Our ML models enable highly accurate predictability of the final place and route design qualities, runtime, and optimal mapping parameters. We identify key compilation features that may require aggressive compilation efforts using our ML models. Experiments based on our large-scale database from an industry’s emulation system show that our ML models help reduce the total number of jobs required for a given netlist by 33%. Moreover, our job scheduling algorithm based on our ML model reduces the overall time to completion of concurrent compilation runs by 24%. In addition, we propose a new method to compute “recommendations” from our ML model to perform re-partitioning of difficult partitions. Tested on a large-scale industry system on chip design, our recommendation flow provides additional 15% compile time savings for the entire system on chip. To exploit our ML model inside the time-critical multi-FPGA partitioning step, we implement it in an optimized multi-threaded representation.

Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation

Home energy management systems (HEMS) are a key technology for managing future electricity distribution systems as they can shift household electricity usage away from peak consumption times and can reduce the amount of local generation penetrating into the wider distribution system. In doing this they can also provide significant cost savings to domestic electricity users. This paper studies a HEMS which minimizes the daily energy costs, reduces energy lost to the utility, and improves photovoltaic (PV) self-consumption by controlling a home battery storage system (HBSS). The study assesses factors such as the overnight charging level, forecasting uncertainty, control sample time and tariff policy. Two management strategies have been used to control the HBSS; (1) a HEMS based on a real-time controller (RTC) and (2) a HEMS based on a model predictive controller (MPC). Several methods have been developed for home demand energy forecasting and PV generation forecasting and their impact on the HEMS is assessed. The influence of changing the battery’s capacity and the PV system size on the energy costs and the lost energy are also evaluated. A significant reduction in energy costs and energy lost to the utility can be achieved by combining a suitable overnight charging level, an appropriate sample time, and an accurate forecasting tool. The HEMS has been implemented on an experimental house emulation system to demonstrate it can operate in real-time.

An Investigation of Power-Hardware-in-the-Loop- Based Electric Machine Emulation for Driving Inverter Open-Circuit Faults

Power-hardware-in-the-loop (PHIL) simulations, in the form of machine emulation, are gaining popularity for electric drive system testing in transportation applications. Since there is a reduced chance of equipment damage with PHIL simulations, they are particularly suited for the testing of electric drive systems, for drive inverter faults. This article investigates PHIL simulations to emulate machine behavior in the event of drive inverter faults resulting due to a gate-drive failure of one or more switches. Modifications are proposed to the closed-loop current control of the machine emulator system. These modifications ensure that various lower order harmonics in the emulated machine currents, resulting due to the drive inverter faults, are accurately emulated. Drive inverter damages resulting due to machine behavior emulation in fault conditions are avoided by proposing appropriate emulator control structure modifications. Experimental results are obtained for the emulation of machine behavior for various drive inverter gate-drive faults. These experimental results are compared with that obtained from a faulty drive inverter feeding a prototype machine. A close match between the two results is shown to prove the sufficiency and utility of the proposed controller modifications in the developed PHIL-based machine emulation system.

A Single Back-to-Back Converter Based System Emulator for Testing Unbalanced Microgrids

Renewable energy sources are typically interfaced to the main grid at the distribution level, through power electronic converter interfaces. Testing these microgrid systems is a crucial aspect which is gaining increased interest and importance among researchers. This article proposes a system emulator , for testing microgrids, with a special focus on replicating unbalanced network conditions . The proposed system uses a single back-to-back bidirectional converter for real-time emulation, and the user has the option to chose any node of their interest to study the dynamics. This is different from the ones proposed to-date - most of them focus on balanced systems, and use several converters to replicate the dynamics of the microgrid system, in which each converter mimics one entity at a time (source or load). A system with two generators is emulated for different control strategies and types of unbalances in the network. The crucial aspects related to the modelling and control are presented in detail supported by simulations and experimental validation on a prototype developed.

A Software based ASL Translator and ASL to Voice Emulation System

A Software based ASL Translator and ASL to Voice Emulation System

Super-twisting control using higher order disturbance observer for control of SISO and MIMO coupled systems

In this paper, accuracy of the existing disturbance observer (DO) for disturbance estimation is increased by increasing its order. Stability of the proposed higher order disturbance observer (HODO) is analysed. Furthermore, a new HODO based super-twisting control (STW) algorithm is presented for the system with the bounded matched disturbances. A HODO based sliding mode control (SMC) algorithm with the integral sliding surface is proposed where the controller gains depend on the disturbance estimation error bound instead of the disturbance magnitude. Therefore, controller gains required in the proposed approach for the disturbance rejection are lesser as compared to the STW. As a result of which, with the proposed control, substantial chattering attenuation better than the STW is achieved. The proposed control technique is successfully applied to the single-input single-output (SISO) Industrial Emulator system with matched disturbance and the multi-input multi-output (MIMO) coupled 2-DOF Helicopter system with complex disturbances. The simulation and experimental outcomes illustrate the effective implementation of the proposed control strategy for tracking desired input, achieving stabilization and robustness of the system in the existence of bounded complex matched disturbances.

Real-Time Hardware-in-the-Loop Emulation of High-Speed Rail Power System With SiC-Based Energy Conversion

Real-Time Hardware-in-the-Loop Emulation of High-Speed Rail Power System With SiC-Based Energy Conversion

ELS: Emulation system for debugging and tuning large-scale parallel programs on small clusters

Continuous scaling-up of high-performance computing systems has brought challenges to the debugging and tuning of large-scale parallel programs. Firstly, to locate bugs in a program or tune its performance, programmer often needs to execute the program in a specified scale repeatedly, which consumes massive resources; secondly, due to the extensively used job scheduling systems, programmers can only submit their programs as jobs and cannot interact with them, which restricts debugging efficiency and flexibility. To address these challenges, this paper proposes an emulation system that supports debugging and tuning of large-scale parallel programs by executing parallel programs in the desired scale on a small cluster. The program is firstly executed in the desired scale on the target HPC system to record necessary information; then, programmers can choose and re-execute a subset of processes of the program repeatedly on a small cluster, during which the emulation system controls the execution of the processes, and programmers can debug their programs by attaching tools to the selected processes. Moreover, our system supports popular CPU+GPU heterogeneous architecture. The system is evaluated on a small cluster, while a 1000-node system is used as the target HPC system; experimental results demonstrate the accuracy and efficiency of emulation-execution.

Reduced Scale PHIL Emulation Concepts Applied to Power Conversion Systems With Battery Storage

This article deals power hardware in the loop (PHIL) real-time simulation (also called emulation) of electric power conversion systems, especially the ones involving battery storage. A case study related to a wind turbine power conversion system hybridized with a lithium-ion battery illustrates the main concepts. A similitude reduction process is presented to scale the model parameters in order to fulfill the sizing of a reduced scale test bench allowing to achieve the PHIL real-time emulation. The original “time compression” concept is also reminded. However, the main contribution of this article is the comparison between two concepts of real-time emulated devices (RTED) depending on whether these concepts are based on a model (“model based” RTED) or on a physical image of the actual device (“image based” RTED). Advantages and drawbacks of both concepts are discussed based on experimental results.

Emulation of Multi-Inverter Integrated Weak Grid via Interaction-Preserved Aggregation

Simplified weak grid models are widely used to emulate the nonideal power grid for the design and stability analysis of grid-connected inverters. However, the dynamic behavior of a real grid with multiple inverters is complex. In this article, an emulation method is proposed for multi-inverter integrated weak grids using an interaction-preserved aggregation model associated with grid impedance. First, the interaction among inverters in weak grids is analyzed using the state-space model and participation analysis. Then, a two-inverter aggregation is proposed for a large-scale system. This model can preserve the impact of parameters on the interaction modes (IMs) and predict the IM-related instability of multi-inverter systems. Thus, the two-inverter representation is applied to emulation to preserve interactions and to simplify the testing of multiple inverters. The emulation of the 16-inverter system is implemented on a hardware-in-the-loop (HIL) test bench with one practical inverter controller under test and the remaining parts integrated in the OPAL-RT real-time simulator. The test results show that the instability attributed to the interaction can be identified by the proposed emulation method.

Emulation of Wind Turbine System Using Vector Controlled Induction Motor Drive

Depleting fossil fuels and concerns about global warming have forced a paradigm shift toward renewable energy resources in meeting our energy requirements. Wind energy utilization has been growing at a rapid rate fuelling research and development in high power wind turbines (WTs). To advance research and education in wind energy conversion systems, a controlled test bed is necessary that does not depend on wind availability. Majority of the existing WT emulation schemes employ a torque compensation loop to account for the inertia difference between the WT and motor used for emulation. However, the loop suffers from noise and instability issues. Also, the torque compensation term is sensitive to parameter estimates. This article proposes one degree of freedom (1-DOF) and 2-DOF control structures for WT emulation. It first illustrates the design and performance of 1-DOF control structure. It further proposes two controllers along with their prefilters in 2-DOF structure, which has superior performance than 1-DOF structure. The design of the controllers and prefilters is explained with the help of root locus. The performance of the WT emulator with the proposed control structures is demonstrated through simulations and experiments on a 7.5 kW doubly fed induction generator driven by a 5.5 kW squirrel cage induction motor, where the dynamics and steady-state operation of a WT–generator system are emulated.