Real-time Hardware-in-the-loop Research Articles

A versatilely high fidelity electric machines emulator for rapid testing of motor controller.

Electric machines emulators (EMEs) based on hardware-in-the-loop (HIL), which effectively act as emulators to mimic the actual motor behavior of Interior Permanent Magnet (IPM) machines. EME is frequently used to evaluate motor controller and motor control methodologies prior to development. The inverse magnetization motor model, which is used as the basis for real-time simulation in this paper's proposal for an electric machine emulator system based on HIL, uses FEA to create the motor model data. The nonlinear features of the motor may be successfully replicated with this motor model, and the accuracy of the electric machine emulator can be enhanced by using a straightforward and trustworthy motor controller. The real-time simulation tool typhoon HIL is used in the study to develop a hardware-in-the-loop simulation platform for an IPM electric machines emulator.

A Semi-Implicit Parallel Leapfrog Solver With Half-Step Sampling Technique for FPGA-Based Real-Time HIL Simulation of Power Converters

Field Programmable Gate Array (FPGA) based Hardware-in-the-loop (HIL) simulation is an effective tool to verify the performance of physical controllers and shorten the development cycle of power converters. In HIL simulations, sampling accuracy is of concern and is desired to be improved by reducing the step size. However, due to the cost of computational time, the step size is hard to reduce indefinitely to meet the requirements for high switching frequency applications. To improve the sampling accuracy and simulation performance of HIL simulation, this paper proposes a semi-implicit parallel leapfrog (SPL) solver with half-step sampling technique. In this solver, the switches and the rest part of the system are implemented to be computed parallel when the switch leg model operates in continuous current mode. Besides, the solver is formulated in leapfrog format to reduce computational costs and to compute at half-step as a minimum step-size. With this format, the half-step sampling technique can be employed to increase the sampling rate by onefold, even in cases where it is challenging to reduce the simulation step size further. A dual active bridge converter case is implemented on the FPGA board with a 12.5-ns sampling step-size, retaining the simulation accuracy while switched at 400 kHz. To further verify the advantages, the results are compared with other HIL method and experimental results.

Real-Time Implementation for the Robust Controller of the Switched Boost Inverter within an Autonomous Modified Nanogrid

SBI stands for switched-boost inverter and is a single-stage power converter used to connect low-power sources, such as solar photovoltaic (PV) arrays within a modified nanogrid, to loads. Despite its many benefits, such as the fact that it does not require expensive sophisticated dead-time circuitry, its duty ratio is limited to between 0 and 0.5. As a result, this publication is a contribution towards improving the SBI's performance for use in a modified nanogrid. Furthermore, it also presents a revolutionary strategy for a simple closed-loop control technique that overcomes the majority of inverter shortcomings and system nonlinearity. The suggested robust controller uses a metaheuristic optimization technique, called gorilla troops optimization (GTO), to optimize the performance of this controller. The robustness of the suggested controller is tested against the sudden change of the nanogrid input voltage (i.e., PV-voltage), modulation index of the inverter, and the step-change in DC-link output voltage of the inverter. The test results obtained from Matlab/Simulink software are compared with particle swarm optimization (PSO) – as another optimization algorithm. Furthermore, the proposed system is experimentally implemented with OPAL RT-4510v real-time hardware in the loop (HIL), rapid control prototyping, OP-8660 HIL controller and data acquisition platform.

MPSoC-Based Dynamic Adjustable Time-Stepping Scheme with Switch Event Oversampling Technique for Real-time HIL Simulation of Power Converters

MPSoC-Based Dynamic Adjustable Time-Stepping Scheme with Switch Event Oversampling Technique for Real-time HIL Simulation of Power Converters

Development of a Hardware-in-the-Loop Platform for the Validation of a Small-Scale Wind System Control Strategy

The use of renewable energies contributes to the goal of mitigating climate change by 2030. One of the fastest-growing renewable energy sources in recent years is wind power. Large wind generation systems have drawbacks that can be minimized using small wind systems and DC microgrids (DC-µGs). A wind system requires a control system to function correctly in different regions of its operating range. However, real-time analysis of a physical wind system may not be feasible. An alternative to counteract this disadvantage is using real-time hardware in the loop (HIL) simulation. This article describes the implementation of an HIL platform in an NI myRIO 1900 to evaluate the performance of control algorithms in a small wind system (SWS) that serves as a distributed generator for a DC-µG. In the case of an SWS, its implementation implies nonlinear behaviors and, therefore, nonlinear equations, and this paper shows a way to do it by distributing the computational work, using a high-level description language, and achieving good accuracy and latency with a student-oriented development kit. The platform reproduces, with an integration time of 10 µs, the response of the SWS composed of a 3.5 kW turbine with a fixed blade pitch angle and no gear transmission, a permanent magnet synchronous generator (PMSG), and a three-phase full-bridge AC/DC electronic power converter. The platform accuracy was validated by comparing its results against a software simulation. The compared variables were the PMSG currents in dq directions, the turbine’s angular speed, and the DC bus’s voltage. These comparisons showed mean absolute errors of 0.04 A, 1.9 A, 0.7 rad/s, and 9.5 V, respectively. The platform proved useful for validating the control algorithm, exhibiting the expected results in comparison with a lab-scale prototype using the same well-known control strategy. Using a well-known control strategy provides a solid reference to validate the platform.

Optimizing Photovoltaic Power Production in Partial Shading Conditions Using Dandelion Optimizer (DO)-Based MPPT Method

This research proposes the dandelion optimizer (DO), a bioinspired stochastic optimization technique, as a solution for achieving maximum power point tracking (MPPT) in photovoltaic (PV) arrays under partial shading (PS) conditions. In such scenarios, the overall power output of the PV array is adversely affected, with shaded cells generating less power and consuming power themselves, resulting in reduced efficiency and local hotspots. While bypass diodes can be employed to mitigate these effects by redirecting current around shaded cells, they may cause multiple peaks, making MPPT challenging. Therefore, metaheuristic algorithms are suggested to effectively optimize power output and handle multiple peaks. The DO algorithm draws inspiration from the long-distance movement of a dandelion seed, which relies on the force of the wind. By utilizing this bioinspired approach, the DO algorithm can successfully capture the maximum power point (MPP) under different partial shading scenarios, where traditional MPPT algorithms often struggle. An essential contribution of this research lies in the examination of the performance of the proposed algorithm through simulation and real-time hardware-in-the-loop (HIL) results. Comparing the DO algorithm with the state-of-the-art algorithms, including particle swarm optimization (PSO) and cuckoo search (CS), the DO algorithm outperforms them in terms of power tracking efficiency, tracking duration, and the maximum power tracked. Based on the real-time HIL results, the DO algorithm achieves the highest average efficiency at 99.60%, surpassing CS at 96.46% and PSO at 94.74%. These findings demonstrate the effectiveness of the DO algorithm in enhancing the performance of MPPT in PV arrays, particularly in challenging partial shading conditions.

DSP based Hardware-in-the-Loop (HIL) Simulation for GCPV-based DSTATCOM using Frequency Domain Controller

This study presents a comprehensive simulation of digital control applications for a grid-connected photovoltaic (GCPV) system using a Hardware-in-the-Loop (HIL) simulation approach that incorporates a Digital Signal Processor (DSP). The simulation is carried out using the MATLAB Simulink block set and employs a frequency domain controller as the control algorithm. The simulation inputs, which consist of voltage and current sensor readings, are processed by an ADC idealizer block that produces output based on a real-time DSP-based HIL system. The output is then utilized to generate a pulse width modulation (PWM) signal, which drives the voltage source inverter (VSI). The simulation’s primary objective is to demonstrate the simplicity and efficacy of the proposed frequency domain controller design for the GCPV-based DSTATCOM system. The simulation results validate the performance of the controller under various operating conditions, including steady-state, unbalanced loads, variable solar insolation, and day-to-night transitions.

Coyote Optimization Algorithm-Based Energy Management Strategy for Fuel Cell Hybrid Power Systems

This research proposes an improved energy management strategy (EMS) for a fuel cell hybrid power system for an electric aircraft based on a recently developed coyote optimization algorithm (COA). The suggested hybrid system consists of fuel cells and an energy storage system (ESS) to supply the required load in stable conditions. The distribution and performance of the hybrid electrical power system are determined by various energy sources. Consequently, having the best energy management system is essential for completing this work. The suggested EMS’s main objectives are to reduce hydrogen energy utilization and increase power source longevity. The proposed coyote optimization algorithm with external energy maximization strategy (COA-EEMS) and coyote optimization algorithm with equivalent consumption minimisation strategy (COA-ECMS) are tested with the help of the Opal-RT 5700 real-time HIL simulator and MATLAB/Simulink. The proposed algorithms confirm their robustness and higher efficiency by minimizing hydrogen fuel consumption compared to existing algorithms. The merits of the proposed algorithms are presented in detailed and compared with existing algorithms.

Novel strategy for fault e-diagnosis of wind energy conversion systems using wavelet analysis based on Rt-Lab and Arduino

The diagnosis of wind energy conversion systems (WECS) turns out to be necessary because of their relatively high cost of operation and maintenance. Wind turbines are hard-to-access structures, and they are often located in remote areas. Therefore, a remote diagnosis (e-diagnosis) is required. This paper proposes an alternative approach for the e-diagnosis of a WECS based on the discrete wavelet transform (DWT) and frequency analysis of the aero generator stator currents. To validate this approach, real-time hardware in the loop (HIL) is used to simulate in real-time the mathematical model of the induction generator on the OPAL-RT OP5600 platform to generate the stator currents and the rotor speed. The DWT is applied to the current signal, to generate the DWT signal, which has a huge number of points that are not supported for direct transmission by the Arduino Mega RobotDyn because of its limited sample time. The absolute values of the DWT peak points (MDWT) are sent as point’s packages form to the diagnosis station via the ESP8266 integrated Wi-Fi board of the Arduino Mega RobotDyn to monitor the SCIG states and determine the number of broken bars.

Implementation and Performances Evaluation of Advanced Automotive Lateral Stability Controls on a Real-Time Hardware in the Loop Driving Simulator

This study concerns the comparative investigation of two advanced lateral stability automotive controllers with respect to a commercial solution. The research aims to improve the stability performances achieved by a combined tracking of yaw rate and side-slip angle through the application of optimal efforts. The proposed solutions are based on Linear Quadratic Regulation and Sliding Mode Control, respectively. Both rely on the same approach for the control objective definition but differ from the action perspective. This solution involves the adoption of a differential braking actuation technique to deliver a desired yaw moment to the car body to track controlled states. Indeed, a sliding controller can also traction torques of hub-motor configurations as well as steering corrections, achieving vehicle stability and a driving response in accordance with the pilot’s intentions. Calibration and validation of the controllers are performed through a Hardware-in-the-Loop simulation rig, along with a real-time static simulator, performing different close-loop maneuvers to assess achievements in terms of lateral stability. Results show that both solutions ensure higher handling performances if compared to Non-controlled or Commercial-controlled vehicle scenarios.

Robust nonlinear control of regenerative fuel cell, supercapacitor, battery and wind based direct current microgrid

Due to their simple structure and tremendous energy efficiency, direct current (DC) microgrids are becoming popular. The recent transition in power generation and consumption is based on the integration of renewable energy sources using DC microgrids. To facilitate this integration, a multi-source DC microgrid structure with five different sources including hybrid photoelectrochemical and photovoltaic (HPEV) cell, fuel cell, supercapacitor, battery and wind is presented in this paper. All the sources are linked to the DC bus via DC–DC power converters. Maximum power points for HPEV and wind have been obtained using artificial neural network. Nonlinear sliding mode controller, integral sliding mode controller, double integral sliding mode controller and super-twisting sliding mode controller have been presented for the output voltage regulation of the power sources. Global asymptotic stability of the framework has been verified using Lyapunov stability analysis. For load-generation balance, energy management system based on fuzzy logic has been devised. The proposed nonlinear controllers have been simulated and compared using MATLAB/Simulink®. Real-time hardware in the loop (HIL) experiment has been performed on the C2000 Delfino Microcontroller F28379D Launchpad for the validation of the proposed nonlinear controllers framework and compared with simulation results to validate the performance of the designed system.

Real-Time Dynamic Performance Enhancement for Solar-Powered Pumping Systems Using PI-Based MPPT Techniques

Abstract The integration of solar-powered pumping systems (SPPS) into agriculture and potable and wastewater sectors becomes mandatory to provide water in remote regions. The broad use of SPPS with classical maximum power point tracking controllers (MPPTCs) showed moderated voltage and power response deterioration. Therefore, the necessity for overcoming these performance degradations and pre-testing of MPPTCs is not an option for the proper operation of such systems. This paper presents a new simple, cost-effective real-time hardware-in-the-loop (RT-HIL) framework to enhance the dynamic performance of SPPS. To accomplish this study, a real pumping station was modeled and equipped with MPPTCs through matlab/simulink. Besides, a practical SPPS was implemented to evaluate the effectiveness of the proposed RT-HIL on system performance. The practical SPPS includes designing a DC-DC buck converter circuit equipped with metaheuristic optimization-based real-time MPPTCs. The tuned PI/FOPI-based MPPTCs are adopted in this work to gain the maximum power from the PV generator under measured real environmental conditions. The proposed real-time MPPTCs techniques are perturb and observe, and incremental conductance (IC) with I, PI, and fractional-order PI (FOPI) controllers. The simulation and the experimental results prove the superiority of the developed real-time FOPI-based MPPTCs in enhancing the system performance in terms of the gained power, module output current, pump flowrate, and pump efficiency. The paper’s novelty lies behind the relatively low-cost real-time execution of PI/FOPI-based MPPT techniques on SPPS. This work was simulated using matlab/simulink in conjunction with Arduino-based RT-HIL and the experimental validation was implemented at the National Water Research Center (NWRC) in Egypt.

Real-Time HIL Emulation of DRM With Machine Learning Accelerated WBG Device Models

Real-Time HIL Emulation of DRM With Machine Learning Accelerated WBG Device Models

An Event-Driven Parallel Acceleration Real-Time Simulation for Power Electronic Systems Without Simulation Distortion in Circuit Partitioning

The trend toward higher switching frequency and larger scale of power electronic systems poses challenges for real-time simulation. This article presents an event-driven hardware-in-the-loop (ED-HIL) simulation framework that does not rely on the small fixed simulation step-size related to the switching frequency. ED-HIL framework can improve the calculation efficiency by positioning switch events and using variable simulation step-size. Further, a parallel acceleration and circuit partitioning (PACP) solver is proposed based on this framework. The PACP solver partitions the circuit with energy storage elements and ensures that the partitioning does not introduce simulation distortion by using the higher order derivatives of the energy storage elements. Meanwhile, it achieves a process-level paralleling through a shared memory architecture in order to accelerate the simulation. As a result, the proposed PACP solver based on the ED-HIL framework can achieve about three times the simulation scale of a commercial FPGA-based real-time simulator at 1/16 the hardware cost under the same conditions. An accurate real-time HIL example of a power electronic transformer with 32 switches at a switching frequency of 20 kHz has been implemented on a personal computer. The simulation results are analyzed by comparing with experiment, offline software, and commercial real-time simulator.

Real-Time Electromagnetic Transient Simulation of AC-DC Networks [Book News

This book provides fundamental methods and hands-on case studies so that readers can become familiar with invaluable modeling methodologies for real-time emulation of modern electrical networks. It is suited for librarians, simulation specialists, advanced modeling and simulation engineers, microgrid planning, and designing professionals and professors in related fields, providing concepts to further explore new trends in real-time modeling and HIL. The book is also essential for engineers/ researchers willing to launch spinoffs in real-time modeling and HIL to take advantage of recent and future developments in FPGA technology.

A Novel Hardware-in-the-Loop Approach to Investigate the Impact of Low System Inertia on RoCoF Relay Settings

This paper presents a novel hardware-in-the-loop (HIL) approach as used to investigate the impact of the reduction in inertia on the Great Britain (GB) electrical power system with regard to rate of change of frequency (RoCoF) settings for Loss-of-Mains (LoM) protection. Furthermore, the research as presented in this paper updates, enhances, and validates a reduced model of the Great Britain transmission system, as originally developed in DIgSILENT PowerFactory by the National Grid Electricity System Operator. The enhanced model has been developed for integrated use with the OPAL-RT real-time HIL simulation toolkit and is validated against phasor measurement unit (PMU) data from actual disturbance events using novel automated interfacing between both integrated simulation platforms, PowerFactory from DIgSILENT and ePHASORSIM from OPAL-RT. The corresponding simulations show that the updated reduced model is capable of capturing the dynamic behaviour of the GB transmission system, including both local and inter-area oscillations, with satisfactory accuracy. Finally, the paper presents HIL study results with the reduced model to investigate the influence of decreasing system inertia on the response of LoM protection relays. The studies show that decreasing system inertia may have a significant impact on LoM relays using RoCoF detection, particularly relays using the legacy G59 setting of 0.125 Hz/s. Initial studies have also demonstrated the potential for a previously unrecognised interaction between system oscillations and the 500 ms operating delay, as specified in G59 and G99 Engineering Recommendations. Consequently, faster local oscillations (>1 Hz) reset the relay and decrease the sensitivity, whereas slower inter-area oscillations (<1 Hz) appear to cause the relay to overestimate the average RoCoF.

Nonlinear Self-Synchronizing Current Control for Grid-Connected Photovoltaic Inverters

Three-phase inverters for photovoltaic grid-connected applications typically require some form of grid voltage phase-angle detection in order to properly synchronize to the grid and control real and reactive power generation. Typically, a phase-locked loop scheme is used to determine this real-time phase angle information. However, in the present work, a novel method is proposed whereby the phase angle of the grid can be accurately identified solely via the grid current feedback. This phase-angle observer is incorporated into a current controller which can manage the real and reactive power of the grid-connected PV inverter system. Moreover, the maximum power point of the photovoltaic arrays is achieved without using a DC–DC converter. The proposed method achieves the grid current and DC-link voltage control objectives without the knowledge of the grid information and without the need for a cascaded control scheme. The design of this combined observer/controller scheme is motivated and validated via a Lyapunov stability analysis. The experimental setup is prototyped utilizing a real-time Typhoon HIL 603 and National Instrument cRIO embedded controller in order to validate the proposed observer/controller scheme under different operation scenarios such as irradiation changes, frequency changes, reactive power injection, and operation with a distorted grid. The results show that the DC-link voltage and the active and reactive powers are well regulated from the proposed control scheme without the measurement of the grid phase and frequency.

Real-time Implementation of a Single Phase Asynchronous Motor Drive, Feeding within an Open Energy Source

A modified nanogrid (MnG) is a very small scalable grid with a low power single-input multi-output (SIMO) inverter. This inverter simultaneously produces both AC and DC currents, such as the switched boost inverter (SBI) and the z-source inverter. These inverters are suitable for low-power loads such as home appliances that use fractional horse-power motors as single-phase asynchronous drives. Thus, this article proposes a single-phase induction motor powered from a modified nanogrid that involves multiple types of inverters such as a SBI and a ZS inverter. The modified nanogrid is mainly dependent on photovoltaic (PV) as a renewable resource. Thus, this manuscript involves a full design for this proposed grid with its maximum power point tracking (MPPT) and the mathematical models for motor drive with both a SBI and a ZSI. Time-varying speed trajectories are proposed to test the robustness of the proposed drives relative to the fluctuation of PV-parameters like its irradiance. Test results are obtained using the Matlab/ Simulink software package and a comparison with the traditional sinusoidal pulse width modulation (SPWM) inverter as a single-input single-output inverter (SISOI). The results indicate that the proposed single-input multi-output inverters are suitable for driving these motors through start-up and operation, although the DC-link voltage is minimized. Furthermore, the proposed system is experimentally implemented with OPAL RT-4510v real-time hardware in the loop (HIL), rapid control prototyping, and OP-8660 HIL controller and data acquisition platform.

Predictive Energy Management for Dual-Motor BEVs Considering Temperature-Dependent Traction Inverter Loss

In this paper, a predictive energy management system (EMS) for dual-motor battery electric vehicles (BEVs) is proposed, considering temperature-dependent traction inverter loss. First of all, we establish a high-fidelity BEV powertrain under a hardware-in-the-loop (HIL) testbed. The high-frequency switching of power electronics and electro-thermal traction inverters is considered. Subsequently, because transient current and voltage-based electro-thermal models in the literature are unsuitable for vehicle-level EMS design, we propose an innovative control-oriented inverter loss model and introduce approximate junction temperature dynamics in the predictive EMS. Then, based on Pontryagin’s Minimum Principle, we propose a fast solution algorithm, making it possible to validate the EMS in a real-time HIL testbed. To the best of our knowledge, temperature-dependent traction inverter loss has not yet been studied in EMSs. The traction inverter loss model has been experimentally validated and used in the proposed predictive EMS to provide more comprehensive validation. Results have shown that the proposed predictive EMS can reduce the power loss by 5-9% compared to the widely-used instantaneous optimization-based controller in academia.

Hybrid Interval Type-2 Fuzzy PID+I Controller for a Multi-DOF Oilwell Drill-String System

The control of multibody drill-string systems is not easy and designing such systems is considered challenging because of the difficulty in the dynamic analysis of its nonlinear characteristics and parametric uncertainties. An optimal hybrid interval Type-2 fuzzy PID+I logic controller (OH-IT2FPID+I) using a practical swarm optimization algorithm for a multi-degree-of-freedom oil well drill-string system is proposed in this paper. The suggested control concept is aimed to overcome several bit sticking troubles and stick–slip vibration by regulating the rotary velocities of drill-string components, especially rotary table velocity and drill bit velocity, to a predefined value. The drill-string system considered here has four degrees of freedom in the down-hole parts and the model takes the nonlinear interactions of the drill bit and the rocks into account, including friction torque and the mud drilling effect. Extensive simulations in Matlab/Simulink and experimental validations through a real-time hardware in the loop (HIL) system were performed to demonstrate the effectiveness of the suggested controller in comparison with sliding mode, Type 1 fuzzy logic and PID controllers. The quantitative comparison performed using simulation results proves that the proposed OH-IT2FPID+I provides higher control performance in terms of settling time and peak overshoot under variation of the weight on bit, the desired drill bit rotary speed, and handling parametric uncertainties. On the other hand, HIL results confirm the control performance provided by the proposed control under all different testing scenarios.