Off-line Simulation Research Articles

Study on 500Hz Modular Multi-level Convertor (MMC) by Real Time Simulation

This paper describes a study on 500Hz modular multi-level converter(MMC) using real time simulators. Integral time step in real time simulation is limited to keep real time performance. The outline specification of experimental model, control system for MMC, and results of off-line simulation and real-time simulation using two real-time simulaters are reported.

RETRACTED ARTICLE: The energy management strategy for parallel hybrid electric vehicles based on MNN

The energy management of the hybrid electric vehicle is still the research hotspot. In order to improve the fuel economy of the parallel hybrid electric vehicle, a new energy management design method based on the kernel fuzzy C clustering (KFCM) for multi neural network (MNN) is proposed. The global optimal solution is obtained by the dynamic programming global optimization off-line simulation, and the KFCM algorithm is used to cluster the global optimal data set according to the vehicle running mode, and the neural network is established for each cluster. The MNN model structure after training is used as the output of the energy management strategy to realize the real-time optimal allocation of engine and motor torque according to the real-time condition. The simulation results show that the energy management strategy based on KFCM-MNN has good learning simulation ability for dynamic planning energy management strategy, and it is a quasi-optimal control strategy.

The temperature distribution and underlying cooling mechanism of steel wire rod in the Stelmor type cooling process

The temperature distribution within wire ring during the Stelmor type cooling process has been investigated to understand the underlying cooling mechanism of steel wire rod using the well-designed off-line simulator and numerical simulation. The temperature deviation within wire ring varied with increasing air velocity and the maximum temperature deviation occurred at the air velocity of 10 m/s. Interestingly, the middle and inner edge regions of wire ring had a higher cooling rate than the center region under the air blowing cooling conditions because the air velocity around middle and inner edge regions was higher than that around center region. The cooling behavior of edge region is highly related to the ring pitch: the cooling rate of edge region dramatically decreased with decreasing ring pitch due to the more complicated ring structure. The proposed empirical equations as a function of wire diameter and air velocity can predict the cooling rates of wire ring well at both center and edge regions, which is a great benefit in industrial applications.

A systematic hybrid method for real-time prediction of system conditions in natural gas pipeline networks

The current framework of management of natural gas pipeline systems, based on off-line simulation, is facing challenges because of the increasing complexity, uncertainty and a number of time-dependent factors. To be effective, it requires comprehensive knowledge of system characteristics, accurate initial and boundary conditions. In an attempt to circumvent these problems, in this work we propose to use the deep learning method in the natural gas transmission system operation and management context. A data-driven prediction method is developed from real-time data of operation pressure and gas consumption. Specifically, the deep learning method is combined with the data window method and structural controllability theory to predict the conditions of gas pipeline network components. The data window method is applied to reconstruct the data structure and build a “memory” for the deep learning method. Structural controllability theory is applied to extract critical parameters, for reducing the problem size. The developed method allows accurate and efficient predictions, especially in abnormal conditions. For demonstration, the method is applied to a complex gas pipeline network. The results show that the developed method can provide accurate real-time predictions useful for reducing potential losses in operation, and perform efficient and effective management of the gas pipeline system. In the case study, the average prediction accuracy is higher than 0.99.

Non‐linear behavioural modelling of device‐level transients for complex power electronic converter circuit hardware realisation on FPGA

Detailed device-level models of the insulated-gate-bipolar-transistor (IGBT) and diode are essential for power converter design evaluation for providing insight into circuit and device behaviours, as well as to shorten the design cycle and reduce costs. In this study, the non-linear behavioural models of IGBT and power diode are utilised for emulating the modular multilevel converter (MMC) on the field programmable gate array. For digital hardware-in-the-loop (HIL) emulation, these time-domain continuous models are discretised and linearised prior to being designed into the corresponding hardware modules using the hardware description language VHDL that features a fully paralleled and pipelined implementation. A circuit partitioning approach is adopted according to the MMC structure to enhance computation efficiency and then, detailed information from the system-level performance to the specific features of individual switches is available. HIL emulation and the subsequent comparison with results from the commercial off-line simulation tools prove that the complex IGBT and diode models can be involved in the efficient simulation of large-scale power converters.

Impact of Using Near Real-Time Green Vegetation Fraction in Noah Land Surface Model of NOAA NCEP on Numerical Weather Predictions

Green vegetation fraction (GVF) is one of the input parameters of the Noah land surface model (LSM) that is the land component of a number of operational numerical weather prediction (NWP) models at the National Centers for Environmental Prediction (NCEP) of NOAA. The Noah LSM in current NCEP operational NWP models has been using static multiyear averages of monthly GVF derived from satellite observations of NOAA Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index. The multiyear averages of GVF are evidently not the representative of actual conditions of the land surface vegetation cover. This study used a near-real-time (NRT) GVF data set generated from the 8-day composite of the leaf area index product from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess the impact of NRT GVF on off-line Noah LSM simulations and NWP forecast model. Simulations of the off-line Noah LSM in the Land Information System (LIS) and weather forecasts of the NASA-Unified Weather and Research Forecasting (NUWRF) were obtained using either the static multiyear average AVHRR GVF data set or the NRT MODIS GVF while meteorological forcing data and other settings were kept the same. The off-line simulations and WRF forecasts were then compared against in situ measurements or reanalysis products to assess the impact of using NRT GVF. Improvements of both soil moisture simulations as well as forecasts of 2-meter air temperature and humidity and precipitation from NUWRF were observed using the NRT GVF data products. The RMSE in SM estimates from the off-line Noah model is reduced by around 1.0% (1.41%) during the green-up phase and by 1.48% (2.24%) over the senescence phase for the surface (root zone) SM simulations. Around 82.3% validation sites (out of 1178 sites) showed positive impact on coupled WRF model with the insertion of NRT GVF.

Real-Time Device-Level Simulation of MMC-Based MVDC Traction Power System on MPSoC

Real-time simulation of device-level power electronic converter models plays an essential role in traction power systems by allowing accurate prediction of device stresses to design improved control and protection schemes. This paper proposes the electrothermal behavioral power electronic models for the modular multilevel converter (MMC)-based medium voltage direct current (MVDC) traction power system based on the Wiener–Hammerstein configuration. The new configuration introduces the carrier charge prerequisite dynamic transients before device turn-ON or turn-OFF operation. The equivalent carrier charge circuit is also proposed, and the first-order delay assumption of turn-ON and turn-OFF delay time has been proven by the device datasheet. The power electronic device models are implemented in a Xilinx® Zynq® multiprocessing system-on-chip platform. By utilizing hardware and software codesign, both 25- $\mu \text{s}$ time-step system-level and 100-ns time-step device-level transients can be captured in real time within a single device. The three-phase unbalance issue has been resolved by introducing the three-phase to single-phase MMC topology. In the case study, the MMC-based MVDC traction power system has been utilized for the performance of the proposed electrothermal behavioral power electronic models by the off-line simulation models on SaberRD® for device-level transients and PSCAD/EMTDC® for system-level transients.

A Simulation Study of Global Evapotranspiration Components Using the Community Land Model

The Qian atmospheric forcing dataset is used to drive the Community Land Model, version 4.0 and 4.5 (CLM4 and CLM4.5) in off-line simulation tests. Based on flux network (FLUXNET) data and reanalysis data provided by National Oceanic and Atmospheric Administration (NOAA) and Climate Forecast System Reanalysis (CFSR), the simulation results of CLM4.5 on the global evaporation of intercepted water from the vegetation canopy (Ec), vegetation transpiration (Et), evaporation of soil (Es) and latent heat flux are evaluated. Subsequently, the improvement in the simulation results of CLM4.5 compared with CLM4.0 is tested and analyzed. The results show that the simulated spatial distribution of Ec, Et and latent heat flux in CLM4.5 are closer to the reanalysis data than Es. The simulated annual means of Et, Es and latent heat flux in CLM4.5 are larger than the reanalysis data, but Ec is smaller. The spatial distribution of the simulation bias of latent heat flux in CLM4.5 is mainly determined by the bias distribution of Es. There is a significant difference in the simulation of Et, Es and latent heat flux between CLM4.5 and CLM4.0. These differences are mainly present near the equator and in the middle and high latitudes in the Northern Hemisphere. In general, compared with CLM4.0, the simulation bias of Et, Es, and latent heat flux have been reduced in CLM4.5, and the simulated means are more consistent with the reanalysis data. Although there is a significant improvement in the simulation of the spatial distribution of Et and Es in CLM4.5 compared with CLM4.0, the ability of CLM4.5 to simulate the spatial distribution of global latent heat flux shows little improvement relative to CLM4.0.

Deformation simulation based on model reduction with rigidity-guided sampling

The deformation results of previous model reduction methods with external forces applied show noticeable differences from full-scale finite element method (FEM) simulation. We found that data-driven approaches, specifically proper orthogonal decomposition, can be a solution to this nonlinear deformation simulation problem in the subspace. Nevertheless, off-line FEM simulation with an infinite number of possible input forces at different locations makes it infeasible if no prior information is given. We propose rigidity-guided sampling to efficiently select the points of application of forces (force sample points) to construct more effective and compact subspace bases, thereby improving the simulation accuracy of reduced deformable models with applied external forces and still retaining fast run-time performance. The key idea of our approach is that distinct deformations of an object at different force sample points can be estimated prior to FEM simulation. By selecting the force sample points with distinct deformations, the computational cost of off-line FEM simulation can be reduced significantly. Our run-time deformation results are much closer to the full-scale FEM simulation with external forces applied, compared to the results of using only the modal derivative bases while the speedup over full-scale simulation is still substantial.

Approximate Bayesian network formulation for the rapid loss assessment of real-world infrastructure systems

This paper proposes to learn an approximate Bayesian network (BN) model from Monte-Carlo simulations of an infrastructure system exposed to seismic hazard. Exploiting preliminary physical simulations has the twofold benefit of building a drastically simplified BN and of predicting complex system performance metrics. While the approximate BN cannot yield exact probabilities for predictive analyses, its use in backward analyses based on evidenced variables yields promising results as a decision support tool for post-earthquake rapid response. Only a reduced set of infrastructure components, whose importance is ranked through a random forest algorithm, is selected to predict the performance of the system. Further, owing to the higher importance of evidenced nodes, the ranking method is enhanced with a recursive evidence-driven BN-building algorithm, which iteratively inserts evidenced components into the subset identified by the random forest algorithm. This approach is applied to a French road network, where only 5 to 10 components out of 58 are kept to estimate the distribution of system performance metrics that are based on traffic flow. Sensitivity studies on the number of selected components, the number of off-line simulation runs and the discretization of variables reveal that the reduced BN applied to this specific example generates trustworthy estimates.

Reconfiguration-based methodology for improving recovery performance of faults in smart grids

This paper aims to enhance the reliability and quality of service (QoS) of power smart grids by searching and applying reconfiguration oriented solutions. A novel definition of recovery performance is provided in terms of automatic recoverability and unavailability rates. The proposed approach is based on a hierarchical and distributed multi-agent system (MAS). It involves static and mobile agents, respectively, dedicated to search for new feasible reconfigurations and to identify the consumers which may play the role of feeders over smart grids. An automatic reconfiguration corresponds to the addition of a new pertinent line in a smart grid to allow further recoveries. This paper provides the implemented communication protocol for negotiating (CPN) the resources allocation which is performed by the deployed agents. The management and assignment of the energy resources are modeled as a combinatorial optimization multiple-knapsack problem (MKP) to reach a better configuration with a higher possible recovery performance rate. To decrease the cost of automatic actions, which increases the smart grid performance and reduces the costs of the human interventions, a short list of failures is identified based on proposed relations of dominance and equivalence between observed failures. Furthermore, this work investigates the effectiveness of the designed and implemented software tool for off-line assistance-design, simulation and modeling of reconfigurable smart grids. The efficiency of the proposed strategy is validated through an experimental study performed by the developed simulator.

PMU based voltage stability indices with intermediate load compensation

Wide area measurement has revolutionized the monitoring of electric power systems (EPS) which are often operated near of their stability limits. Currently, several grid operators make off-line studies of different electric system topologies to determine the voltage stability margins under different fault scenarios (loss of transmission links, loss of generation units, etc.); from these studies several decisions are taken including the disconnection of primary equipment. There are several voltage stability indices for radial electric systems that employ wide area measurement; however their major drawback is that they do not consider the intermediate load scenario in the transmission link. In this paper we propose a method to find the maximum power of a radial link between two nodes with intermediate loads and a general method to compensate loads at the receiving end that can be applied to indices that use that parameter to determine the proximity to the collapse. The performance of the compensated stability indices is evaluated by off-line simulations and it is concluded that the intermediate load compensation improves the accuracy of the indices.

Real-time characterisation of driver steering behaviour

ABSTRACTIn recent years the application of driver steering models has extended from the off-line simulation environment to autonomous vehicles research and the support of driver assistance systems. For these new environments there is a need for the model to be adaptive in real time, so the supporting vehicle systems can react to changes in the driver, their driving style, mood and skill. This paper provides a novel means to meet these needs by combining a simple driver model with a single-track vehicle handling model in a parameter estimating filter – in this case, an unscented Kalman filter. Although the steering model is simple, a motion simulator study shows it is capable of characterising a range of driving styles and may also indicate the level of skill of the driver. The resulting filter is also efficient – comfortably operating faster than real time – and it requires only steer and speed measurements from the vehicle in addition to the reference path. Adaptation of the steer model parameters is demonstrated along with robustness of the filter to errors in initial conditions, using data from five test drivers in vehicle tests carried out on the open road.Abbreviations: ADAS: advanced driver assistance systems; CG: centre of gravity; CAN: controller area network; EKF: extended Kalman filter; GPS: global positioning system; UKF: unscented Kalman filter

Real-Time System-on-Chip Emulation of Electrothermal Models for Power Electronic Devices via Hammerstein Configuration

Real-time emulation of device-level power electronics plays an essential role in many industrial applications for design and hardware-in-the-loop testing of system components and controllers. Due to the complexity and heavy computational burden of the real-time hardware implementation of the analytical and the numerical models, this paper proposes dynamic electrothermal behavioral models for diode, thyristor, and insulated-gate bipolar transistor based on the Hammerstein configuration. The power electronic device model parameters are extracted from the known device datasheets and implemented in Zynq System-on-Chip platform with accelerated processing for real-time application. An electromagnetic rail gun system has been employed as the study case to compare the performance of the proposed electrothermal behavioral models with that of off-line simulation models on SaberRD software.

USING THE SIMULATION PROGRAM FOR THE DESIGN AND OPTIMIZATION OF THE PRODUCTION LINE

Urgency of the research. Increasing productivity while maintaining sufficient production quality is one of the main crite-ria for maintaining competitiveness. An appropriate way is to automate and robotize the production process. In order for robotization to succeed, all design steps need to undergo indepth research. Target setting. The aim is to design a robotic device (robotic line) capable of increasing the production of components in a smaller workspace from 91,000 to 160,000 per year for each of the 7 types of components. Actual scientific researches and issues analysis. The introduction of robotic devices into production systems is devoted to a large part of the publication. In general, it is possible to state that the robot deployment is specific and depends on the partic-ular manufacturing process. For this reason, it is necessary to carry out a new analysis of the suitability of the robot for each manufacturing process, supported by off-line simulation. Uninvestigated parts of general matters defining. This article focuses on a specific workplace solution that uses one type of robot delivered by a parent company. The use of a different robot type with more appropriate parameters was not feasible in financial terms. The research objective. The aim is to design the most suitable placement of production machines against the position of the industrial robot. Then analyse all the robot's working moves so that it can be manipulated by one of the 7 types of component on the line, with a production increase of 483.000 pieces per year. The statement of basic materials. Simulating the production workspace in the offline environment allows you to optimize your design before it is actually created on the selected desktop. This reduces the development costs and saves the total time when the work is completed. Conclusions. The article describes the problems of design, optimization and simulation of a robot equipped workplace. For optimizing workplace was precisely defined robot type when, which limited the use of the robot from better parameters. Using the robot can increase workplace productivity while reducing the work area. With the implementation of the proposal, the target was achieved to increase workplace output by 483.000 components/year.

The design of a prototype system which controls the flow of milk in the collector’s column of an autonomous milking apparatus

The research paper presents a prototype system controlling the flow of milk in the collection column of an autonomous milking apparatus. In the Matlab®-Simulink program, the simulation model of such a system was created. Its essential operation is illustrated in the block diagrams. The logic verification of the model’s operational accuracy (off-line simulation) did not reveal errors. Therefore a laboratory stand for hardware verification – (on-line simulation) was developed. Within it a virtual feedback loop of the control system (stored in computer memory), with elements of real object control incorporated – in this way a prototype of the device was created. During the hardware verification of the proposed technical solution, operation errors were not observed. In response to certain signals from the measuring elements, the controller correctly calculated control signals for the actuators.

Methods for building ATRU real‐time model based on different application scenarios

This study introduces three methods for building an auto-transformer rectifier units (ATRU) real-time model based on different application scenarios. Real-time models run on an advanced real-time simulator that has the capability to leverage central processing units and field programming gate arrays. In the first section, the disadvantages of the off-line simulation are explained and the solution is offered through real-time simulation. In the second section, applications of real-time simulation in a more electric aircraft (MEA) electric power system will be presented. In the third section, methods to build the ATRU real-time model are illustrated based on requirements and different scenarios. Simulations are conducted to demonstrate the agreement between the results and analysis.

Design of Hardware-In-Loop Simulation Platform for Air Suspension Systems

With the development of control algorithms and structural features in the control system, the hardware-in-loop simulation technology has been widely used after unremitting research and exploration on the basis of off-line simulation. In this paper, the dSPACE real-time simulation system is used to design and develop a hardware loop simulation experiment platform for an air suspension. CarSim vehicle model and suspension control algorithms can be run in the real time. Based on the dSPACE realtime simulation platform mentioned above, a real-time monitoring interface and control program are developed to complete the test of the sliding mode control method of the 1/4 air suspension.

Physics-Based Low-Order Model for Transonic Flutter Prediction

This paper presents a physical low-order model for two-dimensional unsteady transonic airfoil flow, based on small unsteady disturbances about a known steady flow solution. This is in contrast to traditional small-disturbance theory, which assumes small disturbances about the freestream. The states of the low-order model are the flowfield’s lowest moments of vorticity and volume-source density perturbations, and their evolution equation coefficients are calibrated using off-line unsteady computational fluid dynamics simulations through dynamic mode decomposition. The resulting low-order unsteady flow model is coupled to a typical-section structural model, thus enabling prediction of transonic flutter onset for wings with moderate to high aspect ratios. The method is fast enough to permit incorporation of transonic flutter constraints in conceptual aircraft design calculations. The accuracy of this low-order model is demonstrated for forced pitching and heaving simulations of an airfoil in compressible flow. Finally, the model is used to describe the influence of compressibility on the flutter boundary, and its accuracy is demonstrated for the Isogai Case A classical flutter test case.

Real-Time Testing Approaches for Microgrids

Microgrids (MGs) are seen today as the solution to the challenge of meeting the ever-increasing demand of energy which is clean. A variety of challenges need to be overcome for these MGs to be successful varying from stability, power quality to protection, and management. Since the various control strategies are actively being researched and emerging challenges still being addressed, there has been a lot of interest related to the aspect of testing. The ever-increasing complexity of control mechanisms invokes the need for safer, faster yet reliable testing methods, which do not compromise on the degree of detail and at the same time are economical and require the minimum testing time. Off-line simulation, real-time (RT) simulation, hardware in the loop simulation, RT emulation, hardware test beds, pilot plants, and other integrated approaches are the major methods for testing in MGs. This paper gives an overview of the testing techniques and discusses the trends in the various technologies employed for testing MGs. First, the various methods are briefly discussed and a comparison is provided. Next, the various research efforts carried out on the aspect of MG testing are categorized and presented one-by-one. Furthermore, new methodologies and emerging approaches for the testing have also been highlighted, and the challenges and future research avenues have been presented.