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Aircraft ground braking control is a complex time-varying dynamic problem, especially when there are unexpected disturbances from lateral wind or visual error. Therefore, under some extreme conditions, it is hard for the pilot to control aircraft braking as well as usual without assistant control. This paper solves this problem by proposing a novel assistant control for aircraft ground braking, mainly based on the pilot control model and the LPV theory. And in order to reflect the control characteristics of the pilot, the sensory and control-theoretic model were combined together for controller designing. To test the performance of proposed control method, a real time pilot-in-loop simulation system is constructed. According to experiment results, the proposed assistant control shows better performance than pilot control, for it not only help the pilot to resist disturbance, but also hardly run counter to the pilot’s intent.

This paper investigates the response to grid disturbances of the wind energy conversion system based on the doubly fed induction generator (DFIG-based WECS). It is proposed a new control termed as heightened state-feedback control structure (HSFC) with predictive behavior to regulate the rotor current loops, which is able to effectively counteract the back electromotive force surge oscillating dynamics that occur in the event of a disturbance in the grid voltage. The proposed method is able to mitigate oscillations in DFIG currents exempting the need to use low voltage ride-through current-modify (LVRT-CM) strategies during intermediate symmetrical and asymmetrical voltage sags or during the voltage recovery process, while provide the DFIG to contribute active and reactive current featuring bounded torque oscillations. During severe faults, the proposed structure is able to effectively track the required post-fault rotor current references as demanded by LVRT-CM, which allows the DFIG to ride-through the fault with constrained currents and torque. The proposed structure also employs a novel flux damping technique which accentuate the rotor d-axis current in order to significantly reduce stator flux settling time after faults, while the torque minimally oscillates during post-fault recovery. Real-time digital simulations and experimental results considering symmetrical and asymmetrical voltage sags due to faults show the proposed solutions advantages over classical and previous strategies.

Sharing of hardware and software facilities together with knowledge and expertise among laboratories is a key point in research. In the power systems field this is possible even remotely by coupling real-time simulators located in different laboratories. In this paper an experimental test-bed is described. It consists of the remote interconnection of the realtime simulators, located at Politecnico di Torino and Politecnico di Bari respectively, in order to perform Remote Power Hardware-in-the-Loop experiments. The possibilities and limitations of this type of co-simulation are described and a case study is presented.

The real time simulation is a key tool for the implementation of monitoring and diagnostic methods as well as of model-based control strategies in modern photovoltaic systems. Under the hypothesis that all the cells of the photovoltaic array operate in the same temperature and irradiance conditions and have the same degradation level, the values of the parameters appearing in the single diode equivalent circuit referred to one cell are scaled up to the whole array, so that the simulation is not computationally demanding at all. Unfortunately, when mismatching effects have to be taken into account, including partial shadowing phenomena and uneven degradation of the cells, the simulation is not as straightforward as in the previous case. A numerical method, which has been recently presented in literature, allows to simulate a large mismatched photovoltaic array with a low computational effort. It exploits a suitable formulation of the non linear system of equations leading to an inverse Jacobian matrix formulated explicitly. In this paper it is shown the process for engineering such a numerical method by using a low cost system-on-chip device available on the market. The analysis presented shows the critical aspects of the implementation, if the computing time has to be minimized for real-time simulation purposes. The advantages offered by the system-on-chip are explored in order to deploy in the best way the algorithm functions on the ARM processor and on the FPGA available therein. Implementation results show the performance of the proposed approach, especially in terms of computation time and use of resources.

Microgrids today include more and more renewable sources both for environmental and economic reasons. The advantage of microgrids is their capacity of running isolated. The presence of largely uncontrollable sources (PV plants and wind farms) makes the grid control a complex task. During the design stage it is mandatory to consider the expected variations of both loads and sources to identify proper solution for stabilizing the Microgrid when it runs isolated. The paper presents a simulator that was developed to support the design of the Microgrid both in terms of power devices and control techniques. The main goal of this simulator is to test the automation system of the Microgrid before its site installation. The simulator calculates the dynamic behavior of conventional generators, renewable source, and loads. The model of renewable sources includes the expected power variations as well as the random profile of loads. If required, energy storage systems can be integrated in the simulator. All the control set-point of controllable equipment and the calculated frequency and voltage of the Microgrid are interfaced with the control system using a standard Ethernet-base fieldbus. Such a solution makes it possible to study different control logics and to tune the control parameters of the system using the real control system. The data exchange between the simulator and the control system is identical to the real data flow that will be found in the Microgrid. With the use of the simulator, the control system of the Microgrid is implemented during the design stage, with reduced development, testing, and commissioning times.

International audience; The paper describes the development of a power converter small scale mock-up and a real time model of an offshore wind farm. A Power Hardware In-the-Loop validation is proposed for a demonstration of grid architecture and control principles. The paper presents the design methodology of the PHIL test bench and underlines the contribution of PHIL in the design flow of power converter development for DC grid application. Experimental results of preliminary PHIL tests are presented.

The installation of facilities replicating the realworld condition is often required for carrying out meaningful tests on new devices and for collecting data with the aim to create realistic device model. However, these facilities require huge investments, as well as areas where they can be properly installed. In this paper, we present a test infrastructure exploiting the concept of Remote Power Hardware-In-the-Loop (RPHIL), applied for characterizing the performances of a 8kW Proton Exchange Membrane (PEM) electrolyser installed at the Hanze University of Applied Sciences in Groningen (The Netherlands). The electrolyser is subjected to different test conditions imposed both locally and remotely. The results show that this measurement procedure is effective and can open new perspectives in the way to share and exploit the existing research infrastructure in Europe.

We derive reduced models (RM) of NH3-SCR automotive converters as a strategy to provide accurate simulations with minimized computational costs, in view of applications to the rapid calibration of SCR kinetics and to on-board control of the engine after-treatment systems. In the first part of this work, a reduced model of SCR monolithic catalysts is developed. To decrease the computational effort, a combination of explicit Euler methods for ODEs integration in time and backwards finite differences for discretization of space derivatives is implemented, adopting a simplified approach to calculate the region of stability of the explicit method. In the second part, we compare the reduced model with a reference, fully detailed SCR monolith converter model in terms of accuracy and computational costs for different engine test cycles, comprising cold start transients, for both light- and heavy-duty diesel engines. The tests demonstrate a decrease in the computational time for RM with respect to the reference full model by one to two orders of magnitude, while retaining a comparable accuracy.

This article presents the simulation of a BLDC motor and its closed control system in FPGA. The simulation is based on a mathematical model of the motor, including the electromagnetic torque, phase currents, back electromotive force, etc. In order to ensure calculation precision, the equations describing the motor were solved using a floating point representation of real numbers, and a small step of numerical calculations of 1 μs was assumed. The time step selection methodology has been discussed in detail. The motor model was executed with the use of Textual Programming Languages (with HDL codes).

Real-time simulation (RT) is very useful for rapid prototyping of complex and expensive systems using the high performance of a multiprocessor system. It has many applications in the field of testing controllers and protection systems under real conditions. In this article, Real-time simulations results of sensorless control of permanent magnet synchronous motor (PMSM) are presented. This simulator consists of two major subsystems, software with a Matlab / Simulink and hardware including FPGA boards for data acquisition, control boards and sensors. The two subsystems were coordinated together to achieve the simulation RT. To estimate the rotor position, a sliding mode observer (SMO) based on back emfs of the motor was implemented. The stability of the proposed method was verified using the concept of Lyapunov. A real-time system based on FPGA, is used for implementing and testing the algorithm for rotor position estimation based on back-emf tracking.

A FPGA-based dynamic model of three-phase induction machines is presented in this work. The model includes the effects of temperature in the stator and rotor resistances and magnetic saturation in the magnetizing and leakage inductances, according to the stator and rotor currents. Moreover, iron core losses have been properly modeled. The proposed implementation ensures high accuracy of the simulations in a wide range of operating conditions, keeping a reasonable computational burden. Experimental tests confirm the matching between the results provided by the hardware in the loop system and those coming from the experimental rig, the last including an electronic control unit used in automotive systems.

To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform.

In this paper are presented FPGA-based models of IGBT power converters for hardware in the loop systems. The analytical model of each single power device is straightforwardly obtained from technical specifications. The proposed approach can be considered a viable solution featuring minimal modeling complexity and thus reduced computational efforts, still maintaining high accuracy. The main target is to provide an easy model plant for testing electric drive configurations and control strategies, fault tolerant drives, and so on. The Field-Programmable Gate Arrays (FPGA)-based real-time models have been used to simulate a step down dc-dc converter and a 10kW three-phase inverter for automotive applications. The results carried out using the hardware in the loop system are in good agreement with that obtained from off-line numerical simulations and experimental tests.

International audience; Composites manufacturing processes usually involve multiscale models in both space and time, highly non-linear and anisotropic behaviors, strongly coupled multiphysics and complex geometries. In this framework, the use of simulation for real-time decision making directly in the manufacturing facility is still precluded nowadays, in spite of the impressive progresses reached in numerical analysis and computer science during the last decade. In this paper, a process-specific simulation tool based on reduced order modeling is introduced, the Simulation App. This concept is presented through a practical case involving a multi-physics and coupled problem describing the manufacturing process of a composite outlet guide vane. We show that several manufacturing settings can be simulated in few seconds with the Simulation App, thus enabling fast process optimization. Finally, the advantages over general-purpose simulation software, in the context of process simulation, are discussed.

This study aims to construct a reduced thermodynamic cycle model with high accuracy and high model execution speed based on artificial neural network training for real-time numerical analysis. This paper proposes a method of constructing a fast average-value model by combining a 1D plant model and exhaust gas recirculation (EGR) control logic. The combustion model of the detailed model uses a direct-injection diesel multi-pulse (DI-pulse) method similar to diesel combustion characteristics. The DI-pulse combustion method divides the volume of the cylinder into three zones, predicting combustion- and emission-related variables, and each combustion step comprises different correction variables. This detailed model is estimated to be within 5% of the reference engine test results. To reduce the analysis time while maintaining the accuracy of engine performance prediction, the cylinder volumetric efficiency and the exhaust gas temperature were predicted using an artificial neural network. Owing to the lack of input variables in the training of artificial neural networks, it was not possible to predict the 0.6–0.7 range for volumetric efficiency and the 1000–1200 K range for exhaust gas temperature. This is because the mean value model changes the fuel injection method from the common rail fuel injection mode to the single injection mode in the model reduction process and changes the in-cylinder combustion according to the injection timing of the fuel amount injected. In addition, the mean value model combined with EGR logic, i.e., the single-input single-output (SISO) coupled mean value model, verifies the accuracy and responsiveness of the EGR control logic model through a step-transient process. By comparing the engine performance results of the SISO coupled mean value model with those of the mean value model, it is observed that the SISO coupled mean value model achieves the desired target EGR rate within 10 s. The EGR rate is predicted to be similar to the response of volumetric efficiency. This process intuitively predicted the main performance parameters of the engine model through artificial neural networks.

In order to systematically shift existing control and management paradigms in distribution systems to new interoperable communication supported schemes in smart grids, we need to map newly developed use cases to standard reference models like Smart Grid Architecture Model (SGAM). From the other side, any new use cases should be tested and validated ex-ante before being deployed in the real-world system. Considering various types of actors in smart grids, use cases are usually tested using co-simulation platforms. Currently, there is no efficient co-simulation platform which supports interoperability analysis based on SGAM. In this paper, we present our developed test platform which offers a support to design new use cases based on SGAM. We used this platform to develop a new scheme for wide area monitoring of existing distribution systems under growing penetration of Photovoltaic production. Off-the-shelf solutions of state estimation for wide area monitoring are either used for passive distribution grids or applied to the active networks with wide measurement of distributed generators. Our proposed distribution state estimation algorithm does not require wide area measurements and relies on the data provided by a PV simulator we developed. This practical scheme is tested experimentally on a realistic urban distribution grid. The monitoring results shows a very low error rate of about 1 % by using our PV simulator under high penetration of PV with about 30 % error of load forecast. Using our SGAM-based platform, we could propose and examine an Internet-of-Things-based infrastructure to deploy the use case.

Loads monitoring is of central interest for both aircraft manufacturers and operators. The proper monitoring approach can represent the success or failure of a new aircraft design as well as the economic growth of air carriers. This paper introduces the development of a rigid-body multipoint loads model based on flight test data using System-Identification in time domain. Several strain sensors were calibrated to enable local loads measurements. Direct loads measurements at different positions of the aircraft structure were used to extend the typical set of observation variables, in order to enable the prediction of local aerodynamic loads by this model. For this purpose specific flight test maneuvers covering low frequency inputs at different airspeeds were performed. The test platform is a high-performance sailplane equipped with special flight test instrumentation, in order to allow the modeling of the multipoint loads model at several aircraft load stations. The main contribution of this work is the extension of the conventional System-Identification approach for enabling the simulation of local loads in real time. In this context, the multipoint model structure is outlined and a host of results from the identification of a rigid-body seven-point loads model is presented.

The operation of a ROV requires significant off-shore dedicated manpower to handle and operate the robotic platform. In order to reduce the burden of operations, DexROV proposes to work out more cost effective and time efficient ROV operations, where manned support is in a large extent delocalized onshore (i.e. from a ROV control center), possibly at a large distance from the actual operations, relying on satellite communications. The proposed scheme makes provision for advanced dexterous manipulation capabilities, exploiting human expertise from a remote location when deemed useful. The outcomes of the project will be integrated and evaluated in a series of tests and evaluation campaigns, culminating with a realistic deep sea (1,300 meters) trial. After one year, the project specified the system architecture of the system and carried out preliminary technological trade-offs for the subsystems.

This paper describes a new modeling and simulation approach in order to enhance the diagnosis ability of an electronic embedded system, including in the automotive field. Our modeling approach integrates the hardware specifications to the functional model in order to establish better system observation. It is based on hardware/software (HW/SW) co- modeling with multilevel of granularity. To reach this objective, we have set up a relationship between the desired diagnosis accuracy and the level of granularity of the HW/SW co-model, for every Electronic Computing Unit (ECU). Our contribution allows the attribution of the right co-simulation hierarchical level by attributing the right simulation accuracy, for each function under observation.

Low Frequency AC Transmission (LFAC) at 16.7 Hz is seen by many as a realistic cost effective alternative to VSC-HVDC for the interconnection of offshore wind. The implementation of the LFAC transmission system envisaged in this work requires the use of full conversion wind turbines which output power to a 16.7 Hz collection network, which requires some redesign of the back to back converter typically used in such turbines. This paper presents the real time scaled hardware emulation of a full conversion wind turbine connected to a 16.7 Hz grid. The study concentrates on both software control strategies for the converters, highlighting the performance of the generator for the export of power to the grid. The LFAC grid side PLL (Phase Locked Loop) is also introduced – synchronizing with the imposed 16.7 Hz. An emulation test bed is built and demonstrated in hardware - with the system successfully exporting power to the LFAC grid. This contribution highlights the ability to design a wind turbine network offshore to interface to an LFAC transmission system.

Underwater inspection and maintenance (e.g. in the oil & gas industry) are demanding and costly activities for which ROV based setups are often deployed in addition or in substitution to deep divers - contributing to operations risks and costs cutting. However the operation of a ROV requires significant off-shore dedicated manpower to handle and operate the robotic platform. In order to reduce the burden of operations, DexROV proposes to work out more cost effective and time efficient ROV operations, where manned support is in a large extent delocalized onshore (i.e. from a ROV control center), possibly at a large distance from the actual operations, relying on satellite communications. The proposed scheme also makes provision for advanced dexterous manipulation capabilities, exploiting human expertise when deemed useful. The outcomes of the project will be integrated and evaluated in a series of tests and evaluation campaigns, culminating with a realistic deep sea (1,300 meters) trial.