Hardware-in-the-loop Platform Research Articles

An Optimal Switching Sequence Model Predictive Control Scheme for the 3L-NPC Converter with Output LC Filter

In some applications of microgrids and distributed generation, it is necessary to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an LC filter is usuallyconnected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltages and currents in these systems. However, these strategies have some drawbacks, particularly when multiple-input–multiple-output plants (MIMO) are controlled using single-input–single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross–coupling between different control loops and state variables. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an LC filter connected to a three-level neutral-point clamped converter. The strategy solves an optimisation problem to achieve control of the LC filter variables, i.e., currents and output voltages. Hardware-in-the-loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS–RT HIL platform and a dSPACE Microlab Box controller. In addition to the good dynamic performance of the proposed OSS–MPC, it is demonstrated using HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different operating conditions.

Transferability Assessment of OBD-Related Calibration and Validation Activities from the Vehicle to HiL Applications

With the Euro 7 pollutant emission legislation currently under discussion, advanced and more efficient exhaust aftertreatment systems are being developed. The technologies required for these are leading to an increase in the number of components and control systems requiring diagnoses strategies under the on-board diagnostics (OBD) legislation. With concurrent shorter development times and significant reductions in budgets allocated to conventional powertrain development, challenges in the field of OBD calibration and verification are already rising sharply. In response to these challenges, hardware-in-the-loop (HiL) approaches have been successfully introduced to support and replace conventional development methods. The use of complex simulation models significantly improves the quality of calibrations while minimizing the number of required prototype vehicles and test resources, thus reducing development costs. This paper presents a feasibility study for moving OBD-related calibration and validation tasks from the vehicle to a HiL platform. In this context, the calibration and verification process of an active diagnostic for monitoring the condition of the three-way catalyst (TWC) and the oxygen sensors in the exhaust aftertreatment system is presented. It is shown that all relevant signals are simulated with sufficient accuracy to ensure a robust transfer from the vehicle to a HiL test bench. Special attention is given to the simulation of aged components and their influence on the emission behavior of the system. Furthermore, it is discussed that transferring OBD tasks from the vehicle to the HiL test bench could result in significant savings in development time and a reduction in the number of physical prototype vehicles and test resources required.

Compensation Method for Current Measurement Errors in the Synchronous Reference Frame of a Small-Sized Surface Vehicle Propulsion Motor

This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as the current harmonic extractor and the compensator, respectively. It can compensate for the dq-axes offset and scaling errors simultaneously, improving phase current distortion while reducing the ripples of motor speed and torque. Compared to the traditional motor model-based compensation strategies, the proposed method is robust against the changes in motor parameters with the online adaptive capability of the ADALINE algorithm. Furthermore, due to the good real-time performance of SOGIs and ADALINEs, the proposed compensation strategy can effectively operate in both the steady state and transient state of the motor. Finally, the effectiveness of the proposed method is verified through the physical and hardware-in-the-loop (HIL) experiments. After compensating for the current measurement errors of a 1 kW test motor with the propeller-characteristics load, the torque ripple and speed ripple are reduced by more than 65% and 80%, respectively. At the same time, the DC component and the second-order and third-order harmonics in the phase currents are also significantly reduced. Similar test results can be also obtained on the HIL platform with a 100 kW permanent magnet motor.

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.

An open circuit fault-tolerant seven-level inverter with symmetric sources and reduced switch count

In this study, a new structure of symmetrical multilevel inverter is proposed. The proposed structure offers fewer controlled switches, power diodes, DC sources voltage stress across switches and losses compared with classical and a few recently proposed topologies in the literature. This paper presents a fault-tolerant (FT) seven-level inverter to provide uninterrupted supply to the connected load under open circuit fault in any single switch of the presented configuration. This configuration uses only six unidirectional and one bidirectional switch for any switch fault-tolerant operation. The phase opposition disposition sinusoidal pulse width modulation (POD-SPWM) and phase disposition sinusoidal pulse-width modulation (PD-SPWM) scheme are used for proper DC link utilisation in seven-level output voltage. The proposed symmetrical 7-level topology requires fewer power components and offers reduced voltage total harmonic distortion (THD) compared to other multi-level inverter (MLI) topologies. This MLI is investigated in MATLAB and validated using hardware in the loop platform of OPAL-RT. The obtained results are presented to demonstrate the successful FT operation under any single switch open circuit fault.

Fault Diagnosis and Fault‐Tolerant Control Method for a Multistack Fuel Cell Thermal Management Subsystem

Multistack fuel cell systems (MFCS) are promising developments of fuel cell technology. For MFCS, faults affect durability and stability, and appropriate fault diagnosis methods and control strategies need to be proposed for different multistack structures. Herein, the integrated MFCS thermal management subsystem (TMS), which is based on the optimized split‐stack approach, is first studied, and its possible sensor and actuator faults are analyzed. The sensor fault signal is corrected based on the unscented Kalman filter (UKF), the controller design under the hardware in the loop platform is carried out, and an active fault‐tolerant control (FTC) strategy based on sliding mode control is deployed for the TMS to enable it to recover its performance quickly and effectively in case of faults. The results show that the estimated values are closer to the true values after using the UKF on the sensor signals, avoiding the impact of sensor faults on the system performance. Under New European Driving Cycle dynamic conditions, the FTC controller also exhibits better control compared to the conventional proportional–integral controller, with smaller maximum overshoot and shorter system recovery and stabilization time in the event of a TMS fault, mitigating the impact of system fault on performance.

GRU-Based Denoising Autoencoder for Detection and Clustering of Unknown Single and Concurrent Faults during System Integration Testing of Automotive Software Systems.

Recently, remarkable successes have been achieved in the quality assurance of automotive software systems (ASSs) through the utilization of real-time hardware-in-the-loop (HIL) simulation. Based on the HIL platform, safe, flexible and reliable realistic simulation during the system development process can be enabled. However, notwithstanding the test automation capability, large amounts of recordings data are generated as a result of HIL test executions. Expert knowledge-based approaches to analyze the generated recordings, with the aim of detecting and identifying the faults, are costly in terms of time, effort and difficulty. Therefore, in this study, a novel deep learning-based methodology is proposed so that the faults of automotive sensor signals can be efficiently and automatically detected and identified without human intervention. Concretely, a hybrid GRU-based denoising autoencoder (GRU-based DAE) model with the k-means algorithm is developed for the fault-detection and clustering problem in sequential data. By doing so, based on the real-time historical data, not only individual faults but also unknown simultaneous faults under noisy conditions can be accurately detected and clustered. The applicability and advantages of the proposed method for the HIL testing process are demonstrated by two automotive case studies. To be specific, a high-fidelity gasoline engine and vehicle dynamic system along with an entire vehicle model are considered to verify the performance of the proposed model. The superiority of the proposed architecture compared to other autoencoder variants is presented in the results in terms of reconstruction error under several noise levels. The validation results indicate that the proposed model can perform high detection and clustering accuracy of unknown faults compared to stand-alone techniques.

A H‐type architecture for electric/hybrid‐electric aircraft propulsion systems

AbstractIn this paper, an H‐type electric/hybrid electric aircraft propulsion architecture is proposed to address the issues associated with the radial electric propulsion architecture. In a radial architecture, a fault on the main bus or failure of the generator leads to shut down of all the propulsion motors in that channel, thus increasing the burden on the remaining motors to maintain the power required by the aeroplane. As a result, it is necessary to oversize the motors for the purpose of compensating for the loss of other motors. To mitigate these issues, a new H‐type architecture is introduced to isolate the particular faulty section while still maintaining power flow to the remaining healthy motors. The proposed architecture minimises the oversizing of various components in the system as compared to radial propulsion architecture. The sizing of components and the amount of overall mass reduction is discussed by using the proposed architecture. Typhoon Hardware in the Loop platform is used to validate the performance of both the architectures for faults at different locations, and the results are presented.

Intelligent Fault Detection and Classification Based on Hybrid Deep Learning Methods for Hardware-in-the-Loop Test of Automotive Software Systems.

Hardware-in-the-Loop (HIL) has been recommended by ISO 26262 as an essential test bench for determining the safety and reliability characteristics of automotive software systems (ASSs). However, due to the complexity and the huge amount of data recorded by the HIL platform during the testing process, the conventional data analysis methods used for detecting and classifying faults based on the human expert are not realizable. Therefore, the development of effective means based on the historical data set is required to analyze the records of the testing process in an efficient manner. Even though data-driven fault diagnosis is superior to other approaches, selecting the appropriate technique from the wide range of Deep Learning (DL) techniques is challenging. Moreover, the training data containing the automotive faults are rare and considered highly confidential by the automotive industry. Using hybrid DL techniques, this study proposes a novel intelligent fault detection and classification (FDC) model to be utilized during the V-cycle development process, i.e., the system integration testing phase. To this end, an HIL-based real-time fault injection framework is used to generate faulty data without altering the original system model. In addition, a combination of the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) is employed to build the model structure. In this study, eight types of sensor faults are considered to cover the most common potential faults in the signals of ASSs. As a case study, a gasoline engine system model is used to demonstrate the capabilities and advantages of the proposed method and to verify the performance of the model. The results prove that the proposed method shows better detection and classification performance compared to other standalone DL methods. Specifically, the overall detection accuracies of the proposed structure in terms of precision, recall and F1-score are 98.86%, 98.90% and 98.88%, respectively. For classification, the experimental results also demonstrate the superiority under unseen test data with an average accuracy of 98.8%.

Maneuver control at high angle of attack based on real-time optimization of integrated aero-propulsion

To reduce the propulsion system installation thrust loss under high angle of attack maneuvering, a control method based on real-time optimization of the integrated aero-propulsion is proposed. Firstly, based on data fitting and physical principle, an integrated onboard model of propulsion system is established, which can calculate various performance parameters of the propulsion system in real time, and has high accuracy and real-time performance. Secondly, to improve the compatibility of optimization real-time performance and search accuracy, the online optimization control of aero-propulsion system is realized based on an improved trust region algorithm. Finally, by controlling the auxiliary intake valve, a good match between inlet and engine is realized, which solves the problems of intake flow reducing and total pressure recovery coefficient declining, and improves the installation performance of propulsion system. The simulation results indicate that, compared with the conventional independent engine control, the real-time integrated optimization method reduces the installed thrust loss by 3.61% under the design condition, and 4.58% under the off-design condition. Furthermore, the simulation on HIL (Hardware-In-the-Loop) platform verifies the real-time performance of integrated optimization method.

Interval-Valued Invehicular Latency Characterization for Risk/Fault Management Purposes

Guaranteeing the reliability of Intelligent Transportation Systems (ITSs) is an overlapping issue. Not only the in-road risks must be mastered, but also the internal threats that emerge from the ITS material aspects should be addressed carefully. Most of the safety verification solutions ignore the limitations issued from the ITS onboard embedded structure, such as the invehicular communication delays. In this work, a novel Response Time Analysis (RTA) method is introduced to bridge the gap between the risk/failure management issues and the material aspects (the invehicular communication delays in particular) for ITSs. Aside of its simplicity, the suggested RTA reveals all potential latency scenarios by returning an interval estimation of delays. The interval results enclose certainly the exact delay that may occur in runtime. As a proof of concept of the introduced RTA algorithm, the Hardware-in-the-Loop (HIL) validation technique is adopted. The HIL platform is realized thanks to a model of a modern industrial automotive system. The validation work proves the consistency and efficiency of the proposed RTA solution to ensure ITS safety assurance.

Hardware in the Loop Real-time Simulation of Doubly Fed Off-grid Wind Power System

Hardware in the Loop (HIL) semi-physical real-time simulation can shorten the research period and complete the harsh working condition test, which is difficult to be carried out on the physical platform. Taking the off-grid Doubly Fed Induction Generator (DFIG) wind power system as the research object, this paper proposes the bottom modelling method of HIL real-time simulation. Using the Hardware Description Language VERILOG, the bottom real-time models of DFIG, converter and load are designed on Field Programmable Gate Array (FPGA), connected with the real controller, and the HIL real-time simulation platform is constructed. The experiments of conventional working conditions and unbalance load are carried out on the HIL platform and the physical platform. The operation speed of the HIL platform reaches 0.48μs. Compared with the physical platform, the error of HIL platform is between 1.17 ~ 3.29% under various working conditions.

Power Sharing Control in a Grid-Tied DC Microgrid: Controller Hardware in the Loop Validation

This article presents the development of a low-cost control hardware in the loop platform for the validation and analysis of controllers used for the management of power sharing between the main grid and a DC microgrid. The platform is made up of two parts: a main grid interconnection system emulator (MGISE) and a controller under test (CUT). The MGISE operates on a 260 V DC bus and includes a 1000 W photovoltaic array, a DC variable load and a single H full bridge converter (HFBC). The CUT includes a phase locked loop and a main cascade control structure composed of two PI controllers. Both the MGISE and the CUT were embedded on an NI myRIO-1900 development board and programmed using LabVIEW virtual instrumentation software. These devices communicate with each other using analog signals representing the AC side current, the DC side voltage, and the HFBC control signal. The MGISE operates with an integration time of 6 µs and its performance is validated by comparing it with a simulation in PSIM. The integration time of the MGISE, the development boards used, as well as its programming environment, and the results obtained from the comparison with PSIM simulation, show that the proposed platform is useful for the validation of controllers for power sharing, with a simple implementation process compared to other hardware description methods and with a low-cost platform.

Operation of the Microgrid with Improved Droop Control Strategy and an Effective Islanding Detection Technique for Automatic Mode Switching

This paper presents the islanding detection and automatic mode switching for inverter-based distributed generation sources (DGs) in the microgrid with an improved droop controlled scheme. The modification in the conventional droop among the DGs is contrived to share the load proportionate to their power capacity. And to reduce the circulating currents and to improve reactive power-sharing the virtual impedance is implemented for the microgrid in the stand-alone mode operation. Also, the modified Park synchronous reference frame based phase-locked loop (PSRF-PLL) is implemented for the operation of the microgrid in the grid-connected mode. The islanding detection and automatic mode switching depend on the PSRF-PLL, which uses the input obtained from the stationary reference frame. The proposed PLL implemented in this work is simple in construction and keeps the phase locking error to near zero, thus leading to proper locking with reduced complexity. The control scheme's performance in the microgrid is validated using the real time hardware in the loop platform. The performance of PSRF-PLL based islanding detection scheme is analyzed considering the various grid disturbances, and the comparative study with the other PLL based scheme is also presented in this paper to show the improved performance of the proposed PSRF-PLL scheme.

Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms

The combination of different propulsion and energy storage systems for hybrid vehicles is changing the focus in the field of powertrain calibration. Shorter time-to-market as well as stricter legal requirements regarding the validation of Real Driving Emissions (RDE) require the adaptation of current procedures and the implementation of new technologies in the powertrain development process. In order to achieve highest efficiencies and lowest pollutant emissions at the same time, the layout and calibration of the control strategies for the powertrain and the exhaust gas aftertreatment system must be precisely matched. An optimal operating strategy must take into account possible trade-offs in fuel consumption and emission levels, both under highly dynamic engine operation and under extended environmental operating conditions. To achieve this with a high degree of statistical certainty, the combination of advanced methods and the use of virtual test benches offers significant potential. An approach for such a combination is presented in this paper. Together with a Hardware-in-the-Loop (HiL) test bench, the novel methodology enables a targeted calibration process, specifically designed to address calibration challenges of hybridized powertrains. Virtual tests executed on a HiL test bench are used to efficiently generate data characterizing the behavior of the system under various conditions with a statistically based evaluation identifying white spots in measurement data, used for calibration and emission validation. In addition, critical sequences are identified in terms of emission intensity, fuel consumption or component conditions. Dedicated test scenarios are generated and applied on the HiL test bench, which take into account the state of the system and are adjusted depending on it. The example of one emission calibration use case is used to illustrate the benefits of using a HiL platform, which achieves approximately 20% reduction in calibration time by only showing differences of less than 2% for fuel consumption and emission levels compared to real vehicle tests.

Development of an integrated platform for hardware-in-the-loop evaluation of microgrids prior to site commissioning

This paper presents an integrated hardware-in-the-loop (HIL) platform for testing the operation and control of a real-world microgrid system prior to site commissioning. The proposed testing approach shows the value of setting up an integrated HIL platform to test multiple hardware devices (including the system-level controller, device controllers, and field devices). A test bed developed for the Borrego Springs community microgrid is used as an example to demonstrate the feasibility of the integrated platform. Comprehensive tests are carried out using the Borrego Springs test bed to validate the platform, meet the test objectives, and gain valuable insight prior to site commissioning. The selected test scenarios, initial conditions, events, test metrics, etc., are similar to those defined in IEEE P2030.8. The test objectives are to evaluate the microgrid controller and the operation of the microgrid. The HIL platform presented in this paper shows good value for microgrid testing in terms of its flexibility and scalability for testing various microgrids; its accuracy in its representation of the field; the comprehensiveness of the testing capability; and the efficiency of testing, which can reduce risks prior to field deployment.

Low-Frequency Stability Analysis of Vehicle-Grid System With Active Power Filter Based on dq-Frame Impedance

To eliminate the low-frequency oscillation (LFO) phenomenon in the vehicle-grid system of high-speed railways, a single-phase cascaded H-bridge multilevel active power filter (APF) directly accessed to the 27.5-kV traction network is proposed in this article, which can provide the dynamic reactive and interharmonic compensation. To explore the mechanism of APF on LFO suppression, the dq-frame impedance model of vehicle-grid system with APF is established first. The impact of the second-order generalized integrator model and the duty ratio model on the impedance accuracy is discussed in detail. Then, based on the generalized Nyquist stability criterion and system power consumption criterion, the stability of vehicle-grid system and its sensitivity to parameters in different cases are compared. The results indicate that the proposed APF can significantly improve the low-frequency stability of vehicle-grid system and owns much better performance than the STATCOM proposed in previous literatures. Finally, the time-domain simulations in MATLAB and the experiments on the controller hardware in the loop platform are implemented, which further validate the accuracy of theoretical analysis and the superior performance of APF in LFO elimination.

Hardware-in-the-Loop Validation of Different Power Train Topologies’ Models in Electric Vehicles: A Plug-and-Play Capability

This study presents a novel modelling methodology for electric vehicle power train. This covers both Front Wheel and all-wheel drives. The simulation is built in PSIM and verified in Typhoon's hardware in the loop (HIL) solution. HIL technology is used for real time verification. The approach is highly attractive due to characteristics of rapid prototyping which allows quick and easy adjustment in simulation in real time. Thus, avoiding the high costs associated with physical prototypes. The paper presents results (dynamic responses of various vehicle components) and the effects of adjusting various vehicle parameters. The results obtained from simulation is successfully verified in the HIL platform. The result from this study proves the robustness of the simulation and HIL model and control algorithms. This methodology saves costs and lead time to build and design a physical hardware. Additionally, the results from the modeled vehicles agree with data provided by the manufacturer. Finally, the design is simulated in a modular way such that they can be used for various propulsion setups and schemes

Hardware in the Loop Platform for Testing Photovoltaic System Control

The hardware in the loop (HIL) technique allows you to reproduce the behavior of a dynamic system or part of it in real time. This quality makes HIL a useful tool in the controller validation process and is widely used in multiple areas including photovoltaic systems (PVSs). This study presents the development of an HIL system to emulate the behavior of a PVS that includes a photovoltaic panel (PVP) and a DC-DC boost converter connected in series. The emulator was embedded into an NI-myRIO development board that operates with an integration time of 10 µs and reproduces the behavior of the real system with a mean percent error of 2.0478%, compared to simulation results. The implemented emulator is proposed as a platform for the validation of control systems. With it, the experimental stage is carried out on two controllers connected to the PVS without having the real system and allowing to emulate different operating conditions. The first controller is based on the Hill Climbing algorithm for the maximum power point tracking (MPPT), the second is a proportional integral (PI) controller for voltage control. Both controllers generate settling times of less than 3 s; the MPPT controller generates variations in the output in steady state inherent to the algorithm used. For both cases, the comparison of the experimental results with those obtained through software simulation show that the platform fulfills its usefulness when evaluating control systems.

Design and implementation of a wideband channel emulation platform for 5G mmWave vehicular communication

In this study, the authors design and implement a real-time hardware-in-the-loop (HIL) wideband high-velocity channel emulation platform for the performance evaluation and verification of 5G mmWave systems. A novel spectral splitting & stitching method and channel partitioning algorithm are developed to synchronously combine up to eight 160 MHz sub-channels. The HIL platform was calibrated in the time and frequency domains and then validated using back-to-back results from a pair of experimental 60 GHz mmWave modems. The emulated path loss was generated for an additive white Gaussian noise channel to characterise the data throughput versus signal-to-noise ratio for a fixed point-to-point deployment. The wideband emulator was then used to introduce the Doppler shifts and spreads observed in a high velocity (up to 600 km/h) mmWave channel. For a Ricean channel (K-factor greater than or equal to 10 dB), negligible data throughput losses were observed for velocities up to 293.9 km/h. Using the emulator, they show that the 5G modems can achieve continuous connectivity (albeit with some throughput loss) at velocities up to 587.8 km/h. Tests were also conducted in Rayleigh channels with uniformly distributed spatial multipath. In the Rayleigh case, the maximum vehicular velocity dropped to 51.4 km/h.