Hardware In Loop Testing Research Articles

A state‐space average model of a three‐level PV inverter for transient short‐circuit currents analysis

AbstractThis paper presents a state‐space average model of a three‐level photovoltaic (PV) inverter to understand short‐circuit currents transient characteristics. Analytical solution of the model is also derived. The proposed model is validated with PV system controller hardware in‐loop (HIL) test method. The errors between simulation and HIL tests results under various conditions are evaluated, testifying the validity of the proposed model. With the model and analytical solution, the decaying time constants of sub‐transient and transient processes are derived, which shows that the time constants of a three‐level PV inverter are not fixed and they vary with voltage dips. The analytical expression of short‐circuit currents is also formulated. The findings from this study are essential to short‐circuit current calculations of a power grid with large‐scale PV plants, coordination of power system protections, and grid planning.

Integrated Active Suspension and Anti-Lock Braking Control for Four-Wheel-Independent-Drive Electric Vehicles

This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system (ASS) and anti-lock braking system (ABS). First, a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model. Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed. An ASS-ABS integrated control system is proposed, utilizing an H∞ controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation. Finally, the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop (HIL) test platform. The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

A fast and high‐accurate commutation failure identification method for LCC‐HVDC system

AbstractCommutation failure (CF) is one of the most common issues in line‐commuted converter‐based high voltage direct current systems (LCC‐HVDC), leading to critical power system security and stability problems. Accurate and rapid identification of CF is crucial to prevent subsequent CF in HVDC systems. However, the existing CF identification methods are lack of the required accuracy and speed. The relationship between bridge arm current, commutation voltage, and trigger pulse based on the commutation progress mechanism after the AC fault is analysed in this paper. A novel CF identification method is presented, which utilises the CF identification factor, enabling fast and high‐accurate identification without relying on the value of the extinction angle. The proposed method offers a simpler and more efficient implementation in engineering practice. Finally, the effectiveness of the proposed method is verified in both the standard International Council on Large Electric systems HVDC model and the Hardware in Loop test using practical project parameters. The results demonstrate that the proposed method can accurately and fast identify CF.

A review on hardware in loop testing for various SAE levels of autonomous vehicle subsystems

A review on hardware in loop testing for various SAE levels of autonomous vehicle subsystems

SIMULATING ELECTRIC VEHICLE DRIVING CYCLES WITH A HARDWARE-IN-LOOP (HIL) SYSTEM

Electric vehicles (EVs) are gaining attention as a promising solution to reduce greenhouse gas emissions. This paper proposes system architecture of a Hardware-In-Loop (HIL) system to explore simulating the electric vehicle (EV) driving cycles using HIL testing approach. The HIL system uses an Arduino DUE as the controller, connecting MATLAB Simulink to an RC Car acting as the EV. It employs an L298N motor driver, B25, and ACS712 sensors to measure voltage and current behavior from an 11.1V 4200mAh Lithium-Ion battery. Simulink's GUI allows users to select desired driving cycles for simulation. Results show that the voltage decreases with speed, while the current increases as expected across various driving cycles (NEDC, WHVC, WLTP Class 1, UDDS, and SC03). This success confirms the HIL system's architecture capability to simulate and monitor battery discharging trends in terms of their voltage and current.

Observer-based adaptive dynamic sliding mode control for automatic clutch position tracking

The automatic clutch’s precise and stable position tracking is critical in automated manual transmission, significantly influencing vehicle performance. Clutch position control is challenging due to directly unmeasurable clutch output position, nonlinear characteristics, parameter uncertainties, and external disturbance of the automatic clutch system. This paper proposes an observer-based adaptive dynamic sliding mode control strategy to overcome these obstacles to the clutch position tracking process. The extended state observer (ESO) introduced in the designed strategy handles total disturbance, including nonlinearities and uncertainties for feedback control and total compensation. A sigmoid tracking differentiator arranges the transient process and smooth approach signal for the reference input and its differential signal. An adaptive dynamic sliding mode controller acts as the primary feedback control to realize fast and precise position tracking of the automatic clutch system based on the signal from ESO. Simulation and hardware-in-loop (HIL) experimental tests verify the effectiveness and advantage of the proposed control strategy for the clutch position tracking performance in the face of parameter perturbation and external disturbance, for example, the root mean square value of static tracking error of the designed strategy is 14.9% and 24.7% lower than that of ESO-based sliding mode control and robust sliding mode control strategy in the HIL test, respectively.

Cyber-Physical Optimization-Based Fuzzy Control Strategy for Plug-in Hybrid Electric Buses Using Iterative Modified Particle Swarm Optimization

The fuel economy of plug-in hybrid electric bus (PHEB) is highly dependent on its energy management strategy (EMS). In practice, the fuzzy control (FC) is widely used in EMS due to its real-time performance and robustness. However, the FC with fixed parameters is difficult to obtain the optimal fuel economy under changing traffic conditions. Regarding this, the control parameters of FC need to be optimized, but this scheme needs to overcome the subsequent calculation burden and time consumption. Therefore, the design of a real-time EMS with parameter optimization is a challenging problem. Inspired by this issue, a cyber-physical optimization-based fuzzy EMS is proposed in this paper. Firstly, a cyber-physical system framework is formulated for PHEB to eliminate the conflict between parameter optimization and real-time operation of EMS. Secondly, considering the uncertainty of the vehicle environment, an IT2 FC with optimization parameters is designed for real-time torque allocation. Thirdly, an iterative modified particle swarm optimization (IMPSO) algorithm is proposed to optimize parameters to accurately and quickly converge to the optimal solution. Additionally, the optimization problem with multi-objective that takes battery life into account is introduced. Finally, simulation and hardware in loop test are used to discuss the performance of the proposed EMS. The results reveal that the IMPSO algorithm can improve the optimization effect. Compared to conventional rule-based and fuzzy-based strategies, the proposed EMS can reduce fuel consumption at least 10% and 4.5%, respectively. Meanwhile, it shows the proposed EMS could reduce the battery capacity loss by 6.42%∼9.72% with a slight increase in fuel consumption.

Design and hardware in loop testing of an intelligent controller for power quality improvement in a complex micro grid

The wide-ranging use of renewable energy sources (RES) in the modern era leads to the association of distributed non-conventional energy resources in contrary to large-scale and localized conventional non-renewable sources. The prevalent use of distributed sources produces various Power-Quality issues. A thorough review of the literature provides numerous approaches for Power Quality (PQ) improvements; however, most techniques can improve only a few PQ problems. The new technical challenges like power loss, stability, reliability and power quality (PQ) issues are observed in present micro grid scenario. In this regard, this research work is an attempt to address PQ improvement in a three-phase realistic complex micro grid (integration of three simple micro grids to the point of common coupling. Improvement of various PQ factors for example sag/swell, unbalancing, power factor (Pf), total harmonic distortion (THD), communication delay and addition of impedance has been addressed in this research work. In this research article, a Kernel based Deep Auto Regressive Exogenous Output Neural Network (KDNARX) controller has been proposed and applied to improve power quality issues in a complex or realistic three phase complex micro grid (RTPCMG) in grid connected mode of operation. The RTPCMG is a combination of three simple grids with individual ratings of (4 kW, 4 kW and 6 kW). Photo voltaic cell, wind generator (WG), fuel cell (FC) and battery energy storage system (BESS) are the constituent distributed generators (DGs) for the proposed micro grid. The PQ improvement by application of proposed KDNARX controller to the DG inverter switching, has been overly tested in 12 different power quality issues under various operating conditions. The Kernel parameters are optimized by a new optimization technique called Cosine Chaotic PSO (CCPSO) algorithm. The results proved the strength of the new control technique ensuring PQ improvement and stability study of a three phase AC micro grid. Also, the potentiality of the new control scheme is compared with ANN and NARX and its superiority has been proved. Further, some case studies are validated through hardware in loop (HIL) environment thus justifying its real time implementation.

Optical simulator design for hardware in loop testing of medium and long range angles-only navigation of spacecraft

设计了一种航天器中远距仅测角导航硬件在环测试的光学模拟器，可对仅测角导航视觉传感器的硬件、软件和算法的性能及可靠性进行验证。首先对该光学模拟器进行了系统描述，包括硬件组成和星图模拟软件设计。硬件选用的都是商用、现成的部组件，可大幅节约研发成本，缩短开发周期。其次，重点阐述屏幕亮度与恒星星等之间的关系，以及该光学模拟器的光学原理。最后对该光学模拟器的星图模拟进行实验测试，并介绍了一种基于Clohessy-Wiltshire (CW)方程的仅测角导航模型，用于硬件在环测试。验证了几何校正后的光学模拟器完全满足航天器中远距仅测角导航硬件在环测试要求，并得出相对于几何校正前，终端时刻的相对位置精度提高了25.5%，相对速度精度提高了31.3%。

Region of convergence by parameter sensitivity constrained genetic algorithm-based optimization for coordinated load frequency control in multi-source distributed hybrid power system

The imbalances created by generation and load can indeed result in frequency variations demanding a load frequency control (LFC). The LFC becomes even more complicated with the multi-source distributed hybrid power system (HPS), where designing optimal controller parameters by identifying the region of convergence (RoC) is critical as it guarantees the HPS's stability. Hence, this paper aims to address the frequency regulation (FR) issue in a state-of-the-art modeled multi-source distributed HPS with a coordinated control approach. The modeled HPS includes a reheat thermal power system (RTPS), wind turbine generator (WTG), fuel cell (FC) stack, battery energy storage system (BESS), diesel engine generator (DEG), and various controllers.A novel method called parameter sensitivity algorithm (PSA) is proposed to obtain the RoC of the controller gains and is further optimized using a constrained genetic algorithm (GA). To demonstrate coordinated control effectiveness, a hybrid objective function for optimization is formulated as constrained GA's fitness function using the integral time absolute error (ITAE) and integral absolute error (IAE). Furthermore, a comparative assessment for PI, PID with filter (PIDN), cascaded PI-PD with filter (PIPDN) controller topologies is carried out using error index-based performance metrics to ascertain the preeminence of the hybrid objective function over existing objective functions. The investigation results validate that the suggested optimized controllers provide enhanced FR and are robust to uncertainties. The practical feasibility of the proposed methodology is reinforced using dSPACE hardware in loop testing.

Analytical Damping Contribution Assessment Method of Multiconverters System Based on Energy Network Model

Multiconverters connected to grid can induce subsynchronous oscillation (SSO). This article proposed an analytical damping contribution assessment method that can explicitly reveal how (positively or negatively) and to which degree each converter in the multiconverters system changes the system stability level. First, the energy network model of the multiconverters system that satisfies energy conservation is proposed. On this basis, a theory proof is presented that the real part of eigenvalue of SSO mode in the multiconverters system is equal to the sum of coefficient in the aperiodic components of the derivative of dynamic energies injected by each converter and dissipation energy of network, which illustrates analytically how the SSO stability level is shaped. The dynamic energy showing a decreasing trend is good for the oscillation to disappear, and the faster the dynamic energy decreases, the faster the oscillation amplitude decreases. Thus, how and to which degree converter changes stability level can be revealed by the changing trend and rate of its dynamic energy, respectively. Moreover, the expression of dynamic energy is brief, which is, thus, readily for online use, and is universal for converters with different control strategies. Finally, hardware in loop tests verifies that, eliminate converters’ rapidly increasing dynamic energy, the unstable SSO converges rapidly, and eliminate converters’ slowly increasing dynamic energy, the unstable SSO converges but slowly, and eliminate converters’ decreasing dynamic energy, unstable SSO diverges more rapidly, which demonstrates that dynamic energy can precisely assess damping contribution of converter.

Improve hydrogen economy for vehicular fuel cell system via investigation and control of optimal operating oxygen excess ratio

This study investigates and controls the optimal operating oxygen excess ratio (OER) for PEMFC, which effectively prevents oxygen starvation and improves the hydrogen economy of proton exchange membrane fuel cells (PEMFC). Firstly, the PEMFC output characteristic model and the five-order nonlinear air supply system model are established. Moreover, an adaptive algebraic observer was developed to observe the partial pressure of gas in PEMFC and further reconstruct OER. Secondly, to achieve the minimum hydrogen consumption under the required power, the reference OER is determined by analyzing the PEMFC system output power with its minimum current. Finally, the super-twisting algorithm is adopted to track reference OER. Simulation results show that the average absolute observation errors of oxygen, nitrogen, and cathode pressures under the Highway Fuel Economy Test are 1351.1 Pa (5.1%), 1724.2 Pa (0.9%), and 409.9 Pa (1.6%), respectively. The OER adjust average absolute error is 0.03. Compared with the commonly used fixed OER (e.g., OER of 1.5 and 2.3), the optimal OER strategy can reduce the hydrogen consumption of the PEMFC system by 5.2% and 1.8%, respectively. Besides, a DSP hardware in loop test is conducted to show the real-time performance of the proposed optimal method.

Design and modeling of hardware-in-loop test bench for hydraulic excavator based on dynamic load emulation

Hardware-In-Loop (HIL) testing is an effective means to improve the development process of construction machinery. This paper presents a HIL test bench for hydraulic excavator based on dynamic load emulation. The critical technology of HIL test bench is the ability to emulate realistic load. Therefore, a digging load emulating model is established and implemented in real-time environment. To improve the load emulating accuracy, the soil-bucket interaction model is calibrated based on the coupling of the discrete element method (DEM) and multibody dynamics (MBD). The experimental scheme under positive and negative load working conditions is designed to correct the testing error. The performance of the HIL test bench is evaluated from multiple perspectives of load emulating accuracy, system power flow and fuel consumption. Compared with actual excavation tests, the testing error of the proposed HIL test bench is no more than 12%.

Design and Hardware in Loop Testing of an Intelligent Controller for Power Quality Improvement in a Complex Micro Grid

Design and Hardware in Loop Testing of an Intelligent Controller for Power Quality Improvement in a Complex Micro Grid

An Improved Motion Control With Cyber-Physical Uncertainty Tolerance for Distributed Drive Electric Vehicle

A lateral motion control scheme for a distributed drive electric vehicle is presented in this paper, which takes into account both in-car network and movement-parameter uncertainty in a synthetic manner. Distributed drive vehicles have obvious advantages in terms of safety and comfort at high speeds due to the well-known E/E architecture, which includes an in-vehicle network, advanced vehicle motion control, and Advanced Driver Assistance System (ADAS) technologies. This is a fundamentally cyber-physical system. However, on the other hand, the application/insertion of in-vehicle network and the dynamic of wide-range varying speeds introduce additional system uncertainties, such as time-varying network induced delays and inevitable system perturbation, making controller design a difficult problem and even making the system unstable. This paper develops a cyber-physical control scheme and under which a two-process perturbation analysis is proposed to illustrate the system uncertainties. A hierarchical control strategy is also devised, with an upper-level gain-scheduling controller dealing with speed perturbation uncertainties and a lower-level <inline-formula> <tex-math notation="LaTeX">$H_{\mathrm {\infty }}$ </tex-math></inline-formula>-LQR controller dealing with in-vehicle network uncertainty. Using real-time hardware in loop testing, the suggested control technique was found to be effective in dealing with both in-vehicle network and system perturbation problems while also ensuring reliable vehicle stability in all three scenarios.

Fuzzy energy management strategy for electric vehicle combining driving cycle construction and air-conditioning load identification

Energy management strategy is developed by considering the random and air conditioning load fluctuation, which greatly affected the torque control of the electric motor in electric vehicle. Firstly, the vehicle power consumption model is established, based on the influencing factors of electric vehicle energy consumption: random load and air conditioning load. Therefore, driving conditions with random characteristics representing the actual random load are constructed. According to the clustered characteristic parameters, the driving conditions were classified as different driving modes. Secondly, the mode of predicted condition was taken as a variable to evaluate the logic threshold strategy and fuzzy control strategy in which the influence of air conditioning was considered. Finally, under the condition of New European Driving Cycle (NEDC), the proposed management strategy was simulated in software environment, and the hardware in-loop (HIL) test was performed to verify the strategy. The simulation and HIL test results show that the proposed energy management strategy can increase the driving range by considering the load fluctuation of air conditioning. Furthermore, the strategy combining the driving mode prediction can alleviate the decline rate of SOC. And the fuzzy control strategy has better adaptability in complex conditions and lower battery energy consumption rate.

Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control

This paper presents an adaptive inertia weight particle swarm optimization (AIWPSO) employed for solving the multiobjective weight optimization problem of LQR applied for the vehicle active suspension system (ASS). To meet the competing control objectives of ASS including the ride comfort, road handling, and suspension travel, the state feedback controller design for ASS is formulated as an optimization problem and an improved PSO is employed for finding the optimal weights of the linear-quadratic regulator (LQR). Specifically, for solving the premature convergence of the particles and imbalance between exploration and exploitation capabilities of PSO, an adaptive inertia weight that updates the velocity of the particles based on the success rate is used. The efficacy of the AIWPSO-tuned LQR is experimentally tested on a quarter-car ASS plant using the hardware in loop (HIL) testing for an uneven road surface. Experimental results highlight that, compared to conventional PSO-tuned LQR, the proposed scheme can significantly minimize the vehicle body acceleration due to irregular road profile while guaranteeing the minimum tire friction for passenger safety. The ISO 2361-1 standards adopted to evaluate the ride and health criteria substantiate that the proposed scheme reduces the vibration dose value by 25.34% for a bumpy road profile. Moreover, the cumulative power spectral density (CPSD) of vehicle body acceleration assessed in both low- and high-frequency regions manifests the significant improvement in the ride comfort.

An improved numerical distance relay based on CCVT transient characteristic matching

The transients of the coupling capacitor voltage transformer (CCVT) have an impact on the performance of distance relays and result in the overreach problem. Based on the equal transfer process of transmission lines (ETPTL) theory, the virtual digital CCVT can be applied to reduce the impact of the CCVT transients and improve the operation speed of distance relays. The virtual digital CCVT is required to have the same transient characteristics as the actual CCVT. This paper proposes a simple and universal design method of virtual digital CCVT. Based on the CCVT transient characteristic matching and the ETPTL theory, this paper proposes an improved numerical distance relay algorithm to prevent the overreach problem of distance relays without sacrificing the operation speed of distance relay under the internal fault conditions. An extensive performance evaluation using PSCAD/EMTDC simulation corroborates the effectiveness of the proposed distance relay under different fault conditions. Finally, a prototype device based on the proposed distance relay is developed in laboratory and evaluated through a hardware in loop test using real-time digital simulator (RTDS).

Model predictive coordinated control of heavy‐duty vehicle using non‐linear three‐directional coupled model

This study proposes a coordinated control strategy to improve the safety, handling stability, riding comfort of the heavy-duty vehicle. The strategy is based on the coordination of direct yaw moment control (DYC) and anti-lock braking system. The model predictive control (MPC) method for DYC considering sideslip angle and yaw rate is presented. The sideslip angle and yaw rate are adopted to be the indicators for handling stability, constraints considering the maximal force of actuator are implemented in the MPC. The control scheme is examined on a non-linear three-directional coupled model in the environment of MATLAB/Simulink and TruckSim. The relationship between yaw moment and wheel slip ratio is obtained by the Dugoff model, which can be easily implemented in hardware-in-loop (HIL) tests. HIL tests are conducted to verify the improvement introduced by the coordinated control with MPC. Vehicle responses under various speeds and turning radii are analysed by comparison of proportional–integral control and MPC. The results specify that the proposed coordinated control scheme with MPC could obtain better lateral stability.

Control strategy of wind energy conversion system based on H‐MMC under asymmetrical grid faults

This study proposes a topology of wind energy conversion system based on hexagonal modular multilevel converter (H-MMC), which can connect the wind turbine and the AC grid with one stage conversion. It has the advantages of low power losses, low ripple of capacitor voltage and transformer-less grid connection. The operation principle of the proposed topology is analysed in detail. Then, the positive and negative sequence control method is proposed to eliminate the second harmonics in the output power of H-MMC under asymmetrical grid faults. The double proportional resonant (PR) controller is proposed to track arm current references without steady error. The effectiveness of the proposed topology and its control method are verified by simulations and hardware in loop tests.