Hardware-in-the-loop Simulation Environment Research Articles

Design and Implementation of Hardware-in-the-Loop Simulation Environment Using System Identification Method for Independent Rear Wheel Steering System

In the automotive field, with the advancement of electronic and signal processing technologies, active control-based chassis systems have been developed to enhance vehicle stability. In this study, a Hardware-in-the-Loop (HiL) simulation environment was developed to effectively improve time and cost during the development process of an independent rear-wheel steering system. The HiL Simulation Environment was developed—a specific test bench capable of simulating driving loads on the prototype. Based on the system identification method, a reaction force modeling technique for the target driving loads was proposed. The full vehicle dynamics simulation model was developed with a lateral maximum error of 4.5% and a correlation coefficient of 0.98, as well as a longitudinal maximum error of 0.1% and a correlation coefficient of 0.99. The reaction force generation system had a maximum error of 2.9%. Using the developed HiL simulation environment, performance verification and analysis of the independent rear-wheel steering system were conducted, showing reductions of 5.1% in lateral acceleration and 5.2% in yaw rate.

Hardware-in-the-Loop Testing of Automatic Lift Dropping System for Heavy Trucks

This paper focuses on a novel hardware-in-the-loop (HIL) system designed for developing the automatic operation of the axle lifting and dropping system for heavy trucks for compliance with the European Union Mass and Dimensions Policy and for evaluating the developed system for different axle loading, road slippage, truck speed, handbrake position and driver input combinations. Such a system is expected to be advantageous over manual operation in fuel consumption, tire wear, road surface damage and ease of taking off on slippery surfaces. An auto lift/drop algorithm in the form of a State Transition Diagram (STM) was developed to meet these requirements and has been implemented in the developed HIL simulation system that contains mechanical, pneumatic, electrical and control elements and a TruckMaker simulation model. In the HIL simulator, the electronic control unit (ECU) operated as if it is working in the real truck. Comprehensive scenarios can be generated and executed in this HIL simulation environment to test the algorithm and the set-up itself before the more expensive and time consuming experimental verification with a real truck. This approach allowed the lift axle automation algorithm and hardware to be tested fully in a safe lab environment where the algorithm could be improved and optimized Results of the HIL simulation verified the advantages of such an automated lift axle lifting and dropping system over manually operated axle dropping systems. The developed system was successfully implemented later in a truck and was used in series production trucks.

Ancillary Service with Grid Connected PV: A Real-Time Hardware-in-the-Loop Approach for Evaluation of Performances

The integration of photovoltaic (PV) systems with the grid is undoubtedly an issue of great interest both in terms of energy production, but also as a support to the grid as an ancillary service, but to evaluate the performance of the use of PV in an unconventional way, it is necessary to have reference models to be applied to evaluate the characteristics and integration requirements. In this work, an ancillary service provided by a grid-connected PV is shown and a hardware in the loop simulation environment is created to simulate performances and integration issues.

A testing framework for predictive driving features with an electronic Horizon

This paper proposes a novel approach for automated functional testing of map-based fusion algorithms in complex vehicle networks. The hybrid data representation of detailed digital maps and physical automotive sensors provides an extended view of the ego-vehicle environment and thereby facilitates improved inferences and more competent decision-making. It has therefore been instrumental in the ongoing development of predictive driving features, e.g. fuel-efficient driving, traffic sign recognition and highway-pilot. The presented approach utilises a closed-loop Hardware-in-the-Loop (HiL) co-simulation framework to evaluate the performance of the decision level fusion algorithms. The method contains both the structural design and resource-efficient integration into the HiL test bench in the example of traffic sign recognition. In reality, discrepancy between visual and map data is omnipresent due to map errors, old map data or optical detection failure. Through fault injection, defined inconsistencies can be produced within the HiL simulation environment. Amongst others, the fault injection covers the placement and value of traffic signs. These failures can be used for robustness testing of the fusion algorithms. Subsequently, a method for correlation analysis between field observations and synthetic simulation is realised to extend the requirements-based test coverage adaptively and systematically by modular and parameterised scenario specifications. In summary, the results show that the extended HiL environment is capable of generating electronic Horizon data which can easily be adapted or extended.

Sensitivity-Based Fault Detection and Isolation Algorithm for Road Vehicle Chassis Sensors.

Vehicle control systems such as ESC (electronic stability control), MDPS (motor-driven power steering), and ECS (electronically controlled suspension) improve vehicle stability, driver comfort, and safety. Vehicle control systems such as ACC (adaptive cruise control), LKA (lane-keeping assistance), and AEB (autonomous emergency braking) have also been actively studied in recent years as functions that assist drivers to a higher level. These DASs (driver assistance systems) are implemented using vehicle sensors that observe vehicle status and send signals to the ECU (electronic control unit). Therefore, the failure of each system sensor affects the function of the system, which not only causes discomfort to the driver but also increases the risk of accidents. In this paper, we propose a new method to detect and isolate faults in a vehicle control system. The proposed method calculates the constraints and residuals of 12 systems by applying the model-based fault diagnosis method to the sensor of the chassis system. To solve the inaccuracy in detecting and isolating sensor failure, we applied residual sensitivity to a threshold that determines whether faults occur. Moreover, we applied a sensitivity analysis to the parameters semi-correlation table to derive a fault isolation table. To validate the FDI (fault detection and isolation) algorithm developed in this study, fault signals were injected and verified in the HILS (hardware-in-the-loop simulation) environment using an RCP (rapid control prototyping) device.

A Control-Oriented Charge Mixing and Two-Zone HCCI Combustion Model

A control-oriented engine model is often used in the hardware-in-the-loop (HIL) simulation environment for developing and validating the corresponding control strategies. For homogeneous charge compression ignition (HCCI) combustion, mixture heterogeneity should be considered in the control-oriented model to provide accurate combustion phase prediction. This paper describes a two-zone HCCI combustion model, where the in-cylinder charge is divided into the well-mixed and unmixed zones as the result of charge mixing. Simplified fluid dynamics is used to predict the residual gas fraction before the combustion phase starts, which defines the mass of the unmixed zone, during real-time simulations. The unmixed-zone size determines not only how well the in-cylinder charge is mixed, which affects the start of HCCI combustion, but also the resulting peak in-cylinder pressure and temperature during the combustion process. The developed model was validated in the HIL simulation environment. The HIL simulation results show that the proposed charge mixing and HCCI combustion model provides better agreement with the corresponding GT-Power simulation results than the previously developed one-zone model.

Hardware‐in‐the‐loop simulation for visual target tracking of octorotor UAV

PurposeThe purpose of this paper is to present the development of hardware‐in‐the‐loop simulation (HILS) for visual target tracking of an octorotor unmanned aerial vehicle (UAV) with onboard computer vision.Design/methodology/approachHILS for visual target tracking of an octorotor UAV is developed by integrating real embedded computer vision hardware and camera to software simulation of the UAV dynamics, flight control and navigation systems run on Simulink. Visualization of the visual target tracking is developed using FlightGear. The computer vision system is used to recognize and track a moving target using feature correlation between captured scene images and object images stored in the database. Features of the captured images are extracted using speed‐up robust feature (SURF) algorithm, and subsequently matched with features extracted from object image using fast library for approximate nearest neighbor (FLANN) algorithm. Kalman filter is applied to predict the position of the moving target on image plane. The integrated HILS environment is developed to allow real‐time testing and evaluation of onboard embedded computer vision for UAV's visual target tracking.FindingsUtilization of HILS is found to be useful in evaluating functionality and performance of the real machine vision software and hardware prior to its operation in a flight test. Integrating computer vision with UAV enables the construction of an unmanned system with the capability of tracking a moving object.Practical implicationsHILS for visual target tracking of UAV described in this paper could be applied in practice to minimize trial and error in various parameters tuning of the machine vision algorithm as well as of the autopilot and navigation system. It also could reduce development costs, in addition to reducing the risk of crashing the UAV in a flight test.Originality/valueA HILS integrated environment for octorotor UAV's visual target tracking for real‐time testing and evaluation of onboard computer vision is proposed. Another contribution involves implementation of SURF, FLANN, and Kalman filter algorithms on an onboard embedded PC and its integration with navigation and flight control systems which enables the UAV to track a moving object.

HILS를 이용한 함정의 관성항법장치 전달정렬 환경 모의 기법

A simulation technique, which simulate dynamic motion and communication environments of ship in the lab, is needed in order to reduce the testing cost when we evaluate the transfer alignment performance of shipboard INS. Hardware-In-the-Loop Simulation(HILS) can be used as an effective test method for those system because it can provide flexible and realistic simulation environments, various test scenario, and repeated test environment in the lab without additional cost and person. This paper presents the methods for implementing the real time HILS environment for testing transfer alignment performance of shipboard INS. It includes real time executive for controlling realtime simulation and calculating the ship motion, communication method for interfacing between the systems, and coordinate transformation method for converting real ship coordinate attitude data to lab coordinate attitude data.

Control system design and testing for a small‐scale autonomous helicopter

PurposeThe purpose of this paper is to conduct the design, development and testing of a controller for an autonomous small‐scale helicopter.Design/methodology/approachThe hardware in the loop simulation (HILS) platform is developed based on the nonlinear model of JR Voyager G‐260 small‐scale helicopter. Autonomous controllers are verified using the HILS environment prior to flight experiments.FindingsThe gains of the multi‐loop cascaded control architecture can be effectively optimized within the HILS environment. Various autonomous flight operations are achieved and it is demonstrated that the prediction from the simulations is in a good agreement with the result from the flight test.Research limitations/implicationsThe synthesized controller is effective for the particular test‐bed. For other small‐scale helicopters (with different size and engine specifications), the controller gains must be tuned again.Practical implicationsThis work represents a practical control design and testing procedures for an autonomous small‐scale helicopter flight control. The autonomous helicopter can be used for various missions ranging from film making, agriculture and volcanic surveillance to power line inspection.Originality/valueThe research addresses the need for systematic design, development and testing of controller for a small‐scale autonomous helicopter by utilizing HILS environment.

Individual evaluation scheduling for experiment‐based evolutionary multi‐objective optimization

AbstractSince the pioneer work on Evolution Strategies, experiment‐based optimization is one of the most promising applications of evolutionary computation. Recent progress in automatic control and instrumentation provides us with a smart environment called Hardware in the Loop Simulation (HILS) for such applications. However, since optimization through experiment has the severe condition of limited evaluation time and fluctuation of observations, we must develop methodologies that overcome these problems. This paper discusses the application of Multi‐Objective Evolutionary Algorithms (MOEAs) to Experiment‐ Based Multi‐Objective Optimization of the parameters of dynamical systems. In such applications, we must apply various parameter candidates spreading near the Pareto frontier to the system, which causes fluctuation of the observed criteria due to the transient response by parameter switching. For reduction of loss time caused by such transient responses in the evaluation of criteria, we propose the techniques called Evaluation Order Scheduling and Evaluation Time Scheduling. Numerical experiments using a formal test problem and experiments in a HILS environment with real internal‐combustion engines have demonstrated the effectiveness of the proposed methods. © 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(2): 12–24, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10224

Hardware-in-the-loop simulator for research on fault tolerant control of electrohydraulic actuators in a flight control application

Testing fault tolerant control and diagnosis systems for hydraulic actuators under operating conditions that closely resemble the intended application is an important part of control system verification. This paper describes a hardware-in-the-loop (HIL) simulation framework that enables an experimental hydraulic actuator to be exercised as a flight control actuator against the numerical simulation of a high-performance jet aircraft. The HIL simulator is centered around a state-of-the-art hydraulic test bench that can experimentally simulate many of the common component faults in a servovalve driven actuator circuit. A second experimental hydraulic ram is used to create a wide range of in-flight operating conditions by replicating the aerodynamic load disturbance that is transmitted through the control surface hinge during flight maneuvers. The goal of the HIL simulator is to develop and objectively test novel fault tolerant control and diagnostics algorithms for fluid power actuators and to investigate, for the first time, the complex interaction between faulty flight actuator hardware and the overall aircraft performance. An overview of the HIL simulation architecture, which is executed on four networked desktop computers, is given and the hardware implementation is described. Issues related to the design of the force control system around the load emulator actuator are also discussed. The results of several HIL case studies, including a human-in-the-loop simulation, are presented to demonstrate the functionality of the HIL simulation environment.

実験ベース進化的多目的最適化のための個体評価スケジューリング

Since the pioneer work on Evolution Strategies, experiment-based optimization is one of the most promising applications of evolutionary computation. Recent progress in automatic control and instrumentation provides us with a smart environment called Hardware in the Loop Simulation (HILS) for such applications. However, since optimization through experiment has the severe condition of limited evaluation time and fluctuation of observations, we must develop methodologies that overcome these problems. This paper discusses the application of Multi-Objective Evolutionary Algorithms (MOEAs) to Experiment- Based Multi-Objective Optimization of the parameters of dynamical systems. In such applications, we must apply various parameter candidates spreading near the Pareto frontier to the system, which causes fluctuation of the observed criteria due to the transient response by parameter switching. For reduction of loss time caused by such transient responses in the evaluation of criteria, we propose the techniques called Evaluation Order Scheduling and Evaluation Time Scheduling. Numerical experiments using a formal test problem and experiments in a HILS environment with real internal-combustion engines have demonstrated the effectiveness of the proposed methods. © 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(2): 12–24, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10224

Acceleration of Experiment-Based Evolutionary Multi-Objective Optimization Using Fitness Estimation

Evolutionary Multi-objective Optimization (EMO) is expected to be a powerful optimization framework for real world problems such as engineering design. Recent progress in automatic control and instrumentation provides a smart environment called Hardware In the Loop Simulation (HILS). It is available for our target application, that is, the experiment-based optimization. However, since Multi-objective Evolutionary Algorithms (MOEAs) require a large number of evaluations, it is difficult to apply it to real world problems of costly evaluation. To make experiment-based EMO using the HILS environment feasible, the most important pre-requisite is to reduce the number of necessary fitness evaluations. In the experiment-based EMO, the performance analysis of the evaluation reduction under the uncertainty such as observation noise is highly important, although the previous works assume noise-free environments. In this paper, we propose an evaluation reduction to overcome the above-mentioned problem by selecting the solution candidates by means of the estimated fitness before applying them to the real experiment in MOEAs. We call this technique Pre-selection. For the estimation of fitness, we adopt locally weighted regression. The effectiveness of the proposed method is examined by numerical experiments.

Hardware-In-The-Loop Simulation (HILS) Based Design and Evaluation of an Intelligent Gantry Crane System

The use of gantry crane systems for transporting payload is very common in industrial applications. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. To overcome this problem, this paper describes development of an intelligent gantry crane system based on the mechatronics design. A lab-scale gantry crane is designed and then its intelligent controllers are developed. Fuzzy logic controllers are adopted, designed and implemented for controlling payload position as well as the swing angle of the gantry crane. The performance of the proposed intelligent gantry crane system is evaluated on a hardware-in-the-loop simulation (HILS) environment. Moreover robustness of the proposed system is also evaluated experimentally in the HILS environment. The result shows that the proposed intelligent gantry crane system designed based on the mechatronics design approach has better performance than the automatic gantry crane system controlled by classical PID controllers. Moreover the result also shows that the intelligent gantry crane system is more robust to parameter variation than the automatic gantry crane system.

A cost- and time-effective hardware-in-the-loop simulation platform for automotive engine control systems

A new PC-based hardware-in-the-loop simulation (HILS) platform is developed for designing an automotive engine control system. The HILS equipment consists of a widely used PC and commercial off-the-shelf (COTS) I/O boards instead of a powerful computing system and custom-made I/O boards. These features make the HILS equipment more cost effective and flexible. The HILS uses an automatic code generation extension, REAL-TIME WORKSHOP® of the MATLAB® tool-chain, which is one of the standard tools for modelling and off-line simulation in the area of controller design. This helps the control system developers to handle the controlled-object model more easily and to test the control system more comfortably and time effectively. The mean value engine model, which is used in the control design phase, is imported in this HILS. The engine model is supplemented with some I/O subsystems and I/O boards to interface actual input and output signals in real time. The I/O subsystems are designed to synchronize the status of the engine model with the control system as well as to convert the raw data of the I/O boards to the appropriate forms for proper interfaces. To prove the feasibilities of the proposed environment, a pilot project for the development of an air-to-fuel ratio control system is carried out. The HILS environment is proved to be an efficient tool to develop various control functions and to validate the software and hardware of the engine control system.