Nowadays due to the technology development and use of digital computers in various systems, need for development of high performance and robust software is attracting great attentions. Because of increasing complexity in algorithms and implementation hardware for embedded systems, proper simulation tools are required. In sophisticated systems design, hardware in the loop (HIL) simulation is known as a prominent simulation tool before realistic tests of the system and a step after software simulation. Simultaneously it can be used for verification and validation of automation and control software. HIL has had an historical background in aerospace industries. Recently, this tool has spread in different steps of system life cycle such as design, development, implementation and test of various applications including automobile industry, shipbuilding, power lines, robotic systems and etc. Utilizing a suitable hardware in the loop laboratory, in system design stages is a practical way to increase the system reliability and efficiency as well as value of product. Also, by proper investigation in this modelling and simulation method, many errors can be avoided in design procedure of software and hardware as well as their interconnections. In this study, structure and components of an hardware in the loop laboratory for different systems are explored, also it is tried to more evaluate the applications of HIL simulations in dynamics and control engineering. At last, general structure of an hardware in the loop lab for diverse industries is proposed and discussed.

State of the art: hardware in the loop modeling and simulation with its applications in design, development and implementation of system and control software

Influence of texture on tyre road noise spectra in rubberized pavements

With the development of autonomous driving, offline testing remains an important process allowing low-cost and efficient validation of vehicle performance and vehicle control algorithms in multiple virtual scenarios. This paper aims to propose a novel simulation platform with hardware in the loop (HIL). This platform comprises of four layers: the vehicle simulation layer, the virtual sensors layer, the virtual environment layer and the Electronic Control Unit (ECU) layer for hardware control. Our platform has attained multiple capabilities: (1) it enables the construction and simulation of kinematic car models, various sensors and virtual testing fields; (2) it performs a closed-loop evaluation of scene perception, path planning, decision-making and vehicle control algorithms, whilst also having multi-agent interaction system; (3) it further enables rapid migrations of control and decision-making algorithms from the virtual environment to real self-driving cars. In order to verify the effectiveness of our simulation platform, several experiments have been performed with self-defined car models in virtual scenarios of a public road and an open parking lot and the results are substantial.

Autonomous Vehicle Testing and Validation Platform: Integrated Simulation System with Hardware in the Loop*

An adaptive cruise control system with a longitudinal controller that follows a preceding vehicle in autonomous vehicles is proposed. The adaptive cruise control system in a test vehicle recognizes a preceding vehicle located in front of the test vehicle and drives the test vehicle with a safety distance to the preceding vehicle by controlling its accelerator and brake. Vehicle distance errors caused by preceding vehicle distances can be determined by the distance information obtained from the laser scanner installed on the front side of a succeeding vehicle. The acceleration control in a succeeding vehicle performs velocity control by transmitting APS (Acceleration Position Sensor) signals, which can be generated at the speed control unit artificially, to ECU (Electronic Control Unit). An adaptive cruise control system presented in this research is simulated with CARSIM and SIMULINK and its performance is also proved to be very practical after several experimental test on a real car.

An adaptive cruise control system for autonomous vehicles

An active noise control system is provided to select a test signal for determining a transfer function of a second path for a vehicle so that a passenger can not listen to the test signal, thereby improving the quality of internal sound and audio signal transmission. A loudspeaker(LS) outputs an attenuation signal for reducing or attenuating an undesired noise signal. The attenuation signal is transmitted to a listening position via a second path from the loudspeaker. An error microphone(E) determines a reduction level through an error signal at the listening position. A first adaptive filter(W) filters a signal indicating the undesired noise signal through a transfer function suitable for a first path transfer function by using the error signal from the error microphone and the signal indicating the undesired noise signal to generate the attenuation signal. A reference generator generates a reference signal supplied to the loudspeaker with the attenuation signal from the first adaptive filter. The reference signal has amplitude and/or frequency masked for a listener at the listening position by the undesired noise signal and/or a desired signal at the listening position.

Active noise control system

In this paper, a hardware-in-the-loop simulation (HILS) system was developed before the development of an electric power steering (EPS) system in a vehicle. This study was focused on the establishment of the HILS system. Driving conditions are simulated with the HILS system. The actual steering input parameters are confirmed on the monitor while driving the HILS system. The steering forces observed in the simulation with the developed HILS system are similar to those in real vehicle tests. The developed HILS system can be applied in the development of various types of EPS systems.

Development of a hardware in the loop simulation system for electric power steering in vehicles

This paper deals with the process to identify the exciting forces generated from a rotary compressor. The equation of motion of a rigid compressor supported by several mounts was derived with 6 degree of freedom. The mass moment of inertia of compressor and the stiffness of rubber mounts were also identified by experiments. The exciting force at the center of mass of the compressor were estimated from the acceleration data measured at compressor shell. The piping system connected to the compressor was modeled. The acceleration of a pipe was predicted numerically by using the predicted exciting force. The numerical results showed good agreement with experimental results, which validated the identified exciting force.

http://www.koreascience.or.kr:80/article/JAKO201030560145178.pdf

Force Identification of a Rotary Compressor and Prediction of Vibration on a Pipe

For the numerical simulation of tire rolling noise, an important subject is the extraction of normal velocity data of the tire surface that are essential for the acoustic analysis. In the current study, a concept of periodically exciting contact force is introduced to effectively extract the tire normal velocity data. The ground contact pressure within contact patch that is obtained by the static tire contact analysis is periodically applied to the whole tread surface of stationary tire. The periodically exciting contact forces are sequentially applied with a time delay corresponding to the tire rolling speed. The tire vibration is analyzed by the mode superposition in the frequency domain, and the acoustic analysis is performed by commercial BEM code. The proposed method is illustrated through the numerical experiment of 3-D smooth tire model and verified from the comparison with experiment, and furthermore the acoustical responses are investigated to the tire rolling speed.

Numerical method for simulating tire rolling noise by the concept of periodically exciting contact force

Enclosures are widely used to alleviate the contribution of machinery noise. It has been long concerned with the noise transmission through the access openings of the enclosures. In this study, we investigate active noise control technology for reduction of the transmission. A numerical model based on the acoustic boundary element method is first established. Using the numerical model, the acoustic transfer functions of the field points over the opening to the primary source at arbitrary locations are estimated. The feedforward control to minimize the acoustic power through the opening is then numerically implemented. The controller drives the secondary source to destructively interfere the noise transmission through the opening. Finally, a parametric study is conducted to evaluate the effects of the location and the number of the microphones on the control performance. Furthermore, the effects of the location of the secondary source on the performance of active noise control are investigated. It is followed that the control system implemented in this study leads to a significant reduction of about 31.5 dB in the sound power through the opening using only one secondary source located at the optimized position.

Active Control of Propagated Noise through Opening of Enclosures Surrounding a Noise Source

Let and . We prove that the Segal-Bargmann transform is a bounded operator from fractional Hermite-Sobolev spaces to fractional Fock-Sobolev spaces .

/pdf/boundedness-of-the-segal-bargmann-transform-on-fractional-3ep7xeuw0m.pdf

Han-Wool Lee

Papers

Development of a hardware in the loop simulation system for electric power steering in vehicles

Force Identification of a Rotary Compressor and Prediction of Vibration on a Pipe

Numerical method for simulating tire rolling noise by the concept of periodically exciting contact force

Active Control of Propagated Noise through Opening of Enclosures Surrounding a Noise Source

Boundedness of the Segal-Bargmann Transform on Fractional Hermite-Sobolev Spaces