• Structural Engineering and Mechanics
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• v.23 no.3
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• pp.279-292
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• 2006

Natural hazards, including the wind hazard and others, threaten the integrity of the modern society. A transportation system usually consists of roadways, bridges and related vehicles. Harsh environmental conditions, caused by such as wind, exist in the real world frequently and affect the dynamic performance of the transportation system through their interactions. Long-span bridges are usually the backbones of transportation lines. In windy conditions, the information about the dynamic performance of bridges and vehicles considering full interactions of environmental factors is very essential for people to assess the overall operational conditions and safety risks of the transportation lines. Most of existent approaches target specifically at several isolated tasks considering partial interaction effects. In order to improve the understanding of these related-in-nature problems integrally as well as the consistency of different approaches, a unified approach to integrally predict the dynamic performance of long-span bridges and vehicles under wind is introduced. Such an approach can be used as a general platform to predict the dynamic responses of vehicles and bridges under various situations through adopting both commercial and in-house software. Dynamic interaction effects can be fully considered automatically for each situation. An example of a prototype bridge in US is given for the purpose of demonstration.

• Journal of Power Electronics
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• v.16 no.1
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• pp.238-248
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• 2016

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.785-793
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• 2006

The topic of this study is the control strategy of a mild hybrid electric vehicle (HEV) equipped with a continuously variable transmission (CVT). A brief powertrain and vehicle configuration is introduced followed by the control strategy of the HEV with emphasis on two key parts. One of them is an ideal operating surface (IOS) that operates the CVT powertrain optimally from the viewpoint of the tank-to-wheel efficiency. The other is a charge sustaining energy management to maintain the battery state of charge (SOC) within an appropriate level. The fuel economy simulation results of the HEV over standard driving cycles were compared with those of the baseline vehicle. Depending on the driving cycle, 1.3-20% fuel saving potential is predicted by the mild hybridisation using an integrated starter alternator (ISA). The detailed energy flow analysis shows that the majority of the improvement comes from the idle stop function and the benefits for electrical accessories. Additionally, the differences between the initial and the final SOC are in the range $-1.0{\sim}+3.8%$ in the examined cycle.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.41-46
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• 2017

Magnetically levitated (Maglev) vehicles maintain a constant air gap between guideway and car bogie, and thereby achieves non-contact riding. Since the straightness and the flatness of the guideway directly affect the stability of levitation as well as the ride comfort, it is necessary to monitor the status of the guideway and to alert the train operators to any abnormal conditions. In order to develop a signal processing algorithm that extracts guideway irregularities from sensor data, virtual testing using a simulation model would be convenient for analyzing the exact effects of any input as long as the model describes the actual system accurately. Simulation model can also be used as an estimation model. In this paper, we develop a state-space dynamic model of a maglev vehicle system, running on the guideway that contains jumps. This model contains not only the dynamics of the vehicle, but also the descriptions of the power amplifier, the anti-aliasing filter and the sampling delay. A test rig is built for the validation of the model. The test rig consists of a small-scale maglev vehicle, tracks with artificial jumps, and various sensors measuring displacements, accelerations, and coil currents. The experimental data matches well with those from the simulation model, indicating the validity of the model.

• Journal of Power Electronics
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• v.19 no.1
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• pp.190-200
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• 2019

The flyback converter, which can be regarded as a nonlinear time-varying system, has complex dynamics and nonlinear behaviors. These phenomena can affect the stability of the converter. To simplify the modeling process and retain the information of the output capacitor branch, a special sampled-data model of a peak current-mode (PCM) controlled flyback converter is established in this paper. Based on this, its dynamic behaviors are analyzed, which provides guidance for designing the circuit parameters of the converter. With the critical stability boundary equation derived by a Jacobian matrix, the stable operation range with a varied output capacitor, proportional coefficient of error the amplifier, input voltage, reference voltage and slope of the compensation ramp of a PCM controlled flyback converter are investigated in detail. Research results show that the duty ratio should be less than 0.5 for a PCM controlled flyback converter without ramp compensation to operate in a stable state. The stability regions in the parameter space between the output capacitor and the proportional coefficient of the error amplifier are enlarged by increasing the input voltage or by decreasing the reference voltage. Furthermore, the ramp compensation also can extend to the stable region. Finally, time-domain simulations and experimental results are presented to verify the theoretical analysis results.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.252-255
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• 2008

In this study, the characteristics of crossing a river of Ground Armored Vehicle (GAV) were evaluated by numerical method and real size tests. 3-D hybrid mesh systems were constructed by 3-D models of the GAV, and a commercial software, FLUENT, was used in numerical analysis. In order to deal with multi-phase problem (air and water), Volume Of Fluid (VOF) method was used, and Moving and Deforming Mesh (MDM) was adapted for unsteady motion of GAV. There were two steps in this research. Firstly, stability of the GAV which cruised a river was evaluated by changing several shapes of water-proof-front-wing of the GAV in steady state, and compared results (free surface shape and drag value in 10km/h) with those of real size tests. Secondly, results of unsteady analysis considering weight and moment of inertia of the GAV were presented. There were showed a maximum velocity with a designed water jet and dynamic stability including pitch, roll, and yaw moment. Based on these results, the optimal shape of water-proof-front-wing of the GAV was determined for a proto-type of the GAV.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.859-866
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• 2009

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

• Structural Monitoring and Maintenance
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• v.6 no.4
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2115-2120
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• 2017

Presently, It is required to change convergence the role of hardware system and software technology that promoted trust of In-Vehicle for integrated complex system visibility evaluation. There is possibility for the period system can invoke unpredictable confusing blank state. The blank state systems have ecosystem characteristics that are supplied, maintained and operated through the complex interactions of technology and culture. Using universal middleware can support the life-cycle model and increase the visibility of complex systems and prepare for confusing situations. In this study, based on universal middleware, data and service dynamic standardized modules were evaluated to support stable system visibility platform. The system visibility module consists of Intelligent Pervasive Cloud module, Memorial Service module and Life Cycler connection module. In addition, the analysis results are supported by various network application service standards through platform independent system and architecture.

• Smart Structures and Systems
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• v.31 no.5
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• pp.501-516
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• 2023

Dynamic irregularity and acceleration of bridges subjected to high-speed trains provide crucial information for comprehensive evaluation of the health state of under-track structures. This paper proposes a novel approach for real-time estimation of vertical track dynamic irregularity and bridge acceleration using deep generative adversarial network (GAN) and vibration data from in-service train. The vehicle-body and bogie acceleration responses are correlated with the two target variables by modeling train-bridge interaction (TBI) through least squares generative adversarial network (LSGAN). To realize supervised learning required in the present task, the conventional LSGAN is modified by implementing new loss function and linear activation function. The proposed approach can offer pointwise and accurate estimates of track dynamic irregularity and bridge acceleration, allowing frequent inspection of high-speed railway (HSR) bridges in an economical way. Thanks to its applicability in scenarios of high noise level and critical resonance condition, the proposed approach has a promising prospect in engineering applications.