• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.214-230
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• 2014

This paper presents a high performance sensor less control four motorized wheels for electric vehicle. Firstly, we applied a sensor less master-slave DTC based control to both the two in wheel motors by using sliding mode observer for its quick response and its high reliability in electric vehicle application. Secondly, to overcome the possible loss of adherence of one of the four wheels which is likely to destabilize the vehicle a solution is proposed in this paper. Thirdly, a Fuzzy logic anti-skid control structure well adapted to the non-linear system is used to overcome the main problem of power train system in the wheel road adhesion characteristic. Various Simulation results have been include in this paper to show that the proposed control strategy can prevent vehicle sliding and show good vehicle stability on a curved path.

• Wind and Structures
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• v.11 no.4
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• pp.257-273
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• 2008

A number of passive aerodynamic drag reduction methods were applied separately and then in different combinations on an intercity bus model, through wind tunnel studies on a 1:20 scale model of a Mercedes Benz Tourismo 15 RHD intercity bus. Computational fluid dynamics (CFD) modelling was also conducted in parallel to assist with flow visualisation. The commercial CFD package $CFX^{TM}$ was used. It has been found that dramatic reductions in coefficient of drag ($C_D$) of up to 70% can be achieved on the model using tapered and rounded top and side leading edges, and a truncated rear boat-tail. The curved front section allows the airflow to adhere to the bus surfaces for the full length of the vehicle, while the boat-tails reduce the size of the low pressure region at the base of the bus and more importantly, additional pressure recovery occurs and the base pressures rise, reducing drag. It is found that the CFD results show remarkable agreement with experimental results, both in the magnitude of the force coefficients as well as in their trends. An analysis shows that such a reduction in aerodynamic drag could lead to a significant 28% reduction in fuel consumption for a typical bus on intercity or interstate operation. This could translate to a massive dollar savings as well as significant emissions reductions across a fleet. On road tests are recommended.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.103-114
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• 2011

In this study, we discuss a fatal accident severity model obtained from the analysis of 112 crash sites collected since 2000, and the resulting relationship between fatal accidents and roadway geometry design. From the 720 times computer simulations for improving driving safety, we then reached the following conclusions:. First, the result of cross and frequency-analyses on the car accident sites showed that 43.7% of the accidents occurred on the curved roads, 60.7% on the vertical curve section, 57.2% on the roadways with radius of curvature of 0 to 24m, 83.9% on the roads with superelevation of 0.1 to 2.0% and 49.1% on the one-way 2-lane roads; vehicle types involved are passenger vehicles (33.0%), trucks (20.5%) and buses (14.3%) in order of frequency. The results also show that the superelevation is the most influencing factor for the fatal accidents. Second, employing the Ordered Probit Model (OPM), we developed a severity model for fatal accidents being a function of on various road conditions so as to the damages can be predicted. The proposed model possibly assists the practitioners to predict dangerous roadway segments, and to take appropriate measures in advance. Third, computer simulation runs show that providing adequate superelevation on the segment where a fatal accident occurred could reduce similar fatal accidents by at least 85%. This result indicates that the regulations specified in the Rule for Road Structure and Facility Standard (description and guidelines) should be enhanced to include more specific requirement for providing the superelevation.

• Journal of Drive and Control
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• v.14 no.2
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• pp.30-36
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• 2017

This paper presents a sliding mode observer-based fault detection algorithm for steering inputs of an all-terrain crane. All-terrain cranes with multi-axles have several steering modes for various working purposes. Since steering angles at the other axles except the first wheel are controlled by using the information of steering angle at the first wheel, a reliable signal of the first axle's steering angle should be secured for the driving safety of cranes. For the fault detection of steering input signal, a simplified crane model-based sliding mode observer has been used. Using a sliding mode observer with an equivalent output injection signal that represents an actual fault signal, a fault signal in steering input was reconstructed. The road steering mode of the crane's steering system was used to conduct performance evaluations of a proposed algorithm, and an arbitrary fault signal was applied to the steering angle at the first wheel. Since the road steering mode has different steering strategies according to different speed intervals, performance evaluations were conducted based on the curved path scenario with various speed conditions. The design of algorithms and performance evaluations were conducted on Matlab/Simulink environment, and evaluation results reveal that the proposed algorithm is capable of detecting and reconstructing a fault signal reasonably well.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.99-108
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• 2007

The bi-modal tram guided by the magnetic guidance system has two car-bodies and three axles. Each axle of the vehicle has an independent suspension to lower the floor of the car and improve ride quality. The turning radius of the vehicle may increase as a consequence of the long wheel base. Therefore, the vehicle is equipped with the All-Wheel-Steering(AWS) system for safe driving on a curved road. Front and rear axles should be steered in opposite directions, which means a negative mode, to minimize the turning radius. On the other hand, they also should be steered in the same direction, which means a positive mode, for the stopping mode. Moreover, only the front axle is steered for stability of the vehicle upon high-speed driving. In summary, steering angles and directions of the each axle should be changed according to the driving environment and steering mode. This paper proposes an appropriate AWS control algorithm for stable driving of the bi-modal tram. Furthermore, a multi-body model of the vehicle is simulated to verify the suitability of the algorithm. This model can also analyze the different dynamic characteristics between 2WS and AWS.

• Journal of Korean Society of Steel Construction
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• v.14 no.2
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• pp.329-337
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• 2002

The skid proof pavement is used for safety driving on curved bridges and high level roads. This study analyzed the effect of skid proof pavement on the bridge using actual spot test and computer analysis. In the actual spot test, the natural frequency and dynamic deflection of steel box girder bridges were measured before and after skid proof pavement. Likewise, in the computer analysis, the dynamic response of the finite element model was evaluated. The model was based on real steel box girder bridge according to the skid proof pavement. The analyzed results provide basic data on the effect of skid proof pavement on road structure.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.444-450
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• 2007

The bi-modal tram guided by the magnetic guidance system has two car-bodies and three axles. Each axle of the vehicle has an independent suspension to lower the floor of the car and improve ride quality. The turning radius of the vehicle may increase as a consequence of the long wheel base. Therefore, the vehicle is equipped with the All-Wheel-Steering(AWS) system for safe driving on a curved road. Front and rear axles should be steered in opposite directions, which means a negative mode, to minimize the turning radius. On the other hand, they also should be steered in the same direction, which means a positive mode, for the stopping mode. Moreover, only the front axle is steered for stability of the vehicle upon high-speed driving. In summary, steering angles and directions of the each axle should be changed according to the driving environment and steering mode. This paper proposes an appropriate AWS control algorithm for stable driving of the bi-modal tram. Furthermore, a multi-body model of the vehicle is simulated to verify the suitability of the algorithm. This model can also analyze the different dynamic characteristics between 2WS and AWS.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.229-238
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• 2009

In this paper, AWS ECU test method, which is considering behavior of a Bi-modal tram, is described. In order to evaluate the performance of an electronic automotive ECU, the method which combines HILS (Hardware In the Loop Simulation) and RBT (Requirement Based Testing) is introduced. HILS is the method to predict the behavior of a vehicle adopting an ECU. The behavior of a Bi-modal tram can be analyzed by using the vehicle dynamic model. Requirement Based Testing compare the outputs of a real system with a virtual electronic unit (oracle) which created by the requirements. Rear axles of the Bi-modal tram are independently controlled by two AWS ECU. Especially, swing out can happen when an articulated vehicle is operated in the curved road. Therefore dynamic behaviour of a Bi-modal tram is considered at this situation. Through this study, the reliability of ECU can be verified economically and safely using the proposed test method before conducting the track test.

• Journal of the Korean Society of Safety
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• v.26 no.2
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• pp.89-98
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• 2011

The traffic accidents at a construction site, which happen due to construction vehicles' frequent access to a construction site, its subsequent conflicts with ordinary vehicles and pedestrians, and inappropriate installation & management of traffic security facilities, have not many proportions in all traffic accidents, but obviously, the accident damage is quite serious when comparing the level of the fatal per one accident. This research conducted an analysis of traffic accident injury severity using Ordered Probit Model in relation to 241 traffic accident cases that occurred caused by construction sites among the traffic accidents that took place in Seoul and Gyeoggi-do region for two years from 2006 until 2007. As a result, the significant variables enough to explain traffic accident injury severity were analyzed to be the state of road surface, linear shape of an accident spot & whether the damaging car belongs to the vehicle for construction, and whether vehicles have access to a construction site at the time of an accident. Through this, this research found out some fact as follows: first, there need to be more aggressive management of the vehicles for construction and a year-round placement of the manpower who can control vehicular access to a construction site. Second, it is necessary to get drivers to recognize the fact that there exists a construction site on the construction section which is on the border of curved roads in advance to prevent a traffic accident, helping to reduce socioeconomic loss & costs incurred by a traffic accident.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.101-116
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• 2012

Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.