• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.140-143
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• 2005

The hybrid CAE/CAT methods are widely applied to product development in various fields because this method can predict the response of the whole system when a part of the system is changed. Especially, the hybrid CAE/CAT method is very useful to predict tile vehicle NVH characteristics after changing some parts of the vehicle. Target parts can be established on the basis of test models and FE models of the prototype constructed in the planning stage of car development. In this study, the topic was focused on the proper test-based FBS application process to predict vehicle NVH characteristic. First, the test-based FBS method was apply to vehicle substructure and car-body. And then the test-based model was replaced with FE model to apply hybrid CAE/CAT method. The replaced FE model was modified through the optimization process. The interior noise in vehicle during the drive was predicted with Modified FE model, then the predicted results were verified by experimenting with actual modified model.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.166-173
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• 2005

A vehicle stability control logic for 4WD hybrid electric vehicle is proposed using the regenerative braking of the rear motor and electronic brake force distribution module. Performance of the stability control logic is evaluated for J-turn and single lane change. It is found from the simulation results that the regenerative braking at rear motor is able to provide improved stability compared with the vehicle performance without my stability control. Additional improvement can be achieved by applying the regenerative braking plus electronic brake farce distribution control. It is expected that the regenerative braking offers additional improvement of the fuel economy as well as the vehicle stability control.

• IE interfaces
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• v.22 no.4
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• pp.359-367
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• 2009

The vehicle travel time between the demand points in downtown area is greatly influenced by complex road condition and traffic situation that change real time to various external environments. Most of research in the vehicle routing problems compose vehicle routes only considering travel distance and average vehicle speed between the demand points, however did not consider dynamic external environments such as traffic situation by service time zones. A realistic vehicle routing problem which considers traffic situation of smooth, delaying, and stagnating by three service time zones such as going to work, afternoon, and going home was suggested in this study. A mathematical programming model was suggested and it gives an optimal solution when using ILOG CPLEX. A hybrid genetic algorithm was also suggested to chooses a vehicle route considering traffic situation to minimize the total travel time. By comparing the result considering the traffic situation, the suggested algorithm gives better solution than existing algorithms.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.107-116
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• 2010

The vehicle travel time between locations in a downtown is greatly influenced by both complex road conditions and traffic situation that changes real time according to various external variables. The customer's demands also stochastically change by time period. Most vehicle routing problems suggest a vehicle route considering travel distance, average vehicle speed, and deterministic demand; however, they do not consider the dynamic external environment, including items such as traffic conditions and stochastic demand. A realistic vehicle routing problem which considers traffic (smooth, delaying, and stagnating) and stochastic demands is suggested in this study. A mathematical programming model and hybrid genetic algorithm are suggested to minimize the total travel time. By comparing the results considering traffic and stochastic demands, the suggested algorithm gives a better solution than existing algorithms.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.10
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• pp.68-74
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• 2019

In the case of a partition panel for a vehicle, it is used as a vehicle chassis component that serves to distinguish the indoor and outdoor spaces of a vehicle and is mounted on a backrest portion of the vehicle's back seat to ensure the convenience of passengers by connecting the floor and the side of the vehicle. Because it is a relatively large-sized plate material among automobile chassis parts except the moving parts and non-ferrous materials can be applied, it is considered as a part having a large light-weight effect. However, the partition panel is one of the vehicle parts that must satisfy the light-weight effect as well as various structural reliability, such as torsional rigidity, vibration, and impact characteristics, for securing the running stability of the vehicle when driving at the same time. So, In this study, the possibility of replacing the aluminum partition panel as CFRP(Carbon Fiber Reinforced Plastic) partition panel is evaluated through comparing the two partition panels by using the structural reliability(stiffness/strength analysis), vibration analysis, impact analysis.

• Journal of the Korean Society of Industry Convergence
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• v.1 no.1
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• pp.31-41
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• 1998

Fuel conservation and environmental pollution control are the principal motivating factors that are urging at present widespread research and development activities for electric hybrid vehicles throughout the world. The paper describes different possible energy storage devices, such as battery, flywheel and ultra capacitor, and power sources, such as gasoline engine, diesel engine, gas turbine and fuel cell for next generation hybrid electric vehicle. The technology trend and comparison in energy storage and power devices indicate that battery and gasoline engine, respectively will remain the most viable devices for hybrid vehicle at least in the near future.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.73-80
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• 2003

This paper presents considerations on the results of the rotating arm test, which was carried out for assessment of an hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit(IMU), an ultra-short baseline(USBL) acoustic navigation sensor and a doppler velocity log(DVL) accompanying a magnetic compass. A navigational systemmodel is derived to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters are 25 in the order. The extended Kalman filter was used to propagate the error covariance, The rotating arm tests were carried out in the Ocean Engineering Basin of KRISO, to generate circular motion. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.224-229
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• 2011

In this paper, in order to improve safety of hybrid electric vehicle a fault detection algorithm is introduced. The proposed algorithm uses SVDD techniques. Two methods for learning a lot of data are used in this technique. One method is to learn the data incrementally. Another method is to remove the data that does not affect the next learning. Using lines connecting support vectors selection of removing data is made. Using this method, lot of computation time and storage can be saved while learning many data. A battery data of commercial hybrid electrical vehicle is used in this study. In the study fault boundary via SVDD is described and relevant algorithm for virtual fault data is verified. It takes some time to generate fault boundary, nevertheless once the boundary is given, fault diagnosis can be conducted in real time basis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.441-450
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• 2022

The introduction of autonomous underwater gliders (AUGs) specifically addresses the reduction of operational costs that were previously prohibited with conventional autonomous underwater vehicles (AUVs) using a "scaling-down" design philosophy by utilizing the characteristics of autonomous drifters to far extend operation duration and coverage. Long-duration, wide-area missions raise the cost and complexity of in-water testing for novel approaches to autonomous mission planning. As a result, a simulator that supports the rapid design, development, and testing of autonomy solutions across a wide range using software-in-the-loop simulation at faster-than-real-time speeds becomes critical. This paper describes a faster-than-real-time AUG simulator that can support high-resolution bathymetry for a wide variety of ocean environments, including ocean currents, various sensors, and vehicle dynamics. On top of the de facto standard ROS-Gazebo framework and open-sourced underwater vehicle simulation packages, features specific to AUGs for ocean mapping are developed. For vehicle dynamics, the next-generation hybrid autonomous underwater gliders (Hybrid-AUGs) operate with both the buoyancy engine and the thrusters to improve navigation for bathymetry mappings, e.g., line trajectory, are is implemented since because it can also describe conventional AUGs without the thrusters. The simulation results are validated with experiments while operating at 120 times faster than the real-time.

• Journal of ILASS-Korea
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• v.29 no.1
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• pp.7-15
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• 2024

This study investigates the performance of 2.0L hybrid vehicles equipped with Liquefied Petroleum Gas (LPG) fuel engines, using energy flow analysis. By incorporating a direct LPG injection system (LPDi), the research aims to overcome the reduced maximum output commonly associated with LPG engines. Moreover, the integration of a hybrid system is explored as a means to enhance vehicle fuel economy while reducing CO₂ and emissions. The study employs data from FTP-75 and HWFET driving cycle to inform future research efforts focused on predicting CO₂ emissions and fuel economy for Hybrid Electric Vehicles utilizing LPG Direct Injection. The findings offer insights into optimizing fuel systems for better environmental and operational performance in hybrid vehicles.