• Transactions of Materials Processing
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• v.20 no.7
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• pp.485-490
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• 2011

The application of helical gears in crucial parts of automotive transmissions has been steadily increasing due to their higher power transfer performance compared to spur gears. However, the traditional gear manufacturing methods such as hobbing and deburring require large cycle times with expensive production lines so that there have been intensive efforts trying to manufacture gears via forging processes. Although forging processes for spur and bevel type gears have been developed on the practical level, the manufacturing of helical gears is still dependent on the traditional cutting process. Therefore, this paper seeks to develop a cold forward extrusion process for the helical gear with the pitch diameter of 43.5mm and a helix angle of $18.4^{\circ}$. A forward extrusion process was used due to the relatively small diameter of the target geometry. The material deforming behavior influenced by the die geometry was examined by using CAE analysis. Finally, it was found that the helical gear manufactured by the developed extrusion process satisfied the dimensional accuracy and mechanical characteristics for automotive transmissions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.353-354
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• 2006

The automatic inspection system is developed for the formed end part of automotive fuel pipe. The developed system has functions of outer diameter and formed end length measurement by LVDT(linear variable differential transformer) together with burr cleaning of automotive fuel pipe. The measured data are managed and controlled in real time by embedded SPC(statistical process control) program. The system is composed of mechanical part, electronic part and developed software system. These three parts operate automatically by mutual communication with each other. The developed system showed good results in finding inferior goods and efficiency improvement of the fuel pipe production line. It also eliminated the unreliable manual inspection processes and improved the confidence of product quality.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.36-42
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• 2013

Recently, the automobile of the future will be able to substitute an electric vehicle for an internal combustion engine, so the following research is actively in the process of advancing. A traction motor is one of the core parts which compose the electric vehicle. Especially, it is difficult to connect cooling water piping to an in-wheel motor because the in-wheel motor is located within the wheel structure. This structure has disadvantage for closed type and air cooling, so the cooling design of motor housing and internal in-wheel motor is important. In this study, thermo-flow analysis of the in-wheel motor for vehicles was performed in consideration of ram air effect. In order to improve cooling efficiency of the motor, we variously changed geometries of housing and internal shape. As a result, we found that the cooling efficiency was most excellent, in case the cooling groove direction was same with air flow direction and arranged densely. Furthermore, we investigated the cooling performance enhancement with respect to variable geometries of internal in-wheel motor.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.5
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• pp.119-127
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• 2008

In this paper, the influence of the stamping effect is investigated in the performance analysis of a side structure. The analysis covers the performance evaluation such as the crashworthiness and NVH. Stamping analyses are carried out for the center pillar and the side sill made of high strength steels. Then, numerical simulations are carried out in order to identify the stamping effect on the crashworthiness, the natural frequency and the normal mode. The result shows that the analysis of the side structure considering the forming history leads to a different result from that without considering the forming effect. The variation of the system response fully reveals effects of thinning and hardening of members on the performance prediction of vehicle parts. The analysis results demonstrate that the design of auto-body members should be carried out considering the stamping history for accurate assessment of various performances.

• Corrosion Science and Technology
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• v.17 no.4
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• pp.193-201
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• 2018

In order to suppress $CO_2$ emission and protect passengers in case of vehicle collision, continuous efforts are being made to increase the application ratio and tensile strength of advanced high strength steels used in the manufacturing of automotive body. Simultaneously, hydrogen embrittlement which was not a concern in the past has currently become a major issue due to microstructure that is sensitive to hydrogen uptake. The sensitivity increases with residual stress and hydrogen uptake content. Many automotive OEM companies and mill makers are setting specifications to control hydrogen embrittlement. The factors which lead to hydrogen embrittlement are material sensitivity, residual stress, and hydrogen concentration; researches are in progress to develop countermeasures. To reduce material sensitivity, mill makers add high energy trap elements or microstructure refinement elements. Automotive OEM companies design the car parts not to concentrate local stress. And they manage the levels to not to exceed critical hydrogen concentration. In this article, we have reviewed hydrogen embrittlement evaluation methods and corresponding solutions that are being studied in automobile manufacturing industries and mill makers.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.58-67
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• 2003

An automotive engine cooling system is closely related with overall engine performances, such as reduction of fuel consumption, decrease of air pollution, and increase of engine life. Because of complex reaction between each component, the direct experiment, using a vehicle, takes high cost, long time, and slow response to the system change. Therefore, a computer simulation would provide the designer with an inexpensive and effective tool for design, development, and optimization of the engine cooling system over a wide range of operating conditions. In this work, it has been predicted the thermal performance of the engine cooling system in cases of stationary mode, constant speed mode, and city-drive mode by mathematical modelling of each component and numerical analysis. The components are engine, radiator, heater, thermostat, water pump, and cooling fans. Since the engine model is the most important, that is divided into eight sub-sections. The volume mean temperature of eight sub-sections are simultaneously calculated at a time. For detail calculation, the radiator and heater are also divided into many sub-sections like control volumes in finite difference method. Each sub-section is assumed to consist of three parts, coolant, tube with fin, and air. Hence it has been developed the simulation program that can be used in case of design and system configuration changes. The overall performance results obtained by the program were desirable and the time-traced tendencies of the results agreed fairly well with those of actual situations.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.16-22
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• 2014

Automotive NVH on brake operation is mainly caused by a coupling action of vehicle speed and inter parts friction and its frequency occurs over a broad band of 0.1 kHz~10 kHz. Especially, squeal noise, being a self-excited vibration generated by friction force between drum and lining, occurs over 1 kHz and consequently dynamic instability is induced when friction energy is applied to a brake vibration system. The squeal strongly depends on nonlinear properties influenced by the material of lining, velocity of vehicle, and the dynamic properties of a brake system. The dynamic properties are considered as a main influential design factor to squeal noise, however the analysis of the properties are rarely facilitated due to arbitrariness of shape by wearing down. In this paper, we research generating tendency of squeal noise through complex eigenvalue analysis, tracking drum brake's unstable modes in accordance with the wear shape of drum and lining such as tapered and bellmouth shape, and analyze computed unstable modes by variable shapes.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.3
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• pp.261-270
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• 2010

This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional side bands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.