• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.1-8
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• 1999

This paper describes the method for detection of the misfired cylinder by analysis of the variation of pressure occurred in exhaust manifold on an MPI gasoline engine. Misfired cylinder(s) cause a loss of power, an increase of fuel consumption and exhaust emission and vibration is caused by unsteady torque. Therefore early detection and correction of misfired cylinder(s) play a very important role in the proper performance and the exhaust emission. The method is a comparison of integration pressure index during the period of a blowdown in the displacement period. Experimental results showed that the method, using the variation of pressure in the exhaust manifold is proven to be effective in the detection of single cylinder or multiple cylinders misfire on the gasoline engine regardless of the engine revolutions. In addition, this method, using the variation of pressure in the exhaust manifold is a very easy and accurate method compared with other methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.27-32
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• 2010

77GHz FMCW(Frequency Modulation Continuous Wave) radar system has been used for automotive active safety systems. In typical automotive radar, the moving target detection and clutter cancellation including stationary targets are very important signal processing algorithms. This paper proposed the moving target detection algorithm which improve the detection probability and reduce the false alarm rate. First, the proposed moving target beat-frequency extraction filter is used in order to suppress clutter, and then the data association is applied by using the extracted moving target beat-frequency. Then, the zero-Doppler target is eliminated to remove the rest of clutter.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.93-99
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• 2020

A majority of car crash is affected by careless driving that causes extensive economic and social costs, as well as injuries and fatalities. Thus, the research of precise crash detection systems is very significant issues in automotive safety. A lot of crash detection algorithms have been developed, but the coverage of these algorithms has been limited to few scenarios. Road scenes and situations need to be considered in order to expand the scope of a collision detection system to include a variety of collision modes. The proposed algorithm effectively handles the x, y, and z axes of the sensor, while considering time and suggests a method suitable for various real worlds. To reduce nuisance and false crash detection events, the algorithm discriminated between driving mode and parking mode. The performance of the suggested algorithm was evaluated under various scenarios, and it successfully discriminated between driving and parking modes, and it adjusted crash detection events depending on the real scenario. The proposed algorithm is expected to efficiently manage the space and lifespan of the storage device by allowing the vehicle's black box system to store only necessary crash event's videos.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.42-48
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• 1999

Engine misfire causes of the negative effect on exhaust emission such as HC, CO, and NOX . Moreover, it causes damage to the three-way-catalyst(TWC) system permanently. The crankshaft velocity fluctuation(CVF) method has been applied for the real cars as misfire detection system usually, which utilizes the crank angle sensor input to calculate the variation of the crankshaft rotational speed. But this approach has the limit due to the fact that three could be problem under certain engine condition like as deceleration or high speed condition . Therefore the development of new methods are requested today. This study introduced the new method of misfire detection using breakdown voltage(BDV) characteristics between spark plug electrouds.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.2
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• pp.23-31
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• 1996

The crankshaft speed fluctuation was measured every crank angle. In order to detect the misfire, the engine and the dynamometer were considered as a single- degree of freedom system. From this modeling, the detection criteria were derived and examined by the engine test. By this method the single misfire or multiple misfires can be detected. Even on the condition of low load and higher speed than 3000rpm, where it was difficult through the other methods, misfire detection was carried out steadily. From this results, the method proposed by this paper proved reasonable.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.1-8
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• 2000

A new method of knock detection in SI engines, using a change of ion concentration in the combustion chamber, was developed. In order to measure in-cylinder ionization current, ionization probes were installed at spark plug and cylinder head of production engine. It was found that the electric current generated by ionized gas in core burned gas region of knocking cycle is between 2 and 10 times larger than that of normal cycle, because the burned gas temperature which is the dominant parameter of a change of ion concentration increases. However, a change of ionization current in boundary region of burned gas is relatively weak. Hence a change of ion concentration in core burned gas region can be used for knock detection.

• International Journal of Automotive Technology
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• v.3 no.2
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• pp.53-56
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• 2002

A new generation of the BMW child seat and occupant detection system SBE2 far a smart airbag system is described. The SBE2 system consists of two subsystems: OC (Occupant Classification) and FDS (Field Detection System). The OC system is a force sensitive sensor array that measures a pressure profile. The FDS system detects child seat and occupant according to the change of electrical field generated by four capacitive plates. Combining the signals from both subsystems, the BMW SBE2 system can distinguish fully automatically between a child seat and a person.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.1-11
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• 2009

This paper proposes an algorithm capable of detecting vehicles in front or in rear using a monocular camera installed in a vehicle. The vehicle detection has been regarded as an important part of intelligent vehicle technologies. The proposed algorithm is mainly composed of two parts: 1)hypothesis generation of vehicles, and 2)hypothesis verification. The hypotheses of vehicles are generated by the analysis of vertical and horizontal edges and the detection of symmetry axis. The hypothesis verification, which determines vehicles among hypotheses, is done by the AdaBoost algorithm. The proposed algorithm is proven to be effective through experiments performed on various images captured on the roads.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.183-192
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• 2003

Obstacle detection and avoidance are considered as one of the key technologies on an unmanned vehicle system. In this paper, we propose a method of obstacle detection and avoidance and it is composed of vehicle control, modeling, and sensor experiments. Obstacle detection and avoidance consist of two parts: one is longitudinal control system for acceleration and deceleration and the other is lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control system of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are evaluated through road tests.