• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.11
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• pp.2119-2125
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• 1992

An air-fuel ratio control method is studied to keep the air-fuel ratio of the exhaust gas in the neighborhood of the stoichiometric air-fuel ratio to maximize the conversion efficiency of the three-way catalytic converter. Estimators, which estimate the air-fuel ratio of the exhaust gas, are proposed using neural networks to overcome the limit of the presently used bang-bang type exhaust gas oxygen sensor. Using these estimators, PI controller for air-fuel ratio control is designed and is experimented for an automobile engine. The proposed controller reduces the variation of air-fuel ratio of the exhaust gas from the stoichiometric air-fuel ratio by 50%-75% when compared to the existing controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.1013-1018
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• 2007

In general, there are many sensors for fuel injection control such as an air flow sensor, an air intake temperature sensor, a cooling water temperature sensor, a throttle position sensor, and a motor position sensor. In this paper, we proposed a method for controlling the amount of fuel consumption in cars using fuzzy control technique by temperature change of an air intake temperature sensor and air-fuel ratio, the ratio of air and fuel mixture. In the proposed method, the amount of fuel injection is controlled by fuzzy membership functions and fuzzy inference rules established for air-fuel ratio, air intake temperature, and final fuel compensation, after computing air-fuel values using each amount of air intake and each amount of fuel injection. We verified that the proposed method is more efficient than conventional methods in fuel injection control from the results of the simulation program.

• Ceramist
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• v.4 no.5
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• pp.16-28
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• 2001

• Proceedings of the Materials Research Society of Korea Conference
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• 1992.05a
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• pp.89-90
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• 1992

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.395-400
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• 2017

The paper discussed the air-to-fuel ratio control of automotive fuel-injection systems using the cerebellar model articulation controller(CMAC) neural network. Because of the internal combustion engines and fuel-injection's dynamics is extremely nonlinear, it leads to the discontinuous of the fuel-injection and the traditional method of control based on table look up has the question of control accuracy low. The advantages about CMAC neural network are distributed storage information, parallel processing information, self-organizing and self-educated function. The unique structure of CMAC neural network and the processing method lets it have extensive application. In addition, by analyzing the output characteristics of oxygen sensor, calculating the rate of fuel-injection to maintain the air-to-fuel ratio. The CMAC may easily compensate for time delay. Experimental results proved that the way is more good than traditional for petrol control and the CMAC fuel-injection controller can keep ideal mixing ratio (A/F) for engine at any working conditions. The performance of power and economy is evidently improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.67-72
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• 2008

본 논문에서는 하이브리드 차량 내부 전기모터의 등판 마력값과 회전 RPM, 흡기온도 센서의 온도 변화와 공기 및 연료의 혼합비율인 공연비에 대해 퍼지 제어 기법을 적용하여 차량의 연료 소비를 제어하는 방법을 제안한다. 제안된 기법에서는 초기 가속부분에서 등판 마력간과 회전 RPM을 퍼지제어 규칙에 의해 전기모터와 엔진의 사용비율을 제어하고, 엔진이 가동될 때 각각의 공기유입량과 연료 분사량을 이용하여 공연비 수치를 구한 후, 공연비, 흡기온도, 최종 연료 보정량에 대해 설정된 피지 소속 함수와 퍼지 추론 규칙에 따라 차량 연료를 제어한다. 시뮬레이션을 통하여 실험한 결과, 제안된 퍼지 제어 기법을 이용한 엔진 및 연료 제어 방법이 퍼지기법을 적용하지 않은 제어방법보다 평균연비가 개선되어 제안된 연료 제어 방법이 효율적임을 확인하였다.

• Analytical Science and Technology
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• v.12 no.6
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• pp.472-477
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• 1999

It was developed the oxygen sensor of air-fuel ratio measuring system that was controlled the needed air amounts in optimum combustion according to the analysis of oxygen concentration of exhaust gas. The oxygen sensor was prepared by using gold as cathode, which the detection range for the oxygen concentration was from 0.0% to 30.0%. Response time was observed 15 to 20 sec. rapidly and selectively. It was appeared a good result in reproducibility and stability.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.37-50
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• 1997

The objective of this paper is to study on the idle speed control using the fuzzy logic controller under load disturbance. The design procedure for fuzzy logic controller depends on the expert's knowledge or trial and error. The inputs of the fuzzy controller are error of rpm and variation of rpm. The output of the fuzzy controller is an ISC motor step and ignition timing. The airflow is controlled by the ISC motor movement and the idle speed is controlled by the airflow control and ignition timing control. During the control, air to fuel was checked by LAMBDA sensor. All experiments were performed in a real vehicle.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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• pp.102-111
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• 1996

For the air-fuel ratio control in a fuel injection SI engine, the Jump-Ramp control algorithm has been widely adopted by using the on/off type oxygen sensor. But the Jump-Ramp control method has limitation on treating the frequency and amplitude of the air-fuel ratio oscillation. This study suggests another feedback control logic named modulated fuel feedback control, which has a concept of pre-tuned air-fuel ratio oscillation. In the modulation method, the oxygen sensor output is not treated as on/off signal but as analog signal for feedback. By using the modulation method, the frequency and the amplitude of air-fuel ratio oscillation can be adjustable to some extent for improving the conversion efficiency of the Three-Way Catalyst. The result shows that the performance of the modulation method is better than that Jump-Ramp control method in reducing the amplitude of the air-fuel ratio oscillation as well as in increasing the frequency of the air-fuel ratio oscillation.

• Journal of Sensor Science and Technology
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• v.8 no.5
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• pp.394-399
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• 1999

An automobile hot-film air flow sensor is deposited with platinum by sputtering method, patterned by photoresisted lift-off method, annealed in $1,000^{\circ}C$ and passivated with PI-2723. The TCR of the fabricated hot-film is about $3500\;ppm/^{\circ}C$. In the experiment, the output voltage of the sensor is in proportional to the fourth power root in the air mass flow range of 300 kg/h. The error in the full flow range is about ${\pm}0.7%$. In the range of air temperature of $-20^{\circ}C{\sim}120^{\circ}C$, the error is about ${\pm}1%$ that is ${\pm}2%$ lower than that of the reference sensor. Therefore, the fabricated hot-film air flow sensor satisfies the specification for automobile. Lower temperature error of the sensor provides to control the precise air/fuel ratio of automobile engine and results in improvement of a fuel mileage and the less amount of toxic gases emitted by automobile.