• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.602-607
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• 2004

Accurate and quick positioning of the throttle valve in driving situation is required to implement the Traction Control System(TCS). Also, unlike a conventional throttle valve which is connected to the accelerator directly by a wire, an Electronic Throttle Valve(ETV) is driven by a DC motor and can move dependently upon the accurate position of the accelerator. In the research, the Electronic Throttle Body(ETB) and Controller for TCS application was developed. In order to drive the DC motor, the developed controller was built and interfaced to the ECU and ETB. The PID position control algorism and developed systems are designed to realize the robust tracking control of the ETV. Actual vehicle tests with these systems and PID position control algorithm. Finally, the performance of the proposed those are evaluated with the experimental studies.

• 로봇학회논문지
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• 제2권1호
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• pp.1-8
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• 2007

This paper presents a PID automatic gain-tuning algorithm for the electronic throttle valve which is driven by wire. Since the system characteristics of position control for electronic throttle valve are so complicated that both the real time robustness and the manufacturing cost must be considered for mass production. To resolve this paradox, a kind of algorithm called RLS (Recursive Least Square) is adopted for the control of the ETB (Electronic Throttle Body). Using this algorithm, the PID gains can be adjusted automatically with the estimated system parameters. Furthermore, a pre-filter is supplemented for the sake of the robustness against the friction and loads. From the industrial requests for the system, the design specifications are decided as follows: the settling time should be less than 1sec and the overshoot should be kept below 3%. The results of the experiments based on this approach show that the high robustness can be achieved while the system stability is satisfied steadily. A parameter estimation scheme and a gain-tuning algorithm have been properly combined and utilized in this research and the effectiveness is verified through the real experiments.

• 한국자동차공학회논문집
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• 제16권1호
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• pp.71-77
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• 2008

This paper proposes an Electronic Throttle Body (ETB) model considering a non-linearity of DC motor driver which is integrated with a H-bridge and a gate driver. A propagation delay and reverse recovery time of switching components cause non-linear characteristic of DC motor driver. This non-linearity affects not only the amateur voltage of DC motor, but also entire behaviour and parameters of ETB. In order to analyze the behavior of ETB more accurately, this non-linear effect of DC motor driver is modeled. The developed ETB model is validated by use of the step response and ramp response experiments, and it shows relatively accurate results compared with linear DC motor driver model.

• 오토저널
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• 제9권5호
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• pp.66-76
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• 1987

The control technique for an electronic engine is studied. For this study an IBM-PC and a throttle body fuel injection system are selected. The computer controls fuel injection, spark timing, exhaust gas recirculation and idle speed. Fuel injection is adjusted either by a feed back signal of a zirconia $O_{2}$ sensor or programmed logic for starting, deceleration, warm ing up and idle modes. When a 3-way catalytic converter is used with the electronic engine control system, CO, THC, and NOx were reduced more than 90% simultaneously.

• 오토저널
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• 제8권3호
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• pp.16-27
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• 1986

In this study, low emission gasoline engine system is developed utilizing an EGR valve, 3 way catalytic converter and electronic fuel injection system. EGR was controlled by a needle valve and optimized at the engine conditions. Throttle body fuel injection system is used for fueling. When the engine was operated at constant speed by the electronic engine control system with the 3 way catalytic converter, th emissions were reduced by 50 to 90% in volume depending on he engine operating conditions.

• 한국컴퓨터정보학회논문지
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• 제29권11호
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• pp.57-66
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• 2024

본 연구에서는 파라미터 변이 및 비선형 토크를 갖는 차량 전자식 스로틀 바디 시스템(ETB)의 딥러닝 기반의 파라미터 종속적인 PID 제어기 설계 방법을 나타낸다. 시스템 변화 및 부하용량 변화로 인하여 변이된 시스템의 주요 파라미터 값을 딥러닝을 이용하여 추정한다. 파라미터를 추정하기 위하여 심층 신경망을 설계하고, 시스템의 시간응답 특성(상승시간, 오버슈트, 정착시간)을 특성값으로 하여 신경망을 훈련한다. 훈련된 신경망으로부터 시간응답 특성값 이용하여 파라미터는 추정된다. 또한 추정된 파라미터에 동조되어 자동 조정되는 파라미터 종속 PID 제어기를 설계한다. PID 제어기의 최적 이득값은 ITAE 판별법에 의하여 찾아지며, 추정된 파라미터의 함수로 나타내어진다. 또한 비선형 토크의 영향을 감쇄하기 위하여 추정된 비선형 토크값을 상쇄시켜 줄 피드 포워드 제어기를 추가적으로 설계한다. 설계된 제어기의 제어 성능을 나타내기 위하여, 시뮬레이션을 통한 파라미터 변화 및 비선형 토크를 갖는 ETB 시스템의 제어 성능 결과를 나타낸다.