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진동 측정을 위한 압전소자 가속도계와 MEMS 가속도계의 비교
정대이,구본용 한국비파괴검사학회 2019 한국비파괴검사학회지 Vol.39 No.3
An Accelerometer is a device used to measure the shock and vibration of mechanical structures; the recent miniaturization trends for electronics has increased the application of such devices to portable and IoT products. Conventionally, piezoelectric accelerometers have been used for vibration measurement and recently a variety of MEMS based accelerometers are commercially available. With this development of MEMS technology, there is a need to compare the configurations, signal conditioning and performance of devices according to the accelerometer type used. In this study, analog signal conditioning circuits including an amplifier circuit and a band-pass filter, are constructed for a piezoelectric and MEMS accelerometers, and vibration signals were measured with the two accelerometers using the constructed circuits. The measurement system characteristics of the piezoelectric and MEMS accelerometers are compared by evaluating the configuration of the accelerometers signal control circuits and the measured vibration signals. 가속도계 센서는 기계 구조의 진동, 충격 등을 측정하는 감지계로 널리 사용되어 왔으며, 최근 전자 기술의 발달에 따른 소형화로 휴대기기 및 IoT 제품에도 사용이 늘어나고 있다. 전통적으로 진동 계측을 위해 압전소자 방식의 가속도계가 주로 사용되었으나 최근 MEMS에 기반한 다양한 가속도계가 시판되고 있고, 이에 따라 가속도계 방식에 따른 신호 조절(Signal conditioning) 장치 구성과 가속도계 성능을 비교할 필요가 있다. 본 연구에서는 압전소자 가속도계 및 MEMS 가속도계에 대해 증폭 회로와 대역 필터를 포함하는 아날로그 신호 조절 회로를 제작하고, 구성된 회로를 이용하여 두 가속도계에서 진동 신호를 측정하였다. 이러한 가속도계 신호 조절 회로 구성과 측정된 진동 신호를 평가하여 압전소자 가속도계 및 MEMS 가속도계의 측정 시스템 특성을 비교하였다.
정대이(Daeyi Jung),노기한(Kihan Noh),최형진(Hyungjeen Choi),이경수(Kyoungsu Yi) 한국자동차공학회 2006 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
It's significant to considerate human factors for the design of the advanced safety vehicle beyond the general vehicle's performance. Therefore, the development of human driver model to imitate the real human drive pattern is useful for the commencement of advanced vehicle research to reflect the human factors. In this paper, several experiments to verify the human factors of driving a vehicle and the control logic to describe the human's drive logic process are presented. Human factors to influence a vehicle operation are assumed to be consisted of two major components, the preview distance recognition and the human neuromuscular system. The finite preview optimal control strategy has been applied due to the similarity of human's situation awareness in a driving condition. Ultimately, combining the control logic with human factors, the representative human driver model has been developed and simulated with ADAMS/CAR in SIMULINK environment. The simulation results have been compared to the actual vehicle test data (DLC road course test result) in terms of driving experience classified by Novice, Intermediate, and Expert. It has been concluded that the representative human driver model presented in this paper is sufficient to describe the human drive pattern sorted by driving experience.
김민수,정대이,김동규,윤태민 한국자동차공학회 2024 한국 자동차공학회논문집 Vol.32 No.3
The utilization of an Automatic Emergency Braking(AEB) system and Electronic Stability Control(ESC) incommercial vehicles, including large buses and trucks, can enhance driving stability by ensuring the weight of the vehicle, road surface conditions, and the estimation of road gradient. Particularly, this research focuses on road gradient estimation. Previous studies used various sensors and longitudinal vehicle dynamics models to estimate road gradient, but integrating them into production vehicles became challenging due to sensor costs. In this study, a model was developed to predict road gradient based on the vehicle’s Control Area Network(CAN) signals, thus eliminating the need for additional sensors. The estimation performance of various filters, including Low-Pass Filters(LPF), Kalman Filters(KF), and Recursive Least Squares(RLS) filters, were compared. The algorithm was implemented in MATLAB/Simulink, and the performance of each filter achieved estimations within a ±10 % error range.
차량 주행 안전성 향상을 위한 RLS 기반 질량 추정 알고리즘 개발
김민수,정대이,김동규,윤태민 한국자동차공학회 2024 한국 자동차공학회논문집 Vol.32 No.2
The ESC(Electronic Stability Control) system, which is designed to ensure the driving stability of commercial vehicles, is an electronic control device that is responsible for managing the vehicle’s posture. By monitoring the vehicle’s tendencies to skid or experiencerollovers, the ESC system automatically intervenes and stabilizes the vehicle, eliminating the need for the driver to use manual braking. This function is particularly important for commercial vehicles, especially when they are loaded with cargo or carrying many passengers and there is a tendency for the center of gravity to shift. Therefore, effective vehicle posture control is crucial in maintaining driving stability, especially when there is excessive lateral acceleration that can easily lead to rollovers. Consequently, a real-time estimation of the vehicle’s mass while in use is essential in enhancing driving stability. By efficiently managing the braking and steering systems through real-time mass estimation, the ESC system can improve driving stability. This paper validated an algorithm that utilizes the RLS(Recursive Least Squares) filter based on TruckSim and real-time vehicle data, successfully achieving estimation with an error range that is within 10 %.