• 제목/요약/키워드: Friction coefficient estimation

검색결과 89건 처리시간 0.032초

야지 주행 로봇을 위한 횡 방향 힘 추정 모델의 설계 및 마찰계수 추정 신뢰도의 향상 (Design of Lateral Force Estimation Model for Rough Terrain Mobile Robot and Improving Estimation Reliability on Friction Coefficient)

  • 김지용;이지홍;주상현
    • 로봇학회논문지
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    • 제13권3호
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    • pp.174-181
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    • 2018
  • For a mobile robot that travels along a terrain consisting of various geology, information on tire force and friction coefficient between ground and wheel is an important factor. In order to estimate the lateral force between ground and wheel, a lot of information about the model and the surrounding environment of the vehicle is required in conventional method. Therefore, in this paper, we are going to estimate lateral force through simple model (Minimal Argument Lateral Slip Curve, MALSC) using only minimum data with high estimation accuracy and to improve estimation reliability of the friction coefficient by using the estimated lateral force data. Simulation is carried out to analyze the correlation between the longitudinal and transverse friction coefficients and slip angles to design the simplified lateral force estimation model by analysing simulation data and to apply it to the actual field environment. In order to verify the validity of the equation, estimation results are compared with the conventional method through simulation. Also, the results of the lateral force and friction coefficient estimation are compared from both the conventional method and the proposed model through the actual robot running experiments.

순환 최소자승법을 이용한 전동기 관성과 마찰계수 추정 (Inertia and Coefficient of Friction Estimation of Electric Motor using Recursive Least-Mean-Square Method)

  • 김지혜;최종우
    • 전기학회논문지
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    • 제56권2호
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    • pp.311-316
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    • 2007
  • This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.

주행로봇 제어를 위한 험지의 최대마찰계수 추정 (Estimation of the Maximum Friction Coefficient of the Rough Terrain to Control the Mobile Robots)

  • 강현석;곽윤근;최현도;정해관;김수현
    • 제어로봇시스템학회논문지
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    • 제14권10호
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    • pp.1062-1072
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    • 2008
  • When mobile robots perform the mission in the rough terrain, the traversability depended on the terrain characteristic is useful information. In the traversabilities, wheel-terrain maximum friction coefficient can indicate the index to control wheel-terrain traction force or whether mobile robots to go or not. This paper proposes estimating wheel-terrain maximum friction coefficient. The existing method to estimate the maximum friction coefficient is limited in flat terrain or relatively easy driving knowing wheel absolute velocity. But this algorithm is applicable in rough terrain where a lot of slip occurred not knowing wheel absolute velocity. This algorithm applies the tire-friction model to each wheel to express the behavior of wheel friction and classifies slip-friction characteristic into 3 major cases. In each case, the specific algorithm to estimate the maximum friction coefficient is applied. To test the proposed algorithm's feasibility, test bed(ROBHAZ-6WHEEL) simulations are performed. And then the experiment to estimate the maximum friction coefficient of the test bed is performed. To compare the estimated value with the real, we measure the real maximum friction coefficient. As a result of the experiment, the proposed algorithm has high accuracy in estimating the maximum friction coefficient.

Motion of rigid unsymmetric bodies and coefficient of friction by earthquake excitations

  • Zadnik, Branko
    • Structural Engineering and Mechanics
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    • 제2권3호
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    • pp.257-267
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    • 1994
  • Motions of an unsymmetric rigid body on a rigid floor subjected to earthquake excitations with special attention to coefficient of friction are investigated. Motions of a body in a plane are classified (Ishiyama 1980) into six types, i.e. (1) rest, (2) slide, (3) rotation, (4) slide rotation, (5) translation jump, (6) rotation jump. Based upon the theoretical and experimental research work special attention is paid to the sliding of a body. The equations of motions and the behavior of coefficient of friction in the time of floor excitation are studied. One of the features of this investigation is the introduction and estimation of the "time dependent" coefficient of friction. It has been established that the constant kinetic coefficient of friction $${\mu}(kin){\sim_\sim}0.8{\mu}(stat)$$ does not give the appropriate results. The method for the estimation of the friction coefficient variation during the time is given.

타이어-노면 마찰계수 추정을 이용한 AEBS 알고리즘 (AEBS Algorithm with Tire-Road Friction Coefficient Estimation)

  • 한승재;이태영;이경수
    • 자동차안전학회지
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    • 제5권2호
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    • pp.17-23
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    • 2013
  • This paper describes an algorithm for Advanced Emergency Braking(AEB) with tire-road friction coefficient estimation. The AEB is a system to avoid a collision or mitigate a collision impact by decelerating the car automatically when forward collision is imminent. Typical AEB system is operated by Time-to-collision(TTC), which considers only relative velocity and clearance from control vehicle to preceding vehicle. AEB operation by TTC has a limit that tire-road friction coefficient is not considered. In this paper, Tire-road friction coefficient is also considered to achieve more safe operation of AEB. Interacting Multiple Model method(IMM) is used for Tire-road friction coefficient estimation. The AEB algorithm consists of friction coefficient estimator and upper level controller and lower level controller. The numerical simulation has been conducted to demonstrate the control performance of the proposed AEB algorithm. The simulation study has been conducted with a closed-loop driver-controller-vehicle system using using MATLAB-Simulink software and CarSim Vehicle model.

4WD 차량의 후륜 구동력 제어를 위한 구동시 노면마찰계수 추정에 관한 연구 (A Study of Tire Road Friction Estimation for Controlling Rear Wheel Driving Force of 4WD Vehicle)

  • 박재영;심우진;허승진
    • 한국자동차공학회논문집
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    • 제24권5호
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    • pp.512-519
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    • 2016
  • In this study, the tire road friction estimation(TRFE) algorithm for controlling the rear wheel driving force of a 4WD vehicle during acceleration is developed using a standard sensor in an ordinary 4WD passenger car and a speed sensor. The algorithm is constructed for the wheel shaft torque, longitudinal tire force, vertical tire force and maximum tire road friction estimation. The estimation results of shaft torque and tire force were validated using a torque sensor and wheel force transducer. In the algorithm, the current road friction is defined as the proportion calculated between longitudinal and vertical tire force. Slip slop methods using current road friction and slip ratio are applied to estimate the road friction coefficient. Based on this study's results, the traction performance, fuel consumption and drive shaft strength performance of a 4WD vehicle are improved by applying the tire road friction estimation algorithm.

실차 데이터를 이용한 차륜과 노면간의 마찰계수 예측에 관한 연구 (A Study on the Estimation of Frictiom Coefficient between Tire and Road Surface Using Running Car data)

  • 우관제;산기준일
    • 한국자동차공학회논문집
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    • 제7권6호
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    • pp.207-213
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    • 1999
  • In this study, the possibility of estimation of friction coefficient between tire and road surface using running car data are checked. To get necessary data, such as tire and car velocities and braking force, a test car is driven with certain magnitude of decelerations from pre-set initial velocities to stop . The data are used to estimate friction coefficient with property chosen parameters , e.g,, driving stiffness, pressure distribution functions, etc. Experimental results show that running data car be used with properly chosen parameters to estimate friction coefficient.

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인발가공에 있어서 마찰계수의 결정에 관한 연구 (A Study on the Estimation of Friction Coefficient in Drawing Process)

  • 김영수;안병하
    • 수산해양기술연구
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    • 제20권2호
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    • pp.122-126
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    • 1984
  • 1. 미소한 단면적 변화율의 관재인발에서는 직접적인 방법에 의한 평균마찰계수(Mean friction coefficient)와 Sachs의 이론치가 매우 근사한 오차를 나타내므로 축방향 응력으로부터 마찰계수를 결정할 수 있다. 2. 비교적 높은 단면적 감소율의 인발에 있어서는 직접적인 방법에 의한 평균마찰계수가 Sachs등의 값 보다 더욱 실험치에 더욱 접근하므로 반경방향분력의 측정이 필요하다. 3. 봉재인발가공에 사용되는 평균마찰계수의 추정치도 관재인발의 경우에 확대 적용이 가능하다.

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지대치의 재료와 Clasp 재료 사이의 마찰계수와 원형 clasp의 유지력 추정 (Fiction Coefficient between Abutment Materials and Clasp Materials and Estimation of Retention Force of Circumferential Clasp)

  • 임동천
    • 대한치과기공학회지
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    • 제21권1호
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    • pp.67-75
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    • 1999
  • The purpose of this study is to evaluate the friction coefficients between abutment materials and clasp materials, and to an estimation formula for retention force. The coefficients of friction between three clasp materials and four abutment materials were measured under various conditions, polished and sandblasted and wet and dry. The measurement was repeated for each combination up to a total measurement of 1200 times. Estimation formula for retention force is measured as sum of two terms, which the one time is proportional to the product of friction coefficient ${\mu}$ and undercut u and the other term is proportional to u-squared. Two proportional coefficient were obtained by least square method. The results are as follows: 1. Friction coefficients were ranged from 0.08 to 0.53 under various conditions. 2. Friction coefficients of non-metal abutment materials are greater in wet conditions than dry conditions. 3. Friction coefficients of sandblasted clasp against abutment are greater than that of polished clasp. 4. Clasp retention force can be estimated with the model as F=$F_d(3.0{\mu}u+1.5u^2/h)$ with minor error.

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