• Title/Summary/Keyword: Wheel shaft torque estimation

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

  • Park, Jae-Young;Shim, Woojin;Heo, Seung-Jin
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.5
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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.

Driveline Output Torque Estimation Using Discrete Kalman Filter (이산 칼만 필터를 이용한 구동 출력 토크 추정)

  • Gi-Woo, Kim
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.4
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    • pp.68-75
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    • 2012
  • This paper presents a study on the driveline output torque estimation using a discrete Kalman filter. The in-situ output shaft torque is first measured by a non-contacting magneto-elastic torque transducer. The linear state-space system equations are first derived and the discrete Kalman filter is designed based on the Kalman filter theory to recover the driveline output torque contaminated by random noises. In addition to using torque measurement, the estimation of the output torque using two angular velocities: the output and wheel, is also conducted. The experimental results show that the discrete Kalman filter can be effective for not only removing the random noise in output torque but also estimating the output torque without torque measurement.

Tractive Force Estimation in Real-time Using Brake Gain Adaptation (브레이크 게인 적응기법을 이용한 종방향 타이어 힘의 실시간 추정)

  • ;;Karl Hedrick
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.3
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    • pp.214-219
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    • 2003
  • This paper includes real-time tractive force estimation method using standard vehicle sensors such as wheel speed, brake pressure, throttle position, engine speed, and transmission carrier speed sensor. Engine map, torque converter lookup table, shaft torque observer, and brake gain adaptation method are used to estimate the tractive force. To verify this estimator, measurement which uses strain-based brake torque sensor and estimation results are presented. All results was performed using a real vehicle in a real-time.