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Backlash Estimation With Application to Automotive Powertrains

机译:背隙估计及其在汽车动力总成中的应用

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In automotive powertrains, backlash imposes well-known limitations on the quality of control and, hence, on vehicle driveability. High-performance controllers for backlash compensation require high-quality measurements of the current state of the powertrain. Information about the size of the backlash is also needed. In this paper, nonlinear estimators for backlash size and state are developed, using the Kalman filtering theory. A linear estimator for fast and accurate estimation of the angular position of a wheel and the engine is also described. It utilizes standard engine speed sensors and the antilock brake system speed sensors and event-based sampling at each pulse from these sensors. The estimators are validated through experiments on a real vehicle and the results show that the estimates are of high quality, and hence, useful for improving backlash compensation functions in the powertrain control system
机译:在汽车动力总成中,齿隙对控制质量以及因此对车辆的可驾驶性施加了众所周知的限制。用于间隙补偿的高性能控制器需要对动力总成当前状态进行高质量测量。还需要有关间隙大小的信息。在本文中,使用卡尔曼滤波理论开发了用于反冲大小和状态的非线性估计器。还描述了用于快速而准确地估计车轮和发动机的角位置的线性估计器。它利用标准的发动机速度传感器和防抱死制动系统速度传感器,并在这些传感器的每个脉冲处基于事件进行采样。通过在真实车辆上进行的实验对估算器进行了验证,结果表明估算器的质量很高,因此有助于改进动力总成控制系统中的间隙补偿功能

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