线控转向车辆方向盘扭矩建模方法

Felix Heinrich, Jonas Kaste, Sevsel Gamze Kabil, Michael Sanne, Ferit Küçükay, Roman Henze, Joachim Axmann
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引用次数: 2

摘要

与机电转向系统不同,线控转向系统在车轮和方向盘之间没有机械耦合。因此,必须产生合成的转向感觉,以向驾驶员提供必要的触觉信息。在本文中,作者分析了两种创造逼真转向感的方法。一种是模块化方法,使用几个测量和估计的输入信号通过数学函数对方向盘扭矩进行建模。另一种方法是基于人工神经网络。这取决于转向和车辆测量。这两个概念分别经过优化和训练,以最适合从车辆测量中获得的参考转向感觉。为了进行分析,使用由车辆、齿条执行器和方向盘执行器组成的仿真模型对这两种方法进行了评估。研究表明,这两个概念都能够充分模拟所需的转向感觉。
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Methods for modeling the steering wheel torque of a steer-by-wire vehicle

Unlike electromechanical steering systems, steer-by-wire systems do not have a mechanical coupling between the wheels and the steering wheel. Therefore, a synthetic steering feel has to be generated to supply the driver with the necessary haptic information. In this paper, the authors analyze two approaches of creating a realistic steering feel. One is a modular approach that uses several measured and estimated input signals to model a steering wheel torque via mathematical functions. The other approach is based on an artificial neural network. It depends on steering and vehicle measurements. Both concepts are optimized and trained, respectively, to best fit a reference steering feel obtained from vehicle measurements. To carry out the analysis, the two approaches are evaluated using a simulation model consisting of a vehicle, a rack actuator, and a steering wheel actuator. The research shows that both concepts are able to adequately model a desired steering feel.

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