On-Center Steering Model for Realistic Steering Feel based on Real Measurement Data

Andreas Dieing, Hans-Christian Reuss, Marco Schlüter
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Abstract

Driving simulators allow the testing of driving functions, vehicle models and acceptance assessment at an early stage. For a real driving experience, it's necessary that all immersions are depicted as realistically as possible. When driving manually, the perceived haptic steering wheel torque plays a key role in conveying a realistic steering feel. To ensure this, complex multi-body systems are used with numerous of parameters that are difficult to identify. Therefore, this study shows a method how to generate a realistic steering feel with a nonlinear open-loop model which only contains significant parameters, particularly the friction of the steering gear. This is suitable for the steering feel in the most driving on-center area. Measurements from test benches and real test drives with an Electric Power Steering (EPS) were used for the Identification and Validation of the model. The open-loop architecture on steering rack level shows adequate results and generate a nearly delay-free response of the expected steering torque. Further it allows the expansion to a closed-loop or a hybrid model with neural networks. This makes it particularly suitable for force feedback systems in driving simulators or Steer-By-Wire Systems.
基于实际测量数据的真实转向手感中心转向模型
驾驶模拟器可在早期阶段对驾驶功能、车辆模型和验收评估进行测试。为了获得真实的驾驶体验,有必要尽可能真实地描绘所有的沉浸感。手动驾驶时,方向盘的触觉扭矩在传递真实的转向感觉方面起着关键作用。为了确保这一点,需要使用复杂的多体系统,其中包含大量难以识别的参数。因此,本研究展示了一种如何利用非线性开环模型生成逼真转向感的方法,该模型仅包含重要参数,尤其是转向齿轮的摩擦力。这种方法适用于中心驾驶区域的转向感觉。模型的识别和验证采用了试验台和电动助力转向(EPS)实际试车的测量结果。转向齿条级的开环结构显示了充分的结果,并产生了几乎无延迟的预期转向扭矩响应。此外,它还可以扩展到闭环或带有神经网络的混合模型。因此,它特别适用于驾驶模拟器中的力反馈系统或线控转向系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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