基于无气味卡尔曼滤波的车辆横向动力学状态估计

M. Wielitzka, M. Dagen, T. Ortmaier
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引用次数: 30

摘要

为了改进车辆的主动安全系统,需要准确地了解车辆的行驶稳定性。特别是侧滑角的精确确定是非常重要的,因为它对改进当前的控制算法具有重大的潜力。因此,提出了一种基于模型的车辆横向动力学在线估计方法,同时由于模型行为高度非线性,使用了卡尔曼滤波算法的推广,扩展卡尔曼滤波器和无气味卡尔曼滤波器。所介绍的方法的结果提出了两种不同的驾驶机动和验证比较采取的测量与大众高尔夫GTI。在此基础上,对扩展卡尔曼滤波和无气味卡尔曼滤波进行了定性比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State estimation of vehicle's lateral dynamics using unscented Kalman filter
In order to improve vehicle's active safety systems accurate knowledge about the vehicle's driving stability is necessary. Especially the exact determination of the side-slip angle can be of great importance, since it has major potential for improving current control algorithms. Therefore, a model-based methodology for online estimation of vehicle's lateral dynamics is presented, while generalizations of the Kalman Filter algorithm, the Extended and Unscented Kalman Filters are used due to the highly non-linear model behavior. The results of the introduced methodologies are presented for two different driving maneuvers and validated comparing to measurements taken with a VW Golf GTI. Furthermore, a qualitative comparison between Extended and Unscented Kalman Filter is realized.
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