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中文摘要：
基于质心侧偏角的运动学与动力学估计方法,提出了一种新的质心侧偏角融合估计器。它有3个基于不同估计模型的卡尔曼子滤波器,分别独立估计横向车速,并作为初步估计结果送入主滤波器,主滤波器根据信息融合规则,对这些初步估计结果进行融合,得到全局融合估计结果,最后用它算出质心侧偏角。实车试验结果显示,相比于单一估计方法,融合估计器有更高的估计精度和对传感器信号偏差的鲁棒性。
英文摘要：
Based on both kinematic and dynamic estimation methods,a novel sideslip angle fusion estimator（SAFE） is proposed.In SAFE,each of three local Kalman filters based on three different models respectively estimates the lateral velocity by their own as preliminary estimates,which are then sent to the master filter and are fused there to get a global estimate of lateral velocity according to the rules of information fusion,and by which the sideslip angle at mass center is finally calculated.The results of real vehicle test show that compared with single estimation scheme,SAFE has higher estimation accuracy and robustness to sensor signal error.
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