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首页> 外文期刊>Mineralogia >A Robust Method of Vehicle Stability Accurate Measurement Using GPS and INS
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A Robust Method of Vehicle Stability Accurate Measurement Using GPS and INS

机译：利用GPS和INS进行车辆稳定性稳定测量的鲁棒方法

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With the development of the vehicle industry, controlling stability has become more and more important. Techniques of evaluating vehicle stability are in high demand. Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) is a very practical method to get high-precision measurement data. Usually, the Kalman filter is used to fuse the data from GPS and INS. In this paper, a robust method is used to measure vehicle sideslip angle and yaw rate, which are two important parameters for vehicle stability. First, a four-wheel vehicle dynamic model is introduced, based on sideslip angle and yaw rate. Second, a double level Kalman filter is established to fuse the data from Global Positioning System and Inertial Navigation System. Then, this method is simulated on a sample vehicle, using Carsim software to test the sideslip angle and yaw rate. Finally, a real experiment is made to verify the advantage of this approach. The experimental results showed the merits of this method of measurement and estimation, and the approach can meet the design requirements of the vehicle stability controller.
机译：随着汽车工业的发展，控制稳定性变得越来越重要。迫切需要评估车辆稳定性的技术。全球定位系统（GPS）和惯性导航系统（INS）的集成是获取高精度测量数据的一种非常实用的方法。通常，卡尔曼滤波器用于融合来自GPS和INS的数据。本文采用一种鲁棒的方法来测量车辆的侧滑角和横摆率，这是保证车辆稳定性的两个重要参数。首先，基于侧滑角和横摆率，引入了四轮车辆动力学模型。其次，建立了双层卡尔曼滤波器，以融合来自全球定位系统和惯性导航系统的数据。然后，使用Carsim软件在样车上对该方法进行仿真，以测试侧滑角和横摆率。最后，进行了真实的实验以验证这种方法的优势。实验结果表明了该方法的优越性，可以满足车辆稳定性控制器的设计要求。

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