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首页> 外文会议>2017 15th International Conference on Quality in Research : International Symposium on Electrical and Computer Engineering >Two-stage least square method for model identification of vehicle motion
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Two-stage least square method for model identification of vehicle motion

机译：车辆运动模型识别的两阶段最小二乘法

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摘要

Vehicle dynamics have very complex characteristic and nonlinear behaviour. Vehicle dynamics are decomposed of many internal and external components which influence vehicle stability. External components come from environment such as wind forces, surface coarse of road, lane bend or sudden maneuver, which will change the value of vehicle stability parameters, i.e. yaw rate and sideslip. Both are influenced by the longitudinal velocity change and are difficult to be measured by installed sensors in vehicle. For driving convenience and high safety performance, the vehicle stability parameters must be controlled. Researches and experiments directly on the vehicle bring quite expensive cost and huge time consuming. Therefore, before doing experiments to the real vehicle, simulation is taken. Simulation needs model of vehicle dynamics that are approaching real vehicle dynamics. In this paper, instead of using simple vehicle model, the replication of the vehicle dynamics has been taken from CarSim multi-degree of freedom vehicle model. CarSim's vehicle model C Class Hatchback Sprungmass 2012 is used in this simulation. All vehicle parameters are already provided by CarSim. Vehicle model run along defined part of vehicle track of Universitas Indonesia. At certain bend lane, the obtained data consists of steering angle, longitudinal forces to all four wheels, yaw rate and side slip angle. Two-stage Least Square method has been applied to those data in order to estimate vehicle dynamics. The estimated model was validated upon another data. The result shows that the estimated vehicle model could represent in approaching real vehicle dynamics. The estimated model has perfect controllable and observable characteristic. The model is stable and its eigenvalues is inside unit circle.
机译：车辆动力学具有非常复杂的特性和非线性行为。车辆动力学由许多影响车辆稳定性的内部和外部组件分解。外部因素来自诸如风力，路面粗糙，车道弯曲或突然操纵等环境，这将改变车辆稳定性参数的值，即偏航率和侧滑。两者均受纵向速度变化的影响，并且难以通过车辆中安装的传感器进行测量。为了驾驶方便和高安全性能，必须控制车辆稳定性参数。直接在车辆上进行研究和实验会带来相当昂贵的成本和大量的时间消耗。因此，在对真实车辆进行实验之前，先进行仿真。仿真需要逼近真实车辆动力学的车辆动力学模型。在本文中，不是使用简单的车辆模型，而是从CarSim多自由度车辆模型中复制了车辆动力学。在此仿真中使用了CarSim的C型两厢掀背式弹簧汽车模型。 CarSim已经提供了所有车辆参数。车辆模型沿着印度尼西亚大学的车辆轨道的定义部分运行。在某个弯道上，获得的数据包括转向角，对所有四个车轮的纵向力，偏航率和侧滑角。两阶段最小二乘方法已应用于这些数据，以估计车辆动力学。估计的模型在另一个数据上得到了验证。结果表明，估计的车辆模型可以代表逼近实际车辆动力学。估计的模型具有完善的可控性和可观察性。该模型是稳定的，其特征值在单位圆内。

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