Laboratory of Automotive Engineering, Helsinki University of Technology, P.O. Box 4300, 02015 TKK, Finland; E-Mail:
Sensors (Basel). 2009;9(11):8761-75. doi: 10.3390/s91108761. Epub 2009 Oct 30.
Future active safety systems need more accurate information about the state of vehicles. This article proposes a method to evaluate the lateral state of a vehicle based on measured tyre forces. The tyre forces of two tyres are estimated from optically measured tyre carcass deflections and transmitted wirelessly to the vehicle body. The two remaining tyres are so-called virtual tyre sensors, the forces of which are calculated from the real tyre sensor estimates. The Kalman filter estimator for lateral vehicle state based on measured tyre forces is presented, together with a simple method to define adaptive measurement error covariance depending on the driving condition of the vehicle. The estimated yaw rate and lateral velocity are compared with the validation sensor measurements.
未来的主动安全系统需要更准确的车辆状态信息。本文提出了一种基于测量的轮胎力来评估车辆横向状态的方法。通过对轮胎胎体变形的光学测量来估计两个轮胎的轮胎力,并通过无线方式传输到车身。另外两个轮胎称为虚拟轮胎传感器,其力是根据实际轮胎传感器的估计值计算得出的。本文提出了一种基于测量轮胎力的横向车辆状态的卡尔曼滤波器估计器,并提出了一种简单的方法来根据车辆的行驶条件定义自适应测量误差协方差。估计的横摆角速度和横向速度与验证传感器测量值进行了比较。