摘要
为了提高汽车质心侧偏角估计的准确性,提出了一种新的、基于运动学—动力学方法的融合估计方法。构建了质心侧偏角融合观测器(SAFO)。该SAFO包括3个子滤波器,每个子滤波器分别将横向车速的初步估计结果送到主滤波器中。主滤波器根据当前车辆行驶工况和融合规则,将子滤波器的估计结果融合成为全局意义下的质心侧偏角估计结果。结果表明:该SAFO具有良好的估计精度和长时间尺度下的计算稳定性,同时对横向加速度传感器偏差具有鲁棒性。因此,车辆测试数据验证了SAFO的性能。
A novel method of vehicle sideslip angle estimation was proposed based on a fusion of kinematics and dynamics methods to improve the estimation accuracy. A sideslip angle fusion observer （SAFO） was constructed with three local iflters to estimate lateral velocities sending preliminary output to a master iflter. The master iflter fuses the outputs from al local iflters to calculate a global sideslip angle estimation result according to driving information and fusion rules. The results show that the SAFO has good estimation accuracy and stability in a long time running with good robust for sensor signal bias. Therefore, the vehicle test data veriifes the SAFO performances.
出处
《汽车安全与节能学报》
CAS
CSCD
2015年第1期72-78,共7页
Journal of Automotive Safety and Energy
关键词
汽车安全
质心侧偏角估计
运动学方法
动力学方法
融合估计器
伪积分
vehicle safety
sideslip angle estimation
kinematics method
dynamics method
fusion observer
pseudo-integration
