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采用UKF算法估计路面附着系数 被引量:14

Unscented Kalman filter for road friction coefficient estimation
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摘要 为了能够迅速准确获取当前道路信息以提高汽车主动安全性能,提出一种实时跟踪路面附着系数变化的汽车状态估计方法.建立包含Pacejka 89轮胎模型的七自由度非线性汽车动力学模型,通过动力学模型估算出前后车轮垂直载荷,结合轮胎力学模型和UKF(Unscented卡尔曼滤波)算法对轮胎纵向力和滑移率进行估计,进而得到不同附着系数路面条件下的Slip-slope(ρ-S曲线斜率),建立了几种典型路面附着系数与Slip-slope之间的映射关系.应用ADAMS/Car中的路面编辑器构造具有不同附着系数的路面测试环境,验证了提出的方法对突变附着系数估计的可靠性和有效性,表明Slip-slope理论在ADAMS/Car的虚拟试验中同样可以再现. To obtain current road information quickly and to improve vehicle active safety performance accurately, a vehicle state estimation method was proposed to real-time track changes in road friction coefficient. A 7-DOF non-linear vehicle dynamic model including Pacejka 89 tire model was established. The normal force of tire was approximately calculated from the vehicle dynamic model, the tire slip and longitudinal force were estimated by a combination of tire mechanical model and UKF algorithm. Then Slip-slope of different road friction coefficient was obtained. A mapping relationship between several typical road friction coefficient and Slip-slope was built. By constructing various ground test environment with different road friction coefficient using the Road Builder in ADAMS/Car, the estimation method proposed was verified to be effective and reliable. Moreover, the simulation results indicated that Slip-slope theory is also applicable in the virtual test under the ADAMS/Car environment.
作者 林棻 黄超
出处 《哈尔滨工业大学学报》 EI CAS CSCD 北大核心 2013年第7期115-120,共6页 Journal of Harbin Institute of Technology
基金 国家自然科学基金资助项目(10902049) 中国博士后科学基金资助项目(2012M521073)
关键词 汽车动力学控制 附着系数 汽车状态估计 Unscented卡尔曼滤波(UKF) 虚拟实验 vehicle dynamic control friction coefficient vehicle state estimation Unscented Kalman Filter(UKF) virtual test
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参考文献13

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二级参考文献12

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