基于双自适应Kalman滤波的线控转向汽车传感器故障诊断  

Sensor Fault Diagnosis for Steer-by-Wire Car Based on Dual Adaptive Kalman Filter

作　　者：田承伟[1] 宗长富[1] 姜国彬[1] 王祥[1] 何磊[1] 

机构地区：[1]吉林大学汽车动态模拟国家重点实验室,吉林长春130025

出　　处：《中国公路学报》2009年第4期115-121,共7页China Journal of Highway and Transport

基　　金：国家高技术研究发展计划("八六三"计划)项目(2006AA110102);国家自然科学基金项目(50775096)

摘　　要：为了解决相对于传统转向系统而言的结构改变带来的可靠性和安全性问题,对线控转向系统主要传感器的故障诊断方法进行了研究。在建立线控转向系统和整车联合动力学模型的前提下,以基于假设检验的双自适应渐消Kalman滤波技术为平台,结合根据各传感器工作状态确定的故障特征向量,构建了线控转向汽车主要传感器的残差门限故障诊断方法,并利用现有的线控转向系统试验台进行了硬件在环仿真验证。结果表明:该方法可以应用到线控转向汽车传感器的故障诊断中,达到了提高系统可靠性和安全性的目的。In order to solve the problem of reliability and safety that relates to the structural changes compared with traditional steering system, the fault diagnosis method of steer-by-wire （SBW） system key sensors was studied. Based on the SBW system and whole car united vehicle dynamic model, regarded dual adaptive fading factor Kalman filter technology with supposing test as platform, combined with the fault feature vectors which were decided according to the work status of every sensor, authors designed a residual scrutiny fault diagnosis method of SBW system key sensors, and made a hardware in the loop simulation validation with the SBW system test rig. Results show that the method can be applied to a fault diagnosis of the SBW system sensors, and can achieve the purpose of improving system reliability and safety.

关 键 词：汽车工程 线控转向系统 双自适应Kalman滤波 残差门限故障诊断 传感器 

分 类 号：U472.42[机械工程—车辆工程]