摘要
介绍了基于多传感器信息融合技术的联合卡尔曼滤波器的结构和算法,并将此方法运用于燃料电池发动机多传感器的复杂系统中.理论分析与仿真结果表明,该联合卡尔曼滤波器设计合理,其融合算法具有全局最优性,能够有效地对燃料电池发动机传感器的故障进行检测,改善了系统的容错能力和复原能力,提高了系统运行的稳定性.
The structure and arithmetic of federated Kalman filter based on multisensor information fusion technique is introduced in this paper and applied in the complicated system of fuel cell engine. With the theory analysis and simulation results, it comes to the conclusion that the design of federated Kalman filter is successful, and the algorithm is excellent on the whole. Also, it is efficient in detecting sensors＇ fault of fuel cell engine, which improves the fault-tolerant and recovery capability of system. It makes system work more stable than before.
出处
《华中师范大学学报（自然科学版）》
CAS
CSCD
2006年第1期42-46,共5页
Journal of Central China Normal University：Natural Sciences
基金
国家"863"电动汽车专项课题资助(2001AA501213)
湖北省重大科技攻关项目(2003AA103B)
