所属单位：自动化学院
发表刊物：Diangong Jishu Xuebao
摘要：The health condition assessment for key components based on characteristic parameter estimation is one of the most significant technologies for circuit-level prognostics and health management (PHM). However, changes in operating temperature can lead to inconsistencies in the estimated values of characteristic parameters and their failure criteria (at 25 degrees Celsius), resulting in inaccurate condition evaluation. Therefore, for the non-ideal Boost converter, firstly, this paper provides the values of characteristic parameters by particle swarm optimization (PSO) algorithm. Then, the mathematical models of the characteristic parameters and operating temperature for electrolytic capacitor and power MOSFET are established, respectively. Meanwhile, the normalized factor (NF) and health index (HI) are defined in this paper. Finally, to achieve health condition assessment under various temperature conditions, a novel approach of updating the model parameters dynamically based on unscented particle filter is proposed. In addition, experimental results show that the parameter identification error is less than 5% and the health evaluation accuracy is over 90%. © 2018, Electrical Technology Press Co. Ltd. All right reserved.
ISSN号：1000-6753
是否译文：否
发表时间：2018-03-25
合写作者：Sun, Quan,Jiang, Yuanyuan,Shao, Liwei
通讯作者：Sun, Quan,王友仁
发表时间：2018-03-25