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孙权,王友仁,吴祎,姜媛媛.基于无迹粒子滤波的功率变换器剩余寿命预测方法[J].电源学报,2019,17(5):197-202
基于无迹粒子滤波的功率变换器剩余寿命预测方法
Remaining Useful Life Prediction Method for Power Converters Based on Unscented Particle Filter
投稿时间:2017-08-04  修订日期:2018-10-09
DOI:10.13234/j.issn.2095-2805.2019.5.197
中文关键词:  功率变换器  特征参数  无迹粒子滤波  剩余寿命预测
英文关键词:power converter  characteristic parameter  unscented particle filter(UPF)  remaining useful life prediction
基金项目:国家自然科学基金资助项目(61371041);江苏省普通高校研究生科研创新计划资助项目与中央高校基本科研业务费专项资金资助项目(KYLX_0250)
作者单位E-mail
孙权 南京航空航天大学自动化学院, 南京 211106 seque l2005@163.com 
王友仁 南京航空航天大学自动化学院, 南京 211106  
吴祎 南京航空航天大学自动化学院, 南京 211106  
姜媛媛 南京航空航天大学自动化学院, 南京 211106  
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中文摘要:
      针对功率变换器难以准确建立表征其性能退化过程的物理模型,提出一种基于无迹粒子滤波的方法实现其剩余寿命预测。首先,通过分析电路关键元器件退化对电路性能的影响,选取输出电压均值作为寿命表征参数;其次,依据电路性能退化历史数据,采用无迹粒子滤波进行故障趋势建模;最后,逐步递推预测寿命特征参数值并结合电路失效阈值从而实现功率变换器剩余寿命预测。以闭环SEPIC电路为例,分析了建模数据规模对预测性能的影响,并与卡尔曼滤波方法进行对比分析,其结果验证了所提方法的有效性及准确性。
英文摘要:
      Aiming at the difficulty in establishing an accurate physical model of a power converter that represents the degradation process, a method based on unscented particle filter(UPF) is proposed in this paper to realize the rema-ining useful life(RUL) prediction. First, through the analysis of influences on the circuit performance due to the degrada-tion of key circuit components, the average output voltage is selected as the characteristic parameter of useful life. Then, UPF is used to perform modeling on the fault trend based on the history data of circuit performance degradation. Finally, the RUL prediction of the power converter is realized by step-by-step recursion of characteristics with the combination of the circuit's failure threshold. A closed-loop SEPIC circuit is taken as an example, and the influences of modeling data size on the prediction performance are analyzed. In addition, the effectiveness and accuracy of the proposed method are verified in comparison with the Kalman filter(KF) method.
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