光纤传感数据不完备下锂电池荷电状态估计

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关键词：光纤布拉格光栅；锂电池；数据缺失；补全方法；荷电状态估计中图分类号：TM912 文献标志码：A文章编号：2095-8188（2026）02-0001-11DOI：10.16628/j.cnki.2095-8188.2026.02.001

Abstract：In response to the issue of incomplete fiber bragg grating（FBG）sensor data in lithium battery monitoring，a method forFBG straindata completion based onnon-linear independent components estimation （NICE）is proposed.To optimize the annealing parameters in the NICE model，the particle swarm optimization （PSO）algorithm is employed for adaptive parameteroptimization，thereby improving thequalityof data generation. Onthis basis to further enhance theeffctiveness of fiber Bragg grating sensing data in state of charge（SOC） estimation forlithium-ion bateries，an SOC estimation model basedonan attention mechanismand bidirectional gated recurrent unit（Bi-GRU-Att） isconstructed in this work．Experimental results show that the proposed PSONICEalgorithm significantlyreduces the earth mover’sdistance compared to thegenerativeadversarial network （GAN） data generation algorithm at data missing rates of 10% ， 30% 50% ，and 7O%. Notably，at a missing rate of 70%，the EM distance is reduced by 73.41% .Compared with traditional zero-value imputation，the proposed data completion method reduces the root mean square error（RMSE）and mean absolute error（MAE）in SOC estimation by 42.384% and 37.256% ，respectively. The proposed approach provides an effective solution and technical reference for addressing fiber-optic sensing data loss in practical applications.

Key words： fiber bragg grating; lithium batteries；missing data；completion methods； state of charge imation

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