光纤传感技术在电池荷电状态/健康状态监测中的研究进展
摘要： 【目的】随着电池和超级电容器等储能设备在全球范围内的广泛应用，对其性能进行实时在线监测变得愈发关键，电池传感系统的重要性也在日益凸显。传统传感器容易受到电磁干扰，而光学传感器具有减少电磁干扰、体积小、重量轻等优点，能明显提高估算荷电状态(state of charge，SOC)和健康状态(state of health，SOH)的准确性。【方法】详细介绍了光纤倏逝波传感器、光纤布拉格光栅传感器、光纤局域表面等离子体共振传感器的工作原理及其应用实例。此外，还探讨了如何利用先进的数据处理技术和算法，从大量原始数据中提取有价值的信息，以进一步优化电池性能、预测故障并提升整体系统效率。【结果】通过应用先进的数据分析技术，如特征选择、模式识别和预测建模等，能够有效提升对电池性能的理解，提前发现潜在问题，从而增强系统的整体性能和安全性。【结论】未来的研究应集中在进一步提高传感器本身的性能，包括灵敏度、稳定性和成本效益；同时也要加强数据处理算法的发展，以更好地适应快速变化的市场需求。
关键词: 光纤传感技术, 电池管理系统, 荷电状态(SOC), 健康状态(SOH), 光纤布拉格光栅, 数据处理技术
Abstract: [Objectives] With the widespread application of energy storage devices such as batteries and super capacitors globally, real-time online monitoring of their performance has become increasingly critical, and the importance of battery sensing systems is also becoming more evident. Traditional sensors are easily affected by electromagnetic interference, while optical sensors have the advantages of reducing electromagnetic interference, small size, and light weight, which can significantly improve the accuracy of estimating SOC and SOH. [Methods] The working principles and application examples of fiber evanescent wave sensors, fiber Bragg grating sensors, and fiber local surface plasmon resonance sensors are introduced in detail. In addition, it also explores how to use advanced data processing technologies and algorithms to extract valuable information from a large amount of raw data to further optimize battery performance, predict failures and improve overall system efficiency. [Results] By applying advanced data analysis technologies, such as feature selection, pattern recognition, and predictive modeling, it is possible to effectively improve the understanding of battery performance and identify potential problems in advance, thereby enhancing the overall performance and safety of the system. [Conclusions]. Future research should focus on further improving the performance of the sensor itself, including sensitivity, stability and cost-effectiveness; at the same time, it should also strengthen the development of data processing algorithms to better adapt to rapidly changing market needs. Key words: text-align:justify, ">batter, fiber sensing technology, battery management system, state of charge (SOC), state of health(SOH), fiber bragg grating, data processing technology相关知识
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