【摘要】 为解决储能电站中光电式感烟探测器易受粉尘、水雾等非火灾气溶胶干扰而误报的问题，构建EC-DEC、EC-DMC和EC-DEC-DMC 3种锂离子电池电解液烟雾模型、正庚烷烟雾模型以及粉尘和水雾2种典型干扰气溶胶模型，模拟储能电站内可能出现的火灾与干扰场景。采用Mieplot和DDA 2种光散射模拟方法，计算并分析颗粒物的光散射矩阵，从光散射偏振特性出发，系统探究火灾烟雾与干扰气溶胶的识别特征。研究结果表明：在2种波长下，利用光散射矩阵元素F₁₁/F₁₁（30°）的前向散射峰值差异，均可有效区分干扰气溶胶、正庚烷烟雾与电解液烟雾，并给出相应的判定阈值；在0.633μm波长下，利用特定散射角范围内的光散射矩阵元素-F₁₂/F₁₁特征参量，可以进一步辨识火灾烟雾与干扰气溶胶；基于此，提出1种具备高可靠性的双参数辨识方法，建议在储能电站单波长探测系统中优先采用0.633μm波长，基于F₁₁/F₁₁（30°）与-F₁₂/F₁₁的双特征冗余判定体系来抑制误报。研究结果可为储能电站火灾烟雾探测的抗干扰设计提供理论与技术支持。更多还原

【Abstract】 In order to solve the problem that the photoelectric smoke detector in the energy storage power station is susceptible to the interference of non-fire aerosols such as dust and water mist, this study constructed three lithium-ion battery electrolyte smoke models of EC-DEC,EC-DMC and EC-DEC-DMC,an n-heptane smoke model and two typical interference aerosol models of dust and water mist, simulating potential fire and interference scenarios within the station.Based on the two light scattering simulation methods of Mieplot and DDA,the light scattering matrix of the above particles was calculated and analyzed.Based on the polarization characteristics of light scattering, the identification characteristics of fire smoke and interfering aerosols were systematically explored.The results indicate that at both investigated wavelengths, the forward scattering peak differences of F₁₁/F₁₁（30°） can effectively distinguish interfering aerosols, n-heptane smoke, and electrolyte smoke, and the corresponding decision thresholds are provided.At the 0.633 μm wavelength, the characteristic parameter-F₁₂/F₁₁ within specific scattering angle ranges allows for the further identification of fire smoke and interfering aerosols.Based on these findings, this paper proposes a highly reliable dual-parameter identification method and suggests that the 0.633 μm wavelength be prioritized in single-wavelength detection systems for energy storage power stations, utilizing a dual-feature redundancy decision system based on F₁₁/F₁₁（30°） and-F₁₂/F₁₁ to suppress false alarms.These research results are expected to provide theoretical and technical support for the anti-interference design of fire smoke detection in energy storage power stations.更多还原