基于标准结构化数据的TBT异构评估模型研究——以欧美电池法规为例

摘要：

【目的】以标准结构化数据为技术手段，聚焦欧美电池相关技术性贸易壁垒（TBT）异构数据，解决TBT互认中的数据互通、等效判定等问题，提升欧美法规差异识别准确率与电池数据适配精度，完善TBT互认理论体系，为提升跨境贸易便利化水平提供实践参考。【方法】提出基于标准结构化数据的异构性分析方案，核心是建立标准法规的结构化解析、映射与适配机制，构建结构化数据驱动的TBT异构评估模型（SSTD-TBT模型），将欧美电池相关TBT标准法规转化为机器可读取、可计算的结构化数据，分析标准法规中的异构性表现及量化方法，推导异构数据映射与等效判定方法。【结果】SSTD-TBT模型实现了欧美电池相关TBT标准法规向机器可读取、可计算的结构化数据转化，提出的异构数据映射与等效判定方法，有效支撑了欧美法规电池数据差异识别，为提升相关判断的准确性奠定了基础。【结论】结构化数据驱动的TBT异构评估模型（SSTD-TBT模型），可有效提升TBT互认中相关数据处理与等效判定的效率和准确性，为电池领域跨境贸易便利化提供实践支撑。

Abstract:

[Objective] Taking standard structured data as the technical means, this paper focuses on the heterogeneous data of Technical Barriers to Trade (TBT) related to batteries in Europe and the United States, aiming to solve problems such as data interoperability and equivalence judgment in TBT mutual recognition, improve the accuracy of identifying differences between European and American regulations and the precision of battery data adaptation, improve the theoretical system of TBT mutual recognition, and provide practical references for enhancing the level of cross-border trade facilitation. [Methods] A heterogeneity analysis scheme based on standard structured data is proposed. Its core is to establish a structured parsing, mapping and adaptation mechanism for standards and regulations, construct a structured data-driven TBT heterogeneity evaluation model (SSTD-TBT Model), convert the TBT standards and regulations related to batteries in Europe and the United States into machine-readable and computable structured data, analyze the manifestations and quantitative methods of heterogeneity in standards and regulations, and deduce methods for heterogeneous data mapping and equivalence judgment. [Results] The SSTD-TBT Model has realized the conversion of TBT standards and regulations related to batteries in Europe and the United States into machine-readable and computable structured data. The proposed heterogeneous data mapping and equivalence judgment methods effectively support the identification of differences in battery data between European and American regulations, laying a foundation for improving the accuracy of relevant judgments. [Conclusion] The structured data-driven TBT heterogeneity evaluation model (SSTD-TBT Model) can effectively improve the efficiency and accuracy of relevant data processing and judgment in TBT mutual recognition, and provide practical support for the facilitation of cross-border trade in the battery field.

引用格式：唐成，宋安利. 基于标准结构化数据的TBT异构评估模型研究——以欧美电池法规为例[J]. 标准化学报，2026(8)：38-45.

作者简介：唐成，硕士，高级工程师，研究方向为标准数字化、区块链、数字经济。宋安利，硕士，副编审，研究方向为国家标准审查、大数据与网络安全。