Abstract: To address the core problems of long development cycle, high maintenance cost and low matrices. A parsing tool converts DBC files from different suppliers into standard JavaScript object notation (JSON) configuration files, and assigns a globally unique logical index to each functional signal, so as to realize complete decoupling between the application layer and physical layer signal positions. During T-BOX operation, corresponding configuration files are dynamically loaded according to vehicle identification codes. The parsing engine accurately extracts signal values based on the configurations, and processes and distributes the signals by classification in accordance with three signal models: event, alarm and status. Upper-layer applications only need to subscribe to fixed logical indexes to shield the heterogeneity of underlying CAN protocols. Experimental results show that the proposed scheme reduces the adaptation cycle for new vehicle models from 40 person-days in traditional schemes to 3 person-days, and decreases the central processing unit (CPU) occupancy rate of the signal parsing module by 62.3%. In cross-vehicle switching tests, upper-layer applications operate normally without any modification. The method effectively improves development efficiency, system maintainability and scalability, and provides a feasible solution for the platform-based and standardized development of intelligent connected vehicles. platformization caused by inconsistent controller area network (CAN) communication matrices when intelligent connected vehicle terminals are adapted to different vehicle models, this paper proposes a T-BOX platform design method based on signal ID decoupling and dynamic configuration loading. The core of the method is to construct a signal parsing middleware abstracted from specific CAN

Key words: intelligent connected vehicles; T-BOX; platform design; signal decoupling; dynamic configuration; JSON parsing

摘要： 针对当前智能网联汽车终端在适配不同车型时，因控制器局域网（CAN）通信矩阵差 异导致的开发周期长、维护成本高昂及平台化程度低的核心问题，文章提出了一种基于信号 标识解耦与动态配置加载的车载 T-BOX 平台化设计方法。该方法的核心在于构建一个抽象于 具体 CAN 矩阵之上的信号解析中间件。通过解析工具将不同供应商的 DBC 文件转换为标准 化的 JavaScript 对象表示法（JSON）配置文件，并为每个功能信号分配全局唯一的逻辑索引 值，从而实现应用层与物理层信号位置的彻底解耦。T-BOX 运行时根据车辆标识码动态加载 对应配置文件，解析引擎依据配置精准提取信号值，并基于事件、告警、状态三类信号模型 进行分类处理与发布，上层应用仅需订阅固定的逻辑索引，即可屏蔽底层 CAN 协议的异构性。 实验结果表明，该方案将新车型的适配周期从传统方案的 40 人天显著缩短至 3 人天，信号解 析模块的中央处理器（CPU）占用率降低 62.3%，且在不同车型切换测试中，上层应用无需 任何修改即可正常运行，有效提升开发效率、系统可维护性与扩展性，为智能网联汽车平台 化、标准化开发提供了可行方案。

关键词: 智能网联汽车；T-BOX；平台化设计；信号解耦；动态配置；JSON 解析