完整的J2178文档。 This document consists of four parts, each published separately. SAE J2178-1 (Titled: Detailed Header Formats and Physical Address Assignments) describes the two allowed forms of message header formats, Single Byte and Consolidated. It also contains the physical node address range assignments for the typical sub-systems of an automobile. SAE J2178-2 (Titled: Data Parameter Definitions) defines the standard parametric data which may be exchanged on SAE J1850 (Class B) networks. The parameter scaling, ranges, and transfer functions are specified. Messages which refer to these parametric definitions shall always adhere to these parametric definitions. It is intended that at least one of the definitions for each parameter in this part matches the SAE J1979 definition. SAE J2178-3 (Titled: Frame IDs for Single Byte Forms of Headers) defines the message assignments for the single byte header format and the one byte form of the consolidated header format. SAE J2178-4 (Titled: Message Definition for Three Byte Headers) defines the message assignments for the three byte form of the consolidated header format.

给出了SAE-1939J CAN高层协议的各层国家标准，压缩包里有7个文件，供有需要的同仁下载。

ISO/SAE 21434

SAE J1939中文版协议： SAE J1939 串行控制通信汽车网络的推荐操作规程 SAE J1939-11 物理层—250K位/秒，屏蔽双绞线 SAE J1939-13 非车载诊断连接器 SAE J1939-15 简化物理层，250K位/秒，非屏蔽双绞线（UTP） SAE J1939-21 数据链路层 SAE J1939-31 网络层 SAE J1939-71 车辆应用层 SAE J1939-73 应用层—诊断 SAE J1939-81 网络管理协议

SAE-J1939标准整理.pdf

IEEE-1394b Interface Requirements for Military and Aerospace Vehicle Applications

单线CAN总线网络在车辆上的应用

ISO SAE 21434中文版

为了提高情感识别的分类准确率，提出一种将栈式自编码神经网络（SAE）和长短周期记忆单元循环神经网络（LSTM RNN）融合的多模态融合特征情感识别方法。该方法通过SAE对不同模态的生理特征进行信息融合和压缩，随后用LSTM RNN对长时间周期的融合进行情感分类识别。通过将该方法用到开源数据集中进行验证，得到情感分类准确率达到0.792 6。实验结果表明，SAE对多模态生理特征进行了有效融合，LSTM RNN能够有效地对长时间周期中的关键特征进行识别。

车辆信息安全标准ISO SAE 21434 Road vehicles — Cybersecurity engineering不同版本： 包括2018 CD stage版本，2020 DIS版本，2021 FDIS版本以及2021最终发布版