Riassunto analitico
Modern vehicles integrate over seventy Electronic Control Units (ECUs), each responsible for specific functions such as collecting sensor data from the engine and implementing diagnostic capabilities. Automotive diagnostics is essential for various purposes, including fault detection and management, ECU status monitoring, configuration access, and troubleshooting through actuator activation or specific procedures. These diagnostic functions play a crucial role throughout the vehicle's lifecycle: from ECU and vehicle development to manufacturing and post-sale maintenance in repair shops.
Diagnostic access is performed via the On-Board Diagnostics (OBD) connector, which serves as an interface between external Tester Tools and the in-vehicle ECU network. Communication is based on the Unified Diagnostic Services (UDS) protocol, which operates at the application layer of the OSI model. As an application-layer protocol, UDS messages can be transported over different physical and data link layers, the most common being Controller Area Network (CAN) and Ethernet. To define how UDS packets are transmitted over these networks, two intermediate protocols have been introduced: Diagnostics over CAN (DoCAN) and Diagnostics over IP (DoIP).
This thesis aims to provide a general overview of automotive diagnostics and a comprehensive analysis of UDS, DoCAN, and DoIP protocols, explaining their structure, message formats, and practical implementation. The core contribution of this work is the development of DoX (Diagnostics over X), a configurable, flexible, and user-friendly diagnostic platform based on Raspberry Pi. DoX can either work as a UDS Tester Tool or simulate any ECU for testing scenarios that are difficult to achieve with standardized diagnostic devices.
DoX represents a valuable tool for automotive testing engineers, providing a versatile and cost-effective solution for ECU diagnostics and validation. Its configurability allows users to create complex test scenarios beyond the limitations of traditional diagnostic tools. While already functional, DoX has numerous potential improvements that could further enhance its capabilities, making it an even more powerful and adaptable tool for future automotive testing applications.
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