在软件定义的车辆中实现未来的车辆诊断功能

Sandra Bickelhaupt, Michael Hahn, Andrey Morozov, Michael Weyrich
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引用次数: 0

摘要

软件将主导未来汽车的开发和生命周期。如今,越来越多的软件被集成到汽车中,使其发展成为软件定义汽车(SDV)。汽车高性能计算机(HPC)通过提供更多可在车内灵活使用的计算基础设施,起到了推动作用。然而,这也导致了复杂的汽车系统需要在当前和未来发挥作用。尽快检测和排除故障至关重要,但现有的基于故障诊断代码(DTC)的诊断方法并非针对如此复杂的系统设计,而且缺乏灵活性。DTC 是在车辆开发过程中预先确定的,要改变车辆诊断方法需要大量的修改工作。此外,诊断系统并非用于处理动态变化的软件系统,在应用于车载软件系统时存在缺陷。在云技术方面,已经有了观察和诊断软件系统的成熟方法。不过,这些方法过于全面,不能简单地应用于整车。无论如何,这些方法对调整车辆诊断很有帮助。因此,需要对它们在车辆上的适用性进行研究。在本文中,我们讨论了将 DTC 方法移植和调整到车载软件系统以及车辆监控和可观测性方法所面临的挑战。在此基础上,我们提出了未来车辆诊断的概念,该概念将基于 DTC 的现有诊断方法与已确立的监控和可观察性方法相结合。我们提出的概念为今后在 SDV 车辆诊断方面开展进一步工作奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Future Vehicle Diagnostics in Software-Defined Vehicles
Software will lead the development and life cycle of vehicles in the future. Nowadays, more and more software is being integrated into a vehicle, evolving it into a Software-Defined Vehicle (SDV). Automotive High Performance Computers (HPCs) serve as enablers by providing more computing infrastructure which can be flexibly used inside a vehicle. However, this leads to a complex vehicle system that needs to function today and in the future. Detecting and rectifying failures as quickly as possible is essential, but existing diagnostic approaches based on Diagnostic Trouble Codes (DTCs) are not designed for such complex systems and lack of flexibility. DTCs are predefined during vehicle development and changes to vehicle diagnostics require a large amount of modification work. Moreover, diagnostics are not intended to handle dynamically changing software systems and have shortcomings when applied to in-vehicle software systems. In the Cloud, there are already established approaches to observe and diagnose software systems. However, these approaches are too comprehensive and cannot simply be applied to the whole vehicle. Anyway, they are a helpful addition to adapting vehicle diagnostics. Therefore, their vehicle applicability needs to be investigated. In this paper, we discuss the challenges of transferring and adapting the DTC approach to in-vehicle software systems, as well as monitoring and observability approaches to vehicles. Based on this, we introduce a concept for future vehicle diagnostics that addresses existing diagnostic approaches based on DTCs in combination with established approaches for monitoring and observability. Our presented concept provides a basis for further future work in the context of vehicle diagnostics for SDVs.
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