Automotive software increasingly outpaces hardware availability, forcing late integration and expensive hardware-in-the-loop (HiL) bottlenecks. The InnoRegioChallenge project investigated whether a virtual test and integration environment can reproduce electronic control unit (ECU) behavior early enough to run real software binaries before physical hardware exists. We report a prototype that generates instruction-accurate processor models in SystemC/TLM~2.0 using an agentic, feedback-driven workflow coupled to a reference simulator via the GNU Debugger (GDB). The results indicate that the most critical technical risk -- CPU behavioral fidelity -- can be reduced through automated differential testing and iterative model correction. We summarize the architecture, the agentic modeling loop, and project outcomes, and we extrapolate plausible technical details consistent with the reported qualitative findings. While cloud-scale deployment and full toolchain integration remain future work, the prototype demonstrates a viable shift-left path for virtual ECU twins, enabling reproducible tests, non-intrusive tracing, and fault-injection campaigns aligned with safety standards.

翻译：汽车软件的发展速度日益超越硬件的可用性，导致集成阶段滞后并产生昂贵硬件在环（HiL）测试瓶颈。InnoRegioChallenge项目研究了一个虚拟测试与集成环境是否能够足够早地复现电子控制单元（ECU）的行为，以便在物理硬件存在之前运行真实的软件二进制文件。我们报告了一个原型系统，它通过基于代理的、反馈驱动的工作流，并借助GNU调试器（GDB）连接到参考模拟器，在SystemC/TLM~2.0中生成指令级精确的处理器模型。结果表明，最关键的技术风险——CPU行为保真度——可以通过自动化的差分测试和迭代式模型修正来降低。我们总结了系统架构、代理建模循环及项目成果，并基于已报告的定性发现推断出合理的技术细节。虽然云规模部署和完整工具链集成仍是未来工作，但该原型为虚拟ECU双胞胎展示了一条可行的左移路径，能够实现可复现的测试、非侵入式追踪以及符合安全标准的故障注入活动。