Toward Automated Virtual Electronic Control Unit (ECU) Twins for Shift-Left Automotive Software Testing
This work addresses the late integration and expensive hardware-in-the-loop bottlenecks in automotive software testing by enabling early virtual testing, though it is an incremental step with cloud-scale deployment and full toolchain integration remaining as future work.
The InnoRegioChallenge project developed a prototype for automated virtual ECU twins that generate instruction-accurate processor models in SystemC/TLM 2.0, enabling early software testing before physical hardware exists. The results show that CPU behavioral fidelity can be reduced through automated differential testing and iterative model correction, demonstrating a viable shift-left path for automotive software testing.
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 discuss the technical approach in a manner 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.