Toward Automated Virtual Electronic Control Unit (ECU) Twins for Shift-Left Automotive Software Testing

TL;DR

This paper presents a prototype for automated virtual ECU twins using instruction-accurate models in SystemC/TLM, enabling early testing and integration in automotive software development.

Contribution

It introduces an agentic, feedback-driven workflow for generating accurate processor models that can be used before physical hardware is available.

Findings

The prototype reduces CPU behavioral fidelity risks through automated differential testing.

It demonstrates a shift-left approach enabling early, reproducible testing of ECU software.

The approach supports fault-injection and non-intrusive tracing aligned with safety standards.

Abstract

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.