MBSE-Driven XIL Workflow for Energy Evaluation of Automated Vehicles: From Simulation to VIL Testing

This paper presents a Model-Based Systems Engineering (MBSE)-driven X-in-the-Loop (XiL) methodology for quantifying the energy impacts of automated vehicles in realistic road scenarios while preserving high-fidelity powertrain behavior. We developed Argonne’s multi-vehicle simulation tool, RoadRunner, which automatically builds closed-loop road scenarios (road geometry, vehicle sensors, other vehicles, and traffic controls) and connects them to Argonne’s validated, high-fidelity vehicle and powertrain models in Autonomie. The MBSE backbone in AMBER organizes requirements, interfaces, plant and controller models, and test scenarios into a single set of models that carries through pure simulation, Software-in-the-Loop (SiL), Processor-in-the-Loop (PiL), and Vehicle-in-the-Loop (ViL) stages. Each stage has a clear role: simulation enables rapid development and validation of advanced models or controls across a large number of scenarios; SiL supports standalone algorithm verification and scenario down-selection; PiL validates real-time execution and I/O and timing on the target processor; and ViL provides closed-loop evaluation with a real vehicle in controlled laboratory conditions. AMBER’s automated build and configuration enable rapid retargeting across platforms and repeatable scenario reproduction, making validation fast and cost-effective. Using this workflow, we compare an eco-driving control with a calibrated human-driver model across various realistic multi-vehicle scenarios. Experiments show strong repeatability and consistent energy gains for the eco-driving strategy while preserving trip time; average savings of 7-8% were observed across the scenario set. Overall, the MBSE-guided XiL workflow shortens development time and reduces test cost by limiting on-road testing and lowering integration risk before track evaluation, while producing credible, closed-loop energy assessments traceable from requirements to test evidence.