Modular Dynamometer Testing Framework to Evaluate Energy Impacts of Longitudinal Automated Driving Systems

As longitudinal Automated Driving System (ADS) technologies, such as Adaptive Cruise Control (ACC), become more prevalent, robust testing frameworks that encompass both simulation and vehicle-in-the-loop (VIL) methodologies are essential to ensure system reliability, safety, and performance refinement. Although significant research has focused on ACC algorithm development and simulation testing, existing VIL dynamometer testing frameworks are typically tailored to specific vehicle models and sensor simulation tools. These highly customized approaches often fail to account for broader interoperability while overlooking energy consumption as a key performance metric. This paper presents a novel modular framework for ACC dynamometer testing, designed to enhance interoperability across a diverse range of vehicle platforms, simulation tools, and dynamometer facilities with a focus on evaluating impact of automated longitudinal control on the overall energy consumption of the vehicle. The platform leverages a standardized interface to facilitate seamless communication between the simulation environment, vehicle control systems, and the dynamometer. This interface synchronizes virtual test environments with physical dynamometer setups, enabling versatile testing configurations and allowing any vehicle to be evaluated within the simulation environment of choice, tested under the driving scenario of choice. The framework’s architecture and the standard interface are detailed, alongside initial experimental results that demonstrate improvements in testing efficiency, flexibility, and a brief energy performance evaluation. In Spring 2025, the framework will be utilized in a multi-vehicle study to assess the energy efficiency of 13 university-developed ACC systems as part of the U.S. Department of Energy’s EcoCAR EV Challenge. The platform’s adaptability is expected to contribute to more standardized and energy-focused ACC testing.