VDCWorkbench: A Source-Available Modelica Toolbox for Research and Education on Vehicle Dynamics and Control

Kurzfassung

Software-defined vehicles (SDVs) require modular and transparent simulation tools for safety-critical control system development and validation. This paper introduces VDCWorkbench, a source-available Modelica library for vehicle dynamics, control, and energy management, tailored for electric and SDV architectures. The library integrates mechanical, electrical, thermal, and control domains in a unified framework, enabling seamless modeling of battery-electric, hybrid, fuel-cell, and over-actuated by-wire vehicles. The paper demonstrates the versatility of VDCWorkbench through four use cases: (1) Benchmarking of energy management algorithms facilitating the evaluation of diverse energy management strategies for hybrid electric vehicles; (2) Benchmarking of path following controllers, showcasing the library’s ability to compare geometric and predictive control algorithms for automated vehicle guidance; (3) Hybrid reinforcement learning controllers, illustrating how VDCWorkbench can be integrated with data-driven methods, such as residual reinforcement learning, to enhance traditional model-based control approaches; and (4) Educational applications, highlighting its successful integration of the library into university courses to provide hands-on experience in vehicle dynamics modeling and control. The VDCWorkbench library is publicly available on GitHub, offering researchers, engineers, and educators a customizable, transparent, and vendor-independent platform for advancing electric vehicles (EV) dynamics, SDV architectures, and Artificial Inteligence(AI)-driven vehicle control.