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• A unified reconfigurable vehicle dynamics model is developed in this study. • A novel approach in vehicle modeling is presented to develop the proposed model. • The model can be configured for different four- and three-wheeled vehicles. • Wheels and actuators can readily be added or removed using the defined matrices. • Included actuators are active steering, differential braking and torque vectoring. This study presents a novel approach in vehicle modeling to provide a unified reconfigurable vehicle dynamics model. The introduced vehicle model is applicable for analysis, design, and control of a wide variety of vehicles and can be reconfigured for four- and three-wheeled vehicles. Active steering, differential braking, torque vectoring, and active camber are included in the model as the actuators. The proposed set of model equations is reconfigurable and can be adjusted for various vehicles without need for new derivation. Two matrices are defined called the corner reconfiguration matrix and actuator reconfiguration matrix that are responsible for wheel and actuator configurations of the vehicle, respectively. The model can be reconfigured by setting the diagonal elements of these two matrices. The proposed reconfigurable model is compared with different high-fidelity vehicle models in CarSim for validation. Simulation results show that four-wheeled and three-wheeled vehicle models can all be drawn from the single unified reconfigurable model. In addition, the introduced model properly matches the high-fidelity CarSim models for four-wheeled and three-wheeled vehicles. [ABSTRACT FROM AUTHOR]

• A semi-recursive vehicle model is validated in modeling and accuracy. • Constant and adaptive time-step algorithms for real-time simulation are presented. • An accurate real-time simulation of a vehicle is completed in an affordable laptop. • A benchmark problem for the multibody dynamics community is put forward. Semi-recursive formulations and their various versions have made it possible to describe complex nonlinear systems such as vehicles precisely while still solving the relevant equations of motion in real time. An optimal combination of an efficient multibody formulation and a fast numerical time integration scheme are needed to accurately simulate complex systems in real time. This paper introduces a double-step semi-recursive multibody formulation and analyzes its performance with high-order numerical time-integration algorithms for real-time simulation. The Runge-Kutta, Gill, Runge-Kutta-Fehlberg, Adams-Bashforth-Moulton, and adaptive time step Runge-Kutta numerical methods are explained and compared. Results are verified against a commercial multibody software solution. A 15-degree-of-freedom sedan vehicle model serves as a benchmark to verify the theoretical results. The results highlight the differences between the numerical algorithms and suggest appropriate approaches for a nonlinear vehicle dynamics model, particularly for cases where simulation times are long. [ABSTRACT FROM AUTHOR]