Search Results

SIMON is a new vehicle dynamic simulation model. Applications for SIMON include single- and multi-unit vehicle handling simulation in severe limit maneuvers (including rollovers) and 3-dimensional environments. Applications also include vehicle-to-vehicle and vehicle-to-barrier collisions. This paper provides the technical background for the SIMON engineering model. The 3-dimensional equations of motion used by the model are presented and explained in detail. The calculations for suspension, tire, collision, aerodynamic and inter-vehicle connection forces and moments are also developed. The integration of features available in the HVE Simulation Environment, such as DyMESH, the Driver Model, Brake Designer and Steer Degree of Freedom, is also explained. Finally, assumptions and limitations of the model are presented.

Developers of vehicle dynamics simulation software inherently use a mathematical/physical model to represent the vehicle. This paper describes a pre-programmed, object-oriented vehicle model for use in vehicle dynamics simulations. This vehicle model is included as part of an integrated simulation environment, called HVE (Human-Vehicle-Environment), described in previous research [1,2] *. The current paper first provides a general overview of the HVE user and development environments, and then provides detailed specifications for the HVE Vehicle Model. These specifications include definitions for model parameters (supported vehicle types; vehicle properties, such as dimensions, inertias, suspensions; tire properties, such as dimensions and inertias, mu vs slip, cornering and camber stiffnesses; driver control systems, such as engine, transmission/differential, brakes and steering; restraint systems, such as belts and airbags).

Traditional vehicle simulations use two methods of modeling driver inputs, such as steering and braking. These methods are broadly categorized as “Open Loop” and “Closed Loop”. Open loop methods are most common and use tables of driver inputs vs time. Closed loop methods employ a mathematical model of the driving task and some method of defining an attempted path for the vehicle to follow. Closed loop methods have a significant advantage over open loop methods in that they do not require a trial-and-error approach normally required by open loop methods to achieve the desired vehicle path. As a result, closed loop methods may result in significant time savings and associated user productivity. Historically, however, closed loop methods have had two drawbacks: First, they require user inputs that are non-intuitive and difficult to determine. Second, closed loop methods often have stability problems.