High Fidelity Multibody Vehicle Dynamics Models for Driver-in-the-Loop Simulators

Abstract

Modern Driver-in-the-Loop simulators are sophisticated engineering tools that have been developed within Motorsport to support the development and optimization of race cars in Formula 1, NASCAR and Indycar. At the heart of the simulator is the vehicle model which has to accurately capture the behavior of the whole car. Modelica based vehicle models are used by many of the top teams because it enables a multi-domain vehicle model to be used in the simulators and support all the other simulation activities within the team. These technologies are now being deployed into road car applications which presents a number of additional challenges. One of the major differences is the need to include bushes within the suspension. This paper presents a number of the recent developments in Modelica based vehicle dynamics models for both Motorsport and road car applications including new suspension models with bushes, integration with tools to provide high fidelity LiDAR road data and real-time simulation of these models.

Virtual Testing of Automated Driving Systems. A Survey on Validation Methods

“…Mainly used for controller synthesis and for simulations where detailed vehicle modeling is not required such as microscopic traffic studies; medium-fidelity: chassis models such as single-track, double-track, and lumped mass [47] with linear or nonlinear tires. Their range of application spans from the synthesis of model predictive controllers [31], [109] to intermediate fidelity simulations involving the testing and prototyping of ADAS/ADS functionalities; high-fidelity: multibody models [110], [111] including suspensions geometry, chassis compliance, engine mounting stiffness and damping characteristics, driveline dy-namics, and tires contact points to provide the ultimate degree of faithfulness. Concerning VV&UQ methods, a survey addressing the estimation of the uncertainty content in vehicle dynamics simulation models was proposed [73] which identifies four key aspects originating the uncertainty:…”