Multibody parameter estimation: a comprehensive case-study for an innovative rear suspension 2022-36-0059
Numerical and virtual simulation of mechanical systems is a standard part of product development in the automotive sector, and multibody techniques are a consolidated tool to describe vehicle dynamics, elasto- kinematic behavior, handling, and comfort. To achieve high precision results as output of simulations, it is essential to provide the system with reliable data as input, and to accurately describe the vehicle and its subsystems. The task of gathering objective parameters to fully describe a vehicle can seem trivial to the stakeholders directly connected to a project, that can access detailed design data and a plethora of schemes and datasheets covering all subsystems of a vehicle. However, whenever this task regards benchmarking, prototyping, research projects or niche/low-volume products, data availability decreases drastically, and alternative forms of data acquisition become essential. This paper proposes a comprehensive overview of data gathering and experimental procedures used to reliably extract parameters of an existing vehicle using quick and accessible strategies. The analysis is based on a case-study project of an A-segment vehicle mounted with an innovative rear suspension scheme, whose behavior should be described by a dedicated elasto- kinematic multibody model as well as a full vehicle model for dynamic validation. The multibody model is based on Adams/Car with the inclusion of flexible elements, which is briefly described, while a closer focus is given to the experimental extraction of key features, such as: total mass, longitudinal and lateral position of the center of gravity, CoG height, wheel travel and wheel rate, shock-absorber damping coefficient, steering ratio, components inertia and flexible elements strain. The results obtained in the static and dynamic experimental validation suggest a good outcome from the methodology, that can be replicated on many kinds of vehicle modelling activities as an approachable and affordable experimental methodology for small projects.
Citation: de Carvalho Pinheiro, H., Messana, A., Carello, M., and Rosso, N., "Multibody parameter estimation: a comprehensive case-study for an innovative rear suspension," SAE Technical Paper 2022-36-0059, 2023, https://doi.org/10.4271/2022-36-0059. Download Citation