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There is a need to enable the evaluation of ascending vehicle technologies such as the electrified powertrain and the driving assistance systems with low cost and low risk resources. In a context of ever stringent requirements for developing new vehicles, system and production complexities lead to high capital expenses required to ensure serial production will be implemented. One of such complexities is the interdependency between power delivery and dynamic control, which creates trade-offs in the treatment of performance and safety parameters. Virtual models still provide intermediate-level resources, and test platforms have limitations to verifying dynamic parameters; against this situation, scale vehicle platforms provide a low cost and low risk alternative for the implementation of innovative technologies based on integrated systems for improving vehicle performance and safety.

Currently, large companies as well as universities have increased the studies into vehicular dynamic behavior, mainly in order to improve driver and passenger safety. Simulations with complete model vehicle have been used for these studies. The tire is one of the most important vehicular component as the only connection with the ground and responsible for transmitting all vertical, longitudinal and lateral forces, consequenetly it is the main component on the model vehicle, being crucial for the correlation between computer simulations results and field tests, This paper presents a methodology, development and construction of a device to obtain lateral forces in any combination of toe and camber angles for different conditions of normal load, the tests can be performed on any type of ground, whether dry or wet. The tire datas used as reference were obtained through an experimental test using “Flat Trac” equipment.

Lap time simulator (LTS) is a simulation tool used by racing teams to estimate lap time for a given vehicle setup, such as in Formula 1, Indy and Le Mans. This work employs a Formula SAE (FSAE) oriented LTS called OptimumLap, which uses a quasi-steady state method, to simulate prototype cars from Centro Universitário FEI. A MATLAB code has been created to simulate acceleration race and compare this result to OptimumLap. The latter has also been used to simulate skid pad and autocross events. RS8 simulation results have been compared to Michigan 2014 FSAE competition elapsed times for model validation. After validation of RS8 model, the new prototype RS9 was simulated in order to predict its performance; finally the results and the behavior of these two vehicles were compared.

This paper shows the elaboration of studies about the driver’s comfort in a Baja SAE vehicle in different track conditions. The multibody model was designed in ADAMS VIEW software with full vehicle components aim evaluate frequencies, accelerations and displacements in any part of the vehicle. Several tests and measurements were made to acquire springs, dampers and tire data to ensure the model represents the real vehicle. The full vehicle and also the driver were modeled through a CAD software, thus all geometries, mass and inertias were inputted in the multibody model based on the built vehicle. The vertical displacements were modeled in the multibody software simulating the road profile, so it was possible to analyze the vehicle ride behavior with different set ups in different tracks. The validation of multibody mathematical model was made by modeling the same maneuver that the vehicle instrumented with data acquisition was submitted.

This paper shows the elaboration of studies about the driver’s comfort in a Baja SAE vehicle in different track conditions. The multibody model was designed in ADAMS VIEW software with full vehicle components aim evaluate frequencies, accelerations and displacements in any part of the vehicle. Several tests and measurements were made to acquire springs, dampers and tire data to ensure the model represents the real vehicle. The full vehicle and also the driver were modeled through a CAD software, thus all geometries, mass and inertias were inputted in the multibody model based on the built vehicle. The vertical displacements were modeled in the multibody software simulating the road profile, so it was possible to analyze the vehicle ride behavior with different set ups in different tracks. The validation of multibody mathematical model was made by modeling the same maneuver that the vehicle instrumented with data acquisition was submitted.