Browse Publications Technical Papers 2019-36-0091

Parameterization Study of a Driveability Maneuver 2019-36-0091

With the evolution of technological resources as tools for industrial development, it became possible to simulate various components and mechanisms to premeditate evaluations in the virtual environment even before the construction of the first prototype. In the automotive industry, engineers have personal challenge of predicting vehicle behavior in early stages of project development, when it is extremely important to have assertive assessments for the construction of significant physical specimens, improving parameters such as quality and reliability. However, the simulated performance’s objective values often do not provide quantified values in a subjectively way for drivers. The work in question proposes the study and elaboration of a simple vehicle model from a well-structured dynamic model, with information detailing in the powertrain and drivetrain assemblies, considering these as the main mechanisms to promote longitudinal acceleration. This model was simulated in order to obtain data for a comparison with parameters from a real test, in which there were done the same maneuvers under equal conditions of execution. Considering the first loop’s results, there were modified the clutch letter, tire letter and engine’s inertia parameter, in view of a better correlation with the experimental data. Through these betterments, there were achieved more consistent curves related to the rotational engine speed, vehicle speed and longitudinal acceleration, however the engine torque curve presented a considerable nonconformity, due to, e.g., an idealized efficiency coefficient in the powertrain group. Due to the fact that the longitudinal acceleration is the main parameter for driveability assessment and its curve’s consistency in the simulation, it was concluded that the simulation produced significant results. Thus, it was possible to approximate the simulated model to the actual vehicle behavior, obtaining equivalent and coherent answers that validate the model as a testing tool and future subjective evaluations concerning, e.g., the driveability area.


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