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This paper focused on pedal feeling studies at most often longitudinal decelerations for the normal daily usage of customers. Such decelerations were defined in vehicle equipped with sensors in a specific itinerary near Resende/Penedo city (southeastern Brazil) with several clients using the same vehicles. Through the decelerations acquired, one could correlate, objectively and subjectively, the pedal effort and travel that delight the customers, reaching the so called ideal pedal feeling. The mapping provides the needed input data to develop, or adapt, a vehicle to the best condition expected by consumers.

Nowadays, the influence of aerodynamics on vehicles capabilities is mostly studied in terms of energy efficiency; maximum speed; maximum linear accelerations; cooling capacity of brake systems; resistance and deformation of elements exposed to aerodynamic forces; stability during lateral wind and during braking for straight ahead maneuvers; noise caused by airflow; proper evacuation of exhaust gases and aesthetics of cars. Generally, a model for CFD analysis is used and six constant coefficients are determined. However, there is insufficient information about the interaction of vehicle aerodynamics with vehicle suspension and the effects that this interaction generates on the dynamic behavior of the vehicle. In this work this interaction is studied, and there is an analysis of how vehicle aerodynamic characteristics impact on suspension behavior and how suspension characteristics could diminish or amplify aerodynamic.

The lateral drift of a vehicle while driving straight ahead has been a major concern of the OEMs on the South America market. Due to its natural way to evaluate and also to different types of roads on the market (roads with different types of bank angle), a vehicle with slight tendency to drift will certainly be a reason of customer complaint. Since such a vehicle dynamics property is very sensible to small variation of some parameters, such as road bank angle, alignment setting, etc, sometimes the subjective evaluation tends to become worthless due to the parameters control. In this scenario, simulation becomes important. As it is a quite difficult subject, since there is big influence of small parameters variation, the usage of statistical approach allow to obtain better understanding of the phenomenon. This work presents a statistical approach for simulation based on DOE analysis and Monte Carlo method.

Functional vehicle dynamics simulation differs from the regular multi-body simulation especially by means of modeling parameters. The models are usually parametric, involving suspension properties that are commonly used by OEM's. Input data for a multi-body simulation (MBS) is, normally, raw information about suspension hard points coordinates, flexible elements stiffness (such as bushing and springs), etc. As for a functional simulation, the input data can be one outcome of a multi-body one, such as K&C data or even measured data of a bench test. However, the results of both ways of simulation must be the similar. Functional simulation software does not solve the multi-body equations for each integration step as any regular MBS software and, as such, can run the model in a faster way. In this way, software-in-the-loop and hardware-in-the-loop starts to become a clear advantage of these art of simulation.

Nowadays is a common sense the importance of the CAE usage in the modern automotive industry. The ability to predict the design behavior of a project represents a competitive advantage. However, some CAE models have become so complex and detailed that, in some cases, one just can not build up the model without a considerable amount of information. In that case simplified models play an important role in the design phase, especially in pre-program stages. This work intends to build an archetypal vehicle dynamics model able to predict the rollover resistance of a vehicle design. Through the study of a more complex model, carried out in Adams environment, it was possible to identify the key degrees of freedom to be considered in the simplified model along with important elements of the suspension which are also important design factors.

The competition of the market pushes the automotive industry to a continuous evolution of the performance, durability and safety for the current vehicles, balancing them with a competitive price and launch time, using new technologies, in a wide range of disciplines. Among these disciplines, it is possible to highlight the durability, which cares for the various parts of cars that are structurally feasible, considering criteria for usage, safety and life (DAKIN, 2001). Basically, a durability team has available three methodologies for the assessment of structural parts developed: Test Track, Workbenches and Numeric Simulations. Test Tracks, the oldest of the three methodologies, allows a correlation with the usage of the product by the final consumer. However, the introduction of the Workbenches makes the test environment more controlled, reducing the number of the involved variables, and thus reduces the time to test and improve the quality of results (GROTE, 2000).

Among the development phases of an automotive vehicle one can point out the definition of the main characteristics of its suspensions like for example the suspension kinematics and compliances properties. Suspension definition phase can be understood as the following scenario: given a suspension type, which hard points (geometric) and what values of stiffness for the whole system will result in a desired dynamic behavior for the vehicle as well as production feasibility. This present work intends to show the influence of some suspension properties on the global dynamic behavior of the vehicle, having as a target an efficient suspension design. In terms of global dynamic behavior this work point out some control parameters, which describe the vehicle transient and steady-state properties. Those parameters are: Yaw phase lag, understeer gradient, Steady state acceleration gain and yaw overshoot during a maneuver like brake in a turn and power-off in a curve.