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Vehicle dynamics CAE capabilities has increased in the past few years, specially, for handling and steering attributes. However, secondary ride simulations are still highly depended on the tire model. Such tire model must be capable to simulate high order phenomenon such as impact and harshness transmissibility in three directions. In order to gather tire information sufficient to cope with these phenomena, one needs to perform a series of specific tests, and so be able to build the intended tire model. Still, there could be correlation issues. This whole process takes a lot of time and resources. This article presents a semi-analytical approach, using data gathered via wheel force transducers (WFTs) that are typically used for load cascading and durability purposes. The method main advantage is that since it relies on measured data at the wheel center, it is independent of a tire model, and, as such, it demands less time and resources.

The driver judges his vehicle based on subjective aspects. Vehicle dynamics characteristics including ride and handling have a major impact on this evaluation. For this reason, vehicle manufactures have grown investments in order to improve vehicle dynamics behavior. Subjective evaluation and customer satisfaction research show which dynamic characteristics need to be improved. CAE models, after being validated based on experimental measures, give a good insight on vehicle dynamic behavior and guide change proposals. At end, new subjective evaluations and measures are carried out in order to check the real improvement of CAE proposals. This work shows the use of the described methodology for a pickup vehicle dynamics evaluation. One of the major complains of pickup drives is related to ride quality. Thinking of that feature the evaluation process considers several phenomena, such as abruptness, front topping, front bottoming, head toss and rear aftershake.

Recently, in the automotive industry the usage of CAE models in the development of a product has grown significantly. Virtual models allow the auto makers to speed up the programs and also to predict desired characteristics of the product. However in order to build up a reliable model, capable to reproduce in a detailed manner maneuvers done subjectively, a solid procedure to validate the model as well as a robust tire modeling are required. Once with a model validated, detailed enough at suspension, steering and other sub-systems level, all others sources of variation must come from the tire model. And at this moment, properties of the kind of tire modeling can be pointed out. This work shows one approach to have a good validation of a CAE model at sub-systems level and mainly, discuss the properties and limitations of different tire modeling for different maneuvers, including Pacjeka 94, B-Spline and Delft.