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Automotive industry has shown, in the recent years, a dramatically increase of competition at emergent markets. The incoming of new Brands, for example in the Brazilian market, is causing the OEMs to decrease costs while increase quality, which represents a big challenge nowadays. In this challenging scenario, virtual simulation has become mandatory. While cutting costs since no physical prototypes are required, virtual models also reduces development time. Time to time, as computers processing capacity grows, virtual models are becoming more and more accurate, being able to capture even high non-linear phenomena, which ten years ago would not be feasible. It is also known the natural tendency of vehicle dynamics engineers to develop shock absorber tuning only by means of subjective evaluation. Many reasons can be raised to this tendency, but one of them is the lack of representation of the entire shock absorber behavior in the virtual models.

Through the new Automotive Regulation recently deployed by ANFAVEA, vehicles selled in Brazil will have strong incentives to reduce fuel consumption. OEMs are being pushed to develop alternatives to achieve lower levels of fuel consumption either by new engines or reduce overall weight for the vehicles. Reducing the weight is being the logical and first choice by automakers, since it represents a cost reduction as well. The problem lies on the crash resistance (Latin NCAP) that forces the vehicle to have reinforcements, especially in the near future for the lateral crash standard, still to be deployed in the market. Thus, in the opposite direction, there is a natural tendency to increase sprung mass. In this way, the solution is to reduce non-sprung masses. The non-sprung parts likely to be reduced are normally components that impact the customer feeling the least, for example: dampers, stabilizer bars, tires, wheels, etc.

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.

Nowadays, vehicle steering development processes are mostly based on metrics which describe gains over steering wheel angle inputs. Most of these metrics are related to the yaw and lateral motion of the vehicle, for different velocities and curves situations. In practical terms, it is a correct approach, once steering feel is related to yaw motions and lateral accelerations. For example, given a certain steering wheel angle input, a higher yaw will generally provide a quicker response feel. However, there are subjective aspects related to the steering response feel that are not completely captured by traditional metrics alone, which are generally based on response gains over steering wheel inputs. This work presents a new steering evaluation plot, based in a simple maneuver (step steer) and in the sequence of the dynamic events that follow, which showed to be effective on providing additional analysis data that captures important aspects of the steering response subjective feel.

Ride comfort has been always a critical point in the development of a vehicle. In the recent years, has become an increasingly important factor in the vehicle design. Only subjective evaluation of ride comfort is no longer an acceptable or competitive way to assess the driver and passenger experience. And sometimes metrics extracted from measurements are often not correlated with subjective evaluation and with customers feed-back due to difficulties on the process of ride evaluation. Those difficulties are largely due to variations on the tracks where the vehicle is evaluated, on the speed of the vehicle passing through the tracks, etc. In other words, sometimes it is hard to have a process with a good repeatability. This work suggests a method of ride measurement which improves the repeatability and also creates a possibility to generate tracks for evaluation of specific ride problems.

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.

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.