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Fuel Tank Straps very often get different durability fatigue test results from different types of durability testing such as shaker table vibration, road test simulator (RTS) vehicle testing and proving ground vehicle durability testing. One test produces good durability results and other may indicate some durability risk. A special study was conducted to address this inconsistency. It was found that fuel level in the tank plays a big role in fuel tank strap durability. Higher fuel levels in a tank produce higher loads in straps and lower fatigue life. This paper will use a CAE fuel tank strap model and acquired proving ground strap load data to study fuel level influence in fuel tank strap durability. The fuel level study includes a full tank of fuel, 3 quarters tank of fuel, a half tank of fuel and one quarter tank of fuel.

Automotive companies are now offering the option of Hard-top (folding panel) or Soft-top (cloth) convertible roofs. It is therefore necessary to develop Road Test Simulator tests for four roof configurations: 1) Hard-top / Roof Down, 2) Hard-top / Roof Up, 3) Soft-top / Roof Down, and 4) Soft-top / Roof Up. This extends both the data acquisition and drive file development phases of the test. The objective of this paper is to examine whether the drives developed from one configuration (Hard-top / Roof Up) are valid for the other three configurations, assuming no suspension parameter changes. The changes in roof configurations are quantified by the relative difference in a) global body stiffness in torsion and bending, b) vehicle weight distribution, and c) roof center-of-gravity. The responses at the Proving Grounds and on the Rig are measured by: i) spindle loads and accelerations, ii) wheel-to-body displacement, iii) body acceleration, and iv) roof structural strains.

Durability of automotive structures is a primary engineering consideration that is required to be assessed at every design and development stage. Due to limitations of the analytical and experimental tools, the current practice in the automotive industry is to conduct a new data acquisition over a proving ground schedule whenever there are changes in the suspension parameters. This is a time-consuming and expensive operation. This paper provides guidelines for product teams to determine if a new vehicle data acquisition is needed when there are changes in vehicle parameters, and the corresponding effect on Road Test Simulator (RTS) drive file development. The application of this methodology to a truck with and without tuned suspension parameters is described in detail.

In this paper, responses from a vehicle's suspension, chassis and body, are used to demonstrate a methodology to optimize physical test results. It is well known that there is a variability effect due to an increase of wheel unsprung mass (due to loads measurement fixturing), tire pressure, speed, etc. This paper quantifies loading variability due to Wheel Force Transducer (WFT) unsprung mass by using a rainflow cycle counting domain. Also, presents a proving ground-to-test correlation study and the data reduction techniques that are used in road simulation test development to identify the most nominal road load measurement. Fundamental technical information and analytical methodology useful in overall vehicle durability testing are discussed. Durability testing in a laboratory is designed to correlate fatigue damage rig to road. A Proving Ground (PG) loading history is often acquired by running an instrumented vehicle over one or more PG events with various drivers.

During the initial vehicle design phase and as the first prototypes are built, extensive on-board instrumentation and data acquisition is required at the proving grounds (PG). The data is used for various types of testing and analysis. During this phase of development very few parts and assembly components are available for physical test. The objective is to develop a component test for the truck box. This test can be run without suspension parts during the early stages of the vehicle development. A further objective is to correlate the test to FEA models and actual Proving Ground full vehicle test results.