Derivation of Durability Targets and Procedures Based on Real World Usage 2007-26-074
It has been said many times that any new design, in the automotive world or otherwise, has two main goals; to meet the customers' expectations of performance and durability. Many manufacturers assume that if the vehicle performs well and has a suitable ‘strength factor of safety’, then durability is achieved with some cursory checking with a proving test or endurance schedule. This has been termed the ‘build-it test-it fix-it build-another-one’ strategy , and is still very much the model across the industry. It also has to be seen as commercially untenable as we can no longer wait until a prototype is available to assess the durability of the vehicle or product.
Fortunately over the past few years, modelling and analysis techniques have become both accurate and robust enough to provide early indications of the expected durability of designs . These technologies are continuing to develop with the widening use of virtual engineering. But these techniques still rely on the traditional design targets derived from testing or experience. It is the authors' experience that little work has been done in determining the accuracy of these empirical targets .
So what is it that very often prevents the engineering process producing an adequate and believable result at the design stages prior to prototype test? The answer usually lies in the lack of suitable loads and estimates of the life or usage conditions.
This paper outlines how MIRA accurately determines the durability targets for vehicles by extrapolating market information and combining this with Road Load Data (RLD). It also shows how as part of the Integrated Durability Engineering approach to design (IDE) we enhance the tried and trusted durability development test methods, with predictive tools in CAE and proving tests based on ‘Real World’ loading histories.
To illustrate the process this paper describes a recent project that MIRA has undertaken to determine the structural durability target for a large truck correlated to the Middle Eastern market. The usage targets were aimed at designing accelerated structural durability tests of the main truck cab, but can also be used as whole vehicle tests on the MIRA proving ground, component rig tests and to provide suitable CAE load case data for the vehicle.
A substantial customer market survey exercise was completed in territory. This identified the location of different road types, features and speeds that are representative of in service conditions. This survey was also used for calculating the 95th-percentile usage profile, which has been used as the correlation target.
A typical large truck was then fully instrumented to measure the dynamic wheel input forces for these specific road types. Data was acquired from both the MIRA proving ground test surfaces and from the public roads in territory; the latter was used in conjunction with the market survey to assemble the 95th-percentile target usage pattern and associated durability schedule. This statistically accurate and correlated durability target can then be used to generate CAE load cases, conduct component or system rig based durability, whole vehicle proving ground durability and be used within the virtual engineering environment.