Customer Road Correlation and Optimization with Multiple Proving Grounds

Proving ground testing is an essential stage in durability qualification for vehicle components. They represent customer roads with increased severity for accelerated damage accumulation. It is required to correlate proving grounds to actual road conditions in terms of both track mix and mileage. With increasing competition and shorter product development cycle time, vehicle needs be tested in shortest possible time. Using single and most severe track for required damage accumulation is often a suitable choice, but this may result in uneven testing of vehicle components, some parts may be over-tested or under-tested. This paper discusses this challenge and iteratively shows that multiple mix of tracks and payload conditions are required to get better correlation. Strain data on a two wheeler vehicle frame is acquired from different proving ground surfaces as well as representative customer roads. Data is characterized based on RDS (Relative Damage Spectrum) method and Best fit optimization algorithm is used to establish the closest proving ground schedule to the target user. Different tracks and load conditions are taken as input and final solution is optimized in multiple iterations. Result shows that multiple set of proving ground surfaces rather than choosing the single damaging surface gives better proving ground schedule with uniform damage throughout component. Keywords: RDS, Optimization, Correlation, Proving Grounds, Strain Gauges, Durability