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In this paper, loads acting on driveline components during an entire proving ground (PG) durability schedule are used to demonstrate the methodology of optimizing driveline performance reliability using both physical and computational methods. It is well known that there is an effect of driver variability on the driveline component loads. Yet, this effect has not been quantified in the past for lack of experimental data from multiple drivers and reliable data analysis methods. This paper presents the data reduction techniques that are used to identify the extreme driver performance and to extrapolate the short-term measurement to long-term data for driveline performance reliability. The driveline loading variability is made evident in the rotating moment histogram domain. This paper also introduces the concept for a simulation model to predict the driveline component loads based on a complete proving grounds schedule. A model-to-test correlation is also performed in this paper.

Most products are designed to operate for a long period of time, and in such case, life testing is a relatively lengthy procedure. Lengthy tests tend to be expensive and the results become available too late to be of much use. To reduce the experimental cost significantly and provide an efficient tool to assess the life distribution for highly reliable product, a step-stress accelerated test (SSAT) was developed. An example of a rear suspension aft lateral link is used to validate the SSAT method.

A process for establishing an accelerated proving ground durability schedule for a vehicle suspension system, based on real customer roads, was developed in this work. The available road load data for a specific chassis design was acquired by using a test vehicle that was equipped to measure the front and rear spindle loads, wheel-to-body displacements, and body mount loads. The test target representing the customer usage consists of a combination of 5 tracks of public roads located in Michigan, adding up to 100 miles, and is based upon a previous work by Ferris, J.B. and Larsen, J.L. [2]. It was then extrapolated to a target customer equivalent mileage of 150, 000 miles with an assigned extrapolation factor for each public road. A repeat value for each of seven test tracks at the Chelsea Proving Grounds was generated using state-of-the-art optimization techniques to match the weighted, rainflow cycle histograms from the road load data channels, .

In this paper, the development of random vibration testing schedules for durability design verification of engine mounted products is presented, based on the equivalent fatigue damage concept and the 95th-percentile customer engine usage data for 150,000 miles. Development of the 95th-percentile customer usage profile is first discussed. Following that, the field engine excitation and engine duty cycle definition is introduced. By using a simplified transfer function of a single degree-of-freedom (SDOF) system subjected to a base excitation, the response acceleration and stress PSDs are related to the input excitation in PSD, which is the equivalent fatigue damage concept. Also, the narrow-band fatigue damage spectrum (FDS) is calculated in terms of the input excitation PSD based on the Miner linear damage rule, the Rayleigh statistical distribution for stress amplitude, a material's S-N curve, and the Miles approximate solution.

Spot Welding is now widely used in the fabrication of sheet metals, mainly due to the cost and time considerations. Spot welds are found in nearly all products where sheet metal is joined. Examples range from a single metal toolbox to nearly 10,000 spot welds found in a typical passenger car. Obviously the quality of the spot weld has a direct impact on the quality of the product. The problem of estimating the spot-weld quality is an important component in quality control. If the weld nuggets are improperly or incompletely formed, or the area surrounding the nugget is smaller than required, the structural integrity of the entire part may be uncertain. Furthermore these inconsistencies are usually internal and are seldom visible to Optical Inspection. This study is focused on the non-destructive evaluation of the spot welds using “Digital Shearography”.

Friction stir linear welding (FSLW) is widely used in joining lightweight materials including aluminum alloys and magnesium alloys. However, fatigue life prediction method for FSLW is not well developed yet for vehicle structure applications. This paper is tried to use two different methods for the prediction of fatigue life of FSLW in vehicle structures. FSLW is represented with 2-D shell elements for the structural stress approach and is represented with TIE contact for the maximum principal stress approach in finite element (FE) models. S-N curves were developed from coupon specimen test results for both the approaches. These S-N curves were used to predict fatigue life of FSLW of a front shock tower structure that was constructed by joining AM60 to AZ31 and AM60 to AM30. The fatigue life prediction results were then correlated with test results of the front shock tower structures.

This paper introduces a methodology to calculate confidence bounds for a normal and Weibull distribution using Monte Carlo pivotal statistics. As an example, a ready-to-use lookup table to calculate one-sided lower confidence bounds is established and demonstrated for normal and Weibull distributions. The concept of one-sided lower tolerance limits for a normal distribution was first introduced by G. J. Lieberman in 1958 (later modified by Link in 1985 and Wei in 2012), and has been widely used in the automotive industry because of the easy-to-use lookup tables. Monte Carlo simulation methods presented here are more accurate as they eliminate assumptions and approximations inherent in existing approaches by using random experiments. This developed methodology can be used to generate confidence bounds for any parametric distribution. The ready-to-use table for the one-sided lower tolerance limits for a Weibull distribution is presented.

Once a vehicle powertrain is designed and the first prototype is built, extensive on-board instrumentation and testing needs to be carried out at the proving grounds (PG) to generate load histograms for various components. The load histograms can then be used to carry out durability tests in the laboratory. When a component in the vehicle powertrain is changed, the load histograms need to be generated again at the proving grounds. This adds much time and money to the vehicle's development. The objective is to develop a virtual powertrain model that can be simulated through a powertrain endurance driving cycle in order to predict torque histograms and total damage. The predictions are then correlated against measured data acquired on a test vehicle that was driven through the same driving cycle at the proving grounds.

Due to magnesium alloy's poor weldability, other joining techniques such as laser assisted self-piercing rivet (LSPR) are used for joining magnesium alloys. This research investigates the fatigue performance of LSPR for magnesium alloys including AZ31 and AM60. Tensile-shear and coach peel specimens for AZ31 and AM60 were fabricated and tested for understanding joint fatigue performance. A structural stress - life (S-N) method was used to develop the fatigue parameters from load-life test results. In order to validate this approach, test results from multijoint specimens were compared with the predicted fatigue results of these specimens using the structural stress method. The fatigue results predicted using the structural stress method correlate well with the test results.