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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.

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.

Elastomers have large reversible elastic deformation, good damping and high energy absorption capabilities. Due to these characteristics along with low cost of manufacturing, elastomeric components are widely used in many industries and applications, including in automobiles. These components are typically subjected to complex multiaxial and variable amplitude cyclic loads during their service life. Therefore, fatigue failure and life prediction are important issues in the design and analyses of these components. Availability of an effective CAE technique to evaluate fatigue damage and to predict fatigue life under complex loading conditions is a valuable tool for such analysis. This paper discusses a general CAE analytical technique for durability analysis and life prediction of elastomeric components. The methodology is then illustrated and verified by using experimental fatigue test results from an automobile cradle mount.

The first set of SAE J2643 Standard Reference Elastomers (SRE) was developed in 2004. It was composed of a group of 10 compounds covering multiple elastomer families. Since then, more advanced materials from many elastomer families have been introduced to the automotive industry. The purpose of this study is to add a few more reference compounds to SAE J2643, to enhance the portfolio on FKM, AEM and ACM to reflect advancements in elastomer technology, and make it suitable for a variety of fluids, such as transmission fluid and engine oil. Fourteen standard elastomer compounds were involved in this study, covering various materials currently used in automotive powertrain static and dynamic sealing applications. Participants include OEMs, major rubber manufacturers, a fluid additive company and an independent lab. Manufacturers of each test compound provided formulations, designated ingredients from defined sources, and detailed mixing and molding procedures.

This paper will define the process for correlating fatigue based customer duty cycle with laboratory bench test data. The process includes the development of the Median and Design Load-Life curve equations. The Median Load-Life curve is a best fit linear regression; whereas, the Design Load-Life curve incorporates component specific reliability and confidence targets. To account for the statistical distribution of fatigue life, due to sample size, the one-side lower-bound tolerance limit method ( Lieberman, 1958 ) will be utilized. This paper will include a correlation between the predicted design fatigue life and the actual product life.

Airdam is an aerodynamic component in automobile and is designed to reduce the drag and increase fuel efficiency. It is also an important styling component. The front airdam below the bumper is to direct the air flow away from the front tires and towards the underbody, where the drag coefficient becomes less. The flexible airdam is made of Santoprene™ - thermoplastic vulcanizates (TPV), which belongs to thermoplastic elastomer (TPE) family. When a vehicle is parked over a parking block, the flexible airdam will be under strain subjected to bending load from the parking block. If the airdam is kept under constant strain for a certain period, a set will occur and the force will decay over a period of time. Due to the force decay, the stress will reduce and this behavior is called as stress relaxation.

As the demand for Sound Quality improvements in vehicles continues to grow, robust analysis methods must be established to clearly represent end-user perception. For vehicle sounds which are tonal by nature, such as transmission or axle whine, the common practice of many vehicle manufacturers and suppliers is to subjectively rate the performance of a given part for acceptance on a scale of one to ten. The polar opposite of this is to measure data and use the peak of the fundamental or harmonic orders as an objective assessment. Both of these quantifications are problematic in that the former is purely subjective and the latter does not account for the presence of masking noise which has a profound impact on a driver's assessment of such noises. This paper presents the methodology and results of a study in which tonal noises in the presence of various level of masking noise were presented to a group of jurors in a controlled environment.

In an automotive air-conditioning (AC) system, the amount of work done by the compressor is also influenced by the suction line which meters the refrigerant flow. Optimizing the AC suction line routing has thus become an important challenge and the plumbing designers are required to come up with innovative packaging solutions. These solutions are required in the early design stages when prototypes are not yet appropriate. In such scenarios, one-dimensional (1D) simulations shall be employed to compute the pressure drop for faster and economical solution. In this paper, an approach of creating a modeling tool for suction line pressure drop prediction is discussed. Using DFSS approach L12 design iterations are created and simulations are carried out using 1D AMESim software. Prototypes are manufactured and tested on HVAC bench calorimeter. AC suction line pressure drop predicted using the 1D modeling co-related well with the test data and the error is less than 5%.