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This article presents an approach for comparing alternative repairable systems and calculating the value of information obtained by testing a specified number of such systems. More specifically, an approach is presented to determine the value of information that comes from field testing a specified number of systems in order to appropriately estimate the reliability metric associated with each of the respective repairable systems. Here the reliability of a repairable system will be measured by its failure rate. In support of the decision-making effort, the failure rate is translated into an expected utility based on a utility curve that represents the risk tolerance of the decision-maker. The algorithm calculates the change of the expected value of the decision with the sample size. The change in the value of the decision represents the value of information obtained from testing.

Autonomous Vehicles (AVs) operate based on image information and 3D maps generated by sensors like cameras, LIDARs and RADARs. This information is processed by the on-board processing units to provide the right actuation signals to drive the vehicle. For safe operation, these sensors should provide continuous high quality data to the processing units without interruption in all driving conditions like dust, rain, snow and any other adverse driving conditions. Any contamination on the sensor surface/lens due to rain droplets, snow, and other debris would result in adverse impact to the quality of data provided for sensor fusion and this could result in error states for autonomous driving. In particular, snow is a common contamination condition during driving that might block a sensor surface or camera lens. Predicting and preventing snow accumulation over the sensor surface of an AV is important to overcome this challenge.

Importance Sampling is a popular method for reliability assessment. Although it is significantly more efficient than standard Monte Carlo simulation if a suitable sampling distribution is used, in many design problems it is too expensive. The authors have previously proposed a method to manage the computational cost in standard Monte Carlo simulation that views design as a choice among alternatives with uncertain reliabilities. Information from simulation has value only if it helps the designer make a better choice among the alternatives. This paper extends their method to Importance Sampling. First, the designer estimates the prior probability density functions of the reliabilities of the alternative designs and calculates the expected utility of the choice of the best design. Subsequently, the designer estimates the likelihood function of the probability of failure by performing an initial simulation with Importance Sampling.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

Brake torque variation is a source of objectionable NVH body/chassis response. Such input commonly results from brake disk thickness variation. The NVH dynamic characteristics of a vehicle can be assessed and quantified through experimental modal testing for determination of mode resonance frequency, damping property, and shape. Standard full vehicle modal testing typically utilizes a random input excitation into the vehicle frame or underbody structure. An alternative methodology was sought to quantify and predict body/chassis sensitivity to brake torque variation. This paper presents a review of experimental modal test methodologies investigated for the reproduction of vehicle response to brake torque variation in a static laboratory environment. Brake caliper adapter random and sine sweep excitation input as well as body sine sweep excitation in tandem with an intentionally locked brake will be detailed.

This paper describes the application of the modal compliance method to a complex structure such as a vehicle body in white, and the extension of the method from normal modes to the complex modes of a complete vehicle. In addition to the usual bending and torsion calculations, the paper also describes the application of the method to less usual tests such as second torsion, match-boxing and breathing. We also show how the method can be used to investigate the distribution of compliance throughout the structure.

To avoid damage and maximize capacity, the voltages of the individual batteries in series connected packs should be equalized. Long term trickle charging is the traditional equalization method, but this is inconvenient for EVs and HEVs. Electronic equalizers also can be used to redistribute the charge amongst the batteries so that trickle charging is no longer necessary. A new type of high frequency electronic equalizer called the ramp converter uses soft switching techniques and a unique transformer design to minimize size and cost. Experimental results at two different power levels indicate performance similar to trickle charging but with a much shorter charging time.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

In automotive testing, a chassis dynamometer is typically used, during cell testing, to evaluate vehicle performance by simulating actual driving conditions. The use of indoor cell testing has the advantage of running controlled tests where the cell temperature and humidity and solar loads can be well controlled. Driving conditions such as vehicle speed, wind speed and grade can be also controlled. Thus, repeated tests can be conducted with minimum test variations. The tractive effort required at the wheels of a vehicle for a given set of operating parameters is determined by taking into account a set of variables which affect vehicle performance. The forces considered in determination of the tractive effort include the constant friction force, variable friction force due to mechanical and tire friction, forces due to inertia and forces due to aerodynamic and wind effects. In addition, forces due to gravity are considered when road grades are simulated.

This paper identifies the difference in powertrain cooling system content levels using a nominal and a +3 Standard deviation maximum temperature design approach. Variation simulation analysis tools are used along with a 1-D cooling system performance model to predict resulting temperature distribution for different combinations of input variable populations. The analysis will show differential in powertrain cooling system content, mass, and impact to fuel economy for a nominal vs. +3 sigma design approach.

Brake judder, which is a low frequency excitation of the suspension and thus, the body structure during low-G braking, is mainly felt at the steering wheel and throughout the vehicle structure. Brake judder is a problem that costs manufacturers millions of dollars in warranty cost and undesirable trade offs. The magnitude of judder response depends not only on the brake torque variation, but also on the suspension design character-istics. This paper discusses the judder simulation process using ADAMS software to investigate the suspension design sensitivity to the first order brake judder performance. The paper recommends “tuning knobs” to suspension designers and vehicle development engineers to resolve issues in the design and development stages. Various suspension design varia-bles including geometry and compliances as well as brake related characteristics were investigated.

To mitigate head impact injuries of vehicle occupants in impact accidents, the FMVSS 201 requires padding of vehicle interior so that under the free-moving-head-form impact, the head injury criterion (HIC) is below the limit. More recently, pedestrian head impact on the vehicle bonnet has been a subject being studied and regulated as requirements to the automobile manufacturers. Over the years, the square wave has been considered as the best waveform for head impacts, although it is impractical to achieve. This paper revisits the head impact topic and challenges the optimality of aiming at the square waveform. It studies several different simple waveforms, with the objective to achieve minimal HIC or minimal crush space required in head-form impacts. With that it is found that many other waveforms can be more efficient and more practical than the square wave, especially for the pedestrian impact.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.

This paper presents a computer generated model of a hydraulic circuit that is typically seen in hybrid hydraulic vehicles (HHV's). HHV's have shown considerable potential for increasing fuel economy and decreasing emissions for mid-size and commercial trucks that exhibit urban driving habits. The aim of the present model is to aid in further optimizing the performance of the hybrid powertrain and serve as a baseline for future studies into the noise and vibration (NV) associated with the system. The model simulates the regenerative braking process of a parallel type hybrid hydraulic propulsion system. Regenerative braking captures and stores otherwise lost energy into an accumulator. This stored energy can then later be used to propel the vehicle, thus reducing the vehicle's reliance on a conventional internal combustion engine (ICE). This model will serve as a baseline for future developments and will be expanded and validated experimentally in ensuing research.

A complete probabilistic model of uncertainty in probabilistic analysis and design problems is the joint probability distribution of the random variables. Often, it is impractical to estimate this joint probability distribution because the mechanism of the dependence of the variables is not completely understood. This paper proposes modeling dependence by using copulas and demonstrates their representational power. It also compares this representation with a Monte-Carlo simulation using dispersive sampling.

For a vehicle or repairable system, incidents (conditions) are neither necessarily independent nor identically distributed. Therefore, traditional statistical distributions like Weibull, Normal, etc, are no longer valid to estimate reliability. The Non-homogeneous Poisson process (NHPP) model can be used to predict reliability and warranty of the field product. It can also measure the reliability improvement during the development cycle. The NHPP model is discussed in this paper. In applying a NHHP model to reliability data on a repairable system, one may have few or no failures. This paper presents the I/100 and reliability derivations when the parameter β in the ROCOF function is assumed to have a known value.

Load data representing severe customer usage is required during the chassis development process. One area of current research is the use of road profiles for predicting chassis loads. The most direct method of predicting these loads is to run dynamic simulations of the vehicle using numerous road profiles as the excitation. This onerous task may be avoided, and a greatly reduced number of simulations would be required, if roads having similar characteristics can be grouped. Currently, road profiles are characterized by their spectral content. It has been noted by several researches, however, that road profiles are generally nonstationary signals that contain significant transient events and are not well described in the spectral domain. The objective of this work, then, is to develop a method by which the characteristics of the road can be captured by describing these constitutive transient events.

The effects of vehicle “stiffness” and mass on the occupant response during a crash may be determined by evaluation of accident data. However, “stiffness” and mass may be correlated, making it difficult to separate their effects. In addition, a single-valued “stiffness”, although well defined for linear case, is not well defined for non-linear systems, such as in vehicle crash, making the separation task even more difficult. One approach to addressing the lack of a clear definition of stiffness is to use multiple definitions. Each stiffness definition can then be correlated with mass to look for trends. In this study, such an approach was taken, and the different stiffness definitions were given and their values were obtained from rigid barrier crash test data. No clear relationship between mass and stiffness appears to exist. All the stiffness measures reviewed show, at best, only a weak correlation with mass. A stiffness analysis among different vehicle types was also carried out.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

One of the major NVH concerns for automobile manufacturers is the response of a vehicle to the impact of the tire as it encounters a road discontinuity or bump. This paper describes methods for analyzing the impact response of a vehicle to such events. The test vehicle is driven on a dynamometer, on which a bump simulating cleat is mounted. The time histories of the cleat impact response of the vehicle can be classified as a transient and a repeated signal, which should be processed in a special way. This paper describes the related signal processing issues, which include converting the time data into a continous spectrum, determination of the correct scaling factor for the analyzed spectrum, and smoothing out harmonics and fluctuations in the signal. This procedure yields a smooth frequency spectrum with a correctly scaled amplitude, in which the frequency contents can be easily identified.