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Exposure in ISO 26262 is defined as the state of being in an operational situation that can be hazardous if coincident with the failure mode under analysis. An operational situation is defined as a scenario that can occur during a vehicle's life with examples given such as driving, parking, or maintenance. Accurately predicting exposure is one of the more difficult tasks in the ASIL determination. ISO 26262 Part 3 attempts to provide guidance in Annex B through tables of potential operational situations and associated exposure levels. However, the contents of these tables may not allow for an accurate prediction of exposure and may lead to an exposure value that is too high or too low. In this paper, we describe a potential method for determining exposure that considers a potential mishap scenario as a composition of multiple coincident operational situations rather than considering a single operational situation as indicated in the tables in Annex B of Part 3.

In an Automotive air conditioning system, the air flow distribution in the cabin from the HVAC (Heating, ventilation and air conditioning), ducts and outlets is evaluated by the velocity achieved at driver and passenger mannequin aim points. Multiple simulation iterations are being carried out before finalizing the design of HVAC panel duct and outlets until the target velocity is achieved. In this paper, a parametric modeling of the HVAC outlet is done which includes primary and secondary vane creation using CATIA. Java macro files are created for simulation runs in STAR CCM+. ISIGHT is used as an interface tool between CATIA and STARCCM+. The vane limits of outlet and the target velocity to be achieved at mannequin aim points are defined as the boundary conditions for the analysis. Based on the optimization technique and the number of iterations defined in ISIGHT, the vane angle model gets updated automatically in CATIA followed by the simulation runs in STARCCM+.

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.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

Automotive vehicle body electrophoretic (e-coat) and paint application has a high degree of complexity and expense in vehicle assembly. These steps involve coating and painting the vehicle body. Each step has multiple coatings and a curing process of the body in an oven. Two types of heating methods, radiation and convection, are used in the ovens to cure coatings and paints during the process. During heating stage in the oven, the vehicle body has large thermal stresses due to thermal expansion. These stresses may cause permanent deformation and weld/joint failure. Body panel deformation and joint failure can be predicted by using structural analysis with component surface temperature distribution. The prediction will avoid late and costly changes to the vehicle design. The temperature profiles on the vehicle components are the key boundary conditions used to perform structure analysis.

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.

Forward Collision Warning (FCW) is a system intended to warn the driver in order to reduce the number of rear end collisions or reduce the severity of collisions. However, it has the potential to generate driver annoyances and unintended consequences due to high ineffectual (false or unnecessary) alarms with a corresponding reduction in the total system effectiveness. The ineffectual alarm rate is known to be closely associated with the “time to issue warning.” This results in a conflicting set of requirements. The earlier the time the warning is issued, the greater probability of reducing the severity of the impact or eliminating it. However, with an earlier warning time there is a greater chance of ineffectual warning, which could result in significant annoyance, frequent complaints and the driver's disengagement of the FCW. Disengaging the FCW eliminates its potential benefits.

Two finite element optimization techniques are presented for minimizing automotive engine air induction structural radiated noise and mass. Air induction systems are generally made of thin wall plastic which is exposed to high levels of pulsating engine noise. Weak air induction system walls vibrate excessively creating noise that can be heard by the driver. The conventional approach is to add ribs (many times through trial and error) which increase part weight or by adding “kiss-offs,” which restrict air flow. The finite element optimization methods considered here are shape optimization and topometry optimization. Genesis, a fully integrated finite element analysis and optimization package by Vanderplaats Research & Development, was used to perform finite element optimization. Choice of optimization method is primarily dependent on several factors which are appearance, part interference and flow restriction requirements.

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.

An accurate representation of proving ground loading is essential for nonlinear Finite Element analysis and component fatigue test. In this paper, a rainflow counting based multiple blocks loading development procedure is described. The procedure includes: (1) Rainflow counting analysis to obtain the relationship between load range and cumulative repeats and the statistical relationship between load range and mean load; (2) Formation of preliminary multiple loading blocks with specified load range, mean load, and the approximate cycle repeats, and construction of the preliminary multiple loading blocks; (3) Calibration and finalization of the repeats for preliminary multiple loading blocks according to the equivalent damage rule, meaning that the damage value due to the block loads is equivalent to that from a PG loading.

Reliable testing of a mechanical system requires the procedures used for the evaluation to be repeatable and reproducible. However, it is never possible to exactly repeat or reproduce the tests that are used for evaluation. To overcome this limitation, a statistical evaluation procedure can generally be used. However, most of the statistical procedures use scalar values as input without the ability to handle vectors or time-histories. To overcome these limitations, two numerical/statistical methods for determining if the impact time-history response of a mechanical system is repeatable or reproducible are evaluated and elaborated upon. Such a system could be a vehicle, a biological human surrogate, an Anthropometric Test Device (ATD or dummy), etc. The responses could be sets of time-histories of accelerations, forces, moments, etc., of a component or of the system. The example system evaluated is the BioRID II rear impact dummy.

Traditional warm forming of aluminum refers to sheet forming in the temperature range of 200°C to 350°C using heated, matched die sets similar to conventional stamping. While the benefits of this process can include design freedom, improved dimensional capability and potentially reduced cycle times, the process is complex and requires expensive, heated dies. The objective of this work was to develop a warm forming process that both retains the benefits of traditional warm forming while allowing for the use of lower-cost tooling. Enhanced formability characteristics of aluminum sheet have been observed when there is a prescribed temperature difference between the die and the sheet; often referred to as a non-isothermal condition. This work, which was supported by the USCAR-AMD initiative, demonstrated the benefits of the non-isothermal warm forming approach on a full-scale door inner panel. Finite element analysis was used to guide the design of the die face and blank shape.

During component development of multiple fastener bolted joints, it was observed that one or two fasteners had a higher potential to slip when compared to other fasteners in the same joint. This condition indicated that uneven distribution of the service loads was occurring in the bolted joints. The need for an optimization tool was identified that would take into account various objectives and constraints based on real world design conditions. The objective of this paper is to present a method developed to determine optimized multiple fastener locations within a bolted joint for achieving evenly distributed loads across the fasteners during multiple load events. The method integrates finite element analysis (FEA) with optimization software using multi-objective optimization algorithms. Multiple constraints were also considered for the optimization analysis. In use, each bolted joint is subjected to multiple service load conditions (load cases).

Most manufacturing and assembly processes like stamping, clamping, interference fits introduce a pre-stress condition in components or assemblies. Very often these stresses are high enough and alter the mean stress state resulting in significant effect on fatigue life performance and thus cannot be ignored. If the pre-stress is compressive, it will increase the allowable stress range and improve fatigue life performance; on the other hand if these stresses are tensile, they will decrease the allowable stress range resulting in a degradation of fatigue life. At times it becomes critical to effectively introduce the pre-stress condition in order to accurately represent the stress state in an FEA based durability simulation. Accounting for the pre-stress state in FEA based constant amplitude loading fatigue life simulation is relatively straight forward, but when it comes to random variable amplitude multi-channel loads simulation, the problem becomes more complicated.

The air induction system (AIS), which provides clean air to the engine for combustion, is very important for engine acoustics. A practical CAE procedure to predict AIS inlet noise is presented in this paper. GT-Power, a commercially available software program can be used to simulate the engine performance and predict air induction noise. The accuracy of GT-Power is dependent on many variables, such as: proper duct discretization size, proper number of flow splits to model the air box and the capturing of the correct resonator geometry for tuning frequency. Since GT-Power is based on a 1D assumption, several iterations need be performed to model the complex AIS components, such as, irregular shaped air box, resonator volume, porous ducts and perforated pipes. Because of this, the GT-Power AIS model needs to be correlated to test data using transmission loss data.

The complexity of both hardware and software has increased significantly in automotive over the past decade. This is apparent even in the compact passenger car market segment where the presence of electronic control units (ECU) has nearly tripled. In today's luxury vehicles, software can reach 100 million lines of code and are only projected to increase. Without preventive measures, the risk of safety-related system malfunction becomes unacceptably too high. The functional safety standard ISO 26262, released as first edition in 2011, provides crucial safety-related requirements for passenger vehicles. Although the standard defines the proper development for safety-related systems to ensure the avoidance of a hazard, it's implication for electromagnetic compatibility (EMC) is not clearly defined. This paper outlines the impact of ISO 26262 for EMC related issues, and discusses the standard's implications for EMC requirements on the present EMC practices for production vehicles.

This paper presents the design of a hybrid powertrain damping control algorithm using the sliding mode control (SMC) scheme. Motor control-based active damping control strategy is used to ensure smooth drive line operation and provide the driver with seamless driving experience. In the case of active damping control, motor and engine speeds are measured to monitor the driveline state, and corrective motor torques are generated to dampen out drive line vibrations. Drive lines are prone to internal vibration (engine, clutches and motors) as well as external disturbances caused by road inputs. As such, fast-response actuator-based damping control systems are desirable in a hybrid powertrain application, where a torque converter is generally not used. The most significant aspect of an active damping control algorithm is the error calculation, based on proper states information, and torque determination based on the adaptive control gain applied to the nonlinear system.

Brake judder is a brake induced vibration that a vehicle driver experiences in the steering wheel or floor panel at highway speeds during vehicle deceleration. The primary cause of this disturbance phenomenon is the brake torque variation (BTV). Virtual CAE tools from both kinematics and compliance standpoints have been applied in analyzing sensitivities of the vehicle systems to BTV. This paper presents a recently developed analytical approach that identifies parameters of steering and suspension systems for achieving optimal settings that desensitize the vehicle response to BTV. The analytical steps of this integrated approach started with creating a lumped mass noise-vibration-harshness (NVH) control model and a separate multi-body dynamics (MBD) suspension model. Then, both models were linked to run in a sequence through optimization software so the results from the MBD model were used as quasi-static inputs to the lumped mass NVH model.

Flame ionization detector (FID) analyzers used in emission testing to measure total hydrocarbon emissions have been operating for the last forty years on a fuel mixture of 40% H₂ and 60% helium. These mixtures were selected based on research studies reported in the literature indicating that this particular mixed fuel combination gave the best sensitivity and relative response of the different hydrocarbons present in vehicle exhaust with respect to propane, the calibration gas. During the past few years, it was announced that there is a worldwide shortage of helium which triggered the automotive industry to look for alternatives for helium to be used in FID fuels. Helium which is produced as a byproduct from natural gas fields is non-renewable, expensive, and extremely rare on the earth. Current supply cannot keep up with demand. There are only few natural gas fields producing helium and unless new natural gas fields are found, current helium amounts will continue to dwindle.