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In this paper a design methodology for automotive heat exchangers has been applied which brings robustness into the design process and helps to optimize the design goals: as to maintain an optimal coolant temperature and to limit the vehicle underhood air temperature within a tolerable limit. The most influential design factors for the heat exchangers which affect the goals have been identified with that process. The paper summarizes the optimization steps necessary to meet the optimal functional goals for the vehicle as mentioned above. Taguchi's [1] Design for Six Sigma (DFSS) methods have been employed to conduct this analysis in a robust way.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

Accurate numerical prediction of an engine thermal map at a wide range of engine operating conditions can help tune engine performance parameters at an early development stage. This study documents the correlation of an engine thermal simulation using the conjugate heat transfer (CHT) methodology with thermocouple data from an engine operating in a dynamometer and a vehicle drive cell. Three different operating conditions are matched with the simulation data. Temperatures predicted by simulation at specific sections, both at the intake and the exhaust sides of the engine are compared with the measured temperatures in the same location on the operating engine.

To meet TierII/LEVII emissions standards, light duty diesel (LDD) vehicles require high conversion efficiencies from the Aftertreatment Systems (ATS) for the removal of both Hydrocarbon (HC) and Nitrogen Oxide (NOx) species. The most populous configuration for LDD ATS have the Selective Catalytic Reduction (SCR) catalyst positioned on the vehicle behind the close coupled Diesel Oxidation Catalyst (DOC) and Catalyzed Diesel Particulate Filter (CDPF). This SCR position may require active heating measures which rely on the DOC/CDPF to provide heat through the combustion of HC and CO in the exhaust. Although DOCs are always impacted by their aging conditions, some aging conditions are shown to be both reversible and irreversible.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

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.

Computational tools have been extensively applied to predict component temperatures before an actual vehicle is built for testing [1, 2, 3, 4, and 5]. This approach provides an estimate of component temperatures during a specific driving condition. The predicted component temperature is compared against acceptable temperature limits. If violations of the temperature limits are predicted, corrective actions will be applied. These corrective actions may include adding heat shields to the heat source or to the receiving components. Therefore, design changes are implemented based on the simulation results. Sensitivity analysis is the formal technique of determining most influential parameters in a system that affects its performance. Uncertainty analysis is the process of evaluating the deviation of the design from its intended design target.

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.

As vehicle fuel economy continues to grow in importance, the ability to accurately measure the level of efficiency on all driveline components is required. A standardized test procedure enables manufacturers and suppliers to measure component losses consistently and provides data to make comparisons. In addition, the procedure offers a reliable process to assess enablers for efficiency improvements. Previous published studies have outlined the development of a comprehensive test procedure to measure transfer case speed-dependent parasitic losses at key speed, load, and environmental conditions. This paper will take the same basic approach for the Power Transfer Units (PTUs) used on Front Wheel Drive (FWD) based All Wheel Drive (AWD) vehicles. Factors included in the assessment include single and multi-stage PTUs, fluid levels, break-in process, and temperature effects.

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.

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.

This paper presents a process for the selection of spring rate and pre-load for an adaptively controlled pivoting vane oil pump. The pivoting vane pump has two modes: high and low speed. A spring within the pump is installed to induce a torque that causes an adaptive displacement mechanism within the pump to move toward maximum oil chamber size. In low speed mode, two feedback regions are pressurized that produce torques that counter the spring generated torque. Together, both regions being pressurized by main oil gallery pressure tend to reduce pump displacement more at lower speeds than if only a single chamber is pressurized. At higher speeds, a solenoid switch turns off pressure to one of the feedback pressure chambers, thereby reducing feedback torque that counters spring torque. This enables higher pressure calibrations in this speed mode. In this paper, we identify a process for choosing the spring rate and pre-load that calibrates the adaptive displacement mechanism.

The common practice in finite element based fatigue calculation with multiple channels of road load is to perform a set of unit load static stress analysis and conduct stress time history construction later during fatigue calculation. The main advantage of this so-called quasi-static finite element based fatigue calculation is to avoid time-consuming dynamic stress analysis and also reduce static stress analysis from millions of real load cases to a few dozens unit-load cases. The main disadvantage of this quasi-static finite element based fatigue calculation is the absence of vibration-induced stresses in stress time history construction and fatigue analysis. A decade ago, a modal transient finite element based fatigue calculation was proposed to introduce vibration-induced stresses into finite element based fatigue calculation. The idea is to add vibration-induced modal stresses to load-induced instant stresses in stress time history construction and fatigue calculation.

To meet the 2010 diesel engine emission regulations, an aftertreatment system was developed to reduce HC, CO, NOx and soot. In NOx reduction, a baseline SCR module was designed to include urea injector, mixing decomposition tube and SCR catalysts. However, it was found that the baseline decomposition tube had unacceptable urea mixing performance and severe deposit issues largely because of poor hardware design. The purpose of this article is to describe necessary development work to improve the baseline system to achieve desired mixing targets. To this end, an emissions Flow Lab and computational fluid dynamics were used as the main tools to evaluate urea mixing solutions. Given the complicated urea spray transport and limited packaging space, intensive efforts were taken to develop pre-injector pipe geometry, post-injector cone geometry, single mixer design modifications, and dual mixer design options.

Using gasoline and diesel simultaneously in a dual-fuel combustion system has shown effective benefits in terms of both brake thermal efficiency and exhaust emissions. In this study, the dual-fuel approach is applied to a light-duty spark ignition (SI) gasoline direct injection (GDI) engine. Three combustion modes are proposed based on the engine load, diesel micro-pilot (DMP) combustion at high load, SI combustion at low load, and diesel assisted spark-ignition (DASI) combustion in the transition zone. Major focus is put on the DMP mode, where the diesel fuel acts as an enhancer for ignition and combustion of the mixture of gasoline, air, and recirculated exhaust gas. Computational fluid dynamics (CFD) is used to simulate the dual-fuel combustion with the final goal of supporting the comprehensive optimization of the main engine parameters.

EGR systems are widely applied in modern turbocharged diesel engines to reduce engine-out emissions and will, or are being used to mitigate engine knock in SI engines for improved SI engine efficiency and power. In this paper, different EGR systems are detailed and evaluated theoretically based on the thermodynamics of a turbocharged system featuring an EGR sub-system. Turbine expansion ratio is utilized as a metric to estimate engine efficiency, i.e., pumping losses during the gas exchange process. Approaches such as compressor and turbine bypassing are evaluated as well. Based on above analysis, a new approach is put forward to expand the turbocharger work zone, particularly in the high efficiency regions by correctly utilizing EGR systems at all engine speed range: low-pressure loop EGR system at lower engine speed range and high-pressure loop EGR system at high engine speed range.

The concept of full vehicle simulation has been embraced by the automobile industry as it is an indispensable tool for analyzing vehicles. Vehicle loads traditionally obtained by road load data acquisition such as wheel forces are typically not invariant as they depend on the vehicle that was used for the measurement. Alternatively, virtual road load data acquisition approach has been adopted in industry to derive invariant loads. Analytical loads prior to building hardware prototypes can shorten development cycles and save costs associated with data acquisition. The approach described herein estimate realistic component load histories with sufficient accuracy and reasonable effort using full vehicle simulations. In this study, a multi-body dynamic model of the vehicle was built and simulated over digitized road using ADAMS software, and output responses were correlated to a physical vehicle that was driven on the same road.

CAE tools are increasingly important in the automotive design process. In part, CAE tools can be useful in reducing the number of physical prototypes required during a product development effort. CFD tools can assess and predict cylinder charge motion for proposed designs, thereby limiting the need for prototype work. Though detailed combustion simulation results could help guide product development, the time required for such simulations limits their usefulness in the context of a production program. However equally valuable information can be obtained from gas exchange analyses which require less computation time and are run only from Intake Valve opening (IVO) to spark timing. Chemical kinetics is not included in this type of analysis. Using this approach, large numbers of configurations can be evaluated in a short period of time. Every passing year automotive engineers are challenged to attain higher fuel economy targets.