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Exterior component integration presents competing performance challenges for balanced exterior styling, safety, ‘structural feel’ [1] and durability. Industry standard practices utilize noise and vibration mode maps and source-path-receiver [2] considerations for component mode frequency placement. This modal frequency placement has an influence on ‘structural feel’ and durability performance. Challenges have increased with additional styling content, geometric overhang from attachment points, component size and mass, and sensor modules. Base excitation at component attachment interfaces are increase due to relative positioning of the suspension and propulsion vehicle source inputs. These components might include headlamps, side mirrors, end gates, bumpers and fascia assemblies. Here, we establish basic expectations for the behavior of these systems, and ultimately consolidate existing rationales that are applied to these systems.

A Machine Learning (ML) approach is presented to correlate in-cylinder images of early flame kernel development within a spark-ignited (SI) gasoline engine to early-, mid-, and late-stage flame propagation. The objective of this study was to train machine learning models to analyze the relevance of flame surface features on subsequent burn rates. Ultimately, an approach of this nature can be generalized to flame images from a variety of sources. The prediction of combustion phasing was formulated as a regression problem to train predictive models to supplement observations of early flame kernel growth. High-speed images were captured from an optically accessible SI engine for 357 cycles under pre-mixed operation. A subset of these images was used to train three models: a linear regression model, a deep Convolutional Neural Network (CNN) based on the InceptionV3 architecture and a CNN built with assisted learning on the VGG19 architecture.

More stringent emissions regulations are continually being proposed to mitigate adverse human health and environmental impacts of internal combustion engines. With that in mind, it has been proposed that vehicular particulate matter (PM) emissions should be regulated based on particle number in addition to particle mass. One aspect of this project is to study different sample handling methods for number-based aerosol measurements, specifically, two different methods for removing volatile organic compounds (VOCs). One method is a thermodenuder (TD) and the other is an evaporative chamber/diluter (EvCh). These sample-handling methods have been implemented in an engine test cell with a spark-ignited direct injection (SIDI) engine. The engine was designed for stoichiometric, homogeneous combustion.

Over the past several years a task group within the SAE Automotive Corrosion and Protection (ACAP) Committee has conducted extensive on-vehicle field testing and numerous accelerated lab tests with the goal of establishing a standard accelerated test method for cosmetic corrosion evaluations of finished aluminum auto body panels. This project has been a cooperative effort with OEM, supplier, and consultant participation and was also supported in part by DOE through USAMP (AMD 309). The focus of this project has been the identification of a standardized accelerated cosmetic corrosion test that exhibits the same appearance, severity, and type of corrosion products that are exhibited on identical painted aluminum panels exposed to service relevant environments. Multi-year service relevant exposures were conducted by mounting panels on-vehicles in multiple locations in the US and Canada.

As the automotive industry quickly moves towards hybridized and electrified vehicles, the optimal integration of power electronics in these vehicles will have a significant impact not only on the cost, performance, reliability, and durability; but ultimately on customer acceptance and market success of these technologies. If properly executed with the right cost, performance, reliability and durability, then both the industry and the consumer will benefit. It is because of these interdependencies that the pace and scale of success, will hinge on effective collaboration. This collaboration will be built around the convergence of automotive and industrial technology. Where real time embedded controls mixes with high power and voltage levels. The industry has already seen several successful collaborations adapting power electronics to the automotive space in target vehicles.

Hybrid high voltage battery pack is not only heavy mass but also large in dimension. It interacts with the vehicle through the battery tray. Thus the battery tray is a critical element of the battery pack that interfaces between the battery and the vehicle, including the performances of safety/crash, NVH (modal), and durability. The tray is the largest and strongest structure in the battery pack holding the battery sections and other components including the battery disconnect unit (BDU) and other units that are not negligible in mass. This paper describes the mass optimization work done on one of the hybrid batteries using CAE simulation. This was a multidisciplinary optimization project, in which modal performance and fatigue damage were accessed through CAE analysis at both the battery pack level, and at the vehicle level.

Stochastic pre-ignition (SPI) has been commonly observed in turbocharged spark-ignition direct-injection (SIDI) engines at low-speed and high-load conditions, which causes extremely high cylinder pressures that can damage an engine immediately or degrade the engine life. The compositions and properties of fuels and lubricants have shown a strong impact on SPI frequency. This study experimentally evaluated SPI behaviors on a 2.0-liter 4-cylinder turbocharged SIDI engine with China V market fuel and China fuel blended to US Tier II fuel specifications. China V market fuel showed significantly higher SPI frequency and severity than China blended US Tier II fuel, which was attributed to its lower volatility between 100 °C to 150 °C (or lower T60 to T90 in the distillation curve). Two different formulations of lubricant oils were also tested and their impact on SPI were compared.

During the development of an automotive acoustic package, valuable information can be gained by visualizing the acoustic energy flow through the Front-of-Dash (FOD) when a sound source is placed in the engine compartment. Two of the commonly used methods for generating the visual map of the acoustic field include Sound Intensity measurements and array technologies. An alternative method is to use a tracked 3-dimensional acoustic probe to scan and visualize the FOD in real-time when the sound source is injecting noise into the engine compartment. The scan is used to focus the development of the FOD acoustic package on the weakest areas by identifying acoustic leaks and locations with low Transmission Loss. This paper provides a brief discussion of the capabilities of the tracked 3-D acoustic probe, and presents examples of the implementation of the probe during the development of the FOD acoustic package for two mid-sized sedans.

The implementation of electronic shifters (e-shifter) for automatic transmissions in vehicles has created many new opportunities for the customer facing transmission interface and in-vehicle packaging. E-shifters have become popular in recent years as their smaller physical size leads to packaging advantages, they reduce the mass of the automatic transmission shift system, they are easier to install during vehicle assembly, and act as an enabler for autonomous driving. A button-style e-shifter has the ability to create a unique customer interface to the automatic transmission, as it is very different from the conventional column lever or linear console shifter. In addition to this, a button-style e-shifter can free the center console of valuable package space for other customer-facing functions, such as storage bins and Human-Machine Interface controllers.

Electric vehicles have a strong potential to reduce a continued dependence on fossil fuels and help the environment by reducing pollution. Despite the desirable advantage, the introduction of electrified vehicles into the market place continues to be a challenge due to cost, safety, and life of the batteries. General Motors continues to bring vehicles to market with varying level of hybrid functionality. Since the introduction of Li-ion batteries by Sony Corporation in 1991 for the consumer market, significant progress has been made over the past 25 years. Due to market pull for consumer electronic products, power and energy densities have significantly increased, while costs have dropped. As a result, Li-ion batteries have become the technology of choice for automotive applications considering space and mass is very critical for the vehicles.

The objective of this research is a detailed investigation of particulate sizing and number count from a spark-ignited, direct-injection (SIDI) engine at different operating conditions. The engine is a 549 [cc] single-cylinder, four-valve engine with a flat-top piston, fueled by Tier II EEE. A baseline engine operating condition, with a low number of particulates, was established and repeatability at this condition was ascertained. This baseline condition is specified as 2000 rpm, 320 kPa IMEP, 280 [°bTDC] end of injection (EOI), and 25 [°bTDC] ignition timing. The particle size distributions were recorded for particle sizes between 7 and 289 [nm]. The baseline particle size distribution was relatively flat, around 1E6 [dN/dlogDp], for particle diameters between 7 and 100 [nm], before dropping off to decreasing numbers at larger diameters. Distributions resulting from a matrix of different engine conditions were recorded.

Styrene-Butadiene Rubber (SBR), a copolymer of butadiene and styrene, is widely used in the automotive industry due to its high durability and resistance to abrasion, oils and oxidation. Some of the common applications include tires, vibration isolators, and gaskets, among others. This paper characterizes the dynamic behavior of SBR and discusses the suitability of a visco-elastic model of elastomers, known as the Kelvin model, from a mathematical and physical point of view. An optimization algorithm is used to estimate the parameters of the Kelvin model. The resulting model was shown to produce reasonable approximations of measured dynamic stiffness. The model was also used to calculate the self heating of the elastomer due to energy dissipation by the viscous damping components in the model. Developing such a predictive capability is essential in understanding the dynamic behavior of elastomers considering that their dynamic stiffness can in general depend on temperature.

Stochastic Preignition (SPI) is an abnormal combustion phenomenon for internal combustion engines (ICE), which has been a significant impact to automotive companies developing high efficiency, turbocharged, direct fuel injection, spark ignited engines. It is becoming clearer what fuel properties are related to the cause of SPI, whether directly with fuel preparation in the cylinder, or mechanisms related to the deposit build-up which contributes to initial and follow-on SPI events. The purpose of this paper is to provide a summary of global market gasoline fuel properties with special attention given to properties and specific compounds from the fuel and fuel additives that can contribute to SPI and the deposit build-up in engines. Based on a review of the global fuel quality, it appears that the fuel quality has not caught up to meet the technology requirements for fuel economy from modern technology engines.

A primary goal of large eddy simulation, LES, is to capture in-cylinder cycle-to-cycle variability, CCV. This is a first step to assess the efficacy of 35 consecutive computed motored cycles to capture the kinetic energy in the TCC-III engine. This includes both the intra-cycle production and dissipation as well as the kinetic energy CCV. The approach is to sample and compare the simulated three-dimensional velocity equivalently to the available two-component two-dimensional PIV velocity measurements. The volume-averaged scale-resolved kinetic energy from the LES is sampled in three slabs, which are volumes equal to the two axial and one azimuthal PIV fields-of-view and laser sheet thickness. Prior to the comparison, the effects of sampling a cutting plane versus a slab and slabs of different thicknesses are assessed. The effects of sampling only two components and three discrete planar regions is assessed.

Gasoline Direct Injection (GDI) has become the preferred technology for spark-ignition engines resulting in greater specific power output and lower fuel consumption, and consequently reduction in CO2 emission. However, GDI engines face a substantial challenge in meeting new and future emission limits, especially the stringent particle number (PN) emissions recently introduced in Europe and China. Studies have shown that the fuel used by a vehicle has a significant impact on engine out emissions. In this study, nine fuels with varying chemical composition and physical properties were tested on a modern turbo-charged side-mounted GDI engine with design changes to reduce particulate emissions. The fuels tested included four fuels meeting US certification requirements; two fuels meeting European certification requirements; and one fuel meeting China 6 certification requirements being proposed at the time of this work.

The performance of a High Voltage (HV) battery in an advanced propulsion application is often highly dependent on the customer controlled climate settings of the vehicle system. Cooling of the battery requires an understanding of the environment in which it is expected to operate. Results from testing on various air-cooled systems will be discussed to portray the interactions of the battery system design and the climate control system design. The following topics (in relation to battery cooling) will be discussed: climate control system temperature settings; climate-control system fan settings; climate control system recirculation mode and outside air mode settings; venting of the battery thermal system exhaust air; and the battery location and mounting.

Stochastic Preignition (SPI) is an abnormal combustion event that occurs in a turbocharged engine and can lead to the loss in fuel economy and engine hardware damage, and in turn result in customer dissatisfaction. It is a significant limiting factor on the use and continued downsizing of turbocharged spark ignited direct injection (SIDI) gasoline engines. Understanding and mitigating all the factors that cause and influence the rate and severity of SPI occurrence are of critical importance to the engine’s continued use and fuel economy improvements for future designs. Previous studies have shown that the heavy molecular weight components of the fuel formulations are one factor that influences the rate of SPI from a turbocharged SIDI gasoline engine. All the previous studies have involved analyzing the fuel’s petroleum hydrocarbon chemistry, but not specifically the additives that are put in the fuel to protect and clean the internal components over the life of the engine.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

As passenger vehicle design evolves and accelerates, the use of multi-body dynamics solvers has proven to be invaluable in the engineering workflow. MBD solvers allow engineers to build virtual vehicle models that can accurately simulate vehicle responses and calculate internal forces, which previously could only be assessed using physical prototype builds with hundreds of measurement transducers. Evaluation and selection of solvers within an engineering environment is inherently a multi-dimensional activity that can include ease of use, retention of previously developed expertise, accuracy, speed, and integration with existing analysis processes. We discuss here some of the challenges present in developing capability and accumulating data to support each of these criteria. Developing a pilot model that is capable of being applied to a comprehensive set of use cases, and then verifying those use cases, required significant project management activity.

Designing power electronics to operate in harsh vehicle environments while meeting packaging requirements such as mass, volume, and power density, creates several challenges for their mechanical design. In this work, we concentrate on the power inverter module (PIM) which converts high voltage (HV) DC voltage power from the HV battery to AC power to drive the motor. The PIM main components are the power module, gate drive and the bulk capacitor. The sizing and selection of the bulk capacitor and power module depend on performance criteria and drive profiles in addition to operating temperatures. In this work, we share the main challenges of packaging components within the inverter. We then discuss best practices to ensure a robust mechanical design which meets inverter durability and reliability targets for an electric vehicle application. The main challenges discussed are bulk capacitor thermals, sealing, and Silicon Carbide (SiC) packaging.