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In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices or existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations.

Smart technologies enabling connection among vehicles and between vehicles and infrastructure as well as vehicle automation to assist human operators are receiving significant attention as a means for improving road transportation systems by reducing fuel consumption – and related emissions – while also providing additional benefits through improving overall traffic safety and efficiency. For truck applications, which are currently responsible for nearly three-quarters of the total U.S. freight energy use and greenhouse gas (GHG) emissions, platooning has been identified as an early feature for connected and automated vehicles (CAVs) that could provide significant fuel savings and improved traffic safety and efficiency without radical design or technology changes compared to existing vehicles. A statistical analysis was performed based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning.

In an effort to better understand the operational requirements of port drayage vehicles and their potential for adoption of advanced technologies, National Renewable Energy Laboratory (NREL) researchers collected over 36,000 miles of in-use duty cycle data from 30 Class 8 drayage trucks operating at the Port of Long Beach and Port of Los Angeles in Southern California. These data include 1-Hz global positioning system location and SAE J1939 high-speed controller area network information. Researchers processed the data through NREL’s Drive-Cycle Rapid Investigation, Visualization, and Evaluation tool to examine vehicle kinematic and dynamic patterns across the spectrum of operations. Using the k-medoids clustering method, a repeatable and quantitative process for multi-mode drive cycle segmentation, the analysis led to the creation of multiple drive cycles representing four distinct modes of operation that can be used independently or in combination.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.

The traditional method of engine knock detection is to compare the knock intensity with a predetermined threshold. The calibration of this threshold is complex and difficult. A statistical knock detection method is proposed in this paper to reduce the effort of calibration. This method dynamically calculates the knock threshold to determine the knock event. Theoretically, this method will not only adapt to different fuels but also cope with engine aging and engine-to-engine variation without re-calibration. This method is demonstrated by modeling and evaluation using real-time engine dynamometer test data.

In the absence of prototypes, analytical methods such as finite element analysis are very useful in resolving noise and vibration problems, by predicting dynamic behavior of the automotive components and systems. Finite Element Analysis (FEA) is a simulation technique and involves making assumptions that affect analytical results. Acceptance and use of these results is greatly enhanced through test validation. In this paper, dynamic behavior of the automotive propshaft equipped with cardboard liner and torsional damper is investigated. The finite element model is validated at both component and subsystem levels using frequency response functions. Effects of the cardboard liner and torsional damper on the propshaft bending, torsional and breathing frequencies are studied under free-free boundary conditions. Effects of the U-Joint stiffness along with other design variables on the driveshaft dynamic behavior are also studied.

The fundamentals of multi-leaf spring design as determined through beam theory offers a general perspective on how finite element analysis works. Additionally, the fundamentals of combining dissimilar materials require a basic knowledge of how the combined equivalent modulus affects the overall stiffness characteristics of multi-leaf design. By capturing these basic fundamentals into finite element modeling, an analysis of a steel-composite multi-leaf contact model relative to an idealized steel-composite multi-leaf model shows the importance of contact modeling. The results demonstrate the important differences between an idealized non-contact model relative to a complete contact model.

The starter drive clutch is a one way roller clutch and a key component in a starter motor that is used to crank internal combustion engines. The starter drive clutch transmits torque from an electrical motor to a ring gear mounted on a cranking shaft in an engine thus cranks the engine. The clutch also prevents the whole starter from damage caused by extremely high load and/or extremely high speed applied to the starter pinion from the engine. Drive slippage and barrel cracking are two major failure modes for the starter drive[1]. Insufficient torque capacity results in drive slippage while excessive high hoop stress on the clutch barrel ring causes barrel crack. To eliminate drive slippage failure, the clutch should be designed with high torque capacity. High torque capacity, however, is a cause of high hoop stress on the barrel that may result in the cracked barrel failure. Higher torque capacity and lower hoop stress are two completely opposite design directions.

Interior compartment doors are required by Federal Motor Vehicle Safety Standard (FMVSS) 201, to stay closed during physical head impact testing, and when subjected to specific inertia loads. This paper defines interior compartment doors, and shows examples of several different latches designed to keep these doors closed. It also explores the details of the requirements that interior compartment doors and their latches must meet, including differing requirements from automobile manufacturers. It then shows the conventional static method a supplier uses to analyze a latch and door system. And, since static calculations can't always capture the complexities of a dynamic event, this paper also presents a case study of one particular latch and door system showing a way to simulate the forces experienced by a latch. The dynamic simulation is done using Finite Element Analysis and instrumentation of actual hardware in physical tests.

Visteon has developed a CAE procedure to qualify instrument panel (IP) products under the vehicle key life test environments, by employing a set of CAE simulation and durability techniques. The virtual key life test method simulates the same structural configuration and the proving ground road loads as in the physical test. A representative dynamic road load profile model is constructed based on the vehicle proving ground field data. The dynamic stress simulation is realized by employing the finite element transient analysis. The durability evaluation is based on the dynamic stress results and the material fatigue properties of each component. The procedure has helped the IP engineering team to identify and correct potential durability problems at earlier design stage without a prototype. It has shown that the CAE virtual key life test procedure provides a way to speed up IP product development, to minimize prototypes and costs.

Low resolution fractional factorial experimental designs, used in screening, are more popular than ever due to the ever increasing costs of materials and machine time. Experimenters have to be more precise in their analysis, making every degree of freedom count. Resolution III designs are becoming more commonplace for use in screening designs. When running unsaturated resolution III designs there are extra degrees of freedom stemming from unassigned interactions. It is common practice to utilize these extra degrees of freedom to approximate error. In many cases, this common practice can over state the error and lead to erroneous results regarding factor statistical significance. Utilizing saturated resolution III designs and statistically analyzing unassigned interactions while estimating the error with replication is a method for strengthening the DOE strategy and improving the results from screening designs.

There is still much controversy and confusion in industry today regarding the use of process capability indices and analysis. A lack of knowledge regarding the underlying variation assumptions and rationale sampling strategies in indices such as Cp, Cpk, Pp and Ppk have added to the confusion and in many cases has led to misapplication of these widely used metrics. This issue has also promoted inconsistency in the assessment of long-term versus short-term capability and has hampered the true characterization of processes which is a critical step in any continuous improvement effort. Capability indices and analysis, when properly applied can impart a wealth of knowledge regarding process performance as well as provide focus for improvement activity through the proper characterization and enumeration of variation. Being able to properly characterize variation if the first step in reducing it.

Realizing the value of knowledge, corporations are turning to Knowledge Based Engineering (KBE) as a design process. A fuel rail KBE tool was created at Visteon with the purpose of increasing knowledge retention and delivering knowledge based designs to the customer much quicker than with conventional methods. Currently, both engineers and CAD designers are using the Fuel Rail KBE Modeler at Visteon. It has been used on many vehicle programs and has saved the company countless person-hours of development time. The Fuel Rail KBE Modeler is a powerful tool that saves resources through automation of both the design and analysis processes. This paper documents the incorporation of automated FEA capability into the KBE environment.

A new risk management method, the System Integrated Life Cycle Risk Management Methodology (SILC RMM), is based on systems engineering principles and is compatible with current standards. The SILC method, created by automotive engineers, addresses shortcomings with FMEA and other risk management (RM) methods, and integrates the FMEA and risk management functions into day-to-day engineering project activities. The SILC approach accommodates technology, cost, schedule, environmental and safety risks throughout the systems engineering project life cycle - from conception to recycle. It allows direct integration of RM information with system and project information for more efficient and effective utilization of resources and optimal overall risk management.

Composite materials can be used effectively for structural applications where high strength-to-weight and stiffness-to-weight ratios are required. Although the design and analysis techniques for static, buckling and vibration loadings are fairly well established, methodologies for analysis of composite structures under impact loading are still a major research activity. This paper presents a nonlinear finite-element analysis method to analyze a composite structure subjected to axial impact load. The analysis was performed using MSC/DYTRAN FE code while pre and post processing were done using MSC/PATRAN program. In addition, a steel tube of the same geometry was analyzed for comparison purpose.

Visteon has developed a CAE procedure to qualify plastic door trim assemblies under the vehicle door slam Key Life Test (KLT) environments. The CAE Virtual Door Slam Test (VDST) procedure simulates the environment of a whole door structural assembly, as a hinged in-vehicle door slam configuration. It predicts the durability life of a plastic door trim sub-assembly, in terms of the number of slam cycles, based on the simulated stresses and plastic material fatigue damage model, at each critical location. The basic theory, FEA methods and techniques employed by the VDST procedure are briefly described in this paper. Door trim project examples are presented to illustrate the practical applications and their results, as well as the correlation with the physical door slam KLTs.

Noise Vibration and Harshness (NVH) characteristics have become a key differentiator between “Good” vehicles and “Best-In-Class” vehicles. While all OEM's and most Tier 1 suppliers have on-site in-ground chassis dynamometers, a need was identified to design, develop and bring to market, a fully capable portable NVH full vehicle chassis system. The original concept entailed a device, which could be brought to the customer's location, be fully self contained, requiring no external power, and provide data acquisition using transducers that would not contact the vehicle. With traditional instrumentation taking several hours to install, non-contacting lasers would be used to provide significant timesaving, and prevent any possible damage to the vehicle from pinched wires. The new methodology should provide data acquisition in as little as 20 minutes. Analysis would be accomplished immediately following testing, with hard copies available before the next vehicle was ready to run.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and optimization of a hydraulic steering pump for NVH performance. DOE methods were applied to RPM-domain data to examine the effect of several different factors, as well as the interactions between these factors, on pump NVH. Whereas most DOE analyses typically consider only a single response variable, the present work considered multiple response variables. Specifically, pump NVH performance curves for several pump rotational orders over a range of shaft speeds were analyzed. Thus, it was possible to determine the effect of the factors in question over the entire speed range of pump operation, rather than a single speed or setting. Statistical methods were applied to determine which factors and interactions had a significant effect on pump NVH. These factors were used to construct an empirical mathematical prediction model for NVH performance.

Induction noise, which radiates from the open end of the engine air induction system, can be of significant importance in reducing vehicle interior noise and tuning the interior sound to meet customer expectations. This makes understanding the source noise critical to the development of the air induction system and the vehicle interior sound quality. Given the ever-decreasing development times, it is highly desirable to use computer-aided engineering (CAE) tools to accelerate this process. Many tools are available to simulate induction noise or, more generally, duct acoustics. The tools vary in degrees of complexity and inherent assumptions. Three-dimensional tools will account for the most general of geometries. However, it is also possible to model the duct acoustics with quasi-three-dimensional or one-dimensional tools, which may be faster as well.