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Cost reduction in the automotive industry becomes a widely-adopted operational strategy not only for Original Equipment Manufacturers (OEMs) that take cost leader generic corporation strategy, but also for many OEMs that take differentiation generic corporation strategy. Since differentiation generic strategy requires an organization to provide a product or service above the industry average level, a premium is typically included in the tag price for those products or services. Cost reduction measures could increase risks for the organizations that pursue differentiation strategy. Although manufacturers in the automotive industry dramatically improved production efficiency in past ten years, they are still facing the pressure of cost control. The big challenge in cost control for automakers and suppliers is increasing prices of raw materials, energy and labor costs. These costs create constraints for the traditional economic expansion model.

Antilock brake systems for air braked vehicles have been growing in popularity in Great Britain and Europe and appear to be candidates for extensive use in the United States as well. Previous mandated use in the United States during the 1970's was not successful, in part because of reliability problems, and the National Highway Traffic Safety Administration (NHTSA) has decided that a thorough evaluation of air brake antilock systems is necessary prior to any decision about the appropriateness of future mandatory use in the United States. This paper describes the electronic data collection equipment and processing techniques which are being used in the NHTSA 200 truck evaluation project. Detailed maintenance histories for each truck are being recorded manually as a separate segment of the project. An average of 6 to 7 megabytes of data per week is being collected in the various cities in which fleets are operating test vehicles.

There is growing interest in additive manufacturing technologies for prototype if not serial production of complex internal combustion engine components such as cylinder heads and pistons. In support of this general interest the authors undertook an experimental bench test to evaluate opportunities for cooling jacket improvement through geometries made achievable with additive manufacturing. A bench test rig was constructed using electrical heating elements and careful measurement to quantify the impact of various designs in terms of heat flux rate and convective heat transfer coefficients. Five designs were compared to a baseline - a castable rectangular passage. With each design the heat transfer coefficients and heat flux rates were measured at varying heat inputs, flow rates and pressure drops. Four of the five alternative geometries outperformed the baseline case by significant margins.

The classical methods of measuring acoustic absorption coefficient using an impedance tube and a reverberation chamber are well established [1, 2]. However, these methods are not suitable for in-situ applications. The two in-situ methods; single channel microphone (P- probe) and dual channel acoustic pressure and particle velocity (Pu-probe) methods based on measurement of impulse response functions of the material surface under test, provide considerable advantage in data acquisition, signal processing, ease and mobility of measurement setup. This paper evaluates the measurement techniques of these two in-situ methods and provides results of acoustic absorption coefficient of a commercial artificial Astroturf, a Dow quash material, and a grass surface.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

Increasingly, the exchanges of data in complex ECM (Electronic Control Module) systems rely on multiple communication networks across various physical and network layers. This has greatly increased system flexibility and provided an excellent medium to create well-defined exchangeable interfaces between components; however this added flexibility comes with increased network complexity. A system-level approach allows for the optimization of data exchange and network configuration as well as the development of a comprehensive network failure strategy. Many current ECM systems utilize complex multi-network communication strategies to exchange and control data to components. Recently, Caterpillar implemented an HIL (Hardware-In-the-Loop) test system that provides an approach for developing and testing a comprehensive ECM network strategy.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

The effect of flow direction towards the spark plug electrodes on ignition parameters is analyzed using an innovative spark aerodynamics fixture that enables adjustment of the spark plug gap orientation and plug axis tilt angle with respect to the incoming flow. The ignition was supplied by a long discharge high energy 110 mJ coil. The flow was supplied by compressed air and the spark was discharged into the flow at varying positions relative to the flow. The secondary ignition voltage and current were measured using a high speed (10MHz) data acquisition system, and the ignition-related metrics were calculated accordingly. Six different electrode designs were tested. These designs feature different positions of the electrode gap with respect to the flow and different shapes of the ground electrodes. The resulting ignition metrics were compared with respect to the spark plug ground strap orientation and plug axis tilt angle about the flow direction.

The U. S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) National Automotive Center (NAC) owns a fleet of ten Hydrogen Hybrid Internal Combustion Engine (H2ICE) vehicles that have been demonstrated in various climates from 2008 through 2010. This included demonstrations in Michigan, Georgia, California and Hawaii. The fleet was consolidated into a single location between July 2009 and April 2010. Between July of 2009 and January of 2011, data collection was completed on the fleet of H2ICE vehicles deployed to Oahu, Hawaii for long-term duration testing. The operation of the H2ICE vehicles in Hawaii utilized standard operation of a non-tactical vehicle at a real-world military installation. The vehicles were fitted with data acquisition equipment to record the operation and performance of the H2ICE vehicles; maintenance and repair data was also recorded for the fleet of vehicles.

This paper discusses the implications of computerizing the SAE #2 clutch friction durability tests that General Motors Corporation and Ford Motor Company require for automatic transmission fluid certification. There are three reasons for this paper. 1) Friction durability testing is a significant part of a much larger battery of tests needed to qualify a fluid. 2)There have been recent modifications concerning computerization of both the Ford and GM tests. 3) Because there are only two OEM qualified testing facilities, the details of certain testing intricacies in the areas of data acquisition, reduction and reporting may not be as understood as well as in other areas of automotive-based standardized testing. Formulators of automatic transmission fluid need to be aware of all details surrounding the collection and evaluation of the data that will result in the final test report.

Tremendous amount of useful information can be extracted from the cylinder pressure signal for engine combustion control. However, the physical cylinder pressure sensors are undesirably expensive and their health need to be monitored for fault diagnostic purpose as well. This paper presents the results of the development of a virtual cylinder pressure sensor (VCPS) with individual variable-oriented independent estimators. Two neural network-based independent cylinder pressure related variable estimators were developed and verified at steady state. The results show that these models can predict the variables correctly compared with the extracted variables from the measured physical cylinder pressure sensor signal. Good generalization capabilities of the developed models are observed in the sense that the models work well not only for the training data set but also for the new inputs that they have never been exposed to before.

An automated data handling system to assist in the operation of a diesel engine lubricant test laboratory, involving two mini-computers, is described in terms of why it was needed, the design goals sought, and the operating experience which resulted from its use. The concept of two digital systems, one for on-line data logging and another as a ready back-up, as well as a data processor, is discussed. Direct and peripheral benefits which have resulted from the application of the system, such as semi-automated report processing, operational aids, and various engineering applications, are reported.

Trained human raters have been used by organizations such as the Coordinating Research Council (CRC) to assess the vehicle driveability performance effect of fuel volatility. CRC conducts workshops to test fuel effects and their impact on vehicle driveability. CRC commissioned Southwest Research Institute (SwRI) to develop a “Trick Car” vehicle that could trigger malfunctions on-demand that mimic driveability events. This vehicle has been used to train novice personnel on the CRC Driveability Procedure E-28-94. While largely effective, even well-trained human raters can be inconsistent with other raters. Further, CRC rater workshop programs used to train and calibrate raters are infrequent, and there are a limited number of available trained raters. The goal of this program was to augment or substitute human raters with an electronic driveability sensing system.

This paper describes a new method for measuring oil consumption using laser induced breakdown spectroscopy (LIBS). LIBS focuses a high energy laser pulse on a sample to form a transient plasma. As the plasma cools, each element produces atomic emission lines which can be used to identify and quantify the elements present in the original sample. In this work, a LIBS system was used on simulated engine exhaust with a focus on quantifying the inorganic components (termed ash) of the particulate emissions. Because some of the metallic elements in the ash almost exclusively result from lube oil consumption, their concentrations can also be correlated to an oil consumption rate. Initial testing was performed using SwRI’s Exhaust Composition Transient Operation Laboratory®(ECTO-Lab®) burner system so that oil consumption and ash mass could be precisely controlled.

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques.

To enable the evaluation of off-calibration powertrain operation, a selective interrupt and control (SIC) test capability was developed as part of an EPA evaluation of a 1.6 L EcoBoost® engine. A control and data acquisition device sits between the stock powertrain controller and the engine; the device selectively passes through or modifies control signals while also simulating feedback signals. This paper describes the development process of SIC that enabled a test engineer to command off-calibration setpoints for intake and exhaust cam phasing as well as ignition timing without the need for an open ECU duplicating the stock calibration. Results are presented demonstrating the impact of ignition timing and cam phasing on engine efficiency. When coupled with combustion analysis and crank-domain data acquisition, this test configuration provides a complete picture of powertrain performance.

For many years the SAE No. 2 friction machine has been used to measure the coefficient of friction obtained through the interaction of fluid, steel and clutch material. In addition, by forcing energy through the wetted clutch-steel interface and measuring the decay of the coefficient of friction over time, the durability of the materials and fluids can be determined. This paper discusses the use of a numerical computer model to duplicate SAE No. 2 data. The inputs for this model include test stand geometry and physical properties as well as output from a low velocity friction apparatus (LVFA). The LVFA uses a small disc of friction material, a small disc of steel material, and a small sample of fluid to generate a coefficient versus speed curve (m vs v). It was found that torque traces and speed traces generated by this model correlate well with actual SAE No. 2 data. THERE ARE SEVERAL REASONS for creating this model.

Large channel count data acquisition systems have seen increasing use in the acquisition and analysis of rotating machinery, these systems have the ability to generate very large amounts of data for analysis. The most common operating measurement made on powertrains or automobiles on the road or on dynamometers has become the order track measurement. Order tracking analysis can generate a very large amount of information that must be analyzed, both due to the number of channels and orders tracked. Analysis methods to efficiently analyze large numbers of Frequency Response Function (FRF) measurements have been developed and used over the last 20 years in many troubleshooting applications. This paper develops applications for several FRF based analysis methods as applied for efficient analysis of large amounts of order track data.

To meet increasingly stringent emissions and fuel economy regulations, many Original Equipment Manufacturers (OEMs) have recently developed and deployed small, high power density engines. Turbocharging, coupled with gasoline direct injection (GDI) has enabled a rapid engine downsizing trend. While these turbocharged GDI (TGDI) engines have indeed allowed for better fuel economy in many light duty vehicles, TGDI technology has also led to some unintended consequences. The most notable of these is an abnormal combustion phenomenon known as low speed pre-ignition (LSPI). LSPI is an uncontrolled combustion event that takes place prior to spark ignition, often resulting in knock, and has been known to cause catastrophic engine damage. LSPI propensity depends on a number of factors including engine design, calibration, fuel properties and engine oil formulation. Several engine tests have been developed within the industry to better understand the phenomenon of LSPI.

This paper presents the development of a reduced-order powertrain model for energy and SOC estimation of a multi-mode plug-in hybrid electric vehicle using only vehicle speed profile and route elevation as inputs. Such a model is intended to overcome the computational inefficiencies of higher fidelity powertrain and vehicle models in short and long horizon energy optimization efforts such as Coordinated Adaptive Cruise Control (CACC), Eco Approach and Departure (EcoAND), Eco Routing, and PHEV mode blending. The reduced-order powertrain model enables Connected and Automated Vehicles (CAVs) to utilize the onboard sensor and connected data to quickly react and plan their maneuvers to highly dynamic road conditions with minimal computational resources.