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A prototype 2007 ISL Cummins diesel engine equipped with a diesel oxidation catalyst (DOC), diesel particle filter (DPF), variable geometry turbocharger (VGT), and cooled exhaust gas recirculation (EGR) was tested at Southwest Research Institute (SwRI) under a high-load accelerated durability cycle for 1000 hours with B20 soy-based biodiesel blends and ultra-low sulfur diesel (ULSD) fuel to determine the impact of B20 on engine durability, performance, emissions, and fuel consumption. At the completion of the 1000-hour test, a thorough engine teardown evaluation of the overhead, power transfer, cylinder, cooling, lube, air handling, gaskets, aftertreatment, and fuel system parts was performed. The engine operated successfully with no biodiesel-related failures. Results indicate that engine performance was essentially the same when tested at 125 and 1000 hours of accumulated durability operation.

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data.

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability—both of which are important metrics often overlooked during the engineering design process.

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

The authors present transient wind velocity measurements from two successive, well-documented truck platooning track-test campaigns to assess the wake-shedding behavior experienced by trucks in various platoon formations. Utilizing advanced analytics of data from fast-response (100-200-Hz) multi-hole pressure probes, this analysis examines aerodynamic flow features and their relationship to energy savings during close-following platoon formations. Applying Spectral analysis to the wind velocity signals, we identify the frequency content and vortex-shedding behavior from a forward truck trailer, which dominates the flow field encountered by the downstream trucks. The changes in dominant wake-shedding frequencies correlate with changes to the lead and follower truck fuel savings at short separation distances.

For multiphase advanced high strength steels (AHSS), the constituent phase properties play a crucial role in determining the overall mechanical behaviors. Therefore, it is important to accurately measure/estimate the constituent phase properties in the research of AHSS. In this study, a new nanoindentation-based inverse method that we developed was adopted in estimating the phase properties of a low alloy Quenching and Partitioning (Q&P) steel. A microstructure-based Finite Element (FE) model was also generated based on the Electron BackScatter Diffraction (EBSD) and Scanning Electron Microscopy (SEM) images of the Q&P steel. The phase properties estimated from nanoindentation were first compared with those estimated from in-situ High Energy X-Ray Diffraction (HEXRD) test and, then, employed in the generated FE model to examine whether they can be appropriately used as the input properties for the model.

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses a Monte Carlo method to generate parameter sets that are fed to a variant of the road load equation. The modeled road load is then compared to the measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the current state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters.

Electric drive vehicles (EDVs) have complex thermal management requirements not present in conventional vehicles. In addition to cabin conditioning, the energy storage system (ESS) and power electronics and electric motor (PEEM) subsystems also require thermal management. Many current-generation EDVs utilize separate cooling systems, adding both weight and volume, and lack abundant waste heat from an engine for cabin heating. Some use battery energy to heat the cabin via electrical resistance heating, which can result in vehicle range reductions of 50% under cold ambient conditions. These thermal challenges present an opportunity for integrated vehicle thermal management technologies that reduce weight and volume and increase cabin heating efficiency. Bench testing was conducted to evaluate a combined fluid loop technology that unifies the cabin air-conditioning and heating, ESS thermal management, and PEEM cooling into a single liquid coolant-based system.

The strain-induced diffusionless shear transformation of retained austenite to martensite during straining of transformation induced plasticity (TRIP) assisted steels increases strain hardening and delays necking and fracture leading to exceptional ductility and strength, which are attractive for automotive applications. A novel technique that provides the retained austenite volume fraction variation with strain with improved precision is presented. Digital images of the gauge section of tensile specimens were first recorded up to selected plastic strains with a stereo digital image correlation (DIC) system. The austenite volume fraction was measured by synchrotron X-ray diffraction from small squares cut from the gage section. Strain fields in the squares were then computed by localizing the strain measurement to the corresponding region of a given square during DIC post-processing of the images recorded during tensile testing.

Currently, connected and autonomous vehicle (CAV) technology is being developed for Class 8 tractor trucks aimed at improved safety and fuel economy and reduced CO2 emissions. Despite extensive efforts conducted across the world, the reported efficiency gains were varied from different research groups, raising concerns about the fidelity of models, the performance of control, and the effectiveness of the experimental validation. One root cause for this variation stems from the fact that the efficiency gain obtained from the CAV is sensitive to real-world conditions, including surrounding traffic and road grade. This study presents an approach aimed at identifying representative public road sections and facilitating CAV research from this perspective. By employing the decision tree regression (DTR) method to the Fleet DNA database, the most representative road sections can be identified.

This paper presents two methods of characterizing and describing the formability of tailor welded blanks (TWB). The first method involves using miniature tensile specimens, extracted from TWB weld material, to quantify mechanical properties and material imperfection within TWB welds. This technique combines statistical methods of describing material imperfection together with conventional M-K method modeling techniques to determine safe forming limit diagrams for weld material. The second method involves the use of an extended M-K method modeling technique, which places multiple material thickness and material imperfections inside one overall model of TWB performance. These methods of describing TWB formability and their application to specific aluminum TWB populations are described.

This paper describes the need for dynamic (transient) simulation of automotive air conditioning systems, the reasons why such simulations are challenging, and the applicability of a general purpose off-the-shelf thermohydraulic analyzer to answer such challenges. An overview of modeling methods for the basic components are presented, along with relevant approximations and their effect on speed and accuracy of the results.

Diesel particulate samples were collected from a light duty engine operated at a single speed-load point with a range of biodiesel and conventional fuel blends. The oxidation reactivity of the samples was characterized in a laboratory reactor, and BET surface area measurements were made at several points during oxidation of the fixed carbon component of both types of particulate. The fixed carbon component of biodiesel particulate has a significantly higher surface area for the initial stages of oxidation, but the surface areas for the two particulates become similar as fixed carbon oxidation proceeds beyond 40%. When fixed carbon oxidation rates are normalized to total surface area, it is possible to describe the oxidation rates of the fixed carbon portion of both types of particulates with a single set of Arrhenius parameters. The measured surface area evolution during particle oxidation was found to be inconsistent with shrinking sphere oxidation.

In some studies, a relationship has been observed between increasing ethanol content in gasoline and increased particulate matter (PM) emissions from vehicles equipped with spark ignition engines. The fundamental cause of the PM increase seen for moderate ethanol concentrations is not well understood. Ethanol features a greater heat of vaporization (HOV) than gasoline and also influences vaporization by altering the liquid and vapor composition throughout the distillation process. A droplet vaporization model was developed to explore ethanol’s effect on the evaporation of aromatic compounds known to be PM precursors. The evolving droplet composition is modeled as a distillation process, with non-ideal interactions between oxygenates and hydrocarbons accounted for using UNIFAC group contribution theory. Predicted composition and distillation curves were validated by experiments.

An axisymmetric finite element model is generated to simulate the windshield glass damage propagation subjected to impact loading of a flying object. The windshield glass consists of two glass outer layers laminated by a thin poly-vinyl butyral (PVB) layer. The constitutive behavior of the glass layers is simulated using brittle damage mechanics model with linear damage evolution. The PVB layer is modeled with linear viscoelastic solid. The model is used to predict and examine through-thickness damage evolution patterns on different glass surfaces and cracking patterns for different windshield designs such as variations in thickness and curvatures.

In this paper, a two-dimensional microstructure-based finite element modeling method is adopted to investigate the effects of material parameters of the constituent phases on the macroscopic tensile behavior of Q&P steel and to perform a computational material design approach for performance improvement. For this purpose, a model Q&P steel is first produced and various experiments are then performed to characterize the model steel. Actual microstructure-based model is generated based on the information from EBSD, SEM and nano-indentation test, and the material properties for the constituent phases in the model are determined based on the initial constituent properties from HEXRD test and the subsequent calibration of model predictions to tensile test results. The influence of various material parameters of the constituents on the macroscopic behavior is then investigated.

In this paper, results of finite element crash simulation are presented for a TRIP steel side rail with and without considering the phase transformation during forming operations. A homogeneous phase transformation model is adapted to model the mechanical behavior of the austenite-to-martensite phase. The forming process of TRIP steels is simulated with the implementation of the material model. The distribution and volume fraction of the martensite in TRIP steels may be greatly influenced by various factors during forming process and subsequently contribute to the behavior of the formed TRIP steels during the crushing process. The results indicate that, with the forming induced phase transformation, higher energy absorption of the side rail can be achieved. The phase transformation enhances the strength of the side rail.

While standardized laboratory-scale wear tests are available to predict the lubricity of liquid fuels under ambient conditions, the reality is that many injection systems operate at elevated temperatures where fuel vaporization is too excessive to perform the measure satisfactorily. The present paper describes a High Pressure High Frequency Reciprocating Rig (HPHFRR) purposely designed to evaluate fuel lubricity in a pressurized environment at temperatures of up to 300°C. The remaining test parameters are identical to those of the widely standardized High Frequency Reciprocating Rig (HFRR). Results obtained using the HPHFRR indicate that wear rate with poor lubricity fuels is strongly sensitive to both temperature and oxygen partial pressure and may be orders of magnitude higher than at ambient conditions. Surprisingly however, wear rate was found to decrease dramatically at temperatures above 100°C, possibly due to evaporation of dissolved moisture.

This paper examines some key aspects of the manufacturing process that “ Transformation Induced Plasticity” (TRIP) steels would be exposed to, and systematically evaluate how the forming and thermal histories affect final strength and ductility of the material. We evaluate the effects of in-service temperature variations, such as under hood and hot/cold cyclic conditions, to determine whether these conditions influence final strength, ductility and energy absorption characteristics of several available TRIP steel grades. As part of the manufacturing thermal environment evaluations, stamping process thermal histories are included in the studies. As part of the in-service conditions, different pre-straining levels are included. Materials from four steel suppliers are examined. The thermal/straining history versus material property relationship is established over a full range of expected thermal histories and selected loading modes.

Commercial vehicle fuel economy is known to vary significantly with both positive and negative road grade. Medium- and heavy-duty vehicles operating at highway speeds require incrementally larger amounts of energy to pull heavy payloads up inclines as road grade increases. Non-hybrid vehicles are unable to recapture energy on descent and lose energy through friction braking. While the on-road effects of road grade are well understood, the majority of standard commercial vehicle drive cycles feature no road grade requirements. Additionally, the existing literature offers a limited number of sources that attempt to estimate the on-road energy implications of road grade in the medium- and heavy-duty space. This study uses real-world commercial vehicle drive cycles from the National Renewable Energy Laboratory's Fleet DNA database to simulate the effects of road grade on fuel economy across a range of vocations, operating conditions, and locations.