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This paper introduces a promising approach for developing an integrated traction motor drive based on the Integrated Modular Motor Drive (IMMD) concept. The IMMD concept strives to meet aggressive power density and performance targets by modularizing both the machine and power electronics and then integrating them into a single combined machine-plus-drive structure. Physical integration of the power electronics inside the machine makes it highly desirable to increase the power electronics operating temperature including higher power semiconductor junction temperatures and improved device packaging. Recent progress towards implementing the IMMD concept in an integrated traction motor drive is summarized in this paper. Several candidate permanent magnet (PM) machine configurations with different numbers of phases between 3 and 6 are analyzed to compare their performance characteristics and key application features.

To make informed decisions about travel and vehicle purchase, consumers need unbiased and accurate information of the fuel economy they will actually obtain. In the past, the EPA fuel economy estimates based on its 1984 rules have been widely criticized for overestimating on-road fuel economy. In 2008, EPA adopted a new estimation rule. This study compares the usefulness of the EPA's 1984 and 2008 estimates based on their prediction bias and accuracy and attempts to improve the prediction of on-road fuel economies based on consumer and vehicle attributes. We examine the usefulness of the EPA fuel economy estimates using a large sample of self-reported on-road fuel economy data and develop an Individualized Model for more accurately predicting an individual driver's on-road fuel economy based on easily determined vehicle and driver attributes. Accuracy rather than bias appears to have limited the usefulness of the EPA 1984 estimates in predicting on-road MPG.

To provide useful information for automakers to design successful plug-in hybrid electric vehicle (PHEV) products and for energy and environmental analysts to understand the social impact of PHEVs, this paper addresses the question of how many of the U.S. consumers, if buying a PHEV, would prefer what electric ranges. The Market-oriented Optimal Range for PHEV (MOR-PHEV) model is developed to optimize the PHEV electric range for each of 36,664 sampled individuals representing U.S. new vehicle drivers. The optimization objective is the minimization of the sum of costs on battery, gasoline, electricity and refueling hassle.

It is rare for an attempt towards optimization at the fleet-level when consideration is given to the sheer number of seemingly unpredictable interactions among vehicles and infrastructure in congested urban areas. To close the gap, we introduce a simulation based framework to explore the impact of speed synchronization on fuel economy improvement for fleets in traffic. The framework consists of traffic and vehicle modules. The traffic module is used to simulate driver behavior in urban traffic; and the vehicle module is employed to estimate fuel economy. Driving schedule is the linkage between these two modules. To explore the impact, a connected vehicle technology sharing vehicle speed information is used for better fuel economy of a fleet including six vehicles. In all scenarios analyzed, the leading vehicle operates under the EPA Urban Dynamometer Driving Schedule (UDDS), while the other five vehicles follow the leader consecutively.

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.

Metal additive manufacturing has high potential to produce automobile parts, due to its shape flexibility and unique material properties. On the other hand, residual stress which is generated by rapid solidification causes deformation, cracks and failure under building process. To avoid these problems, understanding of internal residual stress distribution is necessary. However, from the view point of measureable area, conventional residual stress measurement methods such as strain gages and X-ray diffractometers, is limited to only the surface layer of the parts. Therefore, neutron which has a high penetration capability was chosen as a probe to measure internal residual stress in this research. By using time of flight neutron diffraction facility VULCAN at Oak Ridge National Laboratory, residual stress for mono-cylinder head, which were made of aluminum alloy, was measured non-distractively. From the result of precise measurement, interior stress distribution was visualized.

The deactivation of diesel oxidation catalysts (DOCs) by soot contamination and lube-oil derived phosphorus poisoning is investigated. Pt/CeO2/γ-AI2O3 DOCs aged using three different protocols developed by the authors and six high mileage field-returned DOCs of similar formulation are evaluated for THC and CO oxidation performance using a bench-flow reactor. Collectively, these catalysts exhibit a variety of phosphorus and soot morphologies contributing to performance deactivation.

Modern diesel engines used in light-duty transportation applications have peak brake thermal efficiencies in the range of 40-42% for high-load operation with substantially lower efficiencies at realistic road-load conditions. Thermodynamic energy and exergy analysis reveals that the largest losses from these engines are due to combustion irreversibility and heat loss to the coolant, through the exhaust, and by direct convection and radiation to the environment. Substantial improvement in overall engine efficiency requires reducing or recovering these losses. Unfortunately, much of the heat transfer either occurs at relatively low temperatures resulting in large entropy generation (such as in the air-charge cooler), is transferred to low-exergy flow streams (such as the oil and engine coolant), or is radiated or convected directly to the environment.

Measuring axial exhaust species concentration distributions within a wall-flow aftertreatment device provides unique and significant insights regarding the performance of complex devices like the SCR-on-filter. In this particular study, a less complex aftertreatment configuration which includes a DOC followed by two uncoated partial flow filters (PFF) was used to demonstrate the potential and challenges. The PFF design in this study was a particulate filter with alternating open and plugged channels. A SpaciMS [1] instrument was used to measure the axial NO2 profiles within adjacent open and plugged channels of each filter element during an extended passive regeneration event using a full-scale engine and catalyst system. By estimating the mass flow through the open and plugged channels, the axial soot load profile history could be assessed.

This paper utilizes GPS tracked multiday travel activities to estimate the temporal distribution of electricity loads and assess battery electric vehicle (BEV) grid impacts at a significant market penetration level. The BEV load and non-PEV load vary by time of the day and day of the week. We consider two charging preferences: home priority assumes BEV drivers prefer charging at home and would not charge at public charging stations unless the state of charge (SOC) of the battery is not sufficient to cover the way back to home; and charging priority does not require drivers to defer charging to home and assumes drivers will utilize the first available charging opportunity. Both home and charging priority scenarios show an evening peak demand. Charging priority scenario also shows a morning peak on weekdays, possibly due to workplace charging.

This paper presents on-going finite element modeling efforts of friction stir spot welding (FSSW) process using Abaqus/Explicit as a finite element solver. Three-dimensional coupled thermal-stress model was used to calculate thermo-mechanical response of FSSW process. Adaptive meshing and advection schemes, which makes it possible to maintain mesh quality under large deformations, is utilized to simulate the material flow and temperature distribution in FSSW process. The predicted overall deformation shape of the weld joint resembles that experimentally observed. Temperature and stress graphs in the radial direction as well as temperature-deformation distribution plots are presented.

Increases in efficiency may be possible by a new technique for non-thermal plasma aftertreatment of exhaust gases. The new technique involves very short risetimes (40ps) high frequency (5Ghz) high power bursts of low duty factor microwaves to generate a dielectric barrier discharge. The technique is illustrated in the simplified example of the dissociation of NO in N2. Electric field distributions and enhancing improvements are briefly described for a number of configurations. The technique is meant to be used in conjunction with material catalyst and can, for a class of catalysts, cause a significant reactivity on the catalyst surface.

Phosphorous in diesel exhaust is derived via engine oil consumption from the zinc dialkyldithiophosphate (ZDDP) oil additive used for engine wear control. Phosphorous present in the engine exhaust can react with an exhaust catalyst and cause loss of performance through masking or chemical reaction. The primary effect is loss of light-off or low temperature performance. Although the amount of ZDDP used in lube oil is being reduced, it appears that there may is a minimum level of ZDDP needed for engine durability. One of the ways of reducing the effects of the resulting phosphorous on catalysts might be to alter the chemical state of the phosphorous to a less damaging form or to develop catalysts which are more resistant to phosphorous poisoning. In this study, lube oil containing ZDDP was added at an accelerated rate through a variety of engine pathways to simulate various types of engine wear or oil disposal practices.

The most significant obstacle to the widespread use of carbon-fiber-based composites by the automotive industry is the high cost of carbon fibers in comparison to other potential structural materials. Carbon fibers are currently produced by thermal pyrolysis of a polyacrylonitrile (PAN) precursor to obtain the desired properties. The most significant cost factors in the process are the high cost of precursors and the high capital equipment and energy costs in conversion to carbon fiber. The Department of Energy is supporting developmental efforts to reduce costs in both precursor production and conversion areas. This paper describes developments in the conversion process. Because of the unsuccessful results of manufacturing carbon fibers through their direct heating with microwave radiation (variable frequency microwave [VFM] and single frequency microwave [SFM] energy), new avenues were explored for this processing.

The U.S. Government plays an important role in the Partnership for a New Generation of Vehicles' (PNGV) electrical and electronics technologies with a program consisting of high-risk research and development (R&D) projects. The Department of Energy (DOE) plays the largest role in supporting these technologies to specifically address automotive needs. DOE has three Automotive Integrated Power Module (AIPM) contractors and two Automotive Electric Motor Drive (AEMD) contractors working to become viable suppliers for PNGV. Materials development projects are working to improve materials and devices needed in automotive motors and drives, such as permanent magnets, capacitors, sensors, connectors, and thermal management materials. Advancements in inverters, controls, and motors and generators conducted at DOE's national laboratories are also presented.

The objective of the Heavy Vehicle Propulsion Materials Program is to develop the enabling materials technology for the clean, high-efficiency diesel truck engines of the future. The development of cleaner, higher-efficiency diesel engines imposes greater mechanical, thermal, and tribological demands on materials of construction. Often the enabling technology for a new engine component is the material from which the part can be made. The Heavy Vehicle Propulsion Materials Program is a partnership between the Department of Energy (DOE), and the diesel engine companies in the United States, materials suppliers, national laboratories, and universities. A comprehensive research and development program has been developed to meet the enabling materials requirements for the diesel engines of the future.

Driver is a key component in vehicle simulation. An ideal driver model simulates driving patterns a human driver may perform to negotiate road profiles. There are simulation packages having the capability to simulate driver behavior. However, it is rarely documented how they work with road profiles. This paper proposes a new truck driver model for vehicle simulation to imitate actual driving behavior in negotiating road grade and curvature. The proposed model is developed based upon Gipps' car-following model. Road grade and curvature were not considered in the original Gipps' model although it is based directly on driver behavior and expectancy for vehicles in a stream of traffic. New parameters are introduced to capture drivers' choice of desired speeds that they intend to use in order to negotiating road grade and curvature simultaneously. With the new parameters, the proposed model can emulate behaviors like uphill preparation for different truck drivers.

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.