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The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).

Today’s electric vehicle (EV) owners charge their vehicles mostly at home and seldom use public direct current fast charger (DCFCs), reducing the need for a large deployment of DCFCs for private EV owners. However, due to the emerging interest among transportation network companies to operate EVs in their fleet, there is great potential for DCFCs to be highly utilized and become economically feasible in the future. This paper describes a heuristic algorithm to emulate operation of EVs within a hypothetical transportation network company fleet using a large global positioning system data set from Columbus, Ohio. DCFC requirements supporting operation of EVs are estimated using the Electric Vehicle Infrastructure Projection tool. Operation and installation costs were estimated using real-world data to assess the economic feasibility of the recommended fast charging stations.

In order to ensure the safety of a structure, adequate strength for structural elements must be provided. Moreover, catastrophic deformations such as buckling must be prevented. Using the linear finite element method, deterministic buckling analysis is completed in two main steps. First, a static analysis is performed using an arbitrary ordinate applied loading pattern. Using the obtained element axial forces, the geometric stiffness of the structure is assembled. Second, an eigenvalue problem is performed between structure's elastic and geometric stiffness matrices, yielding the structure's critical buckling loads. However, these deterministic approaches do not consider uncertainty the structure's material and geometric properties. In this work, a new method for finite element based buckling analysis of a structure with uncertainty is developed. An imprecise probability formulation is used to quantify the uncertainty present in the mechanical characteristics of the structure.

A key strategy to improving the real-world fuel consumption and emissions of medium and heavy duty vehicles is the hybridization of these applications. Unlike the passenger vehicle market, medium and heavy duty applications are typically comprised of a range of components from a variety of manufacturers. The vocational market diversity and size places considerable demand on fuel efficiency and emission compliance. Medium and heavy duty applications have the ability to be successfully hybridized in ways that are not currently, or would not be practical within a passenger vehicle. This would also drive greater truck and bus vertical integration of the hybrid components. However, medium and heavy duty manufacturers have been prevented from certifying a full vehicle level platform due to the current engine only certification requirements.

A full understanding and characterization of the near-field of diesel sprays is daunting because the dense spray region inhibits most diagnostics. While x-ray diagnostics permit quantification of fuel mass along a line of sight, most laboratories necessarily use simple lighting to characterize the spray spreading angle, using it as an input for CFD modeling, for example. Questions arise as to what is meant by the “boundary” of the spray since liquid fuel concentration is not easily quantified in optical imaging. In this study we seek to establish a relationship between spray boundary obtained via optical diffused backlighting and the fuel concentration derived from tomographic reconstruction of x-ray radiography. Measurements are repeated in different facilities at the same specified operating conditions on the “Spray A” fuel injector of the Engine Combustion Network, which has a nozzle diameter of 90 μm.

While the use of injection strategies utilizing multiple injection events for each engine cycle has become common, there are relatively few studies of the spray structure of split injection events. Optical spray measurements are particularly difficult for split injection events with a short dwell time between injections, since droplets from the first injection will obscure the end of the first and the start of the second injection. The current study uses x-ray radiography to examine the near-nozzle spray structure of split injection events with a short dwell time between the injection events. In addition, x-ray phase-enhanced imaging is used to measure the injector needle lift vs. time for split injections with various dwell timings. Near the minimum dwell time needed to create two separate injection events, the spray behavior is quite sensitive to the dwell time.

This paper outlines the development and progress of implementing the SAE J2931, J2847/2 and J1772 communication standards to accomplish off-board DC charging. Communication between the off-board DC Electric Vehicle Supply Equipment (EVSE) and Plug-in Electric Vehicle (PEV) occurs on the pilot wire of the SAE J1772 connector via HomePlug Green PHY power line communication (PLC). An Electric Vehicle Communication Controller (EVCC) was developed to interface with the PEV's Battery Energy Control Module (BECM). A Supply Equipment Communication Controller (SECC) was also developed to interface with the DC EVSE's Power Control Module (PCM). Firmware was developed to implement the SAE J2931/1 communication stack, which is harmonized with the ISO/IEC DIS 15118-2 and DIN 70121 standards for DC charging communication.

To restrain the environmental and energy problems caused by oil consumption and improve fuel economy of heavy-duty commercial vehicles, China started developing relevant standards from 2008. This paper introduces the background and development of China's national standard “Fuel consumption test methods for heavy-duty commercial vehicles”, and mainly describes the test method schemes, driving cycle and weighting factors for calculating average fuel consumption of various vehicle categories. The standard applies to heavy-duty vehicles with the maximum design gross mass greater than 3500 kg, including semi-trailer tractors, common trucks, dump trucks, city buses and common buses. The standard adopts the C-WTVC driving cycle which is adjusted on the basis of the World Transient Vehicle Cycle[1, 2] and specifies weighting factors of urban, rural and motorway segments for different vehicle categories.

This paper implements a coupled approach to integrate the internal nozzle flow and the ensuing fuel spray using a Volume-of-Fluid (VOF) method in the CONVERGE CFD software. A VOF method was used to model the internal nozzle two-phase flow with a cavitation description closed by the homogeneous relaxation model of Bilicki and Kestin [1]. An Eulerian single velocity field approach by Vallet et al. [2] was implemented for near-nozzle spray modeling. This Eulerian approach considers the liquid and gas phases as a complex mixture with a highly variable density to describe near nozzle dense sprays. The mean density is obtained from the Favreaveraged liquid mass fraction. The liquid mass fraction is transported with a model for the turbulent liquid diffusion flux into the gas.

In order to improve understanding of the primary atomization process for diesel-like sprays, a collaborative experimental and computational study was focused on the near-nozzle spray structure for the Engine Combustion Network (ECN) Spray D single-hole injector. These results were presented at the 5th Workshop of the ECN in Detroit, Michigan. Application of x-ray diagnostics to the Spray D standard cold condition enabled quantification of distributions of mass, phase interfacial area, and droplet size in the near-nozzle region from 0.1 to 14 mm from the nozzle exit. Using these data, several modeling frameworks, from Lagrangian-Eulerian to Eulerian-Eulerian and from Reynolds-Averaged Navier-Stokes (RANS) to Direct Numerical Simulation (DNS), were assessed in their ability to capture and explain experimentally observed spray details. Due to its computational efficiency, the Lagrangian-Eulerian approach was able to provide spray predictions across a broad range of conditions.

Extreme Fast Charging (XFC) infrastructure is crucial for an increase in electric vehicle (EV) adoption. However, an unmanaged implementation may lead to negative grid impacts and huge power costs. This paper presents an optimal energy management strategy to utilize grid-connected Energy Storage Systems (ESS) integrated with XFC stations to mitigate these grid impacts and peak demand charges. To achieve this goal, an algorithm that controls the charge and discharge of ESS based on an optimal power threshold is developed. The optimal power threshold is determined to carry out maximum peak shaving for given battery size and SOC constraints.

In this paper the KH-RT and the CAB droplet breakup models are analyzed. The focus is on near nozzle spray simulation data that will be qualitatively compared with results obtained from x-ray experiments. Furthermore, the suitability of the x-ray method for spray studies is assessed and its importance for droplet breakup modeling is discussed. The simulations have been carried out with the Kiva3VRel2 CFD-code into which the KH-RT- and the CAB- droplet breakup models have been implemented. Since the x-ray method gives an integrated line-of-sight mass distribution of the spray, a suitable comparison of the experimental distributions and the simulated ones is made. Additionally, modeling aspects are discussed and the functioning of the models demonstrated by illustrating how the parcel Weber numbers and radii vary spatially. The transient nature of the phenomenon is highlighted and the influence of the breakup model parameters is discussed.

The objective of this study was to evaluate the fuel saving potential of various hybrid powertrain architectures for medium and heavy duty vehicles. The relative benefit of each powertrain was analyzed, and the observed fuel savings was explained in terms of operational efficiency gains, regenerative braking benefits from powertrain electrification and differences in vehicle curb weight. Vehicles designed for various purposes, namely urban delivery, utility, transit, refuse, drayage, regional and long haul were included in this work. Fuel consumption was measured in regulatory cycles and various real world representative cycles. A diesel-powered conventional powertrain variant was first developed for each case, based on vehicle technical specifications for each type of truck. Autonomie, a simulation tool developed by Argonne National Laboratory, was used for carrying out the vehicle modeling, sizing and fuel economy evaluation.

Recent advancements in x-ray radiography diagnostics for direct injection sprays at Argonne's Advanced Photon Source have allowed absorption measurements of individual spray events, in addition to ensemble-averaged measurements. These measurements offer insight into the shot-to-shot variation of these sprays in the near-nozzle, spray formation region. Three single hole diesel injectors are studied across various injection and ambient pressures, spanning 14 different conditions. We calculated two dimensional maps of the standard deviation in line of sight mass distribution between individual spray events. These illuminated the spatial and temporal extent of variability between spray events. Regions of large fluctuations were observed to move downstream during the initial spray period and reached a steady state location after this initial transient.

Cavitation plays an important role in fuel injection systems. It alters the nozzle's internal flow structure and discharge coefficient, and also contributes to injector wear. Quantitatively measuring and mapping the cavitation vapor distribution in a fuel injector is difficult, as cavitation occurs on very short time and length scales. Optical measurements of transparent model nozzles can indicate the morphology of large-scale cavitation, but are generally limited by the substantial amount of scattering that occurs between vapor and liquid phases. These limitations can be overcome with x-ray diagnostics, as x-rays refract, scatter and absorb much more weakly from phase interfaces. Here, we present an overview of some recent developments in quantitative x-ray diagnostics for cavitating flows. Measurements were conducted at the Advanced Photon Source at Argonne National Laboratory, using a submerged plastic test nozzle.

Current-production hybrid electric vehicles (HEVs) have shown a measurable improvement in fuel economy, in comparison with conventional vehicles, by using the internal combustion engine in a more efficient operating region, which therefore reduces petroleum consumption. These HEVs operate with a charge-sustaining control strategy. Plug-in HEVs (PHEVs) show the potential to further decrease petroleum consumption by operating in a charge-depletion control strategy, in which the energy stored in the battery pack in used during normal driving and recharged through stationary, off-board vehicle charging. This charge-depletion strategy uses more electrical energy to propel the vehicle, which displaces more petroleum. This paper discusses the testing and analysis of a Hymotion Prius PHEV, an Energy CS Prius PHEV, and a Renault Kangoo PHEV.

Most previous measurements of diesel sprays have yielded few details regarding the near-nozzle structure of the sprays. X-ray radiography measurements have provided quantitative, time-resolved measurements of spray behavior, but the radiography data are projections of the actual fuel distribution. In this study, diesel sprays from two axial, single-hole nozzles are measured using x-ray radiography from several viewing angles. A model-based reconstruction is used to determine the actual density distribution from the projected data. The spray from the hydroground nozzle is eccentric and relatively dense, while the spray from the non-hydroground nozzle is asymmetric and far less dense. Even several mm from the nozzles, the calculated density values are high enough to call into question the assumptions underlying many standard CFD spray models.

Using synchrotron x-radiography and mass deconvolution techniques, this work reveals strikingly interesting structural and dynamic characteristics of the direct injection (DI) gasoline hollow-cone sprays in the near-nozzle region. Employed to measure the sprays, x-radiography allows quantitative determination of the fuel distribution in this optically impenetrable region with a time resolution of better than 1 μs, revealing the most detailed near-nozzle mass distribution of a DI gasoline fuel spray ever detected. Based on the x-radiographs of the spray collected from four different perspectives, enhanced mathematical and numerical analyses were developed to deconvolute the mass density of the gasoline hollow-cone spray. This leads to efficient and accurate regression curve fitting of the measured experimental data to obtain essential parameters of the density distribution that are then used in reconstructing the cross-sectional density distribution at various times and locations.

Wireless Power Transfer (WPT) promises automated and highly efficient charging of electric and plug-in-hybrid vehicles. As commercial development proceeds forward, the technical challenges of efficiency, interoperability, interference and safety are a primary focus for this industry. The SAE Vehicle Wireless Power and Alignment Taskforce published the Recommended Practice J2954 to help harmonize the first phase of high-power WPT technology development. SAE J2954 uses a performance-based approach to standardizing WPT by specifying ground and vehicle assembly coils to be used in a test stand (per Z-class) to validate performance, interoperability and safety. The main goal of this SAE J2954 bench testing campaign was to prove interoperability between WPT systems utilizing different coil magnetic topologies. This type of testing had not been done before on such a scale with real automaker and supplier systems.