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The Battery Performance and Cost Model (BatPaC), developed by Argonne National Laboratory, is a versatile tool designed for lithium-ion battery (LIB) pack engineering. It accommodates user-defined specifications, generating detailed bill-of-materials calculations and insights into cell dimensions and pack characteristics. Pre-loaded with default data sets, BatPaC aids in estimating production costs for battery packs produced at scale (5 to 50 GWh annually). Acknowledging inherent uncertainties in parameters, the tool remains accessible and valuable for designers and engineers. BatPaC plays a crucial role in National Highway Transportation Traffic Safety Administration (NHTSA) regulatory assessments, providing estimated battery pack manufacturing costs and weight metrics for electric vehicles. Integrated with Argonne's Autonomie simulations, BatPaC streamlines large-scale processes, replacing traditional models with lookup tables.

With the increasing demand for Battery Electric Vehicles (BEVs) capable of extended mileage, optimizing their efficiency has become paramount for manufacturers. However, the challenge lies in balancing the need for climate control within the cabin and precise thermal regulation of the battery, which can significantly reduce a vehicle's driving range, often leading to energy consumption exceeding 50% under severe weather conditions. To address these critical concerns, this study embarks on a comprehensive exploration of the impact of weather conditions on energy consumption and range for the 2019 Nissan Leaf Plus. The primary objective of this research is to enhance the understanding of thermal management for BEVs by introducing a sophisticated thermal management system model, along with detailed thermal models for both the battery and the cabin.

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.

Considerable effort is currently being focused on emerging vehicle automation technologies. Engineers are making great strides in improving safety and reliability, but they are also exploring how these new technologies can enhance energy efficiency. This study focuses on the changes in aerodynamic drag associated with coordinated driving scenarios, also known as “platooning.” To draw sound conclusions in simulation or experimental studies where vehicle speed and gaps are controlled and coordinated, it is necessary to have a robust quantitative understanding of the road load changes associated with each vehicle in the platoon. Many variables affect the drag of each vehicle, such as each gap length, vehicle type/size, vehicle order and number of vehicles in the platoon. The effect is generally understood, but there are limited supporting data in the literature from actual test vehicles driving in formation.

Improvements in vehicle technology impact the purchase price of a vehicle and its operating cost. In this study, the monetary benefit of a technology improvement includes the potential reduction in vehicle price from using cheaper or smaller components, as well as the discounted value of the fuel cost savings. As technology progresses over time, the value and benefit of improving technology varies as well. In this study, the value of improving a few selected technologies (battery energy density, electric drive efficiency, tire rolling resistance, aerodynamics, light weighting) is studied and the value of the associated cost saving is quantified. The change in saving as a function of time, powertrain selection and vehicle type is also quantified. For example, a 10% reduction in aerodynamic losses is worth $24,222 today but only $8,810 in 2030 in an electric long haul truck. The decrease in value is primarily due to expected battery cost reduction over time.

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.

Gasoline compression ignition (GCI) has been shown to offer benefits in the NOx-soot tradeoff over conventional diesel combustion while still achieving high fuel efficiency. However, due to gasoline’s low reactivity, it is challenging for GCI to attain robust ignition and stable combustion under cold operating conditions. Building on previous work to evaluate glow plug-assisted GCI combustion at cold idle, this work evaluates the use of a spark plug to assist combustion. The closed-cycle 3-D CFD model was validated against GCI test results at a compression ratio of 17.3 during extended cold idle operation under laboratory-controlled conditions. A market representative, ethanol-free, gasoline (RON92, E0) was used in both the experiment and the numerical analysis. Spark-assisted simulations were performed by incorporating an ignition model with the spark energy required for stable combustion at cold start.

Connected and automated technologies poised to change the way vehicles operate are starting to enter the mainstream market. Methods to accurately evaluate these technologies, in particular for their impact on safety and energy, are complex due to the influence of static and environmental factors, such as road environment and traffic scenarios. Therefore, it is important to develop modeling and testing frameworks that can support the development of complex vehicle functionalities in a realistic environment. Microscopic traffic simulations have been increasingly used to assess the performance of connected and automated vehicle technologies in traffic networks. In this paper, we propose and apply an evaluation method based on a combination of microscopic traffic simulation (AIMSUN) and a chassis dynamometer-based vehicle-in-the-loop environment, developed at Argonne National Laboratory.

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.

Multi-mode combustion strategies may provide a promising pathway to improve thermal efficiency in light-duty spark ignition (SI) engines by enabling switchable combustion modes, wherein an engine may operate under advanced compression ignition (ACI) at low load and spark-assisted ignition at high load. The extension from the SI mode to the ACI mode requires accurate control of intake charge conditions, e.g., pressure, temperature and equivalence ratio, in order to achieve stable combustion phasing and rapid mode-switches. This study presents results from computational fluid dynamics (CFD) analysis to gain insights into mixture charge formation and combustion dynamics pertaining to auto-ignition processes. The computational study begins with a discussion of thermal wall boundary condition that significantly impacts the combustion phasing.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

Additive manufacturing was used to fabricate a head for an automotive-scale single-cylinder engine operating on natural gas. The head was consisted of a bimetallic composition of stainless steel and bronze. The engine performance using the bimetallic head was compared against the stock cast iron head. The heads were tested at two speeds (1200 and 1800 rpm), two brake mean effective pressures (6 and 10 bar), and two equivalence ratios (0.7 and 1.0). The bimetallic head showed good durability over the test and produced equivalent efficiencies, exhaust temperatures, and heat rejection to the coolant to the stock head. Higher combustion temperatures and advanced combustion phasing resulted from use with the bimetallic head. The implication is that with optimization of the valve timing, an efficiency benefit may be realized with the bimetallic head.

Reduced-order models typically assume that the flow through the injector orifice is quasi-steady. The current study investigates to what extent this assumption is true and what factors may induce large-scale variations. Experimental data were collected from a single-hole metal injector with a smoothly converging hole and from a transparent facsimile. Gas, likely indicating cavitation, was observed in the nozzles. Surface roughness was a potential cause for the cavitation. Computations were employed using two engineering-level Computational Fluid Dynamics (CFD) codes that considered the possibility of cavitation. Neither computational model included these small surface features, and so did not predict internal cavitation. At steady state, it was found that initial conditions were of little consequence, even if they included bubbles within the sac. They however did modify the initial rate of injection by a few microseconds.

The Society of Automotive Engineers Fatigue Design & Evaluation Committee [SAE FD&E] is actively working on a total life project for weldments, in which the welding residual stress is a key contributor to an accurate assessment of fatigue life. Physics-based welding process simulation and various types of residual stress measurements were pursued to provide a representation of the residual stress field at the failure location in the fatigue samples. A well-controlled and documented robotic welding process was used for all sample fabrications to provide accurate inputs for the welding simulations. One destructive (contour method) residual stress measurement and several non-destructive residual stress measurements-surface X-ray diffraction (XRD), energy dispersive X-ray diffraction (EDXRD), and neutron diffraction (ND)-were performed on the same or similarly welded samples.

The Toyota Prius Prime is a new generation of Toyota Prius plug-in hybrid electric vehicle, the electric drive range of which is 25 miles. This version is improved from the previous version by the addition of a one-way clutch between the engine and the planetary gear-set, which enables the generator to add electric propulsive force. The vehicle was analyzed, developed and validated based on test data from Argonne National Laboratory’s Advanced Powertrain Research Facility, where chassis dynamometer set temperature can be controlled in a thermal chamber. First, we analyzed and developed components such as engine, battery, motors, wheels and chassis, including thermal aspects based on test data. By developing models considering thermal aspects, it is possible to simulate the vehicle driving not only in normal temperatures but also in hot, cold, or warmed-up conditions.

Diesel-fueled, heavy-duty engines are critical to global economies, but unfortunately they are currently coupled to the rising price and challenging emissions of Diesel fuel. Public awareness and increasingly stringent emissions standards have made Diesel OEMs consider possible alternatives to Diesel, including electrification, fuel cells, and spark ignition. While these technologies will likely find success in certain market segments, there are still many applications that will continue to require the performance and liquid-fueled simplicity of Diesel-style engines. Three-way catalysis represents a possible low-cost and highly-effective pathway to reducing Diesel emissions, but that aftertreatment system has typically been incompatible with Diesel operation due to the prohibitively high levels of soot formation at the required stoichiometric fuel-air ratios. This paper explores a possible method of integrating three-way catalysis with Diesel-style engine operation.

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.

The CFR engine is the widely accepted platform to test standard Research Octane Number (RON) and Motored Octane Number (MON) for determining anti-knock characteristics of motor fuels. With increasing interest in engine downsizing, up-torquing, and alternative fuels for modern spark ignition (SI) engines, there is a need to better understand the conditions that fuels are subjected to in the CFR engine during octane rating. To take into account fuel properties, such as fuel heat of vaporization, laminar flame speed and auto-ignition chemistry; and understand their impacts on combustion knock, it is essential to estimate accurate cylinder conditions. In this study, the CFR F1/F2 engine was modeled using GT-Power with the Three Pressure Analysis (TPA) and the model was validated for different fuels and engine conditions.

Validation of a vehicle simulation model of the Chevrolet Volt 2016 was conducted. The Chevrolet Volt 2016 is equipped with the new “Voltec” extended-range propulsion system introduced into the market in 2016. The second generation Volt powertrain system operates in five modes, including two electric vehicle modes and three extended-range modes. Model development and validation were conducted using the test data performed on the chassis dynamometer set in a thermal chamber of Argonne National Laboratory’s Advanced Powertrain Research Facility. First, the components of the vehicle, such as the engine, motor, battery, wheels, and chassis, were modeled, including thermal aspects based on the test data. For example, engine efficiency changes dependent on the coolant temperature, or chassis heating or air-conditioning operations according to the ambient and cabin temperature, were applied.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.