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Shock waves have been recently observed in high-pressure diesel sprays. In this paper, three-dimensional numerical simulations of supersonic diesel spray injection have been performed to investigate the underlying dynamics of the induced shock waves and their interactions with the spray. A Volume-of-Fluid based method in the CFD software (CONVERGE) is used to model this multiphase phenomena. An adaptive Mesh Refinement (AMR) scheme is employed to capture the front of the spray and the shock waves with high fidelity. Simulation results are compared to the available experimental observations to validate the numerical procedure. Parametric studies with different injection and ambient conditions are conducted to examine the effect of these factors on the generation of shock waves and their dynamics.

Automated driving functionalities delivered through Advanced Driver Assistance System (ADAS) have been adopted more and more frequently in consumer vehicles. The development and implementation of such functionalities pose new challenges in safety and functional testing and the associated validations, due primarily to their high demands on facility and infrastructure. This paper presents a rather unique Vehicle-in-the-Loop (VIL) test setup and methodology compared those previously reported, by combining the advantages of the hardware-in-the-loop (HIL) and traditional chassis dynamometer test cell in place of on-road testing, with a multi-agent real-time simulator for the rest of test environment.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

Argonne National Laboratory (ANL), working with the Partnership for a New Generation of Vehicles (PNGV), maintains hybrid vehicle simulation software, the PNGV System Analysis Toolkit (PSAT). PSAT, originally proprietary, has been used by both DOE and the “Big Three” as a modeling tool. The number of PSAT users has increased recently because 15 universities participating in the 2001 FutureTruck competition were given the software for their use. PSAT allows companies to look at new types of vehicles (hybrids) and choose the best configuration according to customer expectations within a minimum of time. PSAT, a forward-looking model, allows the user to simulate a large number of different configurations (conventional, series, parallel, and power split). PSAT is well suited for development of control strategies; by using accurate dynamics component models as its code, PSAT can be implemented directly and tested at the bench scale or in a vehicle.

Today’s value proposition of plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV) remain expensive. While the cost of lithium batteries has significantly decreased over the past few years, more improvement is necessary for PHEV and BEV to penetrate the mass market. However, the technology and cost improvements of the primary components used in electrified vehicles such as batteries, electric machines and power electronics have far exceeded the improvements in the main components used in conventional vehicles and this trend is expected to continue for the foreseeable future. Today’s weight and cost structures of electrified vehicles differ substantially from that of conventional vehicles but that difference will shrink over time. This paper highlights how the weight and cost structures, both in absolute terms and in terms of split between glider and powertrain, converge over time.

Reductions in vehicle drive losses are as important to improving fuel economy as increases in powertrain efficiencies. In order to measure vehicle fuel economy, chassis dynamometer testing relies on accurate road load determinations. Road load is currently determined (with some exceptions) using established test track coastdown testing procedures. Because new vehicle technologies and usage cases challenge the accuracy and applicability of these procedures, on-road experiments were conducted using axle torque sensors to address the suitability of the test procedures in determining vehicle road loads in specific cases. Whereas coastdown testing can use vehicle deceleration to determine load, steady-state testing can offer advantages in validating road load coefficients for vehicles with no mechanical neutral gear (such as plug-in hybrid and electric vehicles).

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).

In an earlier paper, the authors described how Model-Based System Engineering could be utilized to provide a virtual Hardware-in-the-Loop simulation capability, which creates a framework for the development of virtual ECU software by providing a platform upon which embedded control algorithms may be developed, tested, updated, and validated. The development of virtual ECU software is increasingly valuable in automotive control system engineering because vehicle systems are becoming more complex and tightly integrated, which requires that interactions between subsystems be evaluated during the design process. Variational analysis and robustness studies are also important and become more difficult to perform with real hardware as system complexity increases. The methodology described in this paper permits algorithm development to be performed prior to the availability of vehicle and control system hardware by providing what is essentially a virtual integration vehicle.

Argonne National Laboratory (ANL) researchers have embarked on an ambitious program to quantitatively demonstrate the potential of hydrogen as a fuel for internal combustion engines (ICEs) in hybrid-electric vehicle applications. In this initiative, ANL researchers need to investigate different hybrid configurations, different levels of hybridization, and different control strategies to evaluate their impacts on the potential of hydrogen ICEs in a hybrid system. Because of limitations in the choice of motor and battery hardware, a common practice is to fix the size of the battery and motor, depending on the hybrid configuration (starter/alternator, mild hybrid, or full hybrid) and to tune the system control for the above-available electrical power/energy. ANL has developed a unique, flexible, Hardware-In-the-Loop (HIL) platform for advanced powertrain technology evaluation: The Mobile Advanced Technology Testbed (MATT).

Exhaust gas recirculation (EGR) is a commonly used technique for the reduction of Nitrogen oxide (NOx) emissions from internal combustion engines. However, it is generally known that the use of EGR will cause an increase in emissions of particulate matter (PM). The effects of EGR operating mode on particulate morphology were investigated for a 1.7-liter light-duty diesel engine. This engine was equipped with a turbocharged and inter-cooled air induction system, a common-rail direct fuel injection system, and an EGR system. A rapid prototyping electronic control system (RPECS) was developed to operate this engine at various EGR rates under different conditions (i.e. constant boost pressure, constant oxygen-to-fuel ratio (OFR)). A unique thermophoretic sampling system was employed to collect particulates directly from exhaust manifold after exhaust valves.

To restrain the phenomenal increase in oil consumption in China, the Chinese government called for measures to reduce oil consumption of the road transportation sector through adopting vehicle fuel consumption standards. This paper describes the development of China's first set of fuel consumption standards for light-duty passenger vehicles. The adopted standards cover M1 class vehicles, which, according to European definition (and adopted by China), include passenger cars, minivans, and sports utility vehicles (SUVs). In particular, we present the goal, technical background, structure, and values of the adopted standards. We also present their potential effect on oil use reduction. The standards are set in liters of fuel consumption per 100 km for individual vehicle weight categories. The standards are maximum fuel consumption values for given vehicle weight categories.

This paper introduces a new systematic workflow for the rapid evaluation of energy-efficient automated driving controls in real vehicles in controlled laboratory conditions. This vehicle-in-the-loop (VIL) workflow, largely standardized and automated, is reusable and customizable, saves time and minimizes costly dynamometer time. In the first case study run with the VIL workflow, an automated car driven by an energy-efficient driving control previously developed at Argonne used up to 22 % less energy than a conventional control. In a VIL experiment, the real vehicle, positioned on a chassis dynamometer, has a digital twin that drives in a virtual world that replicates real-life situations, such as approaching a traffic signal or following other vehicles.

Connectivity and automation provide the potential to use information about the environment and future driving to minimize energy consumption. Aerodynamic drag can also be reduced by close-gap platooning using information from vehicle-to-vehicle communications. In order to achieve these goals, the designers of control strategies need to simulate a wide range of driving situations in which vehicles interact with other vehicles and the infrastructure in a closed-loop fashion. RoadRunner is a new model-based system engineering platform based on Autonomie software, which can collectively provide the necessary tools to predict energy consumption for various driving decisions and scenarios such as car-following, free-flow, or eco-approach driving, and thereby can help in developing control algorithms.

A simulation approach is defined that integrates a military mission assessment tool (One Semi-Automated Forces) with a commercial automotive control/energy consumption development tool (Autonomie). The objective is to enable vehicle energy utilization and fuel consumption impact assessments relative to US Army mission effectiveness and commercial drive cycles. The approach to this integration will be described, along with its potential to meet its objectives.