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In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

A quasidimensional engine simulation which uses the concepts of fractal geometry to model the effects of turbulence on flame propagation in a homogeneous charge SI engine has been developed. Heat transfer and blowby/crevice flow submodels are included in this code and the submodels chosen are found to be reasonable. The model predictions of cylinder pressure histories are then compared with experimental data over a range of loads, equivalence ratios, and engine speeds. The model is not adjusted in any manner to yield better agreement with the data, other than by tuning the simple turbulence model used so as to yield agreement with data for the nonreacting flow. However, current information about the flame wrinkling scales in an engine is inadequate. Therefore, predictions are made for three different assumptions about the flame wrinkling scales which span the range of physically possible scales.

A quasi-dimensional model for a direct injection diesel engine was developed based on experiments at Sandia National Laboratory. The Sandia researchers obtained images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation. Dec [1] combined all of the available images to develop a conceptual diesel combustion model to describe diesel combustion from the start of injection up to the quasi-steady form of the jet. The end of injection behavior was left undescribed in this conceptual model because no clear image was available due to the chaotic behavior of diesel combustion. A conceptual end-of-injection diesel combustion behavior model was developed to capture diesel combustion throughout its life span. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations.

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.

We present a multidimensional numerical model that calculates turbulent premixed flame propagation, assuming the flames have fractal geometries. Two scaling transformations, previously developed for laminar flames, are used to incorporate the fractal burning model in KIVA-II1, a numerical hydrodynamics code for chemically reactive flows. In this work the model is implemented for propane/air mixtures. For applications to internal combustion engines, we have also developed a fractal model for early flame kernel growth. Our multidimensional model can be used in experimental comparisons to test postulated fractal parameters, and we begin this task by comparing calculated results with measurements of propane/air combustion in a spark ignition engine. Good agreement is obtained between computed and measured flame positions and pressures in all cases except a low engine speed case.

It is a very challenging problem to reliably ignite extremely lean mixtures, especially for the low speed, high load conditions of large-bore natural gas engines. If these engines are to be use for the distributed power generation market, it will require operation with higher boost pressures and even leaner mixtures. Both place greater demands on the ignition system. The railplug is a very promising ignition system for lean burn natural gas engines with its high-energy deposition and high velocity plasma arc. It requires care to properly design railplugs for this new application, however. For these engines, in-cylinder pressure and mixture temperature are very high at the time of ignition due to the high boost pressure. Hot spots may exist on the electrodes of the ignitor, causing pre-ignition problems. A heat transfer model is proposed in this paper to aid the railplug design. The electrode temperature was measured in an operating natural gas engine.

As connectivity and sensing technologies become more mature, automated vehicles can predict future driving situations and utilize this information to drive more energy-efficiently than human-driven vehicles. However, future information beyond the limited connectivity and sensing range is difficult to predict and utilize, limiting the energy-saving potential of energy-efficient driving. Thus, we combine a conventional speed optimization planner, developed in our previous work, and reinforcement learning to propose a real-time intelligent speed optimization planner for connected and automated vehicles. We briefly summarize the conventional speed optimization planner with limited information, based on closed-form energy-optimal solutions, and present its multiple parameters that determine reference speed trajectories.

As a result of increasingly stringent regulations and higher customer expectations, auto manufacturers have been considering numerous technology options to improve vehicle fuel economy. Transmissions have been shown to be one of the most cost-effective technologies for improving fuel economy. Over the past couple of years, transmissions have significantly evolved and impacted both performance and fuel efficiency. This study validates the shifting control of advanced automatic transmission technologies in vehicle systems by using Argonne National Laboratory's model-based vehicle simulation tool, Autonomie. Different midsize vehicles, including several with automatic transmission (6-speeds, 7-speeds, and 8-speeds), were tested at Argonne's Advanced Powertrain Research Facility (APRF). For the vehicles, a novel process was used to import test data.

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.

As natural gas engines are designed to operate leaner and with increased boost pressure, durability of the spark plugs becomes problematic. Among the various new ignition devices that have been considered to solve some of the problems facing spark plugs, railplugs appear to hold clear advantages in some areas. There are two types of railplugs: coaxial rail and parallel rail. This paper reports the results of an experimental study of various parameters that affect the performance of parallel railplugs. Their performance was quantified by the distance that the arc traveled along the rails from the initiation point. Travel along the rails is thought to be an important performance metric because rail-travel limits excessive local wear and produces a distributed ignition source which can potentially reduce mixture inhomogeneity induced ignition problems.

Building a vehicle model with sufficient accuracy for fuel economy analysis is a time-consuming process, even with the modern-day simulation tools. Obtaining the right kind of data for modeling a vehicle can itself be challenging, given that while OEMs advertise the power and torque capability of their engines, the efficiency data for the components or the control algorithms are not usually made available for independent verification. The U.S. Department of Energy (DOE) funds the testing of vehicles at Argonne National Laboratory, and the test data are publicly available. Argonne is also the premier DOE laboratory for the modeling and simulation of vehicles. By combining the resources and expertise with available data, a process has been created to automatically develop a model for any conventional vehicle that is tested at Argonne. This paper explains the process of analyzing the publicly available test data and computing the parameters of various components from the analysis.

The Prius - a power-split hybrid electric vehicle from Toyota - has become synonymous with the word “Hybrid.” As of October 2010, two million of these vehicles had been sold worldwide, including one million vehicles purchased in the United States. In 2004, the second generation of the vehicle, the Prius MY04, enhanced the performance of the components with advanced technologies, such as a new magnetic array in the rotors. However, the third generation of the vehicle, the Prius MY10, features a remarkable change of the configuration - an additional reduction gear has been added between the motor and the output of the transmission [1]. In addition, a change in the energy management strategy has been found by analyzing the results of a number of tests performed at Argonne National Laboratory's Advanced Powertrain Research Facility (ARRF).

Alternative electric motor geometry with potentially increased efficiency is being considered for hybrid electric vehicle applications. An axial flux motor with a dynamically adjustable air gap (i.e., mechanical field weakening) has been tested, analyzed, and modeled for use in a vehicle simulation tool at Argonne National Laboratory. The advantage of adjusting the flux is that the motor torque-speed characteristics can better match the vehicle load. The challenge in implementing an electric machine with these qualities is to develop a control strategy that takes advantage of the available efficiency improvements without using excessive energy to mechanically adjust the air gap and thus reduce the potential energy savings. Motor efficiency was mapped in terms of speed, torque, supply voltage, and rotor-to-stator air gap.

Two limited-production hybrid electric vehicles (HEVs) - a 1988 Japanese model Toyota Prius and a 2000 Honda Insight - were tested at Argonne National Laboratory to collect data from vehicle component and systems operation. The test data are used to analyze operation and efficiency and to help validate computer simulation models. Both HEVs have FTP fuel economy greater than 45 miles per gallon and also have attributes very similar to those of conventional gasoline vehicles, even though each HEV has a unique powertrain configuration and operation control strategy. The designs and characteristics of these vehicles are of interest because they represent production technology with all the compromises for production included. This paper will explore both designs, their control strategies, and under what conditions high fuel economy was achieved.

In premixed turbulent combustion models, two mechanisms have been used to explain the increase in the flame speed due to the turbulence. The newer explanation considers the full range of turbulence scales which wrinkle the flame front so as to increase the flame front area and, thus, the flame propagation speed. The fractal combustion model is an example of this concept. The older mechanism assumes that turbulence enables the penetration of unburned mixtures across the flame front via entrainment into the burned mixture zone. The entrainment combustion or eddy burning model is an example of this mechanism. The results of experimental studies of combustion regimes and the flame structures in SI engines has confirmed that most combustion takes place at the wrinkled flame front with additional combustion taking place in the form of flame fingers or peninsulas.

The energy density and power density comparison of conventional fuels and batteries is often mentioned as an advantage of conventional vehicles over electric vehicles. Such an analysis often shows that the batteries are at least an order of magnitude behind fuels like gasoline. However this incomplete analysis ignores the impact of powertrain efficiency and mass of the powertrain itself. When we compare the potential of battery electric vehicles (BEVs) as an alternative for conventional vehicles, it is important to include the energy in the fuel and their storage as well as the eventual conversion to mechanical energy. For instance, useful work expected out of a conventional vehicle as well as a BEV is the same (to drive 300 miles with a payload of about 300 lb). However, the test weight of a Conventional vehicle and BEV will differ on the basis of what is needed to convert their respective stored energy to mechanical energy.

With the success of hybrid electric vehicles (HEVs) and the still uncertain long-term solution for vehicle transportation, Plug-in Hybrid Electric Vehicles (PHEV) appear to be a viable short-term solution and are of increasing interest to car manufacturers. Like HEVs, PHEVs offer two power sources that are able to independently propel the vehicle. They also offer additional electrical energy onboard. In addition to choices about the size of components for PHEVs, choices about powertrain configuration must be made. In this paper, we consider three potential architectures for PHEVs for 10- and 40-mi All Electric Range (AER) and define the components and their respective sizes to meet the same set of performance requirements. The vehicle and component efficiencies in electric-only and charge-sustaining modes will be assessed.

EmiSense Technologies, LLC (www.emisense.com) is commercializing its electronic particulate matter (PM) sensor that is based on technology developed at the University of Texas at Austin (UT). To demonstrate the capability of this sensor for real-time PM measurements and on board diagnostics (OBD) for failure detection of diesel particle filters (DPF), independent measurements were performed to characterize the engine PM emissions and to compare with the PM sensor response. Computational fluid dynamics (CFD) modeling was performed to characterize the hydrodynamics of the sensor's housing and to develop an improved PM sensor housing with reproducible hydrodynamics and an internal baffle to minimize orientation effects. PM sensors with the improved housing were evaluated in the truck exhaust of a heavy duty (HD) diesel engine tested on-road and on a chassis dynamometer at the University of California, Riverside (UCR) using their Mobile Emissions Laboratory (MEL).

Many of today's advanced simulation tools are suitable for modeling specific systems, but they provide rather limited support for automated model building and management. The diverse tools available for modeling different components of a vehicle make it all the more challenging to comprehend their integration and interactions and analyze the complete system. In addition, the complexities and sizes of the models require a better use of computing resources, such as multicore or remote processing, to greatly reduce the simulation time. In this paper we describe how modern software techniques can support modeling and design activities, with the objective to create system models quickly by assembling them in a “plug-and-play” architecture. System models can be integrated, co-simulated, and reused regardless of the environment in which they are developed, and their simulation results can be consolidated for analysis into a single tool.

Condensation of fuel vapor on the cold surfaces within the combustion chamber is investigated as a possible mechanism for increased HC emissions from SI engines during cold start. A one-dimensional, transient, mass diffusion analysis is used to examine the condensation of single-species fuels on the surfaces of the combustion chamber as the pressure within the cylinder rises during compression and combustion, and re-vaporization during expansion, blowdown, and exhaust. The effects of wall temperature, fuel volatility, and engine load and speed on this mechanism are also discussed. This analysis shows that low-volatility fuel components can condense on the surfaces of the combustion chamber when the surface temperatures are sufficiently low. This condensed fuel may re-vaporize during the power and exhaust strokes, or it may remain in the combustion chamber until surface temperatures rise, perhaps tens of seconds later.