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This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

Because of U.S. EPA regulatory actions and the National Academies National Research Council suggestions for improvements in the U.S. EPA emissions inventory methods, the U.S. EPA' Office of Transportation and Air Quality (OTAQ) has made a concerted effort to develop instrumentation that can measure criteria pollutant emissions during the operation of on-road and off-road vehicles. These instruments are now being used in applications ranging from snowmobiles to on-road passenger cars to trans-Pacific container ships. For the betterment of emissions inventory estimation these on-vehicle instruments have recently been employed to measure time resolved (1 hz) in-use gaseous emissions (CO₂, CO, THC, NO ) and particulate matter mass (with teflon membrane filter) emissions from 29 non-road construction vehicles (model years ranging from 1993 to 2007) over a three year period in various counties in Iowa, Missouri, and Kansas.

This paper introduces a Hydraulic Linear Engine (HLE) concept and describes a model to simulate instantaneous engine behavior. The United States Environmental Protection Agency has developed an HLE prototype as an evolution of their previous six-cylinder, four-stroke, free-piston engine (FPE) hardware. The HLE design extracts work hydraulically, in a fashion identical to the initial FPE, and is intended for use in a series hydraulic hybrid vehicle. Unlike the FPE, however, the HLE utilizes a crank for improved timing control and increased robustness. Preliminary experimental results show significant speed fluctuations and cylinder imbalance that require careful controls design. This paper also introduces a model of the HLE that exhibits similar behavior, making it an indispensible tool for controls design. Further, the model's behavior is evaluated over a range of operating conditions currently unobtainable by the experimental setup.

In-use testing of diesel emission control technologies is an integral component of EPA's verification program. Device manufacturers are required to complete in-use testing once 500 units have been sold. Additionally, EPA conducts test programs on randomly selected retrofit devices from installations completed with grants by the National Clean Diesel Campaign. In this test program, EPA identified and recovered a variety of retrofit devices, including diesel particulate filters (DPFs) and diesel oxidation catalysts (DOCs), installed on heavy-duty diesel vehicles (on-highway and nonroad). All of the devices were tested at Southwest Research Institute in San Antonio, Texas. This study's goal was to evaluate the durability, defined here as emissions performance as a function of time, of retrofit technologies aged in real-world applications. A variety of operating and emissions criteria were measured to characterize the overall performance of the retrofit devices on an engine dynamometer.

Implementation of EPA's heavy-duty engine NOx standard of 0.20 g/bhp-hr has resulted in the introduction of a new generation of emission control systems for on-highway heavy-duty diesel engines. These new control systems are predominantly based around aftertreatment systems utilizing urea-based selective catalytic reduction (SCR) techniques, with only one manufacturer relying solely on in-cylinder NOx emission reduction techniques. As with any new technology, EPA is interested in evaluating whether these systems are delivering the expected emissions reductions under real-world conditions and where areas for improvement may lie. To accomplish these goals, an in-situ gaseous emissions measurement study was conducted using portable emissions measurement devices. The first stage of this study, and subject of this paper, focused on engines typically used in line-haul trucking applications (12-15L displacement).

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, a 2018 Toyota Camry front wheel drive eight-speed automatic transmission was benchmarked. The benchmarking data were used as inputs to EPA’s Advanced Light-duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model to estimate GHG emissions from light-duty vehicles. ALPHA requires both detailed engine fuel consumption maps and transmission torque loss maps. EPA’s National Vehicle and Fuels Emissions Laboratory has developed a streamlined, cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to characterize transmissions within ALPHA. This testing methodology targets the range of transmission operation observed during vehicle testing over EPA’s city and highway drive cycles.

The United States Environmental Protection Agency's (EPA) National Center for Advanced Technology (NCAT), located at its National Vehicle and Fuel Emissions Laboratory in Ann Arbor, Michigan, has been a global leader in development and demonstration of low-greenhouse gas emitting, highly fuel efficient series hydraulic hybrid drivetrain technologies. Advances in these exciting new technologies have stimulated industry to begin manufacturing hydraulic hybrids for both commercial truck and non-road equipment markets. Development activities are continuing for other markets, including light-duty vehicles. Given the commercial emergence of these low-greenhouse gas emitting series hydraulic hybrids, EPA has passed the leadership for further development to industry.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to estimate greenhouse gas (GHG) emissions from light-duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. In order to model the behavior of current and future vehicles, an algorithm was developed to dynamically generate transmission shift logic from a set of user-defined parameters, a cost function (e.g., engine fuel consumption) and vehicle performance during simulation. This paper presents ALPHA's shift logic algorithm and compares its predicted shift points to actual shift points from a mid-size light-duty vehicle and to the shift points predicted using a static table-based shift logic as calibrated to the same vehicle during benchmark testing.

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel.

The U.S. Environmental Protection Agency’s (EPA’s) Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all energy flows in the model. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule, ALPHA has been refined and revalidated using newly acquired data from model year 2013-2016 engines and vehicles. The robustness of EPA’s vehicle and engine testing for the MTE coupled with further validation of the ALPHA model has highlighted some areas where additional data can be used to add fidelity to the engine model within ALPHA.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

A GT-SUITE vehicle-aftertreatment model has been developed to examine the cold-start emissions reduction capabilities of a Vacuum Insulated Catalytic Converter (VICC). This converter features a thermal management system to maintain the catalyst monolith above its light-off temperature between trips so that most of a vehicle’s cold-start exhaust emissions are avoided. The VICC thermal management system uses vacuum insulation around the monoliths. To further boost its heat retention capacity, a metal phase-change material (PCM) is packaged between the monoliths and vacuum insulation. To prevent overheating of the converter during periods of long, heavy engine use, a few grams of metal hydride charged with hydrogen are attached to the hot side of the vacuum insulation. The GT-SUITE model successfully incorporated the transient heat transfer effects of the PCM using the effective heat capacity method.

Motor vehicle emission testing during on-road driving is important to assess a vehicle’s exhaust emission control design, its compliance with Federal regulations and its impact on air quality. The U.S. Environmental Protection Agency (EPA) has been developing new approaches to screen the characteristics of vehicle dynamic emission control behaviors (its operating signature) while driving both on-road and on-dynamometer. The so-called “signature device” used for this testing is equipped with an O2/NOx sensor, thermocouple and GPS to record dynamic exhaust NOx concentration, air fuel ratio-controlled tailpipe lambda (λ), tailpipe temperature and vehicle speed (acceleration). In the early EPA research, signature screening was used to characterize a vehicle’s PCM control behaviors (cause/effect bijectivity), which help distinguish operation in normal control state-space and abnormal state-space.

Reducing the weight of the M1A2 tank by lightweighting hull, suspension, and track results in 5.1%, 1.3%, and 0.6% tank mass reductions, respectively. The impact of retrofitting with lightweight components is evaluated through primary energy demand (PED), cost, and fuel consumption (FC). Life cycle stages included are preproduction (design, prototype, and testing), material production, part fabrication, and operation. Metrics for lightweight components are expressed as ratios comparing lightweighted and unmodified tanks. Army-defined drive cycles were employed and an FC vs. mass elasticity of 0.55 was used. Depending on the distance traveled, cost to retrofit and operate a tank with a lightweighted hull is 3.5 to 19 times the cost for just operating an unmodified tank over the same distance. PED values for the lightweight hull are 1.1 to 2 times the unmodified tank. Cost and PED ratios decrease with increasing distance.

Electrification and hybridization have great potential for improving fuel economy and reducing visual signature or soot emissions in military vehicles. Specific challenges related to military applications include severe duty cycles, large and uncertain energy flows through the system and high thermal loads. A novel supervisory control strategy is proposed to simultaneously mitigate severe engine transients and to reduce high electric current in the battery without oversizing the battery. The described objectives are accomplished by splitting the propulsion power demand through filtering in the frequency domain. The engine covers only low frequency power demand profile while the battery covers high frequency components. In the proposed strategy, the separation filter is systematically designed to identify different frequency components with the consideration of fuel consumption, aggressive engine transients, and battery electric loads.

The increasing numbers of hybrid electric and full electric vehicle models currently in the market or in the pipeline of automotive OEMs require creative testing mechanisms to drive down development costs and optimize the efficiency of these vehicles. In this paper, such a testing mechanism that has been successfully implemented at the US Environmental Protection Agency National Vehicle and Fuel Emissions Laboratory (EPA NVFEL) is described. In this testing scheme, the units-under-test consist of a battery pack and its associated battery management system (BMS). The remaining subsystems, components, and environment of the vehicle are virtual and modeled in high fidelity.

After initial trials on Homogeneous Charge Compression Ignition (HCCI) engine design and tests pursuing feedback control to avoid misfire and knocking over wide transient operation ranges, Engineers at the US Environmental Protection Agency's (EPA) National Vehicle Fuel and Emissions Laboratory identified the crucial engine state variable, MRPR (Maximum Rate of Pressure Rise) and successfully controlled a 1.9L HCCI engine in pure HCCI mode [1]. This engine was used to power a hybrid Ford F-150 truck which successfully ran FTP75 tests in 2004. In subsequent research, efforts have been focused on practical issues such as improving transient rate, system simplification for controllability and packaging, application of production grade in-cylinder pressure sensors, cold start, idling and calibration for ambient conditions as well as oxidation catalyst applications for better turbine efficiency and HC and CO emissions control.

As part of an ongoing assessment of the potential for reducing greenhouse gas (GHG) emissions of light-duty vehicles, the U.S. Environmental Protection Agency (EPA) has implemented an updated methodology for applying the results of full vehicle simulations to the range of vehicles across the entire fleet. The key elements of the updated methodology explored for this article, responsive to stakeholder input on the EPA’s fleet compliance modeling, include (1) greater transparency in the process used to determine technology effectiveness and (2) a more direct incorporation of full vehicle simulation results. This article begins with a summary of the methodology for representing existing technology implementations in the baseline fleet using EPA’s Advanced Light-duty Powertrain and Hybrid Analysis (ALPHA) full vehicle simulation. To characterize future technologies, a full factorial ALPHA simulation of every conventional technology combination to be considered was conducted.

During the 1980s, the U.S. Environmental Protection Agency (EPA) incorporated the R factor into fuel economy calculations in order to address concerns about the impacts of test fuel property variations on corporate average fuel economy (CAFE) compliance, which is determined using the Federal Test Procedure (FTP) and Highway Fuel Economy Test (HFET) cycles. The R factor is defined as the ratio of the percent change in fuel economy to the percent change in volumetric heating value for tests conducted using two differing fuels. At the time the R-factor was devised, tests using representative vehicles initially indicated that an appropriate value for the R factor was 0.6. Reassessing the R factor has recently come under renewed interest after EPA's March 2013 proposal to adjust the properties of certification gasoline to contain significant amounts of ethanol.