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The benchmarking study described in this paper uses data from chassis dynamometer testing to determine the efficiency and operation of vehicle driveline components. A robust test procedure was created that can be followed with no a priori knowledge of component performance, nor additional instrumentation installed in the vehicle. To develop the procedure, a 2013 Chevrolet Malibu was tested on a chassis dynamometer. Dynamometer data, emissions data, and data from the vehicle controller area network (CAN) bus were used to construct efficiency maps for the engine and transmission. These maps were compared to maps of the same components produced from standalone component benchmarking, resulting in a good match between results from in-vehicle and standalone testing. The benchmarking methodology was extended to a 2013 Mercedes E350 diesel vehicle. Dynamometer, emissions, and CAN data were used to construct efficiency maps and operation strategies for the engine and transmission.

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, the National Vehicle Fuels and Emissions Laboratory has benchmarked multiple transmissions to determine their efficiency during operation. The benchmarking included a modified “coastdown test,” which measures transmission output drag as a function of speed while in neutral. The transmission drag data can be represented as a second-order expression, like that used for vehicle coastdown test results, as F0 + F1V + F2V2, where V is the vehicle velocity. When represented in this fashion, the relationships among the three coefficients were found to be highly predictable. The magnitude of these coefficients can be quite large, and for some tested transmissions the deviation between the quadratic regression and the measured drag at individual velocities can be significant.

The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.

To make an HCCI engine as a useful commercial product, the engine has to be capable of performing quick transients in a large operating range, especially in vehicle applications. HCCI combustion is kinetically controlled and has to be operated properly between two limits: misfire and knock. To achieve the correct state, the right amount of fuel/air/EGR has to be inducted into the cylinder. The amounts and ratios of the three components are highly dependent on other variables as operating conditions change. It is unrealistic and unreliable to predict the right combination of these variables without principal component analysis. Thus, the optimal response control path has to be based on the quality of the previous combustion event as well as the direction and the rate of transition.

As lightweight materials and advanced combustion engines are being used in both conventional and electrified vehicles with diverse fuels, it is necessary to evaluate the individual and combined impact of these technologies to reduce energy and greenhouse gas (GHG) emissions. This work uses life cycle assessment (LCA) to evaluate the total energy and GHG emissions for baseline and lightweight internal combustion vehicles (ICVs), hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) when they are operated with baseline and advanced gasoline and ethanol engines. Lightweight vehicle models are evaluated with primary body-in-white (BIW) mass reductions using aluminum and advanced/high strength steel (A/HSS) and secondary mass reductions that include powertrain re-sizing. Advanced engine/fuel strategies are included in the vehicle models with fuel economy maps developed from single cylinder engine models.

The current Brazilian tax legislation promotes vehicles, powered by engines with up to 1.0l displacement. In order to offer the customer an engine with the maximum tax advantage, a supercharged derivative of the Ford 1.0l Zetec RoCam engine was developed. The market specific boundary conditions in South America require powertrains with immediate response especially at low engine speeds. This can be achieved by a supercharged engine concept. The paper discusses the required engine modifications for the supercharger application. The combustion system was changed to benefit from the higher volumetric efficiency, including the optimisation of the intake, exhaust and bypass control system. Extensive modifications of the base engine were required to adapt the engine to the higher thermal load and the specific boundary condition of a supercharger application.

Fourier Transform Infrared Spectroscopy (FT-IR) has been used to measure the exhaust emissions from vehicles during standard driving tests. Comparisons with conventional analyzers for modal tests have been made for the regulated species such as carbon monoxide (CO), nitrogen oxides (NOx) and total hydrocarbon (THC). The concentrations of methane, methanol and formaldehyde were also measured at one second time intervals during several driving tests. The average concentration values for these species were compared to the bag samples for several tests. Modal concentration curves were also calculated for MTBE, ETBE and several other species of interest. The results indicate FT-IR can be used for making modal measurements on the regulated species and non-regulated species in vehicle exhaust emissions. Several studies were performed to evaluate the long-term stability and sensitivity of FT-IR in actual test situations.

This paper discusses the effects of stroke-to-bore (S/B) ratio on HCCI combustion. KIVA-3V, coupled with a multi-zone detailed chemical kinetics solver, is used to quantify the effects of changes in S/B ratio to heat transfer, thermal stratification and HCCI combustion. Three S/B ratios (0 5, 1.1 and 1.5) are analyzed. The results indicate that a cylinder with smaller S/B has more heat losses and lower thermal efficiency compared with a cylinder with larger S/B ratio, because of larger area-to-volume ratio near TDC. Moreover, the lowest S/B ratio case has a narrower temperature distribution before the onset of combustion. This leads to shorter burn duration, higher heat release rate and, consequently, increased knocking tendency. The emission results also favor the higher S/B ratio, with S/B=0.5 having the highest CO and HC emissions for relatively early combustion phasing; however, this trend is reversed as combustion is retarded.

As part of its midterm evaluation of the 2022-2025 light-duty greenhouse gas (GHG) standards, the Environmental Protection Agency (EPA) has been acquiring fuel efficiency data from testing of recent engines and vehicles. The benchmarking data are used as inputs to EPA’s Advanced Light Duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model created to estimate GHG emissions from light-duty vehicles. For complete powertrain modeling, ALPHA needs both detailed engine fuel consumption maps and transmission efficiency maps. EPA’s National Vehicle and Fuels Emissions Laboratory has previously relied on contractors to provide full characterization of transmission efficiency maps. To add to its benchmarking resources, EPA developed a streamlined more cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to broadly characterize transmissions within ALPHA.

An advanced Variable Valve Actuation (VVA) system is optimized for response time in order to provide robust switching at high engine speeds. The VVA system considered is Cylinder Deactivation (CDA) for the purpose of improving fuel economy. Specifically, a Switching Roller Finger Follower (SRFF) on a Dual Overhead Camshaft (DOHC) engine is optimized for cylinder deactivation. The objective of this work is to (1) improve the latch response time when the system response is the slowest, and (2) balance the “ON” and “OFF” response time. A proper tradeoff was established to provide the minimum switching time such that deactivation and reactivation occurs seamlessly and in the right sequence. The response time optimization is accomplished while maintaining the existing packaging space of the overhead. A camshaft with a single lobe per SRFF device on a type II valvetrain was used as the baseline configuration for this study.

A supervisory controller strategy for a hybrid vehicle coordinates the operation of the two power sources onboard of a vehicle to maximize objectives like fuel economy. In the past, various control strategies have been developed using heuristics as well as optimal control theory. The Stochastic Dynamic Programming (SDP) has been previously applied to determine implementable optimal control policies for discrete time dynamic systems whose states evolve according to given transition probabilities. However, the approach is constrained by the curse of dimensionality, i.e. an exponential increase in computational effort with increase in system state space, faced by dynamic programming based algorithms. This paper proposes a novel approach capable of overcoming the curse of dimensionality and solving policy optimization for a system with very large design state space.

This study is the second in a series of three EPA studies to investigate the effect of fuel reformulations and modifications on exhaust emissions. Both the first and second study in this series of studies were used to support the development of EPA's complex model for the certification of reformulated gasolines. Phase I of the study tested eight fuels on forty vehicles. This study, termed Phase II, tested twelve fuels on a separate fleet of 39 light-duty vehicles. The Phase II fuel parameters studied included Reid Vapor Pressure (RVP), the 50% and 90% evaporated distillation temperatures (T50 and T90), sulfur content, aromatics content, olefin content, oxygenate type and oxygen content. Measured exhaust emissions included total hydrocarbons (THC), oxides of nitrogen (NOx), carbon monoxide (CO), carbon dioxide (CO2), benzene, 1,3-butadiene, acetaldehyde and formaldehyde.

This study was the first of three EPA studies to investigate the effect of gasoline fuel parameters on hydrocarbon, nonmethane hydrocarbon, nitrogen oxides, benzene, formaldehyde, and acetaldehyde exhaust emissions of 1990 model year or equivalent vehicles. The fuel parameters tested in this program were oxygen concentration, Reid Vapor Pressure (RVP), ninety percent evaporative distillation temperature (T90), and sulfur concentration. Sulfur concentration was found to have the greatest effect on hydrocarbon and nitrogen oxide emissions. Increasing oxygen concentration and RVP reduction was found to reduce hydrocarbon emission more for high-emitting than normal-emitting vehicles. Oxygenate concentration was found to have a significant effect on aldehyde emissions.

Portable Emission Measurement Systems (PEMS) are used by the U.S. Environmental Protection Agency (EPA) to measure gaseous and particulate mass emissions from vehicles in normal, in-use, on-the-road operation to support many of its programs, including assessing mobile source emissions compliance, emissions factor assessment for in-use fleet modeling, and collection of in-use vehicle operational data to support vehicle simulation modeling programs. This paper discusses EPA’s use of Global Positioning System (GPS) measured altitude data and electronically logged vehicle speed data to provide real-world road grade data for use as an input into the Gamma Technologies GT-DRIVE+ vehicle model. The GPS measured altitudes and the CAN vehicle speed data were filtered and smoothed to calculate the road grades by using open-source Python code and associated packages.

EPA has been benchmarking engines and transmissions to generate inputs for use in its technology assessments supporting the Midterm Evaluation of EPA’s 2017-2025 Light-Duty Vehicle greenhouse gas emissions assessments. As part of an Atkinson cycle engine technology assessment of applications in light-duty vehicles, cooled external exhaust gas recirculation (cEGR) and cylinder deactivation (CDA) were evaluated. The base engine was a production gasoline 2.0L four-cylinder engine with 75 degrees of intake cam phase authority and a 14:1 geometric compression ratio. An open ECU and cEGR hardware were installed on the engine so that the CO2 reduction effectiveness could be evaluated. Additionally, two cylinders were deactivated to determine what CO2 benefits could be achieved. Once a steady state calibration was complete, two-cycle (FTP and HwFET) CO2 reduction estimates were made using fuel weighted operating modes and a full vehicle model (ALPHA) cycle simulation.

Fuel economy of both highway and off-highway vehicles is a major driver for new technology development. One of the technologies to meet this driver is a digital valve based hydraulic system. Digital Hydraulics technology employs high speed on/off valves to achieve the same functionality with no throttling loss. Furthermore, by forming various architecture by using digital valves, it provides the system level capability and flexibility for energy saving and productivity improvement. There are many challenges in fully realizing the full efficiency benefits of the system in an actual application. These challenges include packaging, durability, a change in the operator's perception of the vehicle as well as hydraulic system performances during operation. One significant issue is the noise, vibration and harshness (NVH) of the system. Due to the nature of the digital valve operation, there are severe transient dynamics in the fluid system.

The demand for injection molded reinforced plastic products used in the automotive industry is growing due to the capability of the material for volume production, high strength to weight ratio, and its flexibility of geometry design. On the other hand, the application of fiber filled plastic composites has been challenging and subject of research during past decades due to the inability to accurately predict the mechanical strength and stiffness behavior owing to its anisotropic characteristics. This paper discusses a numerical simulation based technique using multiscale (2 scale Micro-Macro) modeling approach for short fiber reinforced plastic composites. Fiber orientation tensors and knit lines are predicted in microscale analysis using Autodesk Inc.’s Moldflow® software, and structural analysis is performed considering the homogenized structure in macroscale analysis using ANSYS® software tool.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of 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. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data. This paper presents an analysis of the effects of varying the absolute and relative gear ratios of a given transmission on carbon emissions and performance.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of 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. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data.

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a freely-distributed, MATLAB/Simulink-based desktop application. Version 1.0 of the ALPHA tool was applicable only to conventional, non-hybrid vehicles and was used to evaluate off-cycle technologies such as air-conditioning, electrical load reduction technology and road load reduction technologies for the 2017-2025 LD GHG rule. The next version of the ALPHA tool will extend its modeling capabilities to include power-split and P2 parallel hybrid electric vehicles and their battery pack energy storage systems. Future versions of ALPHA will incorporate plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) architectures.