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The Michelin Tweel tire structure has recently been developed as an innovative non-pneumatic tire which has potential for improved handling, grip, comfort, low energy loss when impacting obstacles and reduced rolling resistance when compared to a traditional pneumatic tire. One of the potential sources of vibration during rolling of a non-pneumatic tire is the buckling phenomenon and snapping back of the spokes in tension when they enter and exit the contact zone. Another source of noise was hypothesized due to a flower petal ring vibration effect due to discrete spoke interaction with the ring and contact with the ground during rolling as the spokes cycle between tension and compression. Transmission of vibration between the ground force, ring and spokes to the hub was also considered to be a significant contributor to vibration and noise characteristics of the Tweel.

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.

Exhaust emissions of seventeen 2,3,7,8-substituted chlorinated dibenzo-p-dioxin/furan (CDD/F) congeners, tetra-octa CDD/F homologues, twelve WHO 2005 chlorinated biphenyls (CB) congeners, mono-nona CB homologues, and nineteen polycyclic aromatic hydrocarbons (PAHs) from a model year 2008 Cummins ISB engine equipped with aftertreatment including a diesel oxidation catalyst (DOC) and wall flow copper or iron urea selective catalytic reduction filter (SCRF) were investigated. These systems differ from a traditional flow through urea selective catalytic reduction (SCR) catalyst because they place copper or iron catalyst sites in close proximity to filter-trapped particulate matter. These conditions could favor de novo synthesis of dioxins and furans. The results were compared to previously published results of modern diesel engines equipped with a DOC, catalyzed diesel particulate filter (CDPF) and flow through urea SCR catalyst.

Predicting fuel economy during early stages of concept development or feasibility study for a new type of powertrain configuration is an important key factor that might affect the powertrain configuration decision to meet CAFE standards. In this paper an efficient model has been built in order to evaluate the fuel economy for a new type of charge sustaining series hybrid vehicle that uses a Genset assembly (small 2 cylinders CNG fueled engine coupled with a generator). A first order mathematical model for a Li-Ion polymer battery is presented based on actual charging /discharging datasheet. Since the Genset performance data is not available, normalized engine variables method is used to create powertrain performance maps. An Equivalent Consumption Minimization Strategy (ECMS) has been implemented to determine how much power is supplied to the electric motor from the battery and the Genset.

A state of the art proprietary method for aluminum-to-aluminum joining in the automotive industry is Resistance Spot Welding. However, with spot welding (1) structural performance of the joint may be degraded through heat-affected zones created by the high temperature thermal joining process, (2) achieving the double-sided access necessary for the spot welding electrodes may limit design flexibility, and (3) variability with welds leads to production inconsistencies. Self-piercing rivets have been used before; however they require different rivet/die combinations depending on the material being joined, which adds to process complexity. In recent years the introductions of screw products that combine the technologies of friction drilling and thread forming have entered the market. These types of screw products do not have these access limitations as through-part connections are formed by one-sided access using a thermo-mechanical flow screwdriving process with minimal heat.

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).

This manuscript provides a review of different types and categorization of the chassis dynamometer systems. The review classifies the chassis dynamometers based on the configuration, type of rollers and the application type. Additionally the manuscript discusses several application examples of the chassis dynamometer including: performance and endurance mileage accumulation tests, fuel efficiency and exhaust emissions, noise, vibration and harshness testing (NVH). Different types of the vehicle attachment system in the dynamometer cell and its influences on the driving force characteristics and the vehicle acoustic signature is also discussed. The text also highlights the impact of the use of the chassis dynamometer as a development platform and its impact on the development process. Examples of using chassis dynamometer as a development platform using Vehicle Hardware In-the-Loop (VHiL) approach including drivability assessment and transmission calibrations are presented.

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.

Chassis dynamometer tests were conducted on three Class III on-highway motorcycles produced for the North American market and equipped with advanced emission control technologies in order to inform emissions inventories and compare the impacts of existing Tier 2 (E0) fuel with more market representative Tier 3 and LEV III certification fuels with 10% ethanol. For this study, the motorcycles were tested over the US Federal Test Procedure (FTP) and the World Motorcycle Test Cycle (WMTC) certification test cycles as well as a sample of real-world motorcycle driving informally referred to as the Real World Driving Cycle (RWDC). The primary interest was to understand the emissions changes of the selected motorcycles with the use of certification fuels containing 10% ethanol compared to 0% ethanol over the three test cycles.

Substantial fuel economy improvements for light-duty automotive engines demand novel combustion strategies. Low temperature combustion (LTC) demonstrates potential for significant fuel efficiency improvement; however, control complexity is an impediment for real-world transient operation. Spark-assisted compression ignition (SACI) is an LTC strategy that applies a deflagration flame to generate sufficient energy to trigger autoignition in the remaining charge. Operating a practical engine with SACI combustion is a key modeling and control challenge. Current models are not sufficient for control-oriented work such as calibration optimization, transient control strategy development, and real-time control. This work describes the process and results of developing a fast-running control-oriented model for the autoignition phase of SACI combustion. A data-driven model is selected, specifically artificial neural networks (ANNs).

In the U.S., the teenage driving population is at the highest risk of being involved in a crash. Teens often demonstrate poor vehicle control skills and poor ability to identify hazards, thus proper understanding of automotive indicators and warnings may be even more critical for this population. This research evaluates teen drivers’, between 15 to 17 years of age, understanding of symbols from vehicles featuring advanced driving assistant systems and multiple powertrain configurations. Teen drivers’ (N=72) understanding of automotive symbols was compared to three other groups with specialized driving experience and technical knowledge: automotive engineering graduate students (N=48), driver rehabilitation specialists (N=16), and performance driving instructors (N=15). Participants matched 42 symbols to their descriptions and then selected the five symbols they considered most important.

Driving inattention caused by drowsiness has been a significant reason for vehicle crash accidents, and there is a critical need to augment driving safety by monitoring driver drowsiness behaviors. For real-time drowsy driving awareness, we propose a vision-based driver drowsiness monitoring system (DDMS) for driver drowsiness behavior recognition and analysis. First, an infrared camera is deployed in-vehicle to capture the driver’s facial and head information in naturalistic driving scenarios, in which the driver may or may not wear glasses or sunglasses. Second, we propose and design a multi-modal features representation approach based on facial landmarks, and head pose which is retrieved in a convolutional neural network (CNN) regression model. Finally, an extreme learning machine (ELM) model is proposed to fuse the facial landmark, recognition model and pose orientation for drowsiness detection. The DDMS gives promptly warning to the driver once a drowsiness event is detected.

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.

With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

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.

The use of Low Pressure - Exhaust Gas Recirculation (EGR) is intended to allow displacement reduction in turbocharged gasoline engines and improve fuel economy. Low Pressure EGR designs have an advantage over High Pressure configurations since they interfere less with turbocharger efficiency and improve the uniformity of air-EGR mixing in the engine. In this research, Low Pressure (LP) cooled EGR is evaluated on a turbocharged direct injection gasoline engine with variable valve timing using both simulation and experimental results. First, a model-based calibration study is conducted using simulation tools to identify fuel efficiency gains of LP EGR over the base calibration. The main sources of the efficiency improvement are then quantified individually, focusing on part-load de-throttling of the engine, heat loss reduction, knock mitigation as well as decreased high-load fuel enrichment through exhaust temperature reduction.

The pursuit of greater fuel economy in internal combustion engines requires the optimization of all subsystems including thermal management. The reduction of cooling power required by the electromechanical coolant pump, radiator fan(s), and thermal valve demands real time control strategies. To maintain the engine temperature within prescribed limits for different operating conditions, the continual estimation of the heat removal needs and the synergistic operation of the cooling system components must be accomplished. The reductions in thermal management power consumption can be achieved by avoiding unnecessary overcooling efforts which are often accommodated by extreme thermostat valve positions. In this paper, an optimal nonlinear controller for a military M-ATV engine cooling system will be presented. The prescribed engine coolant temperature will be tracked while minimizing the pump, fan(s), and valve power usage.