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Because niobium-clad 304L stainless steel sheets are considered for use as bipolar plates in polymer electrolyte membrane (PEM) fuel cells, their mechanical behavior and failure mechanism are important to be examined. As-rolled and annealed specimens were tested in tension, bending and flattening. The effects of annealing temperature and time on the mechanical behavior and failure mechanism were investigated. Micrographic analyses of bent and flattened specimens showed that the as-rolled specimens have limited ductility and that the annealed specimens can develop an intermetallic layer of thickness of a few microns. The annealed specimens failed due to the breakage of intermetallic layer causing localized necking and the subsequent failure of Nb layer. The springback angles of the as-rolled and annealed specimens were also obtained from guided-bend tests.

Automotive engines are regularly utilized in the material handling market where LPG is often the primary fuel used. When compared to gasoline, the use of gaseous fuels (LPG and CNG) as well as alcohol based fuels, often result in significant increases in valve seat insert (VSI) and valve face wear. This phenomenon is widely recognized and the engine manufacturer is tasked to identify and incorporate appropriate valvetrain material and design features that can meet the ever increasing life expectations of the end-user. Alternate materials are often developed based on laboratory testing – testing that may not represent real world usage. The ultimate goal of the product engineer is to utilize accelerated lab test procedures that can be correlated to field life and field failure mechanisms, and then select appropriate materials/design features that meet the targeted life requirements.

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.

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.

The purpose of this paper is to demonstrate the impact of low- floor bus seating configuration, passenger load factor (PLF) and passenger characteristics on individual boarding and disembarking (B-D) times -a key component of vehicle dwell time and overall transit system performance. A laboratory study was conducted using a static full-scale mock-up of a low-floor bus. Users of wheeled mobility devices (n=48) and walking aids (n=22), and visually impaired (n=17) and able-bodied (n=17) users evaluated three bus layout configurations at two PLF levels yielding information on B-D performance. Statistical regression models of B-D times helped quantify relative contributions of layout, PLF, and user characteristics viz., impairment type, power grip strength, and speed of ambulation or wheelchair propulsion. Wheeled mobility device users, and individuals with lower grip strength and slower speed were impacted greater by vehicle design resulting in increased dwell time.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Greenhouse gas (GHG) emission targets are becoming more stringent for both automakers and electricity generators. With the introduction of plug-in hybrid and electric vehicles, transportation and electricity generation sectors become connected. This provides an opportunity for both sectors to work together to achieve the cost efficient reduction of CO2 emission. In addition, the abundant natural gas (NG) in USA is drawing increased attention from both policy makers and various industries due to its low cost and low carbon content. NG has the potential to ease the pressure from CO2 emission constraints for both the light duty vehicle (LDV) and the electricity generation sectors while simultaneously reducing their fuel costs. To quantify the benefit of this collaboration, an analytical model is developed to evaluate the total societal cost and CO2 emission for both sectors.

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.

Exhaust Gas Recirculation (EGR) coolers are commonly used in on-road and off-road diesel engines to reduce the recirculated gas temperature in order to reduce NOx emissions. One of the common performance behaviors for EGR coolers in use on diesel engines is a reduction of the heat exchanger effectiveness, mainly due to particulate matter (PM) deposition and condensation of hydrocarbons (HC) from the diesel exhaust on the inside walls of the EGR cooler. According to previous studies, typically, the effectiveness decreases rapidly initially, then asymptotically stabilizes over time. Prior work has postulated a deposit removal mechanism to explain this stabilization phenomenon. In the present study, five field aged EGR cooler samples that were used on construction machines for over 10,000 hours were analyzed in order to understand the deposit structure as well as the deposit composition after long duration use.

This study experimentally investigates the impact of Miller cycle strategies on the combustion process, emissions, and thermal efficiency in heavy-duty diesel engines. The experiments were conducted at constant engine speed, load, and engine-out NOx (1160 rev/min, 1.76 MPa net IMEP, 4.5 g/kWh) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Early Intake Valve Closing (EIVC) and Late Intake Valve Closing (LIVC) timing strategies were compared to a conventional intake valve profile. While the decrease in effective compression ratio associated with the use of Miller valve profiles was symmetric around bottom dead center, the decrease in volumetric efficiency (VE) was not. EIVC profiles were more effective at reducing VE than LIVC profiles. Despite this difference, EIVC and LIVC profiles with comparable VE decrease resulted in similar changes in combustion and emissions characteristics.

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 Chevrolet Volt is an electric vehicle with extended-range that is capable of operation on battery power alone, and on engine power after depletion of the battery charge. First generation Chevrolet Volts were driven over half a billion miles in North America from October 2013 through September 2014, 74% of which were all-electric [1, 12]. For 2016, GM has developed the second-generation of the Volt vehicle and “Voltec” propulsion system. By significantly re-engineering the traction power inverter module (TPIM) for the second-generation Chevrolet Volt extended-range electric vehicle (EREV), we were able to meet all performance targets while maintaining extremely high reliability and environmental robustness. The power switch was re-designed to achieve efficiency targets and meet thermal challenges. A novel cooling approach enables high power density while maintaining a very high overall conversion efficiency.

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.

Design of military vehicle needs to meet often conflicting requirements such as high mobility, excellent fuel efficiency and survivability, with acceptable cost. In order to reduce the development cost, time and associated risk, as many of the design questions as possible need to be addressed with advanced simulation tools. This paper describes a methodology to design a fuel efficient powerpack unit for a series hybrid electric military vehicle, with emphasis on the e-machine design. The proposed methodology builds on previously published Finite element based analysis to capture basic design features of the generator with three variables, and couples it with a model reduction technique to rapidly re-design the generator with desired fidelity. The generator is mated to an off the shelf engine to form a powerpack, which is subsequently evaluated over a representative military drive cycles.

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.