A successful piston design requires eliminate the following failure modes: structure failure, skirt scuffing and piston unusual noise. It also needs to deliver least friction to improve engine fuel economy and performance. Traditional approach of using hardware tests to validate piston design is technically difficult, costly and time consuming. This paper presents an up-front CAE tool and an analytical process that can systematically address these issues in a timely and cost-effectively way. This paper first describes this newly developed CAE process, the 3D virtual modeling and simulation tools used in Ford Motor Company, as well as the piston design factors and boundary conditions. Furthermore, following the definition of the piston design assessment criteria, several piston design studies and applications are discussed, which were used to eliminate skirt scuffing, reduce piston structure dynamic stresses, minimize skirt friction and piston slapping noise.
This paper examines the issues concerning particulate matter (PM) emissions measurement at the 3 mg/mi level proposed as the future LEV III standard. These issues are general in nature, but are exacerbated at the low levels contemplated for upcoming emissions standards. They are discussed in the context of gasoline direct injection (GDI) engines, where they can have an important impact on the continued development of this technology for improved fuel economy. GDI particulate emissions, just as engine-out diesel PM, contain a high fraction of soot. But the total PM mass is significantly lower than from diesel engines, and there can be significant variations in emissions rate and apparent PM composition between cold-start and running emissions. PM emissions levels depend on sampling method and location. As a result, there can be substantial differences in PM sampled and diluted directly at the exhaust pipe, as opposed to measurements from a dilution tunnel.
Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Increasing computer models are developed to simulate vehicle crashworthiness, dynamic, and fuel efficiency. Before applying these models for product development, model validation needs to be conducted to assess the validity of the models. However, one of the key difficulties for model validation of dynamic systems is that most of the responses are functional responses, such as time history curves. This calls for the development of an objective metric which can evaluate the differences of both the time history and the key features, such as phase shift, magnitude, and slope between test and CAE curves. One of the promising metrics is Error Assessment of Response Time Histories (EARTH), which was recently developed. Three independent error measures that associated with physically meaningful characteristics (phase, magnitude, and slope) were proposed.
An oil-lubricated wet clutch has a direct impact on the drivability and fuel economy of a vehicle equipped with an automatic transmission system. However, a reliable analysis of clutch behavior still remains a challenge. The purpose of this study is to advance the state-of the-art in CFD methodology for modeling transient clutch behavior. First, a new iterative scheme is developed, in combination with commercial CFD software, which is capable of simulating the squeeze film process in a wet clutch. The numerical results are then validated using analytical solutions of the Reynolds equation for simplified clutch geometry and various boundary conditions. It is found that the choice of boundary conditions has a strong influence on squeeze film simulation. The iterative scheme is further validated by comparison to clutch engagement experiments.
A hybrid electric vehicle (HEV) system model, which directly simulates vehicle drive cycles with interactions among driver, environment, vehicle hardware and vehicle controls, is a critical CAE tool used through out the product development process to project HEV fuel economy (FE) capabilities. The accuracy of the model is essential and directly influences the HEV hardware designs and technology decisions. This ultimately impacts HEV product content and cost. Therefore, improving HEV system model accuracy and establishing high-level model-test correlation are imperative. This paper presents a Parameter Diagram (P-Diagram) based model-test correlation framework which covers all areas contributing to potential model simulation vs. vehicle test differences. The paper describes each area in detail and the methods of characterizing the influences as well as the correlation metrics.
Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.
Ford Motor Company has investigated a series hybrid electric vehicle (SHEV) configuration to move further toward powertrain electrification. This paper first provides a brief overview of the Vehicle System Controls (VSC) architecture and its development process. The paper then presents the energy management strategies that select operating modes and desired powertrain operating points to improve fuel efficiency. The focus will be on the controls design and optimization in a Model-in-the-Loop environment and in the vehicle. Various methods to improve powertrain operation efficiency will also be presented, followed by simulation results and vehicle test data. Finally, opportunities for further improvements are summarized.
The differences in hydrocarbons (HCs) emitted by gasoline (E0) and ethanol (EtOH) blend fuels from flex-fuel capable engines can lead to differences in the performance of aftertreatment devices. Vehicle emission results have shown either better performance on E0 compared to E85 or vice versa, dependent on the vehicle calibration. In order to separate the impact of the vehicle and the catalyst, a laboratory study was conducted to evaluate performance on a pulse-flame (pulsator) reactor and compare reactivity towards E0 and E85 (85% EtOH-15% E0) exhaust. The catalysts evaluated were substrate-only, washcoat-only and fully formulated catalysts that had been aged either on a pulsator reactor or dynamometer engine. Catalyst performance was evaluated with light-off tests utilizing both slow and fast temperature ramp rates.
Reliability-based design optimization (RBDO) has been widely used to obtain a reliable design via an existing CAE model considering the variations of input variables. However, most RBDO approaches do not consider the CAE model bias and uncertainty, which may largely affect the reliability assessment of the final design and result in risky design decisions. In this paper, the Gaussian Process Modeling (GPM) approach is applied to statistically correct the model discrepancy which is represented as a bias function, and to quantify model uncertainty based on collected data from either real tests or high-fidelity CAE simulations. After the corrected model is validated by extra sets of test data, it is integrated into the RBDO formulation to obtain a reliable solution that meets the overall reliability targets while considering both model and parameter uncertainties.
In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.
High concentrations of diesel fuel can accumulate in the engine oil, especially in vehicles equipped with diesel particle filters. Fuel dilution can decrease the viscosity of engine oil, reducing its film thickness. Higher concentrations of fuel are believed to accumulate in oil with biodiesel than with diesel fuel because biodiesel has a higher boiling temperature range, allowing it to persist in the sump. Numerous countries are taking actions to promote the use of biodiesel. The growing interest for biodiesel has been driven by a desire for energy independence (domestically produced), the increasing cost of petroleum-derived fuels, and an interest in reducing greenhouse gas emissions. Biodiesel can affect engine lubrication (through fuel dilution), as its physical and chemical properties are significantly different from those of petrodiesel. Many risks associated with excessive biodiesel dilution have been identified, yet its actual impact has not been well quantified.
Under the current emissions legislation, most of the diesel-powered vehicles have to use Diesel Particulate Filters (DPF) to remove soot particles from the exhaust gas and the accumulated soot particles have to be removed in regular intervals. To initialize the exhaust gas temperature for soot regeneration, diesel fuel is either injected into the combustion chamber in late engine cycle (e.g. post injection) or vaporized and then discharged into the exhaust gas via a dosing device (e.g. fuel vaporizer). Both approaches though require the exothermic catalyst to convert the fuel into thermal energy. For practical reasons, this paper is concentrated on describing how CFD could be used to model the fuel distribution in an aftertreatment system equipped with fuel vaporizer and the exothermic reactions in the catalysts.
Ethanol has a high octane rating and can be added to gasoline to produce high octane fuel blends. Understanding the octane increase with ethanol blending is of great fundamental and practical importance. Potential issues with fuel flow rate and fuel vaporization have led to questions of the accuracy of octane measurements for ethanol-gasoline blends with moderate to high ethanol content (e.g., E20-E85) using the Cooperative Fuel Research (CFR™) engine. The nonlinearity of octane ratings with volumetric ethanol content makes it difficult to assess the accuracy of such measurements. In the present study, Research Octane Number (RON) and Motor Octane Number (MON) were measured for a matrix of ethanol-gasoline blends spanning a wide range of ethanol content (E0, E10, E20, E30, E50, E75) in a set of gasoline blendstocks spanning a range of RON values (82, 88, 92, and 95). Octane ratings for neat ethanol, denatured ethanol, and hydrous ethanol were also measured.
One of the most critical elements in engineering a hydrogen fuel cell vehicle is the design of the on-board hydrogen storage system. Because the current compressed-gas hydrogen storage technology has several key challenges, including cost, volume and capacity, materials-based storage technologies are being evaluated as an alternative approach. These materials-based hydrogen storage technologies include metal hydrides, chemical hydrides, and adsorbent materials, all of which have drawbacks of their own. To optimize the engineering of storage systems based on these materials, it is critical to understand the impacts these systems will have on the overall vehicle system performance and what trade-offs between the hydrogen storage systems and the vehicle systems might exist that allow these alternative storage approaches to be viable.
Two oxygenated fuels were evaluated on a single-cylinder diesel engine and compared to three hydrocarbon diesel fuels. The oxygenated fuels included canola biodiesel (canola methyl esters, CME) and CME blended with dibutyl succinate (DBS), both of which are or have the potential to be bio-derived. DBS was added to improve the cold flow properties, but also reduced the cetane number and net heating value of the resulting blend. A 60-40 blend of the two (60% vol CME and 40% vol DBS) provided desirable cold flow benefits while staying above the U.S. minimum cetane number requirement. Contrary to prior vehicle test results and numerous literature reports, single-cylinder engine testing of both CME and the 60-40 blend showed no statistically discernable change in NOx emissions relative to diesel fuel, but only when constant intake oxygen was maintained.
Successful demonstrations of fully autonomous vehicle operation in controlled situations are leading to increased research investment and activity. This has already resulted in significant advancements in the underlying technologies necessary to make it a practical reality someday. Not only are these idealized events sparking imaginations with the potential benefits for safety, convenience, fuel economy and emissions, they also embolden some to make somewhat surprising and sometimes astonishing projections for their appearance on public roads in the near future. Are we now ready for a giant leap forward to the self-driving car with all its complexity and inter-dependencies? Humans will need to grow with and adapt to the technological advancements of the machine and we'll deeply challenge our social and political paradigms before we're done. Even if we as engineers are ready, is the driving public ready?
A laboratory study was performed to assess the potential capability of TWC+LNT/SCR systems to satisfy the Tier 2, Bin 2 emission standards for lean-burn gasoline applications. It was assumed that the exhaust system would need a close-coupled (CC) TWC, an underbody (U/B) TWC, and a third U/B LNT/SCR converter to satisfy the emission standards on the FTP and US06 tests while allowing lean operation for improved fuel economy during select driving conditions. Target levels for HC, CO, and NOx during lean/rich cycling were established. Sizing studies were performed to determine the minimum LNT/SCR volume needed to satisfy the NOx target. The ability of the TWC to oxidize the HC during rich operation through steam reforming was crucial for satisfying the HC target.
This paper presents a study performed in 10 vehicles available in Brazilian market where the drivability with ethanol and gasoline, also referred as gasohol were compared. The motivation for this work came from the constant competition of the automotive industry, where engineers are searching for ways to improve the quality of the products aiming the “best in class” drivability with the best cost efficiency. For the Brazilian market, a further complexity is added to the development and verification process, which is the need to design and verify the controls and calibration considering the two fuels available in the market, the ethanol and the gasoline. In order to determine how the drivability is impacted by the ethanol, the paper presents a study where the drivability data were generated using the objective drivability measurement system AVL-DRIVE™.
Increasing fuel economy is a high priority of the automotive industry due to consumer demand and government regulations. High strength aluminum alloys such as AA7075-T6 can be used in strength-critical automotive applications to reduce vehicle weight and thus improve fuel economy. However, these aluminum alloys are known to be susceptible to stress corrosion cracking (SCC) for thick plate. The level of susceptibility to SCC must be determined before a material is implemented. ASTM standards exist that generate semi-quantitative data primarily for use in screening materials for SCC. For the purposes of this work ASTM G139 (breaking load method) has been used to evaluate sheet AA7075-T6 for use in automotive applications. A tensile fixture applying a constant strain was used to quantitatively measure residual strength of the material after exposure to a corrosive environment.