Search Results

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

Simplified visualization of the fuel spray developing process in a small D.I. diesel engine was made by the liquid injection technique. In this technique, a liquid fuel was injected into another liquid to simulate injection into a high pressure gaseous atmosphere. For obtaining spray characteristics in the liquid similar to a diesel spray in a high-pressure gaseous atmosphere, the similarity principles based on the Reynolds number of the fuel flow at a nozzle hole and empirical equations of the spray penetration including the breakup length were introduced in this study. Especially, the injector was newly designed for the liquid injection technique based on these similarity principles. The behavior of the spray in a swirling flow was investigated. The spray with different breakup length shows different behavior in the same swirling flow.

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.

An optimal energy management strategy (Optimal EMS) can yield significant fuel economy (FE) improvements without vehicle velocity modifications. Thus it has been the subject of numerous research studies spanning decades. One of the most challenging aspects of an Optimal EMS is that FE gains are typically directly related to high fidelity predictions of future vehicle operation. In this research, a comprehensive dataset is exploited which includes internal data (CAN bus) and external data (radar information and V2V) gathered over numerous instances of two highway drive cycles and one urban/highway mixed drive cycle. This dataset is used to derive a prediction model for vehicle velocity for the next 10 seconds, which is a range which has a significant FE improvement potential. This achieved 10 second vehicle velocity prediction is then compared to perfect full drive cycle prediction, perfect 10 second prediction.

There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.

To get a better understanding of the characteristics of the high pressure gasoline sprays impinging on a wall, a fundamental study was conducted in a high-temperature high-pressure constant volume vessel under the simulated engine conditions of in-cylinder pressures, temperatures, and wall temperatures. The injection pressure was varied from 20 to 120 MPa. The spray tip penetration, vapor mass distribution, and vaporization rate were quantitatively measured with the laser absorption-scattering (LAS) technique. The velocity fields of the wall-impinging sprays under vaporizing conditions were measured with the particle image velocimetry (PIV) technique using silicone oil droplets as tracers. The effects of injection pressure and spray/wall interactions on spray characteristics were investigated. The results showed that the increased injection pressure improved penetration, vaporization, and turbulence of the sprays.

Some experimental investigations have shown that the trade-off curve of NOx vs. particulate of a D.I. diesel engine with split-injection strategies can be shifted closer to the origin than those with a single-pulse injection, thus reducing both particulate and NOx emissions significantly. It is clear that the injection mass ratios and the dwell(s) between injection pulses have significant effects on the combustion and emissions formation processes in the D.I. diesel engine. However, how and why these parameters significantly affect the engine performances remains unexplained. The effects of both injection mass ratios and dwell between injections on vapor/liquid distributions in the split-injection diesel sprays impinging on a flat wall have been examined in our previous work.

The Energy Finite Element Analysis(EFEA) is a recent development for high frequency vibro-acoustic analysis, and constitutes an evolution in the area of high frequency computations. The EFEA is a wave based approach, while the SEA is a modal based approach. In this paper the similarities in the theoretical development of the two methods are outlined. The main scope of this paper is to establish the validity of the EFEA by analyzing several complex structural-acoustic systems. The EFEA solutions are compared successfully to SEA results and to solutions obtained from extremely dense conventional FEA models.

The emerging Variable Valve Timing (VVT) technology complicates the estimation of air flow rate because both intake and exhaust valve timings significantly affect engine's gas exchange and air flow rate. In this paper, we propose to use Artificial Neural Networks (ANN) to model the air flow rate through a 2.4 liter VVT engine with independent intake and exhaust camshaft phasers. The procedure for selecting the network architecture and size is combined with the appropriate training methodology to maximize accuracy and prevent overfitting. After completing the ANN training based on a large set of dynamometer test data, the multi-layer feedforward network demonstrates the ability to represent air flow rate accurately over a wide range of operating conditions. The ANN model is implemented in a vehicle with the same 2.4 L engine using a Rapid Prototype Controller.

An experimental study is performed for homogeneous charge compression ignition (HCCI) combustion focusing on late phasing conditions with high cyclic variability (CV) approaching misfire. High CV limits the feasible operating range and the objective is to understand and quantify the dominating effects of the CV in order to enable controls for widening the operating range of HCCI. A combustion analysis method is developed for explaining the dynamic coupling in sequences of combustion cycles where important variables are residual gas temperature, combustion efficiency, heat release during re-compression, and unburned fuel mass. The results show that the unburned fuel mass carries over to the re-compression and to the next cycle creating a coupling between cycles, in addition to the well known temperature coupling, that is essential for understanding and predicting the HCCI behavior at lean conditions with high CV.

The emission of excessive quantities of NOx when the automobile air conditioner is turned on has received a fair amount of attention in recent years. Since NOx is a smog precursor, it is important to understand the reasons for this jump in emissions especially on hot sunny days when air conditioner usage is at a maximum. A simple thermodynamic model is used to demonstrate how the torque from a typical air conditioner compressor is mainly related to the ambient temperature. The compressor's on-off cycling patterns are also characterized. Since the compressor significantly loads the engine, it affects fuel economy and emissions. The key independent variable that we employ to represent engine load is fuel rate. The correlations between engine-out NOx emissions and fuel rate are shown for a number of light duty vehicles and trucks. From these, a physical model for engine-out NOx emissions (with and without air conditioning) is presented.

Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.

Advanced features in automotive systems often necessitate the management of complex interactions between subsystems. Existing control strategies are designed for certain levels of robustness, however their performance can unexpectedly deteriorate in the presence of significant uncertainties, resulting in undesirable system behaviors. This limitation is further amplified in systems with complex nonlinear dynamics. Hydro-mechanical clutch actuators are among those systems whose behaviors are highly sensitive to variations in subsystem characteristics and operating environments. In a P2 hybrid propulsion system, a wet clutch is utilized for cranking the engine during an EV-HEV mode switching event. It is critical that the hydro-mechanical clutch actuator is stroked as quickly and as consistently as possible despite the existence of uncertainties. Thus, the quantification of uncertainties on clutch actuator behaviors is important for enabling smooth EV-HEV transitions.

In this paper the development of statistical metamodels and statistical fast running models is presented first. They are utilized for propagating uncertainties in a multi-discipline design optimization process. Two main types of uncertainty can be considered in this manner: uncertainty due to variability in design variables or in random parameters; uncertainty due to the utilization of metamodels instead of the actual simulation models during the optimization process. The value of the new developments and their engagement in multi-discipline design optimization is demonstrated through a case study. An underwater vehicle is designed under four different disciplines, namely, noise radiation, self-noise due to TBL excitation, dynamic response due to propulsion impact loads, and response to an underwater detonation.

Developing a complete understanding of the structure and behavior of the near-wall region (NWR) in reciprocating, internal combustion (IC) engines and of its interaction with the core flow is needed to support the implementation of advanced combustion and engine operation strategies, as well as predictive computational models. The NWR in IC engines is fundamentally different from the canonical steady-state turbulent boundary layers (BL), whose structure, similarity and dynamics have been thoroughly documented in the technical literature. Motivated by this need, this paper presents results from the analysis of two-component velocity data measured with particle image velocimetry near the head of a single-cylinder, optical engine. The interaction between the NWR and the core flow was quantified via statistical moments and two-point velocity correlations, determined at multiple distances from the wall and piston positions.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

An experimental study was made of the two-dimensional distributions of the fuel vapor concentration simulated by Freon-12 in the combustion chamber of a SI engine. Laser Rayleigh scattering was applied for this remote, nonintrusive and highly space- and time-resolved measurement. The original engine was modified to introduce YAG laser-induced sheet light into the combustion chamber and the scattered light was captured by a CCD camera fitted with a gated double-microchannel plate image intensifier. The results showed that the fuel vapor concentration was highly heterogeneous during the intake stroke and the inhomogeneity decreased in the compression stroke. But, even at the end of the compression stroke, a number of small lumps of inhomogeneous mixture still existed randomly in the engine combustion chamber, which is assumed to cause the heterogeneity of the mixture strength field at the spark discharge.

Naturally aspirated HCCI operation is typically limited to medium load operation (∼ 5 bar net IMEP) by excessive pressure rise rate. Boosting can provide the means to extend the HCCI range to higher loads. Recently, it has been shown that HCCI can achieve loads of up to 16.3 bar of gross IMEP by boosting the intake pressure to more than 3 bar, using externally driven compressors. However, investigating HCCI performance over the entire speed-load range with real turbocharger systems still remains an open topic for research. A 1 - D simulation of a 4 - cylinder 2.0 liter engine model operated in HCCI mode was used to match it with off-the-shelf turbocharger systems. The engine and turbocharger system was simulated to identify maximum load limits over a range of engine speeds. Low exhaust enthalpy due to the low temperatures that are characteristic of HCCI combustion caused increased back-pressure and high pumping losses and demanded the use of a small and more efficient turbocharger.

This work investigates the potential improvements in vehicle fuel economy possible by optimizing gear shift strategies to leverage a novel boosting device, an electrically assisted variable speed supercharger (EAVS), also referred to as a power split supercharger (PSS). Realistic gear shift strategies, resembling those commercially available, have been implemented to control upshift and downshift points based on torque request and engine speed. Using a baseline strategy from a turbocharged application of a MY2015 Ford Escape, a vehicle gas mileage of 34.4 mpg was achieved for the FTP75 drive cycle before considering the best efficiency regions of the supercharged engine.

An experimental study on emission formation processes, such as these of nitric oxide, particulate and total hydrocarbon in a small direct injection (D.I.) diesel engine was carried out by using a newly developed total in-cylinder sampling technique. The sampling method consisted of rapidly opening a blowdown valve attached to the bottom of the piston bowl, and quickly transferring most of the in-cylinder contents into a large sampling chamber below the piston. No modification of the intake and exhaust ports in a cylinder head was required for the installation of the blowdown apparatus. The sampling experiment gave a history of spatially-averaged emission concentrations in the cylinder. The effects of several engine variables, such as the length-to-diameter ratio of the nozzle hole, the ratio of the piston bowl diameter to the cylinder bore and the intake swirl ratio, on the emission formation processes were investigated.