Search Results

The thermal efficiency of spark-ignition engines can be enhanced by increasing the rate of exhaust gas recirculation (EGR) such that the low temperature combustion regime could be achieved. However, there is an upper limit on the amount of EGR rate, beyond which flame speed becomes slow and unstable, and local quenching starts to hurt the combustion stability, efficiency, and emission. To resolve this issue, the concept of dedicated EGR has been proposed previously to be an effective way to enhance flame propagation under lean burn condition with even higher levels of EGR with reformate hydrogen and carbon monoxide. In this study, the effects of thermochemical fuel reforming on the reformate composition under rich conditions (1.0 < ϕ < 2.0) have been studied using detailed chemistry for iso-octane, as the representative component for gasoline.

Four 1998 Mitsubishi Carismas, two equipped with direct injection and two with port fuel injection engines, were tested in 20,100 km intervals to determine the effect of mileage accumulation cycle, engine type, fuel and lubricant on vehicle deposits and emissions, acceleration and driveability performance. The program showed that engine fuel system deposits, including specifically those on intake valves, combustion chambers and injectors are formed in higher amounts in the GDI engine than the PFI engine. The fuel additive used reduced injector deposits and combustion chamber deposits in the GDI, but had no significant effect on intake valve deposits, which are affected by crankcase oil formulation. In GDI vehicles, deposited engines were found to have increased hydrocarbon and carbon monoxide emissions and poorer fuel economy and acceleration, but lower particulate emissions.

Four 1998 Mitsubishi Carismas, two equipped with direct injection (GDI) and two with port fuel injection engines (PFI) were tested in a designed experiment to determine the effect of mileage accumulation cycle, engine type, fuel and lubricant type on engine wear and engine oil performance parameters. Fuel types were represented by an unadditised base fuel meeting EEC year 2000 specifications and the same base fuel plus synthetic deposit control additive packages. Crankcase oils were represented by two types (1) a 5W-30 API SJ/ILSAC GF-2 type engine oil and (2) a 10W-40 API SH/CF ACEA A3/ B3-96 engine oil. The program showed that specific selection of oil additive chemistry may reduce formation of intake valve deposits in GDI cars.. In general, G-DI engines produced more soot and more pentane insolubles and were found to be more prone to what appears to be soot induced wear than PFI engines.

Experiments have been conducted in a laminar flow system and in a research engine to investigate the effect of additives on the combustion of gasoline-like fuels. The purpose of the laminar system is to enable rapid screening of additives to determine which, if any, have an enhancing effect on the early stages of combustion, especially under conditions of poor fuel vaporization which exist during cold-start in a spark ignited engine and which make flame propagation difficult to start and sustain. The base fuel used in the laminar and engine systems was a 9 component mixture formulated to simulate those components of gasoline expected to be present in the vapor phase in the intake system of an engine under cold-start conditions. In the laminar system, the pre-mixed, pre-vaporized fuel-air mixture is ignited and a time history of the combustion generated, hydroxyl radical chemiluminescence is recorded.

Ethanol-gasoline blends are widely understood to present certain technical challenges to engine operation. Despite widespread use of fuels ranging from E5 (5% ethanol in gasoline) in some European countries to E10 (10% ethanol) in the United States to E100 (100% ethanol; “alcool”) in Brazil, there are certain subjects which have only anecdotally been examined. This paper examines two such issues: the effect of ethanol on intake valve deposits (IVD) and the impact of fuel additive on filter plugging (a measure of solubility). The effect of ethanol on IVD is studied along two lines of investigation: the effect of E10 in a multi-fuel data set carried out in the BMW 318i used for EPA and CARB certification, and the effect of varying ethanol content from 0% to 85% in gasoline carried out in a modern flex-fuel vehicle.

Low vibration and noise level in internal combustion engines has become an essential part of the design process. It is well known that the piston assembly can be a major source of engine mechanical friction and cold start noise, if not designed properly. The piston secondary motion and piston-bore contact pattern are critical in piston design because they affect the skirt-to-bore impact force and therefore, how the piston impact excitation energy is damped, transmitted and eventually radiated from the engine structure as noise. An analytical method is presented in this paper for simulating piston secondary dynamics and piston-bore contact for an asymmetric half piston model. The method includes several important physical attributes such as bore distortion effects due to mechanical and thermal deformation, inertia loading, piston barrelity and ovality, piston flexibility and skirt-to-bore clearance. The method accounts for piston kinematics, rigid-body dynamics and flexibility.

Flame speed data reported in most literature are acquired in conventional apparatus such as the spherical combustion bomb and counterflow burner, and are limited to atmospheric pressure and ambient or slightly elevated unburnt temperatures. As such, these data bear little relevance to internal combustion engines and gas turbines, which operate under typical pressures of 10-50 bar and unburnt temperature up to 900K or higher. These elevated temperatures and pressures not only modify dominant flame chemistry, but more importantly, they inevitably facilitate pre-ignition reactions and hence can change the upstream thermodynamic and chemical conditions of a regular hot flame leading to modified flame properties. This study focuses on how auto-ignition chemistry affects flame propagation, especially in the negative-temperature coefficient (NTC) regime, where dimethyl ether (DME), n-heptane and iso-octane are chosen for study as typical fuels exhibiting low temperature chemistry (LTC).

With the emergence of intelligent ground vehicles, an objective evaluation of vehicle mobility has become an even more challenging task. Vehicle mobility refers to the ability of a ground vehicle to traverse from one point to another, preferably in an optimal way. Numerous techniques exist for evaluating the mobility of vehicles on paved roads, both quantitatively and qualitatively, however, capabilities to evaluate their off-road performance remains limited. Whereas a vehicle’s off-road mobility may be significantly enhanced with intelligence, it also introduces many new variables into the decision making process that must be considered. In this paper, we present a decision analytic framework to accomplish this task. In our approach, a vehicle’s mobility is modeled using an operator’s preferences over multiple mobility attributes of concern. We also provide a method to analyze various operating scenarios including the ability to mitigate uncertainty in the vehicles inputs.

The constant velocity joint (CVJ) has seen increased usage driven by the growth of front wheel drive vehicles over the last 30 years. The CVJ provides a smooth, dynamic connection between the output of the axle or gearbox and the driving wheels of the vehicle. The seemingly simple device, however, requires specially designed greases to maximize protection of the internal components from distress and provide optimum performance and service life. One measure of potential distress in the CVJ can be related to temperature rise which is a reflection of the friction and wear properties of the grease employed. A test rig was designed and a method created to evaluate the temperature response of different greases used in a CVJ. The test rig was designed to allow a wide range of speeds, torques and shaft angles to be used. The rig uses a unique temperature pickup system to allow for dynamic measurement of the grease temperature in the boot.

Real-time measurement or estimation of crank-angle-resolved engine cylinder pressure may become commonplace in the next generation of engine controllers to optimize spark, valve timing, or compression ratio. Toward the development of a real-time cylinder pressure estimator, this work presents a crank-angle-resolved engine cylinder pressure estimation model that could accept inputs such as speed, manifold pressure and throttle position, and deliver crank-angle resolved cylinder pressure in real-time, at engine speeds covering the useful operating range of most engines. The model was validated by comparing simulated cylinder pressure with thirteen sets of cylinder pressure data, from two different commercial engines from two different OEMs. Estimated pressures were compared against the actual measured pressure traces. The average relative error is about 3% while the maximum relative error is 5%. Both can be improved with further tuning.

This work analyzes a cantilevered piezoelectric beam device for harvesting energy from the simultaneous rotation and translational vibration of vehicle wheels. The device attaches to the wheel rim so that it displaces tangentially during operation. A lumped-parameter analytical model for the coupled electromechanical system is derived. The device has one natural frequency that is speed-dependent because of centripetal acceleration affecting the total stiffness of the device. Even though the device has one natural frequency, it experiences three resonances as the rotation speed varies. One resonance occurs when the rotation speed coincides with the speed-dependent natural frequency of the device. The other two resonances are associated with excitations from the vibration of the vehicle wheel. The device’s parameters are chosen so that these three resonances occur when the wheel travels near 30 mph, 55 mph, and 70 mph.

A 100-hour engine dynamometer test for intake valve deposits (IVD) which uses a Ford 2.3L engine was developed by the Coordinating Research Council (CRC). Recently, this test has been approved by the American Society for Testing and Materials (ASTM) as Test Method D 6201-97. Since this test offers improvements in test variability, duration, and cost, it is expected to replace ASTM D 5500-94, a 16,000-km vehicle test run using a BMW 318i, as the key performance test for the Certification of Gasoline Deposit Control Additives by the EPA Final Rule. As a step in the replacement process, a correlation between valve deposit levels for the CRC 2.3L Ford IVD test and ASTM D 5500 BMW IVD test must be determined. This paper provides a statistical review of available data in an attempt to provide such a correlation.

Increasingly stringent vehicle emissions legislation is being introduced throughout the world, regulating the allowed levels of particulate matter emitted from vehicle tailpipes. The regulation may prove challenging for gasoline vehicles equipped with modern gasoline direct injection (GDI) technology, owing to their increased levels of particulate matter production. It is expected that gasoline particulate filters (GPFs) will soon be fitted to most vehicles sold in China and Europe, allowing for carbonaceous particulate matter to be effectively captured. However, GPFs will also capture and accumulate non-combustible inorganic ash within them, mainly derived from engine oil. Studies exist to demonstrate the impact of such ash on GPF and vehicle performance, but these commonly make use of accelerated ash loading methods, which themselves introduce significant variation.

The growing need for improved fuel economy is a global challenge due to continuously tightening environmental regulations targeting lower CO2 emission levels via reduced fuel consumption in vehicles. In order to reach these fuel efficiency targets, it necessitates improvements in vehicle transmission hardware components by applying advanced technologies in design, materials and surface treatments etc., as well as matching lubricant formulations with appropriate additive chemistry. Axle lubricants have a considerable impact on fuel economy. More importantly, they can be tailored to deliver maximum operational efficiency over specific or wide ranges of operating conditions. The proper lubricant technology with well-balanced chemistries can simultaneously realize both fuel economy and hardware protection, which are perceived to have a trade-off relationship.

In the last decade, numerous studies have been conducted to investigate the mechanism of Low Speed Pre-Ignition (LSPI) in Turbocharged Gasoline Direct Injection (TGDi) engines. According to technical reports, engine oil formulations can significantly influence the occurrence of LSPI particularly when higher levels of calcium-based additives are used, increasing the tendency for LSPI events to occur. While most of the studies conducted to date utilized engine tests, this paper evaluates the effect of engine oil formulations on LSPI under real-world driving conditions, so that not only the oil is naturally aged within an oil change interval, but also the vehicle is aged through total test distance of 160,000 km. Three engine oil formulations were prepared, and each tested in three vehicles leading to an identical fleet totaling nine vehicles, all of which were equipped with the same TGDi engine.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

Spark ignition engines utilize catalytic converters to reform harmful exhaust gas emissions such as carbon monoxide, unburned hydrocarbons, and oxides of nitrogen into less harmful products. Aftertreatment devices require the use of expensive catalytic metals such as platinum, palladium, and rhodium. Meanwhile, tightening automotive emissions regulations globally necessitate the development of high-performance exhaust gas catalysts. So, automotive manufactures must balance maximizing catalyst performance while minimizing production costs. There are thousands of different recipes for catalytic converters, with each having a different effect on the various catalytic chemical reactions which impact the resultant tailpipe gas composition. In the development of catalytic converters, simulation models are often used to reduce the need for physical parts and testing, thus saving significant time and money.

With the increased market share of electric vehicles, the demand for energy-efficient routing algorithms specifically optimized for electric vehicles has increased. Traditional routing algorithms are focused on optimizing the shortest distance or the shortest time in finding a path from point A to point B. These traditional methods have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power limits, battery capacity limits, and vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present an ant colony based, energy-efficient routing algorithm that is optimized and designed for electric vehicles. Simulation results show improvements in the energy consumption of electric vehicles when applied to a start-to-destination routing problem.

With increasing demand for cost-effective fuel cells, it is essential to investigate alternative materials for components of the fuel cells. The objective of this paper is to implement elastomeric materials (silicon rubber) for the use of bipolar plates in a polymer electrolyte membrane fuel cell. Two different types of conductive fillers, a graphite fiber and flake, were added at different concentrations to a two-component silicone rubber slurry. Electrical, thermal and mechanical properties of the composite material were investigated. Comparable electrical and thermal conductivities were achieved to that of commercially available plates. The silicone rubber based composite material maintained elastomeric properties for improved sealing of cell fluid reactants and products.

1Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure.