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In a Spark-Ignited engine, there will come a point, as load is increased, where the unburned air-fuel mixture undergoes auto-ignition (knock). The onset of knock represents the upper limit of engine output, and limits the extent of engine downsizing / boosting that can be implemented for a given application. Although effective at mitigating knock, requiring high octane fuel is not an option for most markets. Retarding spark timing can extend the high load limit incrementally, but is still bounded by limits for exhaust gas temperature, and spark retard results in a notable loss of efficiency. Likewise, enriching the air-fuel mixture also decreases efficiency, and has profound negative impacts on engine out emissions. In this current work, a Direct-Injected, Boosted, Spark-Ignited engine with Variable Valve Timing was tested under steady state high load operation. Comparisons were made among three fuels; an 87 AKI, a 91 AKI, and a 110 AKI off-road only race fuel.

The prevention of automotive releases of the unpleasant smelling hydrogen sulfide (H2S) is highly desirable. However, the ability to routinely test catalysts for dynamic H2S releases corresponding to the real world has traditionally proved difficult. The work herein identifies the key steps taken to produce a highly repeatable (overall relative standard deviation of typically less than 10%) procedure capable of replicating H2S releases from wide-open throttle (WOT) events. The testing utilized a chassis dynamometer to test a gasoline vehicle (fitted with one TWC system) over a specific transient drive cycle with H2S emissions detected using a chemical ionization mass spectrometer and an infra-red detection based system. The importance of the warm-up and catalyst preparation parts of the test are discussed, including statistical analysis. A repeatable and short test suited to rapid developmental screening of potential catalyst systems is also presented.

Impingement of jet-to-jet has been found to give improved spray penetration characteristics and higher vaporization rates when compared to multi-hole outwardly injecting fuel injectors which are commonly used in the gasoline engine. The current work studies a non-reacting spray by using a 5-hole impinging-jet style direct-injection injector. The jet-to-jet collision induced by the inwardly opening nozzles of the multi-hole injector produces rapid and short jet breakup which is fundamentally different from how conventional fuel injectors operate. A non-reacting spray study is performed using a 5-hole impinging jet injector and a traditional 6-hole Bosch Hochdruck-Einspritzventil (HDEV)-5 gasoline direct-injection (GDI) injector with gasoline as a fuel injected at 172 bar pressure with ambient temperature of 653 K and 490 K and ambient pressure of 37.4 bar and 12.4 bar.

The automotive industry is heading towards the path of autonomy with the development of autonomous vehicles. An autonomous vehicle consists of two main components. The first is the software which is responsible for the decision-making capabilities of the system. The second is the hardware which encompasses all aspects of the physical vehicle which are responsible for vehicle motion such as the engine, brakes and steering subsystems along with their corresponding controls. This component forms the basis of the autonomous vehicle platform. For SAE Level 4 autonomous vehicles, where an automated driving system is responsible for all the dynamics driving tasks including the fallback driving performance in case of system faults, redundant mechanical systems and controls are required as part of the autonomous vehicle platform since the driver is completely out of the loop with respect to driving.

A computer model solving the 1-D flow in a typical fuel injection system for direct-injection diesel engines is presented. A Bosch distributor - type VE pump connected to four Stanadyne pencil - type nozzles has been used to validate the computer model over a wide range of operating conditions. Validation of the developed computer code has been performed for eight representative test cases. The predicted values which were compared with the experimental ones include the pumping chamber pressure, the line pressure, the needle lift and the injection rate. Results using as input the measured pumping chamber pressure are also presented in order to identify the error in the injection rate signal attributed to the difference between the simulated and the experimental pumping chamber pressure. In addition, the total fuel injection quantity for pump speeds between 500 and 2000 rpm and lever positions between 20% to 100% was calculated and compared with measurements.

The cycle-by-cycle variation of heat transferred per cycle (q) to the combustion chamber surfaces of spark ignition engines has been investigated for quasi-steady and transient conditions produced by throttle movements. The heat transfer calculation is by integration of the instantaneous value over the cycle, using the Woschni correlation for the heat transfer coefficient. By examination of the results obtained, a relatively simple correlation has been identified: This holds both for quasi-steady and transient conditions and is on a per cylinder basis. The analysis has been extended to define a heat flux distribution over the surface of the chamber. This is given by: where F(x/L) is a polynomial function, q″ is the heat transfer per cycle per unit area to head and piston crown surfaces and gives the distribution along the liner

Cycle-by-cycle pressure data have been recorded for a spark ignition engine operating over a wide range of steady state and perturbed running condition. The data base has been analysed to derive mass fraction burnt, pressure development and work mean effective pressure characteristics for individual cycles. Cross-correlation coefficients have been calculated to identify predominant relationships. The effect of combustion phasing on cross-correlation coefficients is particularly significant and three regimes of behaviour have been identified. These are associated with early, optimal and late cases. The cross-correlations between parameters derived from cycle-by-cycle data do not uniformly reflect trends seen between cycle-averaged values of these. Auto-correlation results have been examined for interactions between successive cycles with less success, although, again combustion phasing can have a significant influence on the strength of auto-correlation coefficients.

The rapid heating of an under-body catalyst after cold start by combustion of rich engine products with added secondary air is described. The results of initial durability studies including spark plug fouling, oil dilution and thermal shock are presented, together with emissions performance and a mileage accumulation study. Also discussed are failure mode assessment and the system tolerance to anticipated open-loop errors and real-world driving scenarios.

Previously reported studies of heat transfer between the intake port surface, gas flows in the port, and fuel deposited in surface films have been extended to examine details of the heat flux variations which occur within the engine cycle. The dynamic response characteristics of the surface-mounted heat flux sensors have been determined, and measured heat flux data corrected accordingly to account for these characteristics. Details of the model and data processing technique used are described. Corrected intra-cycle variations of heat transfer to fuel deposited have been derived for engine operating conditions at 1000 RPM covering a range of manifold pressures, fuel supply rates, port surface temperatures, and fuel injection timings. Both pump-grade gasoline and isooctane fuel have been used. The effects of operating conditions on the magnitude and features of the heat flux variations are described.

This paper discusses how the orientation of fiber in fiber-reinforced plastics affects automotive applications. Orientation can adversely affect moldings in applications where stress is important, especially in engine components such as front timing covers, pump flanges, oil sump bosses, and crankshaft housing. The paper examines these problems in detail and suggests ways to avert serious difficulties relating to fiber orientation.

This paper describes a new range of 4 cyl, in-line, single OHC engines produced by Ford in Europe, which is available in three displacements of 1.3, 1.6, and 2.0 1. This engine has been developed for high performance output, high-speed operation, and compliance with various exhaust emission regulations. The significant design features highlighted here are the cylinder block, the cylinder head, the valve arrangement, the intake manifolds, and air cleaners with an air intake pre-heat system, all of which are described here. To establish reliability of this new engine, special test runs were made of 300 engines under customer driving conditions in many countries, covering a total of approximately 10 million km.

The FORD 2.5 Litre DI Engine entered volume production in January 1984, as the World's first high speed naturally aspirated direct injection diesel. Producing 52 KW at 4000 RPM the engine achieves a 15% fuel saving over indirect engines of similar size and rating. The direct injection engine is inherently less thermally active than pre-chamber engines and this, together with other design features, provides a power unit with extended durability for the medium van market. Based on controlled swirl air management, the otherwise conventional combustion system depends heavily on the fuel injection system for control throughout the speed load and temperature ranges. This paper describes the key elements of the design and performance development of the 2.5 litre DI engine, discusses the experience gained and examines the possibilities of a second generation of engines based on this system.

The construction of the Ford ELTEC (Electronic Technology) vehicle has offered a unique opportunity to demonstrate the practical advantages of using modern electronics in a family car. Included in the specification is the integrated control of a lean burn engine and a continuously variable transmission from a single microprocessor. A number of novel features are controlled such as ionisation feedback, intake port, variable geometry induction and an electronic throttle.

With the recent advancements in sensing and processing capabilities of consumer mobile devices (e.g., smartphone, tablet, etc.), they are becoming attractive choices for pervasive computing applications. Always-on monitoring of human movement patterns is one of those applications that has gained a lot of importance in the field of mobility and transportation research. Automatic detection of the current transportation mode (e.g., walking, biking, riding a shuttle, etc.) of a consumer using data from their smartphone sensors enables delivering of a number of customized services for multi-modal journey planning. Most accurate models for automatic mode detection are trained with supervised learning algorithms. In order to achieve high accuracy, the training datasets need to be sufficiently large, diverse, and correctly labeled.

This is the second part of a study on using port water injection to quantifiably enhance the knock performance of fuels. In the United States, the metric used to quantify the anti-knock performance of fuels is Anti Knock Index (AKI), which is the average of Research Octane Number (RON) and Motor Octane Number (MON). Fuels with higher AKI are expected to have better knock mitigating properties, enabling the engine to run closer to Maximum Brake Torque (MBT) spark timing in the knock limited region. The work done in part I of the study related increased knock tolerance due to water injection to increased fuel AKI, thus establishing an ‘effective AKI’ due to water injection. This paper builds upon the work done in part I of the study by repeating a part of the test matrix with Primary Reference Fuels (PRFs), with iso-octane (PRF100) as the reference fuel and lower PRFs used to match its performance with the help of port water injection.

With Euro III emissions standards requiring a 50% reduction in current diesel car emissions from January 1st 2000, there is a need to improve fuel consumption and thus reduce exhaust emissions. One of the ways this is being addressed is by the introduction of lower viscosity crankcase oils and by the use of friction modifiers within these oils. The resulting reduced engine friction contributes to improved fuel economy and should also aid engine cold start ability. To investigate the cold start abilities of different crankcase oils, a matrix consisting of six different oil formulations was tested at -20°C, - 25°C and -30°C in a two litre four cylinder diesel engine. The tests were conducted using a dynamometer, with the engine being driven by the dynamometer at nominal cranking speed for 30 seconds and then increased to cold idle speed for a further 30 seconds.

Currently, 80% of European diesel passenger cars are turbocharged and as emission standards become more stringent exhaust gas recirculation (EGR) will be the primary means of suppressing oxides of nitrogen (NOx). The lighter the load the greater will be the combustion tolerance to increased EGR flow rates and hence increased NOx suppression. Automotive diesel engines using wastegated turbochargers cannot recirculate above 50% EGR without some sort of “added” device or system, which is able to displace the inlet fresh air charge. This has been demonstrated by throttling the diesel intake to reduce the fresh air inlet manifold pressure so allowing more EGR flow by virtue of a higher exhaust-side pressure due the effects of the turbocharger. The method reported here investigates a different approach to increasing the EGR rates by replacing a fixed geometry turbocharger (FGT) with a variable geometry turbocharger, (VGT).

As intelligent automated vehicle technologies evolve, there is a greater need to understand and define the role of the human user, whether completely hands-off (L5) or partly hands-on. At all levels of automation, the human occupant may feel anxious or ill-at-ease. This may reflect as higher stress/workload. The study in this paper further refines how perceived workload may be determined based on occupant physiological measures. Because of great variation in individual personalities, age, driving experiences, gender, etc., a generic model applicable to all could not be developed. Rather, individual workload models that used physiological and vehicle measures were developed.

Air filter elements have been around since the dawn of automotive development. The function of an air induction system and the filter element in particular is to remove particulates such as dust, soot, and relatively minor contaminants from the air flow. This protects the engine, turbocharger, and other components from wear. However, sometimes severe duty cycles may cause large amounts of dust, mud, and water to enter the air induction system (AIS). This can cause filter degradation and even rupture or deformation, leading to highly increased engine and turbocharger wear. One example of this extreme loading is the tar sands region of Alberta, Canada, where trucks can accumulate over 1000 pounds of mud on a vehicle during normal usage over a few weeks’ time. Significant amounts of this mud also get ingested into the AIS. This study attempts to analyze different aspects of filter design to increase robustness to severe usage, particularly mud.

This paper demonstrates a solution to the security problem for automotive wireless powertrain networking. That is, the security for wireless automotive networking requires a localization function before we allow a node to join the network. We explain why for powertrain wireless networking, this ability of identifying the precise location of a communicating wireless node is critical. In this paper, we explore existing methods that others have used to implement localization for wireless networking. Then, we apply machine-learning techniques to a dataset that has localization information associated with received signal strength indication. We reveal insights provided by our dataset though an exploration with statistics and visualization. We then present our problem in terms of pattern recognition via multiple techniques, including Naïve Bayes Classifier and Artificial Neural Networks.