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The object of this paper is to present a new way of analyzing in-cylinder velocity measurements. The technique is called Discrete Wavelet Transform (DWT) and it is similar to Fast Fourier Transform (FFT) with one important difference it is possible to obtain both time localized and frequency resolved information. This paper demonstrates the use of DWT calculations on in-cylinder LDV flow measurements for different combustion geometries in a natural gas converted truck engine. It will furthermore provide some information about how DWT can be used with in-cylinder measurements in the future.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

Previous research has shown that the homogeneous charge compression ignition (HCCI) combustion concept holds promise for reducing pollutants (i.e. NOx, soot) while maintaining high thermal efficiency. However, it can be difficult to control the operation of the HCCI engines even under steady state running conditions. Power density may also be limited if high inlet air temperatures are used for achieving ignition. A methodology using a small pilot quantity of diesel fuel injected during the compression stroke to improve the power density and operation control is considered in this paper. Multidimensional computations were carried out for an HCCI engine based on a CAT3401 engine. The computations show that the required initial temperature for ignition is reduced by about 70 K for the cases of the diesel pilot charge and a 25∼35% percent increase in power density was found for those cases without adversely impacting the NOx emissions.

This paper presents a response to the question: Simulation - mathematical manipulation or useful design tool? A mathematical model of a modulating valve in a transmission control system was developed to predict clutch pressure modulation characteristics. The transmission control system was previously reported in SAE Paper 850783 - “Electronic/Hydraulic Transmission Control System for Off-Highway Vehicles”. The comparison of simulation predictions with test data illustrates the effectiveness of simulation as a design tool. THE EVOLUTION OF COMPUTER hardware and simulation software has resulted in increased interest and usage of simulation for dynamic analysis of hydraulic systems. Most commercially available software is relatively easy to learn to use. The application of such software and the modeling techniques involved require a longer learning curve.

Although soot-formation processes in diesel engines have been well characterized during the mixing-controlled burn, little is known about the distribution of soot throughout the combustion chamber after the end of appreciable heat release during the expansion and exhaust strokes. Hence, the laser-induced incandescence (LII) diagnostic was developed to visualize the distribution of soot within an optically accessible single-cylinder direct-injection diesel engine during this period. The developed LII diagnostic is semi-quantitative; i.e., if certain conditions (listed in the Appendix) are true, it accurately captures spatial and temporal trends in the in-cylinder soot field. The diagnostic features a vertically oriented and vertically propagating laser sheet that can be translated across the combustion chamber, where “vertical” refers to a direction parallel to the axis of the cylinder bore.

Ion current measurements can give information useful for controlling the combustion stability in a multi-cylinder engine. Operation near the dilution limit (air or EGR) can be achieved and it can be optimized individually for the cylinders, resulting in a system with better engine stability for highly diluted mixtures. This method will also compensate for engine wear, e.g. changes in volumetric efficiency and fuel injector characteristics. Especially in a port injected engine, changes in fuel injector characteristics can lead to increased emissions and deteriorated engine performance when operating with a closed-loop lambda control system. One problem using the ion-current signal to control engine stability near the lean limit is the weak signal resulting in low signal to noise ratio. Measurements presented in this paper were made on a turbocharged 9.6 liter six cylinder natural gas engine with port injection.

The control strategy of switched reluctance motor (SRM) in-wheel motor is investigated in order to reduce the influence of torque ripple of SRM on the ride comfort. The nonlinear model of switched reluctance motor (SRM) is established and the variable angle control strategy with optimal switch angles is applied to control SRM. However, the variable angle control strategy can not reduce the torque ripple of SRM significantly. Therefore, some advanced control strategies are developed to improve the ride comfort in electric vehicle. In this paper, the fuzzy proportional integration differential (PID) is developed to improve the torque ripple of SRM in which the fuzzy control idea is utilized to adjust the parameters of proportional integration differential (PID) control online and ensure the adaptive capabilities of the fuzzy proportional integration differential (PID) control to motor driving system.

During development of an air assisted, direct injection combustion system, it was found that an air pulse during the late part of compression stroke significantly shortened the combustion duration and extended the lean limits of the engine. The effect of an injection of pure air through an air assist direct injector was studied with Particle Image Velocimetry, PIV. Results showed that an air pulse during the compression stroke significantly speeded up in-cylinder velocities, which also was showed in the heat release analysis. A system to use low density seeding particles was developed and is presented in the paper.

The different roles played by small and large eddies in engine combustion were studied. Experiments compared natural gas combustion in a converted, single cylinder Volvo TD 102 engine and in a 125 mm cubical cell. Turbulence is used to enhance flame growth, ideally giving better efficiency and reduced cyclic variation. Both engine and test cell results showed that flame growth rate correlated best with the level of high frequency, small eddy turbulence. The more effective, small eddy turbulence also tended to lower cyclic variations. Large scales and bulk flows convected the flame relative to cool surfaces and were most important to the initial flame kernel.

Software systems on electronically controlled diesel truck engines typically provide diagnostic features to enable the engine mechanic to identify and debug system problems. As future systems become more sophisticated, so will the diagnostic requirements. The advantages of serviceability and accuracy found in todays electronic systems must not be allowed to degrade due to this increased sophistication. One method of maintaining a high level of serviceability and accuracy is to place an even greater priority on diagnostics and servicing in the initial design phase of the product than is done today. In particular, three major goals of future diagnostic systems should be separation of component failures from system failures, prognostication of failures and analysis of engine performance. This paper will discuss a system to realize these goals by dividing the diagnostic task into the Electronic System Diagnostics, Engine System Diagnostics and the Diagnostic Interface.

In partly autonomous driving such as level 2 or level 3 automatic driving from SAE international classification, the switching of the driving right between the human driver and the machine plays an important role in the driving process of vehicle [1]. In this paper, the data collected from vehicle states and the driving behavior of drivers is completed via a simulator and self-report questionnaires. A fuzzy analytic network process (Fuzzy-ANP) model is developed to evaluate the driving capability of the drivers in real time from vehicle states due to its direct inherent link to the change of the driving state of drivers Moreover, in this model, the idea of group decision and multi-index fusion is adopted. The questionnaire is required to identify the experimental results from the simulator. The results show that the proposed Fuzzy-ANP model can evaluate the driving capability of the participants in real time accurately.

2-D LDV measurements were performed on two different cylinder designs in a fired two-stroke engine running with wide-open throttle at 9000 rpm. The cylinders examined were one with open transfer channels and one with cup handle transfer channels. Optical access to the cylinder was achieved by removing the silencer and thereby gain optical access through the exhaust port. No addition of seeding was made, since the fuel droplets were not entirely vaporized as they entered the cylinder and thus served as seeding. Results show that the loop-scavenging effect was poor with open transfer channels, but clearly detectable with cup handle channels. The RMS-value, “turbulence”, was low close to the transfer ports in both cylinders, but increased rapidly in the middle of the cylinder. The seeding density was used to obtain information about the fuel concentration in the cylinder during scavenging.

Cost reduction in the automotive industry becomes a widely-adopted operational strategy not only for Original Equipment Manufacturers (OEMs) that take cost leader generic corporation strategy, but also for many OEMs that take differentiation generic corporation strategy. Since differentiation generic strategy requires an organization to provide a product or service above the industry average level, a premium is typically included in the tag price for those products or services. Cost reduction measures could increase risks for the organizations that pursue differentiation strategy. Although manufacturers in the automotive industry dramatically improved production efficiency in past ten years, they are still facing the pressure of cost control. The big challenge in cost control for automakers and suppliers is increasing prices of raw materials, energy and labor costs. These costs create constraints for the traditional economic expansion model.

The application of Artificial Intelligence (AI) in the automotive industry can dramatically reshape the industry. In past decades, many Original Equipment Manufacturers (OEMs) applied neural network and pattern recognition technologies to powertrain calibration, emission prediction and virtual sensor development. The AI application is mostly focused on reducing product development and validation cost. AI technologies in these applications demonstrate certain cost-saving benefits, but are far from disruptive. A disruptive impact can be realized when AI applications finally bring cost-saving benefits directly to end users (e.g., automation of a vehicle or machine operation could dramatically improve the efficiency). However, there is still a gap between current technologies and those that can fully give a vehicle or machine intelligence, including reasoning, knowledge, planning and self-learning.

Accurate estimation of battery state of health (SOH) has become indispensable in ensuring the predictive maintenance and safety of electric vehicles (EVs). While supervised machine learning excels in laboratory settings with adequate SOH labels, field-based SOH data collection for supervised learning is hindered by EVs' complex conditions and prohibitive data collection costs. To overcome this challenge, a battery SOH estimation method based on semi-supervised regression is proposed and validated using field data in this paper. Initially, the Ampere integral formula is employed to calculate SOH labels from charging data, and the error of labeled SOH is reduced by the open-circuit voltage correction strategy. The calculation error of the SOH label is confirmed to be less than 1.2%, as validated by the full-charge test of the battery packs.

Homogeneous Charge Compression Ignition (HCCI) has been proposed for natural gas engines in heavy duty stationary power generation applications. A number of researchers have demonstrated, through simulation and experiment, the feasibility of obtaining high gross indicated thermal efficiencies and very low NOx emissions at reasonable load levels. With a goal of eventual commercialization of these engines, this paper sets forth some of the primary challenges in obtaining high brake thermal efficiency from production feasible engines. Experimental results, in conjunction with simulation and analysis, are used to compare HCCI operation with traditional lean burn spark ignition performance. Current HCCI technology is characterized by low power density, very dilute mixtures, and low combustion efficiency. The quantitative adverse effect of each of these traits is demonstrated with respect to the brake thermal efficiency that can be expected in real world applications.

In an attempt to extend the upper load limit for Homogeneous Charge Compression Ignition (HCCI), supercharging in combination with Exhaust Gas Recirculation (EGR) have been applied. Two different boost pressures were used, 1.1 bar and 1.5 bar. High EGR rates were used in order to reduce the combustion rate. The highest obtained IMEP was 16 bar. This was achieved with the higher boost pressure, at close to stoichiometric conditions and with approximately 50 % EGR. Natural gas was used as the main fuel. In the case with the higher boost pressure, iso-octane was used as pilot fuel, to improve the ignition properties of the mixture. This made it possible to use a lower compression ratio and thereby reducing the maximum cylinder pressure. The tests were performed on a single cylinder engine operated at low speed (1000 rpm). The test engine was equipped with a modified cylinder head, having a Variable Compression Ratio (VCR) mechanism.

Styrene, or ethylbenzene, is mainly used as a monomer for the production of polymers, most notably Styrofoam. In the synthetis of styrene, the feedstock of benzene and ethylene is converted into aromatic oxygenates such as benzaldehyde, 2-phenyl ethanol and acetophenone. Benzaldehyde and phenyl ethanol are low value side streams, while acetophenone is a high value intermediate product. The side streams are now principally rejected from the process and burnt for process heat. Previous in-house research has shown that such aromatic oxygenates are suitable as diesel fuel additives and can in some cases improve the soot-NOx trade-off. In this study acetophenone, benzaldehyde and 2-phenyl ethanol are each added to commercial EN590 diesel at a ratio of 1:9, with the goal to ascertain whether or not the lower value benzaldehyde and 2-phenyl ethanol can perform on par with the higher value acetophenone. These compounds are now used in pure form.

Function and performance test of automated vehicles in the closed field is a necessary way to verify their safety, intelligence and comfort. The design and number of test scenarios will influence if the automated vehicles can be tested and evaluated effectively and fast. Based on the interrelationship among the vehicle, driver’s (or control system) driving strategy and road, we use the permutation and combination method to compare the relative position and movement relations between an automated vehicle (vehicle under test) and the surrounding vehicles to generate a total possible test scenarios group.