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A detailed description of a numerical method for computing unsteady flows in engine intake and exhaust systems is given. The calculations include the effects of heat transfer and friction. The inclusion of such calculations in a mathematically simulated engine cycle is discussed and results shown for several systems. In particular, the effects of bell-mouth versus plain pipe terminations and the effects of a finite surge tank are calculated. Experimental data on the effect of heat transfer from the back of the intake valve on wave damping are given and show the effect to be negligible. Experimental data on wave damping during the valve closed period and on the temperature rise of the air near the valve are also given.

The ratio of two temperature gradients across the combustion-chamber wall in a diesel engine is used to provide a heat flow ratio showing the radiant heat transfer as a per cent of local total heat transfer. The temperature gradients were obtained with a thermocouple junction on each side of the combustion-chamber wall. The first temperature gradient was obtained by covering the thermocouple at the cylinder gas-wall interface with a thin sapphire window, while the second was obtained without the window. Results show that the time-average radiant heat transfer is of significant magnitude in a diesel engine, and is probably even more significant in heat transfer during combustion and expansion.

The objective of this research was to investigate the effect of injection pressure on air entrainment into transient diesel sprays. The main application of interest was the direct injection diesel engine. Particle Image Velocimetry was used to make measurements of the air entrainment velocities into a spray plume as a function of time and space. A hydraulically actuated, electronically controlled unit injector (HEUI) system was used to supply the fuel into a pressurized spray chamber. The gas chamber density was maintained at 27 kg/m3. The injection pressures that were studied in this current research project were 117.6 MPa and 132.3 MPa. For different injection pressures, during the initial two-thirds of the spray plume there was little difference in the velocities normal to the spray surface. For the last third of the spray plume, the normal velocities were 125% higher for the high injection pressure case.

Distracted driving remains a serious risk to motorists in the US and worldwide. Over 3,000 people were killed in 2013 in the US because of distracted driving; and over 420,000 people were injured. A system that can accurately detect distracted driving would potentially be able to alert drivers, bringing their attention back to the primary driving task and potentially saving lives. This paper documents an effort to develop an algorithm that can detect visual distraction using vehicle-based sensor signals such as steering wheel inputs and lane position. Additionally, the vehicle-based algorithm is compared with a version that includes driving-based signals in the form of head tracking data. The algorithms were developed using machine learning techniques and combine a Random Forest model for instantaneous detection with a Hidden Markov model for time series predictions.

A detailed mathematical model of the thermodynamic events of a crankcase scavenged, two-stroke, SI engine is described. The engine is divided into three thermodynamic systems: the cylinder gases, the crankcase gases, and the inlet system gases. Energy balances, mass continuity equations, the ideal gas law, and thermodynamic property relationships are combined to give a set of coupled ordinary differential equations which describe the thermodynamic states encountered by the systems of the engine during one cycle of operation. A computer program is used to integrate the equations, starting with estimated initial thermodynamic conditions and estimated metal surface temperatures. The program iterates the cycle, adjusting the initial estimates, until the final conditions agree with the beginning conditions, that is, until a cycle results.

Autonomous vehicle (AV) developers test extensively on public roads, potentially putting other road users at risk. A safety case for human supervision of road testing could improve safety transparency. A credible safety case should include: (1) the supervisor must be alert and able to respond to an autonomy failure in a timely manner, (2) the supervisor must adequately manage autonomy failures, and (3) the autonomy failure profile must be compatible with effective human supervision. Human supervisors and autonomous test vehicles form a combined human-autonomy system, with the total rate of observed failures including the product of the autonomy failure rate and the rate of unsuccessful failure mitigation by the supervisor. A difficulty is that human ability varies in a nonlinear way with autonomy failure rates, counter-intuitively making it more difficult for a supervisor to assure safety as autonomy maturity improves.

Increasingly sophisticated vehicle automation can perform steering and speed control, allowing the driver to disengage from driving. However, vehicle automation may not be capable of handling all roadway situations and driver intervention may be required in such situations. The typical approach is to indicate vehicle capability through displays and warnings, but control algorithms can also signal capability. Psychophysical methods can be used to link perceptual experiences to physical stimuli. In this situation, trust is an important perceptual experience related to automation capability that is revealed by the physical stimuli produced by different control algorithms. For instance, precisely centering the vehicle in the lane may indicate a highly capable system, whereas simply keeping the vehicle within lane boundaries may signal diminished capability.

Highly time resolved measurements of cylinder pressure acquired simultaneously from three transducers were used to investigate the nature of knocking combustion and to identify biases that the pressure measurements induce. It was shown by investigating the magnitude squared coherence (MSC) between the transducer signals that frequency content above approximately 40 kHz does not originate from a common source, i.e., it originates from noise sources. The major source of noise at higher frequency is the natural frequency of the transducer that is excited by the impulsive knock event; even if the natural frequency is above the sampling frequency it can affect the measurements by aliasing. The MSC analysis suggests that 40 kHz is the appropriate cutoff frequency for low-pass filtering the pressure signal. Knowing this, one can isolate the knock event from noise more accurately.

Extensive modeling and simulation studies have been carried out to evaluate the performance of systems for avoiding run-off-road crashes. Results show that the effectiveness of in-vehicle crash avoidance systems depends on how well they can be tailored to specific vehicle, driver, and roadway characteristics. To this end, a major focus of these studies is the development of improved driver lane-keeping models based on statistical analyses of data collected in driving experiments conducted on highways, rural roads, and test tracks. In recent simulation studies using improved driver models, the performance of crash avoidance systems in tractor-trailers and passenger cars has been compared over a wide range of incipient run-off-road crash conditions. Heavy trucks present a greater challenge for run-off-road crash avoidance systems, because they slightly but frequently leave the lane even under controlled driving, and because they are less stable during recovery maneuvers.

The effects of imaging system resolution and laser sheet thickness on the measurement of the Batchelor scale were investigated in a single-cylinder optical engine. The Batchelor scale was determined by fitting a model spectrum to the dissipation spectrum that was obtained from fuel tracer planar laser-induced fluorescence (PLIF) images of the in-cylinder scalar field. The imaging system resolution was quantified by measuring the step-response function; the scanning knife edge technique was used to measure the 10-90% clip width of the laser sheet. In these experiments, the spatial resolution varied from a native resolution of 32.0 μm to 137.4 μm, and the laser sheet thickness ranged from 108 μm to 707 μm. Thus, the overall resolution of the imaging system was made to vary by approximately a factor of four in the in-plane dimension and a factor of six in the out-of-plane dimension.

A computational, three-dimensional approach to investigate the behavior of diesel soot particles in the micro-channels of wall-flow Diesel Particulate Filters is presented. The KIVA3V CFD code, already extended to solve the 2D conservation equations for porous media materials [1], has been enhanced to solve in 2-D and 3-D the governing equations for reacting and compressible flows through porous media in non axes-symmetric geometries. With respect to previous work [1], a different mathematical approach has been followed in the implementation of the numerical solver for porous media, in order to achieve a faster convergency as source terms were added to the governing equations. The Darcy pressure drop has been included in the Navier-Stokes equations and the energy equation has been extended to account for the thermal exchange between the gas flow and the porous wall.

3-D Computational Fluid Dynamics (CFD) simulations have been performed to study particulate formation in a Spark-Ignition (SI) engine under premixed conditions. A semi-detailed soot model and a chemical kinetic model, including poly-aromatic hydrocarbon (PAH) formation, were coupled with a spark ignition model and the G equation flame propagation model for SI engine simulations and for predictions of soot mass and particulate number density. The simulation results for in-cylinder pressure and particle size distribution (PSDs) are compared to available experimental studies of equivalence ratio effects during premixed operation. Good predictions are observed with regard to cylinder pressure, combustion phasing and engine load. Qualitative agreements of in-cylinder particle distributions were also obtained and the results are helpful to understand particulate formation processes.

Recommender systems guide a user to useful objects in a large space of possible options in a personalized way. In this paper, we study recommender systems for vehicles. Compared to previous research on recommender systems in other domains (e.g., movies or music), there are two major challenges associated with recommending vehicles. First, typical customers purchase fewer cars than movies or pieces of music. Thus, it is difficult to obtain rich information about a customer’s vehicle purchase history. Second, content information obtained about a customer (e.g., demographics, vehicle preferences, etc.) is also difficult to acquire during a relatively short stay in a dealership. To address these two challenges, we propose an interactive vehicle recommender system based a novel machine learning method that integrates decision trees and multi-armed bandits. Decision tree learning effectively selects important questions to ask the customer and encodes the customer's key preferences.

The performance of a structural design significantly depends upon the assumptions made on input load. In order to estimate the input load, during the design and development stage of the suspension assembly of a BAJA car, designers and analysts invest immense amount of time and effort to formulate the mathematical model of the design. These theoretical formulations may include idealization errors which can affect the performance of the car as a final product. Due to the errors associated with the assumption of design load, several components might have more weight or may have less strength than needed. This discrepancy between the assumed input load (lab or theoretical studies) and the actual load from the environment can be eliminated by performing a real life testing process using load recovery methodology. Commercial load cells exist in industry to give engineers insight to understanding the complex real world loading of their structures.

Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity.

Driving through intersections can be potentially dangerous because nearly 23 percent of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year [1]. The impact of traffic intersections on trip delays also leads to waste of human and natural resources. Our goal is to increase the safety and throughput of traffic intersections using co-operative driving. In earlier work [2], we have proposed a family of vehicular network protocols, which use Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environment (WAVE) technologies to manage a vehicle's movement at intersections Specifically, we have provided a collision detection algorithm at intersections (CDAI) to avoid potential crashes at or near intersections and improve safety. We have shown that vehicle-to-vehicle (V2V) communications can be used to significantly decrease the trip delays introduced by traffic lights and stop signs.

The higher cylinder peak pressure and pressure rise rate of modern diesel and gasoline fueled engines tend to increase combustion noise while customers demand lower noise. The multiple degrees of freedom in engine control and calibration mean there is more scope to influence combustion noise but this must first be measured before it can be balanced with other attributes. An efficient means to realize this is to calculate combustion noise from the in-cylinder pressure measurements that are routinely acquired as part of the engine development process. This publication reviews the techniques required to ensure accurate and precise combustion noise measurements. First, the dynamic range must be maximized by using an analogue to digital converter with sufficient number of bits and selecting an appropriate range in the test equipment.

The University of Wisconsin-Madison Snowmobile Team has designed and constructed a clean, quiet, high performance snowmobile for entry in the 2008 Society of Automotive Engineers' Clean Snowmobile Challenge. Built on a 2003 cross-country touring chassis, this machine features a 750 cc fuel-injected four-stroke engine equipped with a fuel sensor which allows operation ranging from regular gasoline to an 85% blend of ethanol and gasoline (E85). The engine has been customized with a Mototron control system which allows for full engine optimization using a range of fuels from E00 to E85. Utilizing a heated oxygen sensor and a 3-way catalyst customized for this engine by W.C. Heraeus-GmbH, this sled reduces NOx, HC and CO emissions by up to 89% to an average specific mass of 0.484, 0.154, 4.94 g/kW-hr respectively. Finally, the Mototron system also allowed Wisconsin to extract another 4 kW from the Weber 750cc engine; producing 45 kW and 65 Nm of torque.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

In recent years society's demand and interest in clean and efficient internal combustion engines has grown significantly. Several ideas have been proposed and tested to meet this demand. In particular, dual-fuel Reactivity Controlled Compression Ignition (RCCI) combustion has demonstrated high thermal efficiency, and low engine-out NOx, and soot emissions. Unlike homogeneous charge compression ignition (HCCI) combustion, which solely relies on the chemical kinetics of the fuel for ignition control, RCCI combustion has proven to provide superior combustion controllability while retaining the known benefits of low emissions and high thermal efficiency of HCCI combustion. However, in order for RCCI combustion to be adopted as a high efficiency and low engine-out emission solution, it is important to achieve high-power operation that is comparable to conventional diesel combustion (CDC).