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Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

Diesel spray experimentation at controlled high-temperature and high-pressure conditions is intended to provide a more fundamental understanding of diesel combustion than can be achieved in engine experiments. This level of understanding is needed to develop the high-fidelity multi-scale CFD models that will be used to optimize future engine designs. Several spray chamber facilities capable of high-temperature, high-pressure conditions typical of engine combustion have been developed, but because of the uniqueness of each facility, there are uncertainties about their operation. For this paper, we describe results from comparative studies using constant-volume vessels at Sandia National Laboratories and IFP.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

This paper first summarizes a new theoretical description that quantifies the effects of real-fluid thermodynamics on liquid fuel injection processes as a function of pressure at typical engine operating conditions. It then focuses on the implications this has on modeling such flows with emphasis on application of the Large Eddy Simulation (LES) technique. The theory explains and quantifies the major differences that occur in the jet dynamics compared to that described by classical spray theory in a manner consistent with experimental observations. In particular, the classical view of spray atomization as an appropriate model at some engine operating conditions is questionable. Instead, non-ideal real-fluid behavior must be taken into account using a multicomponent formulation that applies to hydrocarbon mixtures at high-pressure supercritical conditions.

We investigate the mixing, penetration, and ignition characteristics of high-pressure n-dodecane sprays having a split injection schedule (0.5/0.5 dwell/0.5 ms) in a pre-burn combustion vessel at ambient temperatures of 750 K, 800 K and 900 K. High-speed imaging techniques provide a time-resolved measure of vapor penetration and the timing and progression of the first- and second-stage ignition events. Simultaneous single-shot planar laser-induced fluorescence (PLIF) imaging identifies the timing and location where formaldehyde (CH2O) is produced from first-stage ignition and consumed following second-stage ignition. At the 900-K condition, the second injection penetrates into high-temperature combustion products remaining in the near-nozzle region from the first injection. Consequently, the ignition delay for the second injection is shorter than that of the first injection (by a factor of two) and the second injection ignites at a more upstream location near the liquid length.

Well-mixed lean SI engine operation can provide improvements of the fuel economy relative to that of traditional well-mixed stoichiometric SI operation. This work examines the use of two methods for improving the stability of lean operation, namely multi-pulse transient plasma ignition and intake air preheating. These two methods are compared to standard SI operation using a conventional high-energy inductive ignition system without intake air preheating. E85 is the fuel chosen for this study. The multi-pulse transient plasma ignition system utilizes custom electronics to generate 10 kHz bursts of 10 ultra-short (12ns), high-amplitude pulses (200 A). These pulses were applied to a custom spark plug with a semi-open ignition cavity. High-speed imaging reveals that ignition in this cavity generates a turbulent jet-like early flame spread that speeds up the transition from ignition to the main combustion event.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures. Vehicles with power export capability are an attractive supplement to this electrical power evolution since they are usually on site, would reduce the amount of material for outpost creation, and provide a modular approach to outpost build-up.

Spark-ignition (SI) engine efficiency is typically limited by fuel auto-ignition resistance, which is described in practice by the Research Octane Number (RON) and the Motor Octane Number (MON). The goal of this work is to assess whether fuel properties (i.e. RON, MON, and heat of vaporization) are sufficient to describe the antiknock behavior of varying gasoline formulations in modern engines. To this end, the auto-ignition resistance of three compositionally dissimilar gasoline-like fuels with identical RON values and varying or non-varying MON values were evaluated in a modern, prototype, 12:1 compression ratio, high-swirl (by nature of intake valve deactivation), directly injected spark ignition (DISI) engine at 1400 RPM. The three gasolines are an alkylate blend (RON=98, MON=97), a blend with high aromatic content (RON=98, MON=88), and a blend of 30% ethanol by volume with a gasoline BOB (RON=98, MON=87; see Table 2 for details).

Simulations of the US light duty vehicle stock help policy makers, investors, and auto manufacturers make informed decisions to influence the future of the stock and its associated green house gas emissions. Such simulations require an underlying framework that captures the key elements of consumer purchasing decisions, which can be uncertain. This uncertainty in a simulation’s logic is usually convolved with uncertainty in the underlying assumptions about the futures of energy prices and technology innovation and availability. By comparing simulated alternative energy vehicle (AEV) sales to historical sales data, one can assess the simulation’s ability to capture the dynamics of consumer choice, independent of many of those underlying uncertainties, thereby determining the factors that most strongly impact sales.

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. The engine’s limited operating range can be improved by taking advantage of electrification in the powertrain. In this study, a multi-mode LTC-SI engine is integrated with a parallel hybrid electric configuration, where the engine operation modes include Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI). The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Two-scale command shaping is a recently proposed feedforward control method aimed at mitigating undesirable vibrations in nonlinear systems. The TSCS strategy uses a scale separation to cancel oscillations arising from nonlinear behavior of the system, and command shaping of the remaining linear problem. One promising application of TSCS is in reducing engine restart and shutdown vibrations found in conventional and in hybrid electric vehicle powertrains equipped with start-stop features. The efficacy of the TSCS during internal combustion engine restart has been demonstrated theoretically and experimentally in the authors’ prior works. The present article presents simulation results and describes the verified experimental apparatus used to study TSCS as applied to the ICE shutdown case. The apparatus represents a typical HEV powertrain and consists of a 1.03 L three-cylinder diesel ICE coupled to a permanent magnet alternating current electric machine through a spur gear coupling.

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e., the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry.

High resolution planar laser-induced fluorescence (PLIF) measurements were performed in an optically accessible internal combustion (IC) engine to investigate the behavior of scalar dissipation and the fine-scale structures of the turbulent scalar field. The fluorescent tracer fluorobenzene was doped into one of the two intake streams and nitrogen was used as the carrier gas to permit high signal-to-noise ratio fluorescence measurements without oxygen quenching effects. The resulting two-dimensional images allowed for an analysis of the structural detail of the scalar and scalar dissipation fields defined by the mixing of the two adjacent intake streams. High levels of scalar dissipation were found to be located within convoluted, sheet-like structures in accordance with previous studies. The fluorescence data, which were acquired during the intake stroke, were also used to examine the scalar energy and dissipation spectra.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.