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The work presented here seeks to compare different means of providing scavenging systems for an automotive 2-stroke engine. It follows on from previous work solely investigating uniflow scavenging systems, and aims to provide context for the results discovered there as well as to assess the benefits of a new scavenging system: the reverse-uniflow sleeve-valve. For the study the general performance of the engine was taken to be suitable to power a medium-duty truck, and all of the concepts discussed here were compared in terms of indicated fuel consumption for the same cylinder swept volume using a one-dimensional engine simulation package. In order to investigate the sleeve-valve designs layout drawings and analysis of the Rolls-Royce Crecy-type sleeve had to be undertaken.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

To elucidate the complex characteristics of pre-chamber combustion engines, the interaction of the hot gas jets initiated by an active narrow throated pre-chamber with lean premixed CH4/air in a heavy-duty engine was studied computationally. A twelve-hole KAUST proprietary pre-chamber geometry was investigated using CONVERGE software. The KAUST pre-chamber has an upper conical part with the spark plug, and fuel injector, followed by a straight narrow region called the throat and nozzles connecting the chambers. The simulations were run for an entire cycle, starting at the previous cycle's exhaust valve opening (EVO). The SAGE combustion model was used with the chemistry modeled using a reduced methane oxidation mechanism based on GRI Mech 3.0, which was validated against in-house OH chemiluminescence data from the optical engine experiments.

Due to stringent emission standards, the demand for higher efficiency engines has been unprecedentedly high in recent years. Among several existing combustion modes, pre-chamber spark ignition (PCSI) emerges to be a potential candidate for high-efficiency engines. Research on the pre-chamber concept exhibit higher indicated efficiency through lean limit extension while maintaining the combustion stability. In this study, a unique pre-chamber geometry was tested in a single-cylinder heavy-duty engine at low load lean conditions. The geometry features a narrow throat, which was designed to be packaged inside a commercial diesel injector pocket. The pre-chamber was fueled with methane while the main chamber was supplied with an ethanol/air mixture.

The successful implementation of a clean, quiet, high-performance four-stroke motorcycle engine into an existing snowmobile chassis has been achieved. The snowmobile is easy to start, easy to drive, and environmentally friendly. The following paper describes the conversion process in detail with actual dynamometer and field test data. The vehicle meets the proposed 2010 EPA snowmobile emissions regulations and is quieter than a stock snowmobile. The snowmobile not only addresses environmental concerns, it is economical as well, with an approximate cost of $5874.

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.

As SI engines strive for higher efficiency they are more likely to encounter knock and fuel anti-knock quality, which is currently measured by RON and MON, becomes more important. However, the RON and MON scales are based on primary reference fuels (PRF) - mixtures of iso-octane and n-heptane - whose autoignition chemistry is significantly different from that of practical fuels. Hence RON or MON alone can truly characterize a gasoline for its knock behavior only at their respective test conditions. The same gasoline will match different PRF fuels at different operating conditions. The true anti-knock quality of a fuel is given by the octane index, OI = RON −KS where S = RON − MON, is the sensitivity. K depends on the pressure and temperature evolution in the unburned gas during the engine cycle and hence is different at different operating conditions and is negative in modern engines.

Active regeneration experiments were carried out on a production 2007 Cummins 8.9L ISL engine and associated diesel oxidation catalyst (DOC) and catalyzed particulate filter (CPF) aftertreatment system. The effects of SME biodiesel blends were investigated to determine the particulate matter (PM) oxidation reaction rates for active regeneration. The experimental data from this study will also be used to calibrate the MTU-1D CPF model [1]. The experiments covered a range of CPF inlet temperatures using ULSD, B10, and B20 blends of biodiesel. The majority of the tests were performed at a CPF PM loading of 2.2 g/L with in-cylinder dosing, although 4.1 g/L and a post-turbo dosing injector were also investigated. The PM reaction rate was shown to increase with increasing percent biodiesel in the test fuel as well as increasing CPF temperature.

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.

In this study, the authors investigated the effect of fuel properties on the combustion characteristics by employing methane, methanol, ethanol, and primary reference fuels (PRFs) as the main chamber fuel while using methane for the pre-chamber. Global excess air ratios (λ) from 1.6 to lean limit were tested, while 13% of total fuel energy supplied to the engine was delivered via the pre-chamber. The gaseous methane was injected into the pre-chamber at the gas exchange top-dead-center (TDC). Port fuel injection was tested with both open and closed inlet valves. The pre-chamber assembly was designed to fit into the diesel injector pocket of the base engine, which resulted in a narrow throat diameter of 3.3 mm. The combustion stability limit was set at 5% of the coefficient of variation of gross IMEP, and the knock intensity limit was set at 10 bar. GT-Power software was used to estimate the composition of pre-chamber species and was used in heat release analysis of the two chambers.

Increasing regulatory demand to reduce CO2 emissions has led to an industry focus on electrified vehicles while limiting the development of conventional internal combustion engine (ICE) and hybrid powertrains. Hybrid electric vehicle (HEV) powertrains rely on conventional SI mode IC engines that are optimized for a narrow operating range. Advanced combustion strategies such as Gasoline Compression Ignition (GCI) have been demonstrated by several others including the authors to improve brake thermal efficiency compared to both gasoline SI and Diesel CI modes. Soot and NOx emissions are also reduced significantly by using gasoline instead of diesel in GCI engines due to differences in composition, fuel properties, and reactivity. In this work, an HEV system was proposed utilizing a multi-mode GCI based ICE combined with a HEV components (e-motor, battery, and invertor).

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.

Gasoline-ethanol-methanol (GEM) blends, with constant stoichiometric air-to-fuel ratio (iso-stoichiometric blending rule) and equivalent to binary gasoline-ethanol blends (E2, E5, E10 and E15 in % vol.), were defined to investigate the effect of methanol and combined mixtures of ethanol and methanol when blended with three FACE (Fuels for Advanced Combustion Engines) Gasolines, I, J and A corresponding to RON 70.2, 73.8 and 83.9, respectively, and their corresponding Primary Reference Fuels (PRFs). A Cooperative Fuel Research (CFR) engine was used under Spark Ignition and Homogeneous Charge Compression Ignited modes. An ignition quality tester was utilized in the Compression Ignition mode. One of the promising properties of GEM blends, which are derived using the iso-stoichiometric blending rule, is that they maintain a constant octane number, which has led to the introduction of methanol as a drop-in fuel to supplement bio-derived ethanol.

This paper describes a multi-sensor data set, suitable for testing algorithms to detect and track pedestrians and cyclists, with an autonomous vehicle’s sensor suite. The data set can be used to evaluate the benefit of fused sensing algorithms, and provides ground truth trajectories of pedestrians, cyclists, and other vehicles for objective evaluation of track accuracy. One of the principal bottlenecks for sensing and perception algorithm development is the ability to evaluate tracking algorithms against ground truth data. By ground truth we mean independent knowledge of the position, size, speed, heading, and class of objects of interest in complex operational environments. Our goal was to execute a data collection campaign at an urban test track in which trajectories of moving objects of interest are measured with auxiliary instrumentation, in conjunction with several autonomous vehicles (AV) with a full sensor suite of radar, lidar, and cameras.

The U.S. Renewable Fuel Standard (RFS2) requires an increase in the use of advanced biofuels up to 36 billion gallons by 2022. Longer chain alcohols, in addition to cellulosic ethanol and synthetic biofuels, could be used to meet this demand while adhering to the RFS2 corn-based ethanol limitation. Higher carbon number alcohols can be utilized to improve the energy content, knock resistance, and/or petroleum displacement of gasoline-alcohol blends compared to traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part I of this paper focuses on the development of scenarios by which to compare higher alcohol fuel blends to traditional ethanol blends. It also details the implementation of fuel property prediction methods adapted from literature. Possible combinations of eight alcohols mixed with a gasoline blendstock were calculated and the properties of the theoretical fuel blends were predicted.

Higher carbon number alcohols offer an opportunity to meet the Renewable Fuel Standard (RFS2) and improve the energy content, petroleum displacement, and/or knock resistance of gasoline-alcohol blends from traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part II of this paper builds upon the alcohol selection, fuel implementation scenarios, criteria target values, and property prediction methodologies detailed in Part I. For each scenario, optimization schemes include maximizing energy content, knock resistance, or petroleum displacement. Optimum blend composition is very sensitive to energy content, knock resistance, vapor pressure, and oxygen content criteria target values. Iso-propanol is favored in both scenarios' suitable blends because of its high RON value.

The effect of ethanol blended with three FACE (Fuels for Advanced Combustion Engines) gasolines, I, J and A corresponding to RON 70.3, 71.8 and 83.5, respectively, were compared to PRF70 and PRF84 with the same ethanol concentrations, these being 2%, 5%, 10%, 15% and 20% by volume. A Cooperative Fuel Research (CFR) engine was used to understand the blending effect of ethanol with FACE gasolines and PRFs in spark-ignited and homogeneous charge compression ignited mode. Blending octane numbers (BON) were obtained for both the modes. All the fuels were also tested in an ignition quality tester to obtain Blending Derived Cetane numbers (BDCN). It is shown that fuel composition and octane number are important characteristics of all the base fuels that have a significant impact on octane increase with ethanol. The dependency of octane number for the base fuel on the blending octane number depended on the combustion mode operated.

The blending behavior of ethanol in five different hydrocarbon base fuels with octane numbers of approximately 70 and 84 was examined under Spark-Ignited (SI) and Homogeneous Charge Compression Ignited (HCCI) operating conditions. The Blending octane number (BON) was used to characterize the blending behavior on both a volume and molar basis. Previous studies have shown that the blending behavior of ethanol generally follows several well-established rules. In particular, non-linear blending effects are generally observed on a volume basis (i.e. BON > RON or MON of pure ethanol; 108 and 89, respectively), while linear blending effects are generally observed on a molar basis (i.e. BON = RON or MON of pure ethanol). This work firstly demonstrates that the non-linear volumetric blending effects traditionally observed under SI operating conditions are also observed under HCCI operating conditions.

Blending gasoline with oxygenates like ethanol, MTBE or ETBE has a proven potential to increase the thermodynamic efficiency by enhancing knock resistance. The present research focuses on assessing the capability of a 2- and tert-butanol mixture as a possible alternative to state-of-the-art oxygenates. The butanol mixture was blended into a non-oxygenated reference gasoline with a research octane number (RON) of 97. The butanol blending ratios were 15% and 30% by mass. Both the thermodynamic potential and the impact on emissions were investigated. Tests are performed on a highly boosted single-cylinder gasoline engine with high load capability and a direct injecting fuel system using a solenoid-actuated multi-hole injector. The engine is equipped with both intake and exhaust cam phasers. The engine has been chosen for the fuel investigation, as it represents the SI technology with a strongly increasing market share.