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A spark-assist homogeneous charge compression ignition (SA-HCCI) operating strategy is presented here that allows for stoichiometric combustion from 1000-3000 rpm, and at loads as high as 750 kPa net IMEP. A single cylinder gasoline engine equipped with direct fuel injection and fully variable hydraulic valve actuation (HVA) is used for this experimental study. The HVA system enables negative valve overlap (NVO) valve timing for hot internal EGR. Spark-assist stabilizes combustion over a wide range of engine speeds and loads, and allows for stoichiometric operation at all conditions. Characteristics of both spark-ignited combustion and HCCI are present during the SA-HCCI operating mode, with combustion analysis showing a distinctive spark ignited phase of combustion, followed by a much more rapid HCCI combustion phase. At high load, the maximum cylinder pressure rise rate is controlled by a combination of spark timing and retarding the intake valve closing angle.

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Lignin by-products from biorefineries has the potential to provide a low-cost alternative to petroleum-based precursors to manufacture carbon fiber, which can be combined with a binding matrix to produce a structural material with much greater specific strength and specific stiffness than conventional materials such as steel and aluminum. The market for carbon fiber is universally projected to grow exponentially to fill the needs of clean energy technologies such as wind turbines and to improve the fuel economies in vehicles through lightweighting. In addition to cellulosic biofuel production, lignin-based carbon fiber production coupled with biorefineries may provide $2,400 to $3,600 added value dry Mg−1 of biomass for vehicle applications. Compared to producing ethanol alone, the addition of lignin-derived carbon fiber could increase biorefinery gross revenue by 30% to 300%.

A commercial three-way catalyst (TWC) was evaluated for ammonia (NH3) generation on a 2.0-liter BMW lean burn gasoline direct injection engine as a component in a passive ammonia selective catalytic reduction (SCR) system. The passive NH3 SCR system is a potential low cost approach for controlling nitrogen oxides (NOX) emissions from lean burn gasoline engines. In this system, NH3 is generated over a close-coupled TWC during periodic slightly rich engine operation and subsequently stored on an underfloor SCR catalyst. Upon switching to lean, NOX passes through the TWC and is reduced by the stored NH3 on the SCR catalyst. NH3 generation was evaluated at different air-fuel equivalence ratios at multiple engine speed and load conditions. Near complete conversion of NOX to NH3 was achieved at λ=0.96 for nearly all conditions studied. At the λ=0.96 condition, HC emissions were relatively minimal, but CO emissions were significant.

Two hybrid powertrain configurations, including parallel and series hybrids, were simulated for fuel economy, component energy loss, and emissions control in Class 8 trucks over both city and highway driving conditions. A comprehensive set of component models describing engine fuel consumption, emissions control, battery energy, and accessory power demand interactions was developed and integrated with the simulated hybrid trucks to identify heavy-duty (HD) hybrid technology barriers. The results show that series hybrid is absolutely negative for fuel-economy improvement of long-haul trucks due to an efficiency penalty associated with the dual-step conversions of energy (i.e. mechanical to electric to mechanical).

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.

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.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Accurately predicting the fuel savings that can be achieved with the implementation of various technologies developed for fuel efficiency can be very challenging, particularly when considering combinations of technologies. Differences in the usage of highway vehicles can strongly influence the benefits realized with any given technology, which makes generalizations about fuel savings inappropriate for different vehicle applications. A model has been developed to estimate the potential for reducing fuel consumption when advanced efficiency technologies, or combinations of these technologies, are employed on highway vehicles, particularly medium- and heavy-duty trucks. The approach is based on a tractive energy analysis applied to drive cycles representative of the vehicle usage, and the analysis specifically accounts for individual energy loss factors that characterize the technologies of interest.

The U.S. Department of Energy's Office of Energy Efficiency & Renewable Energy initiated a study that conducted coastdown testing and chassis dynamometer testing of three vehicles, each at multiple test weights, in an effort to determine the impact of a vehicle's mass on road load force and energy consumption. The testing and analysis also investigated the sensitivity of the vehicle's powertrain architecture (i.e., conventional internal combustion powertrain, hybrid electric, or all-electric) on the magnitude of the impact of vehicle mass. The three vehicles used in testing are a 2012 Ford Fusion V6, a 2012 Ford Fusion Hybrid, and a 2011 Nissan Leaf. Testing included coastdown testing on a test track to determine the drag forces and road load at each test weight for each vehicle. Many quality measures were used to ensure only mass variations impact the road load measurements.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

This study investigated the effects of soybean- and coconut-derived biodiesel fuels on combustion characteristics in a 1.7-liter direct injection, common rail diesel engine. Five sets of fuels were studied: 2007 ultra low sulfur diesel (ULSD), 5% and 20% volumetric blends of soybean biodiesel with ULSD (soybean B5 and B20), and 5% and 20% volumetric blends of coconut biodiesel with ULSD (coconut B5 and B20). In conventional diesel combustion mode, particulate matter (PM) and nitrogen oxides (NOx) emissions were similar for all fuels studied except soybean B20. Soybean B20 produced the lowest PM but the highest NOx emissions. Compared with conventional diesel combustion mode, high efficiency clean combustion (HECC) mode, achieved by increased EGR and combustion phasing, significantly reduced both PM and NOx emissions for all fuels studied at the expense of higher hydrocarbon (HC) and carbon monoxide (CO) emissions and an increase in fuel consumption (less than 4%).

Living in the era of rising environmental sensibility and increasing gasoline prices, the development of a new environmentally friendly generation of vehicles becomes a necessity. Hybrid electric vehicles are one means of increasing propulsion system efficiency and decreasing pollutant emissions. In this paper, the series-parallel power-split configuration for Michigan Technological University's FutureTruck is analyzed. Mathematical equations that describe the hybrid power-split transmission are derived. The vehicle's differential equations of motion are developed and the system's need for a controller is shown. The engine's brake power and brake specific fuel consumption, as a function of its speed and throttle position, are experimentally determined. A control strategy is proposed to achieve fuel efficient engine operation. The developed control strategy has been implemented in a vehicle simulation and in the test vehicle.

Greenhouse gas regulations and global economic growth are expected to drive a future demand shift towards diesel fuel in the transportation sector. This may create a market opportunity for cost-effective fuels in the light distillate range if they can be burned as efficiently and cleanly as diesel fuel. In this study, the emission performance of a low cetane number, low research octane number naphtha (CN 34, RON 56) was examined on a production 6-cylinder heavy-duty on-highway truck engine and aftertreatment system. Using only production hardware, both the engine-out and tailpipe emissions were examined during the heavy-duty emission testing cycles using naphtha and ultra-low-sulfur diesel (ULSD) fuels. Without any modifications to the hardware and software, the tailpipe emissions were comparable when using either naphtha or ULSD on the heavy duty test cycles.

This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller.

The increased availability of natural gas (NG) in the United States (US) and its relatively low cost versus diesel fuel has increased interest in the conversion of medium duty (MD) and heavy duty (HD) engines to NG fueled combustion systems. The aim for development for these NG engines is to realize fuel cost savings and increase operating range while reduce harmful emissions and maintaining durability. Traditionally, port-fuel injection (PFI) or premixed NG spark-ignited (SI) combustion systems have been used for light duty LD, and MD engines with widespread use in the US and Europe [1]. However, this technology exhibits poor thermal efficiency and is load limited due to knock phenomenon that has prohibited its use for HD engines. Spark Ignited Direct Injection (SIDI) can be used to create a partially stratified combustion (PSC) mixture of NG and air during the compression stroke.

Technologies that provide potential for significant improvements in engine efficiency include, engine downsizing/downspeeding (enabled by advanced boosting systems such as an electrically driven compressor), waste heat recovery through turbocompounding or organic Rankine cycle and 48 V mild hybridization. FEV’s Integrated Turbocompounding/Waste Heat Recovery (WHR), Electrification and Supercharging (FEV-ITES) is a novel approach for integration of these technologies in a single unit. This approach provides a reduced cost, reduced space claim and an increase in engine efficiency, when compared to the independent integration of each of these technologies. This approach is enabled through the application of a planetary gear system. Specifically, a secondary compressor is connected to the ring gear, a turbocompounding turbine or organic Rankine cycle (ORC) expander is connected to the sun gear, and an electric motor/generator is connected to the carrier gear.

It is advantageous to increase the specific power output of diesel engines and to operate them at higher load for a greater portion of a driving cycle to achieve better thermal efficiency and thus reduce vehicle fuel consumption. Such operation is limited by excessive smoke formation at retarded injection timing and high rates of cylinder pressure rise at more advanced timing. Given this window of operation, it is desired to understand the influence of fuel properties such that optimum combustion performance and emissions can be retained over the range of fuels commonly available in the marketplace. Data are examined from a direct-injection single-cylinder research engine for eight common diesel fuels including soy-based biodiesel blends at two high load operating points with no exhaust gas recirculation (EGR) and at a moderate load with four levels of EGR.