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We assessed the engine-out emissions of an ultra-low sulfur diesel (ULSD) and a neat hydrogenated vegetable oil (HVO) from a light-duty diesel truck equipped with common rail direct injection. The vehicle was tested at least twice on each fuel using the LA-92 drive cycle and at steady-state conditions at 30 mph and 50 mph at different loads. Results showed reductions in the engine-out total hydrocarbon (THC), carbon monoxide (CO), nitrogen oxide (NOx), and particulate emissions with HVO. The reductions in soot mass, solid particle number, and particulate matter (PM) mass emissions with HVO were due to the absence of aromatic and polyaromatic hydrocarbon compounds, as well as sulfur species, which are known precursors of soot formation. Volumetric fuel economy, calculated based on the carbon balance method, did not show statistically significant differences between the fuels.

A quasi-dimensional model for a direct injection diesel engine was developed based on experiments at Sandia National Laboratory. The Sandia researchers obtained images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation. Dec [1] combined all of the available images to develop a conceptual diesel combustion model to describe diesel combustion from the start of injection up to the quasi-steady form of the jet. The end of injection behavior was left undescribed in this conceptual model because no clear image was available due to the chaotic behavior of diesel combustion. A conceptual end-of-injection diesel combustion behavior model was developed to capture diesel combustion throughout its life span. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations.

We assessed gaseous and particulate matter (PM) emissions from a current technology stoichiometric natural gas waste hauler equipped with a 2011 model year 8.9L Cummins Westport ISL-G engine with cooled exhaust gas recirculation (EGR) and three-way catalyst (TWC). Testing was performed on five fuels with varying Wobbe and methane numbers over the William H. Martin Refuse Truck Cycle. The results showed lower nitrogen oxide (NOx) emissions for the low methane fuels (i.e., natural gas fuels with a relatively low methane content) for the transport and curbside cycles. Total hydrocarbon (THC) and methane (CH4) emissions did not show any consistent fuel trends. Non-methane hydrocarbon (NMHC) emissions showed a trend of higher emissions for the fuels containing higher levels of NMHCs. Carbon monoxide (CO) emissions showed a trend of higher emissions for the low methane fuels.

Emissions, fuel economy, and performance are determined over a light and a heavy driving cycle designed to represent the vehicles in-use driving patterns. The vehicles are 2010 class 8 Freightliner tractor trucks equipped with Cummins engines with Selective Catalytic Reduction and Diesel Particulate Filter emission control systems. The hybrid has lower carbon dioxide emissions, better fuel economy, and nitrogen oxide emissions statistically the same as the conventional. The CO emissions are well below the standards for both vehicles, but they are higher from the hybrid. The higher CO emissions for the hybrid are primarily related to the cooling of the Diesel Oxidation Catalyst (DOC) during the standard 20 minute key-off soak between repeats of the driving cycles. With a 1 minute key-off soak the CO emissions from the hybrid are negative.

A large amount of the heat generated during the engine combustion process is lost to the coolant system through the surrounding metal parts. Therefore, there is a potential to improve the overall cycle efficiency by reducing the amount of heat transfer from the engine. In this paper, a Computational Fluid Dynamics (CFD) tool has been used to evaluate the effects of a number of design and operating variables on total heat loss from an engine to the coolant system. These parameters include injection characteristics and orientation, shape of the piston bowl, percentage of EGR and material property of the combustion chamber. Comprehensive analyses have been presented to show the efficient use of the heat retained in the combustion chamber and its contribution to improve thermal efficiency of the engine. Finally, changes in design and operating parameters have been suggested based on the analytical results to improve heat loss reduction from an engine.

Urban air quality in California can have a large impact on the state's economy, natural and managed ecosystems, and human health and mortality. The use of alternative, low-carbon fuels is considered to be an effective measure to meet strict emissions regulations of particulate matter (PM) and oxides of nitrogen (NOx). Natural gas may be a potential alternative to conventional liquid fuels for use in automotive internal combustion engines, and can be used in fulfilling these requirements. The primary objective of this study is to evaluate the impact of varying natural gas composition on the exhaust emissions from a transit bus equipped with a 2003 Cummins C Gas Plus, lean-burn, spark-ignited natural gas engine and an oxidation catalyst while operating on the Central Business District (CBD) cycle on a chassis dynamometer.

This presentation will cover an overview of challenges and key discussion points for advanced electric motor and drive testing . Voiko will visit some examples of how D&V approaches these issues and also some suggestions for how the industry can view these intriguing problems as opportunities. The presentation will also delve into current testing developments that involve resolver, load bank and power measurement devices by highlighting solutions in the market today. There will also be a cursory look into the future of electric motor testing and what we can expect in the near term. Presenter Voiko Loukanov, D&V Electronics Limited

EmiSense Technologies, LLC (www.emisense.com) is commercializing its electronic particulate matter (PM) sensor that is based on technology developed at the University of Texas at Austin (UT). To demonstrate the capability of this sensor for real-time PM measurements and on board diagnostics (OBD) for failure detection of diesel particle filters (DPF), independent measurements were performed to characterize the engine PM emissions and to compare with the PM sensor response. Computational fluid dynamics (CFD) modeling was performed to characterize the hydrodynamics of the sensor's housing and to develop an improved PM sensor housing with reproducible hydrodynamics and an internal baffle to minimize orientation effects. PM sensors with the improved housing were evaluated in the truck exhaust of a heavy duty (HD) diesel engine tested on-road and on a chassis dynamometer at the University of California, Riverside (UCR) using their Mobile Emissions Laboratory (MEL).

This paper describes a diesel engine lean NOx trap (LNT) regeneration air to fuel ratio (AFR) control system using a nonlinear model predictive control (NMPC) technique for simultaneous regeneration fuel penalty and overall tailpipe-out NOx reductions. A physics-based and experimentally validated nonlinear LNT dynamic model was employed to construct the NMPC control algorithm, which dictates the AFR value during regenerations. Different choices of NMPC cost function were examined in terms of the impact on fuel penalty and total tailpipe NOx slip amount. The cost function to achieve the best tradeoff between fuel penalty and tailpipe-out NOx was selected based on physical insights into the LNT system NOx and oxygen storage dynamics. The NMPC regeneration AFR control system was evaluated on a vehicle simulator cX-Emissions1 with a 1.9L diesel engine model through the FTP75 driving cycle.

An electronic particulate matter sensor (EPMS) developed at the University of Texas was used to characterize exhaust gases from a single-cylinder diesel engine and a light-duty diesel vehicle. Measurements were made during transient tip-in events with multiple sensor configurations in the single-cylinder engine. The sensor was operated in two modes: one with the electric field energized, and the other with no electric field present. In each mode, different characteristic signals were produced in response to a tip-in event, highlighting the two primary mechanisms of sensor operation. The sensor responded to both the natural charge of the particulate matter (PM) emitted from the engine, and was also found to create a signal by charging neutral particles. The characteristics of the two mechanisms of operation are discussed as well as their implications on the placement and operation of the sensor.

Alternative combustion modes such as homogeneous charge compression ignition (HCCI) and low temperature combustion (LTC) have shown very promising engine-out emissions. However, these combustion modes are close to the combustion stability boundaries and very sensitive to in-cylinder condition variations. Thus, transient control of engines operating in alternative combustion modes are very challenging compared with control of engines with conventional combustion mode only. This paper presents some advanced air-path control and estimation techniques/practice for multiple and alternative combustion mode engine transient operation. Based on the mean-value engine dynamic models, robust controllers can be designed to track the desired air-path performance variables to ensure desirable combustion during transient operation.

This paper describes an in-cylinder lean-rich combustion (no-post-injection for rich) switching control approach for modern diesel engines equipped with exhaust-treatment systems. No-post-injection rich combustion is desirable for regeneration of engine exhaust-treatment systems thanks to its less fuel penalty compared with regeneration approaches using post-injections and / or in-exhaust injections. However, for vehicle applications, it is desirable to have driver-transparent exhaust-treatment system regenerations, which challenge the in-cylinder rich-lean combustion transitions. In this paper, a nonlinear in-cylinder condition control system combined with in-cylinder condition guided fueling control functions were developed to achieve smooth in-cylinder lean-rich switching control at both steady-state and transient operation. The performance of the control system is evaluated on a modern light-duty diesel engine (G9T600).

This paper presents the latest developments in the design and performance of an electronic particulate matter (PM) sensor developed at The University of Texas at Austin (UT) and suitable, with further development, for applications in active engine control of PM emissions. The sensor detects the carbonaceous mass component of PM in the exhaust and has a time-resolution less than 20 (ms), allowing PM levels to be quantified for engine transients. Sample measurements made with the sensor in the exhaust of a single-cylinder light duty diesel engine are presented for both steady-state and transient operations: a steady-state correlation with gravimetric filter measurements is presented, and the sensor response to rapid increases in PM emission during engine transients is shown for several different tip-in (momentary increases in fuel delivery) conditions.

The basic process of spark ignition in engines has changed little over the more than 100 years since its first application. The rapid evolution of several advanced engine concepts and the refinement of existing engine designs, especially applications of power boost technology, have led to a renewed interest in advanced spark ignition concepts. The increasingly large rates of in-cylinder dilution via EGR and ultra-lean operation, combined with increases in boost pressures are placing new demands on spark ignition systems. The challenge is to achieve strong and consistent ignition of the in-cylinder mixture in every cycle, to meet performance and emissions goals while maintaining or improving the durability of ignitor. The application of railplug ignition to some of these engine systems is seen as a potential alternative to conventional spark ignition systems that may lead to improved ignition performance.

A new diesel engine system adopting alternative combustion with rich and near rich combustion, and an airflow-dominant control system for precise combustion control was used with a 4-way catalyst system with LNT (lean NOx trap) to achieve Tier II Bin 5 on a 2.2L TDI diesel engine. The study included catalyst temperature control, NOx regeneration, desulfation, and PM oxidation with and without post injection. Using a mass-produced lean burn gasoline LNT with 60,000 mile equivalent aging, compliance to Tier II Bin 5 emissions was confirmed for the US06 and FTP75 test cycles with low NVH, minor fuel penalty and smooth transient operation.

An airflow-dominant control system was developed to provide precise engine and exhaust treatment control with low air fuel ratio alternative combustion. The main elements of the control logic include a real-time state observer for in-cylinder oxygen mass estimation, a simplified packaging scheme for all air-handling and fueling parameters, a finite state machine for control mode switching, combustion control models to maintain robust alternative combustion during transients, and smooth rich/lean switching during lean NOx trap (LNT) regeneration without post injection. The control logic was evaluated on a passenger car equipped with a 4-way catalyst system with LNT and was instrumental in achieving US Tier II Bin 5 emission targets with good drivability and low NVH.

Combustion chamber pressure measurement in engines via a passage is an old technique that is still widely used in engine research. This paper presents improved passage designs for an off-set electrode spark plug designed to accept a pressure transducer. The spark plug studied was the Champion model 304-063A. Two acoustic models were developed to compute the resonance characteristics. The new designs have a resonance frequency in a range higher than the fundamental frequency expected from knock so that the signal can be lowpass filtered to remove the resonance and not interfere with pressure signal components associated with combustion phenomena. Engine experiments verified the spark plug resonance behavior. For the baseline engine operating condition approximately 50 of 100 cycles had visible passage resonance in the measured pressure traces, at an average frequency of 8.03 kHz.

This paper describes a hybrid robust nonlinear control approach for modern diesel engines running low temperature combustion and conventional diesel combustion modes. Using alternative combustion modes has become a promising approach to reduce engine emissions. However, due to very different in-cylinder conditions and fueling parameters for different combustion modes, control of engines operating multiple combustion modes is very challenging. It becomes difficult for conventional calibration / mapping based approaches to produce satisfactory results in terms of engine torque responses and emissions. Advanced control techniques are then demanded to accomplish the tasks. An innovative hybrid control system is designed to track different key engine operating variables at different combustion modes as well as avoid singularity which is inherent for turbocharged diesel engines running multiple combustion modes.

This paper describes algorithms that can recognize and track the engine crankshaft position for arbitrary cam- and crank-shaft tooth wheel patterns in both steady-state and transient operating conditions. Crankshaft position tracking resolution is adjustable to accommodate different application requirements. The instantaneous crankshaft position information provided by the position tracking module form the basis for crankshaft angle domain (CAD) engine control and measurement functions such as precise injection / ignition controls and on-line cylinder pressure CAD analyses. The algorithms described make reconfiguration of the tracking module for different and arbitrary cam- and crank-shaft tooth wheel patterns very easy, which is valuable especially for prototyping engine control systems. The effectiveness of the algorithms is shown using test engines with different cam and crank signal patterns.

This paper explores the possibility of on-board fuel classification for fuel property adaptive compression-ignition engine control system. The fuel classifier is designed to on-board classify the fuel that a diesel engine is running, including alternative and renewable fuels such as bio-diesel. Based on this classification, the key fuel properties are provided to the engine control system for optimal control of in-cylinder combustion and exhaust treatment system management with respect to the fuel. The fuel classifier employs engine input-output response characteristics measured from standard engine sensors to classify the fuel. For proof-of-concept purposes, engine input-output responses were measured for three different fuels at three different engine operating conditions. Two neural-network-based fuel classifiers were developed for different classification scenarios. Of the three engine operating conditions tested, two conditions were selected for the fuel classifier to be active.