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This paper forms the third of a series and presents results obtained during the testing and development phase of a dedicated range extender engine designed for use in a compact class vehicle. The first paper in this series used real world drive logs to identify usage patterns of such vehicles and a driveline model was used to determine the power output requirements of a range extender engine for this application. The second paper presented the results of a design study. Key attributes for the engine were identified, these being minimum package volume, low weight, low cost, and good NVH. A description of the selection process for identifying the appropriate engine technology to satisfy these attributes was given and the resulting design highlights were described. The paper concluded with a presentation of the resulting specification and design highlights of the engine. This paper will present the resulting engine performance characteristics.

The diesel engine can be an effective solution to meet future greenhouse gas and fuel economy standards, especially for larger segment vehicles. However, a key challenge facing the diesel is the upcoming LEV III and Tier 3 emission standards which will require significant reductions in hydrocarbon (HC) and oxides of nitrogen (NOx) emissions. The challenge stems from the fact that diesel exhaust temperatures are much lower than gasoline engines, so the time required to achieve effective emissions control after a cold-start with typical aftertreatment devices is considerably longer. To address this challenge, a novel diesel cold-start emission control strategy was investigated on a 2L class diesel engine. This strategy combines several technologies to reduce tailpipe HC and NOx emissions before the start of the second hill of the FTP75. The technologies include both engine tuning and aftertreatment changes.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

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.

The tradeoff between NOx emissions and combustion instability in an engine operating in the dual-fuel Reactivity Controlled Compression Ignition (RCCI) combustion mode was investigated using a combination of engine experiments and detailed CFD modeling. Experiments were performed on a single cylinder version of a General Motors/Fiat JTD 1.9L four-cylinder diesel engine. Gasoline was injected far upstream of the intake valve using an air assisted injector and fuel vaporization system and diesel was injected directly into the cylinder using a common rail injector. The timing of the diesel injection was swept from −70° ATDC to −20° ATDC while the gasoline percentage was adjusted to hold the average combustion phasing (CA50) and load (IMEPg) constant at 0.5° ATDC and 7 bar, respectively. At each operating point the variation in IMEP, peak PRR, and CA50 was calculated from the measured cylinder pressure trace and NOx, CO, soot and UHC were recorded.

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

Two methods of sampling exhaust emissions are typically used for characterizing emissions from diesel engines: total dilution which uses a constant volume sampling (CVS) system and partial flow dilution which relies on proportionally diluting a small part from the main exhaust stream. The CVS dilutes the entire exhaust flow to a constant volumetric flowrate which allows for proportional sampling of the exhaust species during transient engine operation. For partial dilution sampling during transient engine operation, obtaining a proportional sample is more rigorous and dilution of the extracted sample must be continuously changed throughout the cycle in order for the extracted sample flowrate to be proportional to the continuously changing exhaust flow. Typically, regulated emissions measured using both methods for an engine platform have shown good correlation. The focus for this work was on the experimental investigation of the two methods for the measurement of unregulated species.

This paper presents the results of engine and vehicle simulation modeling for a wide variety of individual technologies and technology packages applied to two medium-duty vocational vehicles. Simulation modeling was first conducted on one diesel and two gasoline medium-duty engines. Engine technologies were then applied to the baseline engines. The resulting fuel consumption maps were run over a range of vehicle duty cycles and payloads in the vehicle simulation model. Results were reported for both individual engine technologies and combinations or packages of technologies. Two vehicles, a Kenworth T270 box delivery truck and a Ford F-650 tow truck were evaluated. Once the baseline vehicle models were developed, vehicle technologies were added. As with the medium-duty engines, vehicle simulation results were reported for both individual technologies and for combinations. Vehicle technologies were evaluated only with the baseline 2019 diesel medium-duty engine.

Advanced combustion strategies used to improve efficiency, emissions, and performance in internal combustion engines (IC) alter the chemical composition of engine-out emissions. The characterization of exhaust chemistry from advanced IC engines requires an analytical system capable of measuring a wide range of compounds. For many years, the widely accepted Coordinating Research Council (CRC) Auto/Oil procedure[1,2] has been used to quantify hydrocarbon compounds between C1 and C12 from dilute engine exhaust in Tedlar polyvinyl fluoride (PVF) bags. Hydrocarbons greater than C12+ present the greatest challenge for identification in diesel exhaust. Above C12, PVF bags risk losing the higher molecular weight compounds due to adsorption to the walls of the bag or by condensation of the heavier compounds. This paper describes two specialized exhaust gas sampling and analytical systems capable of analyzing the mid-range (C10 - C24) and the high range (C24+) hydrocarbon in exhaust.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode.

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.

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.

A two-phase study was performed to establish a standard diesel exhaust composition which could be used in the future development of light-duty diesel exhaust aftertreatment. In the first phase, a literature review created a database of diesel engine-out emissions. The database consisted chiefly of data from heavy-duty diesel engines; therefore, the need for an emission testing program for light- and medium-duty engines was identified. A second phase was conducted to provide additional light-duty vehicle emissions data from current technology vehicles. Engine-out diesel exhaust from four 2004 model light-duty vehicles with a variety of engine displacements was collected and analyzed. Each vehicle was evaluated using five steady-state engine operating conditions and two transient test cycles (the Federal Test Procedure and the US06). Regulated emissions were measured along with speciation of both volatile and semi-volatile components of the hydrocarbons.

A solid particle number measurement system (SPNMS) was developed using a catalytic stripper (CS) technology instead of an evaporation tube (ET). The ET is used in commercially available systems, compliant with the Particle Measurement Program (PMP) protocol developed for European Union (EU) solid particle number regulations. The catalytic stripper consists of a small core of a diesel exhaust oxidation catalyst. The SPNMS/CS met all performance requirements under the PMP protocol. It showed a much better performance in removing large volatile tetracontane particles down to a size well below the PMP lower cut-size of 23 nm, compared to a SPNMS equipped with an ET instead of a CS. The SPNMS/CS also showed a similar performance to a commercially available system when used on a gasoline direct injection (GDI) engine exhaust.

A dynamometer test methodology was developed for evaluation of HMMWV axle efficiency with hypoid gearsets, comparing those having various degrees of superfinish versus new production axles as well as used axles removed at depot maintenance. To ensure real-world applicability, a HMMWV variant vehicle model was created and simulated over a peacetime vehicle duty cycle, which was developed to represent a mission scenario. In addition, tractive effort calculations were then used to determine the maximum input torques. The drive cycle developed above was modified into two different profiles having varying degrees of torque variability to determine if the degree of variability would have a significant influence on efficiency in the transient dynamometer tests. Additionally, steady state efficiency performance is measured at four input pinion speeds from 700-2500 rpm, five input torques from 50 - 400 N⋅m, and two sump temperatures, 80°C and 110°C.

The diesel engine can be an effective solution to meet future greenhouse gas and fuel economy standards, especially for larger segment vehicles. However, a key challenge facing the diesel is the upcoming LEV III emissions standard which will require significant reductions of hydrocarbon (HC) and oxides of nitrogen (NOx) from current levels. The challenge stems from the fact that diesel exhaust temperatures are much lower than gasoline engines so the time required to achieve effective emissions control with current aftertreatment devices is considerably longer. The objective of this study was to determine the potential of a novel diesel cold-start emissions control strategy for achieving LEV III emissions. The strategy combines several technologies to reduce HC and NOx emissions before the start of the second hill of the FTP75.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.