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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.

Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

Conventional diesel fuel has been in the market for decades and used successfully to run diesel engines of all sizes in many applications. In order to reduce emissions and to foster energy source diversity, new fuels such as alternative and renewable, as well as new fuel formulations have entered the market. These include biodiesel, gas-to-liquid, and alternative formulations by states such as California. Performance variations in fuel economy, emissions, and compatibility for these fuels have been evaluated and debated. In some cases contradictory views have surfaced. “Sustainable”, “Renewable”, and “Clean” designations have been interchanged. Adding to the confusion, results from one fuel in one type of engine such as an older heavy-duty engine, is at times compared to that of another type such as a modern light-duty. This study was an attempt to compare the performance of several fuels in an identical environment, using the same engine, for direct comparison.

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).

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 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.

Diesel Cylinder Deactivation (CDA) has been shown in previous work to increase exhaust temperatures, improve fuel efficiency, and reduce engine-out NOx for engine loads up to 3 bar BMEP. The purpose of this study is to determine whether or not the turbocharger needs to be altered when implementing CDA on a diesel engine. This study investigates the effect of CDA on exhaust temperature, fuel efficiency, and turbocharger performance in a 15L heavy-duty diesel engine under low-load (0-3 bar BMEP) steady-state operating conditions. Two calibration strategies were evaluated. First, a “stay-hot” thermal management strategy in which CDA was used to increase exhaust temperature and reduce fuel consumption. Next, a “get-hot” strategy where CDA and elevated idle speed was used to increase exhaust temperature and exhaust enthalpy for rapid aftertreatment warm-up.

Structure-borne inputs to hybrid FEA/SEA models could have significant effects on the model prediction accuracy. The purpose of this work was to obtain the structure-borne noise (SBN) inputs using a simplified transfer path analysis (TPA) and identify the significance of the structure-borne and airborne contributions to the spectator sound power of an engine with enclosure for future modeling references. Force inputs to the enclosure from the engine were obtained and used as inputs to a hybrid engine enclosure model for sound prediction.

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.

Dedicated EGR (D-EGR) is an EGR strategy that uses in-cylinder reformation to improve fuel economy and reduce emissions. The entire exhaust of a sub-group of power cylinders (dedicated cylinders) is routed directly into the intake. These cylinders are run fuel-rich, producing H2 and CO (reformate), with the potential to improve combustion stability, knock tolerance and burn duration. A 2.0 L turbocharged D-EGR engine was packaged into a 2012 Buick Regal and evaluated on drive cycle performance. City and highway fuel consumption were reduced by 13% and 9%, respectively. NOx + NMOG were 31 mg/mile, well below the Tier 2 Bin 5 limit and just outside the Tier 3 Bin 30 limit (30 mg/mile).

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.

Octane appetite of modern engines has changed as engine designs have evolved to meet performance, emissions, fuel economy and other demands. The octane appetite of seven modern vehicles was studied in accordance with the octane index equation OI=RON-KS, where K is an operating condition specific constant and S is the fuel sensitivity (RONMON). Engines with a displacement of 2.0L and below and different combinations of boosting, fuel injection, and compression ratios were tested using a decorrelated RONMON matrix of eight fuels. Power and acceleration performance were used to determine the K values for corresponding operating points. Previous studies have shown that vehicles manufactured up to 20 years ago mostly exhibited negative K values and the fuels with higher RON and higher sensitivity tended to perform better.

Fundamental understanding of the sources of fuel-derived Unburned Hydrocarbon (UHC) emissions in heavy duty diesel engines is a key piece of knowledge that impacts engine combustion system development. Current emissions regulations for hydrocarbons can be difficult to meet in-cylinder and thus after treatment technologies such as oxidation catalysts are typically used, which can be costly. In this work, Computational Fluid Dynamics (CFD) simulations are combined with engine experiments in an effort to build an understanding of hydrocarbon sources. In the experiments, the combustion system design was varied through injector style, injector rate shape, combustion chamber geometry, and calibration, to study the impact on UHC emissions from mixing-controlled diesel combustion.

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.

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.

Gasoline Direct Injection (GDI) engines have been widely adopted by manufacturers in the light-duty market due to their fuel economy benefits. However, several studies have shown that GDI engines generate higher levels of particulate matter (PM) emissions relative to port fuel injected (PFI) engines and diesel engines equipped with optimally functioning diesel particulate filters (DPF). With stringent particle number (PN) regulations being implemented in both, the European Union and China, gasoline particulate filters (GPF) are expected to be widely utilized to control particulate emissions. Currently, evaluating GPF technologies on a vehicle can be challenging due to a limited number of commercially available vehicles that are calibrated for a GPF in the United States as well as the costs associated with vehicle procurement and evaluations utilizing a chassis dynamometer facility.

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.