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The tightening emissions regulations across the globe pose significant challenges to vehicle OEMs. As a result, OEMs are diversifying their powertrain solutions e.g., CNG/Propane based conventional powertrains, BEVs, H2 ICE, FCEV, etc. to meet these regulations. More recently, the ‘CARB Advanced Clean Trucks’ and ‘EPA GHG Phase 3’ regulations are forcing manufacturers to increasingly adopt zero tailpipe emission solutions. While passenger vehicle applications are trending towards a single consensus i.e., BEVs, the heavy-duty on-road applications are challenged with unique requirements of high payload capacity, higher range, lower sales volumes, higher durability, short refueling time, etc. These requirements are driving manufacturers to consider FCEV as an alternative powertrain solution to BEV specifically for higher payload capacity, and range applications.

Vehicle OEM’s for MHD applications are facing significant challenges in meeting the stringent 2027 low-NOx and GHG emissions regulations. To meet such challenges, advanced engine and aftertreatment technologies along with powertrain electrification are being applied to achieve robust solutions. FEV has previously conducted model-based assessments to show the potential of 48V engine and aftertreatment technologies to simultaneously meet GHG and low NOx emission standards. This study focuses on evaluating the full potential of 48V electrification technology through addition of 48V P3 hybrid system to the previously developed 48V advanced engine and aftertreatment technology package. Previously, a model-based approach was utilized for selection and sizing of a 48V system-enabled engine and aftertreatment package for class 6-7 MHD application.

Fuel economy improvement of Class 8 long-haul trucks has been a constant topic of discussion in the commercial vehicle industry due to the significant potential it offers in reducing GHG emissions and operational costs. Among the different vehicle categories in on-road transportation, Class 8 long-haul trucks are a significant contributor to overall GHG emissions. Furthermore, with the upcoming 2027 GHG emission and low-NOx regulations, advanced powertrain technologies will be needed to meet these stringent standards. Connectivity-based powertrain optimization is one such technology that many fleets are adopting to achieve significant fuel savings at a relatively lower technology cost. With advancements in vehicle connectivity technologies for onboard computing and sensing, the full potential of connected vehicles in reducing fuel consumption can be realized through V2X (Vehicle-to-Everything) communication.

Stochastic Preignition (SPI) is an abnormal combustion phenomenon for internal combustion engines (ICE), which has been a significant impact to automotive companies developing high efficiency, turbocharged, direct fuel injection, spark ignited engines. It is becoming clearer what fuel properties are related to the cause of SPI, whether directly with fuel preparation in the cylinder, or mechanisms related to the deposit build-up which contributes to initial and follow-on SPI events. The purpose of this paper is to provide a summary of global market gasoline fuel properties with special attention given to properties and specific compounds from the fuel and fuel additives that can contribute to SPI and the deposit build-up in engines. Based on a review of the global fuel quality, it appears that the fuel quality has not caught up to meet the technology requirements for fuel economy from modern technology engines.

The automotive industry continues to develop new powertrain and vehicle technologies aimed at reducing overall vehicle-level fuel consumption. Specifically, the use of electrified propulsion systems, including electrified and electric drive units (EDU), is expected to play a significant role in helping OEMs meet fleet CO2 reduction targets for 2025 and beyond. The change to vehicles propelled by electrified powertrains leads to a reduction in vehicle noise levels. Despite the overall noise levels being low, the NVH behavior of such vehicles can be objectionable due to the presence of tonal noise coming from electric machines and geartrain components. In order to ensure customer acceptance of electrically propelled vehicles, it is imperative that these NVH challenges are understood and solved. Specifically, this paper discusses the EDU NVH development process. This includes considerations for CAE/test-based development and validation processes to ensure optimal NVH development.

Stochastic Preignition (SPI) is an abnormal combustion event that occurs in a turbocharged engine and can lead to the loss in fuel economy and engine hardware damage, and in turn result in customer dissatisfaction. It is a significant limiting factor on the use and continued downsizing of turbocharged spark ignited direct injection (SIDI) gasoline engines. Understanding and mitigating all the factors that cause and influence the rate and severity of SPI occurrence are of critical importance to the engine’s continued use and fuel economy improvements for future designs. Previous studies have shown that the heavy molecular weight components of the fuel formulations are one factor that influences the rate of SPI from a turbocharged SIDI gasoline engine. All the previous studies have involved analyzing the fuel’s petroleum hydrocarbon chemistry, but not specifically the additives that are put in the fuel to protect and clean the internal components over the life of the engine.

Electrification of heavy-duty trucks has received significant attention in the past year as a result of future regulations in some states. For example, California will require a certain percentage of tractor trailers, delivery trucks and vans sold to be zero emission by 2035. However, the relatively low energy density of batteries in comparison to diesel fuel, as well as the operating profiles of heavy-duty trucks, make the application of electrified powertrain in these applications more challenging. Heavy-duty vehicles can be broadly classified into two main categories; long-haul tractors and vocational vehicles. Long-haul tractors offer limited benefit from electrification due to the majority of operation occurring at constant cruise speeds, long range requirements and the high efficiency provided by the diesel engine.

A gasoline’s chemical composition impacts a vehicle’s sooting tendency and therefore has been the subject of numerous emissions studies. From these studies, several mathematical correlation equations have been developed to predict a gasoline’s sooting tendency in modern spark-ignited internal combustion engine vehicles. This paper reviews the recently developed predictive tool methods and summarizes five years of global market fuel survey data to characterize gasoline sooting tendency trends around the world. Additionally, the paper will evaluate and suggest changes to the predictive methods to improve emissions correlations.

In order to further understand the sequence of events leading to stochastic preignition in a spark-ignition engine, a methodology previously developed by the authors was used to evaluate the propensity of a wide range of fuels to establishing propagating flames under conditions representative of those at which stochastic preignition (SPI) occurs. The fuel matrix included single component hydrocarbons, binary mixtures, and real fuel blends. The propensity of each fuel to establish a flame was correlated to multiple fuel properties and shown to exhibit consistent blending behaviors. No single parameter strongly predicted a fuel’s propensity to establish a flame, while multiple reactivity-based parameters exhibited moderate correlation. A two-stage model of the flame establishment process was developed to interpret and explain these results.

Electrification of heavy-duty trucks has received significant attention in the past year as a result of future regulations in some states. For example, California will require a certain percentage of tractor trailers, delivery trucks and vans sold to be zero emission by 2035. However, the relatively low energy density of batteries in comparison to diesel fuel, as well as the operating profiles of heavy-duty trucks, make the application of electrified powertrain in these applications more challenging. Heavy-duty vehicles can be broadly classified into two main categories; long-haul tractors and vocational vehicles. Long-haul tractors offer limited benefit from electrification due to the majority of operation occurring at constant cruise speeds, long range requirements and the high efficiency provided by the diesel engine.

Stochastic Pre-Ignition (SPI) or Low Speed Pre-Ignition (LSPI) is an abnormal combustion event that can occur during the operation of modern, highly boosted direct-injection gasoline engines. This abnormal combustion event is characterized by an undesired and early start of combustion that is not initiated by the spark plug. Early SPI events can subsequently lead to violent auto-ignitions that are referred to as Mega- or Super-Knock in literature and have the potential to severely damage engines in the field. Numerous studies to analyze impact factors on SPI occurrence and severity have been conducted in recent years. While initial studies have focused strongly on engine oil formulation, calibration and engine design and their respective impact on SPI initiation, the impact of physical and chemical properties of the fuel have also become of interest in recent years.

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.

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.

Stochastic or Low-Speed Preignition (SPI or LSPI) is an undesirable abnormal combustion phenomenon encountered in spark-ignition engines. It is characterized by very early heat release and high cylinder pressure and can cause knock, noise and ultimately engine damage. Much of the focus on mitigating SPI has been directed towards the engine oil formulation, leading to the emergence of the Sequence IX test and second-generation GM dexos® oil requirements. Engine design, calibration and fuels also contribute to the prevalence of SPI. As part of a recently completed research consortium, a series of engine tests were completed to determine the impact of fuel composition on SPI frequency. The fuel blends had varying levels of paraffins, olefins, aromatics and ethanol.

The automotive industry continues to develop new powertrain and vehicle technologies aimed at reducing overall vehicle-level fuel consumption. Specifically, the use of electrified propulsion systems is expected to play an increasingly important role in helping OEM’s meet fleet CO2 reduction targets for 2025 and beyond. This will also include a strong growth in the global demand for electric drive units (EDUs). The change from conventional vehicles to vehicles propelled by EDUs leads to a reduction in overall vehicle exterior and interior noise levels, especially during low-speed vehicle operation. Despite the overall noise levels being low, the NVH behavior of such vehicles can be objectionable due to the presence of tonal noise coming from electric machines and geartrain components as well as relatively high shares of road/wind noise. In order to ensure customer acceptance of electrically propelled vehicles, it is imperative that these NVH challenges are understood and solved.

A novel approach to the Integration of Turbocompounding/WHR, Electrification and Supercharging technologies (ITES) to reduce fuel consumption in a medium heavy-duty diesel engine was previously published by FEV. This paper describes a modified approach to ITES to reduce fuel consumption on a heavy-duty diesel engine applied in a Class 8 tractor. The original implementation of the ITES incorporated a turbocompound turbine as the means for waste heat recovery. In this new approach, the turbocompound unit connected to the sun gear of the planetary gear set has been replaced by an organic Rankine cycle (ORC) turbine expander. The secondary compressor and the electric motor-generator are connected to the ring gear and the carrier gear respectively. The ITES unit is equipped with dry clutch and band brake allowing flexibility in mechanical and electrical integration of the ORC expander, secondary compressor and electric motor-generator to the engine.

The occurrence of abnormal combustion events leading to high peak pressures and severe knock can be considered to be one of the main challenges for modern turbocharged, direct-injected gasoline engines. These abnormal combustion events have been referred to as Stochastic Pre-Ignition (SPI) or Low-Speed Pre-Ignition (LSPI). The events are characterized by an undesired, early start of combustion of the cylinder charge which occurs before or in parallel to the intended flame kernel development from the spark plug. Early SPI events can subsequently lead to violent auto-ignitions that are often referred to as Mega- or Super-Knock. These heavy knock events lead to strong pressure oscillations which can destroy production engines within a few occurrences. SPI occurs mainly at low engine speed and high engine load, thus limiting the engine operating area that is in particular important to achieve good drivability in downsized engines.

The Particulate Matter Index (PMI) is a helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and OEMs as a metric to understand the gasoline fuels impact on both sooting found on engine hardware and vehicle out emissions. This paper will explore a new method that could be used to give indication of the sooting tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), and provide the detailed equation in its initial form. In addition, the PEI will be shown to have a good correlation agreement to PMI. The paper will then give a detailed explanation of the data used to develop it. Initial vehicle PM/PN data will also be presented that shows correlations of the indices to the vehicle response.

The goal of this study was to generate exhaust fast gas data that could be used to identify phenomena that occur before, during, and after stochastic preignition (SPI), also called low-speed preignition (LSPI), events. Crank angle resolved measurement of exhaust hydrocarbons, NO, CO, and CO2 was performed under engine conditions prone to these events. Fuels and engine operating strategies were varied in an attempt to understand similarities and differences in SPI-related behavior that may occur between them. Several different uncommon (typically occurring in less than 1% of engine cycles) features of the fast gas data were identified, and the correlations between them and SPI events were explored. Although the thresholds used to define and identify these observations were arbitrary, they provided a practical means of identifying behavior in the fast gas data and correlating it to SPI occurrence.

In this multi-phase study, fuel and lubricant effects on stochastic preignition (SPI) were examined. First, the behavior of fuels for which SPI data had previously been collected were characterized in terms of their combustion and emissions behavior, and correlations between these characteristics and their SPI behavior were examined. Second, new SPI data was collected for a matrix of fuels that was constructed to test and confirm hypotheses that resulted from interpretation of the earlier data in the study and from data in open literature. Specifically, the extent to which the presence of heavy components in the fuel affected SPI propensity, and the extent to which flame initiation propensity affected SPI propensity, were examined. Finally, the interaction of fuels with lubricants expected to exhibit a range of SPI propensities was examined.