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The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

A gasoline’s distillation profile is directly related to its hydrocarbon composition and the volatility (boiling points) of those hydrocarbons. Generally, the volatility profiles of U.S. market fuels are characterized using a very simple, low theoretical plate distillation separation, detailed in the ASTM D86 test method. Because of the physical chemistry properties of some compounds in gasoline, this simple still or retort distillation has some limitations: separating azeotropes, isomers, and heavier hydrocarbons. Chemists generally rely on chromatographic separations when more detailed and precise results are needed. High-boiling aromatic compounds are the primary source of particulate emissions from spark ignited (SI), internal combustion engines (ICE), hence a detailed understanding and high-resolution separation of these heavy compounds is needed.

Designing power electronics to operate in harsh vehicle environments while meeting packaging requirements such as mass, volume, and power density, creates several challenges for their mechanical design. In this work, we concentrate on the power inverter module (PIM) which converts high voltage (HV) DC voltage power from the HV battery to AC power to drive the motor. The PIM main components are the power module, gate drive and the bulk capacitor. The sizing and selection of the bulk capacitor and power module depend on performance criteria and drive profiles in addition to operating temperatures. In this work, we share the main challenges of packaging components within the inverter. We then discuss best practices to ensure a robust mechanical design which meets inverter durability and reliability targets for an electric vehicle application. The main challenges discussed are bulk capacitor thermals, sealing, and Silicon Carbide (SiC) packaging.

Battery Electric Vehicles (BEVs) are becoming more competitive day by day to achieve maximum peak power and energy requirement. This poses challenges to the design of Thermal Interface Material (TIM) which maintains the cell temperature and ensure retention of cell and prevent electrolyte leak under different crash loads. TIM can be in the form of adhesives, gels, gap fillers. In this paper, TIM is considered as structural, and requires design balance with respect to thermal and mechanical requirements. Improving structural strength of TIM will have negative impact on its thermal conductivity; hence due care needs to be taken to determine optimal strength that meets both structural and thermal performance. During various crash conditions, due to large inertial force of cell and module assembly, TIM is undertaking significant loads on tensile and shear directions. LS-DYNA® is used as simulation solver for performing crash loading conditions and evaluate structural integrity of TIM.

Several predictive equations based on the chemical composition of gasoline have been shown to estimate the particulate emissions of light-duty, internal combustion engine (ICE) powered vehicles and are reviewed in this paper. Improvements to one of them, the PEISimDis equation are detailed herein. The PEISimDis predictive equation was developed by General Motor’s researchers in 2022 based on two laboratory gas chromatography (GC) analyses; Simulated Distillation (SimDis), ASTM D7096 and Detailed Hydrocarbon Analysis (DHA), ASTM D6730. The DHA method is a gas chromatography mass spectroscopy (GC/MS) methodology and provides the detailed speciation of the hundreds of hydrocarbon species within gasoline. A DHA’s aromatic species from carbon group seven through ten plus (C7 – C10+) can be used to calculate a Particulate Evaluation Index (PEI) of a gasoline, however this technique takes many hours to derive because of its long chromatography analysis time.

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.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

Gasoline Particulate Filters (GPF) are widely employed in exhaust aftertreatment systems of gasoline engines to meet the stringent particulate emissions requirements of Euro6 and China6 standard. While providing an effective filtration of particles, the GPF increases the engine backpressure as a penalty due to accumulation of soot. To clean the accumulated soot, periodical burning of soot is achieved by the onboard control models and lot of effort is spent on calibrating the same. In order to understand pressure drop behavior across GPF, detailed pressure drop measurements were conducted at clean, soot and ash loaded conditions at engine dynamometer and at vehicle conditions. Effect of degreening of GPF was studied to take into account any change in pressure drop characteristics of onboard control models during GPF aging in the vehicle.

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.

Gasoline Particulate Filters (GPF) are widely employed in exhaust aftertreatment systems of gasoline engines to meet the stringent particulate emissions requirements of Euro 6 and China 6 standard. Optimization of GPF performance requires a delicate trade-off between fuel economy, engine performance and drivability. This results in a complex lengthy and iterative calibration development process which uses a lot of hardware resources. To improve the calibration process and reduce hardware testing, physics-based modeling of the GPF system is used. A 1-D chemical model supplemented with 3D CFD solver is utilized to evaluate pressure drop and soot burning performance characteristics of the GPF under engine dynamometer test conditions. The chemical kinetics of soot burning for the 1D model is developed using test data obtained from well controlled laboratory environment.

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.

There have been tremendous improvements in China fuel quality in recent years in conjunction with newly implemented vehicle emissions standards to combat air pollution. The focus of concern is particulate emissions from gasoline engines especially from high volume gasoline direct inject (GDI) engines, therefore the China 6 (GB 18351.6-2016) emission standard introduces strict PM/PN requirements. Because the fuel and vehicle are an integrated system, the composition of gasoline is one of the factors affecting PM/PN emissions. Ethanol and aromatics are widely used as octane boosters, changing the composition of China’s gasoline pool. In this study, two gasoline oxygenates, ethanol and methyl tert-butyl ether (MTBE), and heavy aromatic hydrocarbons were studied in vehicles with a GDI engines. Vehicle tests were performed on the Worldwide Harmonized Light Vehicles Test Cycle (WLTC).

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.

The piston temperature has to be carefully controlled to achieve effective and efficient thermal management in the internal combustion engines. One of the common methods to cool piston is by injecting oil from the crankcase underside to the piston under-crown area. In the present study, a novel 3-D multiphase thermal-fluid coupled model was developed using the commercial CFD software SimericsMP+ to study the piston cooling using the oil jet. In this model, an algorithm was proposed to couple the fluid and solid computation domain to account for the different timescale of heat transfer in the fluid and solid due to the high thermal inertia of the solid piston. The heat transfer coefficient (HTC) and reference temperature were mapped to the piston top surface and the liner temperature distribution was also used as the boundary condition. The temperature-dependent material properties, piston motion, and thermal contact resistance between the ring and piston were also accounted for.

The General Motors Aero Lab’s Full-Scale Wind Tunnel Facility, which came into operation in August of 1980[1], has undergone the significant upgrade of installing a state-of-the-art moving ground plane system. After almost four decades of continuous use the full-scale wind tunnel also received some significant maintenance to other areas, including a new heat exchanger, main fan overhaul, and replacement of the test section acoustic treatment. A 5-belt system was installed along with an integrated vehicle lift system. The center belt measures 8.5m long and can accommodate two belt widths of 1100mm and 950mm. Flow quality and other wind tunnel performance parameters were maintained to prior specifications which are on par with the latest industry standards [2]. The new 5-belt rolling road system maintains GM’s industry leading vehicle aerodynamic development and the improved acoustic panels ensure GM continues to develop vehicles with leading class acoustics.

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.

This study brings to forefront the analysis capability of CFD for the oil-cooling of an Electric-Motor (E-Motor) powering an automobile. With the rapid increase in electrically powered vehicle, there is an increasing need in the CFD modeling community to perform virtual simulations of the E-Motors to determine the viability of the designs and their performance capabilities. The thermal predictions are extremely vital as they have tremendous impact on the design, spacing and sizes of these motors. In this paper, with the Simerics, Inc. software, Simerics-MP+®, a complete three dimensional CFD with conjugate heat transfer CHT model of an Electric Motor, including all the important parts like the windings, rotor and stator laminate, endrings etc. is created. The multiphase Volume of Fluid (VOF) approach is used to model the oil flow inside this motor.

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.

Hybrid electric vehicles and battery electric vehicles (BEV) use power electronics (PE) devices to convert between high voltage DC power of the battery and other formats of power. These PE components requires operation within certain temperature range, otherwise, overheating causes component as well as vehicle performance degradation. Therefore, a thermal management system is required for PE components. This paper focuses on the design and development of such a PE components thermal control system. The proposed control system is a distributed thermal control system in which all the PE components are placed in series within one cooling loop. The advantage of the proposed control system is its reduced system complexity, energy efficiency and flexibility to add future PE components. In addition, electric control unit (ECU) are utilized so that complex control algorithms can be implemented.

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies and extremely low NOx and particulate emissions, but controlling the combustion timing remains a challenge. This paper explores the potential of Partial Fuel Stratification (PFS) to provide fast control of CA50 in an LTGC engine. Two different compression ratios are used (CR=16:1 and 14:1) that provide high efficiencies and are compatible with mixed-mode SI-LTGC engines. The fuel used is a research grade E10 gasoline (RON 92, MON 85) representative of a regular-grade market gasoline found in the United States. The fuel was supplied with a gasoline-type direct injector (GDI) mounted centrally in the cylinder. To create the PFS, the GDI injector was pulsed twice each engine cycle. First, an injection early in the intake stroke delivered the majority of the fuel (70 - 80%), establishing the minimum equivalence ratio in the charge.