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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.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

The power loss of bearings is a significant factor in the overall efficiency in a drive unit system. Such bearings are subject to combined radial and axial loading needed to support the gear mesh forces. An experimental methodology has been developed to perform sets of power loss measurements on TRB, 4PCBB and DGBB. These measurements were performed under a variety of speed, load, temperature, and lubrication conditions. The loss behaviors of these types of the bearings are discussed, along with the tradeoff of different bearing arrangements for the fuel economy cycles. Several power loss models are employed to assess the accuracy of the estimations as compared to the experimental measurements. At low speed some models showed good correlations for TRB and DGBB, while at higher speed, they start deviating from the testing results. A higher fidelity model for estimating the losses at high speed, especially speed around 20krpm and beyond, needs to be developed.

This paper reviews the relationship between taper wheel bearing damage and vehicle noise and vibration for a body-on-frame pickup truck and a body-on-frame SUV. In addition to understanding how the different levels of bearing damage relate to vehicle noise, it also discusses the level of noise versus the damaged bearing’s position in the vehicle. For this study, the wheel bearing supplier provided front and rear bearings with various amounts of Brinell damage to the bearing raceways. The different bearings were evaluated subjectively for noise in the vehicle. After vehicle testing, the bearing raceway Brinell depths were measured to correlate the level of bearing damage to vehicle noise. The study shows the relationship between bearing Brinell dent depth and vehicle noise for body-on-frame light trucks and SUVs. The noise was most apparent in vehicles between 45 and 60 mph. For bearings with moderate levels of damage, steering inputs were required to hear noise.

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.

Euro 7/VII regulations are currently under discussion and are expected to be the last big regulatory step in Europe. From available documentation, it is clear the aim of further regulating the extended conditions of use which are still responsible of high emission events (e. g. cold start or altitude) as well as regulating secondary emissions such as NH3, N2O, CH4, Aldehydes (HCHO). Even if not completely fixed yet, the EU7 limits will be challenging for internal combustion engines and even more for Diesel. Despite a consistent reduction of market share, Diesel engines are expected to remain a significant portion in certain sectors such as Heavy duty (HD) and Light-commercial vehicle (LCV) for some decades. In order to reach the new limits being proposed, besides minimizing engine-out emissions, Diesel powertrain will need an aftertreatment system able to work at very high efficiency right after engine start and in almost every working and environmental condition.

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.

Finding room to package enough energy at today’s battery energy densities, while preserving performance and configuration requirements is a common problem for electric vehicles. This issue was recently addressed at General Motors by a small team utilizing agile concept development methods, constitutive material model development, and performance simulation tools to create a structural strategy for a family of unique electric light duty trucks. The desire to create a flexible architecture rather than a single vehicle, coupled with an underbody dominant, and rectilinear structural design space precluded any great topological novelty, so a basic principles approach was taken instead. A concept was devised whereby conventional truck frame rails were abandoned in favor of a series of three connected box-like structures along the length of the vehicle. For this to work effectively however, stable shear panels were required as a basic building block.

Cast Al-Si alloys are widely used in automotive industry to produce structural components, such as engine block and cylinder head, because of the increasing demands in reducing mass for improved fuel efficiency. The fatigue performance of the castings is critical in their application. Porosity is highly detrimental to the fatigue behavior of cast Al-Si alloys. Therefore, accurate measurement of pore sizes is important in order to develop the correlations between porosity and fatigue strength. However, quantification of porosity is challenging and shows large variation depending on the measurement methods, particularly for micro-shrinkage porosity due to the torturous and complex morphology. The conventional metallographic image analysis method in the 2D polished surface often underestimates the actual pore size particularly when the porosity morphology is complex.

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.

An experimental piston compounded engine was designed with guidance from thermodynamic modeling, then was built and tested to compare the model predictions to measured results. The piston-compounded concept has shown great potential for improvements in efficiency over current state-of-the-art light-duty engines through the use of an efficient second expansion process to more fully recover energy still present in the exhaust gasses, and was further developed into the Downsized Boosted Dilute Combustion, Exhaust Compounded (DBDC+EC) engine presented here. This paper documents some of the more unique design elements of this engine as well as a performance comparison between test data and modeling expectations. Ultimately, an experimental stoichiometric spark-ignited piston compounded engine was designed, five blocks were built, and collectively they were run for thousands of hours.

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio, and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the first to two papers describing the development of a combustion system combining lean-stratified combustion with Miller cycle for downsized boosted applications. The work was completed under a multi-year US DOE project. The goal was to define a light-duty engine package capable of achieving a 35% fuel economy improvement at US Tier 3 emission standards over a naturally aspirated stoichiometric baseline vehicle.

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the second of two papers describing the multi-cylinder integration of a technology package combining lean-stratified combustion with Miller cycle for downsized boosted applications. The first paper describes the design, analysis and single-cylinder testing conducted to down-select the combustion system deployed to the multi-cylinder engine.

The REAL NOx regulation requires tracking and reporting of NOx emissions starting in 2022MY for both medium-duty and heavy-duty diesel vehicles with potential to be considered during the next light-duty rulemaking. The regulation includes minimum NOx mass measurement accuracy requirements of either +/−20 percent or +/− 0.1 g/bhp-hr. Existing NOx sensor technology may not be able to meet the regulated accuracy requirements especially when exposed to other sources of variation within the emissions control system. This paper provides an assessment of real-world NOx sensor accuracy and the impact of other sources of variation and noise factors on NOx measurement accuracy. Noise factors investigated include NOx sensor tolerance, exhaust flow rate estimation, NOx sensor ammonia (NH3) cross sensitivity, mass air flow (MAF) sensor accuracy, NOx sensor placement, and laboratory emissions measurement capability.

This paper describes the development of the GM Allison 10-Speed Heavy Duty (HD) Transmission. The trend of increased towing capacity and engine horsepower in the automotive heavy-duty truck segment has been steadily climbing for the past 10 years. The development of 10-Speed HD Transmission is designed to be best in class in for towing performance in the 2500/3500 series segment while optimizing fuel economy. The 10-Speed HD Transmission also gives the customers the option to order an integrated power take-off (PTO) unit that benefits downstream installation of utility accessories such as hydraulic pumps, generators, etc.

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies.

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing.

Market demands for increased fuel economy and reduced emissions are placing higher aerodynamic and thermal analysis demands on vehicle designers and engineers. These analyses are usually carried out by different engineering groups in different parts of the design cycle. Design changes required to improve vehicle aerodynamics often come at the price of part thermal performance and vice versa. These design changes are frequently a fix for performance issues at a single performance point such as peak power, peak torque, or highway cruise. In this paper, the motivation for a holistic approach in the form of multi-disciplinary optimization (MDO) early in the design process is presented. Using a Response-surface Informed Transient Thermal Model (RITThM) a vehicle's thermal performance through a drive cycle is predicted and correlated to physical testing for validation.

This article presents experimental results obtained with a disruptive engine platform, designed to maximize the engine efficiency through a synergetic implementation of downsizing, high compression-ratio, and importantly exhaust-heat energy recovery in conjunction with advanced lean/dilute low-temperature type combustion. The engine architecture is a supercharged high-power output, 1.1-liter engine with two-firing cylinders and a high compression ratio of 13.5: 1. The integrated exhaust heat recovery system is an additional, larger displacement, non-fueled cylinder into which the exhaust gas from the two firing cylinders is alternately transferred to be further expanded. The main goal of this work is to implement in this engine, advanced lean/dilute low-temperature combustion for low-NOx and high efficiency operation, and to address the transition between the different operating modes.

There are a variety of test protocols associated with vehicle fuel economy and emissions testing. As a result, a number of test protocols currently exist to measure axle efficiency and spin loss. The intent of this technical paper is to describe a methodology that uses a singular axle efficiency and spin loss procedure. The data can then be used to predict the effects on vehicle FE and GHG for a specific class of vehicles via simulation. An accelerated break-in method using a comparable energy approach has been developed, and can be used to meet the break-in requirements of different vehicle emission test protocols. A “float to equilibrium” sump temperature approach has been used to produce instantaneous efficiency data, which can be used to more accurately predict vehicle FE and GHG, inclusive of Cold CO2. The “Float to Equilibrium” approach and “Fixed Sump Temperature” approach has been compared and discussed.