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Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

Optimization of the engine cold start is critical for gasoline direct injection (GDI) engines to meet increasingly stringent emission regulations, since the emissions during the first 20 seconds of the cold start constitute more than 80% of the hydrocarbon (HC) emissions for the entire EPA FTP75 drive cycle. However, Direct Injection Spark Ignition (DISI) engine cold start optimization is very challenging due to the rapidly changing engine speed, cold thermal environment and low cranking fuel pressure. One approach to reduce HC emissions for DISI engines is to adopt retarded spark so that engines generate high heat fluxes for faster catalyst light-off during the cold idle. This approach typically degrades the engine combustion stability and presents additional challenges to the engine cold start. This paper describes a CFD modeling based approach to address these challenges for the Ford 3.5L V6 EcoBoost engine cold start.

In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

The challenges of flex-fuel vehicle (FFV) emissions measurements have recently come to the forefront for the emissions testing community. The proliferation of ethanol blended gasoline in fractions as high as 85% has placed a new challenge in the path of accurate measures of NMHC and NMOG emissions. Test methods need modification to cope with excess amounts of water in the exhaust, assure transfer and capture of oxygenated compounds to integrated measurement systems (impinger and cartridge measurements) and provide modal emission rates of oxygenated species. Current test methods fall short of addressing these challenges. This presentation will discuss the challenges to FFV testing, modifications made to Ford Motor Company’s Vehicle Emissions Research Laboratory test cells, and demonstrate the improvements in recovery of oxygenated species from the vehicle exhaust system for both regulatory measurements and development measurements.

Selective Catalytic Reduction (SCR) catalysts have been designed to reduce NOx with the assistance of an ammonia-based reductant. Diesel Particulate Filters (DPF) have been designed to trap and eventually oxidize particulate matter (PM). Combining the SCR function within the wall of a high porosity particulate filter substrate has the potential to reduce the overall complexity of the aftertreatment system while maintaining the required NOx and PM performance. The concept, termed Selective Catalytic Reduction Filter (SCRF) was studied using a synthetic gas bench to determine the NOx conversion robustness from soot, coke, and hydrocarbon deposition. Soot deposition, coke derived from propylene exposure, and coke derived from diesel fuel exposure negatively affected the NOx conversion. The type of soot and/or coke responsible for the inhibited NOx conversion did not contribute to the SCRF backpressure.

A systematic methodology has been employed to develop the Duratec 3.5L EcoBoost combustion system, with focus on the optimization of the combustion system including injector spray pattern, intake port design, piston geometry, cylinder head geometry. The development methodology was led by CFD (Computational Fluid Dynamics) modeling together with a testing program that uses optical, single-cylinder, and multi-cylinder engines. The current study shows the effect of several spray patterns on air-fuel mixing, in-cylinder flow development, surface wetting, and turbulence intensity. A few sets of injector spray patterns are studied; some that have a wide total cone angle, some that have a narrow cone angle and a couple of optimized injector spray patterns. The effect of the spray pattern at part load, full load and cold start operation was investigated and the methodology for choosing an optimized injector is presented.

EGR coolers are effective to reduce NOx emissions from diesel engines due to lower intake charge temperature. EGR cooler fouling reduces heat transfer capacity of the cooler significantly and increases pressure drop across the cooler. Engine coolant provided at 40–90 C is used to cool EGR coolers. The presence of a cold surface in the cooler causes particulate soot deposition and hydrocarbon condensation. The experimental data also indicates that the fouling is mainly caused by soot and hydrocarbons. In this study, a 1-D model is extended to simulate particulate soot and hydrocarbon deposition on a concentric tube EGR cooler with a constant wall temperature. The soot deposition caused by thermophoresis phenomena is taken into account the model. Condensation of a wide range of hydrocarbon molecules are also modeled but the results show condensation of only heavy molecules at coolant temperature.

Today's automotive and electronics technologies are evolving so rapidly that educators and industry are both challenged to re-educate the technological workforce in the new area before they are replaced with yet another generation. In early November 2009 Ford's Product Development senior management formally approved a proposal by the University of Detroit Mercy to transform 125 of Ford's “IC Engine Automotive Engineers” into “Advanced Electric Vehicle Automotive Engineers.” Two months later, the first course of the Advanced Electric Vehicle Program began in Dearborn. UDM's response to Ford's needs (and those of other OEM's and suppliers) was not only at the rate of “academic light speed,” but it involved direct collaboration of Ford's electric vehicle leaders and subject matter experts and the UDM AEV Program faculty.

The present production General Motors 2-Mode Hybrid system for full-size SUVs and pickup trucks integrates truck utility functions with a full hybrid system. The 2-mode hybrid system incorporates two electro-mechanical power-split operating modes with four fixed-gear ratios. The combination provides fuel savings from electric assist, regenerative braking and low-speed electric vehicle operation. The combination of two power-split modes reduces the amount of mechanical power that is converted to electric power for continuously variable transmission operation, meeting the utility required for SUVs and trucks. This paper describes how fuel economy functionality was blended with full-size truck utility functions. Truck functions described include: Manual Range Select, Cruise Control, 4WD-Low and continuous high load operation.

As the automotive industry prepares to roll out an unprecedented range of fully electric propulsion vehicle models over the next few years - it really brings to a head for folks responsible for brakes what used to be the subject of hypothetical musings and are now pivotal questions for system design. How do we really go about designing brakes for electric vehicles, in particular, for the well-known limit condition of descending a steep grade? What is really an “optimal’ design for brakes considering the imperatives for the entire vehicle? What are the real “limit conditions” for usage that drive the fundamental design? Are there really electric charging stations planned for or even already existing in high elevations that can affect regenerative brake capacity on the way down? What should be communicated to drivers (if anything) about driving habits for electric vehicles in routes with significant elevation change?

The Particulate Matter Index (PMI) is a tool that provides an indication of a fuel’s tendency to produce Particulate Matter (PM) emissions. Currently, the index is being used by various fuel laboratories and the Automotive OEMs as a tool to understand the gasoline fuel’s impact on both PM from engine hardware and vehicle-out emissions. In addition, a newer index that could be used to give an indication of the PM tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), is shown to have a good correlation to PMI. The data used in those indices are collected from chemical analytical methods. This paper will compare gas chromatography (GC) methods used by three laboratories and discuss how the different techniques may affect the PMI and PEI calculation.

Electrochemical models of lithium ion batteries are today a standard tool in the automotive industry for activities related to the computer-aided engineering design, analysis, and optimization of energy storage systems for electrified vehicles. One of the challenges in the development or use of such models is the need of detailed information on the cell and electrode geometry or properties of the electrode and electrolyte materials, which are typically unavailable or difficult to retrieve by end-users. This forces engineers to resort to “hand-tuning” of many physical and geometrical parameters, using standard cell-level characterization tests. This paper proposes a method to provide information and data on individual electrode performance that can be used to simplify the calibration process for electrochemical models.

Exhaust gas recirculation (EGR) coolers are used on diesel engines to reduce peak in-cylinder flame temperatures, leading to less NOx formation during the combustion process. There is an ongoing concern with soot and hydrocarbon fouling inside the cold surface of the cooler. The fouling layer reduces the heat transfer efficiency and causes pressure drop to increase across the cooler. A number of experimental studies have demonstrated that the fouling layer tends to asymptotically approach a critical height, after which the layer growth ceases. One potential explanation for this behavior is the removal mechanism derived by the shear force applied on the soot and hydrocarbon deposit surface. As the deposit layer thickens, shear force applied on the fouling surface increases due to the flow velocity growth. When a critical shear force is applied, deposit particles start to get removed.

This paper proposes a novel probabilistic approach for multidisciplinary design optimization (MDO) under uncertainty, especially for systems with feedback coupled analyses with multiple coupling variables. The proposed approach consists of four components: multidisciplinary analysis, Bayesian network, copula-based sampling, and design optimization. The Bayesian network represents the joint distribution of multiple variables through marginal distributions and conditional probabilities, and updates the distributions based on new data. In this methodology, the Bayesian network is pursued in two directions: (1) probabilistic surrogate modeling to estimate the output uncertainty given values of the design variables, and (2) probabilistic multidisciplinary analysis (MDA) to infer the distributions of the coupling and output variables that satisfy interdisciplinary compatibility conditions.

Thermal effectiveness of Exhaust Gas Recirculation (EGR) coolers used in diesel engines can progressively decrease and stabilize over time due to inner fouling layer of the cooler tubes. Thermophoretic force has been identified as the major cause of diesel exhaust soot fouling, and models are proposed in the literature but improvements in simulation are needed especially for the long-term trend of soot deposition. To describe the fouling stabilization behavior, a removal mechanism is required to account for stabilization of the soot layer. Observations from previous experiments on surrogate circular tubes suggest there are three primary factors to determine removal mechanisms: surface temperature, thickness, and shear velocity. Based on this hypothesis, we developed a 1D CFD fouling model for predicting the thermal effectiveness reduction of real EGR coolers. The model includes the two competing mechanisms mentioned that results in fouling balance.

Emissions and fuel economy optimization of internal combustion engines is becoming more challenging as the stringency of worldwide emission regulations are constantly increasing. Aggressive transient characteristics of new emission test cycles result in transient operation where the majority of soot is produced for turbocharged diesel engines. Therefore soot optimization has become a central component of the engine calibration development process. Steady state approach for air-fuel ratio limitation calibration development is insufficient to capture the dynamic behavior of soot formation and torque build-up during transient engine operation. This paper presents a novel methodology which uses transient maneuvers to optimize the air-fuel ratio limitation calibration, focusing on the trade-off between vehicle performance and engine-out soot emissions. The proposed methodology features a procedure for determining candidate limitation curves with smoothness criteria considerations.

Misfire is generally defined as be no or partial combustion during the power stroke of internal combustion engine. Because a misfired engine will dramatically increase the exhaust emission and potentially cause permanent damage to the catalytic converters, California Air Resources Board (CARB), as well as most of other countries’ on-board diagnostic regulations mandates the detection of misfire. Currently almost all the OEMs utilize crankshaft position sensors as the main input to their misfire detection algorithm. The detailed detection approaches vary among different manufacturers. For example, some chooses the crankshaft angular velocity calculated from the raw output of the crankshaft positon sensor as the measurement to distinguish misfires from normal firing events, while others use crankshaft angular acceleration or the associated torque index derived from the crankshaft position sensor readings as the measurement of misfire detection.

Hybrid Electric Vehicles (HEV) utilize a High Voltage (HV) battery pack to improve fuel economy by maximizing the capture of vehicle kinetic energy for reuse. Consequently, these HV battery packs experience frequent and rapid charge-discharge cycles. The heat generated during these cycles must be managed effectively to maintain battery cell performance and cell life. The HV battery pack cooling system must keep the HV battery pack temperature below a design target value and maintain a uniform temperature across all of the cells in the HV battery pack. Herein, the authors discuss some of the design points of the air cooled HV battery packs in Ford Motor Company’s current model C-Max and Fusion HEVs. In these vehicles, the flow of battery cooling air was required to not only provide effective cooling of the battery cells, but to simultaneously cool a direct current high voltage to low voltage (DC-DC) converter module.

The airflow that enters the front grille of a ground vehicle for the purpose of component cooling has a significant effect on aerodynamic drag. This drag component is commonly referred to as cooling drag, which denotes the difference in drag measured between open grille and closed grille conditions. When the front grille is closed, the airflow that would have entered the front grille is redirected around the body. This airflow is commonly referred to as cooling interference airflow. Consequently, cooling interference airflow can lead to differences in vehicle component drag; this component of cooling drag is known as cooling interference drag. One mechanism that has been commonly utilized to directly influence the cooling drag, by reducing the engine airflow, is active grille shutters (AGS). For certain driving conditions, the AGS system can restrict airflow from passing through the heat exchangers, which significantly reduces cooling drag.

The Lockheed Martin Low-Speed Wind Tunnel (LSWT) is a closed-return wind tunnel with two solid-wall test sections. This facility originally entered into service in 1967 for aerodynamic research of aircraft in low-speed and vertical/short take-off and landing (V/STOL) flight. Since this time, the client base has evolved to include a significant level of automotive aerodynamic testing, and the needs of the automotive clientele have progressed to include acoustic testing capability. The LSWT was therefore acoustically upgraded in 2016 to reduce background noise levels and to minimize acoustic reflections within the low-speed test section (LSTS). The acoustic upgrade involved detailed analysis, design, specification, and installation of acoustically treated wall surfaces and turning vanes in the circuit as well as low self-noise acoustic wall and ceiling treatment in the solid-wall LSTS.