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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.

Ford Motor Company is introducing “EcoBoost” gasoline turbocharged direct injection (GTDI) engine technology in the 2010 Lincoln MKS. A logical enhancement of EcoBoost technology is the use of E85 for knock mitigation. The subject of this paper is the optimal use of E85 by using two fuel systems in the same EcoBoost engine: port fuel injection (PFI) of gasoline and direct injection (DI) of E85. Gasoline PFI is used for starting and light-medium load operation, while E85 DI is used only as required during high load operation to avoid knock. Direct injection of E85 (a commercially available blend of ∼85% ethanol and ∼15% gasoline) is extremely effective in suppressing knock, due to ethanol's high inherent octane and its high heat of vaporization, which results in substantial cooling of the charge. As a result, the compression ratio (CR) can be increased and higher boost levels can be used.

An analytic model of powertrain efficiency on a drive cycle was developed and evaluated using hundreds of cars and trucks from the US EPA ‘Test Car Lists’. The efficiency properties of naturally aspirated and downsized turbocharged engines were compared for vehicles with automatic transmissions on the US cycles. The resulting powertrain cycle efficiency model is proportional to the powertrain marginal energy conversion efficiency K, which is also its upper limit. It decreases as the powertrain matching parameters, the displacement-to-mass ratio (D/M) and the gearing ratio (n/V), increase. The inputs are the powertrain fuel consumption, the vehicle road load, and the cycle work requirement. They could be modeled simply with only minor approximations through the use of absolute inputs and outputs, and systematic use of scaling. On the Highway test, conventional automatic transmission vehicles of moderate performance achieve between 25% and 30% powertrain efficiency.

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.

The automotive industry is subject to stringent regulations in emissions and growing customer demands for better fuel consumption and vehicle performance. Engine calibration, a process that optimizes engine performance by tuning engine controls (actuators), becomes challenging nowadays due to significant increase of complexity of modern engines. The traditional sweep-based engine calibration method is no longer sustainable. To tackle the challenge, this work considers two powerful global optimization methods: genetic algorithm (GA) and Bayesian optimization for steady-state engine calibration for single speed-load point. GA is a branch of meta-heuristic methods that has shown a great potential on solving difficult problems in automotive engineering. Bayesian optimization is an efficient global optimization method that solves problems with computationally expensive testing such as hyperparameter tuning in deep neural network (DNN), engine testing, etc.

A belt driven Front End Accessory Drive (FEAD) is used to efficiently supply power to accessory components on automotive engines. The total energy absorbed by the FEAD consists of the accessory component requirements, the belt deformation and friction losses as well as the bearing losses. The accessory component torque requirements provide accessory function such as air conditioning, fluid pumping and electrical power generation. Alternatively, belt related torque losses are a significant parasitic loss, since they do not contribute any useful work. This paper will explain the source of energy loss in FEADs and outline a comprehensive strategy to reduce it. Test results comparing the effect of reduced friction on fuel consumption will be presented as well.

Reliability-based design optimization (RBDO) has been widely used to obtain a reliable design via an existing CAE model considering the variations of input variables. However, most RBDO approaches do not consider the CAE model bias and uncertainty, which may largely affect the reliability assessment of the final design and result in risky design decisions. In this paper, the Gaussian Process Modeling (GPM) approach is applied to statistically correct the model discrepancy which is represented as a bias function, and to quantify model uncertainty based on collected data from either real tests or high-fidelity CAE simulations. After the corrected model is validated by extra sets of test data, it is integrated into the RBDO formulation to obtain a reliable solution that meets the overall reliability targets while considering both model and parameter uncertainties.

Dimethyl ether (DME) is an alternative to diesel fuel for use in compression-ignition engines with modified fuel systems and offers potential advantages of efficiency improvements and emission reductions. DME can be produced from natural gas (NG) or from renewable feedstocks such as landfill gas (LFG) or renewable natural gas from manure waste streams (MANR) or any other biomass. This study investigates the well-to-wheels (WTW) energy use and emissions of five DME production pathways as compared with those of petroleum gasoline and diesel using the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model developed at Argonne National Laboratory (ANL).

The drive cycle average powertrain efficiency of current US vehicles is studied by applying a first principles model to the EPA Test Car List database. The largest group of vehicles has naturally aspirated engines and six speed planetary automatic transmissions, and defines the base technology level. For this group the best cycle average powertrain efficiency is independent of vehicle size and is achieved by the lowest power-to-weight vehicles. For all segments of the EPA test, the fuel required per unit of vehicle work (the inverse of powertrain efficiency), is found to increase linearly with a basic powertrain matching parameter. The parameter is (D/M)(n/V), where D is engine displacement, M vehicle mass, and (n/V) the top gear engine speed over the vehicle speed. The fuel consumption penalties in the City segments due to powertrain warm-up, aftertreatment warm-up, stop-and-go operation, and power-off operation are estimated.

The fuel consumption of a vehicle is shown to be linearly proportional to (1) total vehicle work required to drive the cycle due to mass and acceleration, tire friction, and aerodynamic drag and (2) the powertrain (PT) mechanical losses, which are approximately proportional to the engine displaced volume per unit distance travelled (displacement time gearing). The fuel usage increases linearly with work and displacement over a wide range of applications, and the rate of increase is inversely proportional to the marginal efficiency of the engine. The theoretical basis for these predictions is reviewed. Examples from current applications are discussed, where a single PT is used across several vehicles. A full vehicle cycle simulation model also predicts a linear relationship between fuel consumption, vehicle work, and displacement time gearing and agrees well with the application data.

Vehicle certification data are used to study the effectiveness of the major powertrain technologies used by car manufacturers to reduce fuel consumption. Methods for differentiating vehicles effectively were developed by leveraging theoretical models of engine and vehicle fuel consumption. One approach normalizes by displacement per unit distance, which puts both fuel used and vehicle work in mean effective pressure units, and is useful when comparing engine technologies. The other normalizes by engine rated power, a customer-relevant output metric. The normalized work/power is proportional to weight/power, the most fundamental performance metric. Certification data for 2016 and 2017 U.S. vehicles with different powertrain technologies are compared to baseline vehicles with port fuel injection (PFI) naturally aspirated engines and six-speed automatic transmissions.

A normalized analytical vehicle fuel consumption model is developed based on an input/output description of engine fuel consumption and transmission losses. Engine properties and fuel consumption are expressed in mean effective pressure (mep) units, while vehicle road load, acceleration and grade are expressed in acceleration units. The engine model concentrates on the low rpm operation. The fuel mep is approximately independent of speed and is a linear function of load, as long as the engine is not knock limited. A linear, two-constant engine model then covers the speed/load range of interest. The model constants are a function of well-known engine properties. Examples are discussed for naturally aspirated and turbocharged SI engines and for Diesel engines. A similar model is developed for the transmission where the offset reflects the spin and pump losses, and the slope is the gear efficiency.

Auto-manufacturers are under increasing pressure to develop powertrain systems for automotive vehicles, which are more efficient regarding fuel consumption, less polluting and still keep high performance levels. Hybrid electrical vehicles (HEV) are considered the most promising technology in sight, considering a time horizon of more ore less twenty years. HEVs combine benefits of electrical vehicles, such zero emission, low noise and high torques at low velocities and advantages of conventional vehicles, such as large autonomy, great reliability and high levels of performance. This paper is focused on the major elements of an HEV powertrain: electrical motors, internal combustion engine (ICE) and batteries, which are described. The paper also presents a comparison of two possible HEV configurations: series and parallel. The mathematical model of a small hybrid vehicle is developed using software ADVISOR.

Reduced engine idle speed reduces fuel consumption but requires active idle speed control (ISC) to avoid stalls due to accessory load disturbances. For gasoline engines, spark advance is used in conjunction with air flow for the idle speed control. However, for spark control to be effective the nominal spark timing has to be retarded from the optimal timing to allow spark to increase torque. This offsets the fuel consumption benefit from lower speeds. During lean homogenous operating modes, Fuel Assisted ISC (FA-ISC) uses fuel to increase torque (similar to diesel and gasoline stratified charge) eliminating the need for the retarded nominal spark. The engine then operates close to optimal spark and the lean air fuel limit for optimal fuel economy.

In recent years, HCCI (Homogeneous Charge Compression Ignition) combustion concept has attracted attention due to its potential for high fuel efficiency and low emissions. The essence of HCCI combustion is auto ignition of a very lean, homogeneous air-fuel mixture. However it leads to a major challenge for control engineers – controlling combustion timing to achieve required torque and optimal fuel consumption. There is a need for a simplified HCCI engine model to guide control strategy development. This paper presents such a control oriented model for a “heated intake air” HCCI engine concept that uses two streams of air (cold and hot) to achieve a variable temperature at intake valve closing.

This study measures, during various transients of speed and load, in-cylinder-, intake-/exhaust- (manifold) pressures and engine torque. The tests were conducted on a typical high power-density, passenger car powertrain (common-rail diesel engine, of in-line 4-cylinder configuration equipped with a Variable Geometry Turbocharger). The objective was to quantify the deterioration (relative to a steady-steady condition) in transient Specific Fuel Consumption (SFC) that may occur during lagged-boost closed-loop control and thus propose an engine control strategy that minimises the transient SFC deterioration. The results, from transient characterisation and the analysis method applied in this study, indicate that transient SFC can deteriorate up to 30% (function of load transient) and is primarily caused by excessive engine pumping-loss.

In the effort to improve combustion of a Light-load Stratified-Charge Direct-Injection (LSCDI) combustion system, CFD modeling, together with optical engine diagnostics and single cylinder engine testing, was applied to resolve some key technical issues. The issues associated with stratified-charge (SC) operation are combustion stability, smoke emission, and NOx emission. The challenges at homogeneous-charge operation include fuel-air mixing homogeneity at partial load operation, smoke emission and mixing homogeneity at low speed WOT, and engine knock tendency reduction at medium speed WOT operations. In SC operation, the fuel consumption is constrained with the acceptable smoke emission level and stability limit. With the optimization of piston design and injector specification, the smoke emission can be reduced. Concurrently, the combustion stability window and fuel consumption can be also significantly improved.

This paper describes the dynamometer development of a lightly stratified direct-injection spark-ignition engine. The engine was designed for stratified charge operation at speeds and loads below 2000 RPM, 2 bar BMEP. Test results detailed in this report include evaluation of part-load stratified-charge, part-load homogeneous-charge, and WOT operation. The program had aggressive goals in improving WOT performance and part-load fuel consumption compared to a baseline PFI engine while meeting Stage V emissions levels. Mini-map analysis of the engine data indicated that the engine was able to meet the emissions and fuel consumption goals.

An innovative stratified-charge DISI combustion concept has been developed using a mixture formation method referred to as Vortex Induced Stratification Combustion (VISC). This paper describes the combustion system concept and an initial assessment of it, performed on a single-cylinder test engine and through CFD modeling. This VISC concept utilizes the vortex naturally formed on the outside of a wide spray cone that is enhanced by bulk gas flow control and piston crown design. This vortex transports fuel vapor from the spray cone to the spark gap. This system allows a late injection timing and produces a well-confined mixture, which together provide an improved compromise between combustion phasing and combustion efficiency over typical wall-guided systems. Testing results indicate an 18% fuel consumption reduction, compared with a baseline PFI engine, over a drive cycle (neglecting cold start and transient effects).

Ethanol is one of many alternative transportation fuels that can be burned in internal combustion engines in the same ways as gasoline and diesel. Compared to hydrogen and electric energy, ethanol is very similar to gasoline in many aspects and can be delivered to end-users by the same infrastructures. It can be produced from biomass and is considered renewable. It is expected that the improvement in fuels over the next 20 years will be by blending biomass-based fuels with fossil fuels using existing technologies in present-day automobiles with only minor modifications, even though the overall costs of using biomass-based fuels are still considerably higher than conventional fuels. Ethanol may represent a significant alternative fuel source, especially during the transition from fossil-based fuels to more exotic power sources. Mapping engines for flexible fuel vehicles (FFV), however, would be very costly and time consuming, even with the help of model-based engine mapping (MBM).