Search Results

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.

OEMs are racing to develop lightweight vehicles as government regulations now mandate automakers to nearly double the average fuel economy of new cars and trucks by 2025. Lightweight materials such as aluminum, magnesium and carbon fiber composites are being used as structural members in vehicle body and suspension components. The reduction in weight in structural panels increases noise transmission into the passenger compartment. This poses a great challenge in vehicle sound package development since simply increasing weight in sound package components to reduce interior noise is no longer an option [1]. This paper discusses weight saving approaches to reduce noise level at the sources, noise transmission paths, and transmitted noise into the passenger compartment. Lightweight sound package materials are introduced to treat and reduce airborne noise transmission into multi-material lightweight body structure.

The performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

As the world's largest auto producer and consumer, China is both the most promising and complex market given the country's rapid economic growth, huge population, and many regional and segment preference differences. This research is aimed at developing data-driven demand models for customer preference analysis and prediction under a competitive market environment. Regional analysis is first used to understand the impact of geographical factors on customer preference. After a comprehensive data exploration, a customer-level mixed logit model is built to shed light on fast-growing vehicle segments in the Chinese auto market. By combining the data of vehicle purchase, consideration, and past choice, cross-shopping behaviors and brand influence are explicitly modeled in addition to the impact of customer demographics, usage behaviors, and attributes of vehicles.

Motivated by a combination of increasing consumer demand for fuel efficient vehicles, more stringent greenhouse gas, and anticipated future Corporate Average Fuel Economy (CAFE) standards, automotive manufacturers are working to innovate in all areas of vehicle design to improve fuel efficiency. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, reducing vehicle weight by using lighter materials and/or higher strength materials has been identified as one of the strategies in future vehicle development. Weight reduction in vehicle components, subsystems and systems not only reduces the energy needed to overcome inertia forces but also triggers additional mass reduction elsewhere and enables mass reduction in full vehicle levels.

Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

Underhood thermal management is a challenging problem in automotive industry. In order to make sure that vehicle works efficiently, there should be enough airflow through the cooling system so that the consequent heat rejection would be adequate. In idle condition the required air flow is provided by the cooling fan so a better understanding and an accurate predictive CAE tool for fan is very beneficial. Computational Fluid Dynamics (CFD) has been extensively used in predicting aerodynamic performance of automotive components. In the current work, the airflow performance of a fan, shroud and radiator assembly was simulated using Moving Reference Method (MRF) method. Although it is less expensive than Sliding Mesh (SM) method, the CAE results compare well with the test data. The simulation was carried out over 10+ different shrouds and the effect of geometrical parameters on airflow was investigated.

The Multi Material Lightweight Vehicle (MMLV), developed by Magna International and Ford Motor Company, is a result of US Department of Energy project DE-EE0005574. The project demonstrated the lightweighting potential of a five-passenger sedan while maintaining vehicle performance and occupant safety. Prototype vehicles were manufactured and limited full-vehicle testing was conducted. The Mach-I vehicle design, comprised of commercially-available materials and production processes, achieved a 364 kg (23.5%) full-vehicle mass reduction. This resulted in environmental benefits and fuel economy improvements. A significant factor in the overall MMLV mass reduction was the decrease in the powertrain system weight from 340 kg (conventional) to 267 kg (MMLV). This enabled the application of a 1.0-liter three-cylinder engine as the main powerplant. By downsizing the engine, and by implementing material changes within the engine, the weight of the dressed engine was lowered by 29 kg.

Aftertreatment system design involves multiple tradeoffs between engine performance, fuel economy, regulatory emission levels, packaging, and cost. Selection of the best design solution (or “architecture”) is often based on an assumption that inherent catalyst activity is unaffected by location within the system. However, this study acknowledges that catalyst activity can be significantly impacted by location in the system as a result of varying thermal exposure, and this in turn can impact the selection of an optimum system architecture. Vehicle experiments with catalysts aged over a range of mild to moderate to severe thermal conditions that accurately reflect select locations on a vehicle were conducted on a chassis dynamometer. The vehicle test data indicated CO and NOx could be minimized with a catalyst placed in an intermediate location.

During the 1980s, the U.S. Environmental Protection Agency (EPA) incorporated the R factor into fuel economy calculations in order to address concerns about the impacts of test fuel property variations on corporate average fuel economy (CAFE) compliance, which is determined using the Federal Test Procedure (FTP) and Highway Fuel Economy Test (HFET) cycles. The R factor is defined as the ratio of the percent change in fuel economy to the percent change in volumetric heating value for tests conducted using two differing fuels. At the time the R-factor was devised, tests using representative vehicles initially indicated that an appropriate value for the R factor was 0.6. Reassessing the R factor has recently come under renewed interest after EPA's March 2013 proposal to adjust the properties of certification gasoline to contain significant amounts of ethanol.

Engine dynamometer testing was performed comparing fuels having different octane ratings and ethanol content in a Ford 3.5L direct injection turbocharged (EcoBoost) engine at three compression ratios (CRs). The fuels included midlevel ethanol “splash blend” and “octane-matched blend” fuels, E10-98RON (U.S. premium), and E85-108RON. For the splash blends, denatured ethanol was added to E10-91RON, which resulted in E20-96RON and E30-101 RON. For the octane-matched blends, gasoline blendstocks were formulated to maintain constant RON and MON for E10, E20, and E30. The match blend E20-91RON and E30-91RON showed no knock benefit compared to the baseline E10-91RON fuel. However, the splash blend E20-96RON and E10-98RON enabled 11.9:1 CR with similar knock performance to E10-91RON at 10:1 CR. The splash blend E30-101RON enabled 13:1 CR with better knock performance than E10-91RON at 10:1 CR. As expected, E85-108RON exhibited dramatically better knock performance than E30-101RON.

Thermophysical properties of materials used in the design of automotive interiors are needed for computer simulation of climate conditions inside the vehicle. These properties are required for assessment of the vehicle occupants' thermal sensation as they come in contact with the vehicle interior components, such as steering wheels, arm rests, instruments panel and seats. This paper presents the results of an investigation into the thermophysical properties of materials which are required for solving the non-linear Fourier equations with any boundary conditions and taking into account materials' specific heat, volume density, thermal conductivity, and thermal optical properties (spectral and total emissivity and absorptivity). The model and results of the computer simulation will be published in a separate paper.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

Stop/Start technology for conventional automatic transmissions has recently received considerable attention in the automotive industry due to the potential fuel economy, and CO2 emission reduction, benefit at minimal cost. Stop/Start was first developed for manual transmission applications in the EU and Japanese markets. When stop/start is applied to any automatic transmission powertrain the powertrain control challenge is to restart the engine in a manner that simultaneously minimizes the delay in transferring torque to the driven wheel(s) and provides a consistently smooth launch feel with low NVH. It has recently been shown that stop/start can be added to a gas engine powertrain with a conventional torque converter automatic transmission while achieving the desired launch characteristics with minimal change to the powertrain hardware and cost.

Naturally aspirated Homogeneous Charge Compression Ignition (HCCI) operational window is very limited due to inherent issues with combustion harshness. Load range can be extended for HCCI operation using a combination of intake boosting and cooled EGR. Significant range extension, up to 8bar NMEP at 1000RPM, was shown to be possible using these approaches in a single cylinder engine running residual trapping HCCI with 91RON fuel with a 12:1 compression ratio. Experimental results over the feasible speed / load range are presented in this paper for a negative valve overlap HCCI engine. Fuel efficiency advantage of HCCI was found to be around 15% at 2.62bar / 1500RPM over a comparable SI engine operating at the same compression ratio, and the benefit was reduced to about 5% (best scenario) as the load increased to 5bar at the same speed.

Internal combustion (IC) engines fueled by hydrogen are among the most efficient means of converting chemical energy to mechanical work. The exhaust has near-zero carbon-based emissions, and the engines can be operated in a manner in which pollutants are minimal. In addition, in automotive applications, hydrogen engines have the potential for efficiencies higher than fuel cells.[1] In addition, hydrogen engines are likely to have a small increase in engine costs compared to conventionally fueled engines. However, there are challenges to using hydrogen in IC engines. In particular, efficient combustion of hydrogen in engines produces nitrogen oxides (NOx) that generally cannot be treated with conventional three-way catalysts. This work presents the results of experiments which consider changes in direct injection hydrogen engine design to improve engine performance, consisting primarily of engine efficiency and NOx emissions.

This paper presents engine dynamometer testing and modeling analysis of ethanol compared to gasoline at part load conditions where the engine was not knock-limited with either fuel. The purpose of this work was to confirm the efficiency improvement for ethanol reported in published papers, and to quantify the components of the improvement. Testing comparing E85 to E0 gasoline was conducted in an alternating back-to-back manner with multiple data points for each fuel to establish high confidence in the measured results. Approximately 4% relative improvement in brake thermal efficiency (BTE) was measured at three speed-load points. Effects on BTE due to pumping work and emissions were quantified based on the measured engine data, and accounted for only a small portion of the difference.

To better reflect real world driving conditions, the EPA 5-Cycle Fuel Economy method encompasses high vehicle speeds, aggressive vehicle accelerations, climate control system use and cold temperature conditions in addition to the previously used standard City and Highway drive cycles in the estimation of vehicle fuel economy. A standard Powersplit Hybrid Electric Vehicle (HEV) system simulation environment has long been established and widely used within Ford to project fuel economy for the standard EPA City and Highway cycles. Direct modeling and simulation of the complete 5-Cycle fuel economy test set for HEV's presents significant new challenges especially with respect to modeling vehicle thermal management system and interactions with HEV features and system controls. It also requires a structured, systematic approach to validate the key elements of the system models and complete vehicle system simulations.

Engine control unit (ECU) modeling using engine feature C code is an increasingly important part of new vehicle analysis and development tools. The application areas of feature based ECU models are numerous: a) cold vehicle fuel economy (FE) prediction required for recently introduced 5-cycle certification; b) vehicle thermal modeling; c) evaporative (purge) systems design; d) model-in-the-loop/software-in-the-loop (MIL/SIL) vehicle control development and calibration. The modeling method presented in the paper embeds production C-code directly into Simulink at a feature level using an S-Function wrapper. A collection of features critical to accurate engine behavior prediction are compiled individually and integrated according to the newly developed Engine Control Model Architecture (ECMA). Custom MATLAB script based tools enable efficient model construction.

The use of exhaust gas recirculation (EGR) in internal combustion engines has significant impacts on combustion and emissions. EGR can be used to reduce in-cylinder NOx production, reduce emitted particulate matter, and enable advanced forms of combustion. To maximize the benefits of EGR, the exhaust gases are often cooled with on-engine liquid to gas heat exchangers. A common problem with this approach is the build-up of a fouling layer inside the heat exchanger due to thermophoresis and condensation, reducing the effectiveness of the heat exchanger in lowering gas temperatures. Literature has shown the effectiveness to initially drop rapidly and then approach steady state after a variable amount of time. The asymptotic behavior of the effectiveness has not been well explained. A range of theories have been proposed including fouling layer removal, changing fouling layer properties, and cessation of thermophoresis.