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Combustion engines are typically only 20-30% efficient at part-load operating conditions, resulting in poor fuel economy on average. To address this, LiquidPiston has developed an improved thermodynamics cycle, called the High-Efficiency Hybrid Cycle (HEHC), which optimizes each process (stroke) of the engine operation, with the aim of maximizing fuel efficiency. The cycle consists of: 1) a high compression ratio; 2) constant-volume combustion, and 3) over-expansion. At a modest compression ratio of 18:1, this cycle offers an ideal thermodynamic efficiency of 74%. To embody the HEHC cycle, LiquidPiston has developed two very different rotary engine architectures ? called the ?M? and ?X? engines. These rotary engine architectures offer flexibility in executing the thermodynamics cycle, and also result in a very compact package. In this talk, I will present recent results in the development of the LiquidPiston engines. The company is currently testing 20 and 40 HP versions of the ?M?

In this paper a diagnostic design process is proposed for developmental vehicles where mainstream design process is not well-suited. First a review of current practice in on-board vehicle fault diagnostics design is presented with particular focus on the application of this process to the development of the Ford Escape Hybrid Electric Vehicle (HEV) program and a demonstration Fuel Cell Electric Vehicle (FCEV) program. Based on the review and evaluation of these experiences, a new tool for diagnostics design is proposed that promises to make the design more traceable, to reduce the repetition of work, and to improve understandability and reuse.

A uniaxial stress-strain curve obtained from a conventional tensile test is only valid up to the point of uniform elongation, beyond which a diffuse neck begins to develop, followed by localized necking and eventual fracture. However Finite Element Analysis for sheet metal forming requires an effective stress-strain curve that extends well beyond the diffuse necking point. Such an extension is usually accomplished by analytical curve fitting and extrapolation. Recent advancement in Digital Image Correlation (DIC) techniques allows direct measurement of full-range stress-strain curves by continuously analyzing the deformation within the diffuse neck zone until the material ruptures. However the stress-strain curve obtained this way is still approximate in nature. Its accuracy depends on the specimen size, the gage size for analysis, and the material response itself.

Gasoline turbocharged direct injection (GTDI) engines, such as EcoBoost™ from Ford, are becoming established as a high value technology solution to improve passenger car and light truck fuel economy. Due to their high specific performance and excellent low-speed torque, improved fuel economy can be realized due to downsizing and downspeeding without sacrificing performance and driveability while meeting the most stringent future emissions standards with an inexpensive three-way catalyst. A logical and synergistic extension of the EcoBoost™ strategy is the use of E85 (approximately 85% ethanol and 15% gasoline) for knock mitigation. Direct injection of E85 is very effective in suppressing knock due to ethanol's high heat of vaporization - which increases the charge cooling benefit of direct injection - and inherently high octane rating. As a result, higher boost levels can be achieved while maintaining optimal combustion phasing giving high thermal efficiency.

When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

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.

Optimal material selection for a part becomes quite challenging with dynamically changing data from various sources. Multiple manufacturing locations with varying supplier capabilities add to the complexity. There is need to balance product attribute requirements with manufacturing feasibility, cost, sourcing, and vehicle program strategies. The sequential consideration of product attribute, manufacturing, and sourcing aspects tends to result in design churns. Ford R&A is developing a web based material recommender tool to help engineers with material selection integrating sourcing, manufacturing, and design considerations. This tool is designed to filter the list of materials for a specific part and provide a prioritized list of materials; and allow engineers to do weight and cost trade-off studies. The initial implementation of this material recommender tool employs simplified analytical calculators for evaluation of structural performance metrics of parts.

This report is a comprehensive investigation into the use of resin transfer molded glass fiber reinforced plastics in a structural application. A pickup truck cab structure is an ideal application for plastic composites. The cab is designed to fit a production Ranger pickup truck and uses carryover frame and front end structure. The cab concept consists primarily of two molded pieces. This design demonstrates extensive parts integration and allows for low-cost tooling, along with automated assembly.

There are a number of benefits from Ford Motor Company's participation in motorsports. This paper will describe how an engineering team developed a CAE process to assist in the design of a race car to meet impact requirements, with the technology transfer benefit of improved impact performance of composite structures in passenger cars. In 1997/98, a CAE process was developed and applied in the design and test of Formula One race car composite impact structures. For this particular engineering effort, a Ford proprietary software program, COMP-COLLAPSE, was the primary analysis tool that was utilized to successfully predict impact performance. As a result, COMP-COLLAPSE was used extensively in the design of race car composite impact structures. There were two beneficiaries from this effort: Race Vehicles: Improved vehicle impact performance as well as design improvement in crush efficiency, packaging, weight, and manufacturing.

A new diesel engine, called the 6.7L Power Stroke® V-8 Turbocharged Diesel, and code named "Scorpion" has been designed and developed by Ford Motor Company for the full-size pickup truck and light commercial vehicle markets. It incorporates the latest design technology to meet 2010 model year emission regulations for both chassis and dynamometer-based certifications, and is compatible with up to B20 biodiesel fuel. The engine is an entirely new 90 degree V-8 design featuring inboard exhaust, piezo common rail fuel injection, a new dual compressor wheel turbocharger, and dual loop cooling systems. The 6.7L is Ford's first diesel engine designed for the North American pickup and light commercial truck market.

Finite element analysis (FEA) predictions of magnesium beams are compared to load versus displacement test measurements. The beams are made from AM60B die castings, AM30 extrusions and AZ31 sheet. The sheet and die cast beams are built up from two top hat sections joined with toughened epoxy adhesive and structural rivets. LS-DYNA material model MAT_124 predicts the magnesium behavior over a range of strain rates and accommodates different responses in tension and compression. Material test results and FEA experience set the strain to failure limits in the FEA predictions. The boundary conditions in the FEA models closely mimic the loading and constraint conditions in the component testing. Results from quasi-static four-point bend, quasi-static axial compression and high-speed axial compression tests of magnesium beams show the beam's behavior over a range of loadings and test rates. The magnesium beams exhibit significant material cracking and splitting in all the tests.

Ford developed the 6R140 TorqShift six-speed transmission for the Ford F-series SuperDuty trucks. The 6R140 transmission is specifically designed to manage the increased torque produced by the 6.7-liter Power Stroke V-8 turbocharged diesel engine. It is also matched with the 6.2-liter V-8 gasoline engine. By design, the new 6R140 transmission seamlessly delivers the enormous low-rpm torque produced by the new diesel engine and efficiently manages the higher rpm of the new gasoline engine.

A finite element analysis method has been developed to assess the design of an automobile body joint. The concept of the coefficient of joint stiffness and the force distribution ratio are proposed accordingly. The coefficient of joint stiffness reveals whether a joint is stiff enough compared to its joining components. In addition, these parameters can be used to estimate the potential and the effectiveness for any further improvement of the joint design. The modeling and analysis of the proposed process are robust. The coefficient of joint stiffness could be further developed to serve as the joint design target.

A compact in-situ tensile stress fixture was designed for the study of the combined effects of stress and automotive environments on structural glass fiber-reinforced composite materials. With this fixture, a standardized 300 hour laboratory screening test was developed to compare the residual property loss of composite materials due to concurrent exposure to stress and environment. It is of great importance that the data gathered in the laboratory have correlation to on-vehicle (in-service) performance, and that both lab and real world data be taken with a test system (in-situ test fixtures) capable of providing accurate and consistent results under either test condition.

Gear whine in 1st gear for an automatic transmission that has been in production for nearly thirty years was identified as an NVH issue. Due to advances in vehicle level refinement, and reduction of other masking noises, the automatic transmission gear whine became an issue with the customer. Since the transmission was already in production, the improvements had to be within the boundaries of manufacturing feasibility with existing equipment to avoid costly and time consuming investment in new machines. The approach used was one of identifying optimum values of existing gear parameters to provide a reduction in passenger compartment noise. The problem was in a light truck application. Objective noise measurements were recorded for 10 transmissions from more than 50 driven in vehicles. The transmissions were disassembled and the gears inspected.

As automotive manufacturers continue to increase their use of thermoplastics for interior and exterior components, there is a likelihood of squeaks due to material contacts. To address this issue, Ford's Body Chassis NVH Squeak and Rattle Prevention Engineering Department has developed a tester that can measure friction, and any accompanying audible sound, as a function of sliding velocity, normal load, surface roughness, and environmental factors. The Ford team has been using the tester to address manufacturing plant issues and to develop a database of polymeric material pairings that will be used as a guide for current and future designs to eliminate potential noise concerns. Based upon the database, along with a physical property analysis of the various plastic (viscoelastic) materials used in the interior, we are in the process of developing an analytical model which will be a tool to predict frictional behavior.

Drive shaft modelling effects frontal crash finite element simulation. A 35 mph rigid barrier impact of a body on frame SUV with an one piece drive shaft and a unibody SUV with a two piece drive shaft have been studied and simulated using finite element analyses. In the model, the drive shaft can take significant load in frontal impact crash. Assumptions regarding the drive shaft model can change the predicted engine motion in the simulation. This change influences the rocker @ B-pillar deceleration. Two modelling methods have been investigated in this study considering both joint mechanisms and material failure in dynamic impact. Model parameters for joint behavior and failure should be determined from vehicle design information and component testing. A body on frame SUV FEA model has been used to validate the drive shaft modeling technique by comparing the simulation results with crash test data.