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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.

Diesel NOx emissions control utilizing combined Lean NOx Trap (LNT) and so-called passive or in-situ Selective Catalytic Reduction (SCR) catalyst technologies (i.e. with reductant species generated by the LNT) has been the subject of several previous papers from our laboratory [ 1 - 2 ]. The present study focuses on hydrocarbon (HC) emissions control via the same LNT+SCR catalyst technology under FTP driving conditions. HC emissions control can be as challenging as NOx control under both current and future federal and California/Green State emission standards. However, as with NOx control, the combined LNT+SCR approach offers advantages for HC emission control over LNT-only aftertreatment. The incremental conversion obtained with the SCR catalyst is shown, both on the basis of vehicle and laboratory tests, to result primarily from HC adsorbed on the SCR catalyst during rich LNT purges that reacts during subsequent lean engine operation.

Design optimization techniques are widely used to drive designs toward a global or a near global optimal solution. However, the achieved optimal solution often appears to be the only choice that an engineer/designer can select as the final design. This is caused by either problem topology or by the nature of optimization algorithms to converge quickly in local/global optimal or both. Problem topology can be unimodal or multimodal with many local and/or global optimal solutions. For multimodal problems, most global algorithms tend to exploit the global optimal solution quickly but at the same time leaving the engineer with only one choice of design. The paper explores the application of genetic algorithms (GA), simulated annealing (SA), and mixed integer problem sequential quadratic programming (MIPSQP) to find multiple local and global solutions using single objective optimization formulation.

Torque controls for the engine and electric motors in a Powersplit HEV are keys to the success of balancing fuel economy, driveability, and battery power control. The electric variable transmission (EVT) offers an opportunity to let the engine operate at system-optimal fuel efficient points independently of any load. Existing work shows such a benefit can be realized through a decentralized control structure that translates the driver inputs to independent engine torque and speed control. However, our study shows that the decentralized control structures have a fundamental limitation that arises from the nonminimum phase (NMP) zero in the transfer function from the driver power command to the generator torque change rate, and thus not only is it difficult to obtain smooth generator torque but also it can cause violations on battery power limits during transients. Additionally, it adversely affects the driveability due to the generator torque transients reflected at the ring gear.

Hybrid electric vehicle (HEV) systems offer significant improvements in vehicle fuel economy and reductions in vehicle generated greenhouse gas emissions. The widely accepted power-split HEV system configuration couples together an internal combustion engine with two electric machines (a motor and a generator) through a planetary gear set. This paper describes a methodology for analysis and optimization of alternative HEV power-split configurations defined by alternative connections between power sources and transaxle. The alternative configurations are identified by a matrix of kinematic equations for connected power sources. Based on the universal kinematic matrix, a generic method for automatically formulating dynamic models is developed. Screening and optimization of alternative configurations involves verification of a set of design requirements which reflect: vehicle continuous operation, e.g. grade test; and vehicle dynamic operation such as acceleration and drivability.

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.

Sampling-based methods are general but time consuming for solving a Reliability-Based Design Optimization (RBDO) problem. In order to alleviate the computation burden, score function together with the Monte Carlo method was used to compute the stochastic sensitivities of reliability functions. In literature, re-weighting schemes were shown to converge faster than the regular Monte Carlo method. In this paper, a reweighting scheme together with score function is employed to perform sampling-based stochastic sensitivity analysis to improve the computational efficiency and accuracy. An analytical example is used to show the advantages of the proposed method. Comparisons to the conventional methods are made and discussed. Two RBDO problems are solved to demonstrate the use of the proposed method.

The integration of a HIL system involves many software and hardware elements. During the integration process, various errors may occur. In this paper, the Design For Six Sigma (DFSS) methodology is applied to develop an integration process for a generic type of HIL system. The development follows the DCOV (Design, Characterize, Optimize and Verify) four-phase approach. The result is an efficient process proven to meet the customer's needs, reduce integration errors and deliver a high quality HIL system within less time.

A model of Ford's current FTP based OBD-II catalyst monitor has been developed and used in determining the optimal monitored catalyst volume for several LEV applications. The model predictions were found to agree reasonably well with the available experimental data. Furthermore, the results of this study indicate that the optimal monitored catalyst volume for meeting LEV requirements is vehicle application specific. As a result, it is concluded that a general guideline for sizing of the monitored catalyst volume for LEVs will most likely be inadequate and could result in grossly suboptimal catalyst monitor function for some applications. The model which is described in this paper offers a potentially more effective means of determining the best monitored catalyst volume for a given vehicle application. It should be possible to utilize this model during the early phase of a vehicle program in order to provide for the optimal packaging of the catalyst monitor sensor (CMS).

An improved process for determining oven aging times and temperatures for OBD-II threshold catalyst aging has been developed. The new process makes use of a catalyst model along with a kinetic data base in order to project vehicle tailpipe emissions for oven aged catalyst systems. The catalyst oven aging time and temperature required for a given vehicle can be specified such that the actual HC tailpipe emissions are within 15-20% of the desired threshold emission level. It is believed that this process could greatly reduce the need for much of the trial and error iteration which is currently associated with obtaining threshold catalysts for OBD-II calibration purposes.

The effect of fuel sulfur on the dual HEGO sensor OBD-II catalyst monitor has been investigated. Laboratory studies revealed two competing effects of the fuel sulfur on the operation of the catalyst monitor: 1. the loss of catalyst oxygen storage capacity, and 2. the degradation in the response rate of the rear HEGO sensor. The magnitude of the loss in catalyst OSC relative to the increase in rear HEGO sensor response time determined whether the rear HEGO sensor index increased, decreased, or remained constant as the fuel sulfur level was increased. The effect of fuel sulfur on tailpipe emissions and the catalyst monitor was also measured for two LEVs equipped with Pd-only catalyst technology (a 1997MY Escort and a 1998MY Crown Victoria). For both vehicles, the effect of the fuel sulfur on the rear HEGO sensor response characteristics dominated; as the fuel sulfur level was increased, tailpipe emissions increased, but the rear HEGO sensor index decreased.

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.

Introduction of an array of new electrical and electronic features into future vehicles is generating vehicle electrical power requirements that exceed the capabilities of today's 14 volt electrical systems. In the near term (5 to 10 years), the existing 14V system will be marginally capable of supporting the expected additional loads with escalating costs for the associated charging system. However, significant increases in vehicle functional content are expected as future requirements to meet longer-term (beyond 10 years) needs in the areas of emission control, fuel economy, safety, and passenger comfort. A higher voltage electrical system will be required to meet these future requirements. This paper explores the functional needs that will mandate a higher voltage system and the benefits derivable from its implementation.

Rapid Prototyping, Fabrication and Tooling is a process that blends a series of technologies (machines, tools, and methods) capable of generating physical objects directly from a CAD database. The process dramatically reduces the time spent during product development by allowing for fast visualization, verification, iteration, optimization, and fabrication of parts and tools. Many new techniques of tooling have been and are being developed by using rapid fabricated parts. These are having a dramatic impact on both timing and costs throughout the automotive industry. One area that these methods can be utilized to their full potential is motorsports. Of particular interest is the growing use of bridge tooling to provide first article through production intent parts that promote cost effective changes.

Robust on-board diagnosis of emission catalyst performance requires the development of artificially damaged "threshold" catalysts that accurately mimic the performance of damaged catalysts in customer use. The threshold catalysts are used by emissions calibrators to determine fore-aft exhaust oxygen sensor responses that indicate catalyst failure. Rather than rely on traditional trial-and-error processes to generate threshold catalysts, we have used a DFSS (Design For Six-Sigma) approach that explores, at a research level, the relationship between oxygen storage capacity (OSC) of the catalyst (i.e., the fundamental property dictating the response of the aft oxygen sensor) and key process input variables: high-temperature exposure, phosphorus poisoning, and catalyst "recovery."

Multidisciplinary design optimization (MDO) methods are commonly used for weight reduction in automotive industry. The design variables for MDO are often selected based on critical parts, which usually are close to optimal after many design iterations. As a result, the real weight reduction benefit may not be fully realized due to poor selection of design parameters. In addition, most applications require running design of experiments (DOE) to explore the full design space and to build response surfaces for optimization. This approach is often too costly if too many design variables are simultaneously considered. In this research, an alternative approach to address these issues is presented. It includes two optimization phases. The first phase uses critical parts for design iterations and the second phase use non-critical for weight reduction. A vehicle body structure is used to demonstrate the proposed strategy to show its effectiveness.

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.

Ignoring the impact of water condensation leads to incorrect temperature simulation during cold start, and this can lead to questions being raised about the overall accuracy of aftertreatment simulation tools for both temperature and emission predictions. This report provides a mathematical model to simulate the condensation and evaporation of water in exhaust after-treatment devices. The simulation results are compared with experimental data. Simulation results show that the temperature profiles obtained using the condensation model are more accurate than the profiles obtained without using the condensation model. The model will be very useful in addressing questions that concern the accuracy of the simulation tool during cold-start and heating up of catalysts, which accounts for the conditions where tailpipe emission issues are most significant.

Hybrid electric vehicle (HEV) powertrains have become key to developing environmentally friendly and fuel efficient vehicles. As such, companies are continually investing in developing new hybrid powertrain architectures. Ford Motor Company has developed a new “Dual-Drive” full hybrid electric vehicle that overcomes some attribute deficiencies of existing hybrid powertrain architectures due to the kinematic arrangement of the engine, motors and driveline components. This hybrid powertrain is comprised of conventional powertrain components as its base with an electric motor on the rear axle, and a crank integrated starter generator, engine and transmission on the front axle. It forms a complex configuration which provides fuel economy improvement over a conventional powertrain.

Lookup tables and functions are widely used in real-time embedded automotive applications to conserve scarce processor resources. To minimize the resource utilization, these lookup tables (LUTs) commonly use custom data structures. The lookup function code is optimized to process these custom data structures. The legacy routines for these lookup functions are very efficient and have been in production for many years. These lookup functions and the corresponding data structures are typically used for calibration tables. The third-party calibration tools are specifically tailored to support these custom data structures. These tools assist the calibrators in optimizing the control algorithm performance for the targeted environment for production. Application software typically contains a mix of both automatically generated software and manually developed code. Some of the same calibration tables may be used in both auto generated and hand-code [ 1 ] [ 2 ].