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Vehicle target setting is an evolving process based on continually changing internal (management, standards) and external (competitive and legal) requirements. In addition to evolving requirements, the process for establishing and documenting targets may not be clear. The objective of this paper is to detail the overall process of target setting, the critical factors to consider, and key definitions for each stage of the process. It will describe the complete process from early competitive benchmarking to final verification testing. Setting targets for a vehicle requires definition and thorough benchmarking of the competition, an understanding of the key attributes used to describe the vehicles' performance, and a clearly defined set of requirements. These requirements will be regulatory, corporate and competitively based and grouped by clearly defined, customer perceived attributes which can be cascaded to specific vehicle systems.

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.

Having, by now, introduced several new vehicles that comply with FMVSS 202a, manufacturers are reporting an increased number of complaints from consumers who find that the head restraint is too close; negatively affecting their posture. It is speculated that one of the reasons that head restraints meeting the new requirement are problematic is that the FMVSS backset measurement is performed at a back angle that is more reclined than the back angle most drivers choose and the back angle at which the seat / vehicle was designed. The objective of this paper is to confirm this hypothesis and elaborate on implications for regulatory compliance in FMVSS 202a.

Incremental Sheet Forming (ISF) is an emerging sheet metal prototyping technology where a part is formed as one or more stylus tools are moving in a pre-determined path and deforming the sheet metal locally while the sheet blank is clamped along its periphery. A deformation analysis of incremental forming process is presented in this paper. The analysis includes the development of an analytical model for strain distributions based on part geometry and tool paths; and numerical simulations of the forming process with LS-DYNA. A skew cone is constructed and used as an example for the study. Analytical and numerical results are compared, and excellent correlations are found. It is demonstrated that the analytical model developed in this paper is reliable and efficient in the prediction of strain distributions for incremental forming process.

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.

Small crack growth from notches under variable amplitude loading requires that crack opening stress be followed on a cycle by cycle basis and taken into account in making fatigue life predictions. The use of constant amplitude fatigue life data that ignores changes in crack opening stress due to high stress overloads in variable amplitude fatigue leads to non-conservative fatigue life predictions. Similarly fatigue life predictions based on small crack growth calculations for cracks growing from flaws in notches are non-conservative when constant amplitude crack growth data are used. These non-conservative predictions have, in both cases, been shown to be due to severe reductions in fatigue crack closure arising from large (overload or underload) cycles in a typical service load history.

Dynamic vehicle loads play critical roles for automotive controls including battery management, transmission shift scheduling, distance-to-empty predictions, and various active safety systems. Accurate real-time estimation of vehicle loads such as those due to vehicle mass and road grade can thus improve safety, efficiency, and performance. While several estimation methods have been proposed in literature, none have seen widespread adoption in current vehicle technologies despite their potential to significantly improve automotive controls. To understand and bridge the gap between research development and wider adoption of real-time load estimation, this paper assesses the accuracy and performance of four estimation methods that predict vehicle mass and/or road grade.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

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.

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.

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.

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.

The efforts of the ISO “Test Variability Task Force” have been aimed at improving the understanding and at reducing brake dynamometer test variability during performance testing. In addition, dynamometer test results have been compared and correlated to vehicle testing. Even though there is already a vast amount of anecdotal evidence confirming the fact that different procedures generate different friction coefficients on the same brake corner, the availability of supporting data to the industry has been elusive up to this point. To overcome this issue, this paper focuses on assessing friction levels, friction coefficient sensitivity, and repeatability under ECE, GB, ISO, JASO, and SAE laboratory friction evaluation tests.

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.

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.

A task group within the SAE Automotive Corrosion and Protection (ACAP) Committee continues to pursue the goal of establishing a standard test method for in-laboratory cosmetic corrosion evaluations of finished aluminum auto body panels. The program is a cooperative effort with OEM, supplier, and consultant participation and is supported in part by USAMP (AMD 309) and the U.S. Department of Energy. Numerous laboratory corrosion test environments have been used to evaluate the performance of painted aluminum closure panels, but correlations between laboratory test results and in-service performance have not been established. The primary objective of this project is to identify an accelerated laboratory test method that correlates with in-service performance. In this paper the type, extent, and chemical nature of cosmetic corrosion observed in the on-vehicle exposures are compared with those from some of the commonly used laboratory tests

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.

The “Information Age” and the growth of electronics on vehicles are driving forces behind the “personalized” vehicle. The vision is a responsive vehicle where the powertrain, ride, instrumentation and interior can be customized by the driver. A strategy to personalize the vehicle is presented; first, through market research to identify new features, and second, ergonomic design for easy to use displays and controls. Changes in society that are driving forces are discussed along with the counter balancing need for ergonomic design. Approaches to personalization, ergonomic principles, and technologies are presented.

The Service Bay Diagnostic System (SBDS) will be designed to assist the dealership technician in diagnosing and repairing Ford Motor vehicles. The system hardware will be configured around a Service Bay Computer with mass storage capability and auxiliary service equipment. Major system features include: guided service writer/customer interaction, interactive vehicle diagnostics, information management. capabilities, and an additional aid to identifying intermittent failures through the use of a portable over-the-road data acquisition device. In order to assist the technician in properly diagnosing the causal factor, the Service Bay Computer System will also be enhanced through the use of an expert system knowledge base.