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As part of an ongoing technical collaboration between Ford and Rouge Steel Company, a comprehensive study of door slam event was undertaken. The experimental phase of the project involved measurements of accelerations at eight locations on the outer panel and strains on six locations of the inner panel. Although slam tests were conducted with window up and window down, results of only one test is presented in this paper. The CAE phase of the project involved the development of suitable “math” model of the door assembly and analysis methodology to capture the dynamics of the event. The predictability of the CAE method is examined through detailed comparison of accelerations and strains. While excellent agreement between CAE and test results of accelerations on the outer panel is obtained, the analysis predicts higher strains on the inner panel than the test. In addition, the tendency of outer panel to elastically buckle is examined.

A methodology for predicting the fatigue initiation life in metals experiencing multiaxial non-proportional loading is presented. The methodology utilizes nonlinear finite-element analysis to determine the stress distribution of the loaded component. This distribution is used in conjunction with a physically based damage law to determine the cycles to failure. The damage law is based on the fatigue prediction method introduced by Dang Van [1], and further developed by Papadopoulos [2] and Morel [3]. The fatigue damage initiation is treated as the persistent crystalline slip phenomenon taking place on the order of a grain or few grains. The damage variable is chosen to be the accumulated plastic strain at this scale. The initiation life is determined when the damage variable reaches a critical value. The developed methodology is applicable to both in-phase and out-of-phase loading, without any empirical adjustment parameter.

Recently, many authors have attempted to represent an automobile body in terms of experimentally derived frequency response functions (FRFs), and to couple the FRFs with a FEA model of chassis for performing a total system dynamic analysis. This method is called Hybrid FEA-Experimental FRF method, or briefly HYFEX. However, in cases where the chassis model does not include the bushing models, one can not directly connect the FRFs of the auto body to the chassis model for performing a total system dynamic analysis. In other cases when the chassis model includes the bushings, the bushing dynamic rates are modeled as constant stiffness rather than frequency dependent stiffness, the direct use of the HYFEX method will yield unsatisfactory results. This paper describes how the FRF's of the auto body and the frequency dependent stiffness data of the bushings can be combined with an appropriate mathematical formulation to better represent the dynamic characteristics of a full vehicle.

Reducing emissions and the carbon footprint of our society have become imperatives requiring the automotive industry to adapt and develop technologies to strive for a cleaner sustainable transport system and for sustainable economic prosperity. Electrified hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and range extender powertrains provide potential solutions for reducing emissions, but they present challenges in terms of thermal management. A key requirement for meeting these challenges is accurately to predict the thermal loading and temperatures of an internal combustion engine (ICE) quickly under multiple full-load and part-load conditions. Computational Fluid Dynamics (CFD) and thermal survey database methods are used to derive thermal loading of the engine structure and are well understood but typically only used at full-load conditions.

The high-frequency whining noise produced by motors in modern electric vehicles causes a significant issue, leading to annoyance among passengers. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack other noises to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this study, we explored the application of artificial intelligence to optimize the NVH performance of motors during the design phase. Firstly, we selected and modeled three benchmark motor types using Motor-CAD. Machine learning models were trained using Design of Experiment methods to simulate batch runs of Motor-CAD inputs and outputs.

This report explores the relationship of different failure criteria - specifically, surface cracks, stiffness changes, and two-piece failures - on rolled, ductile, cast-iron crankshafts. Crankshaft samples were closely monitored throughout resonant bending fatigue testing and were taken to near complete fracture. By monitoring resonance shifts of the samples during testing, stiffness changes and cracks were monitored. These data showed that an accelerating frequency shift was sufficient to indicate imminent two-piece failure and that this condition can be used as a failure criterion. Fatigue studies on two different crankshafts using this failure criterion were compared to those using a surface crack failure criterion. This comparison showed that using the surface crack failure criterion erroneously decreased the apparent fatigue life of the crankshaft significantly.

Homogenous charge compression ignition (HCCI) engines offer a great potential in achieving high thermal efficiency and extremely low NOx at the same time. However, control of combustion phasing over a wide speed and load range has been a challenge, especially during transient operations. This paper describes work conducted at the National Vehicle and Fuel Emissions Laboratory, which explores the potential use of an HCCI engine as a power plant for a hybrid vehicle. A four-cylinder, 1.9 L commercial diesel engine was modified to operate with port-injected regular grade gasoline in HCCI mode. The combustion phasing is controlled by a combination of boost, EGR and thermal management as a function of engine speed and load. As a stand-alone unit, the engine has demonstrated a wide operation range with efficiency like that of a diesel engine and NOx below 0.2 g/kWh. At room temperature, the engine starts in SI mode and then transitions to HCCI in about 25 seconds.

For electric vehicles (EVs), driving range is one of the major concerns for wider customer acceptance and the cabin climate system represents the most significant auxiliary load for battery consumption. Unlike internally combustion engine (ICE) vehicles, EVs cannot utilize the waste heat from an engine to heat the cabin through the heating, ventilation and air conditioning (HVAC) system. Instead, EVs use battery energy for cabin heating, this reduces the driving range. To mitigate this situation, one of the most promising solutions is to optimize the recirculation of cabin air, to minimize the energy consumed by heating the cold ambient air through the HVAC system, whilst maintaining the same level of cabin comfort. However, the development of this controller is challenging, due to the coupled, nonlinear and multi-input multi-output nature of the HVAC and thermal systems.

If fuel cell vehicles are to compete in the same marketplace as conventional vehicles, then they must provide the consumer with the same, or improved, levels of convenience, comfort, refinement and performance at the same, or lower, price. In 2003/4, several vehicle manufacturers are planning to launch their first commercial fuel cell vehicles onto the market. In this remarkably short timeframe, many systems must be integrated into a vehicle including the fuel cell system plus thermal and water management, cabin heating, ventilation and air-conditioning, control and on-board diagnostics, power electronics, electric motor and gearbox, suspension, steering, braking, refinement and crash protection. This paper presents a range of modelling techniques which allow the user to design and develop key systems, including the power management system, compressed air supply, thermal management and control algorithms.

In light-duty vehicles, there is a fundamental trade-off between fuel consumption and acceleration performance, if other vehicle attributes are held fixed. Earlier econometric studies have estimated the magnitude of this trade-off - the elasticity of fuel consumption with respect to performance - based on historical vehicle data. The majority of these studies assume, a priori, that elasticity is constant across the model year, vehicle power, and technology content. However, there is evidence that the content in the underlying powertrain technology packages is shifting in a way that reduces the value of the elasticity of fuel consumption with respect to performance, such that historical trends would not predict future behavior. This paper presents an alternative strategy for studying vehicle fuel consumption versus performance trade-off.

The growing competition of the automotive market makes more and more necessary the reduction of development time and consequently, the increase of the capacity to quickly respond to the launching of the competitors. One of the most costly phases on the vehicle development process is the field durability test, both in function of the number of prototypes employed and the time needed to its execution. More and more diffused, the fatigue life prediction methods have played an important part in the durability analysis via CAE. Nevertheless, in order they can be reliable and really being able to reduce the development time and cost, they need to be provided with load cases that can accurately represent the field durability tests. This work presents a CAE approach used for light trucks in order to get a reasonable understanding of component durability behavior due to payload increase. In general, road load data is not available for a new payload condition.

By almost any definition, technology has penetrated the U.S. light-duty vehicle fleet significantly in conjunction with the increased stringency of fuel economy and GHG emissions regulations. The physical presence of advanced technology components provides one indication of the efforts taken to reduce emissions, but that alone does not provide a complete measure of the benefits of a particular technology application. Differences in the design of components, the materials used, the presence of other technologies, and the calibration of controls can impact the performance of technologies in any particular implementation. The effectiveness of a technology for reducing emissions will also be influenced by the extent to which the technologies are applied towards changes in vehicle operating characteristics such as improved acceleration, or customer features that may offset mass reduction from the use of lightweight materials.

The 45RFE is a new generation electronically controlled rear wheel drive automatic transmission. It employs real-time feedback, closed-loop modulation of shift functions to achieve outstanding shift quality and to meet demanding durability goals. It uses no shift valves; all friction element applications are effected with high-flow electro-hydraulic solenoid valves. A unique gear train arrangement of three planetary carriers allows all sun gears and annulus gears to have the same number of teeth respectively and use a common pinion gear in all carriers, resulting in significant manufacturing simplification. The three-planetary system is designed for four forward ratios of 3.00, 1.67, 1.00 and 0.75 and one reverse gear ratio equal to the low gear ratio. A fifth ratio of 1.50 is used only in certain kick-down shift sequences for highway passing. A sixth forward ratio, an additional overdrive ratio of 0.67, is available in the hardware.

Loads generated during assembly may cause significant stress levels in components. Under test conditions, these stresses alter the mean stress which in turn, alters the fatigue life and critical stress area of the components as well. This paper describes the Finite Element Analysis (FEA) procedure to evaluate behavior of a cast aluminum wheel subjected to the rotary fatigue test condition as specified in the SAE test procedure (SAE J328 JUN94). Fatigue life of the wheel is determined using the S-N approach for a constant reversed loading condition. In addition, fatigue life predictions with and without clamp loads are compared. It is concluded that the inclusion of clamp load is necessary for better prediction of the critical stress areas and fatigue life of the wheel.

The U.S. Environmental Protection Agency, U.S. Department of Transportation's National Highway and Traffic Safety Administration, and the California Air Resources Board have recently released proposed new regulations for greenhouse gas emissions and fuel economy for light-duty vehicles and trucks in model years 2017-2025. These proposed regulations intend to significantly reduce greenhouse gas emissions and increase fleet fuel economy from current levels. At the fleet level, these rules the proposed regulations represent a 50% reduction in greenhouse gas emissions by new vehicles in 2025 compared to current fleet levels. At the same time, global growth, especially in developing economies, should continue to drive demand for crude oil and may lead to further fuel price increases. Both of these trends will therefore require light duty vehicles (LDV) to significantly improve their greenhouse gas emissions over the next 5-15 years to meet regulatory requirements and customer demand.

Computer applications have been widely used to assist product design. The successes and sophistication of computer aided engineering (CAE) techniques are respectfully recognized in this field. CAE applications in the manufacturing area however are still developing, although the manufacturing community is increasingly starting to pay attentions to computer simulations in its daily workings. This paper will briefly introduce some of these applications and promote awareness of computer simulations in manufacturing area. It contains four main sections: finite element analysis (FEA) in machining fixture design, FEA applications in component assembly, machining process simulations and machining vibrations in the milling operation. Each section comes with a practical case study, potential benefits are identified and conclusions are presented by using an integrated design and analysis approach.

This study attempts to develop a correlation between an airflow motion number, combustion burn rates, and initial flame kernel development. To accomplish this task, several motion plates were evaluated on a flowbench in order to calculate a motion number that would represent the dynamic motion in the combustion chamber. Afterwards, the plates were tested on a spark ignited engine at several part throttle conditions while gathering cylinder pressure measurements. These cylinder pressure measurements would then yield the combustion burn rates for each plate. In addition to the combustion measurements, the flame kernel growth, velocity and direction of the flame kernel were measured using an AVL Visio-flame. Finally, the data was evaluated and an attempt to correlate the motion number of the plates to the different measurements for describing combustion was made.

In this report, the DCX Stress Lab and the Tool Development & Test Support groups investigated automating a resonant bending crankshaft fatigue test. Fatigue testing, in general, is a laborious process since many samples are needed for analysis. This makes development cost and speed dependant on the component test efficiency. In the case of crankshaft resonant bending testing, both cost and speed are influenced by the manual feedback operation needed to run the current procedure. In order to increase the efficiency of this process, this project sought to automate the following tasks: maintaining the load on the part, reacting to resonance changes in the part, mapping resonance changes, logging the number of cycles, and discerning resonance frequency shift failure modes objectively.

The Ethanol-Boosted Direct Injection (EBDI) demonstrator engine is a collaborative project led by Ricardo targeted at reducing the fuel consumption of a spark-ignited engine. This paper describes the design challenges to upgrade an existing engine architecture and the synergistic use of a combination of technologies that allows a significant reduction in fuel consumption and CO₂ emissions. Features include an extremely reduced displacement for the target vehicle, 180 bar cylinder pressure capability, cooled exhaust gas recirculation, advanced boosting concepts and direct injection. Precise harmonization of these individual technologies and control algorithms provide optimized operation on gasoline of varying octane and ethanol content.