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The application of state-of-art thermoelectric generator (TEG) in automotive engine has potential to reduce more than 2% fuel consumption and hence the CO2 emissions. This figure is expected to be increased to 5%~10% in the near future when new thermoelectric material with higher properties is fabricated. However, in order to maximize the TEG output power, there are a few issues need to be considered in the design stage such as the number of modules, the connection of modules, the geometry of the thermoelectric module, the DC-DC converter circuit, the geometry of the heat exchanger especially the hot side heat exchanger etc. These issues can only be investigated via a proper TEG model. The authors introduced four ways of TEG modelling which in the increasing complexity order are MATLB function based model, MATLAB Simscape based Simulink model, GT-power TEG model and CFD STAR-CCM+ model. Both Simscape model and GT-Power model have intrinsic dynamic model performance.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

About 10 years ago in the US, an automotive OEM consortium formed the Oxygenated Fuels Task Force which in turn created the SAE Cooperative Research Project Group 2 to develop a simple rational method for qualifying materials. At that time the focus was Methanol/Gasoline blends. This work resulted in SAE J1681, Gasoline/Methanol Mixtures for Materials Testing. Recently this document was rewritten to make it the single, worldwide, generic source for fuel system test fluids. The paper will describe the rationale for selecting the fuel surrogate fluids and why this new SAE standard should replace all existing test fuel or test fluid standards for fuel system materials testing.

The small-displacement direct-injection (DI) diesel engine is a prime candidate for future transportation needs because of its high thermal efficiency combined with near term production feasibility. Ford Motor Company and FEV Engine Technology, Inc. are working together with the US Department of Energy to develop a small displacement DI diesel engine that meets the key challenges of emissions, NVH, and power density. The targets for the engine are to meet ULEV emission standards while maintaining a best fuel consumption of 200g/kW-hr. The NVH performance goal is transparency with state-of-the-art, four-cylinder gasoline vehicles. Advanced features are required to meet the ambitious targets for this engine. Small-bore combustion systems enable the downsizing of the engine required for high fuel economy with the NVH advantages a four- cylinder has over a three-cylinder engine.

This work was concerned with evaluation of the performance and emissions of potential future biofuels during advanced spark ignition engine operation. The fuels prepared included three variants of gasoline, three gasoline-ethanol blends and a gasoline-butanol fuel altogether covering a range of oxygen mass concentrations and octane numbers to identify key influencing parameters. The combustion of the fuels was evaluated in a turbocharged multi-cylinder direct fuel injection research engine equipped with a standard three-way catalyst and an external EGR circuit that allowed use of either cooled or non-cooled EGR. The engine operating effects studied at both part and boosted high load conditions included fuel injection timing and pressure, excess air tolerance, EGR tolerance and spark retard limits. A number of blends were also mapped at suitable sites across the European drive cycle under downsized engine conditions.

This paper presents an enhanced Bayesian based model validation method together with probabilistic principal component analysis (PPCA). The PPCA is employed to address multivariate correlation and to reduce the dimensionality of the multivariate functional responses. The Bayesian hypothesis testing is used to quantitatively assess the quality of a multivariate dynamic system. Unlike the previous approach, the differences between test and CAE results are used for dimension reduction though PPCA and then to assess the model validity. In addition, physics-based thresholds are defined and transformed to the PPCA space for Bayesian hypothesis testing. This new approach resolves some critical drawbacks of the previous method and provides desirable properties of a validation method, e.g., symmetry. A dynamic system with multiple functional responses is used to demonstrate this new approach.

To meet a need identified in earlier valve train friction testing, a tappet rotation monitor was developed and implemented on a cam/tappet tribometer. The system was based on reflecting a light beam from a rotating and translating segmented surface onto a phototransistor. The resulting output was then processed by linear frequency to voltage conversion and multiple cycle integration. The experimental apparatus, signal processing circuit, and the testing circuit are presented. The multiple cycle integration was found to yield average tappet rotation as a function of cam shaft position. These results agreed well with earlier attempts to measure tappet rotation with high speed photography, were repeatable, and correlated with cam shaft speed. Some selected data is also presented which indicates that tappet rotation reduces cam/tappet friction.

A vehicle's evaporative emission control system is continuously working, even when the vehicle is not running, due to generation of vapors from the fuel tank during ambient temperature variations. Diurnal temperature cycles cause the fuel tank to breathe the fuel vapor in and out, and thus the activated carbon canister is constantly loading and purging the hydrocarbon vapors. This paper discusses a study undertaken at Ford to evaluate the relationship between carbon canister condition and fuel tank vapor generation during diurnal cycles. The results of an extensive set of experiments are presented, and the data from these experiments are compared to the output of a fuel vapor system model also developed at Ford. Key parameters relating to the migration of hydrocarbons during the experimental conditions studied, including initial canister condition, canister volume, and canister geometry, are discussed.

Vehicle body with aluminum riveted construction instead of steel welded one will be a big challenge to NVH. In this paper, aluminum and steel rails with the dimensions similar to the rear rail portion of a typical mid-size sedan were fabricated. Rivets were used to assemble the aluminum rails while welds were used to assemble the steel rails. Adhesive, rivet/weld spacing, and rivet/weld location were the three major factors to be studied and their impact on NVH were investigated. The DOE matrix was developed using these three major factors. Modal tests were performed on those rails according to the DOE matrix. The FEA models corresponding to the hardware were built. CAE modal analysis were performed and compared with test data. The current in-house CAE modeling techniques for spot weld and adhesive were evaluated and validated with test data.

Various methods are available to predict future cylinder air charge for improved air/fuel control. However, there can never be perfect prediction. This paper presents an algorithm to correct for imperfect cylinder charge prediction. This is done by expanding the air/fuel control boundary to include the catalyst, and correcting prediction errors as soon as possible using small corrective changes to later cylinder fuel inputs. The method was experimentally tested and showed improved air/fuel control as indicated by reduced variability of catalyst downstream air/fuel ratio. Additional vehicle testing showed potential to further reduce emissions.

An analytical method for determining engine torque harmonics is presented. The approach employs an engine cycle simulation model to calculate instantaneous cylinder pressure for each operating condition based on engine characteristics that can be determined experimentally and/or analytically. Cylinder pressure is converted to instantaneous torque from which harmonics are determined using an FFT algorithm. A description of the cycle simulation model, including required data, is presented. The method is validated by presenting correlation results at a number of operating conditions (i.e. engine speeds and loads) comparing analytical versus test driveline torque harmonics. Finally, limitations in the method as well as possible extensions to the method are discussed.

The fuel economy and emissions performance of a Diesel engine is strongly influenced by the fuel injection process. This paper presents early results of an experimental investigation into diesel spray development carried out in a novel in-house developed optical pressure chamber capable of operating at pressure up to 50 bar and temperatures up to 900 K. The spatial evolution of a diesel spray tends to experience many transitory macroscopic phenomena that directly influence the mixing process. These phenomena are not considered highly reproducible and are extremely short lived, hence recording and understanding these transient effects is difficult. In this study, high-speed backlight-illuminated imaging has been employed in order to capture the transient dynamics of a short signal duration diesel spray injected into incremental back pressures and temperatures reaching a maximum of 10 bar and 473 K respectively.

In the current design process, the designer generates the detailed geometry of the component based on experience. Prototypes of this design are built and tested to verify the performance. This design - build - test iterative process is continued until performance targets/criteria are met. Computer Aided Engineering is often used to verify the design. This paper presents a new product development process to substantially reduce the number of design - analysis - build - test iterations. This Upfront Analysis Driven Design process incorporates several state of the art technologies in finite element structural analysis, optimization, and Computer Aided Design. This process ensures a near optimum design in the first design level itself.

Closed cell foam has been used for filling vehicle pillar cavities at select locations to block road noise transmitted through pillars. In the past, most pillar foam implementations in vehicle programs were driven by subjective improvements in interior sound. In this study road test results are used to correlate a detailed CAE (Computer-Aided Engineering) model based on the statistical energy analysis method. Noise reduction characteristics of pillar with a number of foam block fillings were then studied using the CAE model. The CAE models provided means to model and understand the mechanism of noise energy flow through pillar cavities. A number of insightful conclusions were obtained as result of the study.

Ford Motor Company has developed a Computer Aided Engineering (CAE) process for predicting NVH performance of its forward model vehicles. This process utilizes simplified models to drive the upstream design effort before detailed drawings are available and then verifies the design with detailed models. The process can be used to determine and evaluate the most effective design modifications and to assist in resolving downstream problems after prototype vehicle evaluations. This paper outlines this process and also gives examples from the work which was done to support the new 1992 Econoline design.

After establishing the performance requirements and initial design assumptions, CAE concept models are used to set targets for major structural components to achieve desirable crash performance. When the designs of these major components become available they are analyzed in detail using nonlinear crash finite element models to evaluate their performance. All these components are assembled together later in a full car model to predict the overall vehicle crash performance. If the analysis shows that the targets are met, the design drawings are released for prototype fabrication. When CAE tools are effectively used, it will reduce product development cycle time and the number of prototypes. Crash analysis methodology has been validated and applied for steel automotive product development. Recently, aluminum is replacing steel for lighter and more fuel efficient automobiles. In general aluminum has quite different performance from steel, in particular with lower ductility.

A CAE method has been developed to address engine tonal noise and whine due to the excitation from a gerotor oil pump. The method involves a multidisciplinary approach including CFD, frequency-response structural analysis and acoustic analysis. The results from the application of the method applied to a couple of pumps with different designs are discussed. Engine tonal noise improvement through reduction in the excitation source from the pump and also stiffening the excitation path from the pump to the engine are studied. The effect of component modal alignment with oil pump orders is addressed as well.

Automotive fuel vapor emissions that would otherwise evaporate into the atmosphere are being captured in activated carbon vapor storage canisters. Fuel vapor is loaded into the canisters via a direct connection to the fuel tank vapor dome. Hydrocarbons are desorbed from the activated carbon into the engine combustion cylinders using engine intake vacuum. The carbon canister capacity requirements have increased in recent years in order to meet both Enhanced Evaporative Emission regulations and the Clean Air Act emission requirements for On-board Refueling Vapor Recovery (ORVR). The higher capacity requirements have generated the need for larger volume canisters that can meet the emission requirements and still be designed within the space and packaging limits of the vehicle application. This paper describes the simultaneous engineering approach used at Ford Motor Company to design a large volume cylindrical shaped carbon canister.

An experimental study of the performance of a reverse tumble, DISI engine is reported. Specific fuel consumption and engine-out emissions have been investigated for both homogeneous and stratified modes of fuel injection. Trends in performance with varying AFR, EGR, spark and injection timings have been explored. It is shown that neural networks can be trained to describe these trends accurately for even the most complex case of stratified charge operation with exhaust gas recirculation.