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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.

The durability certification is one of the critical paths of a mass production vehicle project. For structural components, the development and the execution of experimental tests supported by finite element method (FEM) became mandatory for implementation time reduction, especially when on-board diagnoses (OBD) legislation turns even small cracks in severe structural failures. This job aims to show a simulation method of structural efforts in an exhaust system on a test bench. The exhaust pipe is previously analyzed with FEM and the critical points are instrumented with strain gage in vehicles. The strains are measured and its values reproduced in a dynamometer bench using a shaker with adjustable amplitudes. Therefore, difficulties to reproduce temperature and strain were overcome and the test shows repeatability. The variation of shaker device amplitude makes it possible to define the life cycle curve of the part.

In response to environmental and fossil fuel usage concerns, the automotive industry will gradually move from Hybrid Electric Vehicles (HEV) which includes a shift of internal combustion engines toward Zero Emissions Vehicles (ZEV). Refinement is an important aspect in the successful adoption of any new technology and ZEV brings its own NVH challenges owing to the unique dynamic characteristics of the powertrain and driveline system. This paper presents considerations for addressing dynamic driveline NVH issues that are common to 100% electric vehicles; issues that manifest themselves as groans, rattles and clunks. A dynamic torsional analytical model of the powertrain & driveline will be presented. The analytical model served as the baseline for an extensive parametric study using the Genetic Algorithm (GA) technique, whereby the effectiveness of practical countermeasures was investigated.

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.

Weibull analysis is widely used in many industries to predict the fatigue life of different components. Three typical Weibull distributions are introduced in this paper. The application of two parameter Weibull distribution in exhaust component fatigue life prediction is presented. Potential issues in component testing are addressed. Criteria are provided to define normal test data, and when replacement of a tested sample is required. The studies demonstrate that Weibull method is effective to predict component R90C90 life. However, data investigation and processing are critical to predict component life properly. The predicted fatigue life may differ by more than an order of magnitude if the sample life data is unrepresentative of the testing and manufacturing conditions.

Durability performance is one of the most important aspects of exhaust system design. Great effort has been expended to develop the ability to accurately and quickly predict the durability of the system in the early development stages. Welded joints in an exhaust system are the most prone to failure; however, the fatigue life of a welded joint is usually much more difficult to predict than that of a base material. The difficulty of predicting the fatigue life of a welded structure lies primarily in the variability associated with the elements of a weldment, including differing material and gap requirements, notch generation, residual stresses, and imprecise application, among others. The experts at the Battelle Center for Welded Structures Research have developed an approach to predict the fatigue life of a welded structure known as the Verity method.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

In automotive testing, a chassis dynamometer is typically used, during cell testing, to evaluate vehicle performance by simulating actual driving conditions. The use of indoor cell testing has the advantage of running controlled tests where the cell temperature and humidity and solar loads can be well controlled. Driving conditions such as vehicle speed, wind speed and grade can be also controlled. Thus, repeated tests can be conducted with minimum test variations. The tractive effort required at the wheels of a vehicle for a given set of operating parameters is determined by taking into account a set of variables which affect vehicle performance. The forces considered in determination of the tractive effort include the constant friction force, variable friction force due to mechanical and tire friction, forces due to inertia and forces due to aerodynamic and wind effects. In addition, forces due to gravity are considered when road grades are simulated.

In this study, a full vehicle with durability tire model established with ADAMS is applied to simulate the dynamic behavior of the vehicle under severe rough road proving ground events, where the shock force-velocity characteristics are modeled as nonlinear curves and multi-stage representations, respectively. The shock forces and velocities at each corner are resolved and through full factorial DOE, the shock forces and velocities response surface models are established to analyze the sensitivities of shock force and velocity to the shock damping characteristics.

Accurate motion prediction can be used to evaluate vibrations at seat track and steering wheel. This paper presents the prediction and correlation of truck frame motion from wheel force transducer (WFT) measurements. It is assumed that the method can be used to predict vibrations at seat track and steering wheel for unibody vehicles. Two durability events were used for calculation. WFT measurements were used as inputs applied on frame from suspension. Frame loads were then used as inputs to calculate frame motions using a FEA approach. The predicted frame motions are represented by four exhaust hangers and they are compared with measured motions of the same locations. The correlations include displacement, velocity, and acceleration. It is shown that good correlations are obtained in velocity and displacement. Acceleration shows bigger differences than velocity and displacement.

Automotive electronics and software is getting complex day by day. More and more features and functions are offered and supported by software in place of hardware. Communication is carried out on the CAN bus instead of hard wired circuits. This architectural transition facilitates lots of flexibility, agility and economy in development. However, it introduces risk of unexpected failures due to insufficient testing and million of possible combinations, which can be created by users during the life time of a product. Model based development supports an effective way of handling these complexities during simulation and also provide oracle for its validation. Based on priorities and type of applications, test vectors can be auto generated and can be used for formal verification of the models. These auto-generated test vectors are valuable assets in testing and can be effectively reused for target hardware (ECU) verification.

Exhaust durability is an important measure of quality, which can be predicted using CAE with accurate mount loads. This paper proposes an innovative method to calculate these loads from measured mount accelerations. A Chrysler vehicle was instrumented with accelerometers at both ends of its four exhaust mounts. The vehicle was tested at various durability routes or events at DaimlerChrysler Proving Grounds. These measured accelerations were integrated to obtain their velocities and displacements. The differences in velocities and displacements at each mount were multiplied by its damping and stiffness rates to obtain the mount load. The calculation was conducted for all three translational directions and for all events. The calculated mount loads are shown within reasonable range. Along with CAE, it is suggested to explore this method for exhaust durability development.

This paper describes a lightweight magnesium intensive automobile body structure concept developed at DaimlerChrysler to support a high fuel-efficiency vehicle project. This body structure resulted in more than 40% weight reduction over a conventional steel structure while achieving significantly improved structural performance as evaluated through CAE simulations. A business case analysis was conducted and showed promising results. One concept vehicle was built for the purpose of demonstrating concept feasibility. The paper also identifies areas for further development to enable such a vehicle to become a production reality at a later time.

For the purposes of analyzing and understanding the general effects of a set of different vehicle attributes on overall crash outcome a fleet model is used. It represents the impact response, in a one-dimensional sense, of two vehicle frontal crashes, across the frontal crash velocity spectrum. The parameters studied are vehicle mass, stiffness, intrusion, pulse shape and seatbelt usage. The vehicle impact response parameters are obtained from the NCAP tests. The fatality risk characterization, as a function of the seatbelt use and vehicle velocity, is obtained from the NASS database. The fatality risk is further mapped into average acceleration to allow for evaluation of the different vehicle impact response parameters. The results indicate that the effects of all the parameters are interconnected and none of them is independent. For example, the effect of vehicle mass on fatality risk depends on seatbelt use, vehicle stiffness, available crush, intrusion and pulse shape.

In this paper, cradle design functional objectives are briefly reviewed and a durability development process is proposed focusing on the cradle loads, stress, strain, and fatigue life analysis. Based upon the proposed design process, sample isolated and non-isolated cradle finite element (FE) models for a uni-body sport utility vehicle (SUV) under different design phases are solved and correlated with laboratory bench and proving ground tests. The correlation results show that the applied cradle models can be used to accurately predict the critical stress spots and fatigue life under various loading conditions.

The durability of fuel tank straps is essential for vehicle safety. Extensive physical tests are conducted to verify designs for durability. Due to the complexity of the loads and the fuel-to-tank interaction, computer-aided-engineering (CAE) simulation has had limited application in this area. This paper presents a CAE method for fuel tank strap durability prediction. It discusses the analytical loads, modeling of fuel-to-tank interaction, dynamic analysis methods, and fatigue analysis methods. Analysis results are compared to physical test results. This method can be used in either a fuel-tank-system model or a full vehicle model. It can give directional design guidance for fuel tank strap durability in the early stages of product development to reduce vehicle development costs.

This paper introduces a reliable method to calculate body mount loads from wheel-force-transducer (WFT) measurements on framed vehicles. The method would significantly reduce time and cost in vehicle development process. The prediction method includes two parts: Hybrid Load Analysis (HLA) that has been used by DaimlerChrysler Corporation and Body Mount Load Analysis (BMLA) that is introduced by this paper for the first time. The method is validated on a body-on-frame SUV and a pickup truck through one proving ground events. The example shown in this paper is for a SUV and one of the most severe events. In HLA, the loads at suspension-to-frame attachments are calculated from spindle loads measured by WFT. In BMLA, body mount loads were calculated using outputs of HLA with detailed finite-element-modeled frame and body. The loads are compared with measured body mount loads. The comparisons are conducted in range, standard deviation (S.D.), and fatigue pseudo-damage.

This study will analyze existing procedures and commercially available testing equipment for low temperature impact testing of plastic materials. The results of this analysis will be used to identify continuous improvement opportunities and develop recommended practices for low temperature impact testing to support ongoing efforts to meet related durability and performance needs of automotive components.

It is often necessary to dynamically test a big vehicle part such as a rail tip at component level in high speed. Such a big part can be crush tested dynamically using two sled carriers. The methodology is shown and discussed here, and equations are developed to help determine required parameters such as sled velocity and weights. Test results using a truck rail tip are shown and compared to full vehicle test results for correlation.

For a vehicle or repairable system, incidents (conditions) are neither necessarily independent nor identically distributed. Therefore, traditional statistical distributions like Weibull, Normal, etc, are no longer valid to estimate reliability. The Non-homogeneous Poisson process (NHPP) model can be used to predict reliability and warranty of the field product. It can also measure the reliability improvement during the development cycle. The NHPP model is discussed in this paper. In applying a NHHP model to reliability data on a repairable system, one may have few or no failures. This paper presents the I/100 and reliability derivations when the parameter β in the ROCOF function is assumed to have a known value.