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Cam-phasing is increasingly considered as a feasible Variable Valve Timing (VVT) technology for production engines. Additional independent control variables in a dual-independent VVT engine increase the complexity of the system, and achieving its full benefit depends critically on devising an optimum control strategy. A traditional approach relying on hardware experiments to generate set-point maps for all independent control variables leads to an exponential increase in the number of required tests and prohibitive cost. Instead, this work formulates the task of defining actuator set-points as an optimization problem. In our previous study, an optimization framework was developed and demonstrated with the objective of maximizing torque at full load. This study extends the technique and uses the optimization framework to minimize fuel consumption of a VVT engine at part load.

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.

Over the past five years, the US Automotive Materials Partnership (USAMP) has brought together representatives from DaimlerChrysler, General Motors, Ford Motor Company and over 40 other participant companies from the Mg casting industry to create and test a low-cost, Mg-alloy engine that would achieve a 15 - 20 % Mg component weight savings with no compromise in performance or durability. The block, oil pan, and front cover were redesigned to take advantage of the properties of both high-pressure die cast (HPDC) and sand cast Mg creep- resistant alloys. This paper describes the alloy selection process and the casting and testing of these new Mg-variant components. This paper will also examine the lessons learned and implications of this pre-competitive technology for future applications.

Current engine development processes typically involve extensive steady-state and simple transient testing in order to characterize the engine's fuel consumption, emissions, and performance based on several controllable inputs such as throttle, spark advance, and EGR. Steady-state and simple transient testing using idealistic load conditions alone, however, is no longer sufficient to meet powertrain development schedule requirements. Mapping and calibration of an engine under transient operation has become critically important. And, independent engine development utilizing accelerated techniques is becoming more attractive. In order to thoroughly calibrate new engines in accelerated fashion and under realistic transient conditions, more advanced testing is necessary.

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.

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.

In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

Variable Valve Actuation (VVA) technology provides high potential in achieving high performance, low fuel consumption and pollutant reduction. However, more degrees of freedom impose a big challenge for engine characterization and calibration. In this study, a simulation based approach and optimization framework is proposed to optimize the setpoints of multiple independent control variables. Since solving an optimization problem typically requires hundreds of function evaluations, a direct use of the high-fidelity simulation tool leads to the unbearably long computational time. Hence, the Artificial Neural Networks (ANN) are trained with high-fidelity simulation results and used as surrogate models, representing engine's response to different control variable combinations with greatly reduced computational time. To demonstrate the proposed methodology, the cam-phasing strategy at Wide Open Throttle (WOT) is optimized for a dual-independent Variable Valve Timing (VVT) engine.

This investigation evaluated different pressure transducers in one cylinder to examine the combustion measurement differences between them simultaneously. There were a total of eleven transducers ranging in both diameter and type of transducer (piezo-electric, piezoresistive, and optical). Furthermore, the sensors differed in the methodology for minimizing signal distortion due to temperature. This methodology could take the form of various size mounting passages, heat shields, watercooling or heat transfer paths. To evaluate the sensors, different engine operating conditions were conducted, focusing at full load and low speeds. Other hardware configurations of the same engine family were used to exaggerate the combustion environment, specifically a tumble-motion plate and turbocharging.

Mode management is an essential part of the design process for NVH performance. System resonances must be sufficiently separated to minimize interaction from source inputs and each other [1]. Such resonances are typically determined through experimental modal testing conducted in a lab environment under controlled and repeatable conditions. Global vehicle and suspension system response demonstrate soft nonlinear behavior, however. Their resonant frequencies may thus decrease under on-road input not reproducible in a lab environment. Subsequently, mode management charts derived from lab testing may not be representative of the vehicle's on-road dynamic response. This paper presents modal model determination methodologies, and examines suspension system and vehicle global dynamic response under lab modal test and operating conditions. Vehicle suspension modes measured under static and dynamic (rolling) conditions will be compared.

Different methodologies to test transfer case imbalance were investigated in this study. One method utilized traditional standard single plane and two plane methods to measure the imbalance of the transfer case when running it on a dynamic balance machine at steady RPM, while a second method utilized accelerometers and a laser vibrometer to measure vertical vibration on the transfer case when running it on a dynamic balance machine in 4 Hi open mode during a run up from 1000 to 4000 RPM with a 40 RPM difference between the input and output shaft speeds. A comparison of all of the measurements for repeatability and accuracy was done with the goal of determining an appropriate and efficient method that generates the most consistent results. By using the traditional method, the test results were not repeatable. This may be due to the internal complexity of transfer cases. With the second method, good correlation between the measurements was obtained.

It is becoming increasingly difficult to obtain good repeatability from running lab vehicle correlation testing, since vehicle variability is so significant at the Low ULEV and SULEV emissions levels. These new emission standards are becoming so stringent that it makes it very difficult to distinguish whether a problem is a result of vehicle variability, test cell sampling or the analytical system. A vehicle exhaust emission simulator (VEES) developed by Horiba, can simulate emissions from low emitting gasoline vehicles by producing tailpipe flow rates containing emissions constituents ( HC, CH4, CO, NOx, CO2 ) injected at the tailpipe flow stream via mass flow controllers.

Faced with an ever increasing supply of road load data and no reasonable means to keep track of it, Managing Road Load Data and The Process is about one engineer's charge to deliver a solution. This paper summarizes the approach taken by this engineer and his team to produce a system that not only provides a place to store their data, but facilitates the entire data collection, validation and dissemination process. By following the steps outlined in this document, virtually every opportunity for improvement will be identified. That is, the process is thoroughly explored; the wants and needs of the users are identified, and then, as warranted, turned into functional elements of the system. The result is a central repository that is accessible to all and with the capability of significantly reducing cost and timing. The development process presented here is not a difficult one to accomplish, but does require keeping track of a lot of detail. It can therefore be quite time consuming.

Tire stiffness can have a significant effect on the spindle and component loads. While its’ effect on the component loads may show a different trend. This paper deals with data acquisition loads using Wheel Force Transducer (WFT) with 17 inch, 18 inch and 20 inch tires and shows how the spindle loads changed for different tire. These loads are applied on the analytical suspension model to generate both component and the body attachment loads. Some of the measured channels are correlated for all the wheel sizes for multiple events to ensure the confidence in the model. It is found that even if spindle loads are increased with tire stiffness, the component loads do not necessarily show a similar trend. This paper studies why higher spindle forces do not always give higher component loads and what are the possible alternatives one may look into to shortlist or select one set of loads over the other.

A continuously variable lift, duration and phase mechanical lift mechanism is described, as applied to the intake valvetrain of a SOHC, 4-valve per cylinder, four-cylinder production engine. Improvements in fuel economy were sought by reduction of pumping losses and improved charge preparation, and optimization of WOT torque was attempted by variation of intake valve closing angle. Adjustment of the mechanism is achieved by movement of the pivot shaft for the rocker arms. The relationship between lift, duration and phase is predetermined at the design stage, and is fixed during operation. There is considerable design flexibility to achieve the envelope of lift curves deemed desirable. The operation of the mechanism is described, as are the development procedure, testing with fixed cams, some cycle simulation, friction testing on a separate rig and dyno testing results for idle, part load and WOT.

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.

A project was undertaken to demonstrate an engine stop/start at idle system utilizing a 12 volt Belt driven Starter Generator (BSG). The system was developed on a production four cylinder vehicle to determine emissions, driveability, and fuel economy impact.

An accurate air flow rate model is critical for high-quality air-fuel ratio control in Spark-Ignition engines using a Three-Way-Catalyst. Emerging Variable Valve Timing technology complicates cylinder air charge estimation by increasing the number of independent variables. In our previous study (SAE 2004-01-3054), an Artificial Neural Network (ANN) has been used successfully to represent the air flow rate as a function of four independent variables: intake camshaft position, exhaust camshaft position, engine speed and intake manifold pressure. However, in more general terms the air flow rate also depends on ambient temperature and pressure, the latter being largely a function of altitude. With arbitrary cam phasing combinations, the ambient pressure effects in particular can be very complex. In this study, we propose using a separate neural network to compensate the effects of altitude on the air flow rate.