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The Opposed Piston Two-Stroke (OPTS) engine has many advantages on power density, fuel tolerance, fuel flexibility and package space. A type of self-balanced opposed-piston folded-crank train two-stroke engine for Unmanned Aerial Vehicle (UAV) was studied in this paper. AVL BOOST was used for the thermodynamic simulation. It was a quasi-steady, filling-and-emptying flow analysis -- no intake or exhaust dynamics were simulated. The results were validated against experimental data. The effects of high altitude environment on engine performance have been investigated. Moreover, the matching between the engine and turbocharger was designed and optimized for different altitude levels. The results indicated that, while the altitude is above 6000m, a multi-stage turbocharged engine system need to be considered and optimized for the UAV.

In this paper, a novel driver model is proposed to track vehicle speed in MIL (Model-in-the-Loop) test system, which has structural consistency with HIL (Hardware-in-the-Loop) test system. First, the MIL test system which contains models of driver, vehicle and test bench is established. Second, according to the connections of the established models in Matlab/Simulink environment, the vehicle speed is calculated in vehicle model. Emphatically, through the deviation between driving cycle speed and calculated vehicle speed, PI controller in driver model adjusts the vehicle speed to ideal point through sending the torque command to drive motor, the ILC (Iterative Learning Control) controller modifies and stores P value of PI controller. Then, in order to obtain the better modification of PI controller, iterative learning control algorithm is deeply researched in term of types and parameters.

Realistically experiencing the sound and vibration data through actually listening to and feeling the data in a full-vehicle NVH simulator remarkably aids the understanding of the NVH phenomena and speeds up the decision-making process. In the case of idle vibration, the sound and vibration of the idle condition are perceived simultaneously, and both need to be accurately reproduced simultaneously in a simulated environment in order to be properly evaluated and understood. In this work, a case is examined in which a perceived idle quality of a vehicle is addressed. In this case, two very similar vehicles, with the same powertrain but somewhat different body structures, are compared. One has a lower subjective idle quality rating than the other, despite the vehicles being so similar.

Lightweighting of vehicle panels enclosing vehicle cabin causes NVH degradation since engine, road, and wind noise acoustic sources propagate to the vehicle interior through these panels. In order to reduce this NVH degradation, there is a need to develop new NVH sound package materials and designs for use in lightweight vehicle design. Statistical Energy Analysis (SEA) model can be an effective CAE design tool to develop NVH sound packages for use in lightweight vehicle design. Using SEA can help engineers recover the NVH deficiency created due to sheet metal lightweighting actions. Full vehicle SEA model was developed to evaluate the high frequency NVH performance of “Vehicle A” in the frequency range from 200 Hz to 10 kHz. This correlated SEA model was used for the vehicle sound package optimization studies. Full vehicle level NVH laboratory tests for engine and tire patch noise reduction were also conducted to demonstrate the performance of sound package designs on “Vehicle A”.

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.

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.

Engine dynamometer testing was performed comparing fuels having different octane ratings and ethanol content in a Ford 3.5L direct injection turbocharged (EcoBoost) engine at three compression ratios (CRs). The fuels included midlevel ethanol “splash blend” and “octane-matched blend” fuels, E10-98RON (U.S. premium), and E85-108RON. For the splash blends, denatured ethanol was added to E10-91RON, which resulted in E20-96RON and E30-101 RON. For the octane-matched blends, gasoline blendstocks were formulated to maintain constant RON and MON for E10, E20, and E30. The match blend E20-91RON and E30-91RON showed no knock benefit compared to the baseline E10-91RON fuel. However, the splash blend E20-96RON and E10-98RON enabled 11.9:1 CR with similar knock performance to E10-91RON at 10:1 CR. The splash blend E30-101RON enabled 13:1 CR with better knock performance than E10-91RON at 10:1 CR. As expected, E85-108RON exhibited dramatically better knock performance than E30-101RON.

Stop/Start technology for conventional automatic transmissions has recently received considerable attention in the automotive industry due to the potential fuel economy, and CO2 emission reduction, benefit at minimal cost. Stop/Start was first developed for manual transmission applications in the EU and Japanese markets. When stop/start is applied to any automatic transmission powertrain the powertrain control challenge is to restart the engine in a manner that simultaneously minimizes the delay in transferring torque to the driven wheel(s) and provides a consistently smooth launch feel with low NVH. It has recently been shown that stop/start can be added to a gas engine powertrain with a conventional torque converter automatic transmission while achieving the desired launch characteristics with minimal change to the powertrain hardware and cost.

A new performance simulation capability has been developed for powersplit HEVs to enable analytical assessment of new engine technologies in the context of HEV system operation and to analyze/understand important system dynamics and control interactions affecting HEV performance. This new capability allows direct simulation with closed-loop controls and the driver, is compatible with Ford standard HEV system simulation capabilities and enables simulation with multiple levels of model fidelity and feature content across the vehicle system. The combined plant Vehicle Model Architecture (VMA) in Simulink was used for the infrastructure. The simulation capability includes a Dymola model of the powersplit transaxle, a Vehicle System Control (VSC) model implemented in Simulink, a high fidelity 2L Atkinson GT-Power engine model, and a simplified representation of the engine controls in Simulink.

This paper proposes an effective nonlinear bicycle model including longitudinal, lateral, and yaw motions of a vehicle. This bicycle model uses a simplified piece-wise linear tire model and tire force tuning algorithm to produce closely matching vehicle trajectory compared to real vehicle for wide vehicle operation ranges. A simplified piece-wise tire model that well represents nonlinear tire forces was developed. The key parameters of this model can be chosen from measured tire forces. For the effects of dynamic load transfer due to sharp vehicle maneuvers, a tire force tuning algorithm that dynamically adjusts tire forces of the bicycle model based on measured vehicle lateral acceleration is proposed. Responses of the proposed bicycle model have been compared with commercial vehicle dynamics model (CarSim) through simulation in various vehicle maneuvers (ramp steer, sine-with-dwell).

To better reflect real world driving conditions, the EPA 5-Cycle Fuel Economy method encompasses high vehicle speeds, aggressive vehicle accelerations, climate control system use and cold temperature conditions in addition to the previously used standard City and Highway drive cycles in the estimation of vehicle fuel economy. A standard Powersplit Hybrid Electric Vehicle (HEV) system simulation environment has long been established and widely used within Ford to project fuel economy for the standard EPA City and Highway cycles. Direct modeling and simulation of the complete 5-Cycle fuel economy test set for HEV's presents significant new challenges especially with respect to modeling vehicle thermal management system and interactions with HEV features and system controls. It also requires a structured, systematic approach to validate the key elements of the system models and complete vehicle system simulations.

The pneumatic air brake system for heavy commercial trucks is composed by a large number of components, aiming its proper work and compliance with rigorous criteria of vehicular safety. One of those components, present along the whole vehicle, is the air brake tube, ducts which feed valves and reservoirs with compressed air, carrying signals for acting or releasing the brake system. In 2011, due to a lack of butadiene in a global scale, the manufacturing of these tubes was compromised; as this is an important raw material present on the polymer used so far, PA12. This article introduces the methodology of selecting, developing and validating in vehicle an alternative polymer for this application. For this purpose, acceptance criteria have been established through global material specifications, as well as bench tests and vehicular validation requirements.

In nowadays market, highlighted by global products, companies are pushed to sell products that comply with legal and customer requirements in different countries and, not unusually, different continents. In order to achieve such challenge, and pressed to reduce project and production costs, companies are spreading design centers around the world, based on regional expertise. These excellence centers must work together to benefit from synergies and local skills from different regions. Such projects are staffed by Virtual Team (BINDER, 2007), whose members barely face each other. This means teams will work frequently with people they have never met, who live on different time zones and have different cultures. As a consequence, communication is done basically through computer-based media, mainly based on emailing, and must be even clearer and more direct than with the people who work on the next desk.

Most people still remember the introduction of the IBM PC in 1981 and the first Microsoft Windows operating system in 1985. These were the pioneering technologies that started a revolution in automotive test equipment in the service bay. What was once a purely mechanical garage environment where information was published annually in large paper manuals has evolved into a highly technical computing environment. Today vehicle networks link onboard vehicle control systems with diagnostic systems and updated service information is published daily over the Internet. A lot has changed over the last twenty years, and manufacturers of diagnostic test equipment are learning to deal with the constantly evolving computing platforms and host operating systems. This paper traces the history of automotive diagnostic equipment at Ford Motor Company and shares some of the hard lessons learned from the early systems.

In 1999, the first generation NOx sensor from NGK Spark Plug, Co., Ltd. was commercialized for use in gasoline LNT NOx after-treatment systems [ 1 ]. Since then, as emissions regulations and OBD requirements have become more stringent, the demand for a high-accuracy NOx sensor with fast light-off has increased, particularly for diesel after-treatment systems. To meet such market demands, NGK Spark Plug, Co., Ltd. has developed, in collaboration with Ford Motor Company, a second generation NOx sensor.

The use of lightweight materials in automotive application has greatly increased in the past two decades. A need to meet customer demands for vehicle safety, performance and fuel efficiency has accelerated the development, evaluation and employment of new lightweight materials and processes. The 50 SAE Technical papers contained in this publication document the processes, guidelines, and physical and mechanical properties that can be applied to the selection and design of lightweight components for automotive applications. The book starts off with an introduction section containing two 1920 papers that examine the use of aluminum in automobiles.

A feedgas hydrocarbon emissions model that extends the usefulness of fully-warmed steady-state engine maps to the cold transient regime was developed for use within a vehicle simulation program that focuses on the powertrain control system (Virtual Powertrain and Control System, VPACS). The formulation considers three main sources of hydrocarbon. The primary component originates from in-cylinder crevice effects which are correlated with engine coolant temperature. The second component includes the mass of fuel that enters the cylinder but remains unavailable for combustion (liquid phase) and subsequently vaporizes during the exhaust portion of the cycle. The third component includes any fuel that remains from a slow or incomplete burn as predicted by a crank angle resolved combustion model.

The Vehicle Exhaust Emissions Simulator was developed to evaluate the performance of vehicle emissions sampling and analytical systems. The simulator produces a representative tailpipe volume flow rate containing up to five emission constituents, injected via mass flow controllers (MFCs). Eliminating the variability of test results associated with the vehicle, driver, and dynamometer makes the simulator an ideal quality control tool for use in commissioning new test cells, checking data correlation between test cells, and evaluating overall system performance. Earlier vehicle emissions simulators being used in the industry were primarily for checking Constant Volume Samplers (CVSs) and Bag Benches but they did not have the ability to properly simulate tailpipe volume.

Drive shaft modelling effects frontal crash finite element simulation. A 35 mph rigid barrier impact of a body on frame SUV with an one piece drive shaft and a unibody SUV with a two piece drive shaft have been studied and simulated using finite element analyses. In the model, the drive shaft can take significant load in frontal impact crash. Assumptions regarding the drive shaft model can change the predicted engine motion in the simulation. This change influences the rocker @ B-pillar deceleration. Two modelling methods have been investigated in this study considering both joint mechanisms and material failure in dynamic impact. Model parameters for joint behavior and failure should be determined from vehicle design information and component testing. A body on frame SUV FEA model has been used to validate the drive shaft modeling technique by comparing the simulation results with crash test data.

Effects of DOF and subjective method on evaluations of ride quality on the Ford Vehicle Vibration Simulator were studied. Seat track vibrations from 6 vehicles were reproduced on the 6 DOF seat shaker in a DOE with pitch and roll as factors. These appeared in two evaluations of ride/shake; semantic scaling by 30 subjects of 6 vehicles, and paired comparisons by 16 of the subjects on 3 of the vehicles. Both methods found significant vehicle, pitch and roll effects. Order dependence was shown for semantic scaling. The less susceptible paired comparison method gave a different ordering, and is thus preferred.