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The intake and exhaust port design plays a substantial role in performance of combustion systems. The port design determines the volumetric efficiency and in-cylinder charge motion of the spark-ignited engine which influences the thermodynamic properties directly related to the power output, emissions, fuel consumption and NVH properties. Thus intake port has to be appropriately designed to fulfill the required charge motion and high flow performance. While turbulence intensity and air-mixture quality affect dilution tolerance and fuel economy as a result, breathing ability affects wide open throttle performance. Traditional approaches require experimental techniques to reach a target balance between the charge motion and breathing capacity. Such techniques do not necessarily result in an optimized solution.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

This paper presents the studies on how to efficiently and easily implement ECU application algorithms using the Signal Processing Engine (SPE) of the Copperhead microcontroller. With the introduced development and testing concepts and methods, users can easily establish their own PC based SPE emulation system. All application unit testing and verification work for the fixed point implementation using SPE functions can be easily conducted in PC without relying on a costly real time test bench and expensive third party dedicated software. With this simple development environment, the code can be run in both embedded controllers and PCs with exact bit to bit numerical behavior. The paper also demonstrates many other benefits such as code statistics information retrieval, floating simulation mode, automated code verification, online and offline code sharing.

A 2D model for vehicle-to-vehicle impact analysis that was presented in an earlier paper [1], has been used to study several two-vehicle frontal impacts with different incidence angles, frontal overlap offsets, and mass ratios. The impacts have been evaluated in terms of energy and momentum change in the bullet vehicle and the target vehicle. Based on comparisons between pre- and post-impact longitudinal, lateral, and angular components of kinetic energy, and linear and angular momenta, the impacts experienced by the target vehicle and the bullet vehicle have been classified as collinear or oblique. These results have been used to propose a definition of frontal impact based on vehicle kinematics during a crash.

A process for simultaneously optimizing the mechanical performance and minimizing the weight of an automotive body-in-white will be developed herein. The process begins with appropriate load path definition though calculation of an optimized topology. Load paths are then converted to sheet metal, and initial critical cross sections are sized and shaped based on packaging, engineering judgment, and stress and stiffness approximations. As a general direction of design, section requirements are based on an overall vehicle “design for stiffness first” philosophy. Design for impact and durability requirements, which generally call for strength rather than stiffness, are then addressed by judicious application of the most recently developed automotive grade advanced high strength steels. Sheet metal gages, including tailored blanks design, are selected via experience and topometry optimization studies.

This paper describes the development of an engineering analysis tool that assesses the life of vehicle components, after exposure to heat. As a standard engineering practice, each component or part of a component has a “long term” and a “short term” temperature goal based on the part’s material physical properties. At higher temperatures, component’s physical properties degrade at a faster rate, and the component’s useful life can be significantly reduced. The extent of degradation depends upon the duration of exposure, the magnitude of the over-temperature and rate of thermal degradation. This tool utilizes actual vehicle test data from test cells or road testing, material physical properties, and expected vehicle duty cycle to determine the expected component life. When component temperature goals are exceeded, the software calculates the total duration of time above the goal temperature.

This paper is the fifth in the series of documents designed to identify the progress on the SAE Plug-in Electric Vehicle (PEV) communication task force that follows 2010-01-0837, 2011-01-0866, 2012-01-1036 and 2013-01-1475. The primary focus of this paper is to discuss the most recent revision of J2847/1 [1], which deals with Smart Charging applications, plus the initial release of J2847/3 [2], which can be thought of as dealing with “Smart Discharging” applications. Both documents are based on the use of the Smart Energy Profile 2.0 (SEP2) Application Protocol Standard (V1.0) which was completed by the ZigBee Alliance in April 2013. The standard was then accepted by the IEEE and subsequently released as IEEE 2030.5 [3]. SEP2 started with a Marketing Requirements Document (MRD) that J2836/1™ [4]expanded for the automotive Use Cases for Smart Charging, The MRD was then used to generate the SEP2 Technical Requirements Document (TRD) that set the automotive requirements in J2931/1 [5].

A data processing algorithm is presented for determining the spatial orientation and position of a rigid body in impact tests based on an instrumentation scheme consisting of a triaxial angular rate sensor and a trialaxial linear accelerometer. The algorithm adopts the unit quaternion as the main parameterized representation of the spatial orientation, and calculates its time history by solving an ordinary differential equation with the angular rate sensor reading as the input. Two supplemental representations, the Euler angles and the direction cosine matrix, are also used in this work, which provide an intuitive description of the orientation, and convenience in transforming the linear accelerometer output in the instrumentation frame to the global frame. The algorithm has been implemented as a computer program, and a set of example impact tests are included to demonstrate its application.