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Moir� method is useful to measure the shape and the whole-field distributions of displacement and strain of structures. There are many kinds of moir� methods such as geometric moir� method, sampling moir� method, Fourier transform moir� method, moir� interferometry, shadow moir� method and moir� topography. Grating method analyzing directly deformation of a grating without any moir� fringe pattern is considered as an extended technique of moire method. Phase analysis of the moire fringe patterns and the grating patterns provides accurate measurements of shapes or displacement and strain distributions. Some applications of these moir� methods and grating methods to dynamic shape and strain distribution measurements of a rotating tire, sub-millimeter displacement measurements from long distance for landslide prediction, real-time shape measurements with micro-meter order accuracy, etc. are shown. Presenter Yoshiharu Morimoto, Moire Institute Inc.

Nissan Motor Company has recently released the �Nissan Green Program 2016� which is a six-year action plan embodying the company�s environmental philosophy: Symbiosis of People, Vehicles and Nature. One of the key activities of this Program is the successful penetration of Zero-Emission Vehicles into the market which includes electric vehicle (EV) cumulative sales of 1.5M units with our Alliance partner Renault, introduction of a fuel cell electric vehicle (FCEV) into the market, taking a global leadership in supplying batteries for electric drive and creating zero-emission societies. This presentation will highlight some of these key activities. Presenter Kev Adjemian, Nissan Technical Center NA

In recent years, all major microprocessor manufacturers are transitioning towards the deploymenet of multiple processing cores on every chip. These multi-core architectures represent the industry consensus regarding the most effective utilization of available silicon resources to satisfy growing demands for processing and memory capacities. Porting off-the-shelf software capabilities to multi-core architectures often requires significant changes to data structures and algorithms. When developing new software capabilities specifically for deployment on SMP architectures, software engineers are required to address specific multi-core programming issues, and in the ideal, must do so in ways that are generic to many different multi-core target platforms. This talk provides an overview of the special considerations that must be addressed by software engineers targeting multi-core platforms and describes how the Java language facilitates solutions to these special challenges.

PRESENTATION ABSTRACT (ROI Approval BOE021811-122) REVIEW OF UPDATED AEROSPACE RECOMMENDED PRACTICES ARP5061A, Guidelines for Testing and Support of Aerospace, Fiber Optic, Inter-Connect Systems RATIONALE: A single source document to capture current best practices, methods, test equipment, and materials that support fiber optic interconnect systems including high-density applications deployed in Aerospace platforms. SCOPE: This presentation will describe how the ARP5061 document provides the maintainer unique guidelines for optical performance testing of short haul fiber optic inter-connect systems used in aerospace vehicles. The focus of this document is to establish common pre and post installation test methods, equipment, materials, and troubleshooting methodologies. QUALIFICATIONS AND TRAINING STANDARDS: The repair and maintenance of a fiber optic system should ONLY BE PERFORMED by qualified personnel.

The sustainable use of energy and the reduction of pollutant emissions are main concerns of the automotive industry. In this context, Hybrid Electric Vehicles (HEVs) offer significant improvements in the efficiency of the propulsion system and allow advanced strategies to reduce pollutant and noise emissions. The paper presents the results of a simulation study that addresses the minimization of fuel consumption, NOx emissions and combustion noise of a medium size passenger car. Such a vehicle has a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. The simulation reproduces real-driver behavior through a dynamic modeling approach and actuates an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM). Typical characteristics of parallel hybrid technologies, such as Stop&Start, regenerative braking and electric power assistance, are implemented via an operating strategy that is based on the reduction of total losses.

A conceptual project aimed at understanding the fundamental design considerations concerning the implementation of catalyst systems on outboard marine engines was carried out by Mercury Marine, with the support of the California Air Resources Board. In order to keep a reasonable project scope, only electronic fuel injected four-stroke outboards were considered. While they represent a significant portion of the total number of outboard engines sold in the United States, carbureted four-strokes and direct injected two-strokes pose their own sets of design constraints and were considered to be outside the scope of this study. Recently, three-way catalyst based exhaust emissions aftertreatment systems have been introduced into series production on sterndrive and inboard marine spark ignition engines in North America. The integration of catalyst systems on outboards is much more challenging than on these other marine propulsion alternatives.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

Abstract This study aims to take the first step in bridging the gap between vehicle dynamics systems and autonomous control strategies research. More specifically, a nested method is employed to evaluate the collision avoidance ability of autonomous vehicles in the primary design stage theoretically based on both dynamics and control parameters. An integrated model is derived from a half car mathematical model in the lateral direction, consisting of two degrees of freedom, lateral deviation and yaw angle, with a traction mathematical model in the longitudinal direction, consisting of two degrees of freedom, the longitudinal velocity and rolling velocity of the wheel. The integrated model uses a mathematical power train model to generate the torque on the wheel and connects the two systems via the magic formula tyre model to represent the tyre non-linearity during augmented longitudinal and lateral dynamic attitudes.

Abstract In this paper, an efficient lane detection using deep feature extraction method is proposed to achieve real-time lane detection in diverse road environment. The method contains three main stages: 1) pre-processing, 2) deep lane feature extraction and 3) lane fitting. In pre-processing stage, the inverse perspective mapping (IPM) is used to obtain a bird's eye view of the road image, and then an edge image is generated using the canny operator. In deep lane feature extraction stage, an advanced lane extraction method is proposed. Firstly, line segment detector (LSD) is applied to achieve the fast line segment detection in the IPM image. After that, a proposed adaptive lane clustering algorithm is employed to gather the adjacent line segments generated by the LSD method. Finally, a proposed local gray value maximum cascaded spatial correlation filter (GMSF) algorithm is used to extract the target lane lines among the multiple lines.

Abstract ISO 26262 needs to be considered when developing safety-relevant E/E systems within the automotive industry. One part of the development process according to ISO 26262 is the derivation of the safety requirements for component functions. Here, one attribute of the safety requirements is the Automotive Safety Integrity Level (ASIL). The ASIL at a component level can be determined using ASIL allocation and decomposition. Considering complex systems such as vehicle electrical systems, countless possibilities can be identified for how the ASILs at a component level can be assigned in line with safety goals. In terms of efficiency, manual assignment is not expedient. Therefore, an algorithm for automated assignment of the ASILs will be introduced which considers constraints based on a fault tree analysis. The function of the approach will be demonstrated using the example of a vehicle electrical system from an automated vehicle.

Abstract This article presents a comprehensive investigation for the interaction between vehicle ride vibration control and braking control using two degrees of freedom (2DOF) quarter vehicle model. A typical limited bandwidth active suspension system with nonlinear spring and damping characteristics of practical hydraulic and pneumatic components is controlled to regulate both suspension and tire forces and therefore provide the optimum ride comfort and braking performance of an anti-lock brake system (ABS). In order to design a suitable controller for this nonlinear integrated system, various control techniques are followed including state feedback tuned using Linear Quadratic Regulator (LQR), state feedback tuned using Genetic Algorithm (GA), Proportional Integrated (PI) tuned genetically, and Fuzzy Logic Control (FLC). The ABS control system is designed to limit skid ratio below threshold of 15%.

Abstract In this article, compared with traditional Remote Parameter Control (RPC), the iterative process is improved based on linear transfer function (TF) estimation of the nonlinear dynamic system. In the improved RPC, the iteration coefficient is designed according to the convergence condition of the nonlinear iterative process, so that the convergence level, convergence speed, and iteration stability could be improved. The difference between the traditional and the improved RPC iterative process is discussed, the RPC iterative process of the nonlinear system is analyzed, and channel decoupling for Multi-Input Multi-Output (MIMO) system based on eigen-decomposition of the system TF and linear TF estimation is introduced. It assumes that the eigenvector matrix of the system TF remains the same, and the linear TF in the iterative process is estimated and updated, which is used for iterative calculation.

Abstract Since the tire inflation pressure has a significant influence on safety, comfort and environmental behavior of a vehicle, the choice of the optimal inflation pressure is always a conflict of aims. The development of a highly dynamic Tire Pressure Control System (TPCS) can reduce the conflict of minimal rolling resistance and maximal traction. To study the influence of the tire inflation pressure on longitudinal tire characteristics under laboratory conditions, an experimental sensitivity analysis is performed using a multivalent usable Corner Module Test Rig (CMTR) developed by the Automotive Engineering Group at Technische Universität Ilmenau. The test rig is designed to analyze suspension system and tire characteristics on a roller of the recently installed 4 chassis roller dynamometer. Camber angle, toe angle and wheel load can be adjusted continuously. In addition, it is possible to control the temperature of the test environment between −20 °C and +45 °C.

Abstract In this article, a hierarchical coordinated control algorithm for integrating active rear steering and driving/braking force distribution (ARS+D/BFD) was presented. The upper-level control was synthesized to generate the required rear steering angle and external yaw moment by using a sliding-mode controller. In the lower-level controller, a control allocation algorithm considering driving/braking actuators and tire forces constraints was designed to assign the desired yaw moment to the four wheels. To this end, an optimization problem including several equality and inequality constraints were defined and solved analytically. Finally, computer simulation results suggest that the proposed hierarchical control scheme was able to help to achieve substantial enhancements in handling performance and stability.

Abstract In an automated machining process, monitoring the conditions of the tool is essential for deciding to replace or repair the tool without any manual intervention. Intelligent models built with sensor information and machine learning techniques are predicting the condition of the tool with good accuracy. In this study, statistical models are developed to identify the conditions of the abrasive grinding wheel using the Acoustic Emission (AE) signature acquired during the surface grinding operation. Abrasive grinding wheel conditions are identified using the abrasive wheel wear plot established by conducting experiments. The piezoelectric sensor is used to capture the AE from the grinding process, and statistical features of the abrasive wheel conditions are extracted in time and wavelet domains of the signature. Machine learning algorithms, namely, Classification and Regression Trees (CART) and Support Vector Classifiers (SVC), are used to build statistical models.

Abstract Wet clutch packs are the key component for gear shifting in the step-ratio automatic transmission system. The clutch plates are coupled or de-coupled to alter gear ratios based on the driver’s actions and vehicle operating conditions. The frictional interfaces between clutch plates are lubricated with automatic transmission fluid (ATF) for both thermal and friction management. In a 10-speed transmission, there may be as many as 6 clutch packs. Under typical driving conditions, 2 to 3 clutch packs are open, shearing ATF and contributing to energy loss. There is an opportunity to improve fuel economy by reducing the associated viscous drag. An important factor that directly affects clutch drag is the clearance between rotating plates. The axial position of clutch plates changes continuously during operation. It is known in practice that not only the total clearance, but also its distribution between the plates affects the viscous drag.

Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.

Abstract Modern vehicles have incorporated numerous safety-focused advanced driver-assistance systems (ADAS) in the last decade including smart cruise control and object avoidance. In this article, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy (FE). We combine ADAS sensor data with a previously developed prediction model, dynamic programming (DP) optimal energy management control, and a validated model of a 2010 Toyota Prius to explore FE. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

An automated process was developed for the calibration of numerical aftertreatment models. The chemical kinetic mechanism examined in this case was part of a simplified SCR model. The process adopted for calibrating the SCR model was based on a micro-population multi-objective genetic algorithm. The algorithm developed was used to calibrate the SCR model using data derived from another, more detailed model to ensure that the evaluation focused only on the effectiveness of the calibration process and was not affected by issues of experimental inaccuracies or details of the model chemistry involved.