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This course is verified by Probitas Authentication as meeting the AS9104/3A requirements for continuing Professional Development.  Engineers and managers involved with product development are constantly challenged to reduce time to market, minimize warranty costs, and increase product quality. With less and less time for testing, the need for effective accelerated test procedures has never been greater.

This 2-day foundational-level course teaches functional gaging design. It covers how to verify part dimensional requirements using functional gages and other measurement methods. The course offers an explanation of metrology, the roles of the metrologist and inspector, measurement uncertainty, inspection tools, functional gages, inspection planning and reporting, and simulating datums. Each participant receives: A Functional Gaging and Measurement Workbook and  Drawing handouts. Newly acquired learning is reinforced throughout the class with numerous practice exercises. 

This 2-day foundational-level course builds on geometric dimensioning and tolerancing fundamentals and teaches an introduction of how to inspect GD&T requirements.  The course offers an explanation of the geometric symbols, rules, and concepts, the datum system, and how to inspect GD&T requirements using tools from the four categories of inspection tools (CMM; comparison instruments and fixed gages; hand tools and open set up; and production gaging systems).

This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Project Management and Advanced Product Quality Planning (APQP) are two critical techniques used in product development in the mobility industry today. This course will bring these techniques together in an easy to understand format that goes beyond the typical concept of constructing timelines and project planning, by exploring not only the Automotive APQP process, but also key aspects of PM processes.

The field of motor vehicle rollover research and testing has been one of multiple and varied approaches, dating back to at least the 1930's. The approach has been as simple as tipping a vehicle over at the top of a steep hill ( Wilson et al., 1972 ), to as complex as releasing a vehicle from an elevated roll spit mounted to the rear of a moving tractor and trailer ( Cooper et al., 2001 and Carter et al., 2002 ). Presenter Peter Luepke, P Luepke Consulting

The amount of software, computation and logic embedded into the vehicle systems is increasing. Testing of complex real time embedded systems using Hardware in Loop (HIL) simulations across different vehicle platforms has been a challenge. Data driven testing enables a qualitative approach to test these complex vehicle systems. It consists of a test framework wherein the test logic and data are independent of the HIL test environment. The data comprises variables used for both input values and output verification values. This data is maintained in a database or in the form of tables. Each row defines an independent test scenario. The entire test data is divided into three categories, High, Medium and Low. This feature gives the advantage of leveraging the same set of test data from Unit Level Testing phases to the Integration Test phase in the V-Cycle of software development. A data driven test approach helps the reuse of tests across vehicle platforms.

Driver assistance systems (e.g. the emergency brake assist Active Brake Assist2, or ABA2 for short, in the Mercedes-Benz Actros) are becoming increasingly common in heavy-duty commercial vehicles. Due to the close interconnection with drivetrain and suspension control systems, the integration and validation of the functions make the most exacting demands on processes and tools involved in mechatronics development. Presenter Thomas Bardelang, Daimler AG

There are many macro drivers that are creating opportunities for transportation electrification. They include the environment, dependence on foreign oil, national security, battery technology and government incentives to name a few. In light of this growing momentum consumers will have choices to where they can charge ? at home, workplace or publicly. Electrical vehicle supply equipment will drive value throughout the supply chain ? installer, building owner, automaker, suppliers, utilities and consumers. Market acceptance will occur when consumer?s needs and wants are met. To meet these needs access to products through multiple channels will be required. Presenter Manoj Karwa, Leviton Manufacturing Co. Inc.

Dramatic changes in transportation are coming. Cities and states looking to be at the forefront and reap the benefits, need an engaged and informed citizenry. Hear how the SAE Demo Day in Tampa supported Florida's AV initiatives and can benefit states nationwide.

In May 2018, SAE International in partnership with THEA and leading AV technology companies gave citizens in Tampa a chance to test ride the future. The event included a pre- and post-ride survey, a ride in an automated vehicle, interactive displays and engagement with industry experts. See highlights of the event and feedback from participants.

As an annual subscription, the Wiley Cyber Security Collection Add-On is available for purchase along with one or both of the following: Wiley Aerospace Collection Wiley Automotive Collection The titles from the Wiley Cyber Security Collection are included in the SAE MOBILUS® eBook Package. Titles: Network Forensics Penetration Testing Essentials Security in Fixed and Wireless Networks, 2nd Edition The Network Security Test Lab: A Step-by-Step Guide Risk Centric Threat Modeling: Process for Attack Simulation and Threat Analysis Applied Cryptography: Protocols, Algorithms and Source Code in C, 20th Anniversary Edition Computer Security Handbook, Set, 6th Edition Threat Modeling: Designing for Security Other available Wiley collections: Wiley SAE MOBILUS eBook Package Wiley Aerospace Collection Wiley Automotive Collection Wiley Computer Systems Collection Add-On (purchasable with the Wiley Aerospace Collection and/or the Wiley Automotive Collection)

The 30 papers in this technical paper collection focus on heavy tire modeling/testing and evaluation; vehicle dynamics; wide based tires, sustainability and maintenance; air suspension, off-road chassis and suspension; hybrid drive and chassis; all wheel/multi-wheel drive vehicle dynamics and performance; testing and experimental analysis of chassis and suspension; and advanced chassis control and rollover.

Vehicle aerodynamic development, drag reduction and fuel economy, handling and stability, cooling flows, surface soiling and water management, vehicle internal environment, tyre aerodynamics and modelling, aeroacoustics, structural response to aerodynamic loading, simulating the on-road environment, onset flow turbulence, unsteady aerodynamics, fundamental flow structures, new test methods and facilities, new applications of computational fluid dynamics simulation, competition vehicle aerodynamics.

This technical paper collection discusses the modeling, analysis, and validation of commercial vehicle chassis, suspension, and tire modeling and simulation. Topics include commercial vehicle dynamics; chassis control devices such as ABS, traction control, yaw/roll stability control, and their interaction with suspension controls; modeling and simulation of ride comfort, as well as passive and active suspension control methodologies. Authors are encouraged to discuss the validation of their modeling and simulation.

Abstract Exhaust manifolds are one of the most important components on the engine assembly, which is mounted on engine cylinder head. Exhaust manifolds connect exhaust ports of cylinders to the turbine for turbocharged diesel engine therefore they play a significant role in the performance of engine system. Exhaust manifolds are subjected to very harsh thermal loads; extreme heating under very high temperatures and cooling under low temperatures. Therefore designing a durable exhaust manifold is a challenging task. Computer aided engineering (CAE) is an effective tool to drive an exhaust manifold design at the early stage of engine development. Thus advanced CAE methodologies are required for the accurate prediction of temperature distribution. However, at the end of the development process, for the design verification purposes, various tests have to be carried out in engine dynamometer cells under severe operating conditions.

Abstract The use of nanomaterials and nanostructures have been revolutionizing the advancements of science and technology in various engineering and medical fields. As an example, Carbon Nanotubes (CNTs) have been extensively used for the improvement of mechanical, thermal, electrical, magnetic, and deteriorative properties of traditional composite materials for applications in high-performance structures. The exceptional materials properties of CNTs (i.e., mechanical, magnetic, thermal, and electrical) have introduced them as promising candidates for reinforcement of traditional composites. Most structural configurations of CNTs provide superior material properties; however, their geometrical shapes can deliver different features and characteristics. As one of the unique geometrical configurations, helical CNTs have a great potential for improvement of mechanical, thermal, and electrical properties of polymeric resin composites.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract Vehicle rolling resistance and weight are two of the factors that affect fuel economy. The vehicle tire rolling resistance has a more significant influence than aerodynamics drags on fuel economy at lower vehicle speeds, particularly true for medium- and heavy-duty trucks. Less vehicle weight reduces inertia loads, uphill grade resistance, and rolling resistance. The influence of weight on the fuel economy can be considerable particularly in light- to medium-duty truck classes because the weight makes up a larger portion of gross vehicle weight. This article presents an empirical investigation and a numerical analysis of the influences of rolling resistance and weight on the fuel economy of medium-duty trucks. The experimental tests include various tires and payloads applied on a total of 21vehicle configurations over three road profiles. These tests are used to assess the sensitivity of rolling resistance and weight to the vehicle fuel economy.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.