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This SAE Standard provides performance and general design requirements and related test procedures for a combination tail and floodlamp for use on industrial wheeled equipment that may be operated on public roads.

This session will explore connector concerns related to the needs of Commercial Vehicle Manufacturers and problems/opportunities from a connection system supplier perspective. It will look at differences in requirements for the global market, and their relation to local requirements. Presenter Robin D. Reed, Deutsch Industrial/LADD Industries

Software usability is a quality attribute defined as ?the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specific context of use? (ISO 9241, 1998), usability is also referred to as ?quality in use? (ISO 14598, 1999). Presenter Anabell Beltran, Stoneridge Electronics North America

There are several variables to consider when specifying a hydraulic hybrid system in a commercial vehicle. Parameters which can be controlled include various component sizes and some hybrid system calibration parameters. Presenter Paul Schwark, Bosch Rexroth AG

Can you become a visionary or are you born one? How does a visionary capture an opportunity and makes it a successful business? Are engineers more qualified to solve technical problems or run companies? SAE's "The Visionary's Take" addresses these and many other questions, by talking directly with those who have dared to tackle difficult engineering problems, and create real-life products out of their experience. In these short episodes, Sanjiv Singh and Lyle Chamberlain, respectively CEO and Chief Engineer from Near Earth Autonomy, talk about their experience in creating a brand-new company in the UAV world. Founded in 2011, Near Earth Autonomy brought together a group of engineers and roboticists, looking for unconventional solutions to very hard logistics problems, presenting danger to human life. The answers were developed by pushing technology to a higher level, testing quickly and often, and keeping an open mind to alternative ways of framing engineering challenges.

This set includes: SAE International Journal of Aerospace March 2010 - Volume 2 Issue 1 SAE International Journal of Commercial Vehicles October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Engines October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Fuels and Lubricants October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Materials and Manufacturing October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Passenger Cars - Electronic and Electrical Systems October 2009 - Volume 2, Issue 1 SAE International Journal of Passenger Cars - Mechanical Systems October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2

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 development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

Abstract Reliability analysis of a large-scale system under random dynamic loads can be a very time-consuming task since it requires repeated studies of the system. In many engineering problems, for example, wave loads on an offshore platform, the excitation loads are defined using a power spectral density (PSD) function. For a given PSD function, one needs to generate many time histories to make sure the excitation load is modeled accurately. Global and local approximation methods are available to predict the system response efficiently. Each way has their advantages and shortcomings. The combined approximations (CA) method is an efficient method, which combines the advantages of local and global approximations. This work demonstrates two methodologies that utilize CA to reduce the cost of crude or separable Monte Carlo simulation (MCS) of linear dynamic systems when the excitation loads are defined using PSD functions.

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

Abstract A new concept of instantaneous wheel turn center (IWTC) is proposed to evaluate and improve multi-axle vehicle steering coordination performance. The concept of IWTC and its calculation method are studied. The index named dispersion of IWTC is developed to evaluate the vehicle steering coordination performance quantitatively. The simulation tests based on a three-axle off-road vehicle model are conducted under different vehicle velocities and lateral accelerations. The simulation results show that the turn centers of different wheels are disperse, and the dispersion becomes larger with the increase of vehicle velocities and lateral acceleration. Since suspension has important influences on vehicle steering performance, the genetic algorithm is used to optimize the suspension hard points and bushing stiffness, aiming at minimizing the dispersion of wheel turn centers (DWTC) to improve the vehicle steering coordination performance.

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 In order to improve robustness of vehicle dynamic performance, a steering mechanism model is proposed with alignment parameters of front wheel based on preference function method. In the steering mechanism model controllable variables include the trapezoid connection length, the base angle of steering trapezoid, the kingpin inclination angle, caster, camber and uncontrollable variables include load and initial braking velocity. Optimization objective is some vehicle dynamic performance. In the preference function method the individual performance preference and preference aggregation in designing variable space and performance variable space are analyzed. The individual performance preference includes the controllable variable preference, noise factor preference and optimization objective preference. The aggregation function is developed by aggregating all the individual performance preferences.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

Road vibrations cause fatigue failures in vehicle components and systems. Therefore, reliable and accurate damage and life assessment is crucial to the durability and reliability performances of vehicles, especially at early design stages. However, durability and reliability assessment is difficult not only because of the unknown underlying damage mechanisms, such as crack initiation and crack growth, but also due to the large uncertainties introduced by many factors during operation. How to effectively and accurately assess the damage status and quantitatively measure the uncertainties in a damage evolution process is an important but still unsolved task in engineering probabilistic analysis. In this paper, a new procedure is developed to assess the durability and reliability performance, and characterize the uncertainties of damage evolution of components under constant amplitude loadings.

The emergence of tougher environmental legislations and ever increasing demand for increased ride comfort, fuel efficiency, and low emissions have triggered exploration and advances towards more efficient vehicle gearbox technologies. The growing complexity and spatial distribution of such a mechatronic gearbox demands precise timing and coordination of the embedded electronics, integrated sensors and actuators as well as excellent overall reliability. The increased gearbox distributed systems have seen an increased dependence on sensors for feedback control, predominantly relying on hardware redundancy for faults diagnosis. However, the conventional hardware redundancy has disadvantages due to increased costs, weight, volume, power requirements and failure rates. This paper presents a virtual position sensor-based Fault Detection, Isolation and Accommodation (FDIA), which generates an analytical redundancy for comparison against the actual sensor output.

Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.