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The aerospace industry has long sought a solution for storing maintenance history information directly on aircraft parts. In 2005 leading airframe manufacturers determined that passive Radio Frequency Identification (RFID) technology presented a unique opportunity to address this industry need. Through the efforts of the Air Transport Association (ATA) RFID on Parts Committee and SAE International testing standards and data specifications are in place to support the broad adoption of passive RFID for storing parts history information directly on aircraft parts. The primary focus of the paper will be on the SAE AS-5678 environmental testing standard for passive RFID tags intended for aircraft use. Detail will be provided to help aerospace manufacturers understand their role and responsibilities for current programs and understand how this may impact their parts certification process.

The presentation describes technology developments and the integration of these technologies into new emission control systems. As in other years, the reader will find a wide range of topics from various parts of the world. This is reflective of the worldwide scope and effort to reduce diesel exhaust emissions. Topics include the integration of various diesel particulate matter (PM) and Nitrogen Oxide (NOx) technologies as well as sensors and other emissions related developments. Presenter Atsuo Kondo, NGK Insulators, Ltd.

Simulation-based tolerance analysis is the accepted standard for dimensional engineering in aerospace today. Sophisticated 3D model-based tolerance analysis processes enable engineers to measure variation in complex, often large, assembled products quickly and accurately. Best-in-class manufacturers have adopted Quality Intelligence Management tools for collecting and consolidating this measurement data. Their goal is to completely understand dimensional fit characteristics and quality status before commencing the build process. This results in shorter launch cycles, improved process capabilities, reduced scrap and less production downtime. This paper describes how to use simulation-based approaches to correlate the theoretical tolerance analysis results produced during engineering simulations to actual as-built results. This allows engineers to validate or adjust as-designed simulation parameters to more closely align to production process capabilities.

Probabilistic methods are used in calculating composite part design factors for, and are intended to conservatively compensate for worst case impact to composite parts used on space and aerospace vehicles. The current method to investigate impact damage of composite parts is visual based upon observation of an indentation. A more reliable and accurate determinant of impact damage is to measure impact energy. RF impact sensors can be used to gather data to establish an impact damage benchmark for deterministic design criteria that will reduce material applied to composite parts to compensate for uncertainties resulting from observed impact damage. Once the benchmark has been established, RF impact sensors will be applied to composite parts throughout their life-cycle to alert and identify the location of impact damage that exceeds the maximum established benchmark for impact.

Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

Four-way, integrated, diesel emission control systems that combine selective catalytic reduction for NOx control with a continuously regenerating trap to remove diesel particulate matter were evaluated under real-world, on-road conditions. Tests were conducted using a semi-tractor with an emissions year 2000, 6-cylinder, 12 L, Volvo engine rated at 287 kW at 1800 rpm and 1964 N-m. The emission control system was certified for retrofit application on-highway trucks, model years 1994 through 2002, with 4-stroke, 186-373 kW (250-500 hp) heavy-duty diesel engines without exhaust gas recirculation. The evaluations were unique because the mobile laboratory platform enabled evaluation under real-world exhaust plume dilution conditions as opposed to laboratory dilution conditions. Real-time plume measurements for NOx, particle number concentration and size distribution were made and emission control performance was evaluated on-road.

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 Path tracking is an essential stage for vehicle safety control. It is more newsworthy than ever in the automotive context and especially for autonomous vehicle. The study proposes an optimal control method for path tracking problem in inverse vehicle handling dynamics. The proposed method generates an expected trajectory which guarantees minimum clearance to the prescribed path by identifying the optimal steering torque input. Based on this purpose, the path tracking problem, which is treated as an optimal control problem, is then solved by local collocation method and mesh refinement. Finally, a real vehicle test is executed to verify the rationality of the proposed model and methodology. The results show that using control variables as a mesh refinement function can capture the dramatic changes in state variables, and the efficiency improvement is more significant as the number of the grid points increases.

Abstract It is reasonable to use a two-phase heat transfer loop (TPL) in a thermal control system (TCS) of spacecraft with large heat dissipation. One of the key elements of TPL is a heat-controlled accumulator (HCA). The HCA represents a volume which is filled with vapor and liquid of a single working fluid without bellows. The pressure in a HCA is controlled by the heater. The heat and mass transfer processes in the HCA can proceed with a significant nonequilibrium. This has implications on the regulation of TPL. This article presents a mathematical model of nonequilibrium heat and mass transfer processes in an HCA for microgravity conditions. The model uses the equations of mass and energy conservation separately for the vapor and liquid phases. Interfacial heat and mass transfer is also taken into account. It proposes to use the convective component k for the level of nonequilibrium evaluation.

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

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 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 cabin air quality depends on various parameters such as number of passengers, fan speed, and vehicle speed. In addition to controlling the temperature inside the vehicle, HVAC control system has evolved to improve cabin air quality as well. However, there is no standard test method to ensure reliable and repeatable comparison among different cars. The current study defined Cabin Air Quality Index (CAQI) and proposed a test method to determine CAQI. CAQIparticles showed dependence on the choice of metrics among particle number (PN), particle surface area (PS), and particle mass (PM). CAQIparticles is less than 1 while CAQICO2 is larger than 1. The proposed test method is promising but needs further improvement for smaller coefficient of variations (COVs).