Browse Topic: Identification
This specification covers a fluorosilicone (FVMQ) rubber in the form of molded rings.
This specification covers tungsten carbide-cobalt in the form of powder.
This SAE Standard establishes the minimum circuit identification and requirements for Multi-Voltage Power Distribution Systems (MVPDS) for use on trucks and buses. A Multi-Voltage Power Distribution System is one that distributes two or three voltages, up to 60 VDC, to power the controls, instruments, and devices.
This specification covers procedures for tab marking of bare welding wire to provide positive identification of cut lengths and spools.
This standard establishes the dimensional and visual quality requirements, lot requirements, and packaging and labeling requirements for O-rings molded from AMS7274 rubber. It shall be used for procurement purposes.
This SAE Aerospace Standard (AS) provides requirements for design and installation of aircraft jacking pad adapters and the mating jack socket interface to permit use of standard jacking equipment to be used in civil and military transport aircraft. The adapter defined herein shall be the key interface between the aircraft and the aircraft jack(s).
This paper presents an analytical approach for identifying suspension kingpin alignment parameters based on screw axis theorem and differential calculation model. The suspension kingpin caster and inclination alignment parameters can produce additional tire force, which affects vehicle handling dynamics. In wheel steering process, the multi-link suspension control arms lead to movement of the imaginary kingpin, which can cause change in suspension kingpin alignment parameters. According to the structure mechanism of commercial vehicle multi-link independent suspension, the kinematics characteristics of imaginary kingpin were analyzed based on the screw axis theorem. The angular velocity and translation velocity vectors were calculated. In order to avoid the influence of bushing deformation, the unique differential identification model was established to evaluate the suspension kingpin alignment parameters, and the identification results were compared with the ADAMS/Car data. The
There is an increasing effort to reduce noise pollution across different industries worldwide. From a transportation standpoint, pass-by regulations aim to achieve this and have been implementing increasingly stricter emissions limits. Testing according to these standards is a requirement for homologation, but does little to help manufacturers understand why their vehicles may be failing to meet limits. Using a developed methodology such as Pass-by Source Path Contribution (SPC, also known as TPA) allows for identification of dominant contributors to the pass-by receivers along with corresponding acoustic source strengths. This approach is commonly used for passenger vehicles, but can be impractical for off-highway applications, where vehicles are often too large for most pass-by-suitable chassis dynamometers. A hybrid approach is thereby needed, where the same techniques and instrumentation used in the indoor test are applied to scenarios in an outdoor environment. This allows for
This paper discusses a systematic process that was developed to evaluate the acoustic performance of a production dash system. In this case it is for an electric vehicle application. The production dash panel was tested under different configurations to understand the importance of passthroughs in the acoustics of the system. Results show that often the performance of the passthroughs strongly affects the overall performance of the dash system and this may become the limiting factor to increase the system sound transmission loss. To understand the acoustic strength of different passthroughs and their effects on the overall system, the dash with passthroughs underwent extensive testing. Subsequently, a test procedure using flat panels was developed to quantify the performance of individual passthroughs on a part level. This data can be used by the OEM to develop STL targets that can be considered in the grommet design early in the vehicle development process.
This SAE Aerospace Standard (AS) establishes minimum requirements for eddy current inspection of circular holes in nonferrous, metallic, low conductivity (less than 5% IACS) aircraft engine hardware with fasteners removed. The inspection is intended to be performed at maintenance and overhaul facilities on engine run hardware.
This SAE Aerospace Standard (AS) defines the requirements for a convoluted polytetrafluoroethylene (PTFE) lined, metallic reinforced, hose assembly suitable for use in aerospace fluid systems at temperatures between -65 °F and 400 °F for Class 1 assembly, -65 °F and 275 °F for Class 2 assembly, and at operating pressures per Table 1. The use of these hose assemblies in pneumatic storage systems is not recommended. In addition, installations in which the limits specified herein are exceeded, or in which the application is not covered specifically by this standard, shall be subject to the approval of the procuring activity.
This SAE Recommended Practice provides the lighting function identification codes for use on all passenger vehicles, trucks, trailers, motorcycles, and emergency vehicles.
Innovators at NASA Johnson Space Center have developed an adaptable Radio Frequency Identification (RFID) system that optimizes transmission for priority data as targets move in and out of passive coverage areas. The method extends the range, and reduces data latency, of ultra-low power battery-assisted passive (BAP) RFID sensor tags, improving previously developed store-and-forward techniques to support autonomous operations in complex environments where RFID interrogator access may be strained.
This material type has resistance to hot air, but generally has poor resistance to fuels and lubricants, but usage is not limited to such applications. Each application should be considered separately. This material type has a typical service temperature range of -85 to 500 °F (-65 to 260 °C). The operating temperature range of the material is a general temperature range, but the presence of particular fluids and design parameters may modify this range. Recommendations on the material selection are based on available technical data and are offered as suggestions only. Each user should make his own tests to determine the suitability for his own particular use.
This SAE Recommended Practice establishes recommended procedures for the issuance, assignment, and structure of Identification Numbers on a uniform basis by states or provinces for use in an Assigned Identification Number (AIN).
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions
Researchers have developed a gel polymer-based triboelectric nanogenerator (TENG) that generates electrical signals from body movement to power electronics like LEDs and functions as a self-powered touch panel for user identification. The device can stretch up to 375 percent of its original size and withstand rigorous mechanical deformations, making it suitable for wearable applications. TENGs that convert mechanical energy such as body movement to electrical energy offer a solution to power wearable devices without relying on batteries.
Sodium-ion batteries (SIBs) make their marks in energy storage and electric vehicles due to their abundant reserves, cost-effectiveness, environmental resilience, and high safety. However, maintaining high battery performance in intricate operating conditions is challenging, which necessitates precise control based on timely and accurate acquisition of operation parameters, especially for the state of charge (SOC). Equivalent circuit model (ECM) is the most widely used in the evaluation of SOC. In this work, a 2nd-order resistor-capacitor ECM (2ORC-ECM) is chosen because of its balance between accuracy and computational efficiency. Furthermore, dynamic parameters in the 2ORC-ECM are accurately identified online by introducing an enhanced recursive least squares method with a forgetting factor. Finally, the proposed method is carried out based on the measured data of commercial SIBs. The results show that the proposed method can mitigate data saturation effectively while ensuring high
Monitoring the rotor temperature of drive machines is crucial for the safety and performance of electric vehicles. However, due to the complex operating conditions of electric vehicles, the thermal parameters of vehicular induction machines (IMs) vary significantly and are difficult to identify accurately. This article first establishes a concise but effective thermal network for IMs and analyzes the influencing factors of thermal parameters. Then, a parameter identification network (PIN) with multiple parallel branches is constructed to learn the mapping relationship between electromechanical variables and thermal parameters. Afterward, temperature datasets for network training are built through bench testing. Finally, the effectiveness of identified parameters for rotor temperature estimation application is verified, demonstrating improved interpretability, generalization ability, and accuracy compared to an end-to-end neural network.
This SAE Recommended Practice establishes a procedure for the issuance and assignment of a World Manufacturer Identifier (WMI) on a uniform basis to vehicle manufacturers that may desire to incorporate it in their Vehicle Identification Numbers (VIN). This recommended practice is intended to be used in conjunction with the recommendations for VIN systems described in SAE J853, SAE J187, SAE J272, and other SAE reports for VIN systems. These procedures were developed to assist in identifying the vehicle as to its point of origin. It was felt that review and coordination of the WMI by a single organization would avoid duplication of manufacturer identifiers and assist in the identification of vehicles by agencies such as those concerned with motor vehicle titling and registration, law enforcement, and theft recovery.
This SAE Recommended Practice describes the basic content requirements, barcode specifications, and functional test specifications of the vehicle identification number (VIN) label. On the vehicle, the VIN label is to be mounted in a readily accessible location for use of a barcode scanning device.
The flow structure and unsteadiness of shock wave–boundary layer interaction (SWBLI) has been studied using rainbow schlieren deflectometry (RSD), ensemble averaging, fast Fourier transform (FFT), and snapshot proper orthogonal decomposition (POD) techniques. Shockwaves were generated in a test section by subjecting a Mach = 3.1 free-stream flow to a 12° isosceles triangular prism. The RSD pictures captured with a high-speed camera at 5000 frames/s rate were used to determine the transverse ray deflections at each pixel of the pictures. The interaction region structure is described statistically with the ensemble average and root mean square deflections. The FFT technique was used to determine the frequency content of the flow field. Results indicate that dominant frequencies were in the range of 400 Hz–900 Hz. The Strouhal numbers calculated using the RSD data were in the range of 0.025–0.07. The snapshot POD technique was employed to analyze flow structures and their associated
SAE J3108 Recommended Practice (RP) provides fuel and hazard guidance for first and second responders of incidents associated with alternative fueled vehicles. The intent of SAE J3108-1 is to present responders with a limited number of intuitive letters and colors. The International community is in the process of adopting International Standards Organization (ISO) 17840, which provides first and second responders with a standardized format for emergency information. While the ISO 17840 format in coloring and lettering can be adopted and should be encouraged when possible, it is intended for large and heavy vehicles. SAE J3108-1 provides a means for responders to recognize fuel and vehicle type on North American light duty vehicles due to size constraints preventing use of ISO 17840 labels.1 While encouraged to be adopted or referenced by vehicle manufacturers, this RP has been developed for the use of States and other Governmental bodies. The RP is not intended to replace the standards
Mode identification, particularly Modal Map Generation, is pivotal within the NVH (Noise, Vibration, and Harshness) domain for managing the performance of complex systems like TBIW/Powertrain. This study addresses the critical task of accurately identifying Global / Local behavior of a particular system as single entity (Complete TBIW, Power train) or all the systems attached to main structure (Sub Systems i.e Seat , Fuel Tank , Pump etc), which is crucial for effective NVH post-processing. Introducing a novel tool/methodology developed by the Applus IDIADA team, this paper presents an efficient approach to Global & Local mode identification across subsystems, TBIW, and Powertrain levels. Leveraging ".op2" file content, mainly Strain Energy Density[1] and Displacement [2], the tool integrates Machine Learning Techniques [3] to produce mode predictions along with detailed visual outputs such as graphs , pie chart , modal charts etc. Implemented as a Python-based solution compatible with
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