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Abstract: As an important vibration damping element in automobile industries, the rubber mount can effectively reduce the vibration transmitted from the engine to the frame. In this study, a method of parameters identification of Mooney-Rivlin model by using surrogate model was proposed to more accurately describe the mechanical behavior of suspension. Firstly, taking the rubber mount as the research object, the stiffness measurement was carried out. And then the calculation model of the rubber mount was established with Mooney-Rivlin model. Latin hypercube sampling was used to obtain the force and displacement calculation data in different directions. Then, the parameters of the Mooney-Rivlin model were taken as the design variables. And the error of the measured force-displacement curve and the calculated force-displacement curve was taken as the system response. Two surrogate models, the response surface model and the back-propagation neural network, were established.

Tortuosity, viscous characteristic length and thermal characteristic length are three important parameters for estimating sound insulation and absorption parameters of porous materials, and it is usually measured by ultrasonic measurement technology, which is cost. In this paper, a method for identifying the tortuosity, viscous characteristic length and thermal characteristic length for the mixed porous fiber materials of kapok fiber with low melting fiber and polyester staple fiber is proposed. The tortuosity is calculated by using the porosity and high-frequency sound absorption coefficient of porous materials. Using JCAL (Johnson-Champoux-Allard-Lafarge) model and genetic algorithm, viscous characteristic length and thermal characteristic length are identified by using the measured parameters, the calculated tortuosity and the measured sound absorption coefficient of porous materials under normal incidence.

Currently the world’s transportation sector is experiencing a paradigm shift towards electric mobility where electric and electronic components form an integral part of the vehicle. The heavy usage of electronic systems needs large size PCB boards with multiple subcomponents connected to it. Such a complex electronic system when excited by dynamic loads, would lead to generation of uncomfortable transient rattle events between the parts. As a result of this, there is an increasing requirement to analyze these subsystems to eliminate any unpleasant noise generation mechanisms. In this study, a printed circuit board (PCB) has been considered for such an analysis. A linear transient analysis was carried out for a sine-sweep excitation. Risk and root cause analysis was performed, and critical locations were identified. Variation in parameters like material incompatibility, connection stiffness, tolerances were considered and analyzed for the same.

Abstract: As an important vibration damping element in automobile industries, the rubber mount can effectively reduce the vibration transmitted from the engine to the frame. The influence of preload on the static characteristics of rubber mounts and the identification of hyper-elastic material model coefficients were studied. Firstly, a test rig for stiffness test of a mount with preload was designed, and the influence of preload on the static force versus displacement of mounts was studied. Then, the model for estimating force versus displacement of rubber mounts was established, the response surface model for identifying coefficients was established, and the identification method for estimating constitute parameter of rubber materials was proposed the crow search algorithm.

Aiming at the laborious process in motor structure modeling for acoustic noise calculation, an improved stator structure modeling scheme is proposed, which includes stator structure simplification and equivalent material parameters identification. The stator assembly is modeled as a homogeneous solid with the same size as the stator core, and the influence of model simplification is compensated by orthotropic equivalent material parameters. The equivalent material parameters are acquired through an optimization algorithm by minimizing the error between FEM calculated modal frequencies and the modal tested results. With the stator assembly model, the motor assembly model is built, and the constrained modal characteristics of the motor assembly are verified by comparing the modal frequencies to the resonance bands in the vibration acceleration spectrum. Finally, the motor structure model is used to calculate the electromagnetic noise of an induction motor.

Driving assistance system is regarded as an effective method to improve driving safety and comfort and is widely used in automobiles. However, due to the different driving styles of different drivers, their acceptance and comfort of driving assistance systems are also different, which greatly affects the driving experience. The key to solving the problem is to let the system understand the driving style and achieve humanization or personalization. This paper focuses on clustering and identification of different driving styles. In this paper, based on the driver's real vehicle experiment, a driving data acquisition platform was built, meanwhile driving conditions were set and drivers were recruited to collect driving information. In order to facilitate the identification of driving style, the correlation analysis of driving features is conducted and the principal component analysis method is used to reduce the dimension of driving features.

Intelligent sweeper vehicle is gradually applied to human life, in which the accuracy of garbage identification and classification can improve cleaning efficiency and save labor cost. Although Deep Learning has made significant progress in computer vision and the application of semantic network segmentation can improve waste identification rate and classification accuracy. Due to the loss of some spatial information during the convolution process, coupled with the lack of specific datasets for garbage identification, the training of the network and the improvement of recognition and classification accuracy are affected. Based on the Unet algorithm, in this paper we adjust the number of input and output channels in the convolutional layer to improve the speed during the feature extraction part. In addition, manually generated datasets are used to greatly improve the robustness of the model.

With the development of highway transportation and automobile industry technology, highway truck overload phenomenon occurs frequently, which poses a danger to road safety and personnel life safety. So it is very important to identify the overload phenomenon. Traditionally, static detection is adopted for overload identification, which has low efficiency. Aiming at this phenomenon, a dynamic overload identification method is proposed. Firstly, the coupled road excitation model of vehicle speed and speed bump is established, and then the 4-DOF vehicle model of half car is established. At the same time, considering that the double input vibration of the front and rear wheels will be coupled when vehicle passes through the speed bump, the model is decoupled. Then, the vertical trajectory of the body in the front axle position is obtained by Carsim software simulation.

The use of lightweight materials is one of the important means to reduce the quality of the vehicle, which involves the connection of dissimilar materials, such as the combination of lightweight materials and traditional steel materials. The riveting quality of self-piercing riveting (SPR) technology will directly affect the safety and durability of automobiles. Therefore, in the initial joint development process, the quality of self-piercing riveting should be inspected and classified to meet safety standards. Based on this, this paper divides the self-piercing riveting quality into riveting appearance quality and riveting section quality. Aiming at the appearance quality of riveting, the generation of cracks on the lower surface of riveting will seriously affect the riveting strength. The existing method of identifying cracks on the lower surface of riveting based on artificial vision has strong subjectivity, low efficiency and cannot be applied on a large scale.

Maintaining and diagnosing vehicle systems often involves a technician connecting a service computer to the vehicle diagnostic port through a vehicle diagnostics adapter (VDA). This creates a connection from the service software to the vehicle network through a protocol adapter. Often, the protocols for the personal computer (PC) hosted diagnostic programs use USB, and the diagnostic port provides access to the controller area network (CAN). However, the PC can also communicate to the VDA via WiFi or Bluetooth. There may be scenarios where these wireless interfaces are not appropriate, such as maintaining military vehicles. As such, a method to defeature the wireless capabilities of a typical vehicle diagnostic adapter is demonstrated without access to the source code or modifying the hardware. The process of understanding the vehicle diagnostic adapter system, its hardware components, the firmware for the main processor and subsystems, and the update mechanism is explored.

Many technical projects, most vehicle and component testing, and all accident reconstructions, product failure analyses, and other forensic investigations, require photographic documentation. Roadway evidence disappears, tested or wrecked vehicles are repaired, disassembled, or scrapped, and components can be tested to failure. Photographs are frequently the only evidence that remains of a wreck, or the only records of subjects before or during tests. Making consistently good images during any inspection is a critical part of the evaluation process.

This SAE Standard defines methods and apparatus to evaluate electronic devices for immunity to potential interference from conducted transients along battery feed or switched ignition inputs. Test apparatus specifications outlined in this procedure were developed for components installed in vehicles with 12-V systems (passenger cars and light trucks, 12-V heavy-duty trucks, and vehicles with 24-V systems). Presently, it is not intended for use on other input/output (I/O) lines of the device under test (DUT).

This SAE Aerospace Recommended Practice (ARP) is not a certification document; it contains no certification requirements beyond those already contained in existing certification documents. The purpose of this ARP is to provide: a Guidelines for potential usage of life samples depending upon the mission environment and at user discretion to use them or not. b Guidelines of: 1 Who approves the parts to be used. 2 Notification requirements to manufacturers. 3 Traceability and segregation. 4 Packing and labeling of such parts. This ARP does not claim that the recommended practices and artifacts described herein are the only acceptable ones. They are, however, used widely today, and merit serious consideration of potential usage where applicable in the military and space hardware. This ARP does not supersede any contracts or legal agreements between contractual parties.

THIS STANDARD ESTABLISHES THE DIMENSIONAL AND VISUAL QUALITY REQUIREMENTS, LOT REQUIREMENTS AND PACKAGING AND LABELING REQUIREMENTS FOR O-RINGS MOLDED FROM AMS7361 (ETHYLENE-PROPYLENE) RUBBER WHICH IS ABLE TO PROVIDE THE REQUIRED SEALING PERFORMANCE IN STATIC APPLICATIONS AT TEMPERATURES DOWN TO -75 °F (-59 °C). IT SHALL BE USED FOR PROCUREMENT PURPOSES.

This specification covers requirements and recommendations for the heat treatment of wrought aluminum alloy raw materials (see 2.2.1) by producers. It supersedes AMS-H-6088 and replaces MIL-H-6088.

The document is a recommended guide for evaluating new or replacement test methods. It considers applicability, suitability, accessibility, and return on effort. Particular emphasis should be placed on completing the “strategy definition” portion of this document (Stage 2), to capture all relevant process stages and complete in a recognizable order for any specific development project. The overall process should: 1 address the rationale behind testing; 2 result in a thorough review of whether a test is fit for purpose; 3 act as a pathway for vetting if a test should be added to AS5780. If, in any project, this process is not an exact fit, users should feel free to adjust, as necessary. The process provides the following stages:

This SAE Aerospace Standard (AS) establishes requirements for the manufacture and certification of tool steel rings for magnetic particle inspection.