Search Results

Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement.

The present study discusses about the determination of the Seal drag force in the application where elastomeric seal is used with metallic interface in the presence of different fluids. An analytical model was constructed to predict the seal drag force and experimental test was performed to check the fidelity of the analytical model. A Design of Experiment (DoE) was utilized to perform experimental test considering different factors affecting the Seal drag force. Statistical tools such as Test for Equal Variances and One way Analysis of Variance (ANOVA) were used to draw inferences for population based on samples tested in the DoE test. It was observed that Glycol based fluids lead to lubricant wash off resulting into increased seal drag force. Additionally, non-lubricated seals tend to show higher seal drag force as compared to lubricated seals. Keywords: Seal Drag, DoE, ANOVA

The paper presents a theoretical framework for the detection and first-level preliminary identification of potential defects on aero-structure components while employing ultrasonic guided wave based structural health monitoring strategies, systems and tools. In particular, we focus our study on ground inspection using laser-Doppler scan of surface velocity field, which can also be partly reconstructed or monitored using point sensors and actuators on-board structurally integrated. Using direct wave field data, we first question the detectability of potential defects of unknown location, size, and detailed features. Defects could be manufacturing defects or variations, which may be acceptable from design and qualification standpoint; however, those may cause significant background signal artifacts in differentiating structure progressive damage or sudden failure like impact-induced damage and fracture.

The evaluation of aircraft characteristics through flight test maneuvers is fundamental to aviation safety and understanding flight attributes. This research project proposes a comprehensive methodology to detect and analyze aircraft maneuvers using full flight data, combining signal processing and machine learning techniques. Leveraging the Wavelet Transform, we unveil intricate temporal details within flight data, uncovering critical time-frequency insights essential for aviation safety. The integration of Long Short-Term Memory (LSTM) models enhances our ability to capture temporal dependencies, surpassing the capabilities of machine learning in isolation. These extracted maneuvers not only aid in safety but also find practical applications in system identification, air-data calibration, and performance analysis, significantly reducing pre-processing time for analysts.

Verification and validation (V&V) of autonomous vehicles (AVs) is a challenging task. AVs must be thoroughly tested, to ensure their safe functionality in complex traffic situations including rare but safety-relevant events. Furthermore, AVs must mitigate risks and hazards that result from functional insufficiencies, as described in the Safety of the Intended Functionality (SOTIF) standard. SOTIF analysis includes iterative identification of driving scenarios that are not only unsafe, but also unknown. However, identifying SOTIF’s unknown-unsafe scenarios is an open challenge. In this paper we proposed a systematic optimization-based approach for identification of unknown-unsafe scenarios. The proposed approach consists of three main steps including data collection, feature extraction and optimization towards unknown unsafe scenarios.

As a key technology of intelligent transportation system, vehicle type recognition plays an important role in ensuring traffic safety,optimizing traffic management and improving traffic efficiency, which provides strong support for the development of modern society and the intelligent construction of traffic system. Aiming at the problems of large number of parameters, low detection efficiency and poor real-time performance in existing vehicle type recognition algorithms, this paper proposes an improved vehicle type recognition algorithm based on YOLOv5. Firstly, the lightweight network model MobileNet-V3 is used to replace the backbone feature extraction network CSPDarknet53 of the YOLOv5 model. The parameter quantity and computational complexity of the model are greatly reduced by replacing the standard convolution with the depthwise separable convolution, and enabled the model to maintain higher accuracy while having faster reasoning speed.

This study delves into the dynamic properties of hybrid composite materials, specifically focusing on the natural frequency and modal damping characteristics of Coir Fiber-Rubber Particles Reinforced Polymer Composites (CRP). Comprehensive experimental investigations were conducted utilizing an FFT analyzer. Initial experiments involved the preparation of specimens with varying rubber content, ranging from 2% to 5%. Coir, known for its cellulose-rich composition, was selected due to its innate damping properties, making it highly effective in mitigating vibrations. The primary motivation behind this research is to provide cost-effective solutions for reducing vibrations in mobility vehicles, addressing challenges associated with passenger comfort, durability, and overall performance. The study yielded promising results, with CRP exhibiting substantial reductions in vibrations.

Water content estimation is a key problem for studying the PEM fuel cell. When several hundred fuel cells are connected in serial and their active surface area is enlarged for sufficient power, the difference between cells becomes significant with respect to voltage and water content. The voltage of each cell is measurable by the cell voltage monitor (CVM) while it is difficult to estimate water content of the individual. Resistance of the polymer electrolyte membrane is monotonically related to its water content, so that the new online high frequency resistance (HFR) measurement technique is investigated to identify the uniformity of water content between cells and analyze its sensitivity to operating conditions in this paper. Firstly, the accuracy of the proposed technique is experimentally validated to be comparable to that of a commercialized electrochemical impedance spectroscopy (EIS) measurement equipment.

Rubber isolators are widely used under random vibrations. In order to predict their fatigue life, a study on the fatigue analysis methodology for rubber isolators is carried out in this paper. Firstly, taking a mount used for isolating air conditioning compressor vibrations as studying example, accelerations versus time of rubber isolator at both sides are acquired for a car under different running conditions. The acceleration in time domain is transformed to frequency domain using the Fourier transform, and the acceleration power spectral density (PSD) is the obtained. Using the PSD as input, fatigue test is carried for the rubber isolator in different temperature and constant humidity conditions. A finite element model of the rubber isolator using ABAQUS is established for estimating fatigue life, and model validity is verified through static characteristic testing. Dynamic responses of the rubber isolator at frequency domain are calculated if a unit load is applied.

As a key tool to maintain urban cleanliness and improve the road environment, road cleaning vehicles play an important role in improving the quality of life of residents. However, the traditional road cleaning vehicle requires the driver to monitor the situation of road garbage at all times and manually operate the cleaning process, resulting in an increase in the driver 's work intensity. To solve this problem, this paper proposes a road garbage recognition algorithm based on improved YOLOv5, which aims to reduce labor consumption and improve the efficiency of road cleaning. Firstly, the lightweight network MobileNet-V3 is used to replace the backbone feature extraction network of the YOLOv5 model. The number of parameters and computational complexity of the model are greatly reduced by replacing the standard convolution with the deep separable convolution, which enabled the model to have faster reasoning speed while maintaining higher accuracy.

In the field of autonomous driving trajectory planning, it’s virtual to ensure real-time planning while guaranteeing feasibility and robustness. Current widely adopted approaches include decoupling path planning and velocity planning based on optimization method, which can’t always yield optimal solutions, especially in complex dynamic scenarios. Furthermore, search-based and sampling-based solutions encounter limitations due to their low resolution and high computational costs. This paper presents a novel spatio-temporal trajectory planning approach that integrates both search-based planning and optimization-based planning method. This approach retains the advantages of search-based method, allowing for the identification of a global optimal solution through search. To address the challenge posed by the non-convex nature of the original solution space, we introduce a spatio-temporal semantic corridor structure, which constructs a convex feasible set for the problem.

This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

This paper delves into the investigation of flatness-based active damping control for hybrid vehicle transmissions. The main objective is to improve the current in-production controller performances without the need for additional sensors or observers. The primary goals include improving torque setpoint tracking, enhancing robustness margins, and ensuring zero steady-state torque correction. The investigation proceeds in several steps: Initially, both the general differential flatness property and the identification of flat outputs in linear dynamical systems are revisited. Subsequently, the bond graph formalism is employed to deduce straightforwardly the dynamical equations of the system. Next, a new flat output of the vehicle transmission is identified and utilized to formulate the trajectory tracking controller to align with the required control objectives and to fulfill the system constraints.

The Indian passenger vehicle market has grown by more than 40% by volume in the last decade and has reached a record high in FY23. This has created a more diverse and demanding customer base that values interior design and quality. The modern customer expects a high level of aesthetics and sophistication in their vehicle interiors - including in the luggage area. The Luggage Cover (Parcel Tray) is a component in the luggage area of a passenger vehicle that is used to conceal the luggage & improve its aesthetics. The cover is generally made of thermoplastic material with rotating hinges and is held in its place by the compression from the back door, which is frequently opened and closed. The parts that connect the cover to the door (usually an elastomer interface on the thermoplastic tray) tend to change over a period due to climatic conditions and leads to rattling concerns over a period.

Silicone and rubber composite, often called Ceramifiable Silicone Rubber Composites(CSRCs), has proven to show excellent mechanical and thermal properties. CSRC materials have been mainly used in industrial applications like electrical insulating cables, decorations, and fire-proof materials. The mechanical and ceramifiable properties of CSRC can be altered by changing the silicone rubber matrix and by adding the right additives or fillers. In this work, we prove the potential of CSRCs as thermal insulating materials in battery packs. Specifically, we explore the usage of CSRC inside the battery pack to improve safety during thermal events. We also characterize the material properties before and after exposing the CSRC to elevated temperatures and flame. Finally, we investigate the effectiveness of the CSRC sheet in preventing or delaying cell-to-cell thermal propagation during a thermal runaway event inside the battery pack.

For more than a century, pneumatic (air-inflated) tires have totally dominated the market for road vehicle tires. However, in the recent two decades, interest has grown in developing airless tires. Some of the authors were involved in design of an early version in composite material 15-30 years ago for passenger cars. Presently, the EU project LEON-T (Low particle Emissions and lOw Noise Tyres) includes a part in which prototypes for innovative heavy goods vehicle (HGV) tires are developed, with the main purpose to reduce noise emission by 6 dB. To reduce noise that much it is believed that airless tires are needed. A special challenge is to get a durable design able to carry typical truck tire loads. This paper introduces the principal design of airless tires. Airless tire prototypes are intended to be developed by partner Euroturbine, in cooperation with mainly Applus+ IDIADA, VTI and subcontractor Lightness by Design.

The art of rubber formulation science always has a scope for fine-tuning with changing the parameters like base polymer grade selection, filler selection, curing system/cross link density, manufacturing methods, and many. Hence forth the filler manufacturer arrived differentiation of the filler already, this paper provides a description of rubber formulation tuning for damped vibration automotive applications. Acicular spiky spherical and hollow spherical nano silica selected as filler. With the thorough knowledge of elastomeric formulation and with doping different new selected silica grades, an optimized DOE was done. New formulation development was focused on isolation characteristics without affecting other necessary properties. The different inputs for finite element calculations was studied with the effects of doping different fillers and also studied the resultant virtual output in damping coefficients.

Rubber is one of the most used materials currently selected to produce automotive parts, but, for specific applications, some improvement is required in its properties through the addition of some components to the rubber compound formulation. Because of that, mechanical, thermal, and chemical properties are enhanced in order to meet strict requirements of the vast range of application of the rubber compounds. In addition to improving material properties, the combination of different substances, also aims to improve processability and reduce the costs of the final product. Recently, the use of nanofillers has been very explored because of their distinctive properties and characteristics. Among the nanofillers under study, graphene is known for its high-barrier property, thermal and electrical conductivities, and good mechanical properties.

In the context of distributed-driven electric vehicles, the temperature of permanent magnet in-wheel motors tends to rise during prolonged and overload operating conditions. This temperature increase can lead to parameter drift in the motors, resulting in a decline in motor control performance, and in severe cases, motor failures. To address these issues, this paper establishes a motor parameter identification model based on the dq-axis stator current equation of the permanent magnet in-wheel motor. An improved Particle Swarm Optimization PSO algorithm is introduced to identify parameters such as motor resistance, inductance, and magnetic flux. In contrast to traditional parameter identification algorithms based on mathematical models, the improved PSO algorithm can simultaneously identify multiple parameters without encountering rank deficiency issues.

Pneumatic valves are widely used in heavy commercial vehicles’ air braking systems. These valves are mainly used in the braking system layout to maintain the vehicle stability during dynamic conditions. Rubber components are inevitable in valves as a sealing element, and it is very difficult to predict the behavior due to its nonlinear nature. Basically, this valve efficiency is defined in terms of performance and response characteristics. These characteristics are determined in the concept stage itself using 1D simulation software. AMESim software has a variety of elements to use in a unique way for performance and response behavior prediction. For pneumatic valves, 1D analysis is an effective method and it gives good correlation with actual test results. During the modelling of pneumatic valves, some of the contacts between rubber and metals are controlled by various parameters such as damping, contact stiffness and desired phase angle.