Browse Topic: Materials properties
To obtain real-time tire wear status during vehicle operation, this paper proposes a tire wear detection method based on signal analysis. Firstly, PVDF piezoelectric thin film sensors are pasted in the center of the airtight layer of tires with different degrees of wear to collect tire stress data under different working conditions. Secondly, filter and extract the time-domain and frequency-domain feature information of the collected data to construct a feature dataset. Finally, a deep regression model is established to train the feature dataset and achieve real-time detection of tire damage status. The results indicate that the prediction algorithm based on signal analysis and feature extraction achieves a maximum error of 0.3mm in tire wear detection, demonstrating high accuracy in tire wear detection. Providing tire information for safe driving of vehicles has high industrial application value.
Image-based machine learning (ML) methods are increasingly transforming the field of materials science, offering powerful tools for automatic analysis of microstructures and failure mechanisms. This paper provides an overview of the latest advancements in ML techniques applied to materials microstructure and failure analysis, with a particular focus on the automatic detection of porosity and oxide defects and microstructure features such as dendritic arms and eutectic phase in aluminum casting. By leveraging image-based data, such as metallographic and fractographic images, ML models can identify patterns that are difficult to detect through conventional methods. The integration of convolutional neural networks (CNNs) and advanced image processing algorithms not only accelerates the analysis process but also improves accuracy by reducing subjectivity in interpretation. Key studies and applications are further reviewed to highlight the benefits, challenges, and future directions of
Plasticized polyvinyl chloride (PVC) has many applications in automotive industry including electrical harnesses, door handles, seat and head rest covers, and instrument panel (IP) and other interior trim. In IP applications, the PVC skin plays a critical role in passenger airbag deployment (PAB) by tearing along the scored edge of the PAB door and allowing the door to open and the airbag to inflate to protect the occupant. As part of the IP, the PVC skin may be exposed to elevated temperatures and ultraviolet (UV) radiation during the years of the vehicle life cycle which can affect the PVC material properties over time and potentially influence the kinematics of the airbag deployment. Chemical and thermal aging of plasticized PVC materials have been studied in the past, yet no information is found on how the aging affects mechanical properties at high rates of loading typical for airbag deployment events. This paper compares mechanical properties of the virgin PVC-based IP skin
Automotive chassis components are considered as safety critical components and must meet the durability and strength requirements of customer usage. The cases such as the vehicle driving through a pothole or sliding into a curb make the design (mass efficient chassis components) challenging in terms of the physical testing and virtual simulation. Due to the cost and short vehicle development time requirement, it is impractical to conduct physical tests during the early stages of development. Therefore, virtual simulation plays the critical role in the vehicle development process. This paper focuses on virtual co-simulation of vehicle chassis components. Traditional virtual simulation of the chassis components is performed by applying the loads that are recovered from multi-body simulation (MBD) to the Finite Element (FE) models at some of the attachment locations and then apply constraints at other selected attachment locations. In this approach, the chassis components are assessed
The half vehicle spindle-coupled multi-axial input durability test has been broadly used in the laboratory to evaluate the fatigue performance of the vehicle chassis systems by automotive suppliers and OEMs. In the lab, the front or rear axle assembly is usually held by fixtures at the interfaces where it originally connects to the vehicle body. The fixture stiffness is vital for the laboratory test to best replicate the durability test in the field at a full vehicle level especially when the subframe of the front or rear axle is hard mounted to the vehicle body. In this work, a multi-flexible body dynamics (MFBD) model in Adams/Car was utilized to simulate a full vehicle field test over various road events (rough road, braking, steering). The wheel center loads were then used as inputs for the spindle coupled simulations of the front axle with a non-isolated subframe. Three types of fixtures including trimmed vehicle body, a rigid fixture with softer connections and a rigid fixture
Light Detection and Ranging (LiDAR) is a promising type of sensor for autonomous driving that utilizes laser technology to provide perceptions and accurate distance measurements of obstacles in the vehicle path. In recent years, there has also been a rise in the implementation of LiDARs in modern and autonomous vehicles to aid self-driving features. However, navigating adverse weather remains one of the biggest challenges in achieving Level 5 full autonomy due to sensor soiling, leading to performance degradation that can pose safety hazards. When driving in rain, raindrops impact the LiDAR sensor assembly and cause attenuation of signals when the light beams undergo reflections and refractions. Consequently, signal detectability, accuracy, and intensity are significantly affected. To date, limited studies have been able to perform objective evaluations of LiDAR performance, most of which faced limitations that hindered realistic, controllable, and repeatable testing. Therefore, this
Fatigue design is invariably of prior concern for the automotive industry, no matter of the evolution of the mobility market: at first because carmakers must stay compliant with general structural integrity requirements for reliability, notably applicable to the chassis system, then due to the endless competition for lightweighting in order to mitigate product costs and/or enhance vehicle efficiency. In the past, this key performance was often tackled by basic reference load cases, making use of the simplest signal content, e.g. sinus functions, to practice constant amplitude loads on test rigs and for computations, respectively. Nowadays, full time series coming from proving ground measurements, or any corresponding virtual road load data computations, may be applied to feed complex vehicle computations for virtual assessment and complex test facilities for final approval, under variable amplitude loads. In between, the concept of load spectra (i.e. distribution of amplitudes with
A glow plug is generally used to assist the starting of diesel engines in cold weather condition. Low ambient temperature makes the starting of diesel engine difficult because the engine block acts as a heat sink by absorbing the heat of compression. Hence, the air-fuel mixture at the combustion chamber is not capable of self-ignition based on air compression only. Diesel engines do not need any starting aid in general but in such scenarios, glow plug ensures reliable starting in all weather conditions. Glow plug is actually a heating device with high electrical resistance, which heats up rapidly when electrified. The high surface temperature of glow plug generates a heat flux and helps in igniting the fuel even when the engine is insufficiently hot for normal operation. Durability concerns have been observed in ceramic glow plugs during testing phases because of crack formation. Root cause analysis is performed in this study to understand the probable reasons behind cracking of the
Parts in automotive exhaust assembly are joined to each other using welding process. When the exhaust is subjected to dynamic loads, most of these weld joints experience high stresses. Hence it should be ensured that the exhaust assembly is designed to meet the requirements of exhaust durability for the estimated life of the vehicle. We also know that all parts used in manufacturing of exhaust system have inherent variations with respect to sheet metal thickness, dimensions and shape. Some parts like flex coupling and isolators have high variations in their stiffness based on their material and manufacturing processes. This all leads to a big challenge to ensure that the exhaust system meets the durability targets on a vehicle manufactured with all these variations. This works aims to evaluate the statistical spread in weld life of an exhaust with respect to inherent variations of its components. For the purpose of variational analysis, a Design of Experiments (DOE) is done where
Heat shrink polymer is a type of material used in many industries’ segments due to their ability to contract and fit snugly around objects when heat is applied. These products are commonly commercialized in tube format (e.g.: sleeves), made from polyolefin or fluoropolymers, which have the property of shrinking when heated. Nanomaterials present many applications, and their usage is a remarkable tool aiming to improve many properties of materials. Then, many improvements including increase of performance and price reduction may be achieved due to its unique properties when nanomaterials are used into heat shrink polymer sleeves. This work presents a systematic review about the state of the art on heat-shrinkable materials for the automotive industry. As a methodology, articles from the last 10 years on the subject were selected. The keywords “heat shrink” AND “nanomaterial” AND “tubes OR sleeves” were used in three different databases, being “Scopus”, “Web of Science” and “MDPI”. After
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