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Abstract The rapid development of connected and automated vehicle technologies together with cloud-based mobility services is transforming the transportation industry. As a result, huge amounts of consumer data are being collected and utilized to provide personalized mobility services. Using big data poses serious challenges to data privacy. To that end, the risks of privacy leakage are amplified by data aggregations from multiple sources and exchanging data with third-party service providers, in face of the recent advances in data analytics. This article provides a review of the connected vehicle landscape from case studies, system characteristics, and dataflows. It also identifies potential challenges and countermeasures.

Abstract TOC

Abstract As bicycle design continues to develop, consumers are not satisfied with just the convenience and power-saving features of bicycles, but they also demand a fancy appearance. To achieve dramatic deforming of bike frames, an extreme high-profile difference is required. Thus, this study used rotary swaging, which is the best forging method among shrink forming processes, as the preforming process. The tube diameter reduction rates of 0.28 and 0.31 were set as the main parameters, and the effects of feeding speed, feeding method, and friction factor on the formed tube were analyzed. The results indicated that a higher feeding speed results in a lower rate of tube thickness increase and a lower friction factor results in a lower rate of tube thickness increase. Regarding the effects of feeding methods, the automatic feeding method yielded better surface roughness than the manual method.

Abstract Cavitation erosion caused by high-frequency vibrating walls can appear in the cooling circuit of internal combustion engines along the liners. The vibrations caused by the mechanical forces acting on the crank drive can lead to temporary regions of low pressure in the coolant with local vapor formation, and vapor collapse close to the liner walls leads to erosion damage, which can strongly reduce the lifetime of the entire engine. The experimental investigation of this phenomenon is so time consuming and expensive, which it is usually not feasible during the design phase. Therefore, numerical tools for erosion damage prediction should be preferred. This study presents a numerical workflow for the prediction of cavitation erosion damages by coupling a three-dimensional (3D) Multi-Body-Dynamic (MBD) simulation tool with a 3D Computational Fluid Dynamics (CFD) solver.

Abstract Reducing the weight of automotive components is one of the most achievable solutions for lowering the transport carbon footprint. This is the reason for the rapid increase over the last few years in the replacement of conventional alloys (i.e., steel and cast iron) with low-density materials (i.e., aluminum alloys, composites) and in the redesign of components shape in order to remove the unnecessary material (e.g., related to the introduction of additive manufacturing or high-strength materials). Despite this general trend, the use of higher-density metals and massive geometries is still predominant in the production of structural components, especially for heavy vehicles and safety-relevant parts. Aim of the present review is to summarize how this current situation can be overcome. The analysis started with an investigation about the materials that can be used for the production of structural parts, the potential reduction of the component weight and its costs.

Abstract Single point incremental forming (SPIF) is a sheet forming technology giving low volume production with high flexibility characteristics. The flexibility of the process is mainly related to the fact that incremental forming does not require a dedicated die to operate as compared to other forming processes. Polymers are extensively used for many applications because of their good mechanical properties. Considerable research has been reported for the SPIF of metals, but the researches on polymers are in scarce. In the present work, SPIF is performed on one of the polymers known as polyvinyl chloride. The effect of wall angle, feed rate, and step size on springback, thinning, and surface roughness is observed. It was found that the springback mainly depends on the wall angle but it is least dependent on the feed rate. The thinning and the surface roughness also mainly depend on the wall angle but are least dependent on step size.

Abstract Selective inhibition sintering (SIS) results in easy, flexible, fast, and cost-efficient fabrication of functional parts by using powder material for various applications. The functional part is important for operational examination by fabricating the part unswervingly from computer-aided design (CAD) data. However, poor surface quality is the major disadvantage in the SIS procedure. The selection procedure of optimal operating parameters plays a major role in the fabrication of end products. The present study discusses the effect of key contributing operating parameters on the surface quality of the polyamide parts fabricated by the SIS process. Parameters like heater power (HP), layer thickness (LT), heater feed rate (HFR), machine feed rate (MFR), and bed temperature (BT) were considered in this study.

Abstract Climate change has necessitated the development of “green” alternatives to replace existing materials. This focus has resulted in the push toward fabricating natural fiber-reinforced polymer composites. This research work looks at the surface roughness (SR) of natural fibers like rice husk ash (RHA) and groundnut shell ash (GSA) reinforced in nine different concentrations into an epoxy matrix to form composites. Composite samples are fabricated using various concentrations of natural fibers and measures and optimizes for the SR through the implementation of genetic algorithms (GA). It was found that a minimum SR of 1.422 μm can be obtained for an epoxy/hardener ratio of 3:1 and without the addition of any reinforcements. This optimization was achieved within 102 generations. In addition to GA optimization, another optimization implementation was done through the Taguchi method.

Abstract Combining ball milling with stir casting in the synthesis of nanocomposites is found effective in increasing the strength and ductility of the nanocomposites. In the first step, the nanoparticles used as reinforcement are generated by milling a mixture of aluminum (Al) and manganese dioxide (MnO2) powders. A mixture of Al and MnO2 powders are mixed in the ratio of 1:2.4 by weight and milled at 300 rpm in a high-energy planetary ball mill for different durations of 120 min, 240 min, and 360 min to generate nano-sized alumina (Al2O3) particles. It is supposed that the powders have two different roles during milling, firstly, to generate nano-sized Al2O3 by oxidation at the high-energy impact points due to collision between Al and MnO2 particles, and secondly, to keep nano-sized Al2O3 particles physically separate by the presence of coarser particles.

Abstract Heat-affected zone (HAZ) softening occurs during the laser welding of many Advanced High-Strength Steels (AHSS) that are used for body-in-white (BIW) of automobiles, leading to degradation in the mechanical properties of the welded joints. The microstructure and mechanical properties of dissimilar laser-welded AHSS comprising of as-received 22MnB5 with dual-phase (DP) steels (DP600, DP800, and DP 1000) were investigated in this study. Welds were made at welding speeds ranging from 1 m/min to 3 m/min. Irrespective of welding speed, the DP600-22MnB5 joints fractured in the base metal (BM) of 22MnB5 during tensile tests. Likewise, welded joints of DP800-22MnB5 and DP1000-22MnB5 made at 1 m/min and 2 m/min failed in the BM; however, at 3 m/min the failure location of these joints shifted to the fusion zone (FZ). The fractured surfaces of all the welded combinations were characterized by optical and scanning electron microscopy (SEM).

Abstract Aiming at the problem of low recognition rate and slow speed caused by the small proportion of key area information in feature vectors of original Pyramid Histogram of Gradients (PHOG) features, an improved feature extraction method of PHOG is proposed. The PHOG feature extraction method is combined with edge feature enhancement method based on Census transform to extract feature vectors of fasteners, and dimensionality reduction is processed by Kernel Principal Component Analysis (KPCA) method to reduce the interference of redundant information. The vector is inputted into the support vector machine for training in order to get the classifier model and realize the automatic identification of the fastener’s state. The simulation results show that compared with the traditional PHOG method, this feature extraction method improves the false detection rate by 2.7%, and the complexity of the algorithm is greatly reduced.

Abstract The driving safety performance of autonomous driving vehicles must be ensured before on-road implementation. Because it is not realistic to evaluate every single test condition in real-world traffic, computer simulation methods can be used. The driving safety performance can be evaluated by simulating various driving scenarios and calculating surrogate indicators representing dangerous collision risk. This study used a near-miss database and introduced a surrogate indicator that represents a potential risk in the driving scenarios for rear-end and cut-in collisions. The near-miss video database includes several driving scenarios experienced by human drivers, such as dangerous situations that lead to accidents, potentially dangerous situations that have a risk probability to escalate into dangerous situations, and normal driving situations. A skilled and attentive human driver foresees dangerous situations while driving and avoids them.

Abstract Powder metallurgy is a widely used manufacturing methodology in the gearbox industry. Noise and vibration is a common cause for concern in the gearbox industry due to the continuous contact between gear teeth at high rotational frequencies. Despite this, limited research has been performed investigating the modal properties of powder metal products. This work investigates the damping ratios of a copper-infiltrated steel powder metal ring and a hot-rolled steel ring both experimentally and computationally. Negligible difference was observed between the damping ratios of the powder metal and hot-rolled steel rings. Two proportional damping models were investigated to predict the damping ratios of the powder metal ring. It was found that the Caughey damping model was the most accurate, generating damping ratios within 2.36% for a frequency bandwidth of up to 4000 Hz.

Abstract Road surface characteristics directly influence vehicle safety and performance, and its knowledge can be instrumental to road transportation system safety. This work focuses on the development of a test setup, which was utilized for real-time implementation of a road surface identification algorithm based on the acceleration response of an intelligent tire. Analysis of frequency domain data was used to leverage the tire-road contact information being relayed through the acceleration data. A signal processing algorithm was developed to separate each tire revolution, analyze it in real time, and convert it to the frequency domain in real time. In the end, the performance of the setup was validated with results from the literature, and the distinguishing signature possessed by each surface was used to categorize different terrains into the respective surface categories (Dry Asphalt, Wet Asphalt, Concrete) in real time.

Abstract An innovative analysis approach to evaluate heavy-duty vehicle downhill engine brake performance was developed. The vehicle model developed with GT-Drive simulates vehicle downhill control speeds with different engine brake retarding powers, transmission gears, and vehicle weights at sea level or high altitude. The outputs are then used to construct multi-factor parametric design charts. The charts can be used to analyze the vehicle-level engine brake capabilities or compare braking performance difference between different engine brake configurations to quantify the risk of engine retarding power deficiency at both sea level and high altitude downhill driving conditions.

Abstract The aluminum alloy 7075 sheets have drawn more attention in recent years in the automotive industry for lightweighting. Hot stamping of high-strength aluminum alloy has been developed to improve the formability of the part without springback. Obtaining an adequate quench rate is a critical step of the hot stamping process and corresponds to good strength and corrosion resistance. This work looks at measuring the quench rate of 7075 at advanced aging (AA) and T6 condition via two different approaches: forced air and water with various temperatures. The results verify that water is a superior form of quenching, i.e., from 50°C/s to 550°C/s, the forced air-cooled quench rate is 2°C/s-10°C/s. Besides, mechanical properties such as yield strength, ultimate tensile strength, and uniform elongation were measured by tensile testing. As a result, a correlation between the quench rate and final mechanical properties was developed.

Abstract Crash simulation is targeted mainly carried out by the collision regulations FMVSS simulation to identify problems in vehicle structures. A modern car structure consist of several thousand weld-type connections, and failure in these connections plays an important role for the crashworthiness of the vehicle. Therefore accurate modeling of these connections is important for the automotive industry in order to improve Vehicle collision characteristics. In pursuit of this key requirement, we introduced a proper methodology for the development detailed weld model to study structural response of the weld when the applied load range is beyond the yield strength. Three-dimensional finite element (FE) models of spot welded joints are developed using the LS-Dyna FE code. In this process the force estimation model of spot welds is explained. The results from this paper shows good agreement between the simulations and the tests.

Abstract In the past years, the automotive industry has been integrating multiple hardware in the vehicle to enable new features and applications. In particular automotive applications, it is important to monitor the actions and behaviors of drivers and passengers to promote their safety and track abnormal situations such as social disorders or crimes. These applications rely on multiple sensors that generate real-time data to be processed, and thus, they require adequate data acquisition and analysis systems. This article proposes a prototype to enable in-vehicle data acquisition and analysis based on the middleware framework Robot Operating System (ROS). The proposed prototype features two processing devices and enables synchronized audio and video acquisition, storage, and processing. It was assessed through the implementation of a live inference system consisting of a face detection algorithm from the data gathered from the cameras and the microphone.

Abstract This work puts presents an all-inclusive state of the art bibliographical review of all categories of electrified transportation (xEVs) standards, issued by the most important standardization organizations. Firstly, the current status for the standards by major organizations is presented followed by the graphical representation of the number of standards issued. The review then takes into consideration the interpretation of the xEVs standards developed by all the major standardization organizations across the globe. The standards are differentiated categorically to deliver a coherent view of the current status followed by the explanation of the core of these standards. The ISO, IEC, SAE, IEEE, UL, ESO, NTCAS, JARI, JIS and ARAI electrified transportation vehicles xEV Standards from USA, Europe, Japan, China and India were evaluated. A total approximated of 283 standards in the area have been issued.

Abstract Welding is a dominant joining process employed in fabrication industries, especially in critical areas such as boiler, pressure vessels, and marine structure manufacturing. Online monitoring of welding processes using sensors and intelligent models is increasingly used in industries for predicting weld conditions. Studies are conducted in a Shielded Metal Arc Welding (SMAW) process using sound, current, and voltage sensors to predict the weld conditions. Sensor signatures are acquired from the good weld and defective weld conditions established in this study. Signal processing is carried out, and time-domain statistical features are extracted. Statistical features are also extracted from the power waveform derived from the current and voltage data for all the weld conditions. Classification And Regression Tree (CART) and Support Vector Machine (SVM) algorithms are used to build the statistical models to predict the weld conditions.