Search Results

Abstract An investigation into the pre-ashing of new gasoline particulate filters (GPFs) has demonstrated that the filtration efficiency of such filters can be improved by up to 30% (absolute efficiency improvement) when preconditioned using ash derived from a fuel-borne catalyst (FBC) additive. The additive is typically used in diesel applications to enable diesel particulate filter (DPF) regeneration and can be added directly into the fuel tank of the vehicle. This novel result was compared with ash derived from lube oil componentry, which has previously been shown to improve filtration efficiency in GPFs. The lube oil-derived ash utilized in this work improved the filtration efficiency of the GPF by −30%, comparable to the ash derived from the FBC additive.

Abstract Car manufacturers are continuously improving passenger comfort by advancing technologies including highly automated driving. Before the broad introduction of automated driving, specific human factors regarding passenger comfort must be considered, including motion sickness. Therefore, the identification of the frequency of motion sickness and associated factors in the population is needed to extrapolate the effects for future mobility systems. We conducted three surveys between 2015 and 2020, asking people questions about their experience with motion sickness in cars. Based on the responses of 1165 participants, gender and age showed a strong influence on the self-reported frequency of motion sickness. For deeper analysis, a logistic order regression model was used to estimate the frequency of motion sickness for different user typologies.

Abstract The use of appropriate loads and regulations is of great importance in weld fatigue assessment of rail on-track maintenance equipment and similar vehicles for optimized design. The regulations and available loads, however, are often generalized for several categories, which proves to be overly conservative for some specific categories of machines. EN (European Norm) and AAR (Association of American Railroads) regulations play a pivotal role in determining the applicable loads and acceptance criteria within this study. The availability of track-induced fatigue load data for the cumulative damage approach in track maintenance machines is often limited. Consequently, the FEA-based validation of rail track maintenance equipment often resorts to the infinite life approach rather than cumulative damage approach for track-induced travel loads, resulting in overly conservative designs.

Abstract Water quality monitoring is needed for the effective management of water resources. Periodic sampling and regular inspection/analysis allow one to classify water and identify changes or trends in water quality over time. This article presents a novel concept of an Amphibious Hybrid Unmanned Aerial Vehicle (AHUAV) that can operate in air and water for rapid water sampling, real-time water quality analysis, and water body management. A methodology using the developed AHUAV system for water body management has also been proposed for an easier and effective way of monitoring water bodies using advanced drone technologies. Using drones for water body management can be a cost-effective and efficient way of carrying out regular inspections and continual monitoring.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract The ground-effect problems of loss of thrust and fountain-effect instabilities are quantified. Experiments to control and augment ground-effect lift and stability are presented, including jet momentum reflection and fountain redirection using various types of internal and external underbody ventral strakes. By strategically designing the vertical takeoff and landing (VTOL) ventral surface, reflection of the impinging fountain momentum is possible so that instead of losing 10% thrust while in ground-effect, remarkably, thrust is augmented 10% or more to a considerable height above the ground, in addition to stabilizing random pitch and roll moments caused by fountain instability.

Abstract The crush energy is a key parameter to determine the delta-V in accident reconstructions. Since an accurate car crush profile can be obtained from 3D scanners, this research aims at validating the methods currently used in calculating crush energy from a crush profile. For this validation, a finite element (FE) car model was analyzed using various types of impact conditions to investigate the theory of energy-based accident reconstruction. Two methods exist to calculate the crush energy: the work based on the barrier force and the work based on force calculated by the vehicle acceleration times the vehicle mass. We show that the crush energy calculated from the barrier force was substantially larger than the internal energy calculated from the FE model. Whereas the crush energy calculated from the vehicle acceleration was comparable to the internal energy of the FE model.

Abstract The project of lean management is implemented in General Motors India Private Limited, Pune, India plant. The aim of the project is to improve manpower utilization by removing seven types of wastes using lean management system in kitting process. Lean manufacturing or management is the soul of Just-In-Time philosophy and is not new in Automobile manufacture sector where it born. Kitting area is analogs to the modern supermarket where required components, parts, consumables, subassemblies are kept in bins. These bins are placed in racks so that choosing right part at right time can be achieved easily. Video recording, in-person observation, feedback from online operators and other departments such as maintenance, control, supply chain etc. are taken. It is observed that the work content performed by current strength of operators can be performed by less number of operators. After executing this project, it was possible to reduce one operator and increase manpower utilization.

Abstract As the automotive industry moves toward electrification, battery costs and vehicle range are two large issues that will delay this movement. These issues can be partially resolved through the use of series-hybrid vehicles, which can replace a portion of the batteries with a small engine that serves to recharge the battery. Given the size, weight, and operational constraints of this engine, a 2-stroke engine makes sense. Indeed, 2-stroke engines are currently being used for a number of applications including consumer products, small ground vehicles, boats, and drones. The technology has significantly improved to allow for reduced emissions and increased efficiency, especially through the use of direct injection. This article discusses the state of technology for 2-stroke engines and its application in series-hybrid vehicles. In particular, the use of a 2-stroke engine as a range extender provides significant benefit in range and cost over fully electric vehicles.

Abstract The first objective of this study, addressed in Part 1, is to use finite element (FE) human body modeling (HBM) to evaluate the tangent of the Belt-to-Pelvis angle (tanθBTP) as a submarining predictor in frontal crashes for occupants in reclined seats. The second objective, addressed in Part 2, is to use this predictor to assess two technical solutions for reducing submarining risks for two different occupant anthropometries. In Part 1, tanθBTP (the lap belt penetration from the anterior superior iliac spine [ASIS] in the abdominal direction) was evaluated in impact simulations with varying seat belt anchor positions. Sled simulations with a 56 km/h full-frontal crash pulse were performed with the SAFER HBM morphed to the anthropometry of a small female and average male. A correlation was found between the submarining predictor and submarining.

Abstract Previous works have established strategies to model artificial test lightning plasma with specific waveform parameters and use the predicted plasma behavior to estimate test specimen damage. To date no computational works have quantified the influence of varying the waveform parameters on the predicted plasma behavior and resulting specimen damage. Herein test standard Waveform B has been modelled and the waveform parameters of “waveform peak,” “rise time,” and “time to reach the post-peak value” have been varied. The plasma and specimen behaviors have been modelled using the Finite Element (FE) method (a Magnetohydrodynamic FE multiphysics model for the plasma, a FE thermal-electric model for the specimen). For the test arrangements modelled herein, it has been found that “peak current” is the key parameter influencing plasma properties and specimen damage.

Abstract The development of a long-term sustainable hydrogen energy economy for commercial vehicle transportation will need to overcome key critical technical and logistics considerations in the near term. As compared to zero-emission powertrains, fossil-fuel-based powertrains provide mission flexibility and high uptime at a comparatively low total cost of ownership (TCO). While the incumbent carbon-intensive powertrains suffer from poor efficiency and are not sustainable to support global climate change initiatives in transportation decarbonization, techno-economic challenges continue to create complex barriers to the large-scale displacement of these with highly electrified powertrains architectures. This article specifically addresses opportunities that well-targeted subsidies would afford in achieving fuel cell electric powertrain financial parity with diesel powertrains in heavy-duty trucks (HDTs).

Abstract Gasoline Particulate Filter (GPF) technology is the key method of meeting the new regulations for particulate matter emissions from gasoline cars. Computer-Aided Engineering is widely used for the design of such systems; thus the development of accurate models for GPFs is crucial. Most existing pressure loss models require experimental calibration of several parameters. These experiments are performed at room temperatures, or on an engine test bench, where gas properties cannot be fully controlled. This article presents pressure loss measurements for clean GPF cores performed with uniform airflow and temperatures up to 680°C. The flow regime in GPF is shown to be different to that in the Diesel Particulate Filters (DPF) due to high flow rates and temperatures. Therefore, most of the existing models are not suitable for design of the new generation of aftertreatment devices. To separate pressure loss contribution from different sources, unplugged filter cores are tested.

Abstract China is driving the transition away from internal combustion engine vehicles (ICEVs) to plug-in electric vehicles (PEVs, including plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs)) to address its pressing energy security and environmental pollution problems. The recent enactment of the dual-credit scheme mandate will compensate for the phase out of the subsidy program, while ostensibly shifting the burden of filling in the cost gap between PEVs and ICEVs from the government to the automakers (though in practice to car buyers).

Abstract This article presents a new machine learning (ML) development lifecycle which will constitute the core of the new aeronautical standard on ML called AS6983, jointly being developed by working group WG-114/G34 of EUROCAE and SAE. The article also presents a survey of several existing standards and guidelines related to ML in aeronautics, automotive, and industrial domains by comparing and contrasting their scope, purpose, and results.

Abstract The lack of traceability in today’s supply-chain system for auto components makes counterfeiting a significant problem leading to millions of dollars of lost revenue every year and putting the lives of customers at risk. Traditional solutions are usually built upon hardware such as radio-frequency identification (RFID) tags and barcodes, and these solutions cannot stop attacks from supply-chain (insider) parties themselves as they can simply duplicate products in their local database. This industry-academia collaborative work studies the benefits and challenges associated with the use of distributed ledger (or blockchain) technology toward preventing counterfeiting in the presence of malicious supply-chain parties. We illustrate that the provision of a distributed and append-only ledger jointly governed by supply-chain parties themselves makes permissioned blockchains such as Hyperledger Fabric a promising approach toward mitigating counterfeiting.

Abstract Non-pneumatic tires (NPTs) have been widely used due to their advantages of no occurrence of puncture-related problems, no need of air maintenance, low rolling resistance, and improvement of passenger comfort due to its better shock absorption. It has a variety of applications as in earthmovers, planetary rover, stair-climbing vehicles, and the like. Recently, the unique puncture-proof tire system (UPTIS) NPT has been introduced for passenger vehicles segment. The spoke design of NPT-UPTIS has a significant effect on the overall working performance of tire. Optimized tire performance is a crucial factor for consumers and original equipment manufacturers (OEMs). Hence to optimize the spoke design of NPT-UPTIS spoke, the top and bottom curve of spoke profile have been described in the form of analytical equations. A generative design concept has been introduced to create around 50,000 spoke profiles.

Abstract Intelligent tires, as an emerging technology, have great potential for tire-road contact information identification and new vehicle active safety system design. In this article, a tire-road friction coefficient estimation method is proposed based on intelligent tires application with three-axis accelerometer. At first, a finite element tire model with an accelerometer is established using ABAQUS platform. Accelerometer body frame transformation is considered during the tire rotation. Subsequently, the contact patch length is determined according to the peak of the longitudinal acceleration profile. Meanwhile, tire lateral deflection is calculated from the tire lateral acceleration. By curve fitting the lateral deflection model with least square method, tire lateral force and the aligning moment are derived and then the friction coefficient is estimated via brush model.

Abstract This article introduces a finite element (FE) approach to determine tire deformation and its effect on open-wheel race car aerodynamics at high vehicle velocities. In recent literature tire deformation was measured optically. Combined loads like accelerating at a corner exit are difficult to reproduce in wind tunnels and require several optical devices to measure the tire deformation. In contrast, an FE approach is capable of determining the tire deformation in combined load states accurately. Additionally, the temperature influence on tire deformation is investigated. The FE tire model was validated using three-dimensional (3D) scan measurements; stiffness measurements in the vertical, lateral, and longitudinal direction; and the change of loaded radius with speed at different loads, respectively. The deformed shape of the tire of the FE model was used in a computational fluid dynamics (CFD) simulation.

Abstract The wide application of Gasoline Direct Injection (GDI) engines and the increasingly stringent Particulate Matter (PM) and Particulate Number (PN) regulations make Gasoline Particulate Filters (GPFs) with high filtration efficiency and low pressure drop highly desirable. However, due to the specifics of GDI operation and GDI PM, the design of these filters is even more challenging as compared to their diesel counterparts. Computational Fluid Dynamics (CFD) studies have been shown to be an effective way to investigate filter performance. In particular, our previous two-dimensional (2D) CFD study explicated the pore size and pore-size distribution effects on GPF filtration efficiency and pressure drop. The “throat unit collector” model developed in this study furthers this work in order to characterize the GPF wall microstructure more precisely.