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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 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 When the vehicle is under braking condition in the longitudinal motion, the vehicle body will tilt due to the inertial force in motion. A high amplitude will result in uncomfortable feelings of the occupant, such as nervousness or dizziness. To solve the problem, this article presents an adaptive damping system (ADS), which combines the vehicle anti-pitch compensation control with the mixed skyhook (SH) and acceleration-driven-damper (ADD) control algorithm. This ADS can not only improve the vibration effect of the vertical motion for the vehicle but also consider the longitudinal motion of the vehicle body. In addition, a new damper mechanical hardware-in-the-loop test bench is built to verify the effectiveness of the algorithm.

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 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 Advances in hybrid vehicles and electric vehicles (EV) are creating a need for a new generation of lubricants and new lubricant performance tests. Copper corrosion is one prominent concern for hybrid vehicles and EVs and is routinely assessed using a coupon test. This is characterized as metal dissolution, a surface tarnish, or a corrosion layer where a corrosion product remains on the surface and is characterized by a qualitative visual rating. This deficiency does not provide insight into the nature of the corrosion deposit. In an electric drive unit, there are multiple sources of the electric potential present, which can significantly alter the formation of a corrosion deposit which is not assessed in the coupon tests. The formation of a conductive corrosion deposit can result in catastrophic failure of the electric drive unit, either through direct shorting of the motor winding or failure of the power electronics.

Abstract Emerging technologies for connected and automated vehicles (CAVs) are rapidly advancing, and there is an incremental adoption of partial automation systems in existing vehicles. Nevertheless, there are still significant barriers before fully or highly automated vehicles can enter mass production and appear on public roads. These are not only associated with the need to ensure their safe and efficient operation but also with cost and delivery time constraints. A key challenge lies in the testing and validation (T&V) requirements of CAVs, which are expected to be significantly higher than those of traditional and partially automated vehicles. Promising methodologies that can be used toward this goal are scenario-based (SBT) and X-in-the-Loop (XiL) testing. At the same time, complex techniques such as co-simulation and mixed-reality simulation could also provide significant benefits.

Abstract Scenario-based testing is a promising approach to solving the challenge of proving the safe behavior of vehicles equipped with automated driving systems (ADS). Since an infinite number of concrete scenarios can theoretically occur in real-world road traffic, the extraction of scenarios relevant in terms of the safety-related behavior of these systems is a key aspect for their successful verification and validation. Therefore, a method for extracting multimodal urban traffic scenarios from naturalistic road traffic data in an unsupervised manner, minimizing the amount of (potentially biased) prior expert knowledge, is proposed. Rather than an (elaborate) rule-based assignment by extracting concrete scenarios into predefined functional scenarios, the presented method deploys an unsupervised machine learning pipeline. The approach allows for exploring the unknown nature of the data and their interpretation as test scenarios that experts could not have anticipated.

Abstract A unique torque converter test setup was used to measure the torque transmissibility frequency response function of four torque converter clutch dampers using a stepped, multi-sine-tone, excitation technique. The four torque converter clutch dampers were modeled using a lumped parameter technique, and the damper parameters of stiffness, damping, and friction were estimated using a manual, iterative parameter estimation process. The final damper parameters were selected such that the natural frequency and damping ratio of the simulated torque transmissibility frequency response functions were within 10% and 20% error, respectively, of the experimental modal parameters. This target was achieved for all but one of the tested dampers. The damper models include stiffness nonlinearities, and a speed-dependent friction torque due to centrifugal loading of the damper springs.

Abstract Neutron diffraction is a powerful tool for noninvasive and nondestructive characterization of materials and can be applied even in large devices such as internal combustion engines thanks to neutrons’ exceptional ability to penetrate many materials. While proof-of-concept experiments have shown the ability to measure spatially and temporally resolved lattice strains in a small aluminum engine on a timescale of minutes over a limited spatial region, extending this capability to timescales on the order of a crank angle degree over the full volume of the combustion chamber requires careful design and optimization of the engine structure to minimize attenuation of the incident and diffracted neutrons to maximize count rates.

Abstract High load (18 bar IMEP) dual fuel combustion of a premixed natural gas/air charge ignited by directly injected diesel fuel was studied in a large bore gas engine. A nozzle design with low flow rate was installed to inject a small diesel volume (10.4 mm3) equal an energetic amount of about two percent. The effect of compression end temperature on ignition and combustion was investigated using valve timings with early IVC (Miller) and maximum charging efficiency (MaxCC). Furthermore, the engine speed was reduced (1500 rpm to 1000 rpm) for the Miller valve timing to analyze the impact of the chemical time scale on the combustion process. During all experiments, the cylinder charge density was kept constant adjusting the intake pressure and the resulting air mass flow.

Abstract This study implements Flame Image Velocimetry (FIV), a diagnostic technique based on post-processing of high-speed soot luminosity images, to show the in-flame flow field development impacted by after-injection in a single-cylinder, small-bore optical diesel engine. Two after-injection cases with different dwell times between the main injection and after-injection, namely, close-coupled and long-dwell, as well as a main-injection-only case are compared regarding flow fields, flow vector magnitude, and turbulence intensity distribution. For each case, high-speed soot luminosity movies from 100 individual combustion cycles are recorded at a high frame rate of 45 kHz for FIV processing. The Reynolds decomposition using a spatial filtering method is applied to the obtained flow vectors so that bulk flow structures and turbulence intensity distributions can be discussed.

Abstract One of the most important aluminum (Al) alloys among the 7XXX series is 7075 in the T6 temper condition. However, 7075 T6 alloy is proven to be susceptible to stress corrosion cracking (SCC) and has caused many service failures of airplanes. In this research, the susceptibility of 7075 T6 alloys to SCC is approached according to many variables of stress, sodium chloride (NaCl) concentration, pH variation, and aeration. The testing method selected was the three-point bending under complete immersion for a period of 40 days. The results indicate that the threshold for SCC in 7075 T6 alloy lies between 220 and 340 MPa in environments containing as low as 0.5% NaCl concentrations in both neutral and acid solutions. The cracking direction found was different from the expected using other techniques such as tensile or notched specimens, which opens a new gate for testing and monitoring SCC in the 7XXX series.

Abstract We survey the state of the art in off-board diagnostics for vehicles, their occupants, and environments, with particular focus on vibroacoustic (VA) approaches. We identify promising application areas including data-driven management for shared mobility and automated fleets, usage-based insurance, and vehicle, occupant, and environmental state and condition monitoring. We close by exploring the particular application of VA monitoring to vehicle diagnostics and prognostics and propose the introduction of automated vehicle- and context-specific model selection as a means of improving algorithm performance, e.g., to enable smartphone-resident diagnostics. Towards this vision, four strong-performing, interdependent classifiers are presented as a proof of concept for identifying vehicle configuration from acoustic signatures. The described approach may serve as the first step in developing “universal diagnostics,” with applicability extending beyond the automotive domain.

Abstract Statistical machine learning classification methods have been widely used in the fault detection analysis in several engineering domains. This motivates us to provide in this article an overview on the application of these methods in the fault diagnosis strategies and also their successful use in unmanned aerial vehicles (UAVs) systems. Different existing aspects including the implementation conditions, offline design, and online computation algorithms as well as computation complexity and detection time are discussed in detail. Evaluation and validation of these aspects have been ensured by a simple demonstration of the basic classification methods and neural network techniques in solving the fault detection and diagnosis problem of the propulsion system failure of a multirotor UAV. A testing platform of an Hexarotor UAV is completely realized.

Abstract The civil aircraft nosewheel is clamped, lifted, and retained through the pick-up and holding system of the towbarless towing vehicle (TLTV), and the aircraft may be moved from the parking position to an adjacent one, the taxiway, a maintenance hangar, a location near the active runway, or conversely only with the power of the TLTV. The TLTV interfacing with the nose-landing gear of civil transport aircraft for the long-distance towing operations at a high speed could be defined as a towbarless aircraft taxiing system (TLATS). The dynamic loads induced by the system vibration may cause damage or reduce the certified safe-life limit of the nose-landing gear or the TLTV when the towing speed increases up to 40 km/h during the towing operations due to the maximum ramp weight of a heavy aircraft.

Abstract This study focuses on the sudden shaking phenomenon of a sliding door passing through a corner. This phenomenon requires attention because shaking during movement can lead to a harsh operation feeling and a short service life. An experiment based on a test setup was conducted, and the sudden change in the acceleration of a sliding door panel was measured. Based on multi-body dynamics (MBD) analysis and a rigid-flexible coupled model of the sliding door system, the cause of the sudden shaking was determined to be the discontinuous curvature of the middle rail trajectory. A transition curve was proposed as the solution for the discontinuous curvature, and Euler’s spiral was applied in the redesign of the middle rail trajectory. Verified by simulations, the results exhibit considerable improvement in sliding door movement stability, with large reductions in the maximum center of mass (CM) acceleration and guide roller impact force.

Abstract To realize a fast and high-precision online state-of-health (SOH) estimation of lithium-ion (Li-Ion) battery, this article proposes a novel SOH estimation method. This method consists of a new SOH model and parameters identification method based on an improved genetic algorithm (Improved-GA). The new SOH model combines the equivalent circuit model (ECM) and the data-driven model. The advantages lie in keeping the physical meaning of the ECM while improving its dynamic characteristics and accuracy. The improved-GA can effectively avoid falling into a local optimal problem and improve the convergence speed and search accuracy. So the advantages of the SOH estimation method proposed in this article are that it only relies on battery management systems (BMS) monitoring data and removes many assumptions in some other traditional ECM-based SOH estimation methods, so it is closer to the actual needs for electric vehicles (EVs).

Abstract Previous studies have shown that injector aging adversely affects the diesel engine spray formation and combustion. It has also been shown that the oxygenated fuel additive tripropylene glycol monomethyl ether (TPGME) can lower soot emissions. In this study, the effects of injector aging and TPGME on the late-cycle oxidation of soot were investigated using laser diagnostic techniques in a light-duty optical diesel engine at two load conditions. The engine was equipped with a quartz piston with the same complex piston geometry as a production engine. Planar laser-induced incandescence (LII) was used to obtain semiquantitative in-cylinder two-dimensional (2D) soot volume fraction (fv ) distributions using extinction measurements. The soot oxidation rate was estimated from the decay rate of the in-cylinder soot concentration for differently aged injectors and for cases with and without TPGME in the fuel.

Abstract The progressive development toward highly automated driving poses major challenges for the release and validation process in the automotive industry, because the immense number of test kilometers that have to be covered with the vehicle cannot be tackled to any extent with established test methods, which are highly focused on the real vehicle. For this reason, new methodologies are required. Simulation-based testing and, in particular, virtual driving tests will play an important role in this context. A basic prerequisite for achieving a significant reduction in the test effort with the real vehicle through these simulations are realistic test scenarios. For this reason, this article presents a novel approach for generating relevant traffic situations based on a traffic flow simulation in SUMO and a vehicle dynamics simulation in CarMaker. The procedure is shown schematically for an emergency braking function.