Search Results

Abstract The ground vibration test (GVT) is an important phase in a new aircraft development program, or the structural modification of a certified aircraft, to experimentally determine the structural vibrational modes of the aircraft and their modal parameters. These modal parameters are used to validate and correlate the dynamic finite element model of the aircraft to predict potential structural instabilities (such as flutter), assessing the significance of modifications to research vehicles by comparing the modal data before and after the modification and helping to resolve in-flight anomalies. Due to the high cost and the extensive preparations of such tests, a new method of vibration testing called the taxi vibration test (TVT) rooted in operational modal analysis (OMA) was recently proposed and investigated as an alternative method to conventional GVT.

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 Ground vibration testing (GVT) is an important phase of the development, or the structural modification of an aircraft program. The modes of vibration and their associated parameters extracted from the GVT are used to modify the structural model of the aircraft to make more reliable dynamics predictions to satisfy certification authorities. Due to the high cost and the extensive preparations for such tests, a new method of vibration testing called taxi vibration testing (TVT) rooted in operational modal analysis (OMA) was recently proposed and investigated by the German Institute for Aerospace Research (DLR) as alternative to conventional GVT. In this investigation, a computational framework based on fully coupled flexible multibody dynamics for TVT is presented to further investigate the applicability of the TVT to flexible airframes. The time domain decomposition (TDD) method for OMA was used to postprocess the response of the airframe during a TVT.

Abstract The United Nation Economic Commission for Europe (UNECE) Regulation 155—Cybersecurity and Cybersecurity Management System (UN R155) mandates the development of cybersecurity management systems (CSMS) as part of a vehicle’s lifecycle. An inherent component of the CSMS is cybersecurity risk management and assessment. Validation and verification testing is a key activity for measuring the effectiveness of risk management, and it is mandated by UN R155 for type approval. Due to the focus of R155 and its suggested implementation guideline, ISO/SAE 21434:2021—Road Vehicle Cybersecurity Engineering, mainly centering on the alignment of cybersecurity risk management to the vehicle development lifecycle, there is a gap in knowledge of proscribed activities for validation and verification testing.

Abstract Since the complexity of modern vehicles is increasing continuously, car manufacturers are forced to improve the efficiency of their development process to remain profitable. A frequently mentioned measure is the consequent integration of virtual methods. In this regard, objective evaluation criteria are essential for the virtual design of driving dynamics. Therefore, this article aims to identify robust objective evaluation criteria for the nonlinear combined longitudinal and lateral dynamics of a vehicle. The article focuses on the acceleration in a turn maneuver since available objective criteria do not consider all relevant characteristics of vehicle dynamics. For the identification of the objective criteria, a generic method is developed and applied. First, an open-loop test procedure and a set of potential robust objective criteria are defined.

Abstract The ASTM D130 was first issued in 1922 as a tentative standard for the detection of corrosive sulfur in gasoline. A clean copper strip was immersed in a sample of gasoline for three hours at 50°C with any corrosion or discoloration taken to indicate the presence of corrosive sulfur. Since that time, the method has undergone many revisions and has been applied to many petroleum products. Today, the ASTM D130 standard is the leading method used to determine the corrosiveness of various fuels, lubricants, and other hydrocarbon-based solutions to copper. The end-of-test strips are ranked using the ASTM Copper Strip Corrosion Standard Adjunct, a colored reproduction of copper strips characteristic of various degrees of sulfur-induced tarnish and corrosion, first introduced in 1954. This pragmatic approach to assessing potential corrosion concerns with copper hardware has served various industries well for a century.

Abstract Parking an articulated vehicle is a challenging task that requires skill, experience, and visibility from the driver. An automatic parking system for articulated vehicles can make this task easier and more efficient. This article proposes a novel method that finds an optimal path and controls the vehicle with an innovative method while considering its kinematics and environmental constraints and attempts to mathematically explain the behavior of a driver who can perform a complex scenario, called the articulated vehicle park maneuver, without falling into the jackknifing phenomena. In other words, the proposed method models how drivers park articulated vehicles in difficult situations, using different sub-scenarios and mathematical models.

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.

Abstract To have a more complete understanding of the fuel effects on each subsequent stage of a stochastic preignition event in a spark-ignition engine and to build on the previous work of understanding the propensity of fuel to initiate and sustain a preignition flame, this work is focused on examining the role of fuel on the onset of knock and the intensity of superknock once the unburned mixture reaches certain conditions ahead of the preignition flame. Using a “skip advance” spark test method to simulate preignition flames initiated at different cylinder conditions, more than 20 single- and multicomponent fuels were ranked based on the condition required to reach the onset of knock (the start of end-gas autoignition) and the condition that leads to severe superknock intensities.

Abstract Assessing the functional quality of an engine lubricant through real-time sensing could pave the way for development of comprehensive engine health monitoring systems. In this study, a permittivity-based, commercial off-the-shelf (COTS) oil quality sensor was implemented in the lubricant flow of a diesel engine after detailed evaluation on a benchtop test facility. The sensor was mounted on the oil filter housing of the engine in the post-filter oil flow, and its implementation required no modifications to the engine block. Simultaneously, the lubricant flow was visualized by incorporating a novel test cell in the oil flow path. Both the sensor assembly and the flow visualization cell were fully characterized on the benchtop facility prior to implementation on the engine.

Abstract The shot-to-shot variations in common rail injection systems are primarily caused by pressure wave oscillations in the rail, pipes, and injector body. These oscillations are influenced by fuel physical properties, injector needle movement, and pressure and suction control valve activations. The pressure waves are generated by pump actuation and injector needle movement, and their frequency and amplitude are determined by fluid properties and flow path geometry. These variations can result in cycle-to-cycle engine fluctuations. In multi-injection and split-injection strategies, the pressure oscillation from the first shot can impact the hydraulic characteristics of subsequent shots, resulting in variations in injection rate and amount. This is particularly significant when using alternative fuels such as biodiesel, which aim to reduce emissions while maintaining fuel atomization quality.

Abstract A rapid compression and expansion machine (RCEM) was used to experimentally investigate the ignition phenomena of dielectric-barrier discharge (DBD) in engine conditions. The effect of elevated pressure and temperature on ignition phenomena of a methane/air premixed mixture was investigated using a DBD igniter. The equivalence ratio was changed to elucidate the impact of DBD on flame kernel development. High-speed imaging of natural light and OH* chemiluminescence enabled visualization of discharges and flame kernel. According to experimental findings, the discharges become concentrated and the intensity increases as the pressure and temperature rise. Under different equivalence ratios, the spark ignition (SI) system has a shorter flame development time (FDT) as compared with the DBD ignition system.

Abstract To investigate the interplay between driver handling behaviors, this article collects data on vehicle kinematic parameters characterizing driver handling characteristics under natural driving, estimates the probability density curves of the parameters using the kernel density method, and fits the curve equations. On this basis, a percentile correlation analysis was performed between the parameters to obtain the influence relationship between the handling behaviors. The results show that longitudinal maneuvers are frequent and intense in the 0–10 km/h speed range, lateral maneuvers are more intense in the 10–30 km/h speed range, and the interaction between longitudinal and lateral maneuvers is more intense in the acceleration phase. This study enriches the natural driving dataset and illustrates the correlation of driving behavior under natural driving, providing a theoretical and data basis for the development of driver-oriented intelligent driving technologies.

Abstract Autonomous driving systems (ADS) have been widely tested in real-world environments with operators who must monitor and intervene due to remaining technical challenges. However, intervention methods that require operators to take over control of the vehicle involve many drawbacks related to human performance. ADS consist of recognition, decision, and control modules. The latter two phases are dependent on the recognition phase, which still struggles with tasks involving the prediction of human behavior, such as pedestrian risk prediction. As an alternative to full automation of the recognition task, cooperative recognition approaches utilize the human operator to assist the automated system in performing challenging recognition tasks, using a recognition assistance interface to realize human-machine cooperation.

Abstract While machine-learning-based methods suffer from a lack of transparency, rule-based (RB) methods dominate safety-critical systems. Yet the RB approaches cannot compete with the first ones in robustness to multiple system requirements, for instance, simultaneously addressing safety, comfort, and efficiency. Hence, this article proposes a decision-making and control framework which profits from the advantages of both the RB and machine-learning-based techniques while compensating for their disadvantages. The proposed method embodies two controllers operating in parallel, called Safety and Learned. An RB switching logic selects one of the actions transmitted from both controllers. The Safety controller is prioritized whenever the Learned one does not meet the safety constraint, and also directly participates in the Learned controller training.

Abstract The vehicle dynamic state is essential for stability control and decision-making of intelligent vehicles. However, these states cannot usually be measured directly and need to be obtained indirectly using additional estimation algorithms. Unfortunately, most of the existing estimation methods ignore the effect of data loss on estimation accuracy. Furthermore, high-order filters have been proven that can significantly improve estimation performance. Therefore, a second-order fault-tolerant extended Kalman filter (SOFTEKF) is designed to predict the vehicle state in the case of data loss. The loss of sensor data is described by a random discrete distribution. Then, an estimator of minimum estimation error covariance is derived based on the extended Kalman filter (EKF) framework. Finally, experimental tests demonstrate that the SOFTEKF can reduce the effect of data loss and improve estimation accuracy by at least 10.6% compared to the traditional EKF and fault-tolerant EKF.

Abstract Trajectory tracking control, as one of the core technologies of intelligent driving vehicles, determines the driving performance and safety of intelligent driving vehicles and has received extensive attention and research. In recent years, most of the research results of trajectory tracking control are only applicable to conventional working conditions; however, the actual operating conditions of intelligent driving vehicles are complex and variable, so the research of trajectory tracking control algorithm should be extended to the high-speed low-adhesion coefficient, large curvature, variable curvature, and other compound limit working conditions. This requires more consideration of the vehicle dynamics in the controller design.

Abstract Certain advanced driver assistance systems (ADAS) have the potential to boost energy efficiency in real-world scenarios. This article details a radar-based driver assistance scheme designed to minimize fuel consumption for a commercial vehicle by predictively optimizing braking and driving torque inputs while accommodating the driver’s demand. The workings of the proposed scheme are then assessed with a novel integration of the driver assistance functionality in randomized traffic microsimulation. Although standardized test procedures are intended to mimic urban and highway speed profiles for the purposes of evaluating fuel economy and emissions, they do not explicitly consider the interactions present in real-world driving between the ego vehicle equipped with ADAS and other vehicles in traffic. This article presents one approach to address the drawback of standardized test procedures for evaluating the fuel economy benefits of ADAS technologies.

Abstract This work describes an investigation of measurement techniques for the indicated mean effective pressure (IMEP) on a 55 cc single-cylinder, 4.4 kW, two-stroke, spark ignition (SI) engine intended for use on Group 1 and Group 2 remotely piloted aircraft (RPAs). Three different sensors were used: two piezoelectric pressure transducers (one flush mount and one measuring spark plug) for measuring in-cylinder pressure and one capacitive sensor for determining the top dead center (TDC) position of the piston. The effort consisted of three objectives: to investigate the merits of a flush mount pressure transducer compared to a pressure transducer integrated into the spark plug, to perform a parametric analysis to characterize the effect of the variability in the engine test bench controls on the IMEP, and to determine the thermodynamic loss angle for the engine.

Abstract With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation.