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Abstract Autonomous vehicles (AVs) rely heavily upon their perception subsystems to “see” the environment in which they operate. Unfortunately, the effect of variable weather conditions presents a significant challenge to object detection algorithms, and thus, it is imperative to test the vehicle extensively in all conditions which it may experience. However, the development of robust AV subsystems requires repeatable, controlled testing—while real weather is unpredictable and cannot be scheduled. Real-world testing in adverse conditions is an expensive and time-consuming task, often requiring access to specialist facilities. Simulation is commonly relied upon as a substitute, with increasingly visually realistic representations of the real world being developed.

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 The water droplet erosion (WDE) on high-speed rotating wheels appears in several engineering fields such as wind turbines, stationary steam turbines, fuel cell turbines, and turbochargers. The main reasons for this phenomenon are the high relative velocity difference between the colliding particles and the rotor, as well as the presence of inadequate material structure and surface parameters. One of the latest challenges in this area is the compressor wheels used in turbochargers, which has a speed up to 300,000 rpm and have typically been made of aluminum alloy for decades, to achieve the lowest possible rotor inertia. However, while in the past this component was only encountered with filtered air, nowadays, due to developments in compliance with tightening emission standards, various fluids also collide with the spinning blades, which can cause mechanical damage.

Abstract A critical component of vehicle dynamic control systems is the accurate and real-time knowledge of the vehicle’s key states and parameters when running on the road. Such knowledge is also essential for vehicle closed-loop feedback control. Vehicle state and parameter estimation has gradually become an important way to soft-sense some variables that are difficult to measure directly using general sensors. In this work, a seven degrees-of-freedom (7-DOF) nonlinear vehicle dynamics model is established, where consideration of the Magic formula tire model allows us to estimate several vehicle key states using a hybrid algorithm containing an unscented Kalman filter (UKF) and a genetic algorithm (GA). An estimator based on the hybrid algorithm is compared with an estimator based on just a UKF. The results show that the proposed estimator has higher accuracy and fewer computation requirements than the UKF estimator.

Abstract Advanced passenger vehicles are complex dynamic systems that are equipped with several actuators, possibly including differential braking, active steering, and semi-active or active suspensions. The simultaneous use of several actuators for integrated vehicle motion control has been a topic of great interest in literature. To facilitate this, a technique known as control allocation (CA) has been employed. CA is a technique that enables the coordination of various actuators of a system. One of the main challenges in the study of CA has been the representation of actuator dynamics in the optimal CA problem (OCAP). Using model predictive control allocation (MPCA), this problem has been addressed. Furthermore, the actual dynamics of actuators may vary over the lifespan of the system due to factors such as wear, lack of maintenance, etc. Therefore, it is further required to compensate for any mismatches between the actual actuator parameters and those used in the OCAP.

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 Recently, high-resolution sensors capable of multiple detections (MDs) per object are available for perception applications in autonomous or semi-autonomous vehicles. Conventional multi-target tracking (MTT) approaches start with the point-target assumption and thus cannot be applied directly to the MDs of high-resolution sensors. A popular solution widely used in literature starts with a measurement partitioning approach, followed by repurposing conventional tracking algorithms to accommodate the resulting partitions. However, the computational requirement increases combinatorially, especially under multi-sensor applications that also independently return multiple radar reflections as in the automotive radar sensors used in this work. Thus, a hybrid approach that combines a clustering technique (such as DBSCAN) to alleviate the computational complexity and an MD tracking scheme that admits multiplicity of the target detections is employed.

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 Current End-of-Life Vehicle (ELV) recycling processes are mainly based on mechanical separation techniques. These methods are designed to recycle those metals with the highest contribution in the vehicle weight such as steel, aluminum, and copper. However, a conventional vehicle uses around 50 different types of metals, some of them considered critical by the European Commission. The lack of specific recycling processes makes that these metals become downcycled in steel or aluminum or, in the worst case, end in landfills. With the aim to define several ecodesign recommendations from a raw material point of view, it is proposed to apply a thermodynamic methodology based on exergy analysis. This methodology uses an indicator called thermodynamic rarity to assess metal sustainability. It takes into account the quality of mineral commodities used in a vehicle as a function of their relative abundance in Nature and the energy intensity required to extract and process them.

Abstract Modern vehicles have incorporated numerous safety-focused advanced driver-assistance systems (ADAS) in the last decade including smart cruise control and object avoidance. In this article, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy (FE). We combine ADAS sensor data with a previously developed prediction model, dynamic programming (DP) optimal energy management control, and a validated model of a 2010 Toyota Prius to explore FE. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.

Abstract This article proposes a new misfire detection index, the ΔGap slope, for a four-cylinder engine. However, the proposed index is not limited to four-cylinder engines. The ΔGap slope uses the tooth time measured using the existing crankshaft position sensor; therefore, an additional sensor is not required, which makes it economical. The ΔGap slope is defined as the difference between the gap slopes of the same cylinder for two adjacent cycles. Various factors that cause deviations in gap slopes between cylinders can be eliminated in the process of determining the difference between two gap slopes. Hence, in contrast with the existing engine roughness method, the ΔGap slope has the advantage of not requiring compensation for deviations between the cylinders. The conventional gap slope method must use different sets of thresholds for each cylinder located at the same position on the sensor wheel, which results in multiple thresholds being applied.

Abstract This work develops a comprehensive thermohydrodynamic (THD) model for high-speed squeeze film dampers (SFDs) in the presence of lubricant inertia effects. Firstly, the generalized expression for Reynolds equation is developed. Additionally, in order to reduce the complexity of the hydrodynamic equations, an average radial viscosity is defined and integrated into the equations. Subsequently, an inertial correction to the pressure is incorporated by using a first-order perturbation technique to represent the effect of lubricant inertia on the hydrodynamic pressure distribution. Furthermore, a thermal model, including the energy equation, the Laplace heat conduction equations in the surrounding solids (i.e. the journal and the bush), and the thermal boundary conditions at the interfaces is constructed. Moreover, the system of partial differential hydrodynamic and thermal equations is simultaneously solved by using an iterative numerical algorithm.

Abstract To evaluate that automated vehicle is as safe as a human driver, a following question is studied: how does an automated vehicle react under extreme conditions close to collision? In order to understand the collision avoidance capability of an automated vehicle, we should analyze not only such post-extreme condition behavior but also pre-extreme condition behavior. We present a theory to analyze the collision avoidance capability of automated driving technologies. We also formulate a collision avoidance equation on the theory. The equation has two types of solutions: response driving plans and preparation driving plans. The response driving plans are supported by response strategy on which the vehicle reacts after detection of a hazard and they are highly efficient in terms of travel time.

Abstract Damage is accumulated by vehicles as they travel. Current damage methods allow for the total accumulated damage to be identified; however, they do not allow for identification of the road segments that induce the largest component of the damage. The objective of this article is to develop a measure, Localized Pseudo Damage (LPD), which defines the amount of damage each individual road excitation contributes to the total accumulated pseudo damage. A novel theoretical development of LPD along with analytical and discrete simulation analyses is presented. The results show that the LPD is causal and correctly identifies the location and magnitude of damaging events. This is further demonstrated with the application of the method on a real road surface.

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 Pyrotechnic seat belt pretensioners typically remove 8–15 cm of belt slack and help couple an occupant to the seat. Our study investigated pretensioner deployment on forward-leaning, live volunteers. The forward-leaning position was chosen because research indicates that passengers frequently depart from a standard sitting position. Characteristics of the 3D kinematics of forward-leaning volunteers following pretensioner deployment determines if body size is correlated with subject response. Nine adult subjects (three female), ages 18–43 years old, across a wide range of body sizes (50–120 kg) were tested. The age was limited to young, active adults as pyrotechnic pretensioners can deliver a notable force to the trunk. Subjects assumed a forward-leaning position, with 26 cm between C7 and the headrest, in a laboratory setting that replicated the passenger seat of a vehicle.

Abstract Equal-channel angular pressing (ECAP) is among the most applicable severe plastic deformation processes used to fabricate ultrafine-grained materials with superior mechanical properties. In this work, a commercial purity aluminum has been processed via ECAP process up to four passes. The influence of ECAP routes (A and Bc) on the mechanical properties of the material and its grain size was investigated. Microstructural observations of the as-annealed and the rods processed via ECAP were undertaken using optical microscopy. Hardness profiles and contour maps of sections cut perpendicularly and parallel to the load direction were assessed to investigate the effect of ECAP processing on the hardness distribution across the deformed rods. Compressive properties of the rods were also examined. In addition, digital images correlation was used to display the stress distribution along the longitudinal section of the processed sample during the compression test.

Abstract The causes of failure due to cracking in the resistance spot welding of the advanced high-strength steels dual-phase 590 (DP590) were investigated using scanning electron microscopy (SEM), optical microscopy, and the tensile-shear test. The results showed that by increasing the current amount, the formation of the melting zone occurred in the heat-affected zone, leading to the cracking in this area, reducing the tensile strength and decreasing the mechanical properties; the initiation and growth of cracking and failure in this region also happened. In the heat-affected zone, by increasing the current amount with the softening phenomenon, the recrystallized coarse grains also occurred, eventually resulting in the loss of mechanical properties. The results of the tensile-shear test also indicated that by increasing the current up to 12 kA, the strength was raised, but the ductility was reduced.

Abstract Heavy commercial vehicles play an important role in creating the trade and economic balance of countries. Also, the durability and safety of heavy commercial vehicles come to the fore. Heavy commercial vehicles consist of two parts. These are the chassis area with the equipment that allows the vehicle to move and the cabin section where the driver is located. The cabin area is the most important area that ensures the highest level of driver safety. Considering that the production of trucks is increasing day by day, it is inevitable for companies to increase their R&D activities in the field of cabin and cabin suspension systems for much safer, durable, and comfortable trucks. This study aims to determine the safe torque value of the fasteners and their assembly sequence of the Cab Suspension Console, which is one of the most important connection parts in a truck and which can cause a fatal accident by breaking.

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.