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Abstract Due to the incoming phase out of fossil fuels from the market in order to reduce the carbon footprint of the automotive sector, hydrogen-fueled engines are candidate mid-term solution. Thanks to its properties, hydrogen promotes flames that poorly suffer from the quenching effects toward the engine walls. Thus, emphasis must be posed on the heat-up of the oil layer that wets the cylinder liner in hydrogen-fueled engines. It is known that motor oils are complex mixtures of a number of mainly heavy hydrocarbons (HCs); however, their composition is not known a priori. Simulation tools that can support the early development steps of those engines must be provided with oil composition and properties at operation-like conditions. The authors propose a statistical inference-based optimization approach for identifying oil surrogate multicomponent mixtures. The algorithm is implemented in Python and relies on the Bayesian optimization technique.

Abstract Lubrication has been a major area of interest in engineering. Especially in vehicle transmissions, lubrication plays a very crucial role because gears and bearings are constantly subjected to heavy loads. Proper lubrication is essential for maintaining system performance and ensuring endurance life. Insufficient lubrication can lead to excessive wear, increased friction, and eventually, failures in the transmission components. However, excess lubrication can result in power losses due to the resistance offered by the excessive lubricant. Therefore, achieving effective lubrication using optimized lubrication system design is vital for ensuring the longevity and efficiency of the transmission system. Majorly, two types of lubrication methods are used in transmissions: splash lubrication and forced lubrication. This article focuses on forced lubrication, where the lubrication system actively delivers the required flow of lubricant to specific locations within the transmission.

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Abstract Due to their high strength and good flexibility, wire ropes are widely used in various intense applications. A wire rope will present complex wave mechanics, especially under impact conditions. In this article, wire ropes (steel core rope and hemp core rope alternately twisted) were used to study the wave dynamic response of steel wire ropes with preload shock. The transmission law of wire rope shock waves was obtained through actual measurements. The results showed that the compression wave and shear wave were generated and propagated along the rope after impact. The conduction of shear waves had significant reflection characteristics, and the reflected waves overlapped with each other. The conduction velocity of the impact shear wave of the steel core wire rope increased with increasing pretension. The peak tension caused by impact decayed exponentially.

Abstract The greatest frictional contributor in an internal combustion engine is the contact between the piston ring pack and cylinder liner. Therefore, an improved lubrication regime has the potential to raise engine efficiency while lowering emissions, aiding to meet environmental regulations. Previous ultrasonic measurements of the oil film thickness (OFT) between piston rings and the cylinder liner in a marine engine have been subject to several unexpected trends. This article refines the measurement to identify and remove these factors, the trends were found to have arisen due to the detection of ultrasonic reflections from the piston ring outside of the expected alignment zone. The extent of these undesired reflections is thought to be due to the liner thickness providing a relatively large distance for spreading of the ultrasonic wavefront.

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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 With the trends to increase drain oil interval to reduce the cost of ownership of Heavy-Duty vehicles and to use low ash oils to mitigate degradation of Diesel Particulate Filter performance, the efficiency of lubricant additive s, especially the antiwear ones, are of great interest. However, most of the tribological tests are still done with fresh oils or, in a few cases, with artificially aged oils. In this work, the piston ring and cylinder liner were rig tested for friction and wear on a short reciprocating tester with two oils: a fully formulated SAE 10W-40 API CI-4/ACEA E7 and a sample of the same oil after 500 h of an engine test. Friction was measured along with the rig test, and liner wear was evaluated after test by different parameters based on the bearing curve of roughness. Compared with the fresh oil, the aged oil showed slightly lower friction, but significantly higher liner wear.

Abstract Electric heavy-duty tractor-trailers (EHDTT) offer an important option to reduce greenhouse gases (GHG) for the transportation sector. However, to increase the range of the EHDTT, this effort investigates critical vehicle design features that demonstrate a gain in overall freight efficiency of the vehicle. Specifically, factors affecting aerodynamics, rolling resistance, and gross vehicle weight are essential to arrive at practical input parameters for a comprehensive numerical model of the EHDTT, developed by the authors in a subsequent paper. For example, drag reduction devices like skirts, deturbulators, vortex generators, covers, and other commercially available apparatuses result in an aggregated coefficient of drag of 0.367. Furthermore, a mixed utilization of single-wide tires and dual tires allows for an optimized trade-off between low rolling resistance tires, traction, and durability.

Abstract Three-dimensional patterns representing crosshatched plateau-honed cylinder bores based on two-dimensional Fast Fourier Transform (FFT) of measured surfaces were generated and used to calculate pressure flow, shear-driven flow, and shear stress factors. Later, the flow and shear stress factors obtained by numerical simulations for various surface patterns were used to calculate lubricant film thickness and friction force between piston ring and cylinder bore contact in typical diesel engine conditions using a mixed lubrication model. The effects of various crosshatch honing angles, such as 30°, 45°, and 60°, and texture heights on engine friction losses, wear, and oil consumption were discussed in detail. It is observed from numerical results that lower lubricant film thickness values are generated with higher honing angles, particularly in mixed lubrication regime where lubricant film thickness is close to the roughness level, mainly due to lower resistance to pressure flow.

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

Abstract This paper presents a machine learning application of the force/torque sensor in a human-robot collaborative manufacturing scenario. The purpose is to simplify the programming for physical interactions between the human operators and industrial robots in a hybrid manufacturing cell which combines several robotic applications, such as parts manipulation, assembly, sealing and painting, etc. A multiclass classifier using Light Gradient Boosting Machine (LightGBM) is first introduced in a robotic application for discriminating five different contact states w.r.t. the force/torque data. A systematic approach to train machine-learning based classifiers is presented, thus opens a door for enabling LightGBM with robotic data process. The total task time is reduced largely because force transitions can be detected on-the-fly. Experiments on an ABB force sensor and an industrial robot demonstrate the feasibility of the proposed method.