The present study discusses about the determination of the Seal drag force in the application where elastomeric seal is used with metallic interface in the presence of different fluids. An analytical model was constructed to predict the seal drag force and experimental test was performed to check the fidelity of the analytical model. A Design of Experiment (DoE) was utilized to perform experimental test considering different factors affecting the Seal drag force. Statistical tools such as Test for Equal Variances and One way Analysis of Variance (ANOVA) were used to draw inferences for population based on samples tested in the DoE test. It was observed that Glycol based fluids lead to lubricant wash off resulting into increased seal drag force. Additionally, non-lubricated seals tend to show higher seal drag force as compared to lubricated seals. Keywords: Seal Drag, DoE, ANOVA
Multiple experimental studies were performed on galling intiation for variety of tooling materials, coatings and surface treatments, sheet materials with various surface textures and lubrication. Majority of studies were performed for small number of samples in laboratory conditions. In this paper, the methodology of screening experiment using different combinations of tooling configurations and sheet material in the lab followed by the high volume small scale U-bend performed in the progressive die on the mechanical press is discussed. The experimental study was performed to understand the effect of the interface between the sheet metal and the die surface on sheet metal flow during stamping operations. Aluminum sheet AA5754 2.5mm thick was used in this experimentation. The sheet was tested in laboratory conditions by pulling between two flat insert with controllable clamping force and through the drawbead system with variable radii of the female bead.
Characterization of Embedded Debris Particles on Failed Crankshaft Bearings Jianghuai Yang, Qigui Wang, Zhe Li Materials Engineering & Additive Design & Manufacturing, General Motors Co., LLC Crankshaft bearings serve the function of maintaining the lubrication oil films needed to support the crankshaft journals in hydrodynamic regime of rotation. Discontinuous oil films will cause the journal-bearing couple to be in a mixed or boundary friction condition, or even a bearing seizure or a spun bearing. This condition may further force the crankshaft to break and an engine shutdown. Spun bearings have been identified to be the top reason in engine warranty replacement. Excessive investigations have found large, embedded hard debris particles on the bearings are inevitably the culprit of destroying continuity of the oil films.
The need for even more efficient internal combustion engines in the road transportation sector is a mandatory step to reduce the related CO2 emissions. In particular, this sector is presently responsible of about 12% of the greenhouse gases worldwide, and the path toward hybrid and electric powertrains has just begun. In particular, in heavy-duty vehicles the full electrification of the powertrain is far to be imagined. So, internal combustion engines will still play a significant role in the near/medium future. Hence, technologies having a low costs to benefits ratio will be favorably introduced in existing engines to reduce emissions. The thermal management of engines is today a recognized area of research. Inside this area, the interest toward the lubricant oil has a great potential but not yet fully exploited. Engine oil is responsible of the mechanical efficiency of the engine and has a significant potential of improvement.
In this paper, we present a novel algorithm designed to accurately trigger the engine coolant flow at the optimal moment, thereby safeguarding gas-engines from catastrophic failures such as engine boil. To achieve this objective, we derive models for crucial temperatures within a gas-engine, including the engine combustion wall temperature, engine coolant-out temperature, engine block temperature, and engine oil temperature. To overcome the challenge of measuring hard-to-measure signals such as engine combustion gas temperature, we propose the use of new intermediate parameters. Our approach utilizes a lumped parameter concept with a mean-value approach, enabling precise temperature prediction and rapid simulation. The proposed engine thermal model is capable of estimating temperatures under various conditions, including steady-state or transient engine performance, without the need for extra sensors.
The paper underscores the critical role of effective lubrication path design in determining the durability and performance of automotive transmission systems, particularly in the context of hybrid electric vehicles (HEVs). Measuring the internal distribution of automotive transmission fluid (ATF) to various transmission components remains a formidable experimental challenge due to the structural complexities involved. HEV transmission systems, characterized by a combination of diverse bearings and intricate gear systems, present computational difficulties, often necessitating reliance on one-dimensional (1D) models that require extensive experimental data for validation. To address these challenges, the paper introduces a novel approach—a detailed, transient, three-dimensional Computational Fluid Dynamics (CFD) analysis of ATF flow within HEV transmission systems.
Recent automobile engines are equipped with many devices that are driven by oil pressure. Generally, engine oil is used for oil pressure, and in addition to its conventional functions of lubrication and cooling, etc., it also plays an important role in accurately driving such devices. One of the factors that can interfere with the characteristics of engine oil is air contamination. Excessive air contamination can cause issues with driving devices. Although there are various factors that contribute to air contamination, this paper focuses on, and attempts to help predict, the air generated by engine oil falling and colliding with the surface of the oil in the oil pan as it returns from the top to the bottom of the engine. Using the particle method as the prediction method, the coupled Moving Particle Simulation (MPS) and Discrete Element Method (DEM) calculations were used to represent the generation of air.
Using the recycled waste oils are to be focused for the protection of environment by reducing the land pollution and disposal costs.This study is to use the recycled waste engine oil, waste cooking oil and waste plastic oil along with Bio-butanol from the waste cut vegetables and fruits. Initially, a properties and solubility to choose a suitable blend for fueling into diesel engine from various proportions. These three blends from the base of three waste oils are then tested by modifying and standard engine operating parameters for performance. The properties tests results as 18% of waste engine oil with bio-butanol, 16% of waste cooking oil with bio-butanol and 24% of waste plastic oil with bio-butanol are found competent for fueling engine. These blends produces low efficiency in lower brake powers and the emissions of smoke, hydrocarbons and carbon monoxide are also higher during the operation under standard parameters.
The thermal behavior of the electric axle is an essential indicator which requires certain attention during the development process. Due to the complexity of heat generation mechanism and heat transfer boundary conditions, it is difficult to accurately predict the axle’s temperature, especially in real driving conditions. In this paper, a comprehensive 1D model is developed to simulate its heat transfer process effectively and accurately. The heat transfer model is developed based on the thermal network method, and the electric axle is divided into thermal mass according to its heat transfer characteristics. The heat generation model, which accounts for meshing loss, bearing loss, churning loss, and winding loss, exchanges heat flux and temperature information with the heat transfer model to take into account the effect of lubricating oil temperature on power loss.
Due to the global drive for carbon neutrality, passenger vehicle gasoline engines are transitioning to higher levels of electrification, such as hybrid electric vehicles and plug-in hybrid electric vehicles, HEVs and PHEVs. Compared with conventional internal combustion engines, ICE only operation, the hybrid HEV or plug-in hybrid PHEV engine typically operates for shorter periods, in turn the engine coolant and lubricant temperatures are lower. Conventional internal combustion engines are often able to yield valuable fuel economy benefits by selecting appropriate engine lubricating oils, typically employing reduced viscosity and suitable additives. There are commercial engine tests available for measurement, often in an engine test cell for precision. Steady state testing is also a simplified option. Such efforts require care, as the accurate measurement is technically and practically challenging.
A cylinder block involves bore deformation due to assembling stress of cylinder head and thermal stress. This distortion is found to be the cause of the exacerbation of piston skirt friction and piston slap. This article presents a numerical and experimental study of the effect of an optimized bore profile on engine performance. A friction analysis of 3-dimentional elastohydrodynamic was applied for an estimation of the piston skirt friction. A cylinder bore with barrel shape under the part load operation point was assumed as an optimal bore profile in terms of piston skirt friction without compromising piston slap. From the simulation study, it was found that the piston secondary motion just after firing top dead center can be mitigated by narrower piston – bore clearance at upper position of the cylinder.
During the operation of the engine, some particles that pollute the lubricating oil will be produced, causing damage to the interior of the engine. This paper established a three-coil inductive metal particle sensor model, and verified the rationality and accuracy of the model by simulating the motion process of a single spherical iron particle passing through the sensor. Then, on this basis, different sizes, different spacing and different The dual-particle coupling simulation of the shape explores the influence of particle motion on the sensor sensing signal under different conditions.