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Sintered parts mechanical properties are very sensitive to final density, which inevitable cause an enormous density gradient in the green part coming from the compaction process strategy. The current experimental method to assess green density occurs mainly in set up by cutting the green parts in pieces and measuring its average density in a balance using Archimedes principle. Simulation is the more accurate method to verify gradient density and the main benefit would be the correlation with the critical region in terms of stresses obtained by FEA and try to pursue the optimization process. This paper shows a case study of a part that had your fatigue limit improved 1000% using compaction process simulation for better optimization.

In recent decades, significant technological advances have made cruise control systems safer, more automated, and available in more driving scenarios. However, comparatively little progress has been made in optimizing vehicle efficiency while in cruise control. In this paper, two distinct strategies are proposed to deliver efficiency benefits in cruise control by leveraging flexibility around the driver’s requested set speed, and road information that is available on-board in many new vehicles. In today’s cruise control systems, substantial energy is wasted by rigidly controlling to a single set speed regardless of the terrain or road conditions. Introducing even a small allowable “error band” around the set speed can allow the propulsion system to operate in a pseudo-steady state manner across most terrain. As long as the vehicle can remain in the allowed speed window, it can maintain a roughly constant load, traveling slower up hills and faster down hills.

After-treatment sensors are used in the ECU feedback control to calibrate the engine operating parameters. Due to their contact with exhaust gases, especially NOx sensors are prone to soot deposition with a consequent decay of their performance. Several phenomena occur at the same time leading to sensor contamination: thermophoresis, unburnt hydrocarbons condensation and eddy diffusion of submicron particles. Conversely, soot combustion and shear forces may act in reducing soot deposition. This study proposes a predictive 3D-CFD model for the analysis of the development of soot deposition layer on the sensor surfaces. Alongside with the implementation of deposit and removal mechanisms, the effects on both thermal properties and shape of the surfaces are taken in account. The latter leads to obtain a more accurate and complete modelling of the phenomenon influencing the sensor overall performance.

Internal combustion engines (ICEs) exhaust emissions, particularly nitrogen oxides (NOx), have become a growing environmental and health concern. The biggest challenge for contemporary ICE industry is the development of clean ICEs, and the use of advanced design tools like Computational Fluid Dynamics (CFD) simulation is paramount to achieve this goal. In particular, the development of aftertreatment systems like Selective Catalyst Reduction (SCR) is a key step to reduce NOx emissions, and accurate and efficient CFD models are essential for its design and optimization. In this work, we propose a novel 3D-CFD methodology, which uses a Machine Learning (ML) approach as a surrogate model for the SCR catalyst chemistry, which aims to enhance accuracy of the simulations with a moderate computational cost. The ML approach is trained on a dataset generated from a set of 1D-CFD simulations of a single channel of an SCR catalyst.

Several predictive equations based on the chemical composition of gasoline have been shown to estimate the particulate emissions of light-duty, internal combustion engine (ICE) powered vehicles and are reviewed in this paper. Improvements to one of them, the PEISimDis equation are detailed herein. The PEISimDis predictive equation was developed by General Motor’s researchers in 2022 based on two laboratory gas chromatography (GC) analyses; Simulated Distillation (SimDis), ASTM D7096 and Detailed Hydrocarbon Analysis (DHA), ASTM D6730. The DHA method is a gas chromatography mass spectroscopy (GC/MS) methodology and provides the detailed speciation of the hundreds of hydrocarbon species within gasoline. A DHA’s aromatic species from carbon group seven through ten plus (C7 – C10+) can be used to calculate a Particulate Evaluation Index (PEI) of a gasoline, however this technique takes many hours to derive because of its long chromatography analysis time.

Manual transmissions for passenger cars are facing pressures due to rapid growth of automatic transmissions, which already represents more than 60% of Brazil market, and from higher torque demand due to strict emission legislation, which turbo engines had presented great contribution to it. To solve this contradictory issue, gears with higher strength and lower cost have been studied to replacement Nickel by Niobium in the steels. Furthermore, this technology could be applied to solve the issues with electrified vehicle, where high torque, speed and lifetime are demanded pursued for gears. This study aimed to build prototypes and compare the S-N curves, fracture analysis, microstructure for three kinds of steels (QS4321 with Ni, QS1916 FG without Ni & with Nb and QS 1916 without Ni and Nb) in the condition carburized, hardened and tempered with and without shot peening.

As the automobile industry is moving towards Electrical vehicles, it becomes very important to have low cost and robust solution to seal all the internal Battery sub systems. It’s a known fact that various IC engine Vehicles are already using Room temperature vulcanized rubber (RTV) for many metal and composite sealing interfaces. Nevertheless, it always needs a good structural design to have good sealing performance. For designing a robust RTV joint for composite structures, it becomes important to have standard RTV chamfers. Sometimes even with these standards, it becomes very costly in having warranty issues when we have weak structure around RTV chamfers. Any joint structure involves multiple design parameters which might impact the sealing performance. Some of the joint structural parameters should be well designed at the early phase of product development cycle, which otherwise will later add lot of cost in modifying the product with its integrated components.

A hydrogen economy is an increasingly popular solution to lower global carbon dioxide emissions. Previous research has been focused on the economic conditions necessary for hydrogen to be cost competitive, which tends to neglect the effectiveness of greenhouse gas mitigation for the very solutions proposed. The holistic carbon footprint assessment of hydrogen production, distribution, and utilization methods, otherwise known as “well-to-wheels” carbon intensity, is critical to ensure the new hydrogen strategies proposed are effective in reducing global carbon emissions. When looking at these total carbon intensities, however, there is no single clear consensus regarding the pathway forward. When comparing the two fundamental technologies of steam methane reforming and electrolysis, there are different scenarios where either technology has a “greener” outcome.

Regulations have been established for the monitoring and reporting of greenhouse gas (GHG) emissions and fuel consumption from the transport sector. Low carbon fuels combined with new powertrain technologies have the potential to provide significant reductions in GHG emissions while decreasing the dependence on fossil fuel. In this study, a lean-burn ethanol-diesel dual-fuel combustion strategy has been used as means to improve upon the efficiency and emissions of a conventional diesel engine. Experiments have been performed on a 2.0 dm3 single cylinder heavy-duty engine equipped with port fuel injection of ethanol and a high-pressure common rail diesel injection system. Exhaust emissions and fuel consumption have been measured at a constant engine speed of 1200 rpm and various steady-state loads between 0.3 and 2.4 MPa net indicated mean effective pressure (IMEP).

Multiple automotive applications exist for small electric motors that are activated by vehicle occupants for various functions such as window lifts and seat adjusters. For such a motor to be described as high quality, not only should the sound it produces be low in amplitude, but it also needs to be free from pulsations and variations that might occur during its (otherwise) steady-state operation. If a motor’s sound contains pulsations or variations between 2 and 8 cycles per second, the variation is described as warble. To establish performance targets for warble noise at both the vehicle and component level a way to measure and quantify the warble noise must be established. Building on existing sound quality metrics such as loudness and pitch variation, a method is established by which processed sound data is put through a secondary operation of Fourier analysis.

Loss of power steering assist (LoA) is viewed as a potential hazard in certain vehicle operational scenarios. Despite the importance of this steering failure mode, few published test protocols for the objective or subjective evaluation of vehicle performance in a loss of assist situation exist. The first part of this paper examines five of the key steering failure modes that can result in LoA and discusses why LoA persists as a key industry challenge. The second part analyzes the situational dynamics affecting vehicle controllability during a LoA event and proposes a subjective evaluation driving course that facilitates evaluations in various LoA scenarios. A corresponding objective test procedure and metric is also proposed. These evaluation methods support consistent performance evaluation of physical vehicles while also enabling the prediction of vehicle characteristics early in the vehicle development process (VDP).

Structures with multiple materials have now become one of the perceived necessities for automotive industry to address vehicle design requirements such as light-weight, safety, and cost. The objective of this study is to develop a design methodology for multi-material structures accountable for vehicle crash durability. The heuristic topology synthesis approach of Hybrid Cellular Automaton (HCA) framework is implemented to generate multi-material structures with the constraint on the volume fraction of the final design. The HCA framework is integrated with ordered-SIMP (solid isotropic material with penalization) interpolation, artificial material library, as well as statistical analysis of material distribution data to ensure a smooth transition between multiple practical materials during the topology synthesis.

Fatigue is one of the most common failure mechanism in engineering structures. The statistical nature of fatigue life and the stress gradient are the two challenges among many while designing any component or structure for fatigue. Fatigue lives of the identical components exhibit the considerable variation under the same loading and operating conditions due to the difference in the material micro-structures and other uncontrolled parameters. Stress concentration at the notch causes stress gradient and therefore, applying the plane specimen results for actual engineering components with notches does not give quantitatively reliable results if the stress gradient effects are not considered. The objective of the work presented here was to carry out the fatigue tests of un-notched, U and V-notch specimens which were die cast using aluminum alloy (A380) and to obtain fatigue life using a variable critical distance method which considers the stress gradient due to the notch geometry.

As automotive OEMs (Original Equipment Manufacturer) struggle to reach a balance between Design and Performance, environmental legislations continues to demand more rapid gains in vehicle efficiency. As a result, more attention is being given to the contributions of both tire and wheels. Not only tire rolling resistance, but also tire and wheel aerodynamics are being shown to be contributors to overall efficiency. To date, many studies have been done to correlate CFD simulations of rotating wheels both in open and closed wheeled environments to windtunnel results. Whereas this ensures proper predictive capabilities, little focus has been given to thoroughly explaining the physics that govern this complex environment. This study seeks to exhaustively investigate the complex interactions between the ground, body, and a rotating tire/wheel.

The goal of this study was to generate exhaust fast gas data that could be used to identify phenomena that occur before, during, and after stochastic preignition (SPI), also called low-speed preignition (LSPI), events. Crank angle resolved measurement of exhaust hydrocarbons, NO, CO, and CO2 was performed under engine conditions prone to these events. Fuels and engine operating strategies were varied in an attempt to understand similarities and differences in SPI-related behavior that may occur between them. Several different uncommon (typically occurring in less than 1% of engine cycles) features of the fast gas data were identified, and the correlations between them and SPI events were explored. Although the thresholds used to define and identify these observations were arbitrary, they provided a practical means of identifying behavior in the fast gas data and correlating it to SPI occurrence.

In this multi-phase study, fuel and lubricant effects on stochastic preignition (SPI) were examined. First, the behavior of fuels for which SPI data had previously been collected were characterized in terms of their combustion and emissions behavior, and correlations between these characteristics and their SPI behavior were examined. Second, new SPI data was collected for a matrix of fuels that was constructed to test and confirm hypotheses that resulted from interpretation of the earlier data in the study and from data in open literature. Specifically, the extent to which the presence of heavy components in the fuel affected SPI propensity, and the extent to which flame initiation propensity affected SPI propensity, were examined. Finally, the interaction of fuels with lubricants expected to exhibit a range of SPI propensities was examined.

Planetary gear set is one of the most commonly used gear systems in automotive industry as they cater to high power density requirements. A simple planetary gear set consists of a sun gear, ring gear, planets and carrier which houses planet gears. Efficiency of a transmission is dependent upon performance of gear sets involved in power transfer to a great extent. Structural rigidity of a planetary carrier is critical in a planetary gear set as its deflection may alter the load distribution of gears in mesh causing durability and noise issues. Limited studies exist based on geometrical parameters of a carrier which would help a designer in selecting the dimensions at an early stage. In this study, an end to end automated FEA process based on DOE and optimization in Isight is developed. The method incorporates a workflow allowing for an update of carrier geometry, FE model setup, analysis job submission and post-processing of results.

With rapid increase of vehicles on the road, safety concerns have become increasingly prominent. Since the leading cause of many traffic accidents is known to be by human drivers, developing autonomous vehicles is considered to be an effective approach to solve the problems above. Although trajectory tracking plays one of the most important roles on autonomous driving, handling the coupling between trajectory-tracking control and ESP under certain driving scenarios remains to be challenging. This paper focuses on trajectory-tracking control considering the role of ESP. A vehicle model is developed with two degrees of freedom, including vehicle lateral, and yaw motions. Based on the proposed model, the vehicle trajectory is separated into both longitudinal and lateral motion. The coupling effect of the vehicle and ESP is analyzed in the paper. The lateral trajectory-tracking algorithm is developed based on the preview follower theory.

The paper describes the challenges and results achieved in developing a new high-speed Diesel combustion system capable of exceeding the imaginative threshold of 100 kW/l. High-performance, state-of-art prototype components from automotive diesel technology were provided in order to set-up a single-cylinder research engine demonstrator. Key design parameters were identified in terms boost, engine speed, fuel injection pressure and injector nozzle flow rates. In this regard, an advanced piezo injection system capable of 3000 bar of maximum injection pressure was selected, coupled to a robust base engine featuring ω-shaped combustion bowl and low swirl intake ports. The matching among the above-described elements has been thoroughly examined and experimentally parameterized.

This paper describes the development of an analytical method to assess and optimize halfshaft joint angles to avoid excessive 3rd halfshaft order vibrations during wide-open-throttle (WOT) and light drive-away events. The objective was to develop a test-correlated analytical model to assess and optimize driveline working angles during the virtual design phase of a vehicle program when packaging tradeoffs are decided. A twelve degree-of-freedom (12DOF) system model was constructed that comprehends halfshaft dynamic angle change, axle torque, powertrain (P/T) mount rate progression and axial forces generated by tripot type constant velocity (CV) joints. Note: “tripot” and “tripod” are alternate nomenclatures for the same type of joint. Simple lumped parameter models have historically been used for P/T mount optimization; however, this paper describes a method for using a lumped parameter model to also optimize driveline working angles.