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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 a recent time, which new vehicle lines comes with a huge number of sensors, control units, embedded technologies, and the complexity of these systems (electronics, electrical and electromechanical parts) increases in an exponential way. Considering these events, the expressive generated data amount grows in the same pace, so, consume, transform, and analyze all these data to better understand the modern customer, their needs and how they use the car features becomes necessary. Through that scenario, connected vehicles developed by Ford Motor Company has been generating opportunities to feature’s improvement and cost reduction based on data analysis. This growing quantity of data might be used to optimize feature systems and help engineering teams to understand how the features have been used and enhance the systems engineering design for new or existing features.

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.

Electric vehicles (EVs) are a promising and proven technology for achieving sustainable mobility with zero carbon emissions, very low noise pollution, and reducing the dependency on fossil fuels. Global EV sales have been increasing by ~110 % since 2015, with a significant rise in 2021 (~6.75 mils EV registered) mainly led by China, the US, and Europe, amplifying the EV market share to 8.3% compared to 4.2% in 2020. Future developments aimed at designing better batteries and charging technologies that reduce charging time, reduce initial battery cost, and increased flexibility. In India, EVs are emerging significantly due to stringent Carbon di Oxide (CO2) reduction drives, increasing crude oil prices, and the availability of cheaper renewable energy. Leveraging government promotional policies, evolving the entire ecosystem, globally advantageous manufacturing costs, and competitive engineering skills form the perfect blend for India.

In this paper, a novel mixed-integer programming model is developed to optimally assign the die sets to candidate plants to minimize the total costs. The total costs include freight shipping stamped parts to assembly plants, die set movement, outsourcing, and utilization. Therefore, the objective function is weighted multi-criteria and it takes into consideration some of the key constraints in the real-world condition including “must-move die sets”. An optimization tool has been developed that takes several inputs and feeds them as the input to the mathematical model and generates the optimal assignments with the directional costs as the output. The tool has been tested for several plants at Ford and has proved its robustness by saving millions of dollars. The developed tool can easily be applied to other manufacturing systems and original equipment manufacturers (OEMs).

The advancement of Machine-learning (ML) methods enables data-driven creation of Reduced Order Models (ROMs) for automotive components and systems. For example, Gaussian Process Regression (GPR) has emerged as a powerful tool in recent years for building a static ROM as an alternative to a conventional parametric model or a multi-dimensional look-up table. GPR provides a mathematical framework for probabilistically representing complex non-linear behavior. Today, GPR is available in various programing tools and commercial CAE packages. However, the application of GPR is system dependent and often requires careful design considerations such as selection of input features and specification of kernel functions. Hence there is a need for GPR design optimization driven by application requirements. For example, a moving window size for training must be tuned to balance performance and computational efficiency for tracking changing system behavior.

During the design conception of an automobile, typically low-fidelity physics-based simulations are coupled with engineering judgement to define key architectural components and subsystems which limits the capability to identify NVH issues arising from systems interaction. This translates to non-optimal designs because of unexplored design opportunities and therefore, lost business efficiencies. The sparse design information available during the design conception phase limits the development of representative higher fidelity physics-based simulations. To address that restriction on design optimization opportunities, this paper introduces an alternate approach to develop reduced order predictive models using regression techniques by harnessing historical measurement and simulation data. The concept is illustrated using two driveline NVH phenomenon: axle whine and take-off shudder.

This paper presents a method of using CAE to determine the pre-load and torque applied to a U-Bolt rear Spring Seat. In this paper it is review two U-bolt design and the stresses generated by the pre-load torque applied, based in this study a process to determine the minimal preload and the torque is discussed. By this process it is possible to determine the minimum Torque and the correct pre-load in the U-Bolt element and assuring the correct fastening of the components avoiding over stress in the Bar elements.

Capacity planning is one of the major factors in saving capital and avoiding unnecessary costs in any manufacturing system particularly large original equipment manufacturers (OEMs). However, many manufacturing systems still suffer from huge costs incurred due to a lack of applying a robust capacity planning optimization model. Most of the developed models in literature do not consider real-life situations in manufacturing systems and, hence, are not easy to implement. In this paper, a novel capacity planning optimization model considers various important features of a manufacturing system. The objective function of the model is to minimize the weighted sum of the total number of assets and changeovers. A unique feature of the developed model is the capability of providing the number of additional required assets of each type in case the existing assets are not capable of covering the entire demand.

Automatic transmission (AT) upshift control performance in terms of shift duration and comfort can be improved during the inertia phase by coordinating the off-going clutch together with oncoming clutch and engine torque. The performance improvement is highest in low gear shifts (i.e., for high ratio steps), which are typically performed with open torque converter. In this paper, a discrete-time, linear quadratic regulation (LQR) is applied during the upshift inertia phase, as it provides an optimal multi-input/multi-output control action with respect to the prescribed cost function. The LQR law is based on a reduced-order drivetrain model, which is applicable to actual transmissions characterized by a limited number of available state measurements. The reduced-order model includes the linearized torque converter model. The shift duration is ensured by precise tracking of a linear-like oncoming clutch slip speed reference profile.

Seat strength has increased over the past four decades which includes a transition to dual recliners. There are seat collision performance issues with stiff ABTS and very strong seats in rear impacts with different occupant sizes, seating positions and physical conditions. In this study, eight rear sled tests were conducted in four series: 1) ABTS in a 56 km/h (35 mph) test with a 50th Hybrid III ATD at MGA, 2) dual-recliner ABTS and F-150 in a 56 km/h (35 mph) test with a 5th female Hybrid III ATD at Ford, 3) dual-recliner ABTS in a 48 km/h (30 mph) test with a 95th Hybrid III ATD leaning inboard at CAPE and 4) dual-recliner ABTS and Escape in 40 km/h (25 mph) in-position and out-of-position tests with a 50th Hybrid III ATD at Ford. The sled tests showed that single-recliner ABTS seats twist in severe rear impacts with the pivot side deformed more rearward than the stanchion side.

This study deals with passenger side restraint system design for frontal impact and four impact modes are considered in optimization. The objective is to minimize the Relative Risk Score (RRS), defined by the National Highway Traffic Safety Administration (NTHSA)'s New Car Assessment Program (NCAP). At the same time, the design should satisfy various injury criteria including HIC, chest deflection/acceleration, neck tension/compression, etc., which ensures the vehicle meeting or exceeding all Federal Motor Vehicle Safety Standard (FMVSS) No. 208 requirements. The design variables include airbag firing time, airbag vent size, inflator power level, retractor force level. Some of the restraint feature options (e.g., some specific features on/off) are also considered as discrete design variables. Considering the local variability of input variables such as manufacturing tolerances, the robustness and reliability of nominal designs were also taken into account in optimization process.

Recently, graphene has attracted both academic and industrial interest because it can produce a dramatic improvement in properties at very low filler content. This review will focus on the latest studies and recent progress in the swelling resistance of rubber compounds due to the addition of graphene and its derivatives. This work will present the state-of-the-art in this subject area and will highlight the advantages and current limitations of the use of graphene for potential future researches.

This paper considers using linear quadratic regulation (LQR) for multi-input control of the Automatic Transmission (AT) upshift inertia phase. The considered control inputs include the transmission input/engine torque, oncoming clutch torque, and traditionally not used off-going clutch torque. Use of the off-going clutch has been motivated by discussed Control Trajectory Optimization (CTO) results demonstrating that employing the off-going clutch during the inertia phase along with the main, oncoming clutch can improve the upshift control performance in terms of the shift duration and/or comfort by trading off the transmission efficiency and control simplicity to some extent. The proposed LQR approach provides setting an optimal trade-off between the conflicting criteria related to driving comfort and clutches thermal energy loss.

Optimization of heavy materials like steel, in order to create a lighter vehicle, it is a major goal among most automakers, since heavy vehicles simply cannot compete with a lightweight model's fuel economy. Thinking this way, this paper shows a case study where the Size Optimization technique is applied to a front floor reinforcement. The reinforcement is used by two different vehicles, a subcompact and a crossover Sport Utility Vehicle (SUV), increasing the problem complexity. The Size Optimization technique is supported by Finite Element Method (FEM) tools. FEM in Computer Aided Engineering (CAE) is a numerical method for solving engineering problems, and its use can help to optimize prototype utilization and physical testing.

Squeak and rattle are two undesirable occurrences during component operation and during vehicle driving condition, resulting in one of the top complains from costumers. One common grievance could happen during the user exterior handle operation and during side door closing. The exterior handle system during the operation could generate a squeak between interface parts, if materials and geometric tolerances was not been carefully designed. Also, vibration generated during door closing effort, might generate squeak between parts since the reinforcement for exterior handle touches the outer sheet metal internally. For this reason several guidelines might be included to avoid potential noise condition for this system during vehicle lifetime as correct material reduce friction between parts, taking into consideration the geometric condition between parts. Plus, coupling system on handles two pieces should also be evaluated to avoid squeak during use.

Analysis of road accidents has shown that an important portion of fatal crashes involving Commercial Vehicles are caused by rollovers. ESC systems in Commercial Vehicles can reduce rollovers, severe understeer or oversteer conditions and minimize occurrences of jackknifing events. Several studies have estimated that this positive effect of ESC on road safety is substantial. In Europe, Electronic Stability Control (ESC) is expected to prevent by far the most fatalities and injuries: about 3,000 fatalities (-14%), and about 50,000 injuries (-6%) per year. In Europe, Electronic Stability Control Systems is mandatory for all vehicles (since Nov. 1st, 2011 for new types of vehicle and Nov. 1st, 2014 for all new vehicles), including Commercial Vehicles, Buses, Trucks and Trailers.

Over the last two decades, engine research has been mainly focused on reducing fuel consumption in view of compliance with stringent homologation targets and customer expectations. As it is well known, the objective of overall engine efficiency optimization can be achieved only through the improvement of each element of the efficiency chain, of which mechanical constitutes one of the two key pillars (together with thermodynamics). In this framework, the friction reduction for each mechanical subsystems has been one of the most important topics of modern Diesel engine development. In particular, the present paper analyzes the lubrication circuit potential as contributor to the mechanical efficiency improvement, by investigating the synergistic impact of oil circuit design, oil viscosity characteristics (including new ultra-low formulations) and thermal management. For this purpose, a combination of theoretical and experimental tools were used.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.