Browse Topic: CAD, CAM, and CAE

Items (2,985)
The final step in manufacturing high-precision parts for internal combustion engines, such as cylinder heads and blocks, is the removal of machining chips from the finished parts. This step is crucial because the machining chips and cutting oil left on the surface after machining can cause quality issues in the downstream engine assembly and affect the cooling system’s performance during engine operation. This chip removal step is especially critical for parts with internal cavities, such as the water jackets in cylinder heads, due to the difficulty of removing chips lodged in the narrow passages of these internal channels. To effectively remove chips from the water jacket, machining chip washing systems typically utilize multiple high-velocity water jets directed into the water jacket, creating flows with substantial kinetic energy to dislodge and evacuate the machining chips. For machining chip washing systems equipped with dozens of water nozzles, optimizing washing efficiency
Jan, JamesTorcellini, SabrinaKhorran, AaronHall, Mark
Spray washing is commonly used in car manufacturing to clean and prepare surfaces for subsequent processes like coating and painting. It uses high-pressure spray to deliver cleaning solutions or water onto vehicle surfaces to remove dirt, oils, metal shavings, and contaminants. For optimal washing quality, it is important to have proper nozzle arrangements, spray configuration, and vehicle positioning. Numerical simulations can be used to minimize the trial-and-error process and improve the quality. Spray washing involves strong discontinuities, fragmentation, violent free-surface changes, and complex multiphase flow, which are difficult to simulate using conventional grid-based methods. Lagrangian differencing dynamics (LDD) is a novel numerical method which has the features of being Lagrangian, meshless, and second-order accurate. It employs a meshless finite difference approximation scheme over scattered points and solves the incompressible Navier-Stokes equations in an implicit way
Panov, Dmitrii OlegovichZhu, HuaxiangBasic, JosipZhang, LingranChampaneriya, VrajeshSaghatchi, RoozbehPeng, ChongKotian, AkhileshAndo, Yuya
Recent years have seen a strong move towards Software Defined Vehicles (SDV) concept as it is seen as an enabler for advancing the mobility by integrating complex technologies like Artificial Intelligence (AI) and Connected Autonomous Driving (CAD) into the vehicle. However, this comes with fundamental changes to the vehicle’s Electrical/Electronic (EE) architecture which require novel testing approaches. This paper presents FEV’s SDV Hardware-In- The-Loop (HIL) test setup which focuses on testing the developed HPC-based software. The functionality of the SDV HIL test setup is demonstrated by testing the software of multiple technologies within the High Performance Computer (HPC) environment like ADAS and teleoperation virtual control units with Over-the-air (OTA) up- dates capability. Test results show the effectiveness of utilizing FEV’s HIL setup in developing and validating the software of SDV platforms.
Obando, DavidAlzu'bi, HamzehCarreón Vásquez, ErwinAlrousan, QusayAlnajdawi, Mohammad SamiTasky, Thomas
The linear region of the side-slip mechanical properties of tires is often used in the simulation of linear monorail models for vehicles, especially in the design of active control systems. Side-slip stiffness is a key parameter in tire side-slip, and is significantly influenced by camber and load. In response to the tire industry's need for efficient acquisition of tire mechanical properties and the development of virtual prototyping technology, this paper proposes a method to address the influence mechanism of camber on side-slip in the study of tire camber side-slip prediction models. This paper analyzes the impact of camber on the linear region of tire side-slip mechanical properties at the microscopic level. It then examines the effect of camber on the side-slip condition from the perspective of tire external characteristics, combined with the tire theoretical model, to map the local characteristics of camber onto the external characteristics of tire side-slip. First, a finite
Yin, HengfengSuo, YanruWu, HaidongMin, HaitaoLiu, Dekuan
Virtual prototyping enables tires to be involved in automotive research and development (R&D) at an early stage, eliminating the trial-and-error process of physical tire samples and effectively reducing time and costs. Semi-empirical/empirical tire models are commonly used to evaluate vehicle-tire virtual mating. To parameterize these models, finite element (FE) simulations are necessary, involving combinations of sideslip, camber, and longitudinal slip under various loads. This paper identifies that when multiple inputs are combined, the FE simulation conditions become complex and numerous, presenting a significant challenge in virtual prototyping applications. Through an extensive analysis of more than ten tire prediction modeling methods and models in detail, this paper demonstrates the significant potential of tire prediction modeling in addressing this challenge. We begin with an overview of the current state of research in tire virtual prototyping, reviewing its application
Yin, HengfengSuo, YanruLu, DangXia, DanhuaMin, Haitao
In the automotive industry, the durability and thermal analysis of components significantly impact vehicle component robustness and customer satisfaction. Traditional computer-aided engineering (CAE) methods, while effective, often involve extensive design iterations and troubleshooting, leading to prolonged development times and increased costs. The integration of artificial intelligence (AI) and machine learning (ML) into the CAE process presents a transformative solution to these challenges. By leveraging AI and ML, the durability simulation time of automobile components is significantly enhanced. Altair’s Physics AI tool utilizes historical CAE data to train ML models, enabling accurate predictions of model performance in terms of durability and stiffness. This reduces the necessity for multiple simulations, thereby decreasing CAE model design and solution completion times by 30%. By predicting potential issues early in the design phase, AI and ML allow engineers to make informed
Patil, AmolSonavane, Pravinkumar
Cam gear is a critical component of the timing system in an internal combustion engine, ensuring the synchronized opening of the engine valves, pistons, and rotating parts, but their unavailability may result in long-term downtime or expensive replacement. Reverse engineering (RE) systems also play an important role in promoting sustainable practices projects in automotive technologies. The study focuses on presenting a proposed method for redesigning damaged parts in engines using image processing technology by creating an-accurate CAD model. In addition to clarifying of the expected causes that led to cam gear damage. The proposed method involves taking a high-resolution image of the damaged part, then applying advanced image processing algorithms to analyze and reconstruct the geometry of the part. The data is then converted into a high-resolution 3D CAD model. This approach aims to address the challenges of replicating worn or broken parts, providing a cost-effective maintenance
Ali, Salah H. R.Ehab, EslamBarakat, EbrahimYounes, AbdelrahmanAli, Amr S.H.R.
The significance of the liftgate's role in vehicle low-frequency boom noise is highlighted by its modal coupling with the vehicle's acoustic cavity modes. The liftgate's acoustic sensitivity and susceptibility to vehicle vibration excitation are major contributors to this phenomenon. This paper presents a CAE (Computer-Aided Engineering) methodology for designing vehicle liftgates to reduce boom risk. Empirical test data commonly show a correlation between high levels of liftgate vibration response to vehicle excitations and elevated boom risk in the vehicle cabin. However, exceptions to this trend exist; some vehicles exhibit low boom risk despite high vibration responses, while others show high boom risk despite low vibration responses. These discrepancies indicate that liftgate vibratory response alone is not a definitive measure of boom risk. Nonetheless, evidence shows that establishing a vibration level control guideline during the design stage results in lower boom risk. The
Abbas, AhmadHaider, Syed
Advances in computer aided engineering and numerical methods have made modeling and analyzing vehicle dynamics a key part of vehicle design. Over time, many tools have been developed to model different vehicle components and subsystems, enabling faster and more efficient simulations. Some of these tools use simplified mathematical models to achieve the desired performance. These models depend on model identification methods to determine the parameters and structure that best represent a system based on observed data. This work focuses on the development of a model identification for hydro bushings, a crucial component in nearly all ground vehicles. It introduces an innovative approach to identifying the dynamic properties of hydro bushings using the rapidly evolving physics-informed neural networks. The developed physics-informed network incorporates physical laws into its training process, allowing for an improved mapping of a hydro bushing’s excitation to its dynamic response. The
Koutsoupakis, JosefRibaric, AdrijanNolden, IngoKaryofyllas, GeorgeGiagopoulos, Dimitrios
This paper reports on the development of a simulation model to predict engine blowby flow rates for a common rail DI diesel engine. The model is a transient, three-dimensional computational fluid dynamics (CFD) model. Managing blowby flow rates is beneficial for managing fuel economy and oil consumption. In doing so, an improved understanding of the blowby phenomenon is also possible. A mesh for the sub-micron level clearances (up to 0.5 microns) within the piston ring pack is created using a novel approach. Commercial CFD software is used to solve the pressure, velocity, and temperature distributions within the fluid domain. Ring motions within the piston grooves are predicted by a rigorous force balance. This model is the first of its kind for predicting engine blowby using a three-dimensional simulation model while solving the complete set of governing transport equations, without neglecting any terms in the equations. The predicted blowby flow rate has been validated with
Manne, Venkata Harish BabuBedekar, SanjeevSrinivasan, ChiranthDas, DebasisRanganathan, Raj
The modern luxurious electric vehicle (EV) demands high torque and high-speed requirements with increased range. Fulfilling these requirements, arises the need for increased electric current supply to motors. Increased amperage through the stator causes higher losses resulting in elevated temperature across the motor components and its housing. In most of the cases, stator is mounted on the housing through interference fit to avoid any slippage during operation conditions. High temperature across the stator and housing causes significant thermal expansions of the components which is uneven in nature due to the differences in corresponding coefficient of thermal expansion (CTE) values. Housings are generally made of aluminium and tends to expand more having higher value of CTE than that of steel core of stator which may give rise to a failure mode related to stator slippage. To address this slippage if the amount of interference fit is increased, that’ll result in another failure mode
Karmakar, NilankanPrasad, Praveen
Vibration qualification tests are indispensable for vehicle manufacturers and suppliers. Carmakers’ specifications are therefore conceived to challenge the mechanical endurance of car components in the face of numerous in-service detrimental phenomena: In automotive industries, components are commonly qualified by means of a test without failure, the goal being to determine whether it will or not "pass" customer requirements. Validation of newly designed components is obtained via bench test and structural simulation. Simulation has gained traction in recent years because it represents the first step of the design validation process. In particular, FEA simulations are powerful to predict the dynamic behavior of physical testing on prototypes, enable engineers to optimize the design and predict the durability. This paper illustrates how FEA simulations were applied to product validation in the pre-serial phase to optimize manufacturing process. In particular, we will focus on the PCB of
Duraipandi, Arumuga PandianLeon, RenanBonato, MarcoRaja, Antony VinothKumar, LalithNiwa, Takehiro
The main purpose of the semi-active hydraulic damper (SAHD) is for optimizing vehicle control to improve safety, comfort, and dynamics without compromising the ride or handling characteristics. The SAHD is equipped with a fast-reacting electro-hydraulic valve to achieve the real time adjustment of damping force. The electro-hydraulic valve discussed in this paper is based on a valve concept called “Pilot Control Valve (PCV)”. One of the methods for desired force characteristics is achieved by tuning the hydraulic area of the PCV. This paper describes a novel development of PCV for practical semi-active suspension system. The geometrical feature of the PCV in the damper (valve face area) is a main contributor to the resistance offered by the damper. The hydraulic force acting on the PCV significantly impacts the overall performance of SAHD. To quantify the reaction force of the valve before and after optimization under different valve displacements and hydraulic pressures were simulated
Chintala, ParameshHornby, Ryan
Friction heating in solid cylindrical body contact has been an interesting subject for a long time for physicists (i.e. tribologists) and application engineers. In the current environment where the industry product, such as Diesel Rotary Pump (DRP) which operates at higher speed, the temperature rise from the friction contact is of great importance to the manufacturer for thermal safety and its environment effect. In this paper, a steady-state temperature rise under friction heating is studied on a pump roller to cam ring contact within a cyclic segment of a DRP using quasi steady thermal modeling by both the analytical solution developed to the equations from friction heating and thermal conduction and colling, and the finite element analysis (FEA) method constructed with heat flux data from actual hardware test. In addition to the analytical solution and FEA results, an experimental test was conducted to measure and collect the thermal temperature data adjacent to the contact region
Pang, Michael L.Gunturu, SrinuMothes, DaveO'Brien, Michael
Utilization of fiber-reinforced composite laminates to their full potential requires consideration of angle-ply laminates in structural design. This category of laminates, in comparison with orthotropic laminates, imposes an additional degree of challenge, due to a lack of material principal axes, in determination of elastic laminate effective properties if the same has to be done experimentally. Consequentially, there is a strong inclination to resort to the usage of “CLPT” (Classical Laminated Plate Theory) for theoretically estimating the linear elastic mechanical properties including the cross-correlation coefficients coupling normal and shear effects. As an angle-ply laminate is architecturally comprised of layers of biased orthotropic laminas (based on unidirectional or woven bidirectional fibers), an essential prerequisite for the application of CLPT is an a-priori knowledge of elastic mechanical properties of a constituent lamina. It is natural to expect that the properties of
Tanaya, SushreeDeb, Anindya
Physical testing is required to assess multiple vehicles in different conditions, specially to validate those related to regulations. The acoustic evaluations have difficulties and limitations in physical test; cost and time represent important considerations every time. Additionally, the physical validation happens once a prototype has been built, this takes place in a later phase of the development. Sound pressure is measured to validate different requirements in a vehicle, horn sound is one of these and it is related to a regulation of united nations (ECE28). Currently the validation happens in physical test only and the results vary depending on the location of the horn inside the front end of every vehicle. [7] In this article, the work for approaching a virtual validation method through CAE is presented with the intention to get efficiency earlier in product development process.
Alonso, LilianaCruz, RacielAlvarez, Ezequiel
The design of drive units in electric vehicles (EVs) presents challenges due to the need to pass multiple linear and non-linear load cases. This can result in inefficient design. Therefore, optimization plays a critical role in improving the design efficiency. However, setting up the optimization process itself can be challenging, especially when dealing with complex design variables and different load cases that require the use of various computer-aided engineering (CAE) solvers. The drive unit, being a casting component, presents additional challenges in setting up Multidisciplinary Design Optimization (MDO) process. This paper introduces an efficient process for addressing these challenges by presenting a sample Multidisciplinary Design Optimization (MDO) problem. The problem involves the manipulation of discrete design variables, such as the number of ribs, and incorporates five different load cases that require the utilization of different CAE solvers. The proposed process
Chavare, SudeepBamane, SachinChen, ChiKim, Jong-EunLi, HaiyanBandi, Punit
The engineering design process employs an iterative approach in which proposed solutions are conceived, evaluated and refined until they satisfy a priori requirements - specifications. This iterative cycle generally uses computer aided designs (CAD), engineering analysis (CAE), numerical simulations per operating scenarios, and laboratory or field prototype testing. The availability of product data can be applied to assess the vehicle requirements – specifications to facilitate the next generation design. However, the calibration and use of a digital twin facilitates exploration of tradeoffs between engineering design, product manufacturing, and business demands, plus a desire to shorten the overall time. For instance, digital twin technology enables the swift evaluation of vehicle performance in various configurations and operating conditions. The question arises of how to best integrate digital twin technology into the design process. This paper will review the engineering design
Manvi, PranavSuber II, DarrylGriffith, KaitlynTurner, CameronCastanier, Matthew P.Wagner, John
In the automotive industry, there have been many efforts of late in using Machine Learning tools to aid crash virtual simulations and further decrease product development time and cost. As the simulation world grapples with how best to incorporate ML techniques, two main challenges are evident. There is the risk of giving flawed recommendations to the design engineer if the training data has some suspect data. In addition, the complexity of porting simulation data back and forth to a Machine Learning software can make the process cumbersome for the average CAE engineer to set up and execute a ML project. We would like to put forth a ML workflow/platform that a typical CAE engineer can use to create training data, train a PINN (Physics Informed Neural Network) ML model and use it to predict, optimize and even synthesize for any given crash problem. The key enabler is the use of an industry first data structure named mwplot that can store diverse types of training data - scalars, vectors
Krishnan, Radha
This paper discusses the design and analysis of the Three-point linkage of an agricultural tractor for uncommon abusive usage practices during haulage applications. Some operators use the Three-point linkage for generating additional traction to navigate gradient surfaces, which requires additional wheel torque to overcome road slope when the trailer is attached. These maneuvers induce higher loads on Three-point linkage components, such as the lower link, lift rod, and powertrain components, which may lead to structural failures. A virtual simulation and lab-level test methodology need to be established to simulate the usage pattern upfront and predict potential failures. Multi-body dynamics (MBD) simulation was deployed to simulate the physics and extract realistic loads for Computer Aided Engineering (CAE) analysis. Data acquisition was carried out to record the strain levels during the uncommon haulage usage practices, which will be used for further studies. CAE analysis has been
Kumar, YuvarajPerumal, SolairajV, Ashok KumarSavsani, SmitkumarSubbaiyan, Prasanna BalajiBhandwalkar, AnandV V H Krishna Prasad, Tadikamalla
The Tractor is essential in both agriculture and construction, equipped with a variety of implements for different operational conditions. Its hydraulic system is crucial for controlling these implements during fieldwork and transport. The quadrant assembly is a key part of the tractor’s hydraulic control system, allowing the operator to manage important functions. This includes hydraulic control and draft control, enabling the farmer or operator to use the PC and DC levers to adjust the movement of implements during various tasks. Tractors are commonly used in fields and farms where the soil can be loose and muddy, particularly during wet puddling operations. In these muddy conditions, tractors can accumulate mud in critical components, such as the quadrant assembly. This can lead to functional issues, increased friction, and problems within the hydraulic system, especially affecting the controls for hydraulics and lever shifting for implement handling. As a result, operators may need
K, BheshmaPhadtare, YogeshGomes, MaxsonV, Ashok KumarPerumal, SolairajMagendran, G
Soft-bending actuators have garnered significant interest in robotics and biomedical engineering due to their ability to mimic the bending motions of natural organisms. Using either positive or negative pressure, most soft pneumatic actuators for bending actuation have modified their design accordingly. In this study, we propose a novel soft bending actuator that utilizes combined positive and negative pressures to achieve enhanced performance and control. The actuator consists of a flexible elastomeric chamber divided into two compartments: a positive pressure chamber and a negative pressure chamber. Controlled bending motion can be achieved by selectively applying positive and negative pressures to the respective chambers. The combined positive and negative pressure allowed for faster response times and increased flexibility compared to traditional soft actuators. Because of its adaptability, controllability, and improved performance can be used for various jobs that call for careful
Lalson, AbiramiSadique, Anwar
Today’s agriculture demands increased productivity due to the higher cropping intensities. Agricultural field readiness for cultivation requires various operation in field resulting in delay in cultivation which lower down productivity. Therefore, field operation needs to be more efficient in terms of both input cost and time consumption. One way to achieve this is by performing multiple operations in a single tractor pass, utilizing the increased power available in modern Tractors. In some agricultural operations, implements need to be mounted on the front of the tractor. Therefore, designing a front three-point hitching system for the tractor is essential to meet various farming needs, allowing customers to perform multiple operations simultaneously. The use of a front three-point linkage better utilizes the potential of four-wheel drive, higher horsepower tractors. This paper focuses on the comprehensive design process for developing and validating a front hitch system for both
Kumar, YuvarajV, Ashok KumarPerumal, SolairajGaba, RahulRamdebhai, KaravadaraSubbaiyan, Prasanna BalajiM, Kalaiselvan
Tractors, as agricultural machines consisting of various interconnected assemblies, work in unison to perform specific functions and achieve desired outputs. Among these assemblies, the Hood Assembly, Firewall Assembly, Scuttle Assembly, Fuel Tank Assembly, Fender Assembly, Floor Panel Assembly, and Footstep Assembly are all produced through sheet metal fabrication. The components of these assembly are made from sheet metal and are joined together using various techniques, such as bolts, welds, and others. The inherent characteristics of welding processes generally results in welded joints having lower fatigue strength compared to the individual parts being joined. Moreover, welds are commonly applied at geometric features or areas where the section changes within a structure. As a result, even in a structurally sound design, welded joints are often more vulnerable to fatigue failure. Hence, a comprehensive assessment of the durability of a welded structure requires placing
Kumar, ArunPandey, Manoj KumarThirugnanam, VivekanndanMani, SureshRedkar, Dinesh
This study will explore the banana fibre-reinforced composites (BFRC) as a sustainable alternative to synthetic fibre composites using experimental testing and numerical models. Composites were made using compression moulding and hand lay-up techniques with varying the fibre’s orientations and contents. Mechanical testing was done in conformity with ASTM criteria, with a focus on tensile properties. Strong correlations were established between the prediction models developed by finite element analysis (FEA) using AUTODESK Fusion 360 and the experimental data were predicted by Using the Hirsch model, the tensile strength and modulus of the composites were computed the findings showed that adding more fibre improved the mechanical qualities, especially the tensile strength. The process of scanning electron microscopy (SEM), was used to find defects in the BFRC.
Omprakasam, S.Karthick, N.Althaf, Mohammed Kassim
During the development phase of any product, it is crucial to ensure functionality and durability throughout their whole lifecycle. Physical tests have been traditionally used as the main tool to evaluate the durability of a product, especially in the automotive industry. And the evolution of computational methods combined with the Engineering Fundamentals allowed Computer Aided Engineering (CAE) simulations to predict failures in considering different conditions without building a prototype to perform a test. The use of virtual product validation using CAE simulations leads to product design flexibility on early development phase and both development costs and time reduction. This paper presents a methodology for computing the operation reaction loads in an automotive fuel filler door, which is an input needed to virtually validate the subsystem in terms of durability. The methodology is based on rigid body motion assumptions and the result shows good accuracy when comparing the
Pereira, Rômulo FrancoEspinosa-Aguilar, JonathanSilva, LucasSarmento, AlissonChou, Chun Heng
In recent decades, thermoplastics have become fundamental materials for the automotive industry, due to characteristics such as low density and increased possibility of manufacturing parts into complex geometries. Correlate the mechanical behavior of parts made with these materials, between virtual and physical testing, still poses a challenge that can be explained by the inherent nature of polymeric compounds, which generally exhibit a complex microstructural composition. This study uses a Bumper Grille made of Acrylonitrile Styrene Acrylate (ASA) as case study. This part is a fundamental external vehicle component, not only for safety criteria, but also for consumer satisfaction. To analyze the structural behavior of a vehicle components such as a Grille, Computer Aided Engineering (CAE) tools with the Finite Element Method (FEM) are commonly applied, in which a good understanding of the analysis setup and physical properties used to define the model are essential. For models built
Ferreira, Gabriel RamosSouza Silva, PauloSoares, Annelise Heidrich PietroMaciel, Ronei SantosCarvalho, Gimaézio GomesSanchez, Jorge Romero
In recent years, the automotive industry has been undergoing constant evolution, and to keep up with market trends, it’s necessary to seek better performance in the shortest time possible. Therefore, CAE (Computer Aided Engineering) becomes one of the most efficient tools for this purpose, as it can predict failures and/or improvements virtually before the start of tooling manufacturing. Thus, optimization, a process in which the best value of a parameter is obtained, becomes essential in the CAE field. In this work, Design of Experiments (DOE) will be applied, a methodology that, using applied statistics, plans, conducts, analyzes, and interprets controlled tests, evaluating predefined parameters from different areas. A light vehicle skid plate will be the case study, impacting disciplines such as durability, NVH (Noise, Vibration and Harshness), and aerodynamics, in virtual analyses such as stiffness, vibration modes, and water fording. Using the resources provided by Renault, this
dos Santos Magalhães, Daniella FernandaMoura, Vitor LoicBraga Junior, Francisco EstevanatoAndrade Barbosa, Samuel França MouraTheulen Mueller, André Marcelo
Modal performance of a vehicle body often influences tactile vibrations felt by passengers as well as their acoustic comfort inside the cabin at low frequencies. This paper focuses on a premium hatchback’s development program where a design-intent initial batch of proto-cars were found to meet their targeted NVH performance. However, tactile vibrations in pre-production pilot batch vehicles were found to be of higher intensity. As a resolution, a method of cascading full vehicle level performance to its Body-In-White (BIW) component level was used to understand dynamic behavior of the vehicle and subsequently, to improve structural weakness of the body to achieve the targeted NVH performance. The cascaded modal performance indicated that global bending stiffness of the pre-production bodies was on the lower side w.r.t. that of the design intent body. To identify the root cause, design sensitivity of number and footprint of weld spots, roof bows’ and headers’ attachment stiffness to BIW
Titave, Uttam VasantZalaki, NitinNaidu, Sudhakara
The parametrized twist beam suspension is a pivotal component in the automotive industry, profoundly influencing the ride comfort and handling characteristics of vehicles. This study presents a novel approach to optimizing twist beam suspension systems by leveraging parametric design principles. By introducing a parameter-driven framework, this research empowers engineers to systematically iterate and fine-tune twist beam designs, ultimately enhancing both ride quality and handling performance. The paper outlines the theoretical foundation of parametrized suspension design, emphasizing its significance in addressing the intricate balance between ride comfort and dynamic stability. Through a comprehensive examination of key suspension parameters, such as twist beam profile, material properties, and attachment points, the study demonstrates the versatility of the parametric approach in tailoring suspension characteristics to meet specific performance objectives. To validate the
Pakala, Pradeep KumarGanesh, Lingadalu
Slosh, a phenomenon occurring in a vehicle's tank during movement, significantly contributes to noise and vibration, often exceeding idle levels. Existing methods for evaluating NVH performance of fuel tanks primarily rely on subjective assessment, highlighting the need for a quantifiable approach to address this dynamic noise. This paper introduces a hybrid methodology to standardize the slosh phenomenon by establishing vehicle-level acceleration, braking, and driving profiles. Noise and vibration data capture, combined with defined boundary conditions, categorizes slosh noise into Impact and Roll noise, differentiated by distinct driving profiles and frequency content. Vehicle level performance is then cascaded down to subsystem level. A dedicated test rig is designed that replicates these conditions at the subsystem level where vehicle speed and braking profiles are translated into rig-specific acceleration and deceleration profiles, enabling consistent data capture for correlation
Titave, Uttam VasantZalaki, NitinVardhanan K, Aravindha VishnuNaidu, SudhakaraVirmani, Nishant
A novel design for a radial field switching reluctance motor with a sandwich-type C-core architecture is proposed. This approach combines elements of both traditional axial and radial field distribution techniques. This motor, similar to an in-wheel construction, is mounted on a shared shaft and is simple to operate and maintain. The rotor is positioned between the two stators in this configuration. The cores and poles of the two stators are separated from one another both magnetically and electrically. Both stators can work together or separately to produce the necessary torque. This adds novelty and improves the design’s suitability for use with electrical vehicles (EVs). A good, broad, and adaptable torque profile is provided by this setup at a modest excitation current. This work presents the entire C-core radial field switched reluctance motor (SRM) design process, including the computation of motor parameters through computer-aided design (CAD). The CAD outputs are verified via
Patel, Nikunj R.Mokariya, Kashyap L.Chavda, Jiten K.Patil, Surekha
The automobile industry strives to develop high-quality vehicles quickly that fulfill the buyer’s needs and stand out within the competition. Full utilization of simulation and Computer-Aided Engineering (CAE) tools can empower quick assessment of different vehicle concepts and setups without building physical models. This research focuses on optimizing vehicle ride and handling performance by utilizing a tuning specifications range. Traditional approaches to refining these aspects involve extensive physical testing, which consumes both time and resources. In contrast, our study introduces a novel methodology leveraging virtual Subjective Rating through driving simulators. This approach aims to significantly reduce tuning time and costs, consequently streamlining overall development expenditures. The core objective is to enhance vehicle ride and handling dynamics, ensuring a superior driving experience for end-users. By meticulously defining and implementing tuning specifications, we
Ganesh, Lingadalu
The parametric variation study will be very useful for understanding the design performance of any product based on the input parameters. This type of case study will be done using Design of experiments and generate several design points. Conventionally DoE solver will be working with geometry variation with CAD interface, meshing with appropriate tool then solver, finally with post processing. If a solver itself has workflow of change the geometry variation with mesh deflection method and automated post processing, then no need of geometry variation and meshing will lead to lot of time reduction in doing parametric study. Here HVAC parametric study used to show the performance of solver and accuracy of results generated. This approach can be used to optimize the design using parametric variation. This paper will show how to move Horizontal and vertical vanes using mesh morphing and what is the reduction in timeline in new product development. Here, Ansys Fluent solver is used to
Palanisamy, Vadivel
The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies has significantly changed various industries. This study demonstrates the application of a Convolutional Neural Network (CNN) model in Computational Fluid Dynamics (CFD) to predict the drag coefficient of a complete vehicle profile. We have developed a design advisor that uses a custom 3D CNN with a U-net architecture in the DEP MeshWorks environment to predict drag coefficients (Cd) based on car shapes. This model understands the relationship between car shapes and air drag coefficients calculated using computational fluid dynamics (CFD). The AI/ML-based design advisor feature has the potential to significantly decrease the time required for predicting drag coefficients by conducting CFD calculations. During the initial development phase, it will serve as an efficient tool for analyzing the correlation between multiple design proposals and aerodynamic drag forces within a short time frame
Bijjala, Sridhar
This document provides an overview of currently available and need to be developed modeling and simulation capabilities required for implementing robust and reliable Aerospace WDM LAN applications.
AS-3 Fiber Optics and Applied Photonics Committee
Pick-and-place machines are a type of automated equipment used to place objects into structured, organized locations. These machines are used for a variety of applications — from electronics assembly to packaging, bin picking, and even inspection — but many current pick-and-place solutions are limited. Current solutions lack “precise generalization,” or the ability to solve many tasks without compromising on accuracy.
Reducing vehicle weight is a key task for automotive engineers to meet future emission, fuel consumption, and performance requirements. Weight reduction of cylinder head and crankcase can make a decisive contribution to achieving these objectives, as they are among the heaviest components of a passenger car powertrain. Modern passenger car cylinder heads and crankcases have greatly been optimized in terms of cost and weight in all-aluminum design using the latest conventional production techniques. However, it is becoming apparent that further significant weight reduction cannot be expected, as processes such as casting have reached their limits for further lightweighting due to manufacturing restrictions. Here, recent developments in the additive manufacturing (AM) of metallic structures is offering a new degree of freedom. As part of the government-funded research project LeiMot [Lightweight Engine (Eng.)] borderline lightweight design potential of a passenger car cylinder head with
Kayacan, CanPischinger, StefanAhlborn, KlausBültmann, Jan
In today's fast-paced lifestyle, people spend a maximum amount of time for traveling, leading to a heightened demand for thermal comfort. Automotive HVAC play a crucial role in providing conditioned air to ensure comfort while traveling. Evaluating HVAC systems performance including delivery systems, heat exchanger efficiency, air thermal mixing zones, and temperature distribution are essential to maintain fuel economy and modern vehicle styling. However, accurately predicting cooling/heating performance using CFD simulations poses challenges due to the complex nature of heat exchanger modeling, which demands substantial computational resources and time. This paper presents the development of CFD modeling capabilities for predicting temperature distribution at duct outlet grills for defrost mode. Additionally, it assesses heater performance under maximum hot conditions. STAR-CCM+ software is employed to model the entire system, with the heater and evaporator core represented as porous
Ahmad, TaufeeqParayil, PaulsonSharma, NishantKame, ShubhamJaiswal, AnkitGoel, Arunkumar
Artificial Intelligence (AI) is currently regarded as the foremost technology for automating routine and repetitive tasks, leading to increased productivity. However, the quality of creative and design work with AI remains questionable. This paper presents a quantitative analysis of AI productivity through dynamic simulation and assesses the quality of AI results in the diameter calculation and construction of a 3D model of an engine piston as a case study. To evaluate productivity, the dynamic model segregates design tasks based on AI working hours. The quality of the formulation for calculating the engine piston diameter, derived from engine requirements, is compared with a standard formulation from a literature review. Additionally, the 3D model generated by AI is compared with a model created by human intelligence in Computer-Aided Design (CAD) software, reflecting the characteristics and properties of real engine pistons. While research on AI productivity is abundant, few studies
Gutierrez, MarcosTaco, Diana
The energy transition is a key challenge and opportunity for the transport sector. In this context, the adoption of electric vehicles (EVs) is emerging as a key solution to reduce environmental impact and mitigate problems related to traditional energy sources. One of the biggest problems related to electric mobility is the limited driving range it offers compared to the time needed for recharging, leading to what’s commonly known as “range anxiety” among users. Significant part of the energy consumption of an electric vehicle is represented by the management of the HVAC system, which aim is to ensure the achievement and maintenance of thermal comfort conditions for the occupants of the vehicle. Currently the HVAC control logics are based on the pursuing of specific cabin setpoint temperature, which does not always guarantee the thermal comfort; more advanced human-based control logics allow to attain the thermal comfort in a zone around the subjects, as known as “heat bubble”, rather
Bartolucci, LorenzoCennamo, EdoardoCordiner, StefanoDonnini, MarcoFrezza, DavideGrattarola, FedericoMulone, VincenzoAimo Boot, MarcoGiraudo, Gabriele
Have you ever gazed at the vastness of the stars and wondered what else your CNC machine can create? Greg Green had the opportunity to find out when he joined the staff at the Canada-France-Hawaii Telescope (CFHT) in Waimea, Hawaii.
This study emphasizes the importance of computer-aided engineering (CAE) approach in optimizing exhaust gas recirculation (EGR) tube under thermal load. With exhaust gases generating high temperatures, the EGR tube experiences increased stress and strain, posing challenges to its structural integrity. Moreover, the cyclic heating and cooling cycles of the engine imposes thermal fatigue, further compromising the tube’s performance over time. To address these concerns, the paper introduces a comprehensive CAE methodology for conducting factor of safety analysis. The nonlinear thermal analysis is performed on the assembly as due to high temperatures the stresses cross the yield limit. The strain-based approach is used to calculate the factor of safety. Moreover, a comprehensive case study is presented, illustrating how design modifications can enhance the thermal fatigue factor of safety. By adjusting parameters such as thickness and routing, engineers can mitigate thermal stresses and
Munde, GaneshChattaraj, SandipHatkar, ChandanGodse, Rushikesh
Minimizing vibration transmitted from the exhaust system to the vehicle’s passenger compartment is the primary goal of this article. With the introduction of regulatory norms on NVH behavior and emissions targets, it has become necessary to address these issues scientifically. Stringent emissions regulations increased the complexity of the exhaust system resulting in increased size and weight. Exhaust system vibration attenuation is essential not only from the vehicle NVH aspects but also for the optimized functionality of the subsystems installed on it. Based on earlier studies, this work adopts a more thorough strategy to reduce vehicle vibration caused by the exhaust system by adjusting it to actual operating conditions. To achieve this, a complete vehicle model of 22 DOF is considered, which consists of a powertrain, exhaust system, chassis frame, and suspension system. A method for evaluating static and dynamic vibration response is proposed. Through the use of the vehicle’s rigid
Sarna, Amit KumarSingh, JitenderKumar, NavinSharma, Vikas
Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined. Absolute and
Jacob, Jan D.
This study emphasizes the importance of CAE approach in optimizing EGR tube under vibrational load. EGR tube is a weak link in the EGR system and chances of failure due to vibration and relative displacement of mating parts, i.e., overhang or improper support at exhaust manifold, intake manifold, or EGR system. Consideration of the mating parts for the EGR tube is very important to get the realistic resonance frequencies, otherwise it could have some different results in the CAE, which will deviate from the reality. So, it’s important to study the dynamic response on the EGR tube, which needs to be taken care during the design phase. This paper aims to optimize the EGR tube under vibrational load by using CAE techniques and the industry experience as a product expertise. some critical parameter such as damping is very important during the CAE, which can be generated by doing the rigorous testing and how it affects the stress and correspondingly FOS. CAE model of EGR tube is created on
Munde, GaneshChattaraj, SandipHatkar, ChandanThakur, Abhishek Kumar
Tire/Road noise is a dominant contribution to a vehicle interior noise and requires significant engineering resources during vehicle development. A process has been developed to support automotive OEMs with road noise engineering during vehicle design and development which has test as its basis but takes advantage of simulation to virtually accelerate road noise improvement. The process uses noise sources measured on a single tire installed on a test stand in a chassis dynamometer. The measured sources are then combined with vehicle level transfer functions calculated using a Finite-Element model for structure-borne noise and a Statistical Energy Analysis (SEA) model for airborne noise to predict the total sound at the driver’s ears. The process can be applied from the initial stages of a vehicle development program and allows the evaluation of vehicle road noise performance as perceived by the driver long before the first prototype is available. This process is also extensible to
Hadjit, RabahWeilnau, KelbyEngels, BretMartin, SimonCalloni, MassimilianoMusser, Chad
The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly calibrated and validated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Model-in-the-loop (MIL), Software-in-the-loop (SIL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and previously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails. Thus, it is imminent to build simulation models which can reliably reproduce failures of components like the compressor, recirculation pump
Pandit, Harshad RajendraDimitrakopoulos, PantelisShenoy, ManishAltenhofen, Christian
The high-frequency whining noise produced by motors in modern electric vehicles can cause a significant issue, which leads to passenger annoyance. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack background noise sources to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this project, the application of artificial intelligence was applied to optimize the NVH performance of motors during the design phase. Firstly, three benchmark motor types were modelled using the Motor-CAD CAE tool. Machine learning models were trained using DoE methods to simulate batch runs of CAE inputs and outputs. By applying AI, a CatBoost-based regression model was developed to estimate motor performance, including NVH and torque, based on motor design parameters, achieving impressive R
Noh, KyoungjinLee, DongchulJung, InsooTate, SimonMullineux, JamesMohd Azmin, Farraen
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