Browse Topic: Product development

Items (1,891)

Virtual Calibration Approach to the Development of Control Systems and Strategies for Hybrid L-Category Vehicles

2024-32-006604/18/2025

Hybrid powertrain for motorcycles has not been widely adopted to date but has recently shown significant increased interest and it is believed to have great potential for fuel economy containment in real driving conditions. Moreover, this technology is suitable for the expected new legislations, reduced emissions and enables riding in Zero Emissions Zones, so towards a more carbon neutral society while still guaranteeing “motorcycle passion” for the product [1, 2]. Several simulation tools and methods are available for the concept phase of the hybrid system design, allowing definition of the hybrid components and the basic hybrid strategies, but they are not able to properly represent the real on-road behaviour of the hybrid vehicle and its specific control system, making the fine tuning and validation work very difficult. Motorcycle riders are used to expect instant significant torque delivery on their demand, that is not properly represented in legislative cycles (e.g. WMTC); rider

Antoniutti, Christian, Sweet, David, Hounsham, Sandra

Fatigue Analysis of Motorcycle Rear Swing Arm on Different Road Surfaces

2024-32-004604/18/2025

The rear swing arm, a crucial motorcycle component, connects the frame and wheel, absorbing the vehicle’s load and various road impacts. Over time, these forces can damage the swing arm, highlighting the need for robust design to ensure safety. Identifying potential vulnerabilities through simulation reduces the risk of failure during the design phase. This study performs a detailed fatigue analysis of the swing arm across different road conditions. Data for this research were collected from real-vehicle experiments and simulation analyses, ensuring accuracy by comparing against actual performance. Following CNS 15819-5 standards, road surfaces such as poorly maintained, bumpy, and uneven roads were tested. Using Motion View, a comprehensive multi-body dynamic model was created for thorough fatigue analysis. The results identified the most stress-prone areas on the swing arm, with maximum stress recorded at 109.6N on poorly maintained roads, 218.3N on bumpy surfaces, and 104.8N on

Chiou, Yi-Hau, Hwang, Hsiu-Ying, Huang, Liang-Yu

2024 Create the Future Design Contest: Honorable Mentions

TBMG-5215312/01/2024

Scientists Fuse Simulations and Machine Learning to Accelerate Novel Additively Manufactured Materials

TBMG-5212712/01/2024

Researchers at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, have demonstrated a novel approach for applying machine learning to predict microstructures produced by a widely used additive manufacturing technique. Their approach promises to dramatically reduce the time and cost of developing materials with tailored physical properties and will soon be implemented on a NASA-funded effort focused on creation of a digital twin.

Bio-Ink for 3D Printing

TBMG-5218912/01/2024

Biomedical engineers have developed a “bio-ink” for 3D-printed materials that could serve as scaffolds for growing human tissues to repair or replace damaged ones in the body. Bioengineered tissues show promise in regenerative, precision, and personalized medicine; product development; and basic research, especially with the advent of 3D printing of biomaterials that could serve as scaffolds or temporary structures to grow tissues.

SCENE ADJUSTMENT TOOLS FOR AUTONOMY SIMULATION

2024-01-400511/15/2024

ABSTRACT This paper introduces a set of Simulation Scene Adjustment Tools which allow users to adjust relevant geo-environmental parameters to create an unlimited number of new scenes that are based on, and share relevant characteristics with, the original. We also introduce a set of novel quantitative metrics that compare the simulation scenes from the perspective of an automated vehicle system. These tools are useful for automated vehicle development and testing to alleviate the problem of having only a few simulation scenes with which to prove out the system. Citation: J. Auchter, R. Brothers, D. Beer, “Scene Adjustment Tools for Autonomy Simulation,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023.

Auchter, Joseph, Brothers, Robert, Beer, Daniel

Bridging the Gap - Applying Performance Driven Aviation Technologies in Cost Driven Ground Platforms

2024-01-334911/15/2024

ABSTRACT The complexity of ground vehicle mission systems has evolved significantly over the last few years resulting in over-taxed platforms with federated mission suites. Department of Defense (DoD) is pursuing platform evolution toward integrated mission suites. Opportunities exist to apply aspects of previously developed methodologies from the aviation sector to ground platforms. This paper describes the parallels of the evolution of aviation platforms with the similarities to ground platforms. Solutions from the military aviation community will be discussed that could reduce development risks, schedules and costs and improve mission capabilities for ground applications. Specific discussion will be on opportunities and techniques to transition performance driven, high cost, low volume technologies into mission suitable and affordable high volume solutions. Discussion of the feedback opportunities into the aviation community will be addressed. This paper is not intended to be a

Hensley, Marion P.

3D-PRINTING IMPACTS ON SYSTEMS ENGINEERING IN DEFENSE INDUSTRY

2024-01-352711/15/2024

ABSTRACT Today’s combat vehicle designs are largely constrained by traditional manufacturing processes, such as machining, welding, casting, and forging. Recent advancements in 3D-Printing technology offer tremendous potential to provide economical, optimized components by eliminating fundamental process limitations. The ability to re-design suitable components for 3D-printing has potential to significantly reduce cost, weight, and lead-time in a variety of Defense & Aerospace applications. 3D-printing will not completely replace traditional processes, but instead represents a new tool in our toolbox - from both a design and a manufacturing standpoint.

Deters, Jason

BEARING, PLAIN, SELF-ALIGNING, PTFE LINED, WIDE

AS21231B (Current)02/02/2024

ACBG Plain Bearing Committee

Reduced Order Single Parameter Tuning using Dynamic Mode Decomposition: An Application in Vehicle Dynamics

2024-26-027401/16/2024

Vehicle design necessarily involves tuning various parameters to optimize automotive performance metrics like ride and handling. The tuning process is iterative and involves a trial-and-error approach to understand the influence of the input parameters on various output metrics. We develop tuning models and run many simulations to optimize various parameters, followed by validation. This process is computationally expensive and contingent on the output metrics. Alternatively, data-driven modelling could overcome shortcomings but requires extensive data sets to train, which may not be feasible in the initial design phase. In this work, we demonstrate how we can use Dynamic Mode Decomposition, commonly used in Fluid Mechanics, to create Reduced Order Single Parameter Tuning Models, which are computationally lightweight and can provide the output metrics as a function of one tuning parameter. It reduces the tuning time and also helps to understand the system better. We developed reduced

Budhi, Veerendra Harshal

Lightweighting of Two-Wheeler Frame with CAE - Multi Domain Optimization (MDO)

2024-26-026101/16/2024

Lightweighting in the automotive industry without the use of finite element methodologies is now inconceivable. With the development and enhancement of various CAE tools available in the market, CAE-driven optimization has become part of the product development cycle. Using a variety of CAE techniques in a lightweight optimization process can significantly reduce product development lead time with good results. Traditional light weighting can be done through different iterative approaches with different manual inputs from cross-domain teams, which is usually time consuming and leads to repeated analyses, etc. The current method describes the case of a multi-domain optimization (MDO) approach involving E-Motorcycle frame weight reduction while taking into account various important cross-domain load cases using CAE methodologies. For frame optimization, the most important loads - stiffness, durability/strength (Normal & Abusive), and NVH (Modes & Vibration) - were taken into account, as

S, Vishnu, kakanur, Ashok, U PE, Manjunatha, Bhat, Sachin, POOJARY, KIRAN, V N, Kishor

Generation of tire digital twin for virtual MBD simulation of vehicles for durability, NVH and handling evaluation

2024-26-030101/16/2024

With the recent development in virtual modelling and vehicle simulation technology, many OEM's worldwide are using digital road profiles in virtual environment for vehicle durability load prediction and virtual design evaluation. For precise simulation results, it is important to have the tire digital twin which is the realistic representation of tire in the virtual environment. The study comprises of discussion about different types of tire models such as empirical, solid model, rigid ring model and flexural ring models such as Pacejka, MF Swift, CD tire, F tire etc. and also the complexity involved in development of these tire models. Generation of virtual tire model requires highly sophisticated test rigs as well as vehicle level testing with Wheel Force transducers and other vehicle dynamics sensors. The large number of data points generated with testing are converted in standard TYDEX format to be further processed in various software tool for virtual model generation. Thus, a

Bakal, Nikhil

Methodology for jury evaluation and target setting for passenger vehicle operational sound quality

2024-26-022701/16/2024

In automotive market, with competitive car prices, build quality of a car will be a major distinguishing factor. Consumer's need for acoustic comfort has evolved from the removal of annoying noises to perceived sound quality. Operational sounds from electromechanical systems like sunroof system, window regulator, door lock system, HVAC etc. directly interact with users' senses. The perceived acoustics comfort of these sounds are direct indicators of vehicle character and can influence customer's buying decision. With the reduction in product development time and stringent cost constraints, a proper structured target setting methodology to benchmark & evaluate these operational sounds is crucial. In this paper, such a target setting methodology is proposed and discussed for operational sound quality evaluation. Electromechanical noises from various vehicles are measured using binaural head measurement system. Using Simultaneous Categorical Scaling method, jury evaluation is performed

Somasundharam, Sundaralingam, Manoj K, Mridul, RAJ, GAURAV, Mohammed, Riyazuddin, R, Prasath

Optimization of Trim Clips Design for Performance Improvement

2024-26-036701/16/2024

As customers are inching towards adoption of electric vehicles as an alternative to internal combustion engines, automotive OEM's will have to embrace this change and equip with new product development process. When it comes to Electric Vehicle (EV) in comparison with Internal Combustion Engine (ICE), NVH plays a major differentiator for vehicle refinement. Squeak and rattles will account for 25% of overall in-cabin noise source in an electric vehicle, most of which is observed from interior trims. Trim is mounted using small plastic clips which act as mounts and play a significant role in part retention and part integrity during normal operation and in case of any transient events. The engineering specifications for selecting a clip is force and it is mostly driven by ease of assembly, serviceability, and durability. A single DOF system with a specimen mass is developed and stiffness and damping are calculated for different options based on transmissibility. In this work, an attempt

Deole, Sameer Shrikant, Mohammed, Riyazuddin

Systems Engineering – a key approach to Transportation Electrification

2024-26-012801/16/2024

The automotive industry has seen accelerating demand for electrified transportation. While the complexity of conventional ICE vehicles has increased, the powertrain still largely consists of a mechanical system. In contrast, vehicle architectures in electrified transportation are a complex integration of power electronics, batteries, control units, and software. This shift in system architecture impacts the entire organization during new product development, with increased focus on high power electronic components, energy management strategies, and complex algorithm development. Additionally, product development impact extends beyond the vehicle and impacts charging networks, electrical infrastructure, and communication protocols. The complex interaction between systems has a significant impact on vehicle safety, development timeline, scope, and cost. A systems engineering approach, with emphasis on requirements definition and traceability, helps ensure decomposition of top level

Narasipuram, Rajanand Patnaik, Karkhanis, Varad Abhimanyu, Ellinger, Michael, K M, Saranath, Alagarsamy, Guruprasath, Jadhav, Ravindra

Drivetrain pressure spike evaluation methodology & optimization: Simulation and Testing Correlation

2024-26-027701/16/2024

This paper describes a simulation methodology developed for pressure spike evaluation and optimization of hydraulic system architecture for off-highway applications with hydraulically actuated clutch. This pressure spike leads to a very high torque spike in driveline components during clutch pop-up conditions in puddling operations. These torque spikes lead to potential failure of driveline components i.e. gear, shaft, bearing and torsional damper during sudden engagement events. To assess the hydraulic system performance during clutch pop-up cornering conditions is very challenging and leads to compromise on operator safety in the paddy field. It is essential to develop a simulation methodology in a virtual environment to understand the system behavior during clutch pop-up condition and impact of various hydraulic system parameters. This study adopts a model-based design approach for understanding hydraulic system pressure spike phenomenon and dynamic response. Pressure spike

Memane, Nilesh, Kumar, Suneel, Veerkar, Vikrant

Tire-Rim Impact failure prediction using mathematical model

2024-26-031401/16/2024

Early design or concept phase involve decision of key Chassis & Suspension parameters finalization, in which tire size selection is one of the most important aspect. Tire size affects overall vehicle ride & handling, steering performance and styling. In addition, it will dictate the majority of suspension packaging in subsequent design phase. An improper tire size selection can lead to major design changes in later stages and cause delay in the project deliverables. Conventional method of tire size selection mainly based on load rating using Tire standards like ETRTO, JATMA etc. is sufficient for vehicle application & basic durability point of view but lacks the insight for typical tire-rim impact failure mode. Aim of the study is to develop the methodology of predicting durability failure especially kerb strike event using simplified suspension-tire mathematical model, which will help in selection of optimal tire size or its specifications in early design phase to mitigate the impact

Atal, Abhishek, Lakhera, Vivek

Implementation Of Machine Learning In Acoustics Source Detection by Leveraging Synthetic Sound Data Generation Approach

2024-26-021301/16/2024

E-Mobility and Low Noise IC Engines has pushed product development teams to focus more on sound quality rather than just focus on reduced noise levels and legislative needs. Further more qualification of products from a sound quality perspective from an end of line testing requirement is also a major challenge. End of line (EOL) NVH testing is key evaluation criteria for product quality with respect to NVH and warranty. Currently for subsystem or component level evaluation, subjective assessment of the components is done by a person to segregate OK and NOK components. As human factor is included, the process becomes very subjective and time consuming. Components with different acceptance criteria will be present and it’s difficult to point out the root cause for NOK components. In this paper, implementation of machine learning is done for acoustic source detection at end of line testing. To improve the fault detection an automated intelligent tool has been developed for subjective to

Shukle, Srinidhi, Iyer, Ganesh, Faizan, Mohammed

Controlled Production Quantity Release Applicability Determination Method

2024-26-035501/16/2024

During product development or design change, the aim is to fully validate all potential issues. On programs with significant complexity, it is difficult or impossible to fully retire all combinations of risk factors even with comprehensive analysis and testing approaches. These complex projects have the highest risk to launching with hidden defects can result in high warranty costs and erosion of customer satisfaction. This paper discusses a conservative approach called Controlled Production Quantity Release (CPQR) to manage the risks of these complex releases or changes by presenting a decision framework executed by a cross-functional team to identify those complex releases that deserve the methodical and monitored approach necessary to manage risk. The purpose of this method is to gain early concurrence with the program team with documented decision criteria rather than relying on individual opinions. This paper focus on structured approach of determining the applicability criterion

Mohammed, Zubair, Freeland, James, Soma, Nagaraju, Quadri, Danishuddin S.F.

Electric Vehicle Battery SOH and RUL prediction using Digital Twin Hybrid ML Model considering effect of Driving Behaviour

2024-26-012201/16/2024

The adoption of Electric Vehicles (EVs) is primarily limited by their dependence on batteries, which have lesser power density as compared to conventional fossil fuels as well as its ageing deterioration issues over time. Therefore, there is an urgent need to understand the modifications in battery performance characteristics with respect to changes in temperature, charging behaviour and usage pattern, low and high charge states, current variations etc. To resolve such issues, this work proposes the development of a battery digital twin model to accurately reflect battery dynamics during run time. A digital twin is a virtual model replicating a physical system's characteristics. The digital twin is developed using a physics and machine learning model trained with bench-level and vehicle level actual test data. It uses an equivalent circuit model (ECM) to predict the battery's internal resistance and polarization effect due to ionic diffusion process in the cell. ECM model generates

Dongaonkar, Saharsh, Sarkar, Prasanta, Patil, Gaurav, KONDHARE, MANISH, nath, Subhrajyoti

An AI-based digital twin of the Electric Vehicle

2024-26-009301/16/2024

For commercial vehicles, reliability is key since the vehicle is typically linked to the daily earnings of the owner. To ensure continuous vehicle operation, early issue diagnostics and proactive maintenance are important. However, an electric vehicle is a complex and dynamic system consisting of numerous components interacting with each other and with external environments such as road conditions, traffic, weather, and driving behavior. Thus, vehicle operation and performance are highly contextual and for identifying an abnormal operation (diagnostics) the solution must take into account the conditions under which it is driven. To address this, we have built an AI-based digital twin of electric vehicles. The model is an AI-based generative transformer network that generates near-ideal vehicle behavior. The present focus has been on motor, controller and battery. The model is trained using 200 vehicles first 1500 km driven data. To ensure the digital twin model learns near-ideal

Jain, Siddhant, Kumar, Vedant, Soni, Nimish, Saran, Amitabh

Machine learning based fault detection of powertrains in electric vehicles using a digital twin

2023-01-121406/26/2023

Vehicles are subject to effects that lead to a more or less rapid degradation of functions. On the one hand, aging effects lead to a gradual reduction in functional capability. On the other hand, unexpected defects in components or modules can lead to functional losses. Therefore faults in the powertrain or vehicle dynamics can cause hazards for the driver as well as uninvolved road participants. They must therefore be detected and intercepted as early as possible in order to maintain vehicle function even in critical situations until a safe operating mode can be established without any risk. This contribution presents an approach that can improve both the product development process and the operation of electrified vehicles by dynamically detecting abnormal situations in the powertrain and vehicle dynamics to infer the fault in the system. For this purpose, the vehicle is connected via 5G to an intelligent digital twin located in the Edge backend. The core component is the fault

Dettinger, Falk, Jazdi, Nasser, Weyrich, Michael, Brandl, Lukas, Reuss, Hans-Christian, Pecha, Urs, Parspour, Nejila, Li, Shiqing, Frey, Michael, Gauterin, Frank, Nägele, Ann-Therese, Lüntzel, Vitus Alexander, Sax, Eric

Model Based NVH Simulator for Virtual Development

2025-01-005905/05/2023

For mature virtual development, enlarging coverage of performances and driving conditions comparable with physical prototype is important. The subjective evaluation on various driving conditions to find abnormal or nonlinear phenomenon as well as objective evaluation becomes indispensable even in virtual development stage. From the previous research, the road noise had been successfully predicted and replayed from the synthesis of system models. In this study, model based NVH simulator dedicated to virtual development have been implemented. At first, in addition to road noise, motor noise was predicted from experimental models such as blocked force and transfer function of motor, mount and body according to various vehicle conditions such as speed and torque. Next, to convert driver’s inputs such as acceleration and brake pedal, mode selection button and steering wheel to vehicle condition, 1-D performance model was generated and calibrated. Finally, the audio and visual feedback

Park, Sangyoung, Dirickx, Tom, Kang, Yeon June, Nam, Jeong Min

Correlated beamforming based on deconvolution methods for identified vehicle exterior wind noise sources and interior noise

2025-01-002505/05/2023

Sound source identification based on beamforming is widely used today as a spatial sound field visualization technology in wind tunnel experiments for vehicle development. However, the conventional beamforming technique has its inherent limitations. To improve the performance, three deconvolution methods CLEAN, CLEAN-SC and DAMAS were investigated. These algorithms were applied for the wind noise sources identification on a production car. After analysis of vehicle exterior wind noise sources distribution, to study the energetic contribution of identified exterior noise sources to interior noise, correlation analysis between them were conducted. The results show that, the algorithm CLEAN-SC based on spatial source coherence shows the outstanding capability to remove the sidelobes for the uncorrelated wind noise sources, while CLEAN and DAMAS which based on point spread function have definite limitations. In the application aspect, the main noise source outside vehicle is from the

He, Yinzhi, Shen, Henghao, Wu, Yu, Zhang, Lijun, Yang, Zhigang

Evaluation of invariant structural and acoustic loads estimation methods to be used in vehicle platform development independent to the boundary conditions of load generation.

2025-01-005305/05/2023

Platform based vehicle development is standardized at Deere. The challenges of frontloading the integration effects of individual components within different platforms using predictive methods is key to shorten the development cycle. Components are generally characterized on test benches and can not directly be used to evaluate system performance. Invariant characterization is needed which is possible through techniques such as blocked loads estimation. To evaluate the applicability of such methods, the test stand based, and vehicle in-situ operational loads needs to be compared. The confident use of these methods for structural and acoustic loads enables the use of combination of test and simulation models of common components and system modules in a variety of products, enhancing early NVH response predictions. In this work, we compare a powertrain characterization in a vehicle and a test stand to assess the invariance of the operating mount structural loads as well as operating

Vesikar, Prasad Balkrishna, Edgington, Jason, Drabison II, John, Chaduvula, Prasanna

Simulation of in-vehicle tire noise performance from single-tire test stand

2025-01-006105/05/2023

A test and signal processing strategy was developed to allow a tire manufacturer to predict vehicle-level interior response based on component-level testing of a single tire. The approach leveraged time-domain Source-Path-Contribution (SPC) techniques to build an experimental model of an existing single tire tested on a dynamometer and substitute into a simulator vehicle to predict vehicle-level performance. The component-level single tire was characterized by its acoustic source strength and structural forces estimated by means of virtual point transformation and a matrix inversion approach. These source strengths and forces were then inserted into a simulator vehicle model to predict the acoustic signature, in time-domain, at the passenger’s ears. This approach was validated by comparing the vehicle-level prediction to vehicle-level measured response. The experimental model building procedure can then be adopted as a standard procedure to aid in vehicle development programs.

Nashio, Hiroshi, Kajiwara, Kohei, Rinaldi, Giovanni, Sakamoto, Yumiko

Application of Hybrid SEA in Vehicle NV Package Optimization

2025-01-005005/05/2023

As India’s economy expands and road infrastructure improves, the number of car owners are expected to grow substantially in the coming years. This market potential has intensified competition among original equipment manufacturers (OEMs) to position their products with a focus on cost efficiency while delivering a premium user experience. Noise and Vibration (NV) performance is a critical differentiator in conveying a vehicle's premiumness, and as such, NV engineers must strategically balance the achievement of optimal acoustic performance with constraints on cost, mass, and development timelines. Traditionally, NV package optimization occurs at the prototype or advanced prototype stage, relying heavily on physical testing, which increases both cost and time to market. Furthermore, late-stage design changes amplify these challenges. To address these issues, this paper proposes the integration of Hybrid Statistical Energy Analysis (HSEA) into the early stages of vehicle development

Rai, Nitesh, Mehta, Makrand, Ravindran, Mugundaram

Experimental Investigation into Modulated Aeroacoustic Cabin Noise arising from Unsteady Flow Conditions

2025-01-002905/05/2023

The unsteady wind conditions experienced by a vehicle whilst driving on the road are different to those typically experienced in the steady-flow wind tunnel development environment, due to turbulence in the natural wind, moving through the unsteady wakes of other road vehicles and travelling through the stationary wakes generated by roadside obstacles. This paper presents the use of experimental approach using an SUV-shaped vehicle to assess the effect of unsteady wind on the modulated noise performance, commonly used to evaluate unsteady wind noise characteristics. The approach is extended to assess the pressure distribution on the front side glass of the vehicle, caused by the aerodynamic interactions of the turbulent inflow, to provide insight into the noise generation mechanisms and differences in behaviour between the two environments. The vehicle response to unsteady wind conditions was assessed using two approaches: a dynamic upstream unsteady flow the using active side wind

Jamaluddin, Nur Syafiqah, Oettle, Nicholas, Staron, Domenic

Prediction and Optimization of Noise radiation from a Heavy-Duty Commercial Vehicle Transmission using Statistical Energy Analysis

2025-01-005105/05/2023

Heavy Duty (HD) linehaul vehicles are majorly used in transportation of goods and heavy loads between different cities or long distances. Considering the current trend, payload capacity of these heavy-duty trucks are increasing due to constant increase in the load demand. Due to which engine torques of these HD vehicles are increasing which in turn increases the transmission input torque. At higher torque levels, gear excitation also increases and transmission becomes more susceptible towards higher noise radiation. Global vehicle pass-by noise regulations for HD commercial vehicles are becoming more stringent. Historically transmissions have been considered a secondary noise source but with overall HD vehicle noise becoming quieter, the transmission can be more of a significant noise contributor. Hence, noise radiation from the transmission is also an important factor to be considered in the design phase. Gear whine is the major concern for sound radiation from the transmission. The

Rastogi, Sarthak, Milind, T. R.

The DANA EV NVH Laboratory

2025-01-000705/05/2023

A cutting-edge EV powertrain NVH laboratory has been established at DANA Incorporation’s world headquarters in Maumee, enhancing their capabilities in EV powertrain NVH development. This state-of-the-art and industry lead laboratory is designed to meet various NVH requirements for EV powertrain development and sign-off processes. This laboratory supports the use of a live motor for input and is equipped with an input module that allows for detailed examination of NVH characteristics of new powertrain configurations before prototype motors are available, significantly reducing development time for new drivetrain systems. Key features of the laboratory include a hemi-anechoic chamber, two AC asynchronous load motors, an acoustically isolated high-speed input motor, and two battery emulators that cover both low and high voltage requirements. The NVH laboratory enables engineers to assess system performance and correlate it with digital twin models. DANA engineers can develop and optimize

Cheng, Ming-Te, Zugo, Chris

A Study on Reduction of Gear Rattle Noise through Clutch Hysteresis Stabilization

2025-01-010005/05/2023

Reducing gear rattle noise within the passenger cabin is a crucial objective in vehicle development due to its direct impact on customer comfort and driving experience. Gear rattle occurs when free gears collide during meshing, primarily driven by high torsional vibrations generated by engine fluctuations. These vibrations are transmitted through the clutch system to the transmission, amplifying noise inside the cabin. To address this issue, this study focuses on optimizing the clutch by stabilizing its hysteresis, which helps in minimizing the torsional vibrations transferred to the transmission input shaft, thereby reducing gear rattle. The investigation centers on a case where significant gear rattle was observed at high vehicle speeds, particularly under high engine torque conditions. A thorough root cause analysis identified that the primary contributor to the noise was a drop in the clutch hysteresis value at elevated engine torques. This drop increased torsional vibrations in

Awasthi, Mradul, Dhankhar, Dinesh Singh, Khare, Devendra Kumar, Rana, Deepak, pandey, Anant

Keys to NVH Engineering Success You Won’t Learn in School

2025-01-007205/05/2023

Based on 44 years of NVH engineering experience, there are some keys to success that aren’t taught in engineering schools. This paper will describe these in detail and provide examples to add context. The keys are: 1. A good generalist makes a better expert. The more you understand about the complete product development process, and the better contacts you have throughout the product development organization, the easier it will be for you to find cost effective solutions to your specific issues. 2. Know your customers, and that means both internal and external customers. If you work for a supplier, it means OEMs and end users. The more you understand about the customers’ needs, the better you can address them and make your product stand out. 3. Make a crazy idea practical. Sometimes you might find a completely insane solution to your problem, such as making a major component out of solid gold. If you can use the insight gained from the insane solution to develop a practical solution

Reinhart, Thomas

Determination of optimum location of active tuned mass dampers to obtain improved NVH performance during cylinder de-activation events

2025-01-011005/05/2023

Cylinder deactivation has been a proven technique to improve fuel economy for several years now. But on the flip side during cylinder deactivation events, high amplitude torque pulsations are generated at the crankshaft of the engine over a wide frequency range creating a potential risk for NVH performance of the vehicle. As passive tuned mass dampers are effective only in a narrow frequency range, active tuned mass dampers (ATMD) have become a popular choice to mitigate the risk. Often, engineers rely on finite element (FE) models of vehicle structures to make design decisions during the early stages of vehicle development. However, there is relatively little literature available on simulation of ATMD using FE techniques. Consequently, in most cases, ATMDs are not included in the FE models of vehicle structures. Several details related to the ATMD design are decided through physical testing at the latter stages of vehicle development. To address this issue, a methodology to simulate

Maddali, Ramakanth, mogal, Akbar, Haider, Syed, Jahangir, Yawar

Navigating Evolving Vehicle NVH Challenges with Application of Emerging Technologies in Artificial Intelligence and Machine Learning

2025-01-013005/05/2023

The multifaceted, fast-paced evolution in the automotive industry includes noise and vibration (NVH) behavior of products for regulatory requirements and ever-increasing customer preferences and expectations for comfort. There is pressing need for automotive engineers to explore new and advanced technologies to achieve a ‘First Time Right’ product development approach for NVH design and deliver high-quality products in shorter timeframes. Artificial Intelligence (AI) and Machine Learning (ML) are trending transformative technologies reshaping numerous industries. AI enables machines to replicate human cognitive functions, such as reasoning and decision-making, while ML, a branch of AI, employs algorithms that allow systems to learn and improve from data over time. The purpose of the paper is to show an approach of using machine learning techniques to analyze the impact of variations in structural design parameters on vehicle NVH responses. The study begins by executing the Design of

Miskin, Atul R., Parmar, Azan, Raj, Sonia, himakuntla, Uma Maheswar

Condition Monitoring of High-Speed Rotating Machinery using Digital Twins & Machine Learning Techniques

2025-01-012805/05/2023

In the era of Industry 4.0, maintenance of factory equipment is changing with new maintenance system using predictive or prescriptive methods. These methods leverage condition monitoring through digital twins, AI, & machine learning techniques to obtain early signs of faults, type of faults, locations of fault etc. Bearings and Gears are one of the most common components and cracking/misalignment/rubbing/bowing are the most common failure modes in high-speed rotating machinery. In the present work, an end-to-end automated Machine Learning based condition monitoring algorithm is developed for predicting and classifying internal gear and bearing faults using external vibration sensors. A digital twin model of the entire rotating system consisting of the gears, bearings, shafts, and housing was developed as a co-simulation between MSC ADAMS and MATLAB. The gears and bearing dynamic models were developed in MATLAB and shaft and housing models were developed in MSC ADAMS flexible body. The

Rastogi, Sarthak, SINGHAL, SRIJAN, Ahirrao, Sachin, Milind, T. R.

Experimental Analysis of Pressure Pulsation Noise Phenomenon in a CNG-Powered Passenger Vehicle

2025-01-011205/05/2023

Compressed Natural Gas (CNG) engine has proved itself to be a worthy replacement for conventional fuels like gasoline & diesel in heavy commercial and passenger transport applications all over the world. Natural gas can be used to reduce carbon dioxide emissions while the global distribution of natural gas allows energy independence for regions with gas rather than oil reserves. In India, infrastructure development of CNG distribution and stringent emission regulations have increased the interest shown by Original Equipment Manufacturers (OEM) to concentrate towards development of CNG vehicles in every segment. From noise & vibration perspective, CNG powered vehicles are expected to maintain the same level of cabin refinement as their fossil fuel equivalents. However, one of the major challenges associated with CNG vehicles is the excitation due to additional components like CNG Pressure Regulator, Injector et al. The operational metallic / pulsation noises are generally higher as

Chatterjee, Joydeep, Ravindran, Mugundaram

Tire simulation to optimize road noise

2025-01-011105/05/2023

Tires have a significant impact on vehicle road noise. In the past, tire development has been driven by testing that is costly and time-consuming. Simulation approaches are becoming more important as the need for NVH performance requirements rises and vehicle development cycles get shorter. Therefore, simulation techniques should be used to tires at an early stage. Among various road noise, the noise of 80~160 Hz is easily felt when driving on the rough road, and this noise has a great relationship with the tire structural design. How to improve the road noise problem through tire simulation has become an important issue, so this paper puts forward the concept of virtual tire design and clarifies the responsibility of automotive enterprises and tire suppliers. In virtual tire design or tuning, an appropriate tire model is crucial for road noise performance. The CDtire model can meet the requirements, so in this article, CDtire is used to improve road noise at 80-120Hz. To obtain an

zhang, Ben, Yu Sr, Jing, Chen, Qimiao, Liu, Xianchen, Gu, Perry

test 2023/03/03 3:32 pmauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto test

SAE-PP-0782503/03/2023

test 2023/03/03 3:32 pmtest 2023/03/03 3:32 pmtest 2023/03/03 3:32 pmtest 2023/03/03 3:32 pmtest 2023/03/03 3:32 pmtest 2023/03/03 3:32 pmtest 2023/03/03 3:32 pm

Mutagaana, Festo

Design Thinking and CDIO based hybrid technique for new product design and development

2022-28-048411/18/2022

Product design and development is an essential activity in an industry to sustain in the competitive market of today's world. It is also predicted by many expert that the next industrial revolution is going to be on mass customisation. The new product development needs to address the customer requirements to become a successful commercial product. Generally, the products fail to succeed in the market as they do not satisfy the need of the customer. Several systematic approaches are available to execute product design and development in an effective manner. However, there is a lag in maping the actual expectations of the customer with the design features of the product. This research work discuss a hybrid method of new product design and development. The concept of design thinking is fused with the concept of Conceive-Design-Implement-Operate (CDIO). The design thinking tools aid the concept development stage of the design to understand and map the customer requirements with the concept

P, Hariharasakthisudhan, K, Sathickbasha, B, Surya Rajan

Development Of A Novel Methodology In Predicting Transient Deicing Simulation Of An Automotive Windshield

2022-28-043111/09/2022

Design and developments are part and parcels in any organization, mostly in the automotive sectors. Development in any field is of utmost importance aiming in reduction of time and cost. Computational Fluid Dynamics is one such field where methodology development is a prime requisite. CFD is one such time and cost saving platform where it aids the designer in product development focusing in reduction of various prototypes. The field of CFD has its presence for the past thirty years. During recent years many CFD softwares upgradation have taken place, thus many new methodologies for problem-solving also came out, in-turn leading to a reduction of computational time. One such development took place is in the multiphase models in CFD. The present study focuses in introducing a new methodology for predicting the transient deicing pattern in an automotive windshield. Simcenter STAR-CCM+ version 2021.2.1 is used for the analysis. The new method integrates two multiphase models ‘Fluid Film

SEN, ANIT, Singh, Shobhit

Comparative Study Between OpenFOAM and STAR-CCM+ for HVAC Airflow Analysis

2022-28-043711/09/2022

Vehicle air conditioning and heating system is one of the most important part of an automobile system. Computational fluid dynamics (CFD) is widely used to predict air flow rates and distribution in such HVACs. Commercial CFD codes such as FLUENT and STAR-CCM+ are widely used in simulation for industrial research. But usage of these software comes with a heavy cost. Cost is one such parameter where industries try to bring down, without compromising on the deliverables in product development. OpenFOAM is one such license free, open source code that can be used to modify and compile its code based on the needs and the physics of the problem in hand. This study assesses the performance of airflow magnitude and distribution in an HVAC using OpenFOAM. The assessment uses the same mesh with initial and boundary conditions. The results between STAR-CCM+ and OpenFOAM are compared in terms of grid-independent solutions using various scalar and vector plots. The results thus obtained is also

Baruah, Murchana

test 11/01/2022 10:40 amauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto testauto test

SAE-PP-0778011/01/2022

test 11/01/2022 10:40 am

Mutagaana, Festo

Stable Electrodes for Long-Term BCI

TBMG-4694511/01/2022

Extraction of Largely Unexplored Bodily Fluid Could Be a New Source of Biomarkers

TBMG-4691911/01/2022

Jeep springs its first BEVs

22AUTP10_0910/01/2022

Four all-new, battery-electric models will spearhead Jeep's plan to electrify 100% of its product lineup by 2025, the Stellantis brand announced on Sept. 7. The quartet of BEVs includes the 4-door Jeep Recon and an electric Wagoneer code-named Wagoneer S, to be built in North America, and the Jeep Avenger, a compact 5-door SUV that will be built and sold in Europe. Jeep executives noted a fourth new BEV model also is in the near-term launch pipeline but provided no details. The Avenger enters production next year, with Recon and the Wagoneer S following in 2024, said Christian Meunier, Jeep brand CEO. The “4xe” used to delineate Jeep's current range of plug-in hybrid vehicles will also serve as an umbrella for the new battery-electric models, with Meunier explaining that “4xe is a forward-thinking strategy” aimed at transforming Jeep into “the leading electrified SUV brand in the world” (www.youtube.com/thejeep-channel). The BEV escalation aims for 100% of Jeep's European sales and 50

Brooke, Lindsay

Enhancing Meta Model of the Brake Pad Friction Coefficient using the Explainable Machine Learning

2022-01-117509/19/2022

As increasing system complexity and various customer demands result in the need for highly efficient vehicle development processes. Once the brake torque is predicted accurately during the driving scenario in the earlier stage, it will be able to prevent the changing the vehicle or brake system design to satisfy the legal regulation and customer requirement. As brake torque performance target allocate brake pad friction coefficient level and characteristic, the accurate friction coefficient prediction should be preceded for accurate prediction for brake torque. Generally, the friction coefficient of the brake pad is known to vary nonlinearly depending on the physical properties of the disc and the pad, as well as the rotational speed of the brake disc, the disc temperature, and the hydraulic pressure. Furthermore, it varies depending on the driving scenario even the same condition. Therefore, there was a need for a new method : machine learning to solve this problem. A Mixed Effect

Cho, Sunghyun, Bang, Sunghoon, Jang, Jiwoo, Kim, Youngjae

Challenges with Commercial Supersonic Travel and some resolutions

2022-26-121505/26/2022

Innovation is the fulcrum for the Modern world.Aviation sector has adapted niche technologies for the improvement and sustainability of the business.Supersonic aircrafts were designed and developed for faster and seamless transportation. Use of Supersonic Aircrafts in the commercial arena has many technological and regulatory challenges.The NASA Advanced Air Vehicles Program Commercial Supersonic Transport (CST) Project was initiated in this regard and it details out the propositions laid out to bring Supersonic Aircrafts into the Commercial use. This highlights the importance of the Commercial Supersonic Aircraft.Intent of this paper is to provide technical analysis and solution to the norms in line with NASA Research for the Super sonic travel Infrastructure. This includes steps taken to modularize technical, logistical and Operational changes required for the Infrastructure of Commercial Supersonic Travel without discounting safety and reliability of the existing setup Integrated

JOSHI, SRIKANTH, Ramaiah, chethan prasad, Palanikumar, Senthil Kumar, Reddy, Vikramasimha

Aerospace Digital Design and Manufacturing Services- DDMS

2022-26-114805/26/2022

Digital Design, Manufacturing & Services (DDMS) is a digital approach to the way aerospace products are designed, manufactured, operated & serviced. The DDMS process focuses on digital methods & tools for end to end digital connectivity of data to meet the business process objectives like cost reduction and time to market, meeting our customers' expectations for quality, safety, functional and environmental performance. The paper covers DDMS technology where unique tools and technologies are developed to meet individual organization requirement which includes study of current available infrastructures in terms design, manufacturing, existing tools etc. Digital serves the long-term perspective, which is the next generation of planes, the new development of the new systems. Digital manufacturing is the use of an integrated, computer-based system comprised of simulation, 3D visualization, analytics and collaboration tools to create product and manufacturing process definitions

R, Suresh M.

Cloud based Architecture to implement Digital Twins

2022-26-114705/26/2022

Increased operating cost of aircraft for maintenance and repair is an area that has garnered a lot of attention. Efforts to reduce the cost has not always met with success despite aircraft being built with increased reliability including more durable engines and innovations in approach to maintenance. Most airlines focus on cutting cost of maintenance, repair and overhaul while ensuring operational availability of assets. Means to optimize cost must always be within mandatory bounds of safety of operations. Existing approaches for fleet management and sustainment are largely based on statistical distributions of material properties, physical testing and heuristic design philosophies which are often unable to address extreme requirements. Some of the major challenges include employment of conventional maintenance practices, slower turnaround time, suboptimal supply chain management, poor utilization of resources, below par manufacturing processes, outdated manual processes and inferior

Padmanabhan, Suresh, Sunkara, Bhanu Prakash

Using Digital Twin for faster & accurate performance prediction of Industrial Assets.

2022-26-114605/26/2022

Digital Twin is an emerging trend on Industrial use cases. Digital Twin is a Replica of a physical asset in Real time. The traditional way of developing Digital twin is, by using complex transfer functions. However, this requires tremendous amount of expertise with good understanding of the domain & the physics. The accuracy of the Twin model is directly dependent on the transfer functions, which many times result in a disconnect with the physical world. Physics based simulations can result in a better accuracy. However, the time taken by the software to make Real time virtual simulations is a bigger Industrial challenge due to high computational speed. So, we need to strike the right balance between speed & accuracy. There are some software who are attempting to provide solutions to this challenge. One of the techniques is to use Reduced Order Modelling (ROM) to speed up the computation of virtually simulating complex Industrial assets, without too much of approximation. The intent of

Narasimhan, Vijay Sarathy

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