Browse Topic: Optimization

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Shape Optimization of a Single-Stator Dual-Rotor Axial Flux Motor for eVTOL AircraftF-0082-2026-02935/5/2026
Emerging technologies in the field of electrified propulsion systems offer a promising solution to reduce the dependence on fossil fuels and improve efficiency. However, the design of high-power density electric machines introduces new challenges, including limited passive cooling potential and the issue of the weight of electric motors. To address these challenges, this paper considers analysis and design methods for high torque-to-weight ratio axial flux motors. A magnetic equivalent circuit model coupled with a lumped parameter thermal network is developed for design space exploration and optimization. This inexpensive analytical model predicts the performance of a single-stator dual-rotor axial flux motor based on geometry, loading condition, and slot and pole pair combination. To enable comparisons against real-world data, the optimization study was demonstrated using the hover mission requirements from the Research Aircraft for eVTOL Enabling techNologies (RAVEN) vehicle to
Arulampalam, Seiyon, German, Brian, Kennedy, Graeme, Smith, Cameron, Gutknecht, Jonathan
Requirements Extract for AS13001A Delegated Product Release Verification Training RequirementsSA-DIG-000065/1/2026
This digital standard is a requirements extract of AS13001A Delegated Product Release Verification Training Requirements. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
Requirements Extract for AS861C Minimum General Standards for Oxygen SystemsSA-DIG-000015/1/2026
This digital standard is a requirements extract of AS861C Minimum General Standards for Oxygen Systems. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
Requirements Extract for AS4159 Specification for an Automated Interchange of Standards DataSA-DIG-000045/1/2026
This digital standard is a requirements extract of AS4159 Specification For An Automated Interchange Of Standards Data. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
Requirements Extract for AS5127D Aerospace Standard Test Methods for Aerospace Sealants Methods for Preparing Aerospace Sealant Test SpecimensSA-DIG-000025/1/2026
This digital standard is a requirements extract of AS5127D Aerospace Standard Test Methods for Aerospace Sealants Methods for Preparing Aerospace Sealant Test Specimens. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
Requirements Extract for AS6500A Manufacturing Management ProgramSA-DIG-000055/1/2026
This digital standard is a requirements extract of AS6500A Manufacturing Management Program. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
Requirements Extract for AS50881H Wiring Aerospace VehicleSA-DIG-000035/1/2026
This digital standard is a requirements extract of AS50881H Wiring Aerospace Vehicle. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC. <img src="https://wcm14-tst.cld.sae.org/site/binaries/content/gallery/mobilus-brx/digital-supplements/as7140-data-model.png/as7140-data-model.png/sae%3Amedium" alt="AS7140 Data Model" />
uam4x: A Python-based Framework for Multi-modal UAM Design Space ExplorationSM-2026-VLADA-51741/27/2026
Urban Air Mobility (UAM) concepts require multidisciplinary analyses across multiple modes of operation and often involve discrete architectural differences such as propulsion type, rotor configuration, and mission context. Existing optimization and workflow frameworks support continuous design variables but provide limited mechanisms for handling discrete variants, multi-modal vehicle definitions, and vehicle management for UAM vehicles. This paper presents uam4x, an open-source Python framework that addresses these challenges through a structured problem definition representation, a plugin-based execution engine, integrated version control, and a function-based branching script mechanism for constructing analysis scenarios. The framework provides integration of existing tools including Open Vehicle Sketch Pad (OpenVSP), NASA Design and Analysis of Rotorcraft (NDARC), M4 Structures Studio (M4SS), and Intelligent Cross Section Generator (IXGEN) through unified plugin interfaces
Nascenzi, Thomas, Lang, Nathan, Gedney, Xuan, Fernandez, Joseph, Silva, Christopher, Welstead, Jason
Simulation of Higher Harmonic Vibration Control System Considering Actuator Amplitude LimitSM-2026-VLADA-51661/27/2026
A comprehensive numerical study was conducted to reduce helicopter rotor hub vibratory loads and fuselage vibrations using the Higher Harmonic Control (HHC) technique. A CAMRAD II model of a medium utility helicopter was developed for aeromechanical simulation, and a linear system model representing both hub vibratory load and fuselage vibration characteristics was identified offline. Optimal control inputs were then computed to minimize vibration responses under different weightings on hub vibratory load and fuselage vibration in the objective function. The predicted performance was verified through CAMRAD II simulations. Additionally, a closed-loop HHC system incorporating actuator amplitude limitations was investigated. A control algorithm regulated actuator amplitudes while maintaining phase consistency, dynamically adjusting control inputs after each iteration. The results demonstrate that the amplitude-limited closed-loop control limits excessive pitch link loads while
Kim, Do-Hyung, Park, Jae-Sang, Kang, Woo-Ram
Robust Outer-Loop Control of Quadrotors via Reinforcement LearningSM-2026-VLADA-52011/27/2026
This paper presents a reinforcement learning (RL)–based outer-loop controller for quadrotor UAV trajectory tracking and its real-world experimental validation. The proposed approach integrates RL into a standard cascaded flight-control architecture by replacing the conventional PID outer loop while retaining the onboard attitude and body-rate PID controllers. This hierarchical design preserves reliable inner-loop stabilization while leveraging RL to address nonlinear dynamics, coupling effects, and modeling uncertainty in translational motion. The controller is trained entirely in a physics-based simulation using Proximal Policy Optimization (PPO) and transferred directly to a Crazyflie quadrotor without additional tuning. Performance is evaluated through real-world figure-8 trajectory tracking experiments with varying time scales to impose increasing dynamic demands. Compared to a conventional PID outer-loop controller operating under identical conditions, the RL-based controller
Saj, Vishnu, Vemuri, Sushil, Kalathil, Dileep, Benedict, Moble
Design, Development, and Subscale Flight Testing of an Emergency Response eVTOL AircraftSM-2026-VLADA-51861/27/2026
This paper presents the design, development, and subscale flight testing of an optionally-autonomous lift-plus-cruise (LPC) eVTOL aircraft for emergency response missions that bridges the gap between existing aerial capabilities and the needs of first responders. A 4+1 LPC configuration consisting of four vertical lift propellers and a single pusher propeller was selected to balance hover performance and cruise efficiency. The vehicle is sized around a 600 lbs gross takeoff weight with a 125 lbs payload capacity. VTOL and Pusher propeller blades were optimized using parametric studies, resulting in a high Figure of Merit and propulsive efficiency. Trim analysis demonstrates efficient hover to cruise transition, lift-to-drag ratios of 10-11 between 70-90 knots, and propulsive efficiency exceeding 0.9 at the cruise speed of 100 knots. The subscale configuration utilized a simulation framework for trim and optimization of flight control laws, which were subsequently implemented on a 1/3
Sarker, Ripon, Pudasaini, Anup, Bhandari, Pratribha, Atkinson, Zach, Comer, Anthony, Fardin, Nabia, Dabaghian, Pedram, Halder, Atanu
Durability Validation of Full Vehicle Structures Using Strain Correlation and RLDA-Based Simulations2026-26-05231/16/2026
Durability validation of full vehicle structures is crucial to ensure long-term performance and structural integrity under real-world loading conditions. Accurate strain correlation between physical testing and finite element (FE) simulations plays a key role in the validation, ensuring reliable predictions of vehicle durability. In this paper, a comprehensive methodology for strain correlation on a full vehicle subjected to torture track testing is implemented. Strategic placement of strain gauges is determined through a combination of static analysis, modal analysis, and identification of critical stress regions in the FE model. Strain gauges were installed on key structural locations of a prototype to capture strain responses under severe loading environments. Simultaneously, vehicle wheel loads were recorded on the torture track to build a detailed Road Load Data Acquisition (RLDA) dataset at critical hard points, Loads measured in terms of wheel loads (WFT) are fed to MBD model to
JAJU, MAYUR, Dokhale, Sandeep, Gadre, Nilesh, Patil, Sanjay
Emerging Trends in Emission Optimization2026-26-02291/16/2026
The exhaust emission control is a vital aspect of automotive development, aimed at ensuring effective control of pollutants such as NOx, CO, and HC. The traditional method of calibrating emission control strategies, that requires extensive vehicle testing with both the fresh and aged catalysts under a variety of operating conditions, is a time-consuming process. The frequent changes in emission legislation creates new challenges for achieving a faster time to market and effective utilization of resources. So, the use of automation and machine learning (ML) in the domain of emission control is the need of the hour to proactively tackle these challenges. This paper attempts to explore emerging trends in emission optimization, such as the automated measurement process and ML/AI based data analysis, that can improve the overall process efficiency in the calibration of emission control strategies. The automated measurement process is achieved using the automation software. The data
Dhayanidhi, Hukumdeen, Balasubramanian, Karthick, A, Akash
Analysis and optimization of noise and vibrational performance of an e-axle2026-26-03401/16/2026
As the electric mobility landscape evolves, there is a growing emphasis on addressing the Noise, Vibration, and Harshness (NVH) challenges associated with electric drivetrains. The absence of an IC engine in EVs shifts the focus to other noise contributors such as gear meshing, electric machine operation, and structural vibrations. Despite the known influence of micro-geometry on gear dynamics, current optimization practices often rely on empirical adjustments or standard guidelines without fully utilizing advanced computational methods to predict and optimize NVH performance. There exists a pressing need for a systematic approach to analyse and optimize gear micro-geometry to reduce noise and vibration in high-speed e-axle applications. This research aims to bridge that gap by investigating the relationship between micro-geometry optimization and NVH characteristics of an e-axle. Through detailed modelling and optimization techniques, this research aims to identify optimal gear micro
Ankit, Priyadarshi, KULKARNI, KRISHNA, Momin, Vaseem
Development of a Systematic Methodology for Identifying and Mitigating Squeak & Rattle Issues in Automotive Seating Systems2026-26-03331/16/2026
The automotive industry constantly strives to enhance vehicle safety, comfort, and customer satisfaction. One of the critical aspects influencing these factors is the mitigation of Buzz, Squeak, and Rattle (BSR) issues, which can significantly impact perceived vehicle quality and user experience. This paper focuses on the BSR challenges specifically encountered in two key components: seat headrests and latch & striker mechanisms. Seat headrests, designed to provide comfort and safety, often face BSR issues due to component misalignment, material incompatibility, or wear and tear during usage. Vibrations and movement, especially during vehicle operation, exacerbate these problems, leading to acoustic disturbances that detract from the overall ride quality. Similarly, latch and striker in seat system is prone to squeaks and rattles due to improper fitment, environmental conditions, or mechanical stress. These issues not only compromise the auditory experience but may also raise concerns
Deole, Sameer Shrikant, Rahman, Shafeeq, Mohammed, Riyazuddin, shah, Prashant
Experimental and Numerical Investigation of Modal Behaviour in Electric Two-Wheeler Frames2026-26-03101/16/2026
This research investigates the dynamic characteristics of an electric two-wheeler chassis through a combined experimental and numerical approach. The study commences with the development of a detailed CAD model, which serves as the basis for Finite Element Analysis (FEA) to predict the chassis's natural frequencies and mode shapes. These numerical simulations offer initial insights into the structural vibration behaviour crucial for ensuring vehicle stability and rider comfort. To validate the FEA predictions, experimental modal analysis is performed on a physical prototype of the electric two-wheeler chassis using impact hammer excitation. Multiple response measurements are acquired via accelerometers, and the resulting data is processed to extract experimental modal parameters. The correlation between the simulated and experimental mode shapes is quantitatively assessed using the Modal Assurance Criterion (MAC). This matrix provides a measure of the consistency and similarity between
Das Sharma, Aritrya, Iyer, Siddharth, Prasad, Sathish, Anandh, Sudheep
A procedure for validation of full vehicle CAE models with physical tests for passive safety applications2026-26-04111/16/2026
With the fast development of computational analysis tools and capacities during the past ten years, complex and substantial computer-aided engineering (CAE) simulations are now economically possible. While the cost of crash tests has risen steadily, the fidelity and complexity, which numerical simulations could address, has multiplied keeping the cost of computational analysis more stable. The use of CAE simulations complements physical testing, accelerating the product development process, reducing cost, and ensuring safe and more optimized designs. The fundamental goal of CAE is a significant reduction in the number of physical tests conducted during the product development process. However, validating the CAE model with physical tests is essential to ensure accuracy and reliability. Simulations performed using a validated CAE model could be used to make decisions like airbag deployment or high voltage shutdown without an actual physical test. This paper discusses validating an
UPENDRAN, ANOOP
Optimizing Vehicle Dynamics: A Methodology for Reducing Correlation Gaps2026-26-00911/16/2026
In the highly competitive automotive industry, final design decisions are often made early in the product development cycle. However, physical prototypes may exhibit deviations from nominal specifications due to design tolerances, manufacturing tolerances, stiffness element fitment, and other noise factors. These deviations can lead to significant performance discrepancies (correlation gaps) between real-world performance and the digital twin representation created during the design phase. Repeatedly measuring all system parameters to account for these differences can be both costly and impractical. This research aims to bridge the gap between digital and physical models by identifying key system parameters from system characteristic data generated through controlled dynamic testing. Specifically, dynamic load cases are conducted using a 4-poster test rig, where vehicle responses are recorded at various suspension locations under controlled conditions. By analyzing these target
Verma, Rahul Ranjan, Goli, Naga Aswani Kumar, PRASAD, TEJ PRATAP
Comparative Analysis of Charger Identification Methods in Electric Truck Routing Algorithms2026-26-02061/16/2026
Optimizing Vehicle Routing is a key application for determining the most effective sequence of locations in electric trucks. This optimization not only enhances operational efficiency but also minimizes energy consumption and reduces overall costs. A critical aspect of Optimal Vehicle Routing is identifying charging stations along the route, particularly for electric vehicles with specific range requirements. The availability of these charging stations are crucial for maintaining the continuity of operations and preventing delays. This paper explores multiple methods for charger identification, simulating and comparing their effectiveness. The primary parameter for comparison is the execution time of the algorithm, which directly impacts the feasibility of real-time applications in logistics. The results of this study provide insights into the efficiency of different charger identification methods within the Optimal Vehicle Routing framework. By analysing execution times, the paper
Bhat, Adithya, Prasad P, Shilpa, Kolakar, Rakshita, Myers, Michael, Klein, Fischer, Shrivastava, Himanshu
Balancing global and local formability properties through Nb microalloying2026-26-03031/16/2026
David Martin, CBMM Asia Bernardo Barile, CBMM Europe BV Caio Pisano, CBMM Europe BV Automotive high strength steels have specific microstructure-dependent forming characteristics. Global formability is generally associated with high uniform strain values which imply good drawability and stretch forming properties driven by pronounced work hardening. Local formability on the other hand is often measured by various fracture strain values—generally higher in single phase steels. In this respect, the so-called ‘local/global formability map’ concept has been established not only to provide a comprehensive methodology to characterize existing automotive steels but also to enable improvement strategies toward more balanced forming characteristics. Niobium (Nb) microalloying is a powerful tool to achieve both property improvement in general and property balance in particular. More than two decades of research has demonstrated that Nb-induced microstructural optimization is applicable to HSLA
Barile, Bernardo
Simulation driven design of robust Crank-train systems for elevated In-cylinder combustion pressure2026-26-04001/16/2026
The need for increased in-cylinder pressure to meet the higher engine rating and stringent emissions norms requires special attention on the Main moving components torsional behaviour and the bearing performance. The work presented in this paper utilizes the 1D and 3D simulation potential of AVL EXCITE for the assessment of design changes required in Crank-Train system for the increased in-cylinder pressure from 170bar to 220bar. The key feature of the executed work was that all the design changes were accommodated with minimal changes in packaging / layout interfaces. The given work was executed on 6-Cylinder Turbocharged In-cylinder with Type V valve-train configurations. Initial brain storming & 0d calculation helped in understanding the design optimization required in each and every crank-train parts. Considering the guidelines available in terms of L/d ratio for the bearing, connecting rod length, the overall linkage specification was set up for starting with design work for
Khandelwal, Meha
Coupled Thermo-Mechanical Simulation Framework for Structural Evaluation of Battery Pack2026-26-04141/16/2026
With the rapid adoption of electric vehicles (EVs), ensuring the structural integrity and thermal safety of lithium-ion battery pack has become a critical priority. Battery failures resulting from mechanical abuse, thermal stress, internal pressure build up or electrical faults may lead to structural failure. To address these challenges, it is essential to understand the coupled thermal and mechanical responses of battery structure under extreme conditions. Thermo-mechanical simulation serves as a powerful tool for predictive safety assessment and design optimization, particularly in addressing thermal propagation and pressure-induced failure events. This study presents a comprehensive coupled thermo-mechanical simulation framework designed to evaluate the structural performance of EV battery enclosures under worst-case thermal and overpressure conditions. The methodology involves high-fidelity three-dimensional modeling of the battery pack enclosure, incorporating realistic material
BHAT, SADASHIV C, Sugumar, Mohanraj
Accelerating engine auxiliaries’ development by deploying ML techniques in CFD virtual verification2026-26-03741/16/2026
The automotive and off-road industries are heavily investing in research and development (R&D) to improve both physical and virtual verification and validation techniques. Recent software and hardware advancements have extended these techniques from simple component evaluations to complex system assessments such as involving multi-physics scenarios. Despite the benefits of virtual validation tools like structural analysis and computational fluid dynamics (CFD), they often come with high development costs, particularly in CFD applications. Virtual verification methodology, especially when combined with data science, offer significant advantages over traditional physical methods by enhancing computer-aided engineering (CAE) efficiency and reducing resource consumption which can greatly improve product design and validation efficiency across many industries. The success of machine learning applications depends on effective data processing, adequate computational resources, and the right
Jadhav, Mitali, Kumbhar, Appaso, Tirumala, Bhaskar, Nisha, Kumari
A Novel Approach to Deep Drawing Using Hybrid System and Pneumatic-Assisted Forming2026-26-03011/16/2026
ABSTRACT: This paper presents a novel Plunger-Integrated Hybrid System aimed at enhancing the efficiency and performance of deep drawing operations in metal forming processes. The proposed hybrid system strategically combines the mechanical strength of metals with the elastic flexibility of polymers, specifically polyurethane rubber, to improve formability and reduce spring-back, two critical challenges in conventional sheet metal forming. A novel two-stage forming technique is employed, an initial drawing operation using a larger radius with polyurethane rubber, followed by final radius formation using the same rubber in conjunction with a pneumatic cylinder. This integrated approach ensures uniform force distribution via the embedded plunger, significantly minimizing forming defects and enhancing the dimensional accuracy of the final components. The solution has been validated using Finite Element (FE) simulation methods, confirming its capability to produce high-quality parts
Chava, Seshadri Reddy, Singh, Prakhar, DHANAJKAR, NARENDRA, Roy, Amlan, Raju, Gokul
Simulation Based Approach to Optimize Electric Vehicle Battery Thermal System2026-26-03761/16/2026
The performance and longevity of Li-ion batteries in electric vehicles are significantly influenced by the cell temperature. Hence, efficient thermal management techniques are essential for battery packs. Simulation based optimization approaches can enhance these techniques during early product development and life cycle. In this work, a method to optimize the battery thermal system comprising of cooling plate and external insulation is described. The first part is to optimize the cell heat extraction by the cooling plate. The heat transfer coefficient of the coolant is a parameter which can indicate the thermal efficiency of a cooling plate. At the same time, it's important to keep the coolant pressure drop within a reasonable limit. A 1D simulation methodology is described to optimize the cooling channel height based on pressure drop and heat transfer coefficient targets. This methodology is based on empirical correlations and multi-objective pareto optimization. The advantage of
U, Reghunath, P S, Shebin
Multi-Model Analysis of O-Ring Compression and Relaxation Force Predictions Using Machine Learning and CAE Simulations2026-26-04661/16/2026
O-rings play a critical role in ensuring leak-proof seals in a wide range of engineering systems. Accurate prediction of their compression and relaxation behavior under various material and geometric configurations is essential for optimal design and reliability. This study presents an analysis of machine learning techniques to predict two key performance outputs, compression force and relaxation force (after 10 minutes) trained on computer-aided engineering (CAE) simulation data. The experimental setup was represented in CAE simulation and the results were compared with experimental data conducted at ZF test facilities. Simulation results correlated well with the experimental data (deviation was less than the 5%). To create a dataset for training machine learning (ML) models, realistic ranges for the input parameters such as hardness and geometrical parameters were determined, and simulation data were generated using design of experiments (DOE). Multiple ML models were developed and
Kosgi, Durgaprasad, Alva, P Pancham, Dangeti, VenkataKrishna Pavan
Optimizing Busbar Design by Investigating Critical Parameters and Their Influence on Electrical and Thermal Behaviors for Reliable Electric Vehicle Battery Packs.2026-26-04741/16/2026
With the rise of EVs, researchers are focusing on optimizing busbar design to meet the demands of high energy density, fast charging, and compact battery packs. The busbar design starts with selecting the cross-sectional area based on current-carrying capacity and material type. The width matches or exceeds the battery cell terminal size, while the length is optimized based on space constraints. The research also highlights the risk of busbars to oxidation and corrosion, which increases resistance and decreases thermal conductivity for which Plating and coating techniques are applied to improve surface hardness, durability, and thermal conductivity while minimizing heat loss. Using simulations and experimental validation, the study examines three key design parameters: weld diameter, electrical resistance, and contact resistance. A detailed analysis investigates how weld diameter influences electrical resistance and temperature rise, as well as the impact of contact resistance between
Nogdhe, Yogesh, Singh, Shobit Kumar, Paul, Jibin, Mishra, Mukesh, MENON, Praveen
Material-Optimization in Rib-Stiffened Polymer structures: A Computational & Analytical Study2026-26-04981/16/2026
Background The demand for lightweight yet rigid polymer components continue to drive innovation in structural design, particularly for applications requiring optimal stiffness-to-weight ratios. This study examines an alternative rib-stiffening approach for polypropylene plates, where conventional single-rib geometries are reconsidered in favor of parallel micro-rib configurations. While single ribs have been extensively studied, the potential benefits of distributed rib architecture remain less explored, particularly regarding their combined bending and shear performance. Key objective: This study systematically evaluates how parallel rib configurations influence mechanical performance in polypropylene plates, with specific focus on:  Bending stiffness preservation through optimized moment of inertia distribution  Shear resistance enhancement via controlled rib spacing  Coupled effect of the bending and shear resistance Prior art and their limitations: Current literature primarily
Sreejith, M P, Jain, Deepak, Maheshwari, Pankaj, Kumar, Mandeep, Ravi, Abhikrishna
Optimizing Stick Slip Performance in Automotive Interiors by Material Selection, Additives, and Design Strategies2026-26-03251/16/2026
The automotive industry is highly competitive, especially in terms of design and perceived quality. The use of hard plastics with a high gloss finish is driven by styling trends and the push towards zero gaps, making interfaces critical. In-cabin mood lighting is another feature being offered as a theme for interiors. Dashboard or cockpit designs often incorporate a significant amount of polycarbonate-acrylonitrile butadiene styrene (PC-ABS) and polycarbonate (PC). These materials provide strength and design flexibility but have the disadvantage of material incompatibility when used together, leading to stick-slip phenomena. Traditionally, felt tapes were used as interface isolation to solve this problem, but this increased manufacturing costs and assembly complications. The study focuses on the stick-slip phenomenon and material interface modifications. Specifically, it examines selecting the right surface finish on one side of the PC & PC-ABS interface to change adhesion and friction
Mohammed, Riyazuddin, R, Prasath, Rahman, Shafeeq
Optimizing Collision Warnings: A Shift from Time to Collide to Time to Brake2026-26-00471/16/2026
In automotive safety systems, Time to Collide (TTC) is traditionally used to trigger warnings in auto-emergency braking systems. However, TTC can lead to premature or inaccurate warnings as it is calculated based on the relative speed and distance between the ego and an obstacle. TTC does not consider the vehicle's braking dynamics, such as brake prefill lag which varies across different vehicles, maximum deceleration, and the effectiveness of braking systems and assumes constant speed which may not always be realistic. We propose Time to Brake (TTB) as a more effective parameter for driver warnings. TTB directly relates to the action a driver needs to take—braking. It provides a clear indication of when braking should begin to avoid a collision, whereas TTC only tells us about the possibility of a collision. To calculate TTB we utilize the brake profile, which incorporates both deceleration and system jerk for improved accuracy. The proposed warning time is the sum of variable brake
Singh, Ashutosh Prakash, Kumawat, Himanshu, Gupta, Sara
A method of selectively elevating a Seamless Switch Integrated in Fabric2026-26-05961/16/2026
This research presents the construction and working principle of Selectively Elevated Seamless Fabric Switch technology aimed at advancing automotive interior design through enhanced aesthetics, functionality, and user experience by providing a tactile surface that is available for operation only during the activated, elevated state. Traditional mechanical switches often suffer from issues such as dust and water ingress, accidental activation, and a fragmented visual profile. The proposed system integrates concealed controls sandwiched with a fabric surface, with switches selectively elevated only upon user interaction. The design incorporates conductive fabric layers and electromagnetic actuation to achieve seamless integration with vehicle interiors while maintaining responsive tactile feedback. The input provided for activating the switch can be a signal such as gesture or proximity of the user’s finger. Upon activation the switch is selectively elevated and ready for operation due
Mohunta, Sanjay, Panchal, Girish, Puthran, Shaunak
Innovative Friction Locking Mechanism for High Voltage Busbar Connections in EV Batteries2026-26-01551/16/2026
In the development of high-voltage (HV) batteries, ensuring secure connections between HV conductors and maintaining the safety and performance of the battery pack is paramount. Therefore, In the pursuit of enhancing efficiency and reliability in electrical connections, this paper explores the innovative alternate for a traditional screwing method with a friction locking mechanism for connecting busbars. The novel design reimagines the busbar as a Friction clamp (Female part) that securely holds the male part of the Busbar, significantly increasing the contact surface area up to 50%. This enhanced surface area not only improves electrical conductivity but also reduces heat generation, addressing common issues associated with traditional screw-based connections. By eliminating the need for screws, the new design streamlines the assembly process, resulting in reduced cycle times and improved overall assembly line efficiency. This study presents the design methodology, performance
Venkatesh, Murali, Raghu, Arun, Bhramanna, Amol
Determination of Acrylonitrile Content in Nitrile Butadiene Rubber Vulcanizates by Py-GCMS Techniques2026-26-05461/16/2026
Nitrile Butadiene Rubber (NBR), a copolymer of butadiene and acrylonitrile is known for its superior resistance to hydrocarbon oil, low gas permeability and excellent thermal stability. It is extensively used in seals, O-rings, conveyor belts and pneumatic tires. It is worth mentioning that these performance attributes are predominantly influenced by acrylonitrile content. While solid-state 13C Nuclear Magnetic Resonance (NMR) is an established technique for structural characterization of rubber vulcanizates, its high cost and accessibility limits its application in routine industrial analysis. This study aims to develop Pyrolysis-Gas Chromatography/Mass Spectrometry (Py-GCMS) as a robust, precise, cost-effective alternative to determine acrylonitrile content in NBR vulcanizates. This research demonstrates and establish a method to determine the acrylonitrile (ACN) content in finished rubber vulcanizates through pyrolysis gas chromatography-mass spectrometry (Py-GCMS). This method
Samanta, Rajyasree, Ghosh, Debojit, Anjana, Kanhaiya, Sen, Amit, Guria, Biswanath, Chanda, Jagannath, Samui, Barun, Ghosh PhD, Prasenjit, Mukhopadhyay, Rabindra
Nexifi11D: A Comprehensive Multidimensional Framework for Futuristic Manufacturing Ecosystems2026-26-02821/16/2026
The manufacturing sector is undergoing a paradigm shift driven by hyper-connectivity, sustainability imperatives, and accelerated digital transformation. Conventional systems, however, remain constrained by their focus on isolated optimizations—such as predictive analytics, IoT-enabled sensing, or workforce scheduling—without providing an integrated operational perspective. To address this fragmentation, Nexifi11D is introduced as a comprehensive, multidimensional framework that consolidates 11 critical dimensions of manufacturing into a unified ecosystem. Nexifi11D advances beyond traditional Industry 4.0 architectures by seamlessly integrating intelligent algorithms, immersive simulation technologies, IoT infrastructure, and predictive systems within a scalable, interoperable mesh. The framework breaks down silos across key manufacturing domains—such as sustainability, cost, operations, and workforce—enabling holistic, data-driven, and proactive decision-making. Each integrated
Kumar, Rahul, Singh, Randhir
Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization2026-26-03961/16/2026
Tyre structural durability validation is a critical aspect of automotive design, considering the worsening road conditions. One of the key validation tests for assessing structural integrity is the curb impact test, which evaluates the tyre's ability to withstand sudden and concentrated impacts. Typically, this process involves physical testing of preliminary tyre samples, followed by iterative modifications to the tyre's construction to meet durability requirements. However, this approach often compromises ride performance, necessitating a more efficient and predictive methodology. To address this challenge, a frugal simulation-based prediction methodology has been developed to evaluate tyre curb impact durability before vehicle-level testing. This allows for the optimization of tyre design parameters early in the development process, ensuring structural performance while minimizing ride and handling (R&H) tuning iterations. By reducing the number of iterations, the methodology
Sundaramoorthy, Ragasruoban, LENKA., VISWESWARA
Virtual Reality in Assembly Simulations: Outpacing Tecnomatix Process Simulate for Faster Time-to-Market2026-26-03981/16/2026
Virtual Reality (VR) technology is emerging as a transformative solution in manufacturing industry. It offers significant advantages over traditional tools like Tecnomatix Process Simulate (PS) in assembly and ergonomic simulations. Analysis using PS is time consuming and lacks real time human interaction as it relies on detailed modelling and sequential workflows, which will delay the identification of assembly no-build conditions and ergonomic issues. This paper evaluates the time and cost saving potential of VR in assembly processes and explores its role in minimizing the need for physical prototypes across various stages of vehicle development. VR provides interactive environments, enabling interaction with 3D models and real-time collaboration with various teams across the globe. This leads to faster identification of assembly process flaws, quicker iteration cycles, and a reduced need for physical prototypes in the station development process for the lines. VR allows individuals
Nagendran, Rakesh Kumar
Digital Twin for Motor & MCU incorporating Deep learning AI-ML algorithms for intelligent prognostics for Electric vehicles2026-26-04791/16/2026
As electric vehicles (EVs) become more advanced, so ensuring the reliability of critical components like the motor and Motor Control Unit (MCU) is essential. This paper presents a digital twin model designed to predict failures in motor and MCU components using machine learning. The approach focuses on detecting early signs of failure through real-world data and advanced analytics. We collected thermal and performance data from field vehicles, capturing both normal (healthy) and abnormal (faulty) operating conditions. Using this dataset, we developed and trained an Auto Encoder-based machine learning model that learns what “normal” looks like and flags deviations as potential issues. One key outcome of this study is the successful early prediction of Insulated Gate Bipolar Transistor (IGBT) degradation, where the system identified subtle behavioral changes long before any visible failure symptoms appeared. This digital twin acts as a virtual replica of the physical components
Joshi, Pawan, Pandey, Suchit, KONDHARE, Manish, UPADHYAY, ABHAY, JaganMoahanarao, Vana, Tank, Prabhu
Automated evaluation of drive file simulation accuracy2026-26-05281/16/2026
In the area of structural durability testing using servo-hydraulic actuators, developing drive files for the actuators is a major step. Testing outcomes depend on ensuring the simulation accuracy of each drive file. These drive files are developed in an iterative process for different test track surfaces at different road and load combinations till the time we achieve better correlation. Evaluation of simulation accuracy of the drive files is an extensive manual review process, making it time-consuming and resource-intensive. To address this challenge, an application has been developed to automate the comparison of actuator signals with predefined target signal files. This tool enables quick and accurate analysis of each drive file in a test run, facilitating a comprehensive review of signal deviations. Each test run has thousands of drive files based on road-load mix and actuator settings. This application helped us significantly optimize the simulation workflow by reducing the manual
SONI, YASH, Katake, Vrishali, Mullapudi, Dattatreyudu, Chaskar, Mithun
Simulation-Driven Load Spectrum Prediction_ Virtual RLDA for Chassis and Suspension System2026-26-00951/16/2026
In the rapidly evolving and highly competitive automotive industry, manufacturers are under immense pressure to bring products to market quickly while meeting customer expectations. As a result, optimizing the product development timeline has become essential. Structural integrity analysis for chassis and suspension systems lies in the accurate acquisition of operational load spectra, conventionally executed through Road Load Data Acquisition (RLDA) on instrumented vehicles subjected to proving ground excitation. At this point, RLDA is mainly used for final validation and fine-tuning. If any performance shortfalls, such as premature component failure or durability issues, are discovered, they often trigger design revisions, prototype rework, and additional testing This study proposes a Virtual Road Load Data Acquisition (vRLDA) methodology employing a high-fidelity full-vehicle multibody dynamic (MBD) representation developed in Adams Car. The system is parameterized and uses high
Goli, Naga Aswani Kumar, PRASAD, TEJ PRATAP
Optimizing Powertrain Performance: A Customer Usage-Centric Approach2026-26-00671/16/2026
The optimization of new generation trucks is crucial for enhancing performance, efficiency, and compliance with regulatory standards. In the conventional product development, the manufacturer often optimises the powertrain to meet the stringent emission which might not account for the customer usage. This study uses the simulation-based approach that integrates customer usage with help of logged vehicle data across various applications, to develop a single engine platform equipped with multiple drivetrain options. Using a data driven approach, real-world usage pattern analysis is conducted to identify key performance metrics required to optimize the driveline components tailored to each application. Additionally, the impact of certification requirements on vehicle performance is examined to ensure compliance while maximizing the benefits of the proposed optimization strategies. The findings of this research will provide valuable insights for manufacturers and fleet operators, enabling
Mohan, Vignesh, Darzi, Mahdi
Reliability of Rubber Grommets by Stochastic Analysis of Geometric Tolerances2026-26-05011/16/2026
Manufacturing tolerances pose considerable challenges in the production of rubber-based components, often leading to dimensional variations that can compromise overall product reliability. These inconsistencies may result in a range of functional issues, including poor sealing, excessive wear, misfit during assembly, and premature failure. Among these components, grommets are especially sensitive due to the complex, non-linear behavior of rubber materials, making precise dimensional control critical to ensure consistent and dependable performance. Even minor deviations in grommet geometry can trigger substantial assembly difficulties. Issues such as misalignment, buckling, insertion challenges, and potential damage to neighboring parts are commonly encountered. These complications typically require multiple rounds of design revisions and physical testing, which extend development timelines and significantly increase production costs. Real-world observations from various automotive
Beesetti, Siva, Hattarke, Mallikarjun, James Aricatt, John, PATHAN, ERAM
Optimized Panel Design for Reducing Seal Squeak and Chucking in Door & Body Seals2026-26-03411/16/2026
Quieter cabins in an automobile are the new era, they provide customers with pleasurable driving experience. Squeak and Rattle are spoil sport for any OEM that aim to improvise customer driving experience. Their nonlinear nature makes it difficult to formulate design frontloading methods. The issue of seals rubbing against the body & door interface is a clear sign of seal squeak & seal chucking. Seals are applied with anti-friction coatings to avoid stick slip phenomena between EPDM and painted panel. Primary root cause for seal squeak is coating erosion. The challenge lies in determining whether the body or the closure side contributes to the seal issue. This paper presents a distinctive approach for identifying the seal squeaking noise and enriches on the new modelling methods for seal interaction with door and body interfaces using FE software. The proposed method was able to highlight the locations along the door-body interface for squeak noise. The approach for reducing the
H, RAVISHANKAR, C M, MITHUN, MICHAEL STEPHAN, NAVIN ESTAC RAJA, Mohammed, Riyazuddin
A strategic approach to the selection of switchgear and busbars for EV battery packs2026-26-01651/16/2026
With the rising adoption of electric vehicles (EVs), the need for robust and efficient power distribution systems has become increasingly important. This paper outlines a strategic method for selecting switchgear and busbars in EV battery packs, emphasizing key factors such as safety, energy efficiency, thermal control, and future scalability. Proper optimization of these components can significantly improve performance, minimize power losses, and ensure durability under demanding operating conditions. The design and selection of battery conducting components, such as switchgears and busbars, are typically based on the maximum continuous and peak current capabilities of the EV battery pack. While this approach ensures that the components can withstand extreme conditions, it often leads to over-engineering, resulting in unnecessary costs and added weight. However, this method overlooks the dynamic power demands of the vehicle, which fluctuate based on driving conditions and usage. Real
Soman, Anu, satheesh, Goutham, K, Mathankumar
An analysis of material damping characteristics: A comparison of Oberst Bar Method and Center Impedance Method and their relationship to Component Level.2026-26-03171/16/2026
Damping materials exhibit advantageous mechanical and acoustic characteristics that enhance the structural integrity of systems. These materials find extensive applications across various industries, including automotive, aerospace, and building acoustics, and are widely employed in the development of soundproofing materials. The damping characteristics of materials primarily pertain to the dissipation of vibrational energy, the reduction of oscillations, and the controlling and subsequent attenuation of vibration-induced noise emanating from structures. To improve both structural integrity and acoustic performance, it is crucial to accurately assess the damping properties of these materials. The Oberst bar test method is a standard method used in the automotive, railway and building industry for initial optimization of damping material However, questions have arisen about the degree to which the outcomes of the Oberst test truly reflect real-world applications. Numerous experimental
Kamble, Prashant Prakash, Joshi, Manasi, Jain, Sachinkumar
Simulation based optimization of the NVH characteristics in modern high speed engine during development phase2026-26-03261/16/2026
Engine noise mitigation is paramount in powertrain development for enhanced performance and occupant comfort. Identifying NVH problems at the prototype stage leads to costly and time-consuming redesigns and modifications, potentially delaying the product launch. NVH simulations facilitate identification of noise and vibration sources, informing design modifications prior to physical prototyping. Early detection and resolution of NVH problems through simulation can significantly shorten the overall development cycle and multiple physical prototypes and costly redesigns. During NVH simulations, predicting and optimizing valvetrain and timing drive noise necessitates transfer of bearing, valve spring, and contact forces to NVH simulation models. Traditional simulations, involved continuous force data export and NVH model evaluation for each design variant, pose efficiency challenges. In this paper, an approach for preliminary assessment of dB level reductions across design iterations is
Rai, Ankur, Deshpande, Ajay Mahadeo, YADAV, RAKESH
Development of a GUI-Based Pitch Sequence Optimization Tool for Tyre Noise Reduction2026-26-03301/16/2026
Minimizing tyre noise is essential for enhancing ride comfort, especially in electric vehicles where the absence of engine noise makes tyre-generated sound more prominent. This work presents the development of a GUI-based pitch sequence optimization tool to support tyre design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. This tool plays a pivotal role in the tire development process, serving as one of the key evaluation criteria for tread pattern approval before mould fabrication. By enabling engineers to generate balanced, low-noise pitch sequences that align with both acoustic targets and engineering constraints, the tool facilitates faster design iterations and smooth integration with downstream processes. Its successful
Sampathraghavan, Lakshmi, Ramarathnam, Krishna Kumar, Mantripragada PhD, Krishna Teja, Ramachandran, Neeraj
Early Prediction of CNG Filling Time using Artificial Intelligence for Design Optimization2026-26-06621/16/2026
The CNG fuel system is a critical component in vehicle development and typically includes large-volume gas cylinders (up to 800 liters). As these vehicles often operate over long distances daily, frequent refueling is necessary, making a short gas filling time highly desirable. Currently, CNG filling time is evaluated after prototype development to determine the refueling duration. If the filling time is excessive, design changes to the fuel system are required, leading to significant cost and time penalties and causing delays in the vehicle product development cycle. By integrating AI/ML technology, a mathematical model has been developed based on various influencing parameters. This model will predict CNG gas filling time across all commercial vehicle platforms at the initial Zero design release gateway. This early prediction will enable further optimization to improve gas filling time. The goal of this research work to optimising the filling time for various platform before physical
Choudhary, Aditya Kant, Petale, Mahendra, Dutta, Surabhi, Bagul, Mithilesh
Study of Style wheel rim failure Due to Rim and disc assembly interference2026-26-05411/16/2026
This study focuses on the investigation of wheel rim failures near weld zone during repeated cornering induced by interference between the rim and disc during the wheel manufacturing assembly process. Strain gauges were employed to capture real-time stress and strain distributions at critical zones during interference fitting. The experimental results revealed that improper interference levels lead to significant stress concentrations, often surpassing the material's elastic limit, initiating micro-crack formation and promoting fatigue failure. Detailed strain analysis indicated that both radial and axial stresses contribute to long-term structural degradation. The study highlights the critical role of dimensional tolerances, surface finishes, and assembly forces in minimizing stress-induced failures. Recommendations are provided for optimizing design and assembly practices to enhance the durability and reliability of automotive wheels.
P, Praveen, DEsigan, Lakshmipathy, K, CHANDRAMOHAN, C, Santhosh
Developing Advanced CAE Model for Door Glass Regulator Operating Noise Reduction through TEST/CAE Correlation2026-26-03111/16/2026
The importance of performance improvement and weight optimization using CAE in the early design stages of vehicle development has been continuously increasing over the past two decades. And, the accuracy of CAE models plays key role, more efforts are required to improve it. Representation of exact physical model in CAE is still a big challenge for achieving an accurate TEST vs CAE correlation. In this research, the procedure and application of door system model correlation were described to reduce the glass regulator operating noise. The function of a regulator in door system is to open and close the glass. The regulator under improper design creates unwanted noise and discomfort to the passenger. In current door CAE Model, we are unable to identify this real time problem. Therefore, this paper discusses how to correlate door system model according to the assembly stage based on modal correlation and it helped in calculating accurate glass regulator operating noise. As a result, the
PANUGANTI, NARESH KUMAR, Choi, Seungchan
Optimisation of frontal impact force scheme to accelerate the target setting process for development of front-end structures in vehicles.2026-26-00011/16/2026
A passenger vehicle's front-end structure's structural integrity and crashworthiness are crucial to ensure compliance with various frontal impact safety standards (such as those set by Euro NCAP & IIHS). For a new front-end architecture, design targets must be defined at a component level for crush cans, longitudinal, bumper beam, subframe, suspension tower and backup structure. The traditional process of defining these targets involves multiple sensitivity studies in CAE. This paper explores the implementation of Physics-Informed Neural Networks (PINNs) in component-level target setting. PINNs integrate the governing equations into neural network training, enabling data-driven models to adhere to fundamental mechanical principles. The underlying physics in our model is based upon a force scheme of a full frontal impact. A force scheme is a one-dimensional representation of the front-end structure components that simplifies a crash event's complex physics. It uses the dimensional and
Gupta, Ishan, Bhatnagar, Abhinav, Kumar, Ayush
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