Browse Topic: Design Engineering and Styling

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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" />
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 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 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 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.
testing new software productSAE-SUP-TEST134/1/2026
Software Diagram https://wcm14-tst.cld.sae.org/site/binaries/content/gallery/mobilus-brx/digital-supplements/software-diagram.png/software-diagram.png/sae%3Amedium
Enhancing Engine Reliability Testing with IoT, AI and ML: Real-Time ML-based Limit Monitoring and Predictive Maintenance with IoT sensor2026-26-06471/16/2026
The integration of Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) has transformed various industries, offering substantial benefits. The application of these technologies in engine reliability testing has immense potential as they offer real-time monitoring and analysis of engine performance parameters. Engine reliability testing is vital for ensuring the safety, efficiency, and longevity of engines. Traditional methods are time consuming, expensive, and rely heavily on manual inspection and data analysis. This paper shows how IoT, AI and ML technologies can greatly enhance the efficiency of engine reliability testing. The paper includes the following case studies: 1. ML-based Limit Monitoring for test data: With the help of machine learning models, we monitor the Engine health by comparing predicted and measured values during real-time testing. Intelligent algorithms predict and compare values, detect anomalies, and identify root causes in real-time
Yadav, Sanjay Kumar, kumar, prabhakar, R, Dinesh, Joon, Sushant, Rai, Ayush, Tripathi, Vinay Mani
Implementation of Automotive Cybersecurity Assurance Level2026-26-06241/16/2026
This paper explores the implementation of ISO-21434 Automotive Cybersecurity Assurance Levels (CAL), focusing on enhancing component level cybersecurity for a vehicle. CAL values, which range from 1 to 4, provide a metric for ensuring that assets are protected against relevant threats at various phases of the Software Development Life Cycle (SDLC). By identifying potential attack vectors and their severity early in the SDLC, specifically during the Concept phase of ISO 21434, organizations can determine the CAL values. The CAL value serves as a benchmark to determine the level of severity required during the design, development, and verification phases of the SDLC. This paper outlines a method to establish CAL values as per ISO-21434 guidelines. The proposed methodology includes a detailed analysis of threat modeling, which is crucial for identifying and mitigating potential cybersecurity risks. By conducting threat modeling, organizations can systematically assess vulnerabilities and
Ghosh, Subham, Khader Batcha, Jashic
Vehicle usage Digital Twins - Mobility analysis test case2026-26-03941/16/2026
In the evolving landscape of the automotive industry, this study presents an innovative approach to developing digital twins for driver profiles, establishing a standardized and scalable procedure for collecting and analyzing driving data on a global scale. The proposed methodology centers on the development of a robust cloud infrastructure, including a Data Lake and associated services, designed for efficient storage and processing of large volumes of data from multiple markets and vehicle types. The research introduces a adaptable procedure for data collection campaigns, applicable to diverse global markets and encompassing a wide range of vehicles, from internal combustion engines to electric and hybrid models. A key feature of this approach is the establishment of advanced data decoding protocols, enabling precise interpretation of CAN network information from vehicles of different manufacturers and models, even when the CAN structure is not previously known. The study defines
Arturo, Rubio, Marín Saltó, Anna, Diaz, Francisco, Olivencia, Sergio, Medina, Alba
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
Machine Learning Approach to ISO Road Class Prediction Using Multiple Linear Regression2026-26-06671/16/2026
The inertial profiler methodology is traditionally employed in RLDA (Road Load Data Acquisition) to measure road profiles and classify test routes into ISO road classes. However, this approach demands significant time and effort during instrumentation. Also, during data acquisition, laser height sensor data is affected especially during adverse conditions such as rainy seasons or on surfaces with improper reflectivity. Additionally, substantial resources are required for data processing to convert raw measurements into road classifications. To address these challenges, an initial attempt was made to establish a relationship between axle acceleration responses and road profiles, enabling axle acceleration measurements during RLDA to predict ISO road classes. However, this approach relied on a simple linear model that considered only axle acceleration responses, rendering the predictions susceptible to inaccuracies due to varying parameters such as vehicle speed. To overcome these
P, Praveen Kumar, P, Dayalan, Sriramulu, Yoganandam
Propeller Shaft Yoke Phase and Inclination angle Optimization in Passenger Vehicles through Analytical Method2026-26-03481/16/2026
Customer satisfaction is the most important parameter to achieve the success in the highly competitive automobile industry. Comfortable ride and handling are one of the important aspects for customer viewpoint. Propeller shaft is the critical components in the vehicle to affect the smooth operation of the vehicle. Propeller shaft universal joint (UJ) phase and inclination angle significantly affect the vehicle performance during frequent braking and acceleration. So, for this conditions, comprehensive study of the propeller shaft should be performed for smooth operation. In this paper, Propeller shaft UJ phase and inclination angle optimization is studied through analytical method, which are very essential parameter for optimizing induced vibration performance and comfort. Propeller shaft characteristics influenced by several factors like vehicle torque, propeller shaft joint type, materials properties, UJ phase and inclination angle and shaft unbalance value. By optimizing the above
Kumar, Sarvesh, Sanjay, L, S, Manickaraja, Kanagaraj, Pothiraj
Multi-Objective Optimization and Reduced-Order Modeling for Aftertreatment System Performance Prediction2026-26-04261/16/2026
As emission regulations grow increasingly stringent, aftertreatment system designs are becoming more complex, requiring robust performance across the full range of engine operating points (EOPs). Traditionally, aftertreatment development has relied on computational fluid dynamics (CFD) simulations conducted at a limited set of representative points, focusing primarily on single performance objectives such as minimizing back pressure, enhancing ammonia uniformity, or reducing diesel exhaust fluid (DEF) deposits. However, these objectives are inherently interdependent, and optimizing for a single parameter often negatively impacts others, leading to suboptimal system performance across the full engine map. To address these challenges, this paper presents a multi-objective optimization framework combined with a reduced-order modeling approach to predict aftertreatment system behavior across the full engine operating range. The methodology captures the interactions among various
Nanduru, Enoch, Willey, Donald, Udhane, Tushar Sudam, Pal, Yash
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
Calibration strategy to address abnormal engine noise in cold transient driving condition2026-26-05851/16/2026
Passenger vehicle users often maneuver their cars in diverse and unpredictable driving patterns. The vast and varied terrain of the Indian subcontinent further complicates this scenario, introducing unique challenges due to differences in driving expertise, vehicle usage, and environmental conditions. A specific challenge addressed in this paper arises during cold to ambient engine temperatures and transient driving conditions—a critical phase for engine calibration to ensure optimal drivability and emissions performance. With current calibration practices, an after-burn like abnormal engine noise was observed during certain transient driving patterns in cold to ambient temperature conditions. This paper presents a novel calibration methodology designed to eliminate such abnormal noise. The proposed approach involves a step-by-step transient calibration strategy refinement, making the calibration process more robust and adaptable to any driving behavior. The paper outlines the specific
Suna, Bhagyashree, Tyagarajan, Sethuramalingam, Pise, Chetan, Aishwarya, Amritansh
Addressing Seat Belt Discomfort Among Indian Female Driving Population Through Anthropometric Data Collection and Simulation2026-26-00161/16/2026
The rate of female drivers in India is increasing alongside the rapid growth of the Indian automotive industry. A driving comfort survey conducted among female drivers revealed that many experiences dis-comfort when wearing seat belts—whether while driving or as front-seat passengers. This discomfort is primarily due to a phenomenon referred to as “neck cutting.” The root cause of neck cutting is likely related to vehicle design, which is traditionally based on Anthropometric Test Devices (ATD’s) representing the 50th percentile of the global population. However, a literature review indicated that the anthropometric dimensions of the Indian populations are generally smaller than those of the global for the respective candidate. This highlighted the need to collect region-specific anthropometric data for India. During this research work, Indian anthropometric data was collected through the Size India 2.0 project, covering a wide demographic region across India. This study was in
Kulkarni, Nachiket, Chitodkar, Vivek V, Eknath Chopade, Santosh, Yamgar, Babasaheb S, Mahajan, Rahul
Analysis and Optimization of Stick-Slip Behaviour in Metal-Plastic Interfaces for Connected Tail Lamp Assemblies in Electric Vehicles2026-26-03321/16/2026
The seamless and sleek design of connected tail lamps adds a visually striking element to the car's exterior. It aligns with contemporary automotive trends and gives the vehicle a premium and futuristic appearance. Automakers use these lamps as a design signature to establish brand identity. Connected tail lamps improve visibility for drivers behind the vehicle. The assembly of connected tail lamps can pose several challenges, especially due to their complex design and integration requirements. Metal-plastic creak is a common concern in electric vehicles (EVs), often noticeable when driving on uneven roads. This primarily results from stick-slip behaviour at the interface of metal and plastic components, intensified by improper alignment. When the designed geometric dimensioning and tolerancing (GD&T) is not met in real manufacturing conditions, misalignment introduces unintended contact forces, leading to intermittent micro-sliding and frictional energy release, which manifests as an
MICHAEL STEPHAN, NAVIN ESTAC RAJA, C M, MITHUN, Mohammed, Riyazuddin
A Novel Analytical Approach to Predict Vehicle Parking Brake Cable Performance and Optimize Cable Routing2026-26-04831/16/2026
The performance of vehicle parking brake cables are critical for ensuring vehicle safety and functionality. Vehicle manufacturer evaluate the robustness of cable performance at different road gradient conditions. Effort and stroke performance are among the key parameters for evaluating cable performance. While parking brake system should be designed to minimize effort losses through the cable routing, packaging constraints often prevent it. Therefore, it is essential to estimate the losses through cable routing and optimize parameters of the parking brake cable system. Currently, the methods used for evaluating cable performance are either experimental or empirical based. CAE methods using finite element analysis (FEA) and multibody dynamic approaches are computationally expensive and not yet fully established due to modelling and solving complexity of dynamic cable which involves continuously changing and updating contacts. The available analytical approaches incorporates cable system
Iqbal, Shoaib, sabri, SALAH, Siddiqui, Arshad
Leveraging Telematics Big Data Analytics for Real-Time Monitoring of Catalytic Converter Failures and Root Cause Identification for Emission Compliance2026-26-05911/16/2026
The automotive industry is continuously evolving at high pace to meet rising customer expectations, reliability, reduced maintenance, and most relevant, compliance with stringent emission norms. Traditionally, the analysis of vehicle emissions relies heavily on periodic inspections and manual checks. These conventional methods are often time-consuming, prone to human error, and lack the ability to provide real-time insights. Also, identifying Catalytic converter failures due to non-manufacturing issues require meticulous physical inspections and historical data reviews, which are not always accurate or timely. Telematics or Connected cars technology being one of the major technological innovations in recent times revolutionizes these processes by enabling real-time data exchange between vehicles and external systems. The current study presents an innovative approach to utilizing telematics data for real-time monitoring of vehicle emissions and pinpointing Catalytic converter failures
DEV, Triyambak, Prasad, Kakaraparti Agam, Kalkur, Varun, Modak, Saikat, AGARWAL, Shashank, Chandra, Animesh, Paul, Varsha, Garg, Amit, Sundararaman, Venkataraman, Bose, Sushant
Development of a High-Fidelity Vehicle Dynamics Model with Rear-Wheel Active Roll Control for Improved Stability2026-26-00931/16/2026
This work introduces a unified vehicle dynamics framework that combines detailed modeling and active control to enhance ride comfort and handling stability. A full 12-degree-of-freedom vehicle model is developed to simulate dynamic responses across a range of driving conditions. Unlike conventional approaches, this model incorporates both linear and nonlinear tire behavior, enabling more accurate prediction of vehicle motion. To further improve performance, an active roll control mechanism is proposed, utilizing rear-wheel suspension actuators to counteract undesired body roll and yaw instabilities. A novel co-simulation environment is established by coupling MATLAB/Simulink-based control strategies with high-fidelity multibody dynamics from ADAMS Car. The model is calibrated and validated using experimental data from an instrumented test vehicle. Results show that the integrated control system significantly reduces critical parameters such as roll angle, yaw rate deviation, and
Duraikannu, Dinesh, DUMPALA, GANGI REDDY
Design and Optimization of Air Intake Manifold for 4cylinder 4valve Turbocharged CNG Engines: Enhancing Performance Metrics and Emission Compliance2026-26-01241/16/2026
This study presents the development and optimization of an air intake manifold for a 3-liter, 4-cylinder, 4-valve turbocharged engine operating on Compressed Natural Gas (CNG). The intake manifold plays a critical role in determining engine performance, directly influencing parameters such as power output, brake-specific fuel consumption (BSFC), and emissions. A systematic design methodology was adopted, starting with standard design repository, which were refined through iterative improvements focused on manifold volume, runner geometry, injector location, and fuel injection pressure. Computational Fluid Dynamics (CFD) simulations were conducted to evaluate the influence of manifold geometry and injector positioning on air-fuel mixing. The analysis assessed three potential injector locations: the tangential port, the swirl port, and a common upstream point where air splits into individual intake runners. Among these, the common upstream point consistently demonstrated superior air
Lomada, Balaji, Vasudevan, Sindhuja, RAVI, HARIKRISHNAN, N, Harish, UG, Remesh
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
Streamlined Methodology for E-Motor Performance Evaluation using a configurable Universal Inverter2026-26-05101/16/2026
Electric motor benchmarking is often constrained by limited availability of motor-specific data, particularly when dealing with commercially available or third-party electric motors. This paper presents a streamlined and scalable methodology for characterizing unknown eMotors using a configurable universal inverter platform. The proposed approach is specifically designed for OEMs and Tier 1 suppliers seeking to evaluate performance metrics such as torque accuracy, peak and continuous capability, efficiency, and control behaviour—without prior access to key motor parameters or simulation data. A central challenge in this context is the stepwise electromagnetic characterization required to determine the phase current needed for accurate speed and torque control, especially under a Maximum Torque per Ampere (MTPA) or Maximum Torque per Watt (MTPW) strategy. As this requirement is highly dependent on the motor’s topology and electromagnetic properties, most conventional approaches rely on
Kanya, Benjamin, Duchi, Francesco, Ravi, Abhishek
Development of Component Level Testing Method for Passenger Car Wheels2026-26-05041/16/2026
In the design of automotive wheels, safety is a crucial factor. Wheels contribute to a vehicle handling, braking and overall driving performance. Wheel are designed to withstand the weight of the vehicle and force generated during driving. It is the medium which isolates the obstacles coming from roads. Impact tests are usually performed after the wheel has been already designed and first prototypes have been produced. The test involves 90-degree free fall dynamic impact to determine the wheel resistance to deformation, cracking and overall structural failure. Its best method to captured the exact results during and post impact. These results are contributes the major role in development of automotive wheel rims. Most of the OEM’s are validating the wheels in virtual environment as FEA analysis software and LS Dyna. In this paper detailed procedure of testing of wheels at component level is presented. This work determines the development of test procedure for passenger car wheels in
Tormal, Uday Bapurao
Rear Wiper Motor with Nozzle Integration for Improved wiping performance and Perceived Quality2026-26-06001/16/2026
In the current modern days of driving, rear wiping performance plays a crucial role in safe driving. This study focuses on improving the rear wiping with add on benefits like improved BSR performance, cost saving and perceived quality. This new concept has the rear wiper motor assembly which accommodates the nozzle also thereby making it a single unified assembly with reduced system complexity. This concept eliminates the complex hose routing of washer system for rear wiping which is usually packaged at spoiler or HMSL. It also helps in improved spray coverage and reduced dry wiping which in turn enhances system reliability with clean & quiet operation. This integrated nozzle concept is much more compact than the available products in the market with minimum number of end items. Also, this design comes with non-return valve which ensures there is no delay in the spray execution. And it improves the cleaning efficiency by maintaining consistent fluid pressure. This concept comes with
Dhage, Prashant, K, NAGARAJAN, G, Sabari Rajan
Artificial Neural Network for predicting thermal cool-down behavior of a School Bus Cabin2026-26-06531/16/2026
Passenger vehicles, such as buses, exhibit significant heat absorption when parked under direct sunlight, leading to elevated interior temperatures during daytime and a consequent reduction in thermal comfort. In our previous study, we developed and validated a transient numerical method to predict the thermal behavior of the cool-down process in a school bus cabin. Despite its accuracy, modeling such complex simulations using Computational Fluid Dynamics (CFD) remains time-intensive, with pre-processing taking up to a week and simulations requiring an additional 8-10 hours. While physics-based simulations are known for their accuracy, they are inherently slower. Conversely, data-based meta models offer faster results, but their outputs must be carefully correlated with test data or physics-based model data. This study aims to leverage existing CFD data to train and develop an Artificial Neural Network (ANN) based meta model, which is then benchmarked against test results for
Suryavanshi, Apoorva, sharma, shantanu
Reverse Engineering and Digital Twins in Powertrain Design: Enhancing Performance and Sustainability2026-26-00651/16/2026
This study explores the application of reverse engineering (RE) and digital twin (DT) technology in the design and optimization of advanced powertrain systems. Traditional approaches to powertrain development often rely on legacy designs with limited adaptability to modern efficiency and emission standards. In this work, we present a methodology combining 3D scanning, computational modeling, and machine learning to reconstruct, analyze, and enhance internal combustion engines (ICEs) and electric vehicle (EV) drivetrains. By digitizing physical components through RE, we generate high-fidelity DT models that enable virtual testing, performance prediction, and iterative improvement without costly physical prototyping. Key innovations include a novel mesh refinement technique for scanned geometries and a hybrid simulation framework integrating finite element analysis (FEA) and multi-body dynamics (MBD). Our case study demonstrates a 12% increase in thermal efficiency for a retrofitted ICE
Bernikov, Mark Alexandrovich, Kurmaev, Rinat
Investigating Thermal Fatigue Cracks in Exhaust Manifolds of Longitudinally Mounted 1.2L 4-Cylinder Engines2026-26-04881/16/2026
This study addresses the challenge of ensuring the durability of closed couple exhaust manifolds in the compact engine bays of modern vehicles, focusing on a longitudinally mounted 1.2L 4-cylinder engine. The original sheet metal Exhaust manifold design failed thermal fatigue bench durability test, requiring a complete redesign to improve strength without changing materials. Initial simulation predictions significantly deviated from physical test results, with repeated cracks observed during accelerated thermal fatigue bench testing, despite simulations predicting a higher number of cycles before failure. This difference highlighted the need for a deeper understanding of the manifold's failure modes, primarily thermal fatigue, and mechanical vibration during engine transients. The design of experiment (DOE) approach was used to find the effect of different parameters e.g., gas temperature, surface temperature, air flow, thermal gradient, on the durability result & also to understand
Krishnan, K.S.Gopala, Mishra, Ashutosh, Yadav, Sanjay Kumar, Kumar, Deepak, Tripathi, Manas, kumar, prabhakar
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
Test method and set up development for electric parking brake performance and durability validation in vehicle level as per RWUP2026-26-05051/16/2026
The Objective is to develop a testing load case which can assess vehicle electric parking brake (EPB) performance and durability at vehicle level in different project development phases. In current scenario the EPB become one of a primary feature available in many passenger vehicles helps customers to apply this secondary braking system to hold the vehicle when parked. So, it is particularly important to evaluate this feature close to RWUP for the vehicle service life and studying the result before vehicle launch. The test method should be capable of capturing failures related to physical concerns, electrical characteristics, actuation time, gradient vehicle hold, effectiveness during vehicle running and durability. The most important challenge in this test method development is it should simulate the actual sequence followed by user in field on vehicle. A completely automated test set up integrating PLC and COBOT with closed loop feedback developed and discussed in this paper. During
DHANAPAL, M R, Vijayakumar, Narayanan, MAHESH, B, B, VENKATASUBRAMANIAN, Arthanathan, Sankaranarayanan
Optimization of Air extractor for improved Door closing effort and perceived premium Feel2026-26-05921/16/2026
This research analyses the significance of air extractor on car door closing effort, especially within the context of highly sealed cabins. The goal is to measure their effectiveness in lowering pressure-induced resistance, study how cut-out cross section and location affect performance, and its contribution to vehicle premium feel. Current vehicle design trends prioritize airtight cabin sealing for improving aerodynamic efficiency, NVH performance. This causes a problem in door closing operation. Air trapped while closing door creates transient pressure pulses. This pressure surge creates immediate discomfort to user i.e., Popping in Ears and requires high door closing force, and long-term durability problems in hinges and seals. In properly sealed cabins, air pressure resistance can contribute to 25% to 40% of total door closing force. Air extractors, which are usually installed in the rear quarter panels or behind rear bumpers, serve as pressure relief valves, allowing for smoother
P, Sivasankar, Sankineni, Vikhyath Rao, Shah, Sahil, Marimuthu, Anbarasan
NN FMU: Deep Learning Models for Next-Gen xiL Vehicle Simulation2026-26-04521/16/2026
Functional Mock-up Units (FMUs) have become a standard for enabling co-simulation and model exchange in vehicle system development. However, traditional FMUs derived from physics-based models can be computationally intensive, especially in scenarios requiring real-time performance. This paper presents a Python-based approach for developing a Neural Network (NN) based FMU using deep learning techniques, aimed at accelerating vehicle simulation while ensuring high fidelity. The neural network was trained on vehicle simulation data and developed using Python frameworks such as TensorFlow. The trained model was then exported into FMU, enabling seamless integration with FMI-compliant platforms. The NN FMU replicates thermal behavior of vehicle with high accuracy while offering a significant reduction in computational load. Benchmark comparisons with Physical Thermal Model demonstrate that the proposed solution provides both efficiency and reliability across various driving conditions
Srinivasan, Rangarajan, ASHOK BHARDE, Pooja, MHETRAS, Mayur, CHEHIRE, Marc
Impact of density in simulation model for extreme cold ambient conditions2026-26-03881/16/2026
Battery Electric Vehicles (BEVs) necessitate highly efficient thermal management strategies, as cabin heating directly consumes energy from the finite traction battery, potentially reducing driving range significantly. Early-stage design evaluations of warmup performance commonly rely on one-dimensional (1D) simulations due to their computational speed and efficiency. The accuracy and predictive capability of these models are critically dependent on how well they represent blower operation and account for temperature-induced variations in air density. This fidelity is essential because engineers depend on warmup simulations to set HVAC targets that will deliver real‑world comfort and defrost performance within stringent range constraints. Earlier, warmup simulations employed a Constant Mass Flow (CMF) approach, which simplifies computations by assuming a fixed air density at a standard reference temperature. However, this approach contrasts with real-world blower behavior, where
Subramanian, Karthik, Mishra, Abhishek
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
Road noise improvement of a passenger vehicle through end-to-end CAE-Simulation using Transfer Path Analysis (TPA) approach2026-26-04311/16/2026
Refined NVH performance of a vehicle is a mark of premium quality. Achieving the desired NVH performance in different vehicle operating conditions is always a Herculean task and early stage “CAE design recommendations” play crucial role in overall vehicle design development. This becomes tougher when the program is very much cost, weight and timeline sensitive. This paper explores simulation approach for addressing a major noise issue for a vehicle running at a constant speed on a rough road. The first and the most critical step is to identify the exact root cause of the issue. Hence, we propose a detailed full vehicle level “contribution analysis (CA) + transfer path analysis (TPA)” methodology (everything done through the simulation) and then go for the design recommendations to improve the performance. We used road excitation power spectral density (PSD) as the input at all the four wheels (spindle locations) calculated through MBD software. The first step i.e. contribution analysis
Mahajani, Mihir, Nascimento, Fabio, ADINARAYANA REDDY, KODIDELA, Matyal, Mahantesh, Tenagi, Irappa, Sardar, Chenna
Parameterizing External Factors Influencing E-motor Consumption2026-26-01751/16/2026
In recent times, a standard drive cycle is an excellent way to measure the electric range of EVs. This process is standardized and repeatable; however, it has the drawback of testing in a controlled environment with a low content of active functions. This can cause a significant variation in predicted range between drive cycles and actual on-road tests. This problem can be addressed via on-road testing and by using customer-based velocity cycles which involve more active functions. While on-road tests provide a more accurate idea of real-world consumption, the repeatability of these tests is low due to excessive randomness. External factors such as ambient temperature, driver behavior, traffic, terrain, altitude, and load conditions affect the vehicle during on-road testing, making repeatability difficult. No two measurements can have the same consumption even if done on the same road with the same vehicle due to these factors. This paper presents a machine learning-based method to
Kelkar, Kshitij, Kanakannavar, Rohit
Dimensional Management in Automotive Vehicle Design & Development for Perceived Quality Improvement in Buses2026-26-04471/16/2026
Perceived quality (PQ) is one of the most important factors in engineering signoff as well as customer delight and product improvement (feel, look & touch). The PQ is something related to feel of the product in terms of gap, flushness, fitment and appearance as per the costumer perceptions and expectations. Validate both design and engineering with the perceived quality review. In today's automotive bus industry this is equally applicable. In this paper we have explored the dimensional management scope in improving the PQ requirements and expectations by utilising the dimensional variation analysis (DVA) approach. We have explored & explained the fundamentals of vehicle aggregates fitment process and impact of fitment tolerances as used in DVA model to resolve vehicle packaging issues (critical gaps & clearance variation as per expected no. of vehicles to be manufactured in future at initial stage of the vehicle design). It is further extended into system level DFMEA to include DVA in
Singh, Vinay Kumar, Dewangan, Ved Prakash, Kumar, Rahul, Deep, Amar
Transforming Manufacturing: Increasing Throughput and Reducing production Complexity with Digital Twins2026-26-04491/16/2026
In traditional manufacturing, increasing production line capacity often involves physical trials, leading to downtime, high costs, and operational risks. This paper presents a bidirectional digital twin developed for the Fischertechnik Smart Factory Kit, enabling real-time simulation and validation of production line modifications before actual deployment. The digital twin integrates with a Siemens PLC to mirror real-world operations, capturing live production data and visualizing key parameters like cycle time and machine utilization in a 3D environment. Engineers can test various optimization scenarios adjusting conveyor speeds, optimizing robot paths, and modifying buffer sizes to enhance efficiency. The best-performing configurations are identified based on throughput, cycle time, and resource utilization, and validated changes are automatically deployed to the PLC, ensuring seamless implementation. Beyond capacity optimization, this solution improves overall production efficiency
Kumar, Rahul, Singh, Randhir
Evaluation of Thermo-Mechanical behavior of brake discs in vehicles using Multidisciplinary approach2026-26-04331/16/2026
The objective of this paper is to evaluate the thermal performance of the brake discs in the design stage of its life cycle by developing a methodology to replicate the dynamometer testing using multi-disciplinary Finite Element Analysis (FEA) methods. A simulation workflow was formulated in which Computational Fluid Dynamics (CFD) was used to create temperature and velocity dependent Heat Transfer Coefficients (HTC) which were in turn used in Computer Aided Engineering (CAE) to do a thermo-mechanical analysis. With this workflow various designs of the brake discs were analyzed. A sensitivity study was done to determine critical design features that affected its thermal performance. A final design was fixed that met both the weight and thermal performance targets. This design was evaluated in dynamometer testing, and 95% correlation was achieved. Thus, the developed simulation workflow ensured that a first-time right brake disc can be finalized in the design stage, which will meet the
Balaji, Praveen, K, Karthikeyan, S, KESAVPRASAD, S Kangde, Suhas
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
Johnson-Cook model calibration for brittle materials under impact loads2026-26-03671/16/2026
In the assessment of parts subjected to impact loading, the current process relies on static analysis, which overlooks the significant influence of high strain rate on material hardening and damage. The omission of these effects hinders accurate impact simulations, limiting the analysis to comparative studies of two components and potentially misidentifying critical hot spot locations. To address these limitations, this study emphasizes the importance of incorporating the effects of high strain rate in impact simulations. By utilizing the Johnson-Cook material calibration model, which includes both material hardening and damage models, a more comprehensive understanding of material behavior under dynamic loading conditions can be achieved. The Johnson-Cook material hardening model accounts for the strain rate sensitivity of the material, providing an accurate representation of its behavior under high strain rate conditions. This allows for improved prediction of material response
Pratap, Rajat, Apte Sr, Amol, Babar, Ranjit, Dudhane, Karan, Poosarla, Shirdi Partha Sai, Tikhe, Omkar
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
Comprehensive Durability Assessment of Planet Carrier in Heavy-Duty Tipper Gearboxes Using RLDA Torque Data2026-26-04431/16/2026
In heavy-duty tippers, where challenging conditions demand high torque, planet carriers play a crucial role by enabling efficient load distribution and torque transmission while supporting gear ratio and speed variation in space-constrained systems such as automatic transmissions, hybrid drivetrains, and electric vehicles. This paper focuses on the comprehensive durability performance assessment of planet carriers using duty cycles derived from RLDA measurements for a heavy-duty tipper gearbox development program. The existing Design Validation Plan (DVP) for the planet carrier considers first gear utilization of 10-15% at 40% vehicle overload, in line with historical data. However, recent trends in mining applications revealed vehicle overloads of 55-65%, leading to an increase in first gear utilization (25-35%). This shift presents challenges for OEMs to enhance design durability while incorporating additional safety margins to meet the demands of a competitive, cost-driven market
Bagane, Shivraj, Pendse, Ameya
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