Browse Topic: Simulation and modeling

Items (10,800)

Implementation of Automotive Cybersecurity Assurance Level

2026-26-06241/16/2026

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

Propeller Shaft Yoke Phase and Inclination angle Optimization in Passenger Vehicles through Analytical Method

2026-26-03481/16/2026

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 Prediction

2026-26-04261/16/2026

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

Leveraging Telematics Big Data Analytics for Real-Time Monitoring of Catalytic Converter Failures and Root Cause Identification for Emission Compliance

2026-26-05911/16/2026

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 Stability

2026-26-00931/16/2026

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 Compliance

2026-26-01241/16/2026

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-axle

2026-26-03401/16/2026

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

Experimental and Numerical Investigation of Modal Behaviour in Electric Two-Wheeler Frames

2026-26-03101/16/2026

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

Development of Component Level Testing Method for Passenger Car Wheels

2026-26-05041/16/2026

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

Artificial Neural Network for predicting thermal cool-down behavior of a School Bus Cabin

2026-26-06531/16/2026

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 Sustainability

2026-26-00651/16/2026

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

A procedure for validation of full vehicle CAE models with physical tests for passive safety applications

2026-26-04111/16/2026

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

Optimization of Air extractor for improved Door closing effort and perceived premium Feel

2026-26-05921/16/2026

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 Simulation

2026-26-04521/16/2026

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 conditions

2026-26-03881/16/2026

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

Road noise improvement of a passenger vehicle through end-to-end CAE-Simulation using Transfer Path Analysis (TPA) approach

2026-26-04311/16/2026

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 Consumption

2026-26-01751/16/2026

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

Evaluation of Thermo-Mechanical behavior of brake discs in vehicles using Multidisciplinary approach

2026-26-04331/16/2026

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

Simulation driven design of robust Crank-train systems for elevated In-cylinder combustion pressure

2026-26-04001/16/2026

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 loads

2026-26-03671/16/2026

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 Pack

2026-26-04141/16/2026

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 verification

2026-26-03741/16/2026

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

Comprehensive Durability Assessment of Planet Carrier in Heavy-Duty Tipper Gearboxes Using RLDA Torque Data

2026-26-04431/16/2026

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

Model Standardization for MBD Throughout Entire Power Unit Development Process

2026-26-04281/16/2026

The distribution of mobility equipped with electrified power units is advancing towards carbon-neutral society. The electrified power units require an integration of numerous hardware components and large-scale software to refine high-performance system. Additionally, a value-enhancement cycle of mobility needs to be accelerated more than ever. The challenge is to achieve high-quality performance and efficient development using Model-Based Development (MBD). The development process based on V-model has been applied to electrified power units in passenger vehicle. Traditionally, MBD has been primarily utilized in the left bank (performance design phase) of the V-model for power unit development. MBD in performance design phase has been widely implemented in research and development because it refines prototype performance and reduces the number of prototypes. However, applying MBD to the entire power unit development process, from performance design phase to performance verification

Ogata, Kenichiro, Katsuura, Akihiro, Tsuji, Minako, Matsumoto, Takumi, Iwase, Hiromu, Nakasako, Seiya, TAKAHATA, Motoki

Testing Framework and Safety Evaluation for Vehicle-to-Vehicle (V2V) Charging Systems in Electric Mobility

2026-26-01761/16/2026

As the adoption of electric vehicles (EVs) accelerates, innovative charging strategies like Vehicle-to-Vehicle (V2V) charging are gaining attention for their potential to offer emergency energy support and decentralized charging options. Particularly in countries like India, where the charging infrastructure is still maturing, V2V charging can play a vital role in extending operational range and enhancing user convenience in fleet and remote applications. This paper proposes a structured testing framework to evaluate the functionality, safety, communication protocols, and energy transfer efficiency of V2V systems. Emphasis is placed on real-time testing using HIL simulations, thermal behavior under load transfer, fault detection, and protection mechanisms. The framework supports OEMs and integrators in validating reliable, scalable V2V solutions aligned with future EV interoperability standards.

Uthaman, Sreekumar, Mulay, Abhijit B

Automated Parameterization of CAE Model Based on Test Data Response Bands

2026-26-04361/16/2026

This study presents a data-driven approach aimed at enhancing the correlation between physical test data and Computer-Aided Engineering (CAE) simulations, with an emphasis on adapting the standard CAE model's response to minimize any gaps relative to the response of a given test specimen. Leveraging historical test data, machine learning techniques are used to categorize responses into distinct bands, effectively capturing the inherent variability observed in real-world scenarios. This categorization step recognizes patterns across a wide range of test data, forming the foundation for closely matching and adapting CAE models to new, unseen hardware data. In typical automotive simulation workflows, tuning a standard CAE model to match new hardware test data involves iterative parameter adjustments and simulations. This process can be time-consuming and often lacks predictive insight into the necessary modifications. The approach developed in this study addresses this challenge by

Khopekar, Maria, Arya, Bibhu, Sridhar, Raam, Mohan, Pradeep, Kurkuri, Mahendra

Multi-Model Analysis of O-Ring Compression and Relaxation Force Predictions Using Machine Learning and CAE Simulations

2026-26-04661/16/2026

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

Impact of Virtual ECUs on Software Development and Validation Using the Shift Left Strategy

2026-26-06811/16/2026

The automotive industry is undergoing a transformative shift with the integration of Virtual Electronic Control Units (vECUs) in software development and validation processes. Physical ECUs require actual hardware setups, which can be expensive, time-consuming to configure, and may not be readily available during early development stages. This abstract presents the application of a Level 3 vECU to enable early-stage testing in alignment with the Shift Left Strategy, thereby reducing development time and cost. The developed vECU includes production-intent code for the Application Software (ASW), Runtime Environment (RTE), Basic Software (BSW), and Operating System (OS), while adapting the Microcontroller Abstraction Layer (MCAL) and Complex Device Drivers (CDD) for the virtual environment. The vECU replicates the functional behavior of a physical ECU and supports standard automotive communication protocols such as CAN, LIN, Ethernet and FlexRay, allowing system-level validation in a

Bhopi, Amey, Sengar, Bhan

Material-Optimization in Rib-Stiffened Polymer structures: A Computational & Analytical Study

2026-26-04981/16/2026

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

Experimental Evaluation of Tyre Vertical Dynamic Stiffness and Damping for Ride Model Applications Using Flat Trac

2026-26-06071/16/2026

The damping and vertical dynamic stiffness of a tyre are critical to ride comfort and overall dynamics, particularly for low-frequency excitations in urban and highway driving. Accurate ride models depend on precise tyre parameterization, as tyres are the primary interface between the vehicle and the road, absorbing surface irregularities before the suspension engages. This study investigates an experimental methodology characterizing the vertical dynamic behaviour of pneumatic tyres using a Flat Trac test machine. Contrary to the conventional approaches that depend on intricate shaker rigs or frequency dependence function models, the proposed technique uses a realistic force displacement loop-based technology which is appropriate for ride model applications. Dynamic stiffness is calculated as the peak force divided by peak displacement during vertical sinusoidal excitation. Damping is derived from hysteresis energy loss per cycle. The tests were conducted under various conditions by

Duryodhana, Dasari, Sethumadhavan, Arjun, Tomer, Avinash, Ghosh, Prasenjit, Mukhopadhyay, Rabindra

Driver-in-the-Loop Optimization of Tire-Vehicle Dynamics using Virtual Tire Development approach through CD Tire Models

2026-26-00991/16/2026

This study provides a virtual development process using VI-Grade Driving Simulator and Adams simulation integrating CD tire models to modify all-terrain tire performance for an altered and new proposed version of an existing production vehicle. The proposed alteration introduces ride height changes, weight distribution changes, and centre of gravity changes from existing vehicle design. The proposed new vehicle variant also introduces tire change from highway terrain type to all-terrain type as it was intended to deliver some off-roading capabilities, thereby vehicle dynamics and kinematics recalibration & tuning required. The conventional development cycles through physical prototypes are time-consuming and expensive. Alternatively, this solution combines high-fidelity tire simulation, driver-in-the-loop (DIL) simulation, and multi-body dynamics analysis to reduce development time and prototype cycles. The proposed method begins with baseline correlation, augmenting Adams vehicle

Shrivastava, Apoorv, Asthana, Shivam

Wheel side load calculation using the strain measurement on swingarm and duty cycle development

2026-26-05831/16/2026

Typically duty cycle development for any component carried out in the absence of direct acting load will be based on the measured strain from the Road Load data Acquisition(RLDA) and comparing it with the rig level testing. The biggest drawback from such an approach is the fact that the selected loads can be drastically different from the actual experienced peak load from the actual RLDA. This happens because the strain gauges will have sensitivity toward all three directional loads and sometimes due to complex structure design uni-directional sensitive locations are difficult to find out or strain gauge. This will lead to over predicting the loads in some cases and the selected load may end up yielding the component in a single cycle itself. This paper discusses the method employed to calculate the loads at the input load location using the strain gauges which are cross sensitive and using that input loads to select the loads for the testing of the component. Also it talks about the

Anandh, Sudheep, Prasad, Sathish, R S, Mahenthran

Achieving ride comfort in bus suspension by varying air spring performance

2026-26-00811/16/2026

Air springs are widely used in commercial buses to obtain better quality of ride and comfort. Selecting the right air spring is a critical aspect of suspension design. However, this selection process is often constrained by the limited availability of off-the-shelf components as the development of a custom air spring involves long lead time and high tooling cost. This can be justifiable only at high production volumes. Air springs are tunable as compared to conventional mechanical metal springs. Their performance can be adjusted by varying the internal air pressure and volume, enabling them to accommodate a wide range of vehicle load conditions. In actual design practice, component packaging constraints and fixed mounting dimensions often restrict the choice of air spring. Additionally, Front and rear suspension requires air springs with different characteristics. To overcome these limitations, an auxiliary air tank is also called a ping tank that can be used along with an existing

Patre, Kamlesh, Salunkhe, Swapnil, Paranjape, Shekhar

Human-Centric Automotive Interior Lighting assessment: A feedback-Based Approach

2026-26-01321/16/2026

Automotive interior lighting systems must comply with rigorous internal standards while aligning with evolving customer expectations across diverse vehicle segments. As technological advancements accelerate and consumer demands grow, these systems have become increasingly advanced. Traditionally, validation relied on physical integration with vehicle and its hardware particularly silver box unit and infotainment systems. However, this conventional approach presents several limitations, including dependency on mature hardware and software, challenges in testing and synchronization across multiple lighting modules, and constraints in design validation accuracy. To address these limitations, this paper introduces an innovative approach that employs real-time hardware-in-the-loop (HIL) simulation for digital lamp testing. This method facilitates autonomous and abuse testing, enabling independent validation of interior lighting systems within a controlled virtual environment while

Shah, Kunal, Joshi, Vivek S., Mandloi, Prince

Enhanced Integrated Cooling-Protection Plate for Battery pack Underbody Impact Resistance in Electric Vehicles

2026-26-01691/16/2026

In the quest for enhancing electric vehicle performance and safety, this paper presents a comprehensive investigation into the design and performance of high-voltage (HV) battery cooling plates featuring dedicated cooling channels, integrated with structural bottom protection members positioned at the bottom. The study aims to address the dual challenges of effective thermal management and enhanced crash protection in electric vehicles. Through a combination of Design iterations, Thermal performance evaluation and Crash simulations, the research evaluates the cooling efficiency and structural resilience of the proposed design. Findings reveal that the integrated cooling plates not only maintain optimal battery temperatures under various operating conditions but also significantly improve the vehicle's crashworthiness. The paper concludes with the results of numerical simulations, rigorously validated against the robust design requirement globally accepted for series components to

DUSAD, SAGAR, Kummuru, Srikanth, Joshi, Amarja

Experimental Frequency-Based Substructuring for Full-Vehicle NVH Characterization in Electric Vehicles

2026-26-03091/16/2026

Electric vehicles introduce new NVH challenges due to high-frequency excitations from e-motors and associated electronics. These excitations, often in the kilohertz range, are primarily transmitted as structure-borne noise and require advanced experimental methods for accurate characterization and mitigation. Traditional simulation approaches are insufficient to capture the true dynamic behavior of complex components under operational boundary conditions. This study presents a fully experimental Frequency-Based Substructuring (FBS) methodology applied to a complete electric vehicle. Frequency Response Functions (FRFs) of individual subsystems—such as the e-motor, mounting system, inverter housing, and body connection points—are measured and transformed using Virtual Point Transformation to obtain consistent six-degree-of-freedom representations. These Virtual Point models are assembled into a full-vehicle system to investigate the structure-borne transfer paths to the vehicle interior

Kohlhofer, Daniel, Pingle, Pawan Sharad, de Klerk PhD, Dennis

A methodology to evaluate steering performance using Hardware in Loop Testing

2026-26-05441/16/2026

In the present generation, steering system plays a major role in vehicle performance and factors like vehicle stability and control. This is because it is a direct interface to the driver. But to tune the steering system to the required standard, it takes several months for an OEM. This increases the lead time and development cost. Steering test benches have been increasingly popular in the recent automobile development process as they offering great advantages. They offer high level of control over system parameters which helps tune the performance of a steering system, especially for the perception of steering feel while driving. There are various steering test benches being developed to solve concerns that OEMs are facing while tuning and validating. A new methodology is defined involving the Steering Test Bench which can perform Hardware in Loop (HIL) and Driver in Loop (DIL) simulations. The objective of this paper is to establish correlation between Vehicle level & Virtual level

Agarwal, Gourav, Rajput, Srijan, Rasal, Shraddhesh, ahire, Manoj, Naidu, Kethireddi, Kumar, Deva, Prusty, B Rabi

Engine and After-treatment optimization using Simulation tools

2026-26-00571/16/2026

To achieve world-class engineering quality and reduce the effort and cost associated with conventional techniques, it is essential to incorporate digital validation during the development and validation phases. This research paper explores the methodologies and applications of advanced simulation tools for creating models of engines and their sub-components using MATLAB/Simulink, parameterizing these systems with AVL CruiseM, and operating them using ETAS Labcar-Operator. The paper provides an in-depth analysis of optimizing engine and after-treatment parameters, demonstrating their impact on performance and environmental compliance. It presents a series of simulation case studies that illustrate the effects of different parameter settings on the efficiency and emission levels of diesel passenger and commercial vehicle engines. These case studies highlight the overall workflow of model-based system development, emphasize various development milestones, and correlate these with actual

Shukla, Saurabh, Shilledar, Aneesh

Video 2 Scenario: A Novel Method to Generate Edge Case Traffic Scenarios from Dashcam Videos

2026-26-06661/16/2026

This paper presents Video 2 Scenario, a systematic and cost-effective method to generate edge case scenarios derived from road events captured in dash camera videos. Current methods for obtaining real-world scenarios rely on supplementary sensor data like LiDAR, GPS and radar, which require expensive sensor setups for data collection. Other scenario generation methods rely on manual effort by human experts, which can be laborious and time-consuming. Our proposed methodology utilizes state-of-the-art deep learning models to extract vehicle trajectories, road layouts and other scenario-specific elements and reconstructs a scenario in the format of simulation scripts. The scripts are then refined by replaying the scenario multiple times in a simulation with attached virtual sensors to minimize the discrepancy between the subsequently obtained simulated video data and the original dash camera video data. The refined simulation scripts ensure that critical edge case scenarios are replicated

Ramalingam, Surya Prasath, Priyadarshi, Marut, Khan, Parvej, Kumar, Vaibhav, Pandey, Gaurav, Lohani, Bharat

Virtual Strain correlation with measured strain test data over Frame using nCode Design Life

2026-26-05451/16/2026

Physical tests serve as a benchmark to validate and improve the accuracy of CAE models. If the CAE results correlate well with physical test data, it confirms that the simulation is reliable and can be used for predictive analysis. Earlier for correlation, we use stress output from generic load-cases and single max value of measured strain data which was inappropriate to get exact correlation. Since output of virtual strain gauge is strain history, so entire characteristics can be compared i.e. magnitude and phase. In this paper, we have used nCode Design Life’s virtual strain gauge approach to correlate an FE Model’s (Frame) result with measured strain gauge data of RLDA test. If the model has been properly meshed, loaded, and constrained, the predicted virtual strain from Design Life will correlate with the measured strain. In this problem, model (Frame) is loaded with unit force and moment in all three directions at 31 locations (Hardpoints). Virtual Strain gauge calculates the

Kumar, Mohit, Dhole, Avinash, Trigune, Vinayak, Kangde, Suhas

Optimizing Diesel Engine Performance through Parametric Study of Fuel Injector Configurations for Enhanced Sustainability

2026-26-04021/16/2026

The pursuit of sustainable transportation solutions requires continuous improvement in engine efficiency and performance. This study presents a comprehensive parametric analysis of high-horsepower diesel engine combustion modeling, focusing on fuel injector configurations to optimize power density and overall engine efficiency. The model was first validated with experimental data. Based on the validated model, a series of Design of Experiments (DoE) simulations were conducted, examining four distinct fuel injector hole configurations, each with four different spray inclusion angle (umbrella angle) variations. The set of different fuel injector configurations was selected through benchmarking analysis. The primary objective was to identify the most effective injector design for improved combustion characteristics and engine performance. Upon determining the superior configuration, further simulations were performed with increased injector throughflow to fine-tune the optimal design

Ailaboina, Akhil, Gandhi, Naresh, Marwaha PhD, Akshey, G, Suwarna, Chogule, Vijay, Bhat, Vishal

Nexifi11D: A Comprehensive Multidimensional Framework for Futuristic Manufacturing Ecosystems

2026-26-02821/16/2026

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 Optimization

2026-26-03961/16/2026

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

Qualitative and Quantitative Correlation Study for Exterior Aerodynamics for Automotive Vehicle

2026-26-04071/16/2026

The objective of the exterior aerodynamic performance assessment of automotive vehicles is to reduce the aerodynamic drag pressure and rear side wake zone, which improves overall energy consumption of the vehicle. Almost 30 to 40% of the energy is required to overcome the drag force and wake zone pressure offered by the air on the automotive vehicle. With the increase in high performance computing power (HPC) and its affordability, computational fluid dynamics (CFD) has become a popular and more effective tool for aerodynamic design and analysis in the automobile industry. In the real-world scenario, automotive vehicle is subjected to varying wind and operating conditions which affect its aerodynamic characteristics, and therefore it is difficult to reproduce such physical phenomenon in a conventional wind tunnel. Hence, the entire aerodynamic assessment was done in wind tunnel which is equipped with advanced aerodynamic assessment techniques like wheel rotations, boundary layer

Chalipat, Sujit, Biswas, Kundan, Tare, Kedar

SEooC-Based Design Framework for Integrated EV Power Conversion Systems under ISO 26262 Compliance

2026-26-01921/16/2026

The rapid integration of electric vehicle (EV) power conversion elements—such as traction inverters, onboard chargers, and DC-DC converters—into unified architectures poses new challenges for ensuring functional safety compliance as per ISO 26262. This paper presents a system-level framework that leverages the Safety Element out of Context (SEooC) approach to design and validate reusable safety-critical components independent of vehicle-specific applications. By defining clear assumptions of use and ASIL decomposition strategies, the proposed method facilitates early-stage fault analysis and verification. The framework integrates model-based development with Hardware-in-the-Loop (HIL) testing and formal verification techniques to validate both control logic and hardware behavior under diverse fault injection scenarios. The result is a scalable, standards-compliant methodology that reduces time-to-market and enhances reliability in integrated EV power electronics platforms. The work

Uthaman, Sreekumar, Mulay, Abhijit B, Gadekar, Pundlik

Virtual Reality in Assembly Simulations: Outpacing Tecnomatix Process Simulate for Faster Time-to-Market

2026-26-03981/16/2026

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

Numerical study of a hydrogen ejector with regulated inlet for extended PEMFC operating range in automotive application

2026-26-02491/16/2026

Hydrogen recirculation is a key requirement for enhancing fuel efficiency and anode stability in Proton Exchange Membrane Fuel Cell (PEMFC) systems, particularly in automotive applications. Effective hydrogen recirculation is critical for maintaining high efficiency and fuel utilization. A hydrogen recirculation ejector equipped with a regulated pressure inlet, aimed at eliminating the need for mechanical pumps while maintaining optimal hydrogen utilization. The passive operation of the ejector eliminating the need for rotary components which significantly improves system reliability and reduces failure modes commonly associated with moving parts. This work presents a numerical investigation of a hydrogen recirculation ejector featuring a regulated pressure inlet, with the objective of extending its operating range across varying fuel cell power levels. A combination of 1D system-level modelling and 2D multi-species Computational Fluid Dynamics (CFD) simulations was employed to

Khot, Ranjit Uttreshwar, T P, Muhammad, Chougule, Abhijeet

Integrated Simulation of Electric Vehicle Model Using the ROM Approach

2026-26-03691/16/2026

The growing demand for Electric Vehicles (EVs) has highlighted the importance of efficient and accurate simulation tools for design and performance optimization. The architecture of electric vehicles is distinct from that of internal combustion engine vehicles. It consists of on-board charger, DC-DC converter, Lithium ion battery pack, Inverter, electric motor, controllers and transmission. The battery pack supplies electric current to the traction motor, which then converts this electrical energy into mechanical energy, resulting in the rotational motion needed to drive the vehicle. Wide range of Multiphysics is involved in the simulation which involves Power electronics, Electromagnetics, Fluid Mechanics, Thermal engineering. This paper presents an integrated simulation and range prediction methodology for Electric Vehicles (EVs) using the Reduced Order Model (ROM) approach. The methodology includes simulation in both 3D and 1D domain. Computational fluid dynamics (CFD) simulation is

Shandilya, Anand, Kumar, Vivek

Design & analysis of Dual Mass flywheel during Engine startup condition in 3 Cylinder Gasoline application

2026-26-03491/16/2026

Modern automotive powertrains are increasingly adopting engine downsizing and down speeding to meet stringent emission regulations and improving fuel efficiency However, these changes result in higher torsional vibrations and excitation amplitudes makes more challenge in NVH (Noise, Vibration, and Harshness) refinement. With growing customer expectations for premium driving experiences conventional clutch are no longer sufficient. To meet the NVH performance targets of the vehicle Dual Mass Flywheels (DMFs) are used In DMF due to lower stiffness and inertia separation there is a great advantage on torsional filtration in normal drive and idle condition. but the resonance frequency of the connected DMF is lower than the idle RPM. Engine startup is a key drawback with DMF equipped vehicles. The proper tuning of starter motor performance & DMF stiffness is required to cross the resonance zone faster otherwise it will lead to DMF to stay in the resonance zone for a longer time leading to

Jayachandran, Suresh kumar, Vijayaragavan, Thirupathi, M, DEVAMANALAN, Kanagaraj, Pothiraj, ahire, Manoj, Vellandi, Vikraman

Review on the flyback converter design for multi-output

2026-26-02001/16/2026

With the increasing demand for DC loads, DC-DC converters have become indispensable in modern power electronic architectures. With high-voltage applications typical DC-DC converter topologies are required which include isolation for safety and voltage level conversion. Among various isolated converter topologies, the flyback converter is widely favored for low-power applications, typically under 100 W, due to its simplicity and cost-effectiveness. Like other DC-DC topologies, the flyback converter can operate in either continuous conduction mode or discontinuous conduction mode (DCM). The work have focused on the design and performance analysis of a flyback converter operating in DCM, with a specific emphasis on magnetic component design and loss evaluation. A 55 W multi-winding flyback converter employing a passive snubber circuit is studied and implemented. The loss analysis is done with switch losses around 3.4W and the coupled inductor core losses around 1.5W and copper losses

S, Denis, Deshpande, Prathamesh Pravin, Deshpande, Rohan

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