Browse Topic: Electrical, Electronics, and Avionics

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ALTERNATE CATALYST FOR DOC IN A CATALYTIC CONVERTER2026-28-0016To be published on 02/12/2026
Emission norms have become much more stringent to reduce emissions from vehicles. Diesel engines in particular are the predominant contributors to higher emissions. Diesel Oxidation Catalyst (DOC) in diesel engine catalytic converter systems is the crucial component in reducing harmful emissions such as Carbon Monoxide (CO) and unburnt Hydrocarbons (HC). DOCs often rely on expensive noble metals like platinum or palladium and rhodium as catalyst materials,significantly inflating the cost of emission control units. The proposed idea is to explore MnOxCeO₂ (Manganese Oxide-Cerium Oxide) as an alternative catalyst to traditional DOC materials, with the goal of delivering effective oxidation performance while reducing overall system cost. MnOx-CeO₂ catalysts are promising due to their good low-temperature activity, oxygen storage capacity, and redox behaviour, which are beneficial for diesel engines operating under varied conditions. These properties help improve the oxidation of CO and HC
C, Jegadheesan, T, Karthi, Rajendran, Pawan, Muruganantham, Kowshiik, S, Vaitheeshwaran
ACCIDENTAL DOORING WARNING AND ASSIST SYSTEM2026-28-0053To be published on 02/12/2026
The term dooring refers to the accidents where a vehicle door is suddenly opened into the path of an oncoming cyclist or motorcyclist. These issues are serious road safety hazards, especially in congested urban areas where people may be careless. This project proposes an intelligent, computer vision based warning system designed to detect the approaching vehicles and alert the occupants in the vehicle before opening the door. The system uses the rear parking camera in vehicles with rear parking system or a USB webcam in vehicles without rear parking system to capture live video feed, which is processed by a Raspberry Pi 4 microprocessor. The system will run a lightweight deep learning model, MobileNetSSD, through TensorFlow Lite. Detected objects are classified in real time, and the relative distance of other vehicles is estimated using bounding box dimensions. If a vehicle is identified within a preset safety distance threshold, a clear visual warning is displayed to prevent door
C, Jegadheesan, T, Karthi, Gurusamy, Varun Sankar, Balraj, Tharun, Murugaiya, Tamilselvan
Modelling and Analysis of Complex Shaped Cracks2026-28-0048To be published on 02/12/2026
This study offers a thorough analysis using finite element methods (FEA) to examine how fatigue cracks grow in three different materials: Structural steel , Titanium alloy (Ti Grade 2), and epoxy/aramid-based printed circuit board (PCB) laminates. Using ANSYS Workbench, we ran simulations under both static and repeated loading to understand how these materials fracture. The approach was based on Linear Elastic Fracture Mechanics (LEFM), employing the Maximum Circumferential Stress Criterion to predict where cracks might start and how they could spread. Also, the Equivalent Domain Integral (EDI) method helped us calculate the Stress Intensity Factors (SIFs) when cracks are under mixed loading modes. We modeled the growth of fatigue cracks using the Paris Law, relying on material-specific constants (C and m) drawn from previous studies and experimental tests. For example, titanium Grade 2 showed Paris Law constants with C values between 1.8 × 10⁻¹⁰ and 7.9 × 10⁻¹² m/cycle, and m values
T, Lokesh, Bhaskara Rao, Lokavarapu
IoT-Enabled Cloud-Integrated Smart Parking System with Real-Time Monitoring and AI-Based Space Optimization for Next-Gen Mobility2026-28-0113To be published on 02/12/2026
This study presents the design and implementation of an advanced IoT-enabled, cloud-integrated smart parking system, engineered to address the critical challenges of urban parking management and next-generation mobility. The proposed architecture utilizes a distributed network of ultrasonic and infrared occupancy sensors, each interfaced with a NodeMCU ESP8266 microcontroller, to enable precise, real-time monitoring of individual parking spaces. Sensor data is transmitted via secure MQTT protocol to a centralized cloud platform (AWS IoT Core), where it is aggregated, timestamped, and stored in a NoSQL database for scalable, low-latency access. A key innovation of this system is the integration of artificial intelligence (AI)-based space optimization algorithms, leveraging historical occupancy patterns and predictive analytics (using LSTM neural networks) to dynamically allocate parking spaces and forecast demand. The cloud platform exposes RESTful APIs, facilitating seamless
Deepan Kumar, Sadhasivam, S, Balakrishnan, Dhayaneethi, Sivaji, Boobalan, Saravanan, Abdul Rahim, Mohamed Arshad, S, Manikandan, R, Jamuna, L, Rishi Kannan
Reduction of Inductive Losses in Electric Vehicle Wireless Charging through Resonant Coupling2026-28-0123To be published on 02/12/2026
The growing awareness about sustainability and environmental concerns are accelerating the adoption of electric vehicles. They play a promising role due to their potential to significantly reduce greenhouse gas emissions, improve air quality and lessen reliance on fossil fuels. However, one of the primary concerns for potential buyers is the charging process and infrastructure. Traditional wired charging systems for electric vehicles face limitations such as user inconvenience, wear and tear of connectors and challenges in automation. As a solution, wireless electric vehicle charging has emerged, offering a more user-friendly, automated and contactless method of charging by eliminating the need for physical connectors. Wireless charging can be implemented through various approaches, primarily including inductive and resonant methods. Inductive charging suffers from relatively low efficiency due to higher energy losses during transmission. On the other hand, resonant coupling
Shaik, Amjad, Gudipati, Ravi Sai Hemanth, B, Vikranth Reddy, Anudeep, D B S S, Varshith, Dasari
AI Smart Timer-Based Power Control and Energy Monitoring System for Home Appliances2026-28-0060To be published on 02/12/2026
This paper presents an intelligent home automation system that combines timer-based power control, real-time energy monitoring, and cloud-based AI analytics for individual appliances. The system is built using a Wi-Fi-enabled embedded controller connected to sensing circuits that measure voltage, current, and power consumption. Electromechanical relays are used to control appliance power based on user-defined timers. Users can configure either a fixed runtime or a scheduled cutoff, enabling automated energy-saving without manual input. Alongside local control, the system collects energy consumption data and transmits it to a cloud platform for storage and analysis. A dedicated mobile or web app provides live monitoring, device status, and remote control access. A major innovation is the integration of a cloud-based AI engine that processes historical and real-time data to offer predictive insights. The AI module forecasts energy use, detects anomalies, classifies appliances by behavior
D, Anitha, D, Suchitra, Jain, Utsav, MAITY, SOUVIK, Dinda, Atish
Automotive Ethernet Proxy-Based Security Architecture In Vehicle Computers2026-28-0121To be published on 02/12/2026
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for IP-based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update channels. This strategy
M, Arvind, Praneetha, Appana Durga, Remalli, Ravi Teja
Decentralized Payment Infrastructure for Electric Vehicle Charging via Blockchain and Smart Contracts2026-28-0126To be published on 02/12/2026
As electric vehicles adoption becomes more common, power grid operators are facing new challenges in managing the unpredictable and varying energy demands in the existing electrical infrastructure. Moreover, the cost of Electric vehicle is high when compared to fuel vehicle also it has limited access to charging infrastructure along with the driving range that act as a key barrier preventing the drivers from making shift to EVs. When the EV usage integrates with blockchain, it mitigates the limitation in charging station infrastructure along with the former problem discussed. The lack of trust exists between EV owners and charging station providers can be solved through secure and transparent payment processing possible by blockchain based smart contract. Building charging station on blockchain will ease the automated payment through the use of smart contract and create more efficient EV charging network. Also, the blockchain-based charging system would enable EV owners know if they
Govindasamy, Dhivya, R, Rajarajeswari
MINER’S SAFETY BOT2026-28-0116To be published on 02/12/2026
Mining remains one of the most hazardous industries, with workers constantly exposed to life-threatening conditions such as toxic gases, high temperatures, and confined spaces. To address these concerns, we propose the design and development of an autonomous Miner’s Safety Bot aimed at enhancing underground safety through real-time environmental monitoring and intelligent navigation. The system is built around the ESP32 microcontroller, integrating critical sensors including the MQ7 gas sensor for detecting carbon monoxide and methane, the DHT11 sensor for measuring ambient temperature, and an ultrasonic sensor for obstacle detection. These components work to monitor hazardous parameters and assist the bot in navigating through narrow mine shafts. A servo motor connected to a remote-controlled chassis adjusts the bot's direction when obstacles are detected. The bot employs the ESP32-CAM module to transmit live visuals from the mining site to external observers. Furthermore, sensor data
D, SUCHITRA, D, ANITHA, MUTHUKUMARAN, BALASUBRAMANIAM, MOHANRAJ, SIDDHARTH, SUBASH CHANDRA BOSE, ROHAN
Common Mode Voltage Reduction in Quasi-Z Source Inverter for Electric Vehicle Applications Using MBPWM Technique2026-28-0102To be published on 02/12/2026
Unlike traditional voltage source or current source inverters, ZSI/qZSI can boost and invert DC power in a single stage, making them attractive for applications like EVs where battery voltage may vary. Common mode Voltage (CMV) is the voltage between the neutral point of the motor and ground. High CMV in motor drive systems can cause: Higher leakage currents, Electromagnetic interference (EMI), Insulation stress, bearing currents, leading to premature motor failure. Reducing CMV is essential for reliable and safe EV operation. Pulse-width modulation (PWM) is used to control the QZSI output voltage. The QZSI offers several advantages over traditional inverters, including improved efficiency, reduced cost, and increased reliability. The proposed system is designed to reduce the CMV through a combination of passive LC filtering and shoot-through (ST) modulation techniques. The LC filter is designed to attenuate high-frequency components of the CMV while the ST modulation is used to
N, Kalaiarasi, R, Rajarajeswari, D, Anitha
Artificial Intelligence and Cloud Synergy for Scalable Battery Management Systems2026-28-0119To be published on 02/12/2026
Due to a rapid transformation of EV and the battery storage system, the battery management system (BMS) is essential to ensure an optimal performance of the piles of Battery storage. A BMS monitors and controls parameters such as voltage, current and temperature. A traditional BMS has a minimum support of analytics and its limited to local processing. But when the battery information’s are uploaded to the internet, it's easier to manage maintenance and track battery’s performance from anywhere in the world. This IoT /Cloud based system easy and made earlier thereby giving a system alarm before the issue turns big. Management of a lot number of batteries at once saves a lot of money at places like EV charging station and Energy Storage System (BESS). Software updates to the system can also be sent remotely. Also, a BMS connected to cloud can also be used to support weaker grids in an instant if it needs the reactive power support. Cloud integration of BMS with the grid network will help
R, Rajarajeswari, N, Kalaiarasi, Francis, Elgin Calister
Performance Evaluation of a Novel Coolant Channel Configuration for Liquid-Based Battery Thermal Management in Electric Vehicles2026-28-0042To be published on 02/12/2026
The performance and longevity of lithium-ion (Li-ion) batteries in electric vehicles (EVs) are critically dependent on effective thermal management. As internal heat generation during charge and discharge cycles can lead to uneven temperature distribution, exceeding optimal operating limits (25 - 40°C) can significantly degrade battery performance and lifespan. This study presents a performance evaluation of a novel liquid-based Battery Thermal Management System (BTMS) featuring a dual-directional coolant channel configuration designed to enhance thermal uniformity and heat dissipation. The proposed configuration combines horizontal and vertical coolant passages in an indirect cooling layout to address the limitations of conventional serpentine-type channels. A comprehensive thermal analysis was carried out under realistic loading conditions using three coolant types: water, ethylene glycol-based G48, and graphene-enhanced water nanofluids. These were evaluated for thermal conductivity
Selvan, Arul Mozhi, Periyasamy, Muthukumar, R, Thiruppathi, Prasad S, Hari, Raghav, R, Boddu, Sriram Pydi Aditya
Dynamic Stiffness Prediction in Cracked Cantilever Beams Using Enhanced ANN Techniques2026-28-0050To be published on 02/12/2026
This research paper presents an in-depth investigation into the application of Artificial Neural Networks (ANN) for predicting the dynamic stiffness characteristics of cantilever beams affected by cracks of varying depths and positions. Structural failure due to vibration remains a critical concern, and this study focuses on how crack-induced changes in modal stiffness compromise structural reliability. A significant research gap identified in previous studies is the limited consideration of crack location; this work addresses that gap by analyzing how both crack depth and position influence the natural frequency of the beam. Using modal analysis on cantilever beams with identical dimensions but different crack configurations, it was observed that deeper cracks and cracks near the fixed support led to a marked reduction in natural frequency, making the structure more vulnerable to resonance. Cracks located at the free end, however, showed negligible impact. To model and predict these
SB, Harshini, Rajkumar, Manjari, R, Krithika, K, Anusha, K, Divya, Bhaskara Rao, Lokavarapu
Achieving Reliability, Safety & Security in SDV OS Architecture2026-28-0122To be published on 02/12/2026
Software-Defined Vehicles (SDVs) are vehicles in which functionality and features are primarily governed by software, allowing for continuous updates, upgrades, and the introduction of new capabilities throughout the vehicle’s lifecycle. This transition from hardware-centric to software-driven architectures marks a significant shift in the automotive industry, transforming development processes, operational strategies, and business models. The SDV Operating System (SDV OS) is purpose-built for software-defined vehicles, serving as the foundational platform for managing vehicle software and enabling advanced functionalities. Unlike traditional embedded or general-purpose operating systems, SDV OS is tailored to meet the unique requirements of modern automotive architectures. Ensuring reliability, safety, and security is paramount in software-defined vehicles (SDVs), where even minor software faults can lead to serious consequences. The operating system (OS) plays a central role in
KHAN, Misbah Ullah, Gupta, Vishal
Virtual Development Kit (VDK) for Software Defined Vehicle2026-28-0120To be published on 02/12/2026
This paper explores the technological and architectural shifts essential for the advancement of Software-Defined Vehicles (SDVs), with an emphasis on decoupling hardware from software. It highlights the constraints of traditional development models and proposes modern architectural approaches, including MPU-based designs and virtualization techniques. Furthermore, it presents strategic pathways to cultivate an open and adaptable development ecosystem, empowering software engineers to experiment, innovate, and drive SDV evolution. These efforts aim to accelerate time-to-market and deliver a superior development experience across the SDV lifecycle. The idea is to develop a Virtual Development Kit (VDK) that enables the design, validation, and scaling of Software-Defined Vehicles (SDVs) even before the physical hardware is available. This comprehensive suite will include hardware platform emulators, operating systems, software stacks, and middleware tailored for high-performance computing
KHAN, Misbah Ullah, Gupta, Vishal
Numerical Study of Battery Pack Cooling for Electric Vehicles2026-28-0110To be published on 02/12/2026
Auto manufacturers are increasingly adopting lithium-ion batteries in response to the rapid evolution of electric vehicle technology. These batteries are being integrated into existing vehicles and planned as the primary power source for new models. Many lithium-ion batteries employ air cooling for safety reasons, due to convenience and cost-effective. This study investigates the cooling efficiency of electric vehicle battery packs using a U-shaped domain with various air-inlet sizes and velocities. Results indicate that air intake position and velocity significantly impact the ability to cool the battery pack. Shifting the air intake point from 30 mm to 20 mm lowers the highest temperature by 3.46 K. Increased air velocity causes a ripple-around effect, reducing the temperature in the second part of the battery pack. Balancing these variables can optimize air circulation and enhance convective heat transfer, potentially improving cooling effectiveness. These insights are valuable for
PC, Murugan, J, Sivasankar, W, Beno Wincy, G, Arun Prasad
Preliminary Design and Analysis of Dual Throat Fluidic Thrust Vectoring Nozzle for Supersonic Aerospace Application2026-28-0106To be published on 02/12/2026
The project investigates the performance characteristics of dual-throat nozzle used for fluidic thrust vectoring (FTV) in supersonic aircraft applications, offering a potential alternative to mechanical vectoring methods. Fluidic thrust vectoring provides benefits such as reduced weight, lower radar signature, and improved manoeuvrability and control. Computational methods are used to study the effects of geometric and operational parameters, including nozzle pressure ratios and secondary injection rate and injection angle, on thrust-vectoring efficiency and system dynamics. The study aims to develop optimized design configurations and validate using computational models.
Suresh, Vignesh, M, Akash, SENTHILKUMAR, NIKIL, Sundararaj, Senthilkumar, A, Garry Kiristen, Singh, Swaraj
TOPSIS-Based Multi-Criteria Optimization of WAAM Parameters for Automotive Component Fabrication2026-28-0026To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) can make huge, complicated metal parts quickly and cheaply, making it popular in the automobile sector. This study uses TOPSIS, a multi-criteria decision-making method, to improve WAAM process parameters such wire feed rate, travel speed, and current. Automotive applications need surface roughness, deposition rate, and dimensional precision, which WAAM-fabricated components must meet. TOPSIS normalizes and ranks experimental findings to find parameter combinations that perform best across many quality metrics. The results show that integrated optimization improves component quality and consistency, making WAAM a feasible and economical sustainable vehicle manufacturing option.
Pasupuleti, Thejasree
Parameter Optimization for Improved Surface Finish in WAAM-Fabricated Steel Structures2026-28-0023To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is a cost-effective and scalable metal additive manufacturing technique widely used for fabricating large metallic components. However, surface finish remains a critical challenge, especially for structural applications where post-processing needs to be minimized. This study focuses on optimizing key process parameters to improve the surface finish of ER70S-6 steel structures fabricated using the WAAM process. Experiments were designed using a statistical approach to systematically vary parameters such as wire feed rate, travel speed, voltage, and inter-pass cooling time. Surface roughness was measured using standard metrology tools, and the results were analyzed to identify the most influential parameters. An optimized parameter set was proposed based on the experimental outcomes, leading to a significant reduction in surface roughness without compromising the structural integrity of the deposited material. The findings contribute to enhancing
PN, Vani
Experimental Investigation of Process Parameter Effects in WAAM of Nickel-Based Alloys2026-28-0027To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is an evolving discipline in metal additive manufacturing characterized by rapid deposition, cost-effectiveness, and centrality to the near-net-shape fabrication of large-scale components. This study will concentrate on WAAM application to deposit nickel alloys, which find extensive use in aerospace, power generation, and marine industries, due to their good mechanical strength, corrosion resistance, and thermal stability. However, some drawbacks in WAAM processing of nickel alloys include thermal distortion, porosity, and residual stress. The research looks at how key WAAM process parameters, including wire feed rate, travel speed, current, and interpass temperature affect geometric accuracy, surface integrity, and mechanical performance of the fabricated components. Microstructural characterization was done using optical microscopy, and hardness distribution was measured as an indication of mechanical uniformity throughout the builds. It is
Natarajan, Manikandan
STEERING AUTOMATION FOR LANE KEEP ASSISTANCE2026-28-0117To be published on 02/12/2026
The design of advanced driver-assistance systems (ADAS) is essential to improve the safety and autonomy of vehicles in harsh conditions. This work introduces the design and development of a steering automation system for Lane Keep Assistance (LKA) in a vehicle with a parallel steering system. The system utilizes an ArduCam module to take real-time images of the ground in front, and these are processed via machine learning techniques on a Raspberry Pi in order to identify lane edges with great precision. The corrective steering maneuvers are carried out by a motorized steering actuator based on the visual data after processing, and an encoder that is built into the actuator constantly tracks the steering angle and position. This closed-loop feedback affords accurate, real-time corrections to ensure lane discipline without driver intervention. Extensive calculations for steering effort, torque, and gear design confirm the system's mechanical viability. Combining low-cost vision sensing
A R, Arundas, Sadique, Anwar
Real time implementation of predictive maintenance for service center automation using Automobile Life Extender (ALE) based on Machine Learning2026-28-0124To be published on 02/12/2026
Automobile Life Extender (ALE) consists of an on-board function, machine learning model operating via cloud computing and a smart phone app. The on-board function will receive signals like engine rpm, throttle position, Brake pedal position, hydraulic pressure etc from vehicles Ecu’s. Based on this data onboard ALE module will calculate the engine load, brake circuit load etc . and sends it to the predictive maintenance model via on board IoT system. The predictive maintenance model will have historical data about the type of engine, brake system and their performance curve data acquired based on test done by its OEM. Here machine learning models play a crucial role in analyzing the vehicle data dynamically, identify drive patterns from it and predict the need for maintenance of a part or a system. A hybrid approach of training models based on Supervised and Unsupervised is incorporated, which will work with certain amount of labeled data along with a set of collected unlabeled data
sundaram, Rameshselvakumar, Kumar, Lokesh, Saint Peter Thomas, Edwin, Sureshkumar, Srihari, Muthukumaran, Chockalingam, Menon, Abhijith
Effect of Minimum Quantity Lubrication during Machining of Incoloy 800H Using Vegetable Oil Enriched With Nano Particles2026-28-0038To be published on 02/12/2026
In this experimental work an effort has made to investigate the machining of difficult to machine Incoloy 800H super alloy. Cryogenically treated textured cutting inserts and vegetable oil enriched with nano particles were used for this study. The turning experiments were performed with different parameters such as Cutting speed, feed rate and depth of cut. Surface Roughness, Cutting Force, Tool-Tip Temperature and Power were the output responses considered. Grey Relational Analysis (GRA) and Analysis of Variance (ANOVA) analysis were used to optimize the machining parameters and to find the most influencing machining parameter on the output responses. The results showed that the optimal machining conditions considered were cutting speed at 35 m/min, feed rate at 0.06 mm/rev and depth of cut at 0.5 mm for the multiple-characteristic performances and it was improved by 3.86 % with this approached method. Also, Tool-tip temperature and Power were reduced during machining with cryo
Natarajan, Manikandan
Dual use of Electric Vehicle infrastructure for Enhancing Grid Resilience and Urban Sustainability2026-28-0114To be published on 02/12/2026
The rapid global adoption of Electric Vehicles (EVs) has led to a surge in the deployment of EV charging stations. Beyond their primary role of vehicle charging, these stations hold potential as dynamic, grid-connected assets for sustainable cities and communities (SDG 11). When integrated with renewable energy sources such as wind or solar, EV charging stations can function as decentralized power units, supplying energy to the grid during times of need. This dual functionality allows them to act as flexible loads that mitigate voltage fluctuations during grid faults, facilitating access to reliable energy (SDG 7). Utilizing existing EV infrastructure in this way reduces the need for additional grid-support devices and supports resource efficiency (SDG 13) promoting a low-carbon energy transition. However, their ability to support the grid is limited when fully committed to meeting charging demands, especially during grid faults. To address this challenge, a novel coordinated operation
R, Uthra, Rangarajan, Ravi, D, Suchitra, D, Anitha
Enhanced Solar Desalination Using Natural Dolomite-Integrated PCM and MWCN Thermal Storage: An Experimental Study2026-28-0082To be published on 02/12/2026
Systems for solar desalination provide a practical and environmentally friendly way to turn salty or polluted water into drinkable water. Three configurations are experimentally investigated in this study: a traditional solar desalination system, a system integrated with a thermal energy storage unit (TESU) based on phase change material (PCM), Multi wall Carbon nano particle were mixed with PCM at 1% of total volume of the PCM and a system that incorporates powdered natural dolomite into the PCM-based TESU. Each of the four configurations was created, tested simultaneously, and thoroughly examined. In comparison to the traditional system, the experimental findings showed that the adoption of PCM-based TESUs increased daily cumulative water output by 11.41%, 14.8% with addition of MWCNT and the addition of dolomite powder further increased productivity by 18.60%. Furthermore, the energy efficiency increased by16.1% with PCM, PCM with MWCNT is increased by 17.43% and 18.18% with the
R L, Krupakaran, Petla, Ratnakamala, Anchupogu, Praveen, P, Umamaheswarrao, SATYA MEHER, R, Dunna PhD, Vijay
Computational study on dynamic handling performance of a retro-fitted Electric Two wheeler using 125cc powered ICE reference2026-28-0047To be published on 02/12/2026
With the development in motor technology and battery manufacturing technologies, the scope for a budget working EV has been increasing in India. There remains an after-mark potential for conversion of an ICE powered two-wheeler to an EV power train. Such a move reduces the carbon footprint from the vehicle drastically and is still being explored. This study investigates the effect of replacing the ICE with an electric motor in a 125cc motorcycle, with a particular focus on vehicle handling performance using Slalom test. The two wheelers were modelled using calculated mass properties and estimated / calculated moments of inertia using CAD for both ICE and electric powertrains. The electric propulsion system took into consideration the role of a battery pack in the mass and MI calculation. The framework with degrees of freedom is well established in BIKESIMTM simulation environment. A slalom test with automatic gear shift and throttle to maintain speed of the vehicle was set-up to
Sankarasubramanian, Hariharan, M, Shaghasra, V, Ramprathap
Life Cycle Assessment for Sustainable EV Battery Recycling: A Technical Framework for EBRR.2026-28-0092To be published on 02/12/2026
This technical paper presents a comprehensive framework for implementing a Life Cycle Assessment (LCA) project at EV Batteries Recycling and Regulation (EBRR), focusing on lithium-ion batteries (LIBs) used in electric vehicles (EVs). It identifies key environmental hotspots across resource extraction, battery manufacturing, usage, and end-of-life (EoL) stages. The study evaluates recycling techniques—namely pyrometallurgy, hydrometallurgy, and cascade reuse—to quantify environmental benefits and emission reduction opportunities. The paper uses a cradle-to-grave system boundary with LCA - Ecoinvent datasets, applying ISO 14040/44 standards. Results show that manufacturing accounts for over 60% of life cycle emissions, primarily driven by energy intensity. Transitioning to renewable energy and adopting hydrometallurgical recycling can reduce Global Warming Potential (GWP) by up to 40%. Cascade reuse, when combined with hydrometallurgy, offers the best outcomes with GWP as low as 200 kg
Asokan, Gayathri, Raju cEng, Rajkumar, Dhananjaya, Chandan, Sattigeri cEng, Sudhir V
Development of Multiple level Auto Mode for Climate control in electric vehicles2026-28-0008To be published on 02/12/2026
Electric vehicles, or EVs, are significantly transforming the automotive industry as a cleaner and more environmentally friendly which finds an alternative solution for the vehicles propelled using internal combustion engines. As EV utilize the energy directly from the battery which causes customer or a user to be in panic state as charging infra is not developed well in most of the countries, thus improving vehicle efficiency and driving range requires optimizing energy consumption from battery of EVs. Apart from traction motor load for driving, major supplemental loads in electric car are climate control system, sometimes referred to as HVAC (Heating, Ventilation, and Air Conditioning). HVAC systems can consume a lot of battery power, especially during severe temperatures, which can drastically reduce the vehicle's range. Range anxiety continues to be an important barrier to the general adoption of EVs, the intelligent climate management systems which helps to reduce HVAC power usage
Mulamalla, Sarveshwar Reddy, SV, Master Eniyan, M, Nisshok, Anugu, Anil, E A, Muhammed, Guturu, Sravankumar
Galvanic Corrosion Susceptibility Analysis and Mitigation strategies in Automotive Battery Packs2026-28-0018To be published on 02/12/2026
As electric vehicles continue to revolutionize transportation, ensuring the reliability of their powertrain systems and battery packs has become a critical focus. One key challenge is galvanic corrosion, which occurs when dissimilar metals in contact are exposed to an electrolyte, such as seashore moisture or road salt used in snow or ice zones. This corrosion can weaken structural components, compromise electrical conductivity, and reduce the lifespan of critical systems. Common areas at risk include metallic joints within battery enclosures, busbars, cooling systems, and electrical connectors. Environmental factors such as high humidity and temperature fluctuations further amplify the issue, making it a pressing concern for manufacturers. This paper aims to systematically identify critical galvanic joints within electric powertrain systems and battery packs and provide effective strategies to mitigate corrosion risks. Preventative measures include choosing compatible materials with
NARAIN, ADITYA, Venugopal, Sivakumar, Gopalan, Vijaysankar, Varatharajan, Senthilkumaran
Quantum Meets Agile: Crypto-Agility for a Post-Quantum World2026-28-0127To be published on 02/12/2026
As the automotive industry transitions toward software-defined vehicles and connected ecosystems, cybersecurity becomes a critical design pillar. A pressing challenge emerges with the advent of quantum computing, which threatens to render existing cryptographic standards such as RSA and ECC obsolete. This paper addresses the need for quantum-resilient security architectures in the automotive domain by introducing a combined approach using Post-Quantum Cryptography (PQC) and crypto-agility. Unlike traditional static cryptographic systems, our approach leverages agile architectures that enable seamless integration of new cryptographic algorithms as they emerge. Central to our work is the role of Hardware Security Modules (HSMs), which provide secure, tamper-resistant environments for cryptographic operations within vehicles. We explore how HSMs can evolve into crypto-agile and quantum-safe platforms capable of supporting hybrid and post-quantum algorithms, allowing secure transitions
Kuntegowda, Jyothi
Effect of Sebastiana rostrata Fiber Loading on the Tribological Behaviour of Polycaprolactone Biocomposite.2026-28-0021To be published on 02/12/2026
This study investigates the tribological performance of Sesbania rostrata fibers (SRFs) reinforced polycaprolactone (PCL) composites, focusing on the effects of fiber loading under varying normal loads. Composite samples with fiber contents of 10%, 20%, and 30% were tested at sliding velocities of 0.5 m/s and a fixed sliding distance of 500 m. Results show that the inclusion of SRFs significantly reduces the coefficient of friction (COF) and specific wear rate (SWR) compared to neat PCL, particularly at fiber loadings up to 20%. Beyond this threshold, fiber agglomeration leads to increased wear. The results highlight the potential of SRF/PCL composites for use in wear-critical automotive and orthopedic applications due to improved load-bearing capability and surface resistance.
Raja, K., Senthil Kumar, M.S.
Multi-Storey AI Based Parking System2026-28-0129To be published on 02/12/2026
This paper presents a comprehensive design and implementation of an AI-based parking management system tailored to address the challenges of modern parking facilities. The system is designed to enhance efficiency, reduce manual intervention, and optimize operational costs while providing a seamless experience for drivers. The core architecture of the system integrates advanced technologies, including computer vision and IR sensors, thereby minimizing reliance on conventional sensors and streamlining the parking process. By leveraging computer vision, the system continuously monitors parking areas in real-time, accurately detecting vehicle occupancy status, and dynamically updating the availability of parking spaces. This real-time monitoring capability enables efficient space utilization, allowing for the optimization of parking resources. In addition to optimizing space allocation, the proposed system prioritizes security through the integration of video surveillance. Utilizing AI
N, Kalaiarasi, Gupta, Shivansh, Hajarnis, Mihir, anand, Vikas
A Nature-Inspired Optimization Approach for Vienna Rectifier Control in EV Fast Charging Applications: Performance Comparison with NPC and Swiss Topologies2026-28-0112To be published on 02/12/2026
The growing adoption of electric vehicles (EVs), particularly those utilizing High Voltage battery systems, demands fast-charging infrastructure that ensures high efficiency and power quality. This study proposes a Golden Jackal Optimization (GJO)-based control strategy for a Vienna rectifier used exclusively in a High Voltage EV fast-charging system. Unlike conventional systems that incorporate an additional DC-DC converter stage, the proposed architecture utilizes only the Vienna rectifier for AC-DC conversion, thereby reducing system complexity and improving overall reliability. The GJO algorithm, inspired by the cooperative hunting behavior of golden jackals, is employed to optimize the switching control parameters of the Vienna rectifier, enhancing system performance in terms of efficiency, power factor correction (PFC), and total harmonic distortion (THD). A detailed comparative analysis is performed between the Vienna rectifier, Swiss rectifier, and Neutral-Point Clamped (NPC
R, Mohammed Abdullah, N, Kalaiarasi
An Integrated Model Approach for Predicting Vehicle Dynamics Performance during HiL Validation2026-28-0044To be published on 02/12/2026
In the automotive industry, increasing noise regulations are influencing product sales and passenger comfort, creating a need for more effective noise testing methods. Hardware-in-Loop (HiL) based virtual acoustic testing serves as a critical step before Driver-in-Loop testing, allowing for the assessment of noise levels inside and outside the vehicle under various conditions before real-world testing is performed. This study addresses the conversion of a physical vehicle model in the AMESim environment into FMU-RT (Linux) format, and the translation of a powertrain control system from Simulink to C++ code. Key challenges in the FMU-RT conversion include the integration of appropriate submodels for each component and enabling the interfaces necessary for SCANeR and virtual acoustic testing. In the C++ code conversion, challenges involved configuring the correct parameters, ensuring the model runs at a fixed time step and sampling time of 1 ms, and resolving issues related to the
Visuvamithiran, Rishikesan, Chougule, Sourabh, Srinivasan, Rangarajan, Laurent, Nicolas
Evolution of a Novel Hybrid Stab-Link for a Born Electric Sports Utility Vehicle2026-28-0001To be published on 02/12/2026
The present study details the design evolution and failure analysis of a novel hybrid stabilizer bar link (stab link) developed for the front suspension of a born electric sports utility vehicle (SUV) platform characterized by higher gross vehicle weight (GVW), increased wheel travel, and constrained packaging space. To address these challenges, a unique hybrid stab link was designed featuring dual plastic housings at both the metal ball joint ends, connected by a steel tube, and achieving a 30% weight reduction while offering enhanced articulation angles for extremely lower turning circle diameter (TCD) of the vehicle, compared to the conventional stab link. The unique hybrid stab failed under complex loading conditions during accelerated durability testing (ADT), prompting a comprehensive investigation. The failure analysis included road load data acquisition across various stab bar diameter configurations evolved during suspension tuning, different stabilizer link designs evolved
SELVENDIRAN, P, J, Ramkumar, NAYAK, Bhargav, M, Sudhan, Patnala, Avinash
Multi-Objective Optimization of WAAM for Sustainable Production of Automotive-Grade Components2026-28-0030To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) has emerged as a promising technology for fabricating large-scale metal components with reduced material waste and lead time, aligning with the goals of sustainable manufacturing. This study presents a multi-objective optimization approach for WAAM to enhance both the manufacturing efficiency and sustainability of automotive-grade components. Key process parameters such as travel speed, wire feed rate, and current were systematically varied to evaluate their impact on dimensional accuracy, mechanical performance, and energy consumption. A statistical design of experiments framework was employed, and multiple performance objectives were optimized simultaneously using suitable decision-making techniques. The results demonstrate that optimized WAAM settings not only meet structural and functional requirements for automotive applications but also contribute to material and energy savings. This approach supports the integration of sustainability into
Pasupuleti, Thejasree
Statistical Optimization of Wire Arc Additive Manufacturing Parameters Using Taguchi Methodology2026-28-0035To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is an emerging metal additive manufacturing process known for its high deposition rates and cost-effectiveness in fabricating large-scale components. However, the quality of the final build is highly sensitive to process parameters such as wire feed rate, travel speed, voltage, and current. In this study, the Taguchi method is employed to statistically optimize key WAAM process parameters with the aim of improving surface finish and mechanical integrity of the deposited parts. An L9 orthogonal array was used to design experiments, and signal-to-noise (S/N) ratios were analyzed to identify optimal parameter settings. Analysis of variance (ANOVA) was performed to determine the significance of each factor on the selected output responses. The results demonstrated that specific combinations of process parameters can significantly reduce surface roughness and enhance bead geometry. The optimized settings obtained through the Taguchi approach provide a
PN, Vani
Parameter Selection Strategies for High-Performance WAAM Structures in Automotive Engineering2026-28-0033To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) has gained traction as an advanced fabrication technique for producing large, structurally demanding components in the automotive industry. Achieving high-performance WAAM structures requires precise control and selection of key process parameters, which directly influence mechanical strength, dimensional accuracy, and surface quality. This study investigates the effect of critical process variables—including wire feed rate, travel speed, current, voltage, and inter-layer cooling time—on the structural integrity of WAAM-fabricated components designed for automotive use. A systematic experimental approach, supported by statistical modeling and optimization tools, was employed to identify parameter combinations that yield optimal results. The outcomes demonstrate improved microstructural uniformity, reduced residual stresses, and enhanced tensile properties in the fabricated parts. The findings serve as a foundation for developing robust parameter
V, Aravind
Statistical Modeling of Wire Arc Additive Manufacturing Parameters Using Regression Analysis2026-28-0024To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is gaining prominence for fabricating large metal components due to its high deposition rate and cost-effectiveness. However, the quality and performance of WAAM-fabricated parts are strongly influenced by process parameters such as wire feed rate, travel speed, arc voltage, and current. This study presents a statistical modeling approach using regression analysis to predict the effects of these key parameters on critical output responses, including bead geometry, surface roughness, and material deposition rate. Experiments were designed using a structured methodology, and the collected data were analyzed to develop linear and multiple regression models. The accuracy and reliability of the models were evaluated using statistical metrics such as R² and p-values. The results demonstrate that regression-based models can effectively predict WAAM outcomes, enabling process optimization and quality control. This approach provides a valuable tool for
Pasupuleti, Thejasree
Enhancing Range Prediction Accuracy for the BEV: Bridging the Gap Between Simulation and Real-World Testing2026-26-0521To be published on 01/16/2026
Accurate range estimation in battery electric vehicles (BEVs) is essential for optimizing performance, energy efficiency, and customer expectations. This study investigates the discrepancies between physical test data and simulation predictions for the Jeep Wagoneer model. A detailed range delta analysis identifies key contributors to the observed deviations, including regenerative braking inefficiencies, increased propulsion demand, auxiliary loads, and estimated drivetrain losses within the Electric Drive Module (EDM) during traction and regen. Results indicate that the test vehicle exhibits lower regenerative braking efficiency and higher traction and lower regen consumption than predicted by simulations, primarily due to EDM inefficiencies and friction brake usage during regeneration. The study underscores the importance of refining simulation methodologies by integrating real-world, test based EDM loss maps to improve accuracy and better align predictive models with actual vehicle
Mahajan, Prasad, Kesarkar, Sidhesh, Ali, Shoaib
Swarm-Inspired Cooperative Mapping for Urban Autonomous Navigation2026-26-0635To be published on 01/16/2026
Urban autonomous vehicles today largely rely on individually built maps or centralized cloud services—both rigid under intermittent connectivity and rapid scene changes (construction, pop-up events). Inspired by how ant colonies collectively explore, we introduce a decentralized protocol: each vehicle broadcasts compressed “map particles” embedded with virtual pheromone values that highlight zones of high uncertainty or recent change. Neighboring vehicles incorporate these signals to prioritize sensing and route planning. A lightweight consensus algorithm merges local graphs into a shared dynamic map, resilient to network splits. The result, a bio-inspired SLAM that enables fleets to adapt on the fly to evolving cityscapes, boosting safety, efficiency, and robustness.
Bhargav, Anirudh S, Subbarao, Chitrashree
Real-time range optimization for selected destinations by Dynamic Energy Management Strategy (DEMS) in BEV’s2026-26-0168To be published on 01/16/2026
The automotive industry has undergone significant transformation with the adoption of electric vehicles (EVs). However, to tackle range anxiety, the focus has shifted to energy management strategies for optimal range under different driving conditions. Developing an optimal energy management algorithm is crucial for overcoming optimal range and gaining a competitive edge in the market. This paper introduces a Dynamic Energy Management Strategy (DEMS) for electric vehicles (EVs), designed to optimize battery usage and extend driving range. Utilizing vehicle digital twin model, DEMS estimates energy consumption across Eco, Normal, and Sports driving modes by analyzing vehicle velocity profiles and pedal inputs. By calculating actual battery consumption and pinpointing excess power usage, DEMS operates in a closed loop to periodically assess the power gap based on real-time vehicle conditions, including HV components like the Electric Drive system, DCDC, E-compressor and E-Heater; and
Dey, Supriyo, Venugopal, Karthick Babu, Penta, Amar, Kumar, Rohit, Arya, Harshita
Quantifying the Energy Consumption of HVAC Operation and Its Impact on the Range of Electric Buses Across Diverse Climatic Conditions2026-26-0204To be published on 01/16/2026
Electric buses (e-buses) are essential to sustainable public transport, but their real-world efficiency and range are heavily affected by auxiliary systems, particularly the Heating, Ventilation, and Air Conditioning (HVAC) system. This study investigates how ambient temperature variations and HVAC loads influence energy consumption, range, and efficiency in e-buses operating under diverse climatic conditions. The methodology combines field data collection from urban e-buses across seasons—including extreme summer and winter—with controlled lab testing. Field measurements included ambient temperature, HVAC demand, vehicle speed, state of charge (SOC) variation, and energy consumption. These inputs were used to develop real-world duty cycles, replicating actual thermal loads, passenger profiles, idling periods, and driving patterns. In the lab, these cycles were simulated using a chassis dynamometer and environmental chamber, with HVAC systems tested at controlled ambient temperatures
Vishe, Prashant, Dalela, Saurabh, Saraswat, Shubham, Joshi, Madhusudan
Electric Vehicle Battery’s Testing Challenges in era of Software Defined Vehicle2026-26-0159To be published on 01/16/2026
In era of Software Defined Vehicle (SDV), the whole ecosystem of automobile will be impacted. So, it is going to through several challenges for testing activities. In electric vehicle, most critical component is traction battery, which is controlled and operated through battery management system (BMS). BMS is an electronic system, where is going to function as per software of BMS. And in SDV, software is a key element, which is continuously keep on updating on regular basis. So, it means some of BMS functionalities, features or performance may be also altered on each time on software update, which may impact battery’s operating condition, if some scenario is not evaluated during earlier testing, then there are it may bring battery out of safe operating area, which may significantly impact battery safety, performance or cycle-life. In this paper, we are exploring that different testing requirements for EV Batteries, which may be part of testing practices under era of SDV. Here we will
Bhateshvar, Yogesh Krishan, Mulay, Abhijit B
Comprehensive Insights on Techniques for Managing and Preventing Thermal Runaway in EV Lithium-Ion Batteries.2026-26-0171To be published on 01/16/2026
This paper presents a comprehensive investigation into the mechanisms, risks, and mitigation strategies associated with thermal runaway in lithium-ion batteries used in electric vehicles (EVs). It begins by emphasizing the urgency of the issue, identifying key vulnerabilities within EV battery systems that contribute to runaway events. A multiscale, stage-wise breakdown of thermal runaway progression is provided, illustrating how physical, chemical, and thermal interactions compound during failure scenarios. The study analyzes global incident data from 2000 to 2025, revealing trends in human health impacts, vehicle damage, and public safety concerns. Particular attention is given to how battery aging, manufacturing defects, and external abuse conditions elevate the likelihood and severity of thermal runaway. Current emergency response protocols and state-of-the-art mitigation technologies are critically evaluated to identify best practices and existing gaps in safety management. A
Jain, Gaurav, Premlal, P, Pathak, Rahul, Gore, Pandurang
Early prediction of relaxation voltage & detection of state of battery for functional safety2026-26-0166To be published on 01/16/2026
During parking condition of vehicle, state of the battery is uncertain as it goes through the relaxation process. In such scenarios the battery voltage may exceed the functional safety limits. If we cross the functional safety limits it is hazardous to the driver as well as the occupant. In this case relaxed voltage plays a crucial role in identifying the safe state of the battery. To estimate the relaxed cell voltage there are methods such as RC filter time constat modeling and relaxation voltage error method. The problem with these solutions is the waiting time and accuracy to determine the relaxation voltage. In this manuscript a solution is proposed which ensures the above problem gets reduced. To achieve the reduction of relaxation voltage estimation time, a python sparse identification of nonlinear dynamics (PySindy) is used which identifies and fits an equation model based on observing the battery characteristics at different SOC and temperatures. The implementation is done and
Pandey, Priyanshu, Nilajkar, Ankur, Panda, Abinash
EV Battery Evolution in India: Challenges, Innovation, and Policy Synergy2026-26-0174To be published on 01/16/2026
In the pursuit of sustainable transportation and energy security, India is placing increased focus on addressing the multifaceted challenges associated with electric vehicle (EV) battery technology. As a cornerstone of EV performance and adoption, battery systems in India face critical issues such as high import dependency, limited local manufacturing capabilities, cost inefficiencies, safety concerns, and lack of standardized design frameworks. This paper presents a comprehensive analysis of India's evolving battery ecosystem, emphasizing indigenous design, development, and scalable in-house manufacturing under the "Make in India" initiative. It examines supportive government policies, strategic public-private partnerships, and the pivotal role of research institutions in fostering innovation and overcoming original equipment manufacturers' (OEMs) and end-users' concerns. It also focus on prototype product development challenges. Through detailed case studies, technological reviews
Thorat, Jalindar Sukhadev, Sandhu, Jivraj Singh, Kumar, Dharmendra
Developments in 2-Wheeler Electric Vehicle Architecture2026-26-0199To be published on 01/16/2026
Electric vehicles are becoming more popular due to the low-cost investment for individual daily usage, such as traveling to nearby places, offices, and schools. There are environmental benefits that make them green and produce less pollution compared to traditional vehicles. Two-wheeler electric vehicles (EVs) have more electronic components compared to two-wheeler internal combustion engine (ICE) vehicles. The major components in two-wheeler EVs are the motor and battery. The traction motor is driven by the battery, Battery is a primary energy source in 2Wheeler electric vehicle. An electric vehicle comprises different major electronic components such as the battery management system (BMS), motor control unit (MCU), human-machine interface (HMI), and, in some cases, a vehicle control unit (VCU) as well. Considering a 48V architecture or less than 60V provides advantages of low system cost as it requires less effort for safety measures. Furthermore, this paper explores diverse
Karunakar, Praveen, K R, Amogh
Performance Enhancement and Safety Discharge Control Strategies for SPMSM in Automotive Applications.2026-26-0179To be published on 01/16/2026
Surface Permanent Magnet Synchronous Motors (SPMSMs) have gained significant attention in modern industrial, automotive, and aerospace applications due to their high efficiency, power density, and superior dynamic performance. This paper explores the fundamental principles, control strategies, and optimization techniques for SPMSMs. The study focuses on advanced vector control methods, i.e., Field-Oriented Control (FOC), to achieve precise torque and speed regulation. Additionally, to ensure the safety and reliability of EV motors, Active discharge strategies are focused. The paper also discusses a comparison of Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM) techniques, where the maximum speed of the motor is achieved. The findings highlight the potential of SPMSMs in high-performance applications, emphasizing future research directions in energy-efficient and intelligent motor control systems.
Munnur, Swathi, Gandhi, Nikita, Tendulkar, Swati, Masand, Deepika, Murty, V. Shirish, Peruka, Mahesh
Intelligent Sequential Charging Control via Fleet-Managed Cloud System2026-26-0207To be published on 01/16/2026
Electric Vehicles (EV) are increasingly becoming more and more popular in the markets, especially in the commercial vehicle segments. Amidst this, the need to find new elegant methods to perform charging of EV battery becomes extremely crucial. In areas with high demand and limited power capacity, performing charging for multiple vehicles necessitates efficient usage of charging infrastructure, which can’t be guaranteed by the traditional charging methods. Sequential charging is a new state of art technique for managing the charging of multiple EV’s simultaneously connected to a single charging station. Rather than dividing the available power equally among all connected vehicles or charging them one at a time, this technique dynamically allocates power based on various factors such as charging priority, vehicle needs and available infrastructure capacity. Currently, sequential Charging can only be implemented by a particular set of chargers that are interconnected via backend and
De, Abir, Bhattacharya, Ullash, Parihar, Aakash
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