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This study focuses on the vibration analysis of hybrid composite laminated plates fabricated from E-glass Fiber and areca Fiber reinforced with epoxy resin. The hybrid laminates were prepared using the Vacuum Assisted Resin Transfer Moulding (VARTM) process with different stacking sequences and Fiber ratios, where brake lining powder was also incorporated as a filler in selected configurations to enhance mechanical and damping properties. The fabricated plates (280 × 280 mm) were subjected to experimental modal analysis using an impact hammer and accelerometer setup, with data acquisition carried out through DEWESoft software. Natural frequencies and damping ratios were determined under three boundary conditions (C- C-C-C, C-F-C-F, and C-F-F-F). The results revealed that Plate 1, with E-glass outer layers, areca reinforcement, and filler addition, exhibited the best vibration performance, achieving a maximum natural frequency of 332.8 Hz under C-C-C-C condition, while Plate 2 showed a
D R, RajkumarO, Vivin LeninR, SaktheevelR G, Ajay KrishnaNg, Bhavan
Internal combustion engines generate intense acoustic pulses during combustion, necessitating the use of exhaust mufflers to suppress noise emissions. With evolving regulations on permissible noise levels and the automotive industry's drive toward lightweight, high-performance vehicles, muffler designs must balance effective sound attenuation, minimal back pressure, and reduced mass. This study presents a comparative analysis of three muffler configurations serpentine, rectangular, and zigzag designed using Solid Works for a light commercial vehicle (LCV) diesel engine. The models were evaluated using computational fluid dynamics (CFD) simulations to assess their acoustic and flow performance. Each design incorporated internal baffle arrangements to enhance sound absorption while aiming to minimize back pressure. The serpentine model featured a perforated baffle layout that promoted multiple reflections and dissipated acoustic energy more efficiently. Simulation results indicated that
Deepan Kumar, SadhasivamPalaniselvam, Senthil KumarD, AshokkumarR, KrishnamoorthyMahendran, MPasupuleti, ThejasreeG, DhayanithiL, Boopalan
This study provides an extensive analysis through finite element analysis (FEA) on the effects of fatigue crack growth in three different materials: Structural steel, Titanium alloy (Ti Grade 2), and printed circuit board (PCB) laminates based on epoxy/aramid. A simulation of the materials was created using ANSYS Workbench with static and cyclic loading to examine how the materials were expected to fail. The method was based on LEFM and made use of the Maximum Circumferential Stress Criterion to predict where cracks would happen and how they would progress. Normalizing SIFs while a crack was under mixed loading conditions was achieved using the EDI method [84]. We used Paris Law to model fatigue crack growth using constants (C and m) for the materials from previous studies and/or tests. For example, in the case of titanium Grade 2, we found Paris Law constants with C values from 1.8 × 10-10 to 7.9 × 10-12 m/cycle and m values from 2.4 to 4.3, which illustrate differing effects of their
T, LokeshBhaskara Rao, Lokavarapu
This research paper provides a comprehensive study on how Artificial Neural Networks (ANNs) can be deployed to predict the stiffness characteristics of a cantilever beam with a crack of various depths and positions. The most destructive source of failure is considered to be vibration, so the major focus of this paper will be on how the cracks affect the modal stiffness. This study has various applications, such as airplane wings, bridges, stadiums, and arenas. A common research gap was noticed amongst the existing studies; the position of the cracks in the cantilever wasn’t considered, but this paper discusses how the location of cracks severely affects the dynamic behaviour of the cantilever. This study was done by carrying out modal analysis on a cantilever of the same dimensions with different crack configurations. Various crack dimensions and orientations were analysed to understand the effects of the crack on the dynamic behaviour of the cantilever. From the modal analysis results
SB, HarshiniRajkumar, ManjariR, KrithikaK, AnushaK, DivyaBhaskara Rao, Lokavarapu
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 Internet Protocol (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
M, ArvindPraneetha, Appana DurgaRemalli, Ravi Teja
Mining operations are important to industrial growth, but they expose the mining workers to risk including hazardous gases, elevated ambient temperatures, and dynamic structural instabilities within underground environments. Safety systems in the past, typically based on fixed sensor networks or manual patrols, fall short in accurate hazard detection amidst shifting mine conditions. The proposed project Miner's Safety Bot advanced this paradigm by leveraging an ESP 32 microcontroller as a mobile platform that integrates gas sensing, thermal monitoring, visual inspection and autonomous obstacle avoidance. The system incorporates MQ7 semiconductor gas sensor to monitor real time carbon monoxide (CO), offering detection range from 5 to 2000 ppm with accuracy of 5 ppm. Temperature and humidity are monitored through DHT11 digital sensor, calibrated to ensure reliability across the harsh microclimates in mines. Navigation and autonomous movement are enabled by Ultrasonic Sensor (HC-SR04
D, SuchitraD, AnithaMuthukumaran, BalasubramaniamMohanraj, SiddharthSubash Chandra Bose, Rohan
In commercial vehicles, Hydraulic Power Assisted Steering (HPAS) gear plays a crucial role in enhancing steering performance by providing hydraulic assistance. The HPAS gear comprises a Directional Control Valve (DCV) assembly, where the input shaft and recirculation units are integrated. The valve system which is known for the heart of the HPAS gear, operates under high-pressure conditions. In the DCV, the input shaft is equipped with bearings to support side loads exerted by the system, and a valve component is freely assembled to minimize friction caused by these side loads. The complexity of the floating valve design results in the less slot volume, leading to cavitation and vibrational noise. While this noise is typically suppressed in internal combustion (IC) engine-powered vehicles, its implementation in electric vehicles (EVs) has led to pronounced audible noise, dominating the system. Experimental vibration analysis of the steering gear reveals both low and high-frequency
Vijayenthran, PraveenAyyappan, RakshnaD, Senthil KumarN, Prabhakar
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 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 are
Govindasamy, DhivyaR, Rajarajeswari
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. A wireless electric vehicle charging offers more user-friendly, automated and contactless method by eliminating the need for physical connectors. However, wireless inductive charging suffers from relatively low efficiency due to higher energy losses. Whereas resonant coupling significantly improves efficiency by using electromagnetic resonance to transfer power more effectively over short distances. This paper mainly focuses on design and implementation
Shaik, AmjadGudipati, Ravi Sai HemanthB, Vikranth ReddyAnudeep, D B S SVarshith, Dasari
The paper presents the design and implementation of an AI-enabled smart timer-based power control and energy monitoring solution for household appliances. The proposed system integrates real-time sensing of electrical device parameters with cloud artificial intelligence for predictive analytics and automatic control. Continuous measurement of voltage, current and power consumption of the connected appliances are performed for analysis of the usage patterns. The appliance operation is completely automated by choosing between the best option which is the user-defined schedule or the load shifted schedule recommended by AI. The AI recommendation depends on peak demand of the day and the current load requirement thereby aiding approximate smoothening of daily load curve and improving load factor. The data collected is transmitted to the cloud for real-time and historical data collection, for prediction of consumption patterns, anomaly detection, and clustering appliances according to their
D, AnithaD, SuchitraJain, UtsavMaity, SouvikDinda, Atish
This study investigates the parameter optimization of a Rear Twist Beam (RTB) for an electric vehicle (EV) during the early stages of product development. Adapting an RTB design from an Internal Combustion Engine (ICE) vehicle platform presents several challenges, one of the challenges is accommodating increased rear vehicle load while minimizing cost, with maintaining existing rear hard points. To address this, we employed an experimental study for Computer-Aided Engineering (CAE) using the Taguchi DOE, which avoids costly physical durability tests. The key design parameters considered were the thickness and material grade of the RTB's components, specifically the cross beam, trailing arms, and reinforcements while preserving their original shapes. L8 Orthogonal array is constructed to design the experiment and identify the influence of the design parameters on durability performance, and the optimal combinations for maximizing durability are identified by using TOPSIS multi objective
Madaswamy, ArunachalamDhanraj, SudharsunGovindaraju, KarthikLokaiah, Srinivasan
All automotive vehicles with enclosed compartments must pass the shower test standard - IS 11865 (2006). One of the most severe and critical areas of water leakage is “water entry into HVAC (heating, ventilation, and air conditioning) opening”. Excess water flow at high-pressure conditions and seepage during long-time low-pressure conditions could potentially have a significant impact on water entry inside the HVAC suction cutout given on BIW (body in white) and subsequently into the cabin. The present study clearly indicates that for making leak proof HVAC opening (suction interface), it is crucial for the structure of BIW plenum, plenum applique, and its sealing components to be robust enough to effectively collect and divert the water during rainy seasons.
Gunasekaran, MohanrajNamani, PrasadRamaraj, RajasekarJunankar, AshishRaju, Kumar
In the context of electro-mobility for commercial vehicles, the failure analysis of a connector panel in a DCDC converter is crucial, particularly regarding crack initiation at the interface of busbar and plastic component. This analysis requires a thorough understanding of thermo-mechanical behavior under thermal cyclic loads, necessitating kinematic hardening material modeling to account for the Bauschinger effect. As low cycle fatigue (LCF) test data is not available for glass fiber reinforced polyamide based thermoplastic composite (PA66GF), we have adopted a novel approach of determining non-linear Chaboche Non-Linear Kinematic Hardening (NLK) model parameters from monotonic uniaxial temperature dependent tensile test data of PA66GF. In this proposed work a detailed discussion has been presented on manual calibration and Genetic Algorithm (GA) based optimization of Chaboche parameters. Due to lack of fiber orientation dependent test data for PA66GF, here von Mises yield criteria
Basu, ParichaySrinivasappa, Naveen
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, SadhasivamS, BalakrishnanDhayaneethi, SivajiBoobalan, SaravananAbdul Rahim, Mohamed ArshadS, ManikandanR, JamunaL, Rishi Kannan
Dooring accidents occur when a vehicle door is opened into the path of an approaching cyclist, motorcyclist, or other road user, often causing serious collisions and injuries. These incidents are a major road safety concern, particularly in densely populated urban areas where heavy traffic, narrow roads, and inattentive behavior increase the likelihood of such events. To address this challenge, this project presents an intelligent computer vision based warning system designed to detect approaching vehicles and alert occupants before they open a door. The system can operate using either the existing rear parking camera in a vehicle or a USB webcam in vehicles without such a feature. The captured live video stream is processed by a Raspberry Pi 4 microprocessor, chosen for its compact size, low power consumption, and ability to support machine learning frameworks. The video feed is analyzed in real time using MobileNetSSD, a lightweight deep learning object detection model optimized
C, JegadheesanT, KarthiGurusamy, Varun SankarBalraj, TharunMurugaiya, Tamilselvan
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, AdityaVenugopal, SivakumarGopalan, VijaysankarVaratharajan, Senthilkumaran
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
Selvan, Arul MozhiPeriyasamy, MuthukumarR, ThiruppathiPrasad S, HariRaghav, RBoddu, Sriram Pydi Aditya
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, palladium, and rhodium as catalyst materials. This significantly raises the cost of emission control units. The proposed idea is to explore MnO2-CeO₂ (Manganese Oxide, Cerium Oxide) as an alternative catalyst to traditional DOC materials. The goal is to deliver effective oxidation performance while reducing overall system cost. MnO2-CeO₂ catalysts are promising because of their good low-temperature activity, oxygen storage capacity, and redox behavior. These features are helpful for diesel engines that operate under various conditions. They improve the oxidation of CO and HC
C, JegadheesanT, KarthiRajendran, PawanMuruganantham, KowshiikS, Vaitheeshwaran
In commercial vehicles, conventional engine-driven hydraulic steering systems result in continuous energy consumption, contributing to parasitic losses and reduced overall powertrain efficiency. This study introduces an Electric Powered Hydraulic Steering (EPHS) system that decouples steering actuation from the engine and operates only on demand, thereby optimizing energy usage. Field trials conducted under loaded conditions demonstrated a 3–6% improvement in fuel economy, confirming the system’s effectiveness in real-world applications. A MATLAB-based simulation model was developed to replicate dynamic steering loads and vehicle operating conditions, with results closely aligning with field data, thereby validating the model’s predictive accuracy. The reduction in fuel consumption directly translates to lower CO₂ emissions, supporting regulatory compliance and sustainability goals, particularly in the context of tightening emission norms for commercial fleets. These findings position
T, Aravind Muthu SuthanMani, KishoreAyyappan, RakshnaD, Senthil KumarS, Mathankumar
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, KalaiarasiR, RajarajeswariD, Anitha
As there is a major shift in customer demand for energy efficient transportation, electric vehicle development has taken prominence worldwide as they provide pollution free and noise free mobility. The subframe being an important structural component of the chassis system, the designers always find it challenging to provide best-in-class rear subframe (RSF) optimized in terms of cost and weight within the available packaging space especially in an electric sport vehicular boundary. The main function of rear subframe is to transmit forces to BIW without deflections hence for this it should be very stiff. At the same time, it should be light in weight and simpler to industrialize. In the present work, the design evolution of a novel sub-frame assembly for a multilink rear suspension of a born electric sports utility vehicle (e-SUV) platform is detailed. With increased rear axle weight contributed by the battery weight and rear mounted motor, the design evolution of the rear subframe (RSF
Nidasosi, Basavraj MarutiJ, RamkumarNayak, BhargavMani, ArunM, Sudhan
Electric Vehicles (EVs) are rapidly transforming the automotive landscape, offering a cleaner and more sustainable alternative to internal combustion engine vehicles. As EV adoption grows, optimizing energy consumption becomes critical to enhancing vehicle efficiency and extending driving range. One of the most significant auxiliary loads in EVs is the climate control system, commonly referred to as HVAC (Heating, Ventilation, and Air Conditioning). HVAC systems can consume a substantial portion of the battery's energy—especially under extreme weather conditions—leading to a noticeable reduction in vehicle range. This energy demand poses a challenge for EV manufacturers and users alike, as range anxiety remains a key barrier to widespread EV acceptance. Consequently, developing intelligent climate control strategies is essential to minimize HVAC power consumption without compromising passenger comfort. These strategies may include predictive thermal management, cabin pre-conditioning
Mulamalla, Sarveshwar ReddySV, Master EniyanM, NisshokAnugu, AnilE A, MuhammedGuturu, Sravankumar
Due to the rapid transformation of EVs and the battery storage system, the battery management system (BMS) is essential to ensure optimal performance of the battery storage piles. A BMS monitors and controls parameters such as SOC, voltage, current, and temperature. A traditional BMS has a minimum support of analytics, and it’s limited to local processing. However, when the battery information is uploaded to the internet, it becomes easier to manage maintenance and track the battery’s performance from anywhere in the world. This Cloud-based system is easy and made earlier, thereby giving a system alarm before the issue becomes big. Managing many batteries at once saves a significant amount of money in places like EV charging stations and Energy Storage Systems (BESS). Software updates to the system can also be sent remotely. Also, a BMS connected to the cloud can be used to support weaker grids in an instant if it needs the reactive power support. Cloud integration of BMS with the grid
R, RajarajeswariN, KalaiarasiFrancis, Elgin Calister
This paper presents the design, development, and validation of an Advanced Rider Assistance System (ARAS) tailored for electric motorcycles, with a specific focus on a Level-1 collision-avoidance and emergency-braking prototype employing ultrasonic sensing. The study is motivated by the disproportionately high accident exposure of two-wheeler riders and the slow adoption of ARAS technologies relative to the well-established Advanced Driver Assistance Systems (ADAS) in passenger vehicles. The proposed system utilizes front and rear ultrasonic sensors operating at 40 kHz, offering a measurement range of 2 cm to 4 m with ±1% accuracy, and maintaining reliable performance at motorcycle lean angles of up to 30°. Sensor data are processed using an STM32-series microcontroller running a real-time collision-risk estimation algorithm based on obstacle distance and relative velocity. A configurable safety threshold (typically 3 m) initiates a hierarchical warning strategy comprising visual
Deepan Kumar, SadhasivamKaru, RagupathyKarthick, K NR, Vishnu Ramesh KumarKumar, VManojkumar, RM, KarthickM, Rishab