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G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
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. The proposed GJO algorithm is employed to optimize the control and switching parameters of the Vienna rectifier, thereby improving harmonic performance and conversion efficiency without altering the converter hardware. This paper focuses solely on control optimization of the Vienna rectifier topology and does not include DC–DC isolation or galvanic separation. Filter components are modeled with equivalent series resistance (ESR) to account for incremental losses. Simulation results demonstrate that the Golden Jackal optimization (GJO) based control reduces input current THD to 2.09%, has a power factor of 0.998, and achieves an efficiency of 98.53%, representing a fractional but consistent improvement over conventional control methods such as SSA, ALO, and PSO. These findings highlight the
R, Mohammed AbdullahN, Kalaiarasi
In this study, the combustion and emission characteristics of a single-cylinder direct injection (DI) diesel engine fueled with Spirulina biodiesel along with diesel blends were examined using a combined CFD and thermodynamic simulation framework. Three test fuels, including pure diesel (D100), Spirulina biodiesel blends (B20 and B40), and pure Spirulina biodiesel (B100), were analysed at 1500 rpm under full load. In the first stage, CFD simulations were performed in ANSYS Fluent, where the Discrete Phase Model (DPM) was applied to capture spray atomization and droplet evaporation, while a non-premixed combustion model coupled with the RNG k-ε turbulence model was employed to resolve in-cylinder flow and heat release dynamics. Subsequently, the Diesel-RK software was utilised to predict engine performance and exhaust emissions based on compression ratios (18.5) and injection timings. Results from the CFD analysis revealed faster atomization and reduced ignition delay for biodiesel
Kumar, B Varun
As the automotive industry transitions toward software-defined vehicles and highly connected ecosystems, cybersecurity is becoming a foundational design requirement. A challenge arises with the advent of quantum computing, which threatens the security of widely deployed cryptographic standards such as RSA and ECC. This paper addresses the need for quantum-resilient security architectures in the automotive domain by introducing a combined approach that leverages Post-Quantum Cryptography (PQC) and crypto-agility. Unlike conventional static cryptographic systems, our approach enables seamless integration and substitution of cryptographic algorithms as standards evolve. Central to this work is the role of Hardware Security Modules (HSMs), which provide secure, tamper-resistant environments for cryptographic operations within vehicles. We present how HSMs can evolve into crypto-agile, quantum-safe platforms capable of supporting both hybrid (RSA/ECC + PQC) and fully post-quantum
Kuntegowda, Jyothi
The Dual Throat Nozzle (DTN) is a unique nozzle configuration that enables fluidic thrust vectoring (FTV), improving aircraft maneuverability while reducing the mechanical complexity of traditional vectoring systems. In this study, a two-dimensional DTN was developed based on a validated NASA Langley model, incorporating a newly designed plenum geometry guided by area expansion ratio principles. Numerical simulations were carried out in ANSYS Fluent using a density-based, steady-state solver with the SST k–ω turbulence model to capture key compressible flow features such as shock waves, flow separation, and jet deflection. Secondary injection rates were determined using choked-flow relations, and a 12-case parametric study was conducted to analyze the effects of Nozzle Pressure Ratio (NPR), injection rate, and injection angle on thrust deflection and efficiency. The simulation results at NPR = 4 with 3% injection showed strong agreement with NASA experimental data, validating the
Suresh, VigneshM, AkashSenthilkumar, NikilSundararaj, SenthilkumarA, Garry KiristenSingh, Swaraj
This paper examines the technological and architectural transformations critical for advancing Software-Defined Vehicles (SDVs), emphasizing the decoupling of hardware from software. It highlights the limitations of traditional development models and proposes modern architectural approaches, including MPU-based designs and virtualization techniques, to foster flexible and scalable software ecosystems. Central to this vision is the concept of a Virtual Development Kit (VDK), which enables the design, validation, and scaling of SDVs even before physical hardware is available. The VDK integrates hardware platform emulators, operating systems, software stacks, and middleware optimized for high-performance computing (HPC) environments, providing developers with tools for early-stage testing, debugging, and integration while minimizing dependence on physical prototypes. As the automotive industry increasingly relies on software-defined features as primary drivers of innovation and
Khan, Misbah UllahGupta, Vishal
The Automobile Life Extender (ALE) comprises an on-board function, a machine learning model operating via cloud computing and a smartphone app. The on-board function receives signals such as engine RPM, throttle position, brake pedal position, and hydraulic pressure from the vehicle's ECUs. Based on this data, the on-board ALE module calculates the engine load, brake circuit load, etc., and sends it to the predictive maintenance model via the on-board IoT system. The predictive maintenance model contains recorded data about the type of engine, brake system, and their performance curves acquired from tests conducted by its OEM. Machine learning models holds a crucial role in dynamically analyzing vehicle data, identifying drive patterns, and predicting the need for maintenance of a part or system. A hybrid approach of training models based on supervised and unsupervised learning is incorporated, creating an active learning strategy to maximize the use of available data. Amazon SageMaker
Sundaram, RameshselvakumarKumar, LokeshSaint Peter Thomas, EdwinSureshkumar, SrihariMuthukumaran, ChockalingamMenon, Abhijith
This study presents a systematic CFD-based investigation of air-cooled lithium-ion battery pack thermal management using a novel U-shaped channel. The U-shaped domain was selected due to its ability to promote recirculation and uniform air distribution, which enhances cooling effectiveness compared to conventional straight and Z-type channels. A systematic parametric optimization of inlet position and airflow velocity was performed to minimize hotspot formation and improve temperature uniformity. Results reveal that shifting the inlet from 30 mm to 20 mm and increasing velocity from 2 m/s to 3 m/s reduced the maximum battery temperature by 3.46 K, from a baseline of 333 K to 329.54 K, while maintaining minimal pressure drop. These findings highlight that strategic control of inlet parameters can yield significant thermal improvements with high cost-effectiveness and geometric simplicity.
PC, MuruganJ, SivasankarW, Beno WincyG, Arun Prasad
The design of advanced driver-assistance systems (ADAS) is essential to improve the safety and autonomy of rear wheel driven four-wheel vehicle in harsh conditions. This work introduces the design and development of a steering automation system for Lane Keep Assistance (LKA) in an rear wheel driven four-wheel 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
A R, ArundasSadique, AnwarRafeek, Aayisha
Fires in Urban high-rise structures and industrial areas pose significant challenges to traditional firefighting methods. Traditional firefighting methods often struggle to address the challenges posed by height, accessibility and rapid response. In such a scenario innovative technologies become vital for effective and efficient methods. This project introduces an unmanned aerial vehicle designed to suppress fire on high-rise building by using drone technologies and robotics. The drone is equipped with a stereo camera which will detect fire and measure its coordinates with the help of algorithms fed on the companion computer raspberry pi. Upon receiving the coordinates, the drone will station itself at a predetermined distance from the fire. The drone will adjust itself in the vertical direction for proper ejection of water at the fire. The water will be ejected through a nozzle integrated with the drone, which is connected to the pump at the ground via hose. This drone solution
R, AbhiramSadique, AnwarPV, AnuragJ, Harisankar VA, Geethuvs, Amarnath
The integration of ethanol into gasoline presents compatibility challenges for automotive fuel-system materials. In this study, the degradation of NBR-PVC fuel hoses exposed to ethanol-gasoline blends (E30, E50, E70, and E100) was investigated under dynamic flow conditions. A custom-designed test rig simulates real-time fuel circulation for 1,200 h. FESEM, ATR-FTIR, and elemental mapping analyses revealed ethanol-induced degradation, including dehydrochlorination, plasticizer leaching, and filler detachment. Among the blends, E30 exhibited the least material degradation, whereas E100 showed significant surface damage and chemical alteration. This study recommends multilayered fuel hose structures with ethanol-resistant inner linings for enhanced durability.
PC, MuruganL S, AdhityaG, Arun PrasadW, Beno WincyT, Karthi
The spring link or the lower control arm (LCA) is a critical structural component in a multi-link rear suspension system especially in a sports utility vehicle (SUV). The design of the rear LCA is thus challenging due to higher loads owing to higher suspension articulation typical of a SUV and further complicated in a born electric vehicle (BEV) due to increased vehicle weight contributed by a large battery. In the present work, a novel LCA was designed for the rear suspension system of one such born electric SUV application. The unique link was designed to withstand 20% higher rear axle weight compared to the conventional LCA used in a typical SUV. The LCA housed the spring with increased stiffness and a semi-active damper with varying and higher damping forces which complicated the design. The link design was further complicated with stab link mounting provision and mass damper mounting for improved NVH performance. Furthermore, the link was designed to withstand significantly higher
Selvaraj, SaravananNayak, BhargavJ, RamkumarM, SudhanChaudhari, Varun
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, PJ, RamkumarNayak, BhargavM, SudhanPatnala, Avinash
This study investigates the tribological behaviour of Sesbania rostrata fiber (SRF) reinforced polycaprolactone (PCL) biocomposites using a pin-on-disc wear couple. The stationary SRF/PCL composite specimen interacted with a rotating EN31 steel disc (64 HRC), establishing the sliding wear interface in accordance with ASTM G99 standards. Composite laminates containing 10, 20, and 30 wt% SRF were evaluated at a sliding velocity of 1 m/s over a fixed distance of 1000 m under varying normal loads. The incorporation of SRF significantly enhanced the wear performance relative to neat PCL, with 20 wt% fiber loading achieving the lowest coefficient of friction and specific wear rate due to improved load transfer, stronger interfacial adhesion, and a more uniform laminate structure. In contrast, the 30 wt% composite exhibited fiber agglomeration, reduced homogeneity, and weakened fiber–matrix interactions, resulting in increased wear. SEM microstructural analysis confirmed the formation of a
Raja, K.Senthil Kumar, M.S.
Software-defined vehicles are those whose functionalities and features are primarily governed by software, thus allowing continuous updates, upgrades, and the introduction of new capabilities throughout their lifecycle. This shift from hardware-centric to software-driven architectures is a major transformation that reshapes not only product development and operational strategies but also business models in the automotive industry. An SDV operating system provides the base platform to manage vehicle software and enable those advanced functionalities. Unlike traditional embedded or general-purpose operating systems, it is designed to meet the particular demands of modern automotive architectures. Reliability, safety, and security become crucial because even minor faults may have serious consequences. Key challenges to be handled by the SDV OS include how to handle software bugs, perform real-time processing, address functional safety and SOTIF compliance, adhere to regulations, minimize
Khan, Misbah UllahGupta, Vishal
This study presents a comparative investigation of the vibration characteristics of rectangular and circular plates with fixed edges using analytical, numerical, and computational approaches. Analytical models based on classical plate theory were employed to calculate natural frequencies and mode shapes, while finite element analysis (FEA) was performed in a CAE tool to provide high-fidelity simulation results. A detailed mesh convergence study confirmed numerical stability, with frequency variations below 1% between successive refinements. Analytical predictions showed excellent agreement with simulation results for lower modes, with errors as low as 0.25% for the rectangular plate and 2.65% for the circular plate. However, higher modes exhibited significant deviations, with errors reaching up to 29.01% for rectangular and 181.52% for circular geometries, highlighting the limitations of closed-form solutions in capturing complex vibrational behavior. Python-based computational tools
N, SuhasR, SanjayBhaskara Rao, Lokavarapu
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 Tube were mixed with PCM at 2% of total volume of the PCM and a system that incorporates powdered natural dolomite/MWCNT at 1% each into the PCM-based TESU. Each of the four configurations was created, tested simultaneously, and thoroughly examined. In comparison to the Standard Still (SS), the experimental findings showed that the adoption of PCM-based TESUs increased daily cumulative water output (collection efficiency) by 24%, 26% with addition of MWCNT and the addition of dolomite powder/MWCNT further increased productivity by 27%. The average exergy efficiencies for for SS, SS with PCM, SS with nano enriched PCM, and
R L, KrupakaranPetla, RatnakamalaAnchupogu, PraveenP, UmamaheswarraoSatya Meher, RDunna, Vijay
This study investigates the potential of using a dual green alternative fuel combination, the one is hydrogen fuel and another one is biodiesel for enhancing the Performance, combustion and emission profile of a compression ignition engine. The kapok oil biodiesel was blended with Diesel in proportions of 20% (K20) and 40% (K40) by volume. The hydrogen gas was supplied at a constant flow of 4 liter per minute (LPM). The experimental fuels are neat diesel D100, K20 (80% Diesel and 20 % kapok methyl ester), K40 (60% Diesel + 40 % Kapok methyl ester), K20 + H4L (K20 with 4 LPM hydrogen) and K40+H4L (K40 with 4 LPM hydrogen). These test blends are investigated in a single cylinder direct injection CI engine under 0% to 100% load conditions at a fixed speed of 1500 rpm combustion, and emissions characteristic were evaluated and compared with base fuel. The outcomes indicated that the use of B20 and B40 blends without hydrogen led to reduced BTE because of their lower cetane number and
Anbarasan, BM, KumaresanBalamurugan, SRajesh, Munnusamy
This SAE Recommended Practice is applicable to all heat exchangers used in vehicle and industrial cooling systems. This document outlines the tests to determine the heat transfer and pressure drop performance of heat exchangers under specified conditions. This document has been reviewed and revised by adding several clarifying statements to Section 4.
Cooling Systems Standards Committee
Range estimation for electric vehicles based on standard drive cycles generally underestimates energy consumption and fails to accurately represent the actual driving characteristics. This paper aims to develop a representative driving cycle for electric two-wheelers that emulate the real-world driving scenario in Lucknow, India. The micro-trip-based random selection scheme is used to form the drive cycle. The onboard Global Positioning System (GPS) module is used to log vehicle speed data for every second, and nine assessment parameters were used to analyze the candidate drive cycles. The total duration of the developed drive cycle is 1800 s, and the length is 17.45 km. Traffic attributes of the developed drive cycle are compared with the India drive cycle (IDC), Delhi motorcycle drive cycle (DMDC), and Edinburgh motorcycle drive cycle (EMDC). A comparison of the estimated energy requirement of the developed drive cycle with IDC indicates that the estimated actual energy requirement
Vashist, DevendraPandey, BhaskarMalik, Varun
This paper presents a novel AI-based parking management system designed to enhance efficiency, reduce manual intervention, and optimize operational costs in modern parking facilities. By integrating computer vision with infrared (IR) sensors, the system continuously monitors parking areas in real time, accurately detecting vehicle occupancy and dynamically updating the space availability. The hybrid approach minimizes reliance on conventional sensors, improving accuracy and environmental robustness. Additional features include intelligent navigation assistance guiding drivers to available spots and integrated video surveillance for enhanced security through AI-driven suspicious activity detection. The user interface provides real-time updates ensuring a seamless and convenient parking experience. Overall, this system offers a comprehensive solution that advances parking technology through automation, real-time monitoring, and secure, user-friendly operation.
N, KalaiarasiGupta, ShivanshHajarnis, MihirAnand, Vikas
The growing global adoption of electric vehicles (EVs) has resulted in a spike in the number of EV charging stations. As EVs have become more and more popular worldwide, a large number of EV charging stations are opening up to accommodate their demands. During grid failures, an EV charging station can also serve as a flexible load connected to the grid to balance out voltage fluctuations. An EV charging station when powered using a separate source, such as solar or wind, can function as a powerhouse, bringing electricity to the grid when it's needed. Therefore, instead of installing more equipment to sustain voltage, the current EV charging station can be efficiently used to meet the grid's needs during failures. These stations have the potential to be dynamic, grid-connected assets for sustainable cities and communities in addition to their core function of vehicle charging (SDG 11). Because of their dual purpose, they can serve as adaptable loads that reduce voltage variations during
R, UthraRangarajan, RaviD, SuchitraD, Anitha