Browse Topic: Electrical, Electronics, and Avionics

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Comparative study between MQTT 3.1 and MQTT 5.0: Evaluating Theoretical Enhancements Through Practical Throughput Benchmarks for Aerospace IoT Systems2026-26-0711To be published on 06/01/2026
As aerospace platforms increasingly adopt connected architectures for avionics, telemetry, and predictive diagnostics, lightweight messaging protocols have become foundational. MQTT (Message Queuing Telemetry Transport), due to its simplicity and minimal network overhead, is widely used in both ground and onboard aerospace systems. With the release of MQTT 5.0, the protocol introduces a suite of new capabilities designed to enhance scalability, reliability, and diagnostics. However, these benefits come with trade-offs in complexity and potential overhead, particularly in real-time and resource-constrained environments typical in aerospace. This paper presents a comparative evaluation of MQTT 3.1 and MQTT 5.0, exploring their theoretical differences — such as reason codes, session expiry, user properties, topic aliasing, shared subscriptions, and enhanced error feedback — and their impact on system-level performance. We analyze these aspects using practical throughput benchmarks
Bhuyar, Prabhudev, M, Meghana, Kaniraja, Christina, Thomas, Tinto
Automating Compliance Workflows in Aerospace Systems: A Scalable Framework for Specification Review and Requirement Mapping2026-26-0714To be published on 06/01/2026
Compliance verification in aerospace systems often relies on labor-intensive workflows that demand extensive manual effort to produce structured review documentation and requirement matrices. These processes can span dozens of hours per review, are vulnerable to inconsistencies due to non-standardized annotations, and depend heavily on individual interpretation of fragmented technical sources. With a growing backlog of review tasks and a steady influx of new requests, the need for scalable automation has become increasingly urgent. This study presents a modular automation framework designed to streamline compliance assessments through intelligent document parsing, requirement extraction, and matrix generation. The system integrates optical character recognition, computer vision, and natural language processing techniques to process both scanned and digital documents. By digitizing data across multiple hardware configurations and automating extraction from diverse technical records, the
Mirani, Harsh, Baviskar, Yash G.
Automated Flight Maneuver Recognition for Intelligent Flight Simulator2026-26-0713To be published on 06/01/2026
The rapid growth in the number of aircrafts and pilots emphasizes the need for an AI-enabled training framework that can offer precise, automated examination of flight maneuvers, thereby optimizing the pilot’s training efficiency and minimizing iterations of the conduct of flight maneuvers thereby reducing the training time of the pilot for a flight. This paper introduces a novel hybrid methodology to intelligently detect manoeuvres performed during a flight using signal processing and machine learning techniques. A general framework is developed that can be used for all kinds of flight phases and aircraft types. The framework is implemented in a two-step approach. Firstly, Continuous Wavelet Transform (CWT) of the signals of interest for different manoeuvres are generated, to find the time at which a manoeuvre happens during a sortie. CWT looks at the energy levels in the transformed signal and uses smart thresholding technique to pick out only the parts with high energy, to extract
sahu, Akash, c, Poornima, C, Aravindh, Kaliyari, Dushyant, Tk, Khadeeja Nusrath
Enabling Circularity in the Aerospace Maintenance Ecosystem through Generative-AI Driven Back-to-Birth Traceability of Life-Limited Engine Parts2026-26-0719To be published on 06/01/2026
Circular economy principles are increasingly central to aerospace sustainability strategies, aiming to extend asset life, improve asset valuations, and enhance benefits to stakeholders in the part ownership and maintenance lifecycle. In aircraft engines, achieving circularity hinges on the safe reuse, repair, and recirculation of high-value components. Life-Limited Parts (LLPs) are among the most critical in this context, but their reuse is strictly contingent on complete Back-to-Birth (BtB) traceability. Any gap in BtB records—often due to fragmented data across multiple airline operators, shop visits, document formats, and time expanse—renders otherwise serviceable LLPs unusable, leading to premature scrappage and lost circular value. This paper presents a Generative AI (GenAI)-driven methodology to reconstruct and validate complete LLP BtB histories from heterogeneous, unstructured, and legacy maintenance datasets. By combining aerospace domain-trained language models with embedded
Bhate, Ujwal, Jain, Dilip Kumar, Kulkarni, Ninad, Kalaiyarasan, Aravindh, Jha, Ashish, Shenoy, Karthik
Implementation of Wireless IoT Technology in EVAC Slide Emergency Systems2026-26-0792To be published on 06/01/2026
Emergency evacuation slides (EVAC slides) are critical safety devices used on aircraft to enable rapid egress during emergencies. While these slides provide a quick and reliable escape route, communication between separated slides during evacuation remains a challenge. Often, during raft deployment over water, slides may drift apart, impeding communication among evacuees and rescue personnel, potentially compromising safety. Existing aircraft EVAC systems on the market lack integrated wireless communication, relying on visual or shouted voice signals, which are unreliable in noisy or chaotic conditions. With the rise of the Internet of Things (IoT), wireless sensor networks have become effective tools for monitoring and communication in various safety and industrial applications. This paper explores the integration of wireless IoT technology into EVAC slide systems to facilitate inter-slide communication and monitor critical parameters, such as slide air pressure and the floating
Sengodan, Rajkumar, Talore, Suresh
Aircraft cabin Diagnosis - Inspection of the Aircraft cabins and seats using AI2026-26-0789To be published on 06/01/2026
Operational challenges related to aircraft interiors particularly damaged seats, compromised seat cushions, and liquid or food spillages have a direct impact on airline operations and passenger satisfaction. Allowing passengers to use defective seating not only degrades the travel experience but also risks damaging the airline’s reputation. Moreover, addressing these issues often results in increased aircraft ground time, contributing to significant financial implications for airline operators. To mitigate these challenges, a predictive maintenance approach leveraging artificial intelligence (AI) is proposed. This system utilizes radar scans and high-definition camera images captured when the aircraft is unoccupied to detect interior issues. The collected data is then compared against a baseline “master scan” taken under ideal, clean, and properly maintained conditions. Advanced AI algorithms analyze these comparisons to accurately identify problem areas, down to specific seat
Nagoal, Chandrasekhar Reddy, Prathipati, Krishna Chaitanya, Kandukuri, Ravindra
Leveraging True Altitude Data to Improve Static Pressure Calibration from Dynamic Manoeuvres2026-26-0729To be published on 06/01/2026
Accurate calibration of aircraft air data systems is essential for reliable measurement of flow angles, altitude, and airspeed, particularly during dynamic flight manoeuvres where errors can become significant. Externally mounted vanes and probes are used to measure flow angles, local pressures and temperature, respectively. However, because these sensors are positioned close to the aircraft fuselage, they operate within disturbed local flow fields that differ notably from the free-stream conditions. As a result, their outputs require Position Error Corrections (PEC) to accurately estimate free-stream parameters such as pressure, temperature, and flow angles. The pre-flight PEC data or calibration tables for these sensors are generated based on the CFD predictions/wind tunnel experiments. All the flight-measured local variables from air data sensors need to pass through the air data computers, which contain these lookup tables, to obtain the free stream information. Despite the pre
Tk, Khadeeja Nusrath, Patel, Dr. Ambalal V, J, Prabhavathi Bhai
A Clamping-Based Design Approach for Optical Assemblies in Aircraft Lighting: Eliminating Fastener-Induced Cracks and Validated by Thermo-Mechanical Testing2026-26-0750To be published on 06/01/2026
Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. Currently, Aircraft Lights are based on Light Emitting Diode (LED) technology, where they are mounted on a Circuit Board Assembly (CBA). For some applications, Total Internal Reflection (TIR) Optics are mounted concentric over these LEDs so that light is focused in the required areas. The use of high-performance polymers such as Cyclo Olefin Polymers (COP) for these Optics provides excellent light transmission and stability. Hence, there is a need to secure these Optics to CBA. A critical challenge is securing the Optics to CBA. In the initial design, Optic was fastened directly onto the CBA using self-threading fasteners. However, due to inherent properties of COP, this fastening method proved not ideal. During assembly, frequent crack initiation was observed around the fastener locations, raising concerns over durability, reliability, and
Vialta, Frederico, S, Nikhil, Katageri, Praveen, SP, Pradeep, Singh, Abhimanyu Kumar
System and Method of Strain Emulation using a Beam Load Cell Test Setup2026-26-0743To be published on 06/01/2026
This novel method deals with emulation of Strain of a Structural Measurement System which includes software validation, acceptance tests and training. Current methods for simulating strain and force data for developing and verifying data acquisition (DAQ) software typically rely on costly electronic simulators or specialized hardware, making it challenging and expensive for developers, researchers, and small organizations to test their solutions under realistic conditions. To verify DAQ software, multiple specialized hardware solutions are deployed, that include Electronic Simulators, Commercial DAQ Modules and Hydraulic/Pneumatic test rigs. These technologies pose a challenge with limited flexibility and scalability options for small-scale prototyping, especially in budget-constrained scenarios. The sensors on these equipment may or may not be company approved inducing acceptance challenges. Our invention is an inexpensive, scalable, and mechanically simple alternative. Using a 3D
Murthy, Harsha, Bhat Venkatesh, Aditi, K Padmanabhan, Rahul, Madhu, Sheetal, Garag, Naveen
Augmented Reality and Multimodal Interfaces for Astronaut Training and In-Orbit Operations2026-26-0796To be published on 06/01/2026
Augmented Reality (AR) and multimodal human–machine interfaces (HMI)—combining visual overlays, voice, gesture, eye-tracking, and biometric sensing—are now maturing into flight-relevant technologies capable of transforming astronaut training and in-orbit operations. These interfaces reduce task time, lower error rates, and mitigate cognitive load, thereby strengthening both crew autonomy and mission safety. For India, the timing is critical: Gaganyaan human spaceflight program is approaching decisive crewed missions in the late 2020s, and the Bharatiya Antariksh Station (BAS) is targeted for the 2030s. AR/MMI can be positioned not as an accessory but as a core enabling system for training throughput, real-time crew support, and resilient station operations. This paper provides (i) an overview of India’s current scenario, including Gaganyaan astronaut training ecosystems, IIT Madras collaborations on AR/VR, and Vyommitra humanoid readiness; (ii) synthesis of global case studies—NASA
Yadav, Anoop Singh
A GenAI-Based Approach for Real-Time Multilingual In-Flight Communication Systems.2026-26-0784To be published on 06/01/2026
In today’s global aviation industry, passenger experience is strongly influenced by effective communication. In-flight announcements, often limited to English and a single local language, can create confusion and stress for international travelers who may not be fluent in either. This communication gap not only impacts passenger comfort but also poses potential risks in conveying time-sensitive or safety-critical information. Recent advances in Generative Artificial Intelligence (GenAI), particularly in speech recognition, neural machine translation, and naturalistic text-to-speech, provide a pathway to overcome these challenges. This paper explores the concept of real-time multilingual in-flight announcements, delivered in each passenger’s preferred language through connected headphones or personal devices. The proposed system architecture integrates speech-to-text conversion, language translation, and speech synthesis with aircraft infotainment platforms. Potential applications range
Mishra, Ashwini, Kature, Kartik, Patil, Ashish
Adaptive HVAC Strategies for Enhanced Cabin Thermal Comfort, Air Quality and Energy Efficiency2026-26-0791To be published on 06/01/2026
Passenger comfort within vehicle and aerospace cabins relies on finely tuned management of temperature, air quality, and energy use. This paper proposes an integrated HVAC framework that combines zonal climate control, intelligent airflow distribution, and real-time sensor data to maintain thermal balance across different cabin zones. Leveraging predictive thermal load modeling and machine learning, the system anticipates environmental changes—such as sudden shifts in external temperature or passenger load—and proactively adjusts heating and cooling outputs. Simultaneously, air quality is enhanced through a multistage filtration system, active air purification technologies, and dynamic CO₂ concentration monitoring. Comfort assessment integrates PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) indices to adapt environmental conditions based on passenger feedback and physiological needs. Simulations and early-stage prototypes improve energy savings and improve
Mudavath, Lehitha Sai, Patil, Ashish, Saha, Sudipta
Hybrid Physics-Informed Neural Network and PID Control for Fault-Tolerant Autonomous Multi-copters2026-26-0770To be published on 06/01/2026
This paper addresses the critical challenge of fault-tolerant control in autonomous multi-copters, particularly under conditions of one or two rotor failures a scenario that often leads to severe instability and a complete loss of directional control due to unbalanced torque and resultant autorotation. Existing advanced control strategies, including optimal approaches such as LQR, typically require precise system modeling and state estimation, which are difficult to achieve in real-world, dynamic failure scenarios. Alternative methods like fuzzy logic, sliding mode control, and gain-scheduling either lack robust generalization or are impractical for enumerating all possible failure cases. In this work, a hybrid control framework integrating Physics Informed Neural Networks (PINN) with a standard PID controller is proposed for fault-tolerant operation of autonomous multi-copters subject to multiple actuator failures. PINNs incorporate governing physical laws as regularization in their
Charapalle, Samruddhi, Venugopalan, Nandagopalan, Nerkundram Muralidharan, Arun, Sundararaj, Laveen
Development of Room Temperature Vulcanized Silicone Rubber BasedvNotched Cantilever Beam Isolator for Space Applications2026-26-0742To be published on 06/01/2026
Crystal Oscillators are generally used in the high precision frequency application of satellite hardware for navigational aids. The required precision frequency of the crystal oscillator is affected under the dynamic loads. Mechanical isolators can be used to isolate the crystal oscillator assembly from the base induced vibration. Room Temperature Vulcanized Silicone Rubber is selected as material for isolator due to inherent good damping property. Geometric configuration of isolator is optimized in iterative manner based on the dynamic characteristics obtained from Finite Element Analysis and Low-Level tests on engineering model. The finalized configuration is subjected to qualification level sine and random vibration and shock test to check the mechanical integrity of isolator under dynamic loads.
Singh, Shivam
Electrical Harnessing in Satellite Launch Vehicles of ISRO – Methods for Sustainable, Safe, and Reliable systems2026-26-0779To be published on 06/01/2026
The electrical harness serves as the "neural network" for satellite launch vehicles, providing the interfaces for all guidance, health monitoring, and control systems during a mission. This system is composed of cables, and connectors. The wires are made of metallic conductors, typically copper plated with silver or gold to enhance conductivity and prevent oxidation. These conductors are insulated with polymeric materials such as PTFE, Kapton, ETFE, or TKT. Connectors, which are the interface points for electrical circuits, consist of gold or nickel-plated copper contacts housed within a shell. A typical launch vehicle contains an extensive network of electrical harnesses, with approximately 4,200 connectors and 110,000 meters of cable, which contributes to about 30% of the vehicle's total weight. The weight is mostly due to the polymeric insulation rather than the conductors. Challenges and Solutions for Sustainable Systems The paper highlights several key issues with current
K S, NITHISH, TR, Binny, D S, PRAVEEN KUMAR
Design and Development of a Morphing-Fin Hybrid Rocket-Powered Loitering Interceptor Drone for Surface-to-Air Missile Applications2026-26-0756To be published on 06/01/2026
This project aims to develop a novel loitering interceptor drone that combines the high-speed launch capabilities of a surface-to-air missile (SAM) with the maneuvering and persistence of a drone. The system will utilize a solid-propellant rocket booster to rapidly ascend and reach operational altitude. Upon reaching a designated threshold, the system will activate a morphing-fin mechanism, in which the missile’s stabilizing fins will dynamically reconfigure into a drone-like control surface system. This transformation is intended to enable the vehicle to switch from missile mode to a loitering drone mode, with the ability to hover, patrol, and track aerial threats over extended durations. The proposed interceptor will be equipped with autonomous navigation and decision-making modules, leveraging radar-based target detection, IFF (Identification Friend or Foe) logic, and path-prediction algorithms. Simulations will be developed using MATLAB/Simulink, where radar sweep behaviour
E, Rahul
Data-Driven Air Traffic Management: Forecasting Demand, Modeling Delay Propagation, and Demand Capacity Balancing2026-26-0772To be published on 06/01/2026
Air traffic management (ATM) systems must accurately estimate flight demand, analyze network delays, and optimize capacity. This research uses a global airline dataset with passenger information, airport characteristics (including geographic markers and continental classifications), flight scheduling data (timing and destination details), crew information, operational status records, and OpenSky Network real-time states data to create an intelligent ATM decision-support framework. Advanced machine learning (ML) methods like gradient boosting and sequential modeling are used to build network models of flight routes between origins and destinations, develop temporal demand patterns for individual airports, analyze delay factors, and predict congestion periods. The research uses mixed-effects statistical models using crew data to measure operational variability and demographic and nationality-based analysis to identify demand trends for improving staffing and security processing during
Senthilkumar, N., S, Gopalakrishnan, Gopinath PhD, S
Evaluation of APNT systems to support PBN operations in lieu of GNSS over Indian air space2026-26-0769To be published on 06/01/2026
At present airborne navigation is primarily dependent on GNSS to enable Performance Based Navigation (PBN) services, both Area Navigation (RNAV) and Required Navigation Performance (RNP), to aviation users on a global scale. However, due to the apparent increase in the disruption of GNSS signals in the airspace due to radio frequency interference (RFI), in the event of loss of GNSS, this dependency may lead to inefficient use of airspace and potentially lead to service degradation. Thus, making the sole reliance on GNSS untenable highlighting the need for RNP services based on terrestrial sources. A key aspect of making PBN resilient to RFI and other GNSS threats is to evaluate the current capability and drive modernization of Alternate Positioning, Navigation and Timing (APNT) systems to support seamless RNP operations. Improvements in PNT integration with other aircraft systems and enhancements in RFI situational awareness provided to operators/flight crews are essential to fully
Narayanan, Shrivathsan -., Kottackal, Sebin K, Roy, Joydeep
Unified and Certifiable Cybersecurity Management Framework for IVHM2026-26-0767To be published on 06/01/2026
Commercial and military aircraft’s are increasingly rely on Integrated Vehicle Health Management (IVHM) as a critical enabler for predictive maintenance, operational efficiency, and mission availability. The evolution of IVHM data communication architecture- from legacy wire-based networks to wireless based architecture, involving onboard wireless sensor networks (WSN) and IP-based air-to ground communication networks, including satellite-enabled data links – introduces and expand multi domain, multi channel cyber-physical attack surfaces that challenge both functional, operational safety and continued airworthiness. DO-326A/ED-202A and DO-356A/ED-203A standards define aviation cybersecurity requirements within a safety-driven assurance context, and IEC 62443 standard offers a defense-in-depth, lifecycle-based control framework for industrial systems. A unified approach by mapping and harmonizing the complimentary aspects of these two standards has the potential to simplify and
Samudrala, Ramakrishna, Ramamurthy, Prasanna
Mitigation of Assembly-Induced Cracking in Cyclo Olefin Polymer (COP) Optics through Annealing and Step-Torquing Technique2026-26-0764To be published on 06/01/2026
Light Emitting Diode (LEDs) are the main source of light in Aircraft lighting systems and are mounted on a Circuit Board Assembly (CBA). For some applications, Optics are mounted concentric to these LEDs so that light is focused in the required areas. Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted as Optics due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively high notch sensitivity and the presence of residual molding stresses make them prone to crack initiation during mechanical fastening. In this case study, Optic was fastened directly onto the CBA using self-threading fasteners. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with aerospace durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and
S, Nikhil, Singh, Abhimanyu Kumar, Katageri, Praveen, SP, Pradeep, Chandra, Praveen
Integrating Human Factors and Predictive Modeling for Enhanced Aviation Safety: A Data-Driven Approach to Risk Mitigation and System Design2026-26-0795To be published on 06/01/2026
The evolution of the aviation industry from manual control to highly automated and autonomous systems has brought human factors to the forefront of safety, design, and operational efficiency. This paper presents an integrated analysis combining machine learning techniques with statistical modeling to assess the impact of human-system interaction on aviation incident outcomes. The first phase of this research involved a longitudinal dataset covering aircraft design evolution, training programs, and incident records. Using classification algorithms, including XGBoost, the study achieved an accuracy of 81.82% in predicting incident likelihood. Performance metrics such as F1-scores (0.85 for “Incident” and 0.78 for “No Incident”) highlighted the model’s robustness in identifying risk patterns associated with human factors and system complexity. In the second phase, 50 plus detailed aviation incident reports were analyzed using logistic regression, t-tests, and Cook’s Distance to identify
Valiyaparambil, Praveen
Carbon footprint reduction by selective gold plating of contacts in aerospace grade electrical connectors2026-26-0778To be published on 06/01/2026
In the aerospace industry, where safety and reliability are paramount, every component contributes to the overall integrity of the aircraft. Additionally, sustainability in aerospace engineering is driving a shift toward selective material usage, especially in electrical connectors where contacts are traditionally fully gold-plated. In pursuit of resource efficiency and reduced environmental impact, selective plating techniques are being adopted to minimize gold usage while maintaining electrical performance. One such sustainability approach from our organization has been extended to one of our products used in aircraft without compromising standard requirements. Re-evaluating plating strategies to target only functionally critical areas. The internal surfaces of the contact component have been fully gold plated with the area of 1,176 mm². The idea is to have gold plating on the critical surfaces of area 570.21 mm² only. This will reduce gold plating area by 51.5%. which saves gold
M, PRAVEEN KUMAR, K S, Nayana
Risk-Driven Program Management Framework - Abstract2026-26-0716To be published on 06/01/2026
Avionics programs face increasing complexity due to evolving safety, certification, and cybersecurity requirements. Conventional program management approaches, focused mainly on cost and schedule, often overlook the dynamic and interdependent risks inherent in developing safety-critical systems. This gap results in late surprises, inefficient resource use, and challenges in achieving certification milestones. This paper introduces a risk-driven program management framework tailored for avionics, where risk identification, assessment, and mitigation are embedded within the governance model rather than treated as a parallel activity. The framework integrates industry standards such as DO-178C, DO-254, DO-326A, and ARP4754A, ensuring alignment with regulatory expectations while promoting a holistic view of program health. A key feature of the approach is the use of digital dashboards and predictive analytics to transform static risk registers into actionable tools. These dashboards
Rahul, Saurabh, Benikireddy, Raghunatha
Electric Air Mobility Using Fuel Cells2026-26-0774To be published on 06/01/2026
Electric air mobility (EAM) is redefining the future of aviation by presenting sustainable, efficient, and adaptable solutions for both urban and regional travel. Within this emerging field, aircraft powered by fuel cells are rapidly gaining recognition as a promising route toward cleaner skies. Hydrogen fuel cells, in particular, stand out due to their impressive energy density, quick refueling times, and the fact that they emit no pollutants during operation. This makes them an appealing replacement for traditional internal combustion engines, as well as an alternative to conventional battery-electric systems. This document delves into the core principles, benefits, challenges, and long-term prospects of adopting fuel cell technology for electric air mobility. It examines how these advancements could revolutionize aviation and significantly support the global push for decarbonization. Specifically, the study evaluates Proton Exchange Membrane (PEM) fuel cells operating at 60
Kari, Sreedhar, KOLIPAKA, PRADEEP
Agentic Digital thread for self-healing non-conformities in aerospace product manufacturing lifecycle2026-26-0763To be published on 06/01/2026
Aircraft manufacturing involves a complex ecosystem where quality, traceability and compliance are paramount. Managing non-conformities both before and after manufacturing requires a digitally connected data framework that ensures seamless data flow, decision-making and corrective actions across different functions like sourcing, materials, engineering and production. The advent of agentic AI brings more autonomous solutions through drastically reduced human prompts. This paper presents a comprehensive Agentic Digital thread framework for managing pre and post manufacturing non-conformities, enabling real-time visibility and control from design to delivery. The Agentic digital thread transforms from being passive connectivity layer into living intelligence ecosystem that continuously learns, adapts, and improves in real time Pre-manufacturing nonconformity management focuses on early detection of issues through Agentic AI in sourcing, materials and design through integration of PLM
Veluri, Sastry, Gopala Krishnan, Kannan
Electric Health-Monitoring Wiring (E-Wiring) for Aircraft2026-26-0785To be published on 06/01/2026
Modern aircraft depend on extensive electrical wiring networks for power distribution, avionics, and control systems; however, these wiring systems are vulnerable to wear, insulation degradation, and arcing over time, leading to safety risks and costly unscheduled maintenance. The proposed Electric Health-Monitoring Wiring (E-Wiring) system integrates temperature, current, insulation, vibration, and environmental sensors directly into aircraft wiring harnesses to enable continuous monitoring and intelligent fault detection. Data from these embedded sensors are processed through a distributed edge AI network, forming an Electrical Health Monitoring System (EHMS) capable of real-time diagnostics, predictive maintenance, and fault localization. The architecture comprises smart cable segments with sensor nodes, local harness gateways for edge processing, aircraft-level EHMS integration via AFDX/Ethernet, and cockpit or maintenance displays linked to ground-based cloud analytics for fleet
Tammana, Bala Sai Sri Rohit, Murthy, Harsha, Mendu, HarikaSivaniSunandha
Drilling Studies on Sustainable Lightweight Hybrid Polymer Matrix High Performance Nanocomposites2026-26-0732To be published on 06/01/2026
Worldwide, engineers are exploring the possibility of using polymer composites in their quest for lightweight materials. In an effort to create polymer composites that are less harmful to the environment, the use of biodegradable polymers has been investigated in recent years. Injection molding was used to create a biodegradable polymer composite containing 20 wt.% vetiver fibers (VFs) and 2 wt.% nano-silica (nSiO2) obtained from pearl millet. Parts for unmanned aerial vehicles, interior cabin panels, seating structures, and secondary structural components were made of this composite. Desirability analysis was used to examine and optimize machining (drilling) studies that were designed according to Taguchi's design (L9 orthogonal array). Surface roughness (Ra) and delamination factor (DF) were taken as outputs, while spindle speed (SS) ranging from 1000 to 3000 rpm, feed rate (FR) from 15 to 45 mm/min, and drill diameter (DD) from 6 to 10 mm were used as inputs. The developed
Senthilkumar, N.
Automated health surveillance system for passenger2026-26-0794To be published on 06/01/2026
Ensuring passenger safety and comfort remains a top priority in the aviation industry, particularly during in-flight medical emergencies involving cardiac and respiratory complications. The absence of immediate medical intervention and the limitations of current aircraft health monitoring systems pose significant risks. Existing systems primarily depend on manual observation and basic sensors, lacking continuous health assessment, data analytics, and adaptive response mechanisms. This paper proposes a Smart Passenger Health Monitoring System that integrates Heart Rate (BPM), Electrocardiogram (ECG), and Peripheral Capillary Oxygen Saturation (SpO₂) monitoring into a single intelligent framework. The system utilizes high-precision biomedical sensors for continuous data acquisition, while an embedded microcontroller processes physiological parameters in real time to detect abnormalities. Upon identifying potential distress, the system triggers an automated seat adjustment mechanism that
S, Tejashree, D, Kousalya
AI Based Energy Sustained Series Hybrid Aircraft2026-26-0776To be published on 06/01/2026
This paper investigates the energy consumption characteristics of series hybrid aircraft with a focus on comparing conventional energy management approaches against an AI-powered optimization framework. The study comprehensively models the energy demands of a series hybrid aircraft across all major flight phases, including Idle & Ground Operations, Taxi, Takeoff, Climb, Cruise, Descent, Approach, Landing, and Rollout & Taxi. For each phase, detailed mathematical formulations are developed to capture power requirements and energy flow, incorporating real-time operational parameters to enhance the accuracy of the energy consumption estimations measured in kilowatt-hours (kWh). The AI-based optimization leverages advanced control strategies, specifically Model Predictive Control (MPC) and Reinforcement Learning (RL) algorithms, to dynamically manage the aircraft's energy systems. MPC is employed to predict and optimize future energy usage by solving constrained optimization problems over
Kanchagar, Amogha
Non-Intrusive Fatigue Detection and Alerting for Pilots2026-26-0793To be published on 06/01/2026
Pilot fatigue represents a critical concern in aviation safety, as it can significantly impair cognitive functions, decision-making abilities, and reaction times. In addition to decreasing performance, chronic fatigue has negative long-term health effects. Possible causes of fatigue include sleep loss, extended time awake, circadian phase irregularities and workload. Conventionally, the risk due to fatigue in aerospace is reduced by limiting pilot's flying hours and controlled rest requirements. Despite regulations on flying hours and optimal rostering, fatigue cannot be prevented completely. Hence, there is need to detect pilot fatigue in real time, annunciate in cockpit and transmit the information to airliners post-flight for appropriate fatigue risk management. There is ongoing research to detect pilot fatigue using devices that can capture Electroencephalogram (EEG) and Electrocardiogram (ECG). Though these devices have high fidelity, they are intrusive and can limit pilot
Nyamagoudar, Vinayak, P R, Namratha, Ramachandran, Venkataramani
Neural Network-Enabled Synthetic Air Data System: Development and Validation2026-26-0720To be published on 06/01/2026
Synthetic Air Data System (SADS) provides a smart solution that can be used to predict critical air data parameters in the absence of conventional air data sensors. Traditional air data sensors, such as pitot-static tubes and vanes, are generally expensive, require regular maintenance, and can fail in harsh weather conditions. In addition, these sensors, along with their processor and computers, add weight to the aircraft. To address these issues, a synthetic air data system is proposed using a Recurrent Neural Network (RNN). Several flight variables were checked for Pearson correlation coefficient with respect to the angle-of-attack and angle-of-sideslip, and thereafter, input features were selected based on the thresholding technique. The proposed neural network has two hidden layers and regularization technique was implemented by adding two dropout layers to each hidden layer to prevent overfitting of the model. The neural network was trained using actual flight test data
Sahu, Sanju, c, Poornima, Kaliyari, Dushyant, Tk, Khadeeja Nusrath, Hebbar, Archana
Enabling Digital Transformation in Aerospace: Automated Model Based Engineering2026-26-0722To be published on 06/01/2026
Model-based development (MBD) and testing are critical for airborne software compliance with DO-178C and its supplement DO-331, which specifically addresses model-based approaches for software levels A through D. Traditional manual methods for MBD and testing are time-consuming and prone to variability, impacting consistency, accuracy, and certification timelines as avionics systems grow in complexity. This paper presents an automation framework designed to align with DO-331 objectives by leveraging fine-tuned large language models (LLMs) to automate the generation of high-level textual requirements and low-level model-based requirements. From these, comprehensive test cases are automatically derived, covering normal, edge, mutant, and dynamic scenarios to ensure thorough validation of model behavior. Utilizing Boeing AI, the framework extracts requirements and key parameters from documentation, enabling automated specification analysis and test script generation that simulate real
Lalchandani, Tushar, Purushothaman, Kalaivani, Jeppu, Yogananda, Vijaya Kumar, Shree Harsha, Natarajan, Akilandeswari
Automating DO-178C Verification & Security Compliance in DevSecOps CI/CD Pipelines for Safety Critical Avionics Software2026-26-0717To be published on 06/01/2026
This paper presents an automated framework for security compliance and quality assurance in DevSecOps CI/CD pipelines, specifically designed for safety-critical avionics software. The framework integrates regulatory compliance checks, security validation, and robust verification directly into the software development lifecycle, supporting continuous integration and delivery for aerospace applications. Automated processes such as code compilation, coding standards compliance, Cyclomatic Complexity Measurement, Sources Line of Code and CRC validation on target hardware are seamlessly orchestrated to maintain consistency and reliability. The system generates comprehensive compliance reports, highlights coding standard violations and security issues, and notifies relevant stakeholders to facilitate timely resolution and corrective actions. As new code is checked in, the framework automatically initiates all verification and compliance tasks, ensuring that every software update is
Bhagwat, Shashank Ravi, CHANGAPPA, NAVEEN KUMAR, Nath, Sunny
Hybrid Digital Twin for Aero-Engine Bearing Prognostics: A Physics-Informed Machine Learning Approach to RUL Prediction2026-26-0718To be published on 06/01/2026
Unscheduled maintenance due to the failure of critical components, such as aero-engine rolling element bearings, is a leading cause of costly Aircraft-on-Ground (AOG) events; consequently, current time-based maintenance practices are inefficient and prone to risk. This paper develops a resource-efficient Hybrid Digital Twin (HDT) model for an engine bearing, focusing on the dynamic prediction of spall growth due to Rolling Contact Fatigue (RCF), thereby enabling a condition-based maintenance paradigm. The HDT architecture integrates two core models: (1) a physics-informed model that uses established life and fatigue theory to define initial degradation thresholds and constrain the failure envelope, and (2) a data-driven Recurrent Neural Network (RNN) (specifically, an LSTM) for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, synthetic run-to-failure dataset under varying operational loads
Mohamed, Abbas
Impact Study of Terrestrial Jamming on GNSS receiver on-board Launch Vehicles and Mitigation Techniques2026-26-0766To be published on 06/01/2026
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO's new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO's LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analysed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise ratio and corresponding change in RF AGC gain is also observed. The issue is
A, MOHAMMED BASIM, OT, ANAND SHANKAR, VS, BIJU, V GOPAL, BIJU, VS, VINOJ, K, BALAN, C, RADHAKRISHNA PILLAI
Development of a model-based data-driven control algorithm for a Drive-By-Wire System for a Level 4 Automated Vehicle2026-01-0043To be published on 04/07/2026
Precision control in Level 4 Automated Vehicles is essential for enhancing operational efficiency, accuracy, and safety, including improvements in time and fuel consumption. This research, conducted as part of ARPA-E’s NEXTCAR program, focuses on developing a robust control algorithm for a 2021 Honda Clarity Plug-In Hybrid Electric Vehicle (PHEV) to enable drive-by-wire functionality. A model-based control algorithm was created for a 2021 Honda Clarity Plug-In Hybrid Electric Vehicle (PHEV) to enable drive-by-wire functionality for longitudinal and lateral motion controls. This vehicle was equipped with a set of sensors and an onboard processing unit to enable Level 4 automation. An algorithm was designed to command steering torque to the electronic power steering module, ensuring the vehicle could attain the desired steering angle position at varying speeds. The system leveraged feedforward and feedback mechanisms to command steering torque to the electronic power steering module
Adsule, Kartik, Bhagdikar, Piyush, Drallmeier, Joseph, Alden, Joshua, Gankov, Stanislav
Comparative Analysis of Flux Linkage Characterization Methods for Automotive Permanent Magnet Traction Motors: A Critical Review and Performance Evaluation Framework2026-01-0441To be published on 04/07/2026
Accurate flux linkage characterization is essential for the design, control, performance and efficiency optimization of permanent magnet (PM) traction motors in automotive applications. Precise knowledge of flux linkage across varying load, speed, and temperature conditions directly impacts torque production, field-weakening capability, overall drive system efficiency and torque security. This paper presents a critical review and classification of flux-linkage characterization methods, encompassing offline laboratory mapping, standstill signal injection, self-commissioning inverter-only routines, and online real-time estimation. Each method exhibits distinct trade-offs in terms of accuracy, robustness to inverter nonlinearities, temperature adaptability, cost, and scalability for production and in-vehicle use. With the increasing complexity of automotive traction systems, understanding these trade-offs is crucial for optimal motor design and control. To enable systematic comparison, a
Khan, Ahmad Arshan, Haddad, Reemon, Kim, Jay, Hermann, Justin, Mohamadian, Mustafa
Proactive Faulty Detection in EV Batteries Via Hybrid method: Cell-to-Cell Variation Pattern And Physics-Based Model insights.2026-01-0391To be published on 04/07/2026
This study presents a distinct methodology for the early detection of faulty cells in electric vehicle (EV) battery systems, leveraging temporal voltage deviation patterns under real-world charging scenarios alongside outputs from a physics-based model. A comparative longitudinal analysis was conducted on a fleet of ten EVs—five exhibiting stable performance and five demonstrating early-stage anomalies characterized by intermittent transitions from drive to neutral mode. These behavioral cues were investigated as precursors to deeper battery degradation. The analysis focused on cell-level voltage dispersion during the mid-to-high state-of-charge (SoC) range (approx. 20–30% to full charge). Vehicles in healthy condition consistently displayed minimal voltage differentials among cells, whereas those with latent faults showed markedly higher variance, particularly between the highest and model-expected voltages. Notably, this voltage divergence was often accompanied by a modest yet
Jawle, Bharat Sanjay, Selvakumar, Ashwin, Puttoji Rao, Nagaraj Kumar
Low-voltage electric vehicle with increased electrical safety and distributed charging system2026-01-0396To be published on 04/07/2026
Abstract - Reducing the high-voltage BEV to a household level of 120-240 volts is considered in the article as an effective means of solving the problems of electrical safety, maintenance and minor repairs of an electric vehicle in household conditions, distributed power supply of BEV with walking distance for the driver. The analysis of the low-voltage electric drive is performed under the assumption that the battery has a nominal voltage of 200 volts. The issues of transforming a high-voltage machine (400 volts) into a low-voltage one (200 volts) by switching the stator phase sections from serial to parallel connection without changing the overall and energy characteristics are considered. It is shown that a two-motor unit with induction machines with a capacity of 50 kilowatts can provide 100 kilowatts in long-term and up to 200 kilowatts in peak modes. The article considers the issues of implementing a low-voltage inverter and modern trends in distributed power supply for BEVs
Smolin PhD, Victor, Sobolevskiy, Anatoliy, Volovich, Georgy
From LLM to Deep Learning: Efficient Simulation of Last-Mile Energy Behavior in Campus Communities2026-01-0461To be published on 04/07/2026
Communities are critical nodes in the urban energy network, integrating energy, transportation, and building systems to enhance overall energy efficiency. Accurate management of these systems depends on characterizing individual energy-demand behaviors. However, traditional last-mile behavioral models often fail to capture the complex and non-linear nature of human decision-making, creating a need for advanced simulation techniques. Although agent-based simulations powered by Large Language Models (LLMs) have demonstrated considerable efficacy across diverse domains, their substantial computational demands—specifically in terms of token consumption—pose pronounced constraints in large-scale simulations involving tens of thousands of agents, considerably limiting their practical applicability. To address this challenge, a deep learning-based approach is proposed for single-step prediction of last-mile behavior. A hybrid architecture, consisting of an MLP encoder and a Transformer
Yang, Zhifeng, Chen, Yongjian, Ou, Shiqi(Shawn)
Techno-economic assessment of battery recycling and cascade use for legal and illegal recyclers in China2026-01-0456To be published on 04/07/2026
With the strong momentum of electric vehicles (EVs), the battery recycling industry is undergoing rapid growth. While the Chinese government has implemented a white-list mechanism under which only approved recyclers are allowed to process retired batteries, small-scale illegal battery recycling vendors have posed a serious challenge. This study compares the techno-economic performance of battery recycling between legal and illegal recyclers in China, and makes recommendations to eliminate illegal operations. Our research covers two battery chemistries: lithium nickel-manganese-cobalt oxide (NMC) and lithium iron phosphate (LFP), as well as two technological pathways: resource recycling and cascade utilization. For the general case, the costs of illegal vendors are 35-46% lower than that of legal companies. Although legal companies achieve high resource utilization, their overall economic performance lags behind due to their high costs associated with equipment, environmental protection
Du, Shilong, Li, Haoyang, Dou, Hao, Hao, Han
Enabling Sustainable E-Mobility: An Edge–Cloud Collaborative Framework for Battery Lifecycle Health Management in Electric Vehicles2026-01-0460To be published on 04/07/2026
The rapid adoption of electric vehicles (EVs) is a cornerstone of the transition to sustainable transportation. However, uncertainty regarding battery degradation remains a significant obstacle, hindering vehicle energy efficiency, operational safety, and the recovery of end-of-life value. Accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are therefore critical for sustainable vehicle lifecycle management. This study proposes an edge–cloud collaborative intelligent framework for in-vehicle deployment that leverages a Transformer-based architecture to jointly model SOH and RUL. The cloud-side model retains the full configuration to capture long-term degradation trajectories for high-accuracy RUL prediction. A lightweight edge-side model, engineered via pruning and knowledge distillation, delivers millisecond-level inference for real-time SOH estimation onboard the vehicle. To ensure efficiency, only four core health indicators are
Gao, Weimin, Lv, Zhilong, Ou, Shiqi(Shawn)
Evaluating the Impact of Drag Coefficient Changes on Driving Energy Using a Probability Distribution Model of Yaw Angle Based on Empirical Data from North American Highways2026-01-0615To be published on 04/07/2026
This study estimates the impact on driving energy of differences in aerodynamic characteristics for yaw angle from natural wind during North American Highway mode driving. A previous study[1] clarified the potential to estimate the fuel consumption impact of natural wind by integrating the CD yaw characteristics and yaw angle occurrence frequency. The natural wind was measured on a vehicle while driving a representative North American Highway test course[2]. The driving energy is predicted from the obtained yaw frequency and CD yaw sweep data in a wind tunnel. Measurements were conducted every weekday for 8 hours in 2023, covering 70% of the traffic volume. The validity of the measurement period was evaluated by the deviation from the annual average of wind direction and speed. Since yaw frequency varies depending on the road environment, it is necessary to weight the road environment type frequency when calculating the driving energy. The frequency was calculated using machine
Onishi, Yasuyuki, Nucera, Fortunato, Nichols, Larry, Metka, Matt
Navigation Integrated End-to-end Path Planning Development and Vehicle Testing2026-01-0032To be published on 04/07/2026
In order to achieve fully autonomous driving, point to point autonomous navigation is the most important task. Most existing end-to-end models output a short-horizon path which makes the decision process hard to interpret and unreliable at intersections and complex driving scenarios. In this research, we build a navigation-integrated end-to-end path planner on top of an openpilot open source model. We created a navigation branch that encodes route polyline geometry, distance-to-next-maneuver, and high-level instructions and combines with path plan branch using residual blocks and feed-forward layers. By adding minimal parameters, new model keeps the original openpilot tasks unchanged and have the path output based on the navigation information. The model is trained on diverse urban scenes and lighting conditions, and it shows improved route adherence in vehicle testing. The proposed model is validated in a comma 3x device installed on a 2025 Nissan Leaf test vehicle. The road test
Wang, Hanchen, Li, Taozhe, Hajnorouzali, Yasaman, Burch, Collin, li, Victoria, Tan, Lin, Arjmanzdadeh, Ziba, Xu, Bin
Adaptive Torque Vector Control for Distributed Drive Intelligent Electric Vehicles Using Model and Data Driven Approaches2026-01-0628To be published on 04/07/2026
To effectively improve the performance of chassis control of distributed drive intelligent electric vehicles (EVs) under difference road conditions, especially in combing road information and chassis control for improving road handling and ride comfort, is a challenging task for the distributed drive intelligent EVs. Simultaneously, inaccurate chassis control and uncertainty with system input, are always existing, e.g., varying road input or control parameters. Due to the higher fatality rate caused by variable factors, how to precisely chose and enforce the reasonable chassis control strategy of distributed drive intelligent EVs become a hot topic in both academia and industry. To issue the above mentioned, an adaptive torque vector hierarchical controller based on road level and adhesion is proposed, which optimizes the comprehensive. First, combined with the characteristic of the unbalance dynamic force caused by the air gap between the stator and the rotor of the in-wheel motor, a
Wang, Zhenfeng, Zhao, Gaoming, Zhang, Zhijie, Zhou, Zitao, Huang, Taishuo, Ma, Changye
A Latent Space Framework for Modeling Transient Engine Emissions Using Joint Embedding Predictive Architectures2026-01-0423To be published on 04/07/2026
Accurately modeling exhaust emissions during transient events, such as rapid acceleration and deceleration, remains a long-standing challenge in the automotive field and is a prerequisite for real-time control and optimization in modern powertrain systems. The nonlinear emission behavior is difficult to capture, and early mathematical models frequently relied on approximations that limited their accuracy. With the rise of data-driven methods, especially deep neural networks, including multilayer perceptrons and long short-term memory (LSTM) networks, modeling capabilities have improved significantly. However, to achieve meaningful accuracy, these models often require deep architectures, which increase computational load and inference time. This makes their application in real-time control systems challenging, as controllers must run at high sampling rates while maintaining accuracy, which is often a contradictory requirement. This paper addresses the trade-off with a new framework
Sundaram, Ganesh, Gehra, Tobias, Ulmen, Jonas, Heubaum, Mirjan, Görges, Daniel, Günthner, Michael
A System-Level Calibration Framework for Embedded Vision: Integration of Sensor, Firmware, and Software Enhancements2026-01-0013To be published on 04/07/2026
Embedded vision systems are essential for contemporary applications, including robotics, advanced driver assistance systems (ADAS), and intelligent surveillance; yet they frequently experience diminished image quality due to resource constraints, environmental variability, and inconsistent illumination conditions. Such degradations impact multiple visual attributes-sharpness, contrast, color accuracy, noise levels, and structural similarity-that are critical for reliable perception in safety- and performance-driven domains. This study introduces a comprehensive system-level calibration architecture that integrates three coordinated layers: sensor-level adjustment, firmware optimization, and adaptive software enhancements. At the sensor level, exposure control, gain tuning, and white balance adjustments mitigate luminance imbalance and color shifts under changing light conditions. Firmware optimization leverages image signal processor (ISP) parameters to reduce temporal and spatial
Indrakanti, Rama Kiran Kumar, Vishnoi, Nitin, Kamadi, Venkata
Sensor Fusion Method for In-Cabin Humidity Prediction2026-01-0131To be published on 04/07/2026
Maintaining optimal in-cabin humidity levels is part of occupant comfort, air quality, and the effective operation of climate control systems, particularly for functions like windshield defogging. This paper introduces a novel sensor fusion methodology for predicting in-cabin humidity distribution without dedicated humidity sensor. The proposed approach leverages readily available vehicle data, integrating information from ambient temperature sensors, in-cabin temperature sensors, occupant detection systems, window status, and climate control settings. By intelligently fusing these diverse data streams, a predictive model is developed to infer the dynamic humidity conditions within the vehicle cabin. We discuss the complex interactions between these parameters, such as the moisture contribution from occupants, the influence of external air ingress through open windows, and the dehumidifying or humidifying effects of the Heating, Ventilation, and Air Conditioning system. The paper
Ghannam, Mahmoud, Schroeter, Robert, Shaik, Faizan
An Efficient Approach to Key Negotiation in an Automotive Environment2026-01-0087To be published on 04/07/2026
Negotiating Keys for applications such as message authentication within a vehicle presents many problems as, in designing the algorithm; the algorithm must be able to be utilized by small, fixed-point processors. In addition, if there is a desire to do this algorithm in the manufacturing environment, there are severe time constraints placed on how long this algorithm can take, as there are strict station time requirements, which are expensive to change, and any time utilized in the plant can negatively affect vehicle throughput. Additionally, negotiating these keys between many ECUs can greatly increase the time required to negotiate a common key using standard multi-party Diffie-Hellman. Timing would also be an issue in the case of using pair-wise Diffie-Hellman for encryption and distribution of keys utilizing a key master. To solve these problems in multi-party key negotiation, we have utilized the Elliptic Curve variation of the Burmester-Desmedt (ECBD) algorithm. ECBD is
Van Dam, Theo, Mazzara, Bill
THE IN-VEHICLE CONNECTIVITY FOUNDATION POWERING AUTONOMOUS DRIVING2026-01-0009To be published on 04/07/2026
Achieving full vehicle autonomy is not just about adding sensors or compute-it requires a fundamental shift in how vehicles are architected. Autonomous systems rely on higher-resolution sensors, massive processing power, and the ability to fuse data from multiple sources in real time. Centralized in-vehicle architectures, which consolidate computing and enable sensor fusion, place unprecedented demands on connectivity. Precise time synchronization across all systems becomes critical, as does advanced control to ensure safe and reliable operation. Any delay or data loss can impact decision-making, making robust, resilient communication links essential. High-performance connectivity is the backbone of this evolution. It must deliver the highest bandwidth to handle massive streams of sensor data, support long-reach connections across the vehicle, and maintain error-free performance even in the most challenging electromagnetic environments. This combination of speed, reach, and reliability
Shwartzberg, Daniel
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