Browse Topic: Architecture

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Dynamic Prime Mover Management for Enhanced Energy Efficiency in Electric Tractors2026-26-0185To be published on 01/16/2026
Electric tractors present unique opportunities for efficient power management by decoupling traction and auxiliary loads. In the proposed system, two independent electric motors are employed: one dedicated to vehicle traction and the other to drive the power take-off (PTO) and hydraulic functions, including steering and auxiliary attachments like loaders. Hydraulic flow demand directly impacts operational productivity; traditionally, hydraulic flow is linked to engine speed, requiring frequent manual adjustments. This paper proposes an innovative dynamic control strategy that optimizes motor speed based on real-time application demands, introducing three distinct modes: Low Idle Mode, Loader Mode, and PTO Mode. The Vehicle Control Unit (VCU) at the heart in coordination with the Farm Machinery Control Unit (FMCU) and Motor Control Unit (MCU), dynamically selects the appropriate mode based on user inputs such as PTO activation and joystick controls Low Idle Mode minimizes energy usage
Natarajan, Saravanan, P, Shanmugavel, M, Rojer, Joshi, Priyanka, sundaram, Pavithra
High Voltage Safety for Electric Vehicles from Standards Perspectives2026-26-0188To be published on 01/16/2026
With rise of EV adoption globally, electrical system of EV's are continuously moving towards higher voltage for enabling fast charging capabilities and addressing efficiency. High Voltage electrical safety is a crucial part of safety standards for Electric Vehicles. There are several challenges, when any electrical system operating in High voltage region. This is posing risk for user, it means from design stage these systems should be designed in such a way for safeguarding user. These electric safety concepts are already mapped through different safety standards. In this paper, this high voltage safety related test and functional & constructional requirements will be explored through different EV standards and finally a comparatively analysis carried out.
BHATESHVAR, YOGESH KRISHAN, Mulay, Abhijit B, Santosh Jambhale, Medha, Patil, Sanjay
Lightweight AI Deployment for Legacy Automotive ECUs: A Practical Optimization Approach2026-26-0663To be published on 01/16/2026
Automotive systems are increasing adopting data-driven and intelligent functionality in the areas of predictive maintenance, virtual sensors and diagnostics. This has led to a need for the AI models to be directly run on vehicle ECUs. However, most of these ECUs – especially those in cost-sensitive or legacy platforms lack the computational capacity and parallel processing support required for standard AI implementations. Given the stringent real-time and reliability requirements in automotive environments, deploying such models presents a unique challenge. This paper proposes a practical methodology to optimize both the training and deployment phases of AI models for low-computation ECUs that operate without parallelism. Designing lightweight model architectures, using pruning and quantization techniques to minimize resource utilization, and putting in place a strategy appropriate for single-threaded execution are the three main objectives of the developed approach. The goal is to
Sharma, Sahil, Mathew, Melvin
Self-supervised diagnostics & prognostics framework for predictive maintenance in electric vehicles2026-26-0673To be published on 01/16/2026
Predictive maintenance is essential for enhancing the reliability, safety, and operational efficiency of connected vehicles. However, traditional supervised learning approaches for fault prediction depend heavily on large, labeled datasets of failure events, which are often scarce and expensive to obtain in real-world automotive environments. This paper proposes an original self-supervised anomaly detection framework that predicts emerging failures using only healthy operational data, eliminating the need for explicit failure labels. The approach employs self-supervised pretext tasks, such as masked signal reconstruction and future telemetry prediction, to learn robust representations of normal multi-sensor behavior (e.g., temperature, pressure, current, vibration). An unsupervised anomaly detection model then identifies deviations from these learned patterns. This integrated with data-informed predictive models enable early detection of faults across critical subsystems such as
Kumar, Pankaj, Deole, Kaushik, Hivarkar, Umesh
Conceptual Framework for Real-Time Battery Health Estimation in Automotive Digital Twins Using Reinforcement Learning2026-26-0658To be published on 01/16/2026
The explosive growth of electric vehicles (EVs) calls forth the need for smart battery management systems that can perform health monitoring and predictive diagnostics in real-time. The conventional battery modeling methods mostly do not cover the complicated, dynamic behaviors coming from different usage patterns. The study outlines a structure that would use Reinforcement Learning (RL)-based AI agent as a part of the Battery Electrical Analogy (BEA) simulation platform. With the help of the AI agent, different health parameters such as State of Health (SOH), State of Charge (SOC), and the signs of early thermal runaway can be predicted in real-time. The suggested design takes advantage of the simulation-based approach to have the agent learn and utilizes a decentralized cloud architecture suitable for scaling and reducing the response time. The RL agent performs an essential role in the process by tagging along with the continuous learning and the adjustment of the battery conditions
Pardeshi, Rutuja Rahul, KONDHARE, MANISH, Sasi Kiran, Talabhaktula
Evaluation of critical ignition coil parameters for an application On naturally aspirated gasoline engines2026-26-0589To be published on 01/16/2026
Today’s internal combustion engines require highly efficient combustion systems to meet stricter emission and fuel economy regulations. To fulfil to these requirements the ignition system of a gasoline engine plays a critical role. Along with ensuring that it meets the ignition characteristics across all engine operating conditions, it is also possess challenges like to comply with certain On-Board Diagnostics (OBD) norms .To meet these demands modern gasoline engines use inductive type ignition coils which are directly installed at the cylinder head above the spark plug. These ignition coils generate high voltage to produce a certain amount of spark energy and primary coil current which are necessary to meet the targets. However, it has been observed that in a traditional inductive type ignition coil system the ignition coil operating temperature can be a major limiting factor as it cannot exceed a maximum upper limit. The work described in this paper details the various systematic
Ghadge, Ganesh Narayan, Hosur, Viswanatha
Next-Gen Automotive: Enablers and Monetization for Automotive SaaS and Software Defined Vehicles2026-26-0687To be published on 01/16/2026
The automotive industry is undergoing a paradigm shift, changing its model from hardware-centric products to software-driven platforms. It is driven by two underlying paradigms: the emergence of Software-Defined Vehicles (SDVs) and the increasing adoption of Automotive Software-as-a-Service (SaaS) models. Together, these trends are transforming the way the industry generates value, engages with customers, and builds new revenue models. This research examines the most important technical pillars underpinning next-generation automotive ecosystem creation. Of these pillars, centralized computing infrastructures, embedded cloud integration, efficient over-the-air (OTA) update engines, and enhanced cybersecurity models designed to protect larger numbers of connected vehicles are observed. It also evaluates the imperative significance of digital identity management to provide improved personalized experience, the critical role of edge computing to ensure real-time processing, and the promise
Saini, Gourav, Jahagirdar, Shweta, Khandekar, Dhiraj Baburao
Reducing Risk in Safety Critical Systems through Early Safety Case Development and Dialectic Arguments2026-26-0044To be published on 01/16/2026
The rapid evolution of modern automotive systems—powered by advancements in autonomous driving, and connected vehicle technologies— pose fundamental challenges to design and integration. Ensuring the safety of these highly interconnected, software-driven systems, with the widespread reuse of components across platforms. This growing complexity calls for a more structured and rigorous approach to safety assurance than traditional methods. Traditional safety cases tend to take a linear, justification-focused approach that mainly focuses on positive assertions —statements of compliance or success—while giving limited attention to potential weaknesses, or gaps in supporting evidence. This practice may lead to criticism that such arguments are “too positive,” portraying an overly optimistic view of system safety without sufficiently acknowledging areas of unresolved risk. As a result, conventional approaches for developing safety case may overlook complex interactions, assumptions, and
Kumar, Amrendra, Bagalwadi, Saurabh, McMurran, Ross
Virtual ECU: Development & Validation Platform2026-26-0683To be published on 01/16/2026
Vehicle software is moving towards software-centric architectures and hence software-defined vehicles. With this transition, there is a need to handle various challenges posed during development and validation. Some of the challenges include unavailability of hardware limiting the evaluation of various hardware options, board bring-up and hence leading to delays in software development targeted for the hardware, eventually leading to delayed validation cycles. To overcome the above challenges, we present in this whitepaper a virtual ECU (vECU) framework integrated with a CI/CD pipeline. A Virtual ECU (Electronic Control Unit) is a software-based emulation of a physical ECU. The adoption of virtual ECUs empowers development teams to commence software development prior to the availability of physical hardware. Multiple tools are available to demonstrate virtual ECUs, for example, QEMU, Synopsys, QNX Cabin, etc. vECU setup, when paired with a CI/CD pipeline, allows continuous integration
Singh, Jyotsana, Shaikh, Arshiya, Mane, Rahul, Burangi, Piyush
Powering the Future: Addressing Power Architecture bottlenecks in Next Gen Automotive Platforms.2026-26-0688To be published on 01/16/2026
As the automotive industry moves from conventional function oriented embedded ECU-based systems to Code-driven system, the core electrical and electronic (E&E) architecture is also being redesigned to support more software-driven functionality. Modern and centralized architectures promise scalability and software-driven flexibility, but they also introduce significant challenges in power distribution-an area that remains underexplored despite its critical role in overall vehicle safety and performance. Our paper aims at the adoption of the traditional power distribution approach for Next Gen vehicle architecture. It requires a fresh look at how power is distributed. In a novel E&E architecture, a single power harness supplies battery voltage to each zone. If there's a failure or voltage drop, it can affect multiple functions within that zone at once, and management of voltage regulation, thermal dissipation, and EMI/EMC compliance becomes crucial. Adding to the complexity, safety
Borole, Akash, CHAKRA, PIPUN, Warke, Umakant
Do Not Let the Door Hit2026-26-0026To be published on 01/16/2026
Modern vehicles are equipped with numerous safety systems focused primarily on active and passive crash protection, but less attention is given to low-speed or stationary scenarios: particularly when occupants exits the vehicle. One common and often underestimated risk occurs when the vehicle door is opened without awareness of nearby obstacles such as walls, poles, or other vehicles. This paper introduces a novel, intelligent solution aimed at enhancing safety during driver egress. The proposed system leverages the existing ORVM (Outside Rear View Mirror) cameras to monitor and measure the surface area adjacent to the vehicle. When the vehicle is parked and the engine is turned off, the system becomes active. As the driver initiates the exit, the system scans for obstructions near the door. If an obstacle is detected within a predefined danger zone, it projects a warning symbol on the Instrument cluster via the puddle lamp and triggers an audible chime to alert the occupant. This dual
Bhuyan, Anurag, Khandekar, Dhiraj, Jahagirdar, Shweta
A strategic approach to the selection of switchgear and busbars for EV battery packs2026-26-0165To be published on 01/16/2026
With the rising adoption of electric vehicles (EVs), the need for robust and efficient power distribution systems has become increasingly important. This paper outlines a strategic method for selecting switchgear and busbars in EV battery packs, emphasizing key factors such as safety, energy efficiency, thermal control, and future scalability. Proper optimization of these components can significantly improve performance, minimize power losses, and ensure durability under demanding operating conditions. The design and selection of battery conducting components, such as switchgears and busbars, are typically based on the maximum continuous and peak current capabilities of the EV battery pack. While this approach ensures that the components can withstand extreme conditions, it often leads to over-engineering, resulting in unnecessary costs and added weight. However, this method overlooks the dynamic power demands of the vehicle, which fluctuate based on driving conditions and usage. Real
Soman, Anu, satheesh, Goutham, K, Mathankumar
Design of the BIW structure for battery pack protection in case of side pole impact.2026-26-0025To be published on 01/16/2026
Electric vehicles (EVs) are becoming more popular than Internal Combustion Engine (ICE) powered vehicles, but their battery and motor components elevate their Gross Vehicle Weight (GVW), posing unique collision risks. Manufacturers strategically mount the high voltage (HV) battery packs under the passenger compartment to lower the Centre of Gravity and shield them from the front impacts. However, side impacts remain a concern, as the battery deformation in such instances could trigger fires or explosions, endangering occupants. To address this, crashworthiness designs adhere to New Car Assessment Program (NCAP) standards, particularly against side pole impact and side mobile barrier impact. Unlike the frontal section of BIW, which typically has larger crush space to absorb the crash energy, extensive design attention is required to the vehicle's side structure to absorb pole impacts without transmitting excessive force to the battery pack. Utilizing aluminium extrusions and sheet
Nivesh, Dharun, NAMANI, Prasad, Ramaraj, Rajasekar
Cybersecurity in Automotive OTA Update Systems and Software Store2026-26-0621To be published on 01/16/2026
Automotive Over-the-Air (OTA) software updating has become a cornerstone of the modern connected vehicle, enabling manufacturers to remotely deploy bug fixes, security patches, and new features. However, this convenience comes with significant cybersecurity challenges. This paper provides a detailed examination of automotive OTA update security and the associated software store (software Applications & services store) mechanisms. I discuss the current industry standards and regulations - notably ISO/SAE 21434 and the United Nations Economic Commission for Europe (UNECE) regulations UN R155 (cybersecurity) and UN R156 (software updates) - and explain their relevance to secure OTA and software update management. I then explore the Uptane framework, an open and widely-adopted architecture specifically designed to secure automotive OTA updates. Next, OTA-specific threat models are analyzed, detailing potential attack vectors (such as malicious update injection, man-in-the-middle attacks
Kurumbudel, Prashanth Ram
Unlocking Edge AI in Software-Defined Vehicles: Balancing model complexity, compute resources, and data access2026-26-0686To be published on 01/16/2026
The potential of Edge AI in automotive goes beyond ADAS and automated driving. AI-driven optimizations in driving efficiency, in-cabin personalization, predictive maintenance, and enhanced safety require intelligent processing at the vehicle edge. However, integrating AI into current vehicle electrical/electronic architectures (EEAs) presents significant challenges. This paper examines how AI models can run on general-purpose ECUs, gateways, and domain controllers while balancing model complexity, compute resources, and data availability. We explore trade-offs, architectural choices, and the need for software configurability to ensure AI models evolve with new data and vehicle parameters. We conclude by providing a glimpse into Sonatus’ latest AI product that encapsulates a holistic approach optimized for vehicle platforms—spanning cloud-based model development, optimization, and validation to in-vehicle inference—that unlocks the potential of Edge AI and SDVs for the automotive
Sah, Mohamadali, Khatri, Sanjay
A Scalable ArTOP-Based In-House Toolchain for Automated AUTOSAR Configuration2026-26-0682To be published on 01/16/2026
The rising software complexity in Automotive industry demands reusable, hardware-agnostic development frameworks. AUTOSAR (Automotive Open System Architecture) provides a standardized, scalable ECU software architecture but cost-effective tooling and modern workflows are critical for broad adoption and competitiveness. One such area is for AUTOSAR configuration and authoring of Autosar architecture. Current solutions include commercial offerings which are often built on top of ARTOP (ArTOP is an eclipse-based ecosystem maintained by AUTOSAR consortium) and open-source python implementations. Commercial tools are prohibitive in cost, have complicated development workflows, are difficult to automate and lack quick integration with other tools. Python-based solutions are often community driven with small developer teams and face many challenges. These tools are not mature enough, have staggered development, security concerns, liability issues, lack of approvals etc. These libraries do not
Daware, Kartik, Garg, Mudit, Pasupuleti, Raju
Simulation-Driven Load Spectrum Prediction_ Virtual RLDA for Chassis and Suspension System2026-26-0095To be published on 01/16/2026
In the rapidly evolving and highly competitive automotive industry, manufacturers are under immense pressure to bring products to market quickly while meeting customer expectations. As a result, optimizing the product development timeline has become essential. Structural integrity analysis for chassis and suspension systems lies in the accurate acquisition of operational load spectra, conventionally executed through Road Load Data Acquisition (RLDA) on instrumented vehicles subjected to proving ground excitation. At this point, RLDA is mainly used for final validation and fine-tuning. If any performance shortfalls, such as premature component failure or durability issues, are discovered, they often trigger design revisions, prototype rework, and additional testing This study proposes a Virtual Road Load Data Acquisition (vRLDA) methodology employing a high-fidelity full-vehicle multibody dynamic (MBD) representation developed in Adams Car. The system is parameterized and uses high
Goli, Naga Aswani Kumar, PRASAD, TEJ PRATAP
Monitoring and Diagnosing Software-Defined Vehicle Architectures2026-26-0677To be published on 01/16/2026
Software-Defined Vehicles (SDV) are fostered through initiatives like SOAFEE and Eclipse SDV promoting the use of cloud-native approaches, distributed workloads and service-oriented architectures (SOA). Vehicles are connected to the cloud and functions are partially executed in the cloud and the vehicle. However, these approaches do not provide solutions for monitoring and diagnosing SDVs neither on-board nor off-board. Given the cost-sensitive nature of vehicles, OEMs are unlikely to allocate significant resources to diagnostics. Consequently, conventional data centre monitoring strategies, which rely on transferring large datasets to dedicated servers, are not directly applicable to vehicles. The paper describes a SOA used in research for several years where each vehicle functionality is implemented by independent services with an orchestrator for managing them. ASAM SOVD (ISO 17978) specifically supports diagnosing SDVs by providing functionality beyond UDS, such as access to log
Böhlen, Boris, Fischer, Diana
High-Performance Computing for Software-Defined EV Powertrains: Design and Real-Time Validation with NXP S32E278 Domain Controller2026-26-0684To be published on 01/16/2026
Software-Defined Vehicles (SDVs) are redefining the automotive landscape by decoupling hardware from software and enabling dynamic, over-the-air updates, advanced control strategies, and real-time decision-making. To support this transformation, EV powertrain systems require high-performance computing (HPC) platforms capable of real-time control, data processing, and cross-domain communication. This paper introduces a fully SDV-compatible EV powertrain architecture built around the NXP S32E278 domain controller, which integrates a multi-core, lockstep-enabled processor specifically designed for zonal control and automotive functional safety. To meet the bandwidth and latency demands of modern SDV applications, the system replaces conventional CAN-based communication with automotive Ethernet, enabling gigabit data transfer, Time-Sensitive Networking (TSN), and low-latency coordination across software-defined control domains. The S32E executes critical functions such as field-oriented
Pawar, Ganesh, Inamdar, Sumer Deepak, Kumar, Mayank, Deosarkar, Pankaj, Tayade, Nikhil, Kanse, Dattatray, Chopade, Vipul
Real-Time In-Cabin Vital Sensing and Emergency Response Using Ultra-Wideband Radar in Automotive Environments2026-26-0012To be published on 01/16/2026
This study introduces a novel in-cabin health monitoring system leveraging Ultra-Wideband (UWB) radar technology for real-time, contactless detection of occupants' vital signs within automotive environments. By capturing micro-movements associated with cardiac and respiratory activities, the system enables continuous monitoring without physical contact, addressing the need for unobtrusive vehicle health assessment. The system architecture integrates edge computing capabilities within the vehicle's head unit, facilitating immediate data processing and reducing latency. Processed data is securely transmitted via HTTPS to a cloud-based backend through an API Gateway, which orchestrates data validation and routing to a machine learning pipeline. This pipeline employs supervised classifiers—Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF)—to analyze features such as temporal heartbeat variability, respiration rate stability, and energy distribution patterns
Singh, Samagra, Pandya, Kavita, Jituri, Keerti
Automotive Cybersecurity Regulatory Framework2026-26-0625To be published on 01/16/2026
During the last few years, cybersecurity has become one of the key aspects in the automotive industry to ensure the safety and security of vehicles throughout their lifecycle. The implementation of new technologies and the goal of deploying fully automated vehicles in the not-so-distant future have created new needs regarding vehicle safety. As the automotive industry shifts toward automated and connected vehicles, the possibility of cyberattacks emerges as a significant concern. To address these challenges, different regulatory bodies and governments worldwide have developed or are developing a new set of regulations and standards with varying approaches to legislate or standardize the minimum criteria that manufacturers must follow to ensure security against potential attacks, adding requirements to ensure the cybersecurity of the vehicles at all levels. At the United Nations level, UN Regulation 155 was introduced in 2021, establishing requirements for manufacturers' cybersecurity
Flix, Oriol, Lujan Tutusaus, Carlos, Hidalgo, Justin
RAKSH: A Blockchain Derived In-Vehicle Key Management System2026-26-0620To be published on 01/16/2026
Modern cars have advanced significantly with the rapid growth of connectivity and communication technologies. In the wake of rising cyberattacks and enforcement of regulations, implementation of cybersecurity is imperative to safeguard vehicles. The cybersecurity controls such as secure boot, secure updates, secure communication require cryptographic primitives (keys/certificates). These security features are largely dependent on robust Key Management System (KMS), as keys are the sensitive assets that must be protected throughout the lifecycle of vehicle. Several security critical applications like over-the-air and car-to-car interaction essentially needs robust KMS to protect the vehicle assets from expanding attack vector. Traditionally KMS is established centrally in a backend server. The cloud based KMS is becoming complex due to increased number of keys/certificates required to provision in a vehicle. We propose a self-governing in-vehicle key management system for a gateway
Goyal, Yogendra, Sutar, Swapnil, Jaisingh, Sanjay
MOSAIC-TARA: A Comprehensive TARA Methodology for Automotive Cybersecurity2026-26-0609To be published on 01/16/2026
Threat Analysis and Risk Assessment (TARA) is a continuous activity, acting as a foundation of cybersecurity analysis for electrical and electronics automotive products. Existing TARA methodologies in the automotive domain exhibits challenges due to redundant and manual processes, particularly in handling recurring common assets across Electronic Control Units (ECUs) and functional domains. Two primary approaches observed for performing TARA are Manual-Asset-Centric TARA and Catalogue-Driven TARA. Manual-Asset Centric TARA is constructed from scratch by manually identifying the assets, calculating risks by likelihood, and impact determination. Catalogue-Driven TARA utilizes the precompiled likelihood and impact against identified assets. Both approaches lack standardized and modular mechanisms for abstraction and reuse. This results in poor scalability, increased efforts, and difficulty in maintaining consistency across vehicle platforms. The proposed method in this research overcomes
Goyal, Yogendra, Sinha, Swati, Sutar, Swapnil, Jaisingh, Sanjay
Considerations for Vulnerability Management in the Automotive Industry2026-26-0626To be published on 01/16/2026
With the emergence of Software-Defined Vehicles (SDVs), more complex software and connectivity technologies are introduced to support new advanced use cases. These use cases include, e.g., phone as a key, smart parking, summon vehicle, remote diagnostics and vehicle management. However, complex software functionality and external connectivity also increase the attack surface of vehicles and its ecosystem. As such we have seen various cybersecurity attacks targeting vehicles and OEM backends in the past few years. In this paper, we first perform a classification of recent automotive cybersecurity attacks. We further perform an analysis of these attacks and associated vulnerabilities considering the application of best practices of vulnerability management approaches including Common Vulnerability Scoring System (CVSS), Exploit Prediction Scoring System (EPSS), and Stakeholder-Specific Vulnerability Categorization (SSVC). CVSS is a standardized framework used to assign severity scores to
Oka, Dennis Kengo, Vadamalu, Raja Sangili
Leveraging Telematics Big Data Analytics for Real-Time Monitoring of Catalytic Converter Failures and Root Cause Identification for Emission Compliance2026-26-0591To be published on 01/16/2026
The automotive industry is continuously evolving at high pace to meet rising customer expectations, reliability, reduced maintenance, and most relevant, compliance with stringent emission norms. Traditionally, the analysis of vehicle emissions relies heavily on periodic inspections and manual checks. These conventional methods are often time-consuming, prone to human error, and lack the ability to provide real-time insights. Also, identifying Catalytic converter failures due to non-manufacturing issues require meticulous physical inspections and historical data reviews, which are not always accurate or timely. Telematics or Connected cars technology being one of the major technological innovations in recent times revolutionizes these processes by enabling real-time data exchange between vehicles and external systems. The current study presents an innovative approach to utilizing telematics data for real-time monitoring of vehicle emissions and pinpointing Catalytic converter failures
DEV, Triyambak, Prasad, Kakaraparti Agam, Kalkur, Varun, Modak, Saikat, AGARWAL, Shashank, Chandra, Animesh, Paul, Varsha, Garg, Amit, Sundararaman, Venkataraman, Bose, Sushant
Review on the flyback converter design for multi-output2026-26-0200To be published on 01/16/2026
With the increasing demand for DC loads, DC-DC converters have become indispensable in modern power electronic architectures. With high-voltage applications typical DC-DC converter topologies are required which include isolation for safety and voltage level conversion. Among various isolated converter topologies, the flyback converter is widely favored for low-power applications, typically under 100 W, due to its simplicity and cost-effectiveness. Like other DC-DC topologies, the flyback converter can operate in either continuous conduction mode or discontinuous conduction mode (DCM). The work have focused on the design and performance analysis of a flyback converter operating in DCM, with a specific emphasis on magnetic component design and loss evaluation. A 55 W multi-winding flyback converter employing a passive snubber circuit is studied and implemented. The loss analysis is done with switch losses around 3.4W and the coupled inductor core losses around 1.5W and copper losses
S, Denis, Deshpande, Prathamesh Pravin, Deshpande, Rohan
A procedure for validation of full vehicle CAE models with physical tests for passive safety applications2026-26-0411To be published on 01/16/2026
With the fast development of computational analysis tools and capacities during the past ten years, complex and substantial computer-aided engineering (CAE) simulations are now economically possible. While the cost of crash tests has risen steadily, the fidelity and complexity, which numerical simulations could address, has multiplied keeping the cost of computational analysis more stable. The use of CAE simulations complements physical testing, accelerating the product development process, reducing cost, and ensuring safe and more optimized designs. The fundamental goal of CAE is a significant reduction in the number of physical tests conducted during the product development process. However, validating the CAE model with physical tests is essential to ensure accuracy and reliability. Simulations performed using a validated CAE model could be used to make decisions like airbag deployment or high voltage shutdown without an actual physical test. This paper discusses validating an
UPENDRAN, ANOOP
SEooC-Based Design Framework for Integrated EV Power Conversion Systems under ISO 26262 Compliance2026-26-0192To be published on 01/16/2026
The rapid integration of electric vehicle (EV) power conversion elements—such as traction inverters, onboard chargers, and DC-DC converters—into unified architectures poses new challenges for ensuring functional safety compliance as per ISO 26262. This paper presents a system-level framework that leverages the Safety Element out of Context (SEooC) approach to design and validate reusable safety-critical components independent of vehicle-specific applications. By defining clear assumptions of use and ASIL decomposition strategies, the proposed method facilitates early-stage fault analysis and verification. The framework integrates model-based development with Hardware-in-the-Loop (HIL) testing and formal verification techniques to validate both control logic and hardware behavior under diverse fault injection scenarios. The result is a scalable, standards-compliant methodology that reduces time-to-market and enhances reliability in integrated EV power electronics platforms. The work
Uthaman, Sreekumar, Mulay, Abhijit B, Gadekar, Pundlik
Analysis of High voltage fuse failures due to reverse surge currents flow in the Power distribution unit of Electric vehicles2026-26-0182To be published on 01/16/2026
Commercial Electric vehicles are revolutionizing the transportation industries with zero emission, lower noise level and increased efficiency. But, High voltage (HV) fuse failures due to reverse surge currents in the Power distribution unit (PDU) hampers the field operation and raise the sensitive safety concerns. This paper embarks on an in-depth exploration of the Reverse surge current flows from the DC-DC converter and Auxiliary (AUX) inverters high voltage input side to Traction system high voltage input point. Failures of HV fuses can lead to the unintentional shutdown of the e-compressor system and steering motor system while operating the EV, which raises critical safety concerns. If the steering motor fails, the bus will lose power steering assistance, making the steering wheel much harder to turn. If the e-compressor fails, it could result in loss of braking assist. This could make it difficult to stop the vehicle, especially in an emergency situation or when driving at high
Bamania, Mihir, kinjalkar, Milind, Amancharla, Naga Chaithanya, Salunke, Pradeep
An Innovative Crash Sensing System Architecture for Robust functionality of Safety restraints in different Challenging Real World Accident scenarios2026-26-0017To be published on 01/16/2026
Title: An Innovative Crash Sensing System Architecture for Robust functionality of Safety restraints in different Challenging Real World Accident scenarios. Authors: Sunil Kovalam, Harihara Sudhan, Praveen Bansode and Sanjay Gaddamwar Mahindra & Mahindra Ltd Abstract: In the emerging markets especially like India and other similar countries, growing traffic density on the roads leading to different kind of accident types including head on collision, rear end collision, side impact collision and accidents involving with pedestrians or cyclists or two wheelers etc. These accidents could be due to over-speeding, distracted driving and inadequate road infrastructure. Providing necessary safety restraints system (Airbags and Seat belts) and its robust functionality in different real world accident scenarios will be a challenging to vehicle manufactures. It is a high time to redefine the traditional crash sensing architecture strategies with logical approach based on the thorough study of
KOVALAM, SUNIL KUMAR
Totem-Pole PFC and LLC resonant converter based 6.6kW On-Board Charger for LEV Applications2026-26-0160To be published on 01/16/2026
As light electric vehicles (LEVs) gain popularity, the development of efficient and compact on-board chargers (OBCs) has become a critical area of focus in power electronics. Conventional AC-DC topologies often face challenges, including high inrush currents during startup, which can stress components and affect system reliability. Furthermore, DC-DC converters often have a limited soft-switching range under light load conditions, leading to increased switching losses and reduced efficiency. This paper proposes a novel 6.6 kW on-board charger architecture comprising a bridgeless totem-pole power factor correction (PFC) stage and an isolated LLC resonant DC-DC converter. The main contribution lies in the specific focus on enhancing startup behavior and switching performance. In PFC converters, limiting inrush current during startup is crucial, especially with fast-switching wide-bandgap devices like SiC or GaN. Conventional soft-start techniques fall short in of ensuring smooth voltage
Patil, Amruta, Bagade, Aniket
Automotive Cybersecurity: Safeguarding Connected and Autonomous Mobility2026-26-0629To be published on 01/16/2026
As vehicles transform into complex cyber-physical systems within Intelligent Transportation Systems (ITS), automotive cybersecurity has become a foundational pillar in securing safe, reliable, and trustworthy transportation. This paper examines cybersecurity challenges in connected and autonomous vehicles (CAVs), focusing on Vehicle-to-Everything (V2X) communications technologies, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Pedestrian (V2P) and critical systems like electronic control units (ECUs), battery management units (BMUs), and sensor fusion modules. Key vulnerabilities, such as remote hacking, denial-of-service (DoS) attacks, malware injection, and data breaches, threaten vehicle functionality, passenger safety, and privacy. Key protection mechanisms, including encryption, intrusion detection systems (IDS), cryptographic protocols, secure over-the-air (OTA) updates, and Advanced Artificial Intelligence (AI) and Machine Learning (ML
Kumar, Om, Kumar, Rajiv, Sankar M, Gopi, Haregaonkar, Rushikesh Sambhaji
Software-Defined Vehicles: Architecting the Future of Intelligent and Connected Mobility2026-26-0691To be published on 01/16/2026
The rise of Software-Defined Vehicles (SDVs) marks a fundamental shift in automotive design, where software, rather than hardware, defines vehicle capabilities. This review explores the SDV paradigm within Intelligent Transportation Systems (ITS), emphasizing centralized computing, over-the-air (OTA) updates, and service-oriented architectures (SOA). Key enablers such as high-performance computing units, middleware platforms (e.g., AUTOSAR Adaptive), and digital twins support scalable, flexible software deployment and real-time functionality. Artificial Intelligence (AI) and Machine Learning (ML) enhance features like predictive maintenance, driver personalization, and autonomous decision-making. However, SDVs also introduce complex challenges, including software validation, real-time performance, and system interoperability. Cybersecurity becomes critical, especially as vehicles interface with cloud platforms, edge computing, and Vehicle-to-Everything (V2X) networks. The paper also
Ahmad, Aqueel, Hemanth, Khimavath, Kumar, Om, Kumar, Rajiv, Haregaonkar, Rushikesh Sambhaji
Swarm-Inspired Cooperative Mapping for Urban Autonomous Navigation2026-26-0635To be published on 01/16/2026
Urban autonomous vehicles today largely rely on individually built maps or centralized cloud services—both rigid under intermittent connectivity and rapid scene changes (construction, pop-up events). Inspired by how ant colonies collectively explore, we introduce a decentralized protocol: each vehicle broadcasts compressed “map particles” embedded with virtual pheromone values that highlight zones of high uncertainty or recent change. Neighboring vehicles incorporate these signals to prioritize sensing and route planning. A lightweight consensus algorithm merges local graphs into a shared dynamic map, resilient to network splits. The result, a bio-inspired SLAM that enables fleets to adapt on the fly to evolving cityscapes, boosting safety, efficiency, and robustness.
Bhargav, Anirudh S, Subbarao, Chitrashree
Hybrid Topology Selection & Optimization of a Compact SUV to Meet Future CO2 Norms - an Indian Case Study2026-26-0077To be published on 01/16/2026
Rising environmental concerns and stringent emissions norms are pushing automakers to adopt more sustainable technologies. There is no single perfect solution for any market and there are solutions ranging from biofuels, green hydrogen to electric vehicles. For Indian market, especially in the passenger car segment, hybrid vehicles are favoured when it comes to manufacturers as well as with consumer because of multiple reasons such as reliability, performance, fuel efficiency and lower long-term cost of ownership. For automakers planning to upgrade their fleets in the context of upcoming CAFE III (91.7 g CO2 / km) & CAFE IV (70 g CO2 / km) norms, hybridization emerges as the next natural step for passenger cars. Lately, various state governments have also promoted hybrid vehicle sales by offering certain targeted tax breaks which were previously reserved for EVs exclusively. Current study focuses on various parallel hybrid topologies for an Indian compact SUV, which is the highest
Emran, Ashraf, Sandhu, Rouble, Keizer, Ruben, Warkhede, Pawan
Advancing Automotive Radar Characterization: OTA HIL Testing for Enhanced ADAS Safety2026-26-0043To be published on 01/16/2026
The increasing demand for reliable Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies necessitates the precise validation of automotive radar sensors. Traditional on-road testing, while effective, presents challenges such as limited repeatability, high costs, and safety concerns. To address these limitations, this paper introduces an Over-the-Air (OTA) Hardware-in-the-Loop (HIL) methodology for radar characterization, providing a controlled and repeatable lab-based validation approach. This methodology enables dynamic testing of key radar parameters, including range estimation, angle of arrival measurement, Doppler velocity analysis, and object detection accuracy. The proposed setup supports diverse testing scenarios, such as variable target distances, relative speeds, multiple object simulation, and environmental effects, ensuring a comprehensive evaluation of radar behaviour under complex and safety-critical conditions. Through OTA testing, developers can
Jadhav, Tejas, Karle, Ujjwala, Paul, Harshit, SNV, Karthik
Vision Driven Testing Framework for Human-Machine Interfaces: An Automated Approach Using Computer Vision / Machine Learning2026-26-0571To be published on 01/16/2026
Modern automotive infotainment systems and digital instrument clusters require rigorous testing to ensure reliability and compliance with industry standards. Traditional testing methods are labor-intensive and lack scalability. This research proposes a phased, vision-based approach using image processing, machine learning (ML), and computer vision (CV) to enhance testing automation and accuracy. Phase 1 employs open-loop testing using an NVIDIA Jetson Nano with camera modules to capture visual data from infotainment and instrument cluster displays. This phase focuses on the static analysis of visual elements, screen transitions, animations, and error messages. Feature extraction and pattern recognition techniques identify interface behaviors and detect anomalies without a feedback loop. This research will focus in depth on Phase 1, providing a detailed evaluation of its implementation and effectiveness. Phase 2 extends the testing environment with a hardware-in-the-loop (HIL) system
Lad, Rakesh Pramod, Mehrotra, Soumya, Mishra, Arvind
Integration and Proving Ground Evaluation of a Connected Highway Pilot System2026-26-0136To be published on 01/16/2026
Highway Pilot (HWP) systems, classified as SAE Level 3 Automated Driving Systems (ADS), represent a potential advancement for safer and more efficient highway drives. In this work, the development of a connected HWP prototype is presented. The HWP system is deployed in a real test vehicle and designed to operate autonomously in highway environments. The implementation presented in this paper covers the complete setup of the vehicle platform, including sensor selection and placement, hardware integration and communication interfaces for both autonomous functionality and Vehicle-to-Everything (V2X) connectivity. The software architecture follows a modular design, composed of modules for perception, decision-making and motion control to operate in real-time. The prototype integrates Vehicle-to-Vehicle (V2V) communication, such as Cooperative Awareness Messages (CAM), to enhance situational awareness and improve the overall system behaviour. The modular structure allows new functionalities
Domingo Mateu, Bernat, Leiva Ricart, Gisela, Facerias Pelegri, Marc, Perez, Marc
Thermal Management of High-Voltage Connectors using double-layered Phase-Change Materials (PCM)2026-26-0279To be published on 01/16/2026
Abstract: High Voltage cables and terminals are prone to high temperatures and rapid heat generation due to high current ratings, especially in electric vehicles (EVs). If the temperature exceeds a critical limit, danger may be posed to the components which are connected and the overall safety of the passengers. Traditionally, cooling methods are often energy-intensive and rely on active systems, which may not always be practical for high-power applications. Thus, a localized, fast, and reliable passive thermal management methodology that can be retrofitted into existing connector designs through modifications (e.g., enlargement and PCM integration) would provide significant safety enhancement. The material property of phase change materials, which possess high latent heat, has been used to maintain a steady temperature for a period of time. A dual PCM-layer has been incorporated into the design of the high-voltage connector to serve two purposes:1. The first PCM layer (PCM-1), with
Neogi, Angshuman, Shinde, Shardul
Comparative Analysis and Implementation of data streaming methodologies for Vehicle Navigation Mode for Electric Trucks2026-26-0692To be published on 01/16/2026
In the realm of electric truck logistics, optimizing route planning is essential. This paper presents a key navigation feature for analyzing such optimized routes. Integrating map features into the drive mode improves user experience by offering real-time navigation and dynamic route adjustments based on traffic updates, road closures, and vehicle coordinates. This study compares the performance of Server sent events(SSE), web sockets and API polling methodologies, focusing on metrics such as data transmission efficiency, latency, resource utilization, scalability, and reliability. Our findings demonstrate the advantages and limitations of each method, providing insights into their suitability for real-time route optimization in electric truck logistics. The results highlight the potential of SSE in achieving efficient and timely data updates, contributing to more effective route planning and resource management. Additionally, we discuss how API Polling, Web sockets, and SSE each make
Bhandari, Mehul, Kaur, Prabhjot, DADOO, VISHAL, Mahendrakar, Shrinidhi, Ramanaiah, Rachala
Integrated Powertrain Domain Controller Using Wide Band Gap Devices For EV Applications2026-26-0055To be published on 01/16/2026
The rapid evolution of electric vehicles (EVs) has amplified the demand for highly integrated, efficient, and intelligent powertrain architectures. In the current automotive landscape, EV powertrain systems are often composed of discrete ECUs such as the OBC, MCU, DC-DC Converter, PDU, and VCU, each operating in isolation. This fragmented approach adds wiring harness complexity, control latency, system inefficiency, and inflates costs making it harder for OEMs to scale operations, lower expenses, and accelerate time-to-market. This paper addresses the core issue of fragmented control architectures in EV powertrains by proposing an integrated domain controller-based solution for EV powertrain. The technical gap lies in the absence of a centralized intelligence capable of seamlessly managing and synchronizing the five key powertrain aggregates: OBC, MCU, DC-DC, PDU, and VCU under a unified software and hardware platform. This fragmentation leads to redundancy in computation, increased
Kumar, Mayank, Deosarkar, Pankaj, Inamdar, Sumer, Tayade, Nikhil
Electroluminescent Coating Systems for Heavy-Duty Trucks: Advancing Safety and Sustainability through Smart Surface Technology2026-26-0275To be published on 01/16/2026
As the transportation industry pivots towards safer and more sustainable mobility solutions, the role of advanced surface technologies is becoming increasingly critical. This paper presents a novel application of electroluminescent (EL) coating systems in heavy-duty trucks, exploring to enhance safety and environmental impact through lightweight, energy-efficient lighting integration. EL coatings, capable of emitting light uniformly across painted surfaces when electrically activated, offer a transformative alternative to conventional lighting systems and reflective materials. In the context of heavy-duty trucks, these systems can significantly improve visibility under low-light and adverse weather conditions, thereby reducing the risk of road accidents. Furthermore, illumination achieved without bulky fixtures and without interface gaps contributes to aerodynamic efficiency, fuel economy and reducing carbon emissions. use of this coating system, can optimize tooled up plastic part and
Harel, Samarth Dattatraya, Borse, Manoj
Validation of 0D-1D Co-Simulation Strategies in Cold Climate for ‘Full EV Digital Vehicle’2026-26-0448To be published on 01/16/2026
Electric Vehicles is embedded with increased software algorithms coupled with several physical systems. It demands the efficacy of components which are linked together to build a system. The digital models reviewed in this paper are at system-level and full vehicle-level, comprising several components and control design, analysis, and optimization. Systems pertaining to each functionality such as, AC loop, E-Powertrain, HEVC, Cooling system, Battery Management System, Vehicle control system etc. together make an 'Integrated Digital Vehicle'. Fidelity of Intersystem co-simulation [AMESIM + SIMULINK] is key to validate the thermal and energy management strategies. This paper elucidates the correlation of Digital Vehicle compared to Test for Thermal Strategy in different driving scenarios and Energy management. Validation of Digital vehicle with 52kWh, 40kWh High Voltage Battery for Intercity Travel of Customer usage and WLTP for Cold condition of -7degC). Also, to evaluate range
Sarapalli Ramachandran, Raghuveeran, Srinivasan, Rangarajan, Saravanan, Vivek, Dutta, Souham, Pichon, Martin, Leclerc, Cedric, Guemene, Alexis-Scott
NVH Challenges in Head Up Display (HUD) Design for Modern Connected Vehicles: Balancing Performance and Structural Dynamics2026-26-0354To be published on 01/16/2026
A more recent focus on driver comfort and the increasing demand for access to information make automotive OEMs provide advanced features such as Head Up Display systems. Even though HUD projects vital information onto the windshield/glass, its structural integration comes with significant noise and vibration challenges, leading to noisier in-cabin, display instability and haziness. This paper discusses the significant design parameters influencing the in-cabin NVH levels and functional effectiveness of HUD systems. The structure considered for analysis is the HUD assembly and its integration in vehicle. CCB turns out to be the critical component of the vehicle structure susceptible to road excitations although its mass dampens the vibrations inherently, due to the low mass of the HUD, relative oscillation between its projector, mirror, and either the windshield or display causes image distortion. In addition, the fan incorporated to cool the projector possess threat to in-cabin sound
Vardhanan K, Aravindha Vishnu, Titave, Uttam
Introducing a new catalyst family in gasoline aftertreatment2026-26-0231To be published on 01/16/2026
This paper is to introduce a new catalyst family in gasoline aftertreatment. Indeed, it has been shown that under certain driving conditions, three-way catalysts produce significant amounts of toxic NH3 and the strong greenhouse gas N2O, which are both very unwanted emissions. In a self-committed approach, OEMs could want to minimize these noxious pollutants, especially if this can be done with no architecture change, namely without additional underfloor catalyst. In this paper we will compare different approaches: regular underfloor TWC, SCR derived from diesel aftertreatment, gasoline dedicated Ammonia Slip Catalyst (ASC) and especially developed novel gasoline Secondary Emission Treatment (SET) catalyst, providing both ammonia abatement and underfloor three-way functionality. The data will show that SCR only reduces NH3 from a passive SCR reaction in a limited amount in the cold start including the need of oxygen presence, namely secondary air introduction. ASC is efficient in cold
Kuhn, Sebastian, Magar, Avinash, Kogel, Julius, Lahousse, Christophe
Intelligent Sequential Charging Control via Fleet-Managed Cloud System2026-26-0207To be published on 01/16/2026
Electric Vehicles (EV) are increasingly becoming more and more popular in the markets, especially in the commercial vehicle segments. Amidst this, the need to find new elegant methods to perform charging of EV battery becomes extremely crucial. In areas with high demand and limited power capacity, performing charging for multiple vehicles necessitates efficient usage of charging infrastructure, which can’t be guaranteed by the traditional charging methods. Sequential charging is a new state of art technique for managing the charging of multiple EV’s simultaneously connected to a single charging station. Rather than dividing the available power equally among all connected vehicles or charging them one at a time, this technique dynamically allocates power based on various factors such as charging priority, vehicle needs and available infrastructure capacity. Currently, sequential Charging can only be implemented by a particular set of chargers that are interconnected via backend and
De, Abir, Bhattacharya, Ullash, Parihar, Aakash
Real-time Intrusion Detection System (IDS) for Vehicle Networks Using Machine Learning for Predictive Threat Analysis2026-26-0617To be published on 01/16/2026
The rapid adoption of connected vehicle technologies and advanced driver assistance systems (ADAS) necessitates robust security mechanisms capable of identifying and mitigating sophisticated cyber threats in real-time. Traditional signature-based intrusion detection systems (IDS) are often inadequate in addressing the dynamic and evolving nature of automotive cybersecurity threats, particularly in modern vehicle networks like Controller Area Network (CAN), CAN with Flexible Data-Rate (CAN-FD), and Automotive Ethernet. This research introduces a novel Real-time Intrusion Detection System utilizing advanced Machine Learning (ML) techniques designed specifically for automotive network environments. The proposed IDS framework employs supervised and unsupervised ML algorithms, including anomaly detection, behavioral analytics, and predictive threat modeling, to achieve high accuracy and rapid threat identification capabilities. Through extensive testing in simulated and actual vehicle
chaudhary lng, Vikash, Desai, Manoj, Chatterjee, Avik
Dynamic Diagnostic Controller Architecture for Scalable and Adaptive Zonal Based Vehicle Platforms2026-26-0689To be published on 01/16/2026
The rapid evolution of in-vehicle electronic systems toward zonal and High-Performance Computing (HPC)-based architectures introduces a new layer of complexity in automotive diagnostics. Traditional architectures, built on Controller Area Network (CAN) and Local Interconnect Network (LIN) protocols, operate on a uniform Real-Time Operating System (RTOS), enabling simplified and consistent diagnostic workflows across Electronic Control Units (ECUs). However, next-generation platforms must accommodate diverse communication protocols (e.g., CAN, LIN, DoIP, SOME/IP) and heterogeneous operating systems (e.g., RTOS, Linux, QNX), resulting in fragmented and inflexible diagnostic processes. This paper presents a Centralized Diagnostic Gateway architecture that addresses these challenges by enabling unified, scalable, and adaptive diagnostic capabilities across modern vehicle platforms. The proposed system consolidates protocol handling at the HPC level, abstracts diagnostic complexities, and
MUKHERJEE, SOUMYADEEP, Raman, Kothanda
Connected Traffic Warnings for Enhanced Commercial Trucking Safety2026-26-0680To be published on 01/16/2026
Commercial trucking forms the backbone of global supply chains, but the consistently high number of truck-related fatalities emphasises the pressing need for enhanced safety systems. Connected safety systems present a significant opportunity to mitigate risks and prevent collisions by providing commercial vehicle operators with real-time hazard alerts. This paper delves into the operational mechanisms and potential benefits of such warning systems within the trucking industry. These systems function by establishing a network of connected vehicles capable of detecting and communicating hazardous situations through a centralised, cloud-based platform. By seamlessly integrating real-time telemetry data from individual trucks with information sourced from third-party providers, weather services, the system gains an understanding of prevailing road conditions. This allows for the identification of potential dangers such as traffic accidents, ongoing road construction or maintenance
Madarla, Manoj, George, Basil, Gangapuram, Siva, Hegde, Subrahmanya, Mukherjee, Shubhobroto, Dixith, Sampreetha, Hegde, Preetham
Eliminating High-Voltage Pre-Charge Circuits in Electric Vehicles Using Bidirectional DC-DC Converters2026-26-0075To be published on 01/16/2026
Pre-charge circuit ensure the safety of the electric vehicle. During start up, the pre-charge circuits are critical for managing the initial connection between the high voltage battery and the power electronic system in all electric vehicles. Pre-charge circuits typically consist of resistors and contactors that gradually charge the input capacitors of inverters and DC-link systems to prevent sudden inrush currents that could damage components or trigger faults. However, traditional pre-charge solutions present several limitations like increased component count and system complexity, thermal losses due to resistor dissipation, mechanical wear of contactors over time, Slower start-up response, added cost and potential failure points. This paper introduces a novel method to eliminate conventional pre-charge circuits by utilizing bidirectional DC-DC converters to manage the pre-charge function. Through controlled ramp-up of voltage from the low-voltage system to the high-voltage bus, the
S, Aswathy, R O, Raghi
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