Browse Topic: Architecture

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UMV Peoplemover: Towards a modular fully automated vehicle research platform2026-01-0784To be published on 07/01/2026
The UMV Peoplemover 2+2 is part of a modular vehicle family (Urban Modular Vehicle) that includes derivatives for passenger and cargo transport in urban environments. The platform supports automated movers as well as conventionally controlled vehicles with a human driver, ensuring high flexibility across applications. The modular platform enables the extensive use of common parts, allowing the efficient and cost-effective realization of multiple vehicle variants. The increased share of common parts also improves sustainability by reducing derivative-specific parts, material usage, and production complexity. A drivable demonstrator of the UMV Peoplemover 2+2 has already been realized. The vehicle is designed for the automated transport of up to four occupants in a 2+2 vis-à-vis seating arrangement and is targeted at demand-oriented shuttle services. While the drivable demonstrator validated the proof of concept, it lacked the core Level 4 hardware and software stack for automated
Pohl, Eric, Schmid, Fabian, Münster, Marco, Siefkes, Tjark, Stuebler, Tillmann, Mohammed, Shawan
Impact of Network Latency on the Lateral Control in Automated Vehicle Marshalling2026-01-0781To be published on 07/01/2026
Automated Vehicle Marshalling (AVM) is the first functionally safe Level 4 automated driving system. It consists of the wireless control of unoccupied vehicles at low speed in well-defined environments, such as parking facilities or manufacturing plants. The driverless operation in an AVM system is achieved by transmitting control messages between connected vehicles and intelligent infrastructure. Similar to other wireless applications, network reliability poses a major challenge to ensuring safe automated driving. An AVM system must provide uninterrupted communication between the vehicle and the infrastructure at a stable frequency. However, wireless systems usually suffer from varying latencies and network disturbances. In this context, international organizations and automotive industry contributors have defined requirements specifying network performance, communication interfaces, and message formats for different AVM use cases. These requirements cover communication aspects
Mejri, Mohamed Amine, Münchhausen, Henrik, Flormann, Maximilian, Sturm, Axel, Henze, Roman
Methodology for Battery System Optimization and Evaluation Using Format Flexible Pouch Cells2026-01-0749To be published on 07/01/2026
Electrification using battery systems is one of the most relevant solutions regarding ecological challenges within multiple application cases such as mobility, tools or stationary power supply. Nonetheless besides recent achievements in some cases battery systems are still lacking behind operational requirements compared to conventional propulsion systems, therefore limiting the potential of electrification. Especially when purpose design possibilities are limited. Besides improving properties of cell materials, better usage of the available installation space offers potential for overall optimization of the battery system. The development of battery systems is complex, as it involves multiple system levels and domains, along with a wide range of design options and architectures. Battery cells that can be manufactured in flexible formats offer the potential to make more efficient use of available installation spaces. At the same time, these additional degrees of freedom increase design
Müller-Welt, Philip, Bause, Katharina, Spohn, Hannes, Albers, Albert
Multi-Agent LLM Pipeline for Systems Engineering Automation2026-01-0777To be published on 07/01/2026
The increasing complexity of modern software-intensive systems, particularly in the automotive domain, demands new approaches to bridge the gap between high-level engineering specifications and executable, safety-compliant code. This need is amplified by the rapid transition toward software-defined vehicles (SDVs), where highly dynamic, updateable software functions significantly enlarge the scope and frequency of engineering activities and require scalable, transparent, and adaptive development processes. While recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in automating tasks such as requirements analysis, code generation, and documentation, their deployment in safety-critical engineering workflows remains challenging due to the need for transparency, traceability, and controlled decision-making. This paper presents a modular multi-agent LLM pipeline that automates key steps of the systems engineering lifecycle - from requirement structuring and
Padubrin, Marcel, Kulzer, Andre Casal, Guerocak, Erol
Vision-Language Model Training for Code Generation from Requirements and Model-Based Artifacts2026-01-0770To be published on 07/01/2026
Recent advancements in Vision-Language Models (VLMs) have opened new possibilities for bridging the gap between Systems Engineering artifacts and automated code generation. Traditional Large Language Models (LLMs) are primarily trained on textual data and generic code repositories, which limits their ability to interpret graphical engineering artifacts such as Simulink block diagrams or system architecture models. In safety-critical domains like the automotive industry, these graphical models are central to development workflows and must remain closely aligned with textual requirements and implementation code to ensure traceability, compliance, and functional correctness. This paper proposes a VLM-centered multimodal training framework for code generation that integrates textual requirements, graphical model-based artifacts, and annotated source code into a unified learning process. By leveraging models which combine vision encoders with language backbones, the approach enables the
Padubrin, Marcel, Kulzer, Andre Casal, Guerocak, Erol
Trajectory Tracking Control and State Estimation for Highly Automated Vehicles: A System Framework Implemented on UShift II2026-01-0779To be published on 07/01/2026
Trajectory tracking control and state estimation are core functionalities of highly automated vehicles and must operate reliably under strict real-time constraints as well as in the presence of model uncertainties and limited sensor availability. In particular, low-speed maneuvers pose additional challenges due to weakly excited vehicle dynamics and system delays. This paper presents an integrated, real-time capable framework for trajectory tracking control and state estimation, developed within the UShift II research project and implemented on the highly automated vehicle platform. The framework combines nonlinear model predictive control (NMPC) for trajectory tracking with extended Kalman filter based state estimation within a modular system architecture. The NMPC is based on a vehicle model designed for low-speed automated driving maneuvers and explicitly accounts for actuator constraints. Trajectories are tracked based on local planned reference trajectories while ensuring smooth
Fuchs, Sören, Neubeck, Jens, Wagner, Andreas
Stochastic Gradient Pulse Adaptation for Onboard Pulse Charging in Grid-Friendly DC Fast Charging of Battery Electric Vehicles2026-01-0734To be published on 07/01/2026
The increasing deployment of battery electric vehicles (BEVs), particularly in commercial and heavy-duty applications, is driving demand for higher DC fast-charging power while placing growing pressure on battery lifetime and local grid capacity. In today’s multi-battery-pack vehicles, a common practical solution is the use of multi-step or multi-constant CC-CV charging, where charging current is reduced in stages to accommodate pack-to-pack differences in state of charge, state of health, and ageing behavior. While effective from a safety standpoint, this approach often leads to conservative charging profiles, longer charging times, and inefficient use of available grid power, especially at higher charging rates. This paper presents an onboard pulse-charging concept for electric powertrains that addresses these limitations through a combination of vehicle-side power electronics and an adaptive control strategy referred to as Stochastic Gradient Pulse Adaptation (SGPA). Instead of
Prakashkumar, Balagopal, mannar lng, Vignesh
A graph classification approach to secure the compatibility of software and hardware configurations in distributed automotive systems2026-01-0783To be published on 07/01/2026
Software-defined, highly customizable vehicle architectures drastically increase the number of hardware–software constellations that must be validated, especially under safety and timing constraints. Traditional unit and integration testing, as well as current regression and combinatorial methods, cannot practically cover this configuration space or reliably capture emergent effects arising from complex interactions, such as bandwidth contention and non-linear latency behavior. This work presents a proof-of-concept for predictive, situational validation of self-describing hardware and software components within realistic automotive E/E architectures. Proposing a novel Machine Learning- (ML) based method for early systemic feasibility prediction of automotive configurations using Graph Neural Networks (GNNs). Specifically, the subclass Graph Isomorphism Networks (GINs) is applied to predict the compatibility of a randomly composed configuration of software and hardware components
Wizl, Jens, Guarda, Filippo
Dynamic characterisation and modelling of Electric Cables under representative load conditions2026-01-0676To be published on 06/20/2026
Electric high voltage (HV) cables are commonly used in automotive applications and very prominently in electrified vehicles. These cables are potential flanking transmission paths for structure-borne sound in a broad frequency range and must therefore be included in the NVH design process. Electrical high voltage cables exhibit non-linear mechanical characteristics, when exposed to significant bending the internal geometry of the cable will change and a curvature dependent bending stiffness will result. The electrical cables envisaged in the current publication feature a helically wound stranded aluminium wire core. This conductive core is covered by, in sequence, a silicone rubber insulation, a braided aluminium wire shield with aluminium foil to minimize electromagnetic interference and a silicone rubber outer sheath. An extensive measurement campaign was carried out to dynamically characterize cable specimen of different lengths and cross sections in terms of multi-degree of freedom
Nijman, Eugene, Buchegger, Blasius, Böhler, Elmar, Zeller, Bernhard, Rejlek, Jan, Faksa, Lukáš, Lukavsky, David
Development of a Diesel Combustion System for Next‑Generation Heavy‑Duty Engines Using a Synergistic Analysis‑and‑Testing Approach2026-37-0004To be published on 06/09/2026
Regulators and policymakers have introduced increasingly stringent limits on tailpipe CO₂ and pollutant emissions to accelerate the decarbonization of heavy-duty vehicle applications. The development of innovative propulsion technologies — such as advanced combustion systems, low-friction reciprocating components, and improved aftertreatment solutions — combined with hybridization and the adoption of alternative fuels (e.g., biogas, HVO, green hydrogen), represents a key pathway for meeting future emission and GHG targets. In this study, advanced combustion systems were developed for a 13‑liter diesel engine for heavy-duty truck applications, with the objective of complying with forthcoming Euro VII regulations while maximizing thermal efficiency. The combustion system architecture—including open-bowl geometry with high aspect ratio, injector nozzle with wider spray opening angle, and reduced swirl ratio—was optimized using a Machine Learning–algorithm trained on high-fidelity 3D CFD
Belgiorno, Giacomo, Centini, Maria Pia, Pezza, Vincenzo, Cozza, Ivan F., Pesce, Francesco C., Vassallo, Alberto, Colombo, Giovanni, Gallo, Alessandro, Mirzaeian, Mohsen, Borg, Jonathan
Passenger Car Powertrain for Voltages above 800V2026-37-0020To be published on 06/09/2026
The EU-funded innovation project High-Voltage fast-charging Efficient electric vehicle Powertrains (HiVEP) develops new technologies for mass-market electric vehicles (EVs) by advancing architectures operating above 800 V. These architectures integrate silicon carbide (SiC)-based power electronics, rare-earth-free electric machines with active winding reconfiguration, high C-rate batteries, and optimised thermal management systems. HiVEP aims to deliver sub-10-minute fast charging, reduce energy consumption by at least 25%, extend range by 20%, and cut system costs by up to 20% in volume production. This article expands on the project objectives, methodological approach and expected key innovations as well as technical, environmental, and societal impacts. The discussion situates HiVEP within the European research and innovation landscape, emphasising its role in accelerating adoption of sustainable mobility solutions.
Schernus, Christof, Nada, Shady, Neuhaus, Christoph, Ewald, Jens, Swierc, Daniel, Kallur-Krishnamoorthy, Rajesh, Vasiliadis, Harilaos
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
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
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
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
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
Design of a Modular High-Power High-Repetition-Rate Semiconductor Pulsed Laser Power Supply2026-99-07165/15/2026
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Huang, De, Lu, Jiawei, Yang, Zhiqing, Xv, Ziyi, Xing, Hui
Research on Performance Prediction Methods for Centrifugal Refrigeration Compressors in Data Centers2026-99-07255/15/2026
As the “digital brain” and core foundational support for the development of intelligent transportation and connected vehicles, the performance of data centers directly determines the operational capability of intelligent transportation systems. In the process of advancing the vehicle-road-cloud collaborative architecture, the demand for high-performance computing power in data centers has experienced explosive growth. The substantial increase in computing tasks has posed severe challenges to thermal management, making efficient and reliable cooling systems an indispensable core component. Centrifugal compressor water-cooling units are the mainstream cooling solution for large-capacity scenarios, and their design optimization is crucial for improving the energy efficiency and performance of the entire cooling system. This paper proposes a one-dimensional performance prediction method for centrifugal compressors based on an empirical loss model, and realizes the iterative calculation of
Zhu, Minhao, Jiang, Bin, Li, Min, Zeng, Zihui, Gu, Yunhui
A Real-Time Monitoring and Rapid Warning Method for Guardrail Collisions in Intelligent Transportation Systems2026-99-07235/15/2026
This article proposes a method for real-time monitoring and rapid alert for guardrail collisions based on Distributed Acoustic Sensing (DAS). The aim is to enhance traffic safety through continuous analysis of vibration signals. To achieve this, a system architecture that combines both hardware and software design has been developed, enabling the handling of the entire process from signal acquisition and decoding to intelligent event recognition and visualization. To improve signal reliability, an adaptive noise reduction algorithm and a multi-level feature extraction method are introduced, enabling accurate differentiation between collision events and environmental disturbances. Tests at various vehicle speeds show that the DAS-based system detects collisions with over 98% accuracy and cuts false alarms by more than 60% compared to traditional video and point-sensor monitoring. It can locate accidents with an average error of 4.2 meters and respond in under 1 second, demonstrating
Sun, Lang
Autonomous Navigation Strategy and Docking Mechanism for Intelligent Chassis Module of Split Flying Vehicle2026-99-07435/15/2026
In response to the problems of urban traffic congestion and the limited expansion of infrastructure, this paper conducts two core research focusing on the intelligent chassis system of split-type flying vehicle. Firstly, an autonomous navigation strategy for the intelligent chassis module is proposed based on chassis module Navigation 2 architecture, which fuses LIDAR and IMU positioning to plan paths using the A* global planning algorithm on a global cost map, and update the local cost map in real time with sensor data. It is orchestrated by the BT Navigator using a behavior tree, with failures handled by the Recovery Server, to achieve autonomous driving across multiple waypoints. In simulation and closed-field experiments, the system can stably reach the preset target points. The positioning accuracy and trajectory tracking performance can meet the design requirements. Secondly, a mechanical slide rail-type docking structure adapted to the split flying vehicle architecture is
Zhao, Wenyu, Shi, Qin, Jiang, Cong, He, Zejia
Study on the Hierarchical Control Algorithm of SMES-BESS Hybrid Energy Storage Based on VMD and Fuzzy Control2026-99-07105/15/2026
In China, the installed capacity of renewable energy sources such as wind and photovoltaic power has ranked first in the world for consecutive years, and new energy has become a core driver of energy structure transition. However, the strong volatility and intermittency of new energy output seriously affect the safe and stable operation of the power system, and high-efficiency energy storage technology is the key to solving this problem. Focusing on the short-term high-power charging and discharging characteristics of high-temperature superconducting magnets (SMES), this study proposes a Hybrid Energy Storage System (HESS) that combines SMES with Battery Energy Storage Systems (BESS) to enhance the short-term power support capability of electrochemical energy storage. Variational Mode Decomposition (VMD) is introduced to establish a multi-level power allocation method, which addressing issues such as mode mixing, end effects, and low decomposition efficiency that are prone to occur in
Liu, Haiyang, Wang, Pengfei, Zhou, Wen, Lu, Jing, Wu, Yanan, Yin, Yunkuo, Jiang, Liping
From Autonomous Vehicles to Ship-to-Shore to: Designing 60 GHz Networks for Tactical Applications26AERP05_055/1/2026
Today's defense operations are defined by mobility, speed and data. Whether coordinating ship-to-shore logistics, maneuvering ground forces, or enabling autonomous and semi-autonomous systems at the tactical edge, reliable communications are no longer a support function - they are mission-critical. Defense forces must operate across fixed and mobile environments while maintaining secure, high-bandwidth connectivity amid interference, jamming, and limited spectrum availability. Legacy approaches, typically optimized for either static infrastructure or limited mobility, struggle to meet these combined requirements.
COTS Edge AI Accelerators for SWaP-C Constrained Defense and Space SystemsTBMG-550825/1/2026
The convergence of highly capable edge AI models and advanced commercial-off-the-shelf (COTS) edge AI accelerators is reshaping how computation is deployed across defense, aerospace, and commercial platforms. Mission-critical decisions increasingly must be made at the edge, onboard vehicles, satellites, and infrastructure nodes, where latency, connectivity, and power availability are constrained.
Directional Stiffness Decoupling in Meta-Wheels via Three-Dimensional Discrete Curved Spokes15-19-01-00054/22/2026
Meta-wheels—non-pneumatic wheels whose performance is governed by structural geometry rather than internal pressure—offer new opportunities for directional stiffness control. Yet achieving independent tuning of longitudinal, lateral, and vertical stiffness within a single wheel architecture has remained challenging due to the inherent coupling in conventional radial and planar curved spokes. In this study, we introduce a three-dimensional (3D) discrete curved-spoke design that provides explicit geometric control through two independent parameters: the in-plane curvature angle (α) and the out-of-plane inclination angle (β). Using spoke-level and full-wheel finite-element (FE) simulations, supported by a simplified cantilever-beam analytical model, we show that these two geometric parameters govern stiffness in fundamentally different ways. The curvature angle α serves primarily as a geometric softener, reducing stiffness in all directions while maintaining a high top-loading ratio (TLR
Han, Heeseung, Liu, Zhipeng, Ju, Jaehyung
Automated Vehicle Marshalling SystemJ3292_202604 (Current)4/13/2026
The scope of this standard is Automated Vehicle Marshalling (AVM) of vehicles to enable remote control functionality for achieving SAE Level 4 (High Driving Automation according to the Surface Vehicle Recommended Practice SAE J3016) driving capabilities at controlled speeds within geofenced private controlled environments utilizing infrastructure-assisted sensing. It specifies a concept of operations which includes a reference-system architecture and use cases, system functional and performance requirements, multiple wireless communications protocols, and associated wireless messages to support AVM. AVM use cases such as plant marshalling, depot marshalling, valet parking, electric vehicle charging, etc. The Automated Vehicle Marshalling Central Server (AVM CS) infrastructure does detect objects, vehicles, vulnerable road users, and any obstructions that help guide the Automated Vehicle (AV) starting from uninitiated, activation, identification, automated control, unavailable and
V2X Core Technical Committee
J1939 Digital AnnexJ1939DA_202604 (Current)4/10/2026
This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use.
Truck and Bus Control and Communications Network Committee
Dog Clutch Actuator Control to Mitigate NVH2026-01-00034/7/2026
Dog clutches have long been employed in the automotive industry across various applications, including transmission systems, transfer cases, axle disconnects, and hybrid driveline architectures. Their ability to provide direct mechanical engagement makes it ideal for torque transmission with minimal energy loss. However, the transition between engaged and disengaged states can introduce noise, vibration, and harshness (NVH), which may be perceptible to vehicle occupants and affect overall driving comfort. A typical dog clutch relies on interlocking teeth for torque transfer, and its actuation can result in NVH due to factors such as friction between mating surfaces, backlash between engagement components, teeth-on-teeth contact during synchronization, and impact forces during clutch engagement. This paper presents Stellantis’s approach to controlling the actuator system to mitigate NVH effects during clutch engagement and disengagement, focusing on strategies that enhance drivability
Xu, Chengyi, Madireddy, Krishna Chaitanya, Verhun, Brandon
Understanding Adversarial Transferability in Vision-Language Models for Autonomous Driving: A Cross-Architecture Analysis2026-01-01704/7/2026
Vision-language models (VLMs) are increasingly used in autonomous driving because they combine visual perception with language-based reasoning, supporting more interpretable decision-making, yet their robustness to physical adversarial attacks, especially whether such attacks transfer across different VLM architectures, is not well understood and poses a practical risk when attackers do not know which model a vehicle uses. We address this gap with a systematic cross-architecture study of adversarial transferability in VLM-based driving, evaluating three representative architectures (Dolphins, OmniDrive, and LeapVAD) using physically realizable patches placed on roadside infrastructure in both crosswalk and highway scenarios. Our transfer-matrix evaluation shows high cross-architecture effectiveness, with transfer rates of 73–91% (mean TR = 0.815 for crosswalk and 0.833 for highway) and sustained frame-level manipulation over 64.7–79.4% of the critical decision window even when patches
Fernandez, David, MohajerAnsari, Pedram, Salarpour, Amir, Pese, Mert D.
Model-Based Development of the “Big 5” in Fuel Cell Systems2026-01-00724/7/2026
Fuel cell systems are gaining traction across heavy-duty applications, driven by global decarbonization targets. Managing their inherent complexity and diverse architectural requirements, commonly organized into the “Big 5” fuel cell subsystems (stack, thermal, electric, anode, and cathode), necessitates advanced Model-Based Development (MBD) approaches. This paper presents and validates a constraint-graph-based, equation-oriented, acausal MBD methodology for fuel cell system (FCS) development, implemented in an industrial modeling environment. This methodology supports scalable functional and software development from 75 kW single-stack systems to twin-stack configurations exceeding 250 kW. It facilitates robust parameterization and reuse of consistently formulated, subsystem-level physical models across Model-in-the-Loop (MiL) to Hardware-in-the-Loop (HiL) environments, ensuring numerically robust software architectures and improved embedded control quality. Industrial application
Bandi, Rajendra Prasad, Bleile, Thomas
Architecture-Driven Fixed-Point Scaling for AUTOSAR-Based ECUs: A Production-Feasible Architecture for Centralizing Scaling Semantics2026-01-00694/7/2026
Floating-point arithmetic is widely used in automotive embedded software to scale Controller Area Network signals and calibration parameters with fractional factors such as 0.1. However, floating-point operations, even on microcontrollers equipped with floating-point units, can increase execution time and CPU load. In AUTOSAR architectures, converting floating-point scaling to fixed-point is not trivial because scaling semantics must be integrated consistently across components, yet AUTOSAR platform toolchains offer only limited automation at the Application Data Type level. Although CompuMethod definitions can express scaling, integration typically remains manual and distributed across application software components, reducing consistency and reusability. This study presents an architecture-driven methodology that formalizes fixed-point scaling as a centralized architectural service, realized through a parser-driven fixed-point macro generation pipeline. Standardized CAN DBC and
Lee, Hoseok, Ko, Donggun
Accelerating Electrification through Modular Propulsion: GM’S Strategy for BEV and BET Platforms2026-01-04104/7/2026
General Motors (GM) continues to advance its electrification strategy through the development of scalable Battery Electric Vehicle (BEV) and Battery Electric Truck (BET) platforms. This paper highlights GM’s latest BEV and BET products that leverage shared Drive Unit (DU), Rechargeable Energy Storage System (RESS), and integrated power electronic (IPE) components across multiple vehicle programs. By adopting a modular and commonized propulsion architecture, GM achieves significant benefits in manufacturing efficiency, cost optimization, speed to market, and product flexibility. The shared DU, RESS, and IPE components are engineered to meet diverse performance requirements while maintaining high standards of energy efficiency, thermal management, and durability. This approach enables rapid deployment of electrified solutions across various segments, from passenger vehicles to full-size trucks, without compromising on capability or customer experience. The paper outlines the technical
Liu, Jinming, Sevel, Kris, Anwar, Mohammad, Oury, Andrew, Welchko, Brian, Gagas, Brent
Simulation Study on Rear-Wheel Steering Control of FSAE Vehicles Based on Temporal Convolutional Network2026-01-06504/7/2026
The Formula SAE (FSAE) race track is characterized by a large number of corners, making cornering performance a key factor affecting lap time. Based on the proportional control strategy for rear-wheel steering angles, this paper proposes a steering angle optimization method using a Temporal Convolutional Network (TCN). The TCN model features a faster training speed than traditional sequential neural networks. In addition, dilated convolutions enable an exponential expansion of the receptive field without increasing computational costs, making it particularly suitable for capturing the temporal dependencies of vehicle states. By processing vehicle dynamic parameters including front-wheel steering angle, vehicle speed, yaw rate and sideslip angle, the model calculates the correction value of the rear-wheel steering angle. This correction value is then superimposed with the reference value of the rear-wheel steering angle derived from the proportional control strategy, which serves as the
Liu, Xiyuan
Efficient Embedded Control of Nonlinear Systems for Software-Defined Vehicles2026-01-00754/7/2026
Software-defined vehicles (SDVs) are reshaping automotive control architectures by shifting intelligence to embedded systems, where computational efficiency is paramount. This paper presents a systematic evaluation of control strategies (PID, LQR, MPC) for the classical control problem involving inverted pendulum on a cart under strict embedded constraints representative of software-defined vehicle ECUs. The objective is to evaluate and compare the performance of advanced control algorithms under varying control objectives when deployed on microcontrollers with constrained computational and memory resources, representative of the limitations encountered in embedded platforms used for SDVs. Furthermore, the study illustrates systematic optimization strategies that enable these algorithms to achieve real-time execution within such resource-constrained environments. Each control strategy is implemented with careful consideration of algorithmic complexity, real-time responsiveness, and
Vupparige, Varun, Pandya, Vidit
Leveraging Large Language Models for Natural Language-Driven CAD Automation and Multi-Objective Optimization in Thermal Component Design2026-01-05064/7/2026
The design of thermal components (such as automotive heat exchangers) requires balancing multiple competing objectives—thermal performance, aerodynamic efficiency, structural integrity, and manufacturability. Traditional design workflows rely on manual Computer Aided Design (CAD) modeling and iterative simulations, which are both labor-intensive and time-consuming. Recent advances in Large Language Models (LLMs) present untapped potential for automating parametric CAD generation. However, current LLM-based approaches primarily handle simple, isolated geometric primitives rather than complex multi-component assemblies. This work introduces a progressive framework that leverages fine-tuned LLMs (Qwen2.5-3B-SFT) integrated with the CadQuery CAD kernel to automatically generate parametric geometries from natural language descriptions. As a foundational study, this work focuses on Step 1 of the framework: generating and optimizing isolated geometric primitives (cylinders, pipes, etc.) that
Chaudhari, Prathamesh, Tovar, Andres
Backward Fuzzy Driving Control for 6×4 Off-Road Vehicles2026-01-01484/7/2026
Off-road autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6×4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6×4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6×4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational
Dekhterman, Samuel R., Sreenivas, Ramavarapu S., Norris, William R., Patterson, Albert E., Soylemezoglu, Ahmet, Nottage, Dustin
Beyond PFAS: Unlocking the Potential of R290 and R744 for EV Efficiency2026-01-01274/7/2026
The anticipated PFAS ban in the US by 2029 has created a need to evaluate alternative refrigerant solutions for automotive thermal management systems. This work compares three candidates—Propane (R290), Carbon Dioxide (R744), and R1234yf—through system-level testing and demonstration projects. R1234yf remains the current industry baseline. Test results show that Propane (R290) delivers comparable efficiency while offering a significantly lower global warming potential. However, its flammability presents integration challenges, not present with R1234yf or R744. CO₂ (R744) demonstrated promising performance as well. To address safety concerns with Propane, AVL developed mitigation measures including rapid leak detection, robust containment strategies, and optimized circuit layouts designed to reduce ignition risks. These countermeasures were validated in practice through the European Commission’s QUIET project. Within this program, a Honda B-segment electric vehicle was equipped with a
bires, Michael, Possegger, Jonathan
A Shared Autonomy Architecture: Utilizing an Advanced Personalized Control System (APeCS) and Shared Autonomy Arbiter (SAB)2026-01-01474/7/2026
The shared autonomy framework has become an option with great potential in the field of autonomous vehicles. Human and machine control decisions typically demonstrate strengths in different scenarios. As a result, the robustness of systems can be enhanced by the collaboration between humans and autonomy. A shared autonomy architecture that takes into account both human and environmental factors was proposed in this work. The authority distribution between the human operator and the autonomy algorithm was determined by the Shared Autonomy Arbiter (SAB). Designed with a two-tier structure, the SAB incorporated a policy-level decision module, as well as a numerical-level arbitration tuning module. A fuzzy inference system (FIS) was incorporated to enhance the noise tolerance of the policy selection module. Furthermore, the human factor was taken into account by applying a projection to the users’ control input. The human operator’s control decision was projected by the Adaptive
Sang, I-Chen, Norris, William, Patterson, Albert, Sreenivas, Ramavarapu S., Soylemezoglu PhD, Ahmet, Nottage, Dustin S.
Predictive Modeling and Sensitivity Analysis of Thermal Runaway in 800V Lithium-Ion Battery Module Using DFSS Methodology2026-01-01244/7/2026
Thermal runaway in high-voltage lithium-ion battery modules should focus on critical safety and design challenges in electric vehicle applications, which need predictive methods that enhance passenger safety and support regulatory compliance. The primary purpose of a lithium-ion battery in an electric vehicle is to provide reliable energy storage while maintaining safe operation under different operating conditions. This study proposes a Design for Six Sigma (DFSS) methodology to virtually predict and correlate thermal runaway and its propagation in an 800V high-power lithium-ion battery pack module. Conventional propagation analysis relies heavily on physical testing, whereas the DFSS-based virtual framework enables cost-effective evaluation at early design stages. Input factors included are heat transfer pathways, which are sensitive to the temperature changes, as well as thermal propagation time. Control factors are the design or process parameters that engineers use to establish
Dixit, Manish, Raja, Vinayak, Gudiyella, Soumya
The Golden Tester2026-01-00924/7/2026
The objective of this paper is to understand the effort required to integrate the hardware and software of in-vehicle cybersecurity systems. The in-vehicle cybersecurity method discussed is the SAE J1939-91C, which involves Network formation, Rekeying, and secure Message Exchange between Electronic Control Units (ECUs). The SAE J1939-91C network security protocol operates over a CAN-FD network to perform necessary cryptographic operations and key generation. To evaluate the method, test vectors were created to validate SAE J1939-91C key generations and cryptographic operations on the simulated ECU in-vehicle network system hardware (such as the Beacon or Pi devices). We introduce a lightweight, transport-agnostic benchmark comprising deterministic AES-CMAC test vectors and a simple verification utility, requiring no specialized hardware or build system. This minimal artifact set enables reproducible and machine-parsable validation of SAE J1939-91C security across diverse lab
Zachos, Mark, Medam, Krishna Teja
Evolutionary Paths Toward Vehicle Zonal E/E Architecture: A Unified Architectural Framework2026-01-00714/7/2026
The automotive industry is undergoing a fundamental transformation in Electrical/Electronic (E/E) architecture, evolving from traditional distributed and domain-based designs toward zonal configurations. The rapid growth of software-defined functionality, cross-domain integration, and centralized computing has exposed inherent limitations of legacy architectures in scalability, wiring complexity, and system integration. Zonal E/E architecture addresses these challenges by consolidating computing and Input/Output (I/O) resources into high-performance controllers distributed across physical zones of a vehicle. This transformation, however, cannot occur instantaneously, as contemporary vehicle designs and E/E system solutions are the result of decades of incremental development based on distributed and domain-based paradigms. Moreover, key enabling technologies for zonal E/E architecture—such as high-performance Central Compute Platform (CCP) and zonal controllers, high-speed automotive
Jiang, Shugang
The In-Vehicle Connectivity Foundation Powering Autonomous Driving2026-01-00094/7/2026
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 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
Ultra-Low Latency Video Pipeline Optimization for Perception-Centric Autonomous Systems2026-01-00224/7/2026
Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages—sensor acquisition, video encoding, data transmission, decoding, and display—undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software
Indrakanti, Rama Kiran Kumar
Target Cascading Kinematics and Compliance Tables to Suspension Design2026-01-05844/7/2026
During the initial design phase, automotive Original Equipment Manufacturers (OEMs) require the adaptability to examine various suspension system architectures while maintaining focus on the specific performance objectives. Those requirements are expressed by Kinematics and Compliance (K&C) look-up tables and represent the footprint of what the suspension should look like in real-world applications. However, translating those requirements into the full geometric hardpoint layout is not straightforward. This process often relies on trial-and-error approaches, making it time consuming and requiring significant expertise. This challenge, known as ”target cascading,” remains a major hurdle for many engineers. The main objective of this paper is to cascade the suspension requirements from K&C look-up tables to hardpoint locations by adopting an automatic workflow and ensuring respect for constructive and feasibility constraints. Design space exploration was conducted using a robust
Brigida, Piero, Di Carlo, Paolo, Di Gioia, Niccolò, Geluk, Theo, Tong, Son, Alirand, Marc, Gorgoretti, Davide, Occhineri, Marco, Tassini, Nicola, Berzi, Lorenzo
High-Speed Flashing in the Age of the Software-Defined Vehicle2026-01-01124/7/2026
In recent years, the use of software-defined platforms has become increasingly prevalent. As a result, flashing ECUs has become an important factor in ensuring efficiency, quality, and compliance in vehicle production. Conventional approaches, such as final end-of-line flashing, are increasingly unsuitable for the growing amounts of data, complex dependencies, mixed physics and protocols, and traceability requirements. This SAE paper presents the current trends and challenges in ECU flashing. It highlights the impact of the exponential growth in software payloads and the necessary migration to offline and parallel workflows. This can only be achieved through closer integration with automated and robot-assisted production, considering the requirements of cybersecurity and verifiability. It also addresses the shift toward end-to-end flashing ecosystems, where updates are performed consistently from a single source covering the assembly line, warehouses, yards, workshops, and over-the-air
Böhlen, Boris, Budak, Oguz, Wells, Michael
In-Use Life Digital Twin (Redundant Storage) and Swappable Use Case for Battery Durability2026-01-03974/7/2026
As regulatory frameworks for zero-emission vehicles (ZEVs) and battery electric vehicles (BEVs) continue to evolve, there is growing emphasis on monitoring battery durability and usage throughout the vehicle lifecycle. These regulations increasingly specify the use of data monitors and tracking mechanisms to assess battery health and performance. In addition, regulations require anti tampering mechanisms especially for monitors that have external write access. Historically, regulations focused primarily on vehicle warranty; however, with the introduction of battery durability monitors, clarity is needed for the new battery durability monitors. More specifically if the battery durability monitors track with the lifetime of the vehicle or if they follow the lifetime of the battery. Furthermore, current regulations provide no guidance on high-voltage (HV) traction battery service strategies or methods to protect monitors from tampering by external customers. This paper will classify
Laskowsky, Patricia, Bunnell, Justin, Zettel, Andrew, Albarran, Josue
Mathematical Modeling of Trust Calibration for Human–Automation Safety2026-01-05304/7/2026
Trust calibration is vital for safe human–automation interaction but remains largely qualitative. This study develops multiple quantitative frameworks modeling trust as a function of automation reliability. Four progressive models of binary, linear, triangular, and logistic formalize the calibrated trust zone, defining where human reliance aligns with system performance. The framework corrects major misconceptions: that trust is purely qualitative, that low trust–low reliability states are acceptable, and that overtrust and distrust pose equal risk. It establishes a minimum reliability threshold for meaningful trust and identifies distrust as the safer default in high-risk contexts. A case study on an empirical observation of 32 AI applications plotted in the trust–reliability space confirms the analysis, revealing a consistent distrust tendency where reliability exceeds user confidence and other observations. By quantifying trust through reliability, the study reframes it as a
Wen, He, Mounir, Adil
Roundabout Dilemma Zone Data Mining and Forecasting with Trajectory Prediction and Graph Neural Networks2026-01-00294/7/2026
Traffic roundabouts, as complex and safety-critical road scenarios, present significant challenges for autonomous vehicles. In particular, predicting and managing dilemma zone (DZ) encounters at roundabout intersections remains a pivotal concern. This paper introduces an AI-driven system that leverages advanced trajectory forecasting to anticipate DZ events, specifically within traffic roundabouts. At the core of our framework is a modular, graph-structured recurrent architecture powered by graph neural networks (GNNs). By modeling agent interactions as a dynamic graph, our approach integrates heterogeneous data sources - including semantic maps - while capturing agent dynamics with high fidelity. This GNN-based forecasting model enables accurate prediction of DZ events and supports safer, data-driven traffic management decisions for both autonomous and human-driven vehicles. We validate our system on a real-world dataset of roundabout intersections, where it achieves high precision
Lu, Duo, Satish, Manthan, Farhadi, Mohammad, Chakravarthi, Bharatesh, Yang, Yezhou
Application of DFSS for Optimizing Thermal Protection in Electric Vehicles during Battery Thermal Runaway Events2026-01-01424/7/2026
Battery thermal runaway is a major safety concern in electric vehicles because of the extreme heat and hazardous gases released during cell failure. These venting events can quickly raise the temperature of the battery enclosure and cabin floor, threatening occupant safety. To address this challenge, this study employs the Design for Six Sigma (DFSS) methodology to design and optimize a thermal protection system that delays and limits heat transfer to the cabin. A physics-based transient heat-transfer model was combined with DFSS principles to systematically evaluate insulation materials, shield layouts, surface emissivity, and layer geometry. An L-18 orthogonal array was used to identify key parameters and quantify their influence on thermal robustness. The optimized architecture reduced cabin-floor temperature rise under severe runaway conditions (600–900 °C vent gas), meeting occupant-egress safety requirements. Findings confirm DFSS as an effective framework for developing high
El-Sharkawy, Alaa, Asar, Mona, Taha, Nahla, Sheta, Mai
Sensitivity Analysis and Development Approach of HV Battery Lifetime for Complete Vehicle Integration2026-01-03954/7/2026
The lifetime and aging of the high voltage battery is one of the major discussion points for the end-customer to decide between buying a car with an electric powertrain or still using a conventional powertrain. Therefore, the provision of adequate vehicles to the end-customer, the aging of the high voltage battery become an important topic for the complete vehicle development. In addition, also legal regulations (e.g. EU7) will preset minimum requirements for the warranty of the high voltage battery. These circumstances define the lifetime / aging of the HV battery to be a complete vehicle development target, which needs to be developed. The paper will present a method for the development process of a lifetime target from complete vehicle perspective. The method is based on the generation of a representative monthly power profile and temperature profile. Depending on a monthly user routine, ambient temperature profile and charging behavior, the vehicle specific battery power profile
Martin, Michael
Thermal Characterization of an Automotive High Voltage Junction Box2026-01-03904/7/2026
The high voltage battery junction box (HVJB) controls and protects the high voltage connections of the battery pack to the traction, auxiliary, and charging systems. HVJBs are composed of busbars, contactors, fuses, and other protection systems. The health of the HVJB is paramount to ensure performance of electric vehicles. However, sensing and monitoring in the HVJB are often lacking due to packaging cost, causing limited capability of the vehicle controller to estimate the status and health of the unit. This publication focuses on the experimentation of an automotive HVJB to characterize the operation and build the foundation for the development of prognostic algorithms for HVJB. A production HVJB has been acquired and heavily instrumented. Extensive testings are performed in adiabatic and in ambient conditions at various current levels for various durations of operation. The testing setup was calibrated and iterated based on preliminary results, and the testing conditions were
Arigo, Sam, Borgerson, Joe, D'Arpino, Matilde, Zhu, Di, Zhang, Liwen
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