Browse Topic: Systems engineering

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An open-source framework to Automate Virtual Optimization of Internal Combustion Engine Calibration Maps through shape-based strategy2026-37-0001To be published on 06/09/2026
The automotive industry is facing increasingly stringent regulatory constraints, driving the need for faster and more efficient powertrain development. This results in higher systems complexity, making internal combustion engine calibration progressively more challenging to meet performance and emissions targets. This, combined with the manual nature of traditional calibration workflows, leads to a time‑consuming process that heavily relies on human expertise. Although virtualization can reduce development time and costs, the overall workflow remains largely dependent on manual decision‑making and iterative refinement. In this context, this work presents a virtual calibration framework based on a genetic algorithm, aimed at the automated optimization of engine calibration maps to satisfy performance and emissions constraints, while reducing manual effort. Each calibration map is represented through a polynomial parameterization. Specifically, a generic three‑dimensional polynomial with
Romano, Gianvito, Aglietti, Filippo, Spedicato, Tonio, cozza, Ivan Flaminio, Capra, Andrea
Integrating Formal Methods into Model Based Systems Engineering(MBSE) to Mitigate Requirement Escapes2026-26-0712To be published on 06/01/2026
The industry is undergoing a significant digital transformation in the way system requirements are defined, communicated, and managed. Major original equipment manufacturers (OEMs) are moving toward fully model-based development processes, with plans to deliver requirements exclusively in the form of system models. It is no longer sufficient to manage requirements using traditional document-based approaches; instead, organizations must adopt tools and processes that enable the consumption, interpretation, and implementation of model-based requirements. Preparing to meet this industry direction is critical to maintaining competitiveness and alignment with our customers’ expectations. Model-Based Systems Engineering (MBSE) plays a central role in this transition. MBSE enables engineers to define, analyze, and manage system requirements, architectures, behaviors, and verification strategies within a cohesive model-based framework. It supports traceability, promotes consistency across
Gupta, Chandan, Nakkeeran, Rupashree
Risk-Driven Program Management Framework - Abstract2026-26-0716To be published on 06/01/2026
Avionics programs face increasing complexity due to evolving safety, certification, and cybersecurity requirements. Conventional program management approaches, focused mainly on cost and schedule, often overlook the dynamic and interdependent risks inherent in developing safety-critical systems. This gap results in late surprises, inefficient resource use, and challenges in achieving certification milestones. This paper introduces a risk-driven program management framework tailored for avionics, where risk identification, assessment, and mitigation are embedded within the governance model rather than treated as a parallel activity. The framework integrates industry standards such as DO-178C, DO-254, DO-326A, and ARP4754A, ensuring alignment with regulatory expectations while promoting a holistic view of program health. A key feature of the approach is the use of digital dashboards and predictive analytics to transform static risk registers into actionable tools. These dashboards
Rahul, Saurabh, Benikireddy, Raghunatha
Hybrid Digital Twin for Aero-Engine Bearing Prognostics: A Physics-Informed Machine Learning Approach to RUL Prediction2026-26-0718To be published on 06/01/2026
Unscheduled maintenance due to the failure of critical components, such as aero-engine rolling element bearings, is a leading cause of costly Aircraft-on-Ground (AOG) events; consequently, current time-based maintenance practices are inefficient and prone to risk. This paper develops a resource-efficient Hybrid Digital Twin (HDT) model for an engine bearing, focusing on the dynamic prediction of spall growth due to Rolling Contact Fatigue (RCF), thereby enabling a condition-based maintenance paradigm. The HDT architecture integrates two core models: (1) a physics-informed model that uses established life and fatigue theory to define initial degradation thresholds and constrain the failure envelope, and (2) a data-driven Recurrent Neural Network (RNN) (specifically, an LSTM) for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, synthetic run-to-failure dataset under varying operational loads
Mohamed, Abbas
Enhancing Track Vehicle Design Engineering Through Digital Twins: A Data-Driven Approach2026-01-02664/7/2026
Digital Twin technology can significantly improve the engineering product design process, especially when considering ground vehicle applications. Data-driven computer studies can assist engineers and key stakeholders in evaluating performance, durability, and other system design tradeoffs. To enable this process, the availability of relevant, numerically generated, laboratory, and/or field data is required. Proper data use enables the digital exploration of “what-if” scenarios, reducing necessary field testing and allowing for the examination of hard-to-test operating conditions. When considering the Digital Twin toolset, a collection of models and simulations are assembled to supplement virtual testing endeavors. These models include surrogate, CAD/CAE, and others. In this paper, an off-road track vehicle design is reviewed through the fusion of numerical and field data to evaluate future design enhancements. Preliminary results demonstrate that subtle feature upgrades can produce
Suber II, Darryl, Bradley, Andrew, Singh, Shubhendra, Turner, Cameron, Castanier, Matthew P., Wagner, John
AI Model Creation and System Verification of “Telemotion” Infrastructure-Cooperative Autonomous Driving System Using Digital Twin2026-01-02554/7/2026
The concept of the vehicle has changed as a result of many innovations over the last decade in the fields of connected, autonomous/automated, shared, and electric (CASE) technologies. At the same time, labor shortages in Japan are becoming more serious due to a decline in the working population. To help resolve these issues, a remote-controlled autonomous vehicle driving system called Telemotion has been developed that automates the movement of vehicles in production plants. This system is an autonomous driving and transportation system in which the recognition, judgment, and operation functions of driving are handled by a control system outside the vehicle that communicates wirelessly with the vehicle. This system utilizes artificial intelligence (AI) and other advanced technologies to realize safe unmanned autonomous driving, and is already in operation in production plants. Currently, efforts are under way to build a digital twin environment and conduct AI learning using computer
Hatano, Yasuyoshi, Iwazaki, Noritsugu, Nagafuchi, Yuhei, Iwahori, Kento, Tanaka, Atsushi, Uezu, Satoru, Kanou, Takeshi, Inoue, Go, Okamoto, Yuki, Oka, Yuhei, Kakuma, Daisuke, Chiba, Hiroya, Egashira, Kazuki, Ishikuro, Megumi, Sawano, Takuro
An Integrated Methodology for Sustainable Mobility Infrastructure Planning: The Atlanta Aerotropolis Case Study2026-01-00974/7/2026
By the early 2020s, more than 4.5 billion people have been living in urban areas worldwide, compared to just 1 billion in 1960. Rising growth in urban populations present challenges to infrastructure and transportation systems. Higher traffic levels and reliance on conventional vehicles have contributed to heightened greenhouse gas (GHG) emissions, rising global temperatures, and irreversible environmental degradation. In response, emerging transportation solutions—including intelligent ridesharing, autonomous vehicles, zero-tailpipe-emission transport, and urban air mobility—offer opportunities for safer and more sustainable transportation ecosystems. However, their widespread adoption depends not only on technological performance and efficiency, but also on integration with current infrastructure, safety, resilience to unexpected disruptions, and economic viability. A dynamic agent-based System-of-Systems (SoS) transportation model is developed to simulate vehicle traffic and human
Rana, Vishva, Balchanos, Michael, Mavris, Dimitri, Valenzuela Del Rio, Jose
Vehicle Test Platform with Experimentally Correlated Tire Model for Torque Vectoring Control2026-01-06224/7/2026
This paper presents a testing platform for the development of lateral stability control systems in independent motor electric vehicles (EVs). A 10 degree of freedom (DOF) vehicle simulation and a radio control test vehicle are constructed to enable controls validation scalable to full size vehicles. These vehicle simulations, or ‘digital twins’, have been widely adopted throughout the automotive industry due to their lower operating costs and ease of implementation. Virtual models are not perfect representations of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially true when testing safety-critical features such as stability control. As a result, a simulation environment working in conjunction with a test vehicle represents an optimal hybrid approach. In this work, a high fidelity vehicle model is constructed in the Matlab/Simulink environment. To capture the effect of suspension, the digital twin is capable of
Petersen, Nicholas Conner, Robinette, Darrell
MBSE-Driven XIL Workflow for Energy Evaluation of Automated Vehicles: From Simulation to VIL Testing2026-01-02894/7/2026
With the increasing market penetration of automated vehicles, there is a critical need for credible and repeatable methods to quantify their energy impacts. This paper presents a Model-Based Systems Engineering (MBSE)-driven Anything-in-the-Loop (XIL) methodology for quantifying the powertrain energy consumption and potential savings from various controls for automated vehicles in realistic road scenarios while preserving high-fidelity powertrain behavior. The novelty of this approach lies in its use of a unified MBSE backbone (AMBER: Argonne National Laboratory’s [Argonne’s] MBSE-centric platform for transportation energy analysis) to automate the seamless and traceable progression from pure simulation to Vehicle-in-the-Loop (VIL) testing. This work utilizes Argonne's multi-vehicle simulation tool, RoadRunner, which automatically constructs closed-loop road scenarios (road geometry, vehicle sensors, other vehicles, and traffic controls) and connects them to Argonne’s validated, high
Jeong, Jongryeol, Sharer, Phillip, Di Russo, Miriam, Das, Debashis, Zhang, Yaozhong, Karbowski, Dominik
Digital Twin Aerodynamics Model Validation for HALO Wind Tunnel2026-01-06104/7/2026
A simulation-based aerodynamics model of the Honda Automotive Laboratories of Ohio (HALO) Wind Tunnel, a three-quarter open-jet (ground plane) configuration opened in 2022 for full-scale automotive testing, was initiated to support data fusion for more accurate surrogate models in vehicle engineering programs. The objective was to demonstrate that a matched set of boundary values between the physical wind tunnel and the three-dimensional numerical model yield correct responses for several key flow field quantities, starting with the baseline empty tunnel case: (1) streamwise static pressure distribution, (2) evolution of the free shear layers downstream of the nozzle exit plane, and (3) ground-plane boundary layer development. Pressure-based measurement probes were deployed in these regions using a four-axis overhead traverse to acquire validation data in the large facility, including instrument verification between a 14-hole probe and Pitot-static rake. Detached eddy simulation (DES
Patel, Sajan, Disotell, Kevin, Eagles, Naethan
Optimizing Virtual Scenario Testing for Autonomous Vehicles with Large-Scale Scenario Generation2026-01-00504/7/2026
The validation of Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) Systems, especially at higher automation levels such as SAE Level 3 or 4, demands the testing of a vast array of scenario variants far exceeding the scope of standard safety specifications like Euro NCAP (The European New Car Assessment Programme). Autonomous vehicles require thorough real-world testing to ensure automotive safety. However, public road tests are costly and risky. Instead, virtual scenarios - digital twins of real environments - offer a safe, cost-effective testing alternative. Exhaustive simulation across this high-dimensional scenario space, which includes variations in actor behavior, environmental conditions, and event characteristics, is computationally infeasible. We propose a constraint-solving approach to address this challenge that leverages mathematical and geometric techniques to analytically assess the existence and validity of scenario variants prior to simulation. Two
Karve, Omkar, Saurav, Saket, Purwar, Prabhanshu
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
Standardization of On-Vehicle Measurement of BEV Thermal System Energy Consumption and Range Impacts2026-01-01324/7/2026
This paper presents research and digital twin modeling results to support work on a methodology to properly account for the energy consumed by the thermal system of a BEV, for use within both existing Petroleum-Equivalent Fuel Economy (PEFE) calculations, and the proposed addition of hot and cold weather range values to the consumer-facing Monroney label [1]. Properly accounting for thermal system impacts would incentivize minimizing energy consumption of these systems, since 1) BEV PEFE is a direct input to an OEMs overall CAFE performance, and 2) the values on the Monroney label has some impact on consumer vehicle choice. The impetus for this work was Final Rules issued by the EPA and NHTSA in early 2024 eliminating A/C Efficiency Credits for BEVs from the 2027 MY, thus eliminating regulatory incentives to minimize energy consumption of these systems. Higher energy consumption will produce a number of negative secondary effects, including higher real-world greenhouse gas emissions
Taylor, Dwayne
A System of System Design Framework for Multi-Domain Vehicles2026-01-02634/7/2026
Traditionally, ground vehicle design is based on identifying engineering solutions that fulfil the requirements and specifications put forth by the stakeholders. Although a vehicle is a single entity, it is composed of many subsystems and thousands of parts that must operate together in unison to meet all design goals. A System of Systems (SoS) design approach enables the consideration of subsystem performance within a framework of overall system operation, which includes possible tradeoffs. This collaborative approach to subsystem and primary system design draws upon modelling, optimization, tradespace analysis and virtual studies. In this paper, a system of system design approach will be investigated for a collection of multi-domain vehicles assembled to undertake coordinated search and rescue operations on land and water. A host ground vehicle, an unmanned aerial drone, an unmanned marine drone and an unmanned tracked vehicle constitute the family of multi-domain vehicles which will
Somanchi, Anang, Abeynayake, Chandima, Deshmukh, Mrunal, Suresh, Johir, Ramnath, Satchit, Turner, Cameron, Schmid, Matthias, Castanier, Matthew P., Rapp, Stephen, Jaczkowski, Jeffrey J., Wagner, John
Designing Military Vehicles for a Battlefield Characterized by Drones2026-01-02624/7/2026
The modern battlefield is increasingly characterized by the use of small drones. As such, military vehicles must now be designed to account for this threat. This paper presents a model-based systems engineering approach to identify vehicle vulnerabilities and generate new vehicle requirements to mitigate them. This approach uses a standard set of System Modeling Language diagrams. A vehicle’s primary roles are captured in a series of use cases. Each use case is characterized by a sequence of activities performed by the vehicle. These activity sequences are captured in an activity diagram, which are used to wargame how a drone can exploit the vehicle at each phase. Each potential exploitation is assigned likelihood and severity scores, which feed into a risk index. This risk index is then used to prioritize each vulnerability. From these vulnerabilities, a set of operational requirements are derived, which then informs the development of system requirements. As the system matures, the
Ells, Alec, Werntz, Bryson, Saulsberry, Taylor, Wilkinson, Cooper, Mittal, Vikram
Structuring Cross-Disciplinary Development: A Systems Engineering Framework for ASPICE-Compliant Mechatronic and Cyber-Physical Engineering2026-01-50254/2/2026
Mechatronic and cyber-physical systems emerge from interdisciplinary design efforts, integrating software (SW), electronics, and mechanical components. Developing such systems places high demands on organizations and processes, particularly regarding efficient collaboration across domains. A key challenge lies in establishing organizational structures and workflows which allow cross-discipline work and at the same time ensure compliance with regulations and adherence to standards such as Automotive Software Process Improvement and Capability Determination (ASPICE). In response, the authors have developed an Engineering Process Framework (EPF) grounded in International Council on Systems Engineering (INCOSE) systems engineering principles. The EPF provides a structured approach for system development and therefore defines company-wide processes and methods. This paper presents the development of the EPF’s functional logic and its implementation within a tool landscape. Furthermore, a
Gehrt, Jan-Jöran, Granrath, Christian, Caglayan, Ebru, Reckeweg, Thomas, Richert, Felix
SAE TOMORROW TODAY - SAE J3311: Smarter Vehicle Power Management135603/25/2026
When it comes to today's vehicles, every bit of energy matters. Wasted power can reduce EV driving range, add weight, and increase costs across the supply chain. That's where SAE Standard J3311, comes in. Instead of constantly running systems at full power -- or each automaker using its own proprietary strategy -- SAE J3311 promotes efficient, fine-tuned energy use across the entire vehicle. Listen in as we sit down with SAE J3311 committee members Donald Gignac, Automotive Solutions Architect, Silicon Mobility; Maria Soledad Elli, Sr. Data Scientist, Torc Robotics; and Simone Palombi, Senior Systems Engineer, General Motors, to discuss how creating a common, industry-wide approach to smarter power management can unlock longer range, lighter vehicles, lower costs, and faster innovation across EVs and internal combustion engines alike. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to
Patterson, Lori
Use of Models and Tools for Aircraft Systems Development - A Strategy for Development Assurance Aspects with ExamplesAIR6276 (Current)3/1/2026
The increased use of models in the development of complex aircraft and systems provides great opportunities and benefits, but also introduces some additional risks. The purpose of this document is to clarify ways to identify, prioritize, and mitigate risks associated with the use of models and tools in aircraft and system development. This document introduces considerations for the usage of models and tools in aircraft and system development activities that are defined in ARP4754/ED-79 (at latest revision). Throughout this document, a model refers to an abstract representation of a given set of aspects of a system/function/item, and a tool refers to an application or commercial product that is used for aircraft or system development activities such as developing, managing, and executing models, managing requirements validation and implementation verification activities and associated data, and automation of complex development tasks. The characteristics of models and tools and how they
S-18 Aircraft and Sys Dev and Safety Assessment Committee
Dassault Systèmes and NVIDIA Partner to Build Industrial AI Platform Powering Virtual Twins26AERD03_013/1/2026
Dassault Systèmes and NVIDIA have announced a long-term strategic partnership to establish a shared industrial architecture for mission-critical artificial intelligence across industries. Combining Dassault Systèmes' Virtual Twin technologies with NVIDIA AI infrastructure, open models and accelerated software libraries will establish science-validated industry World Models, and new ways of working through skilled virtual companions on the agentic 3DEXPERIENCE platform, that empower professionals with new expertise.
Earned Value Management SystemsEIA748E (Current)2/17/2026
An Earned Value Management System (EVMS) integrates the work scope of a program with the schedule and cost elements for optimum program planning and control. The primary purpose of the system is to support integrated program management. The system is owned by the organization and is governed by the organization’s policies and procedures. The principles of an EVMS are: Plan all work scope for the program to completion. Break down the program work scope into finite pieces that are assigned to a responsible person or organization for control of technical, schedule, and cost objectives. Integrate program work scope, schedule, and cost objectives into a performance measurement baseline plan against which accomplishments are measured. Control changes to the baseline. Use actual costs incurred and recorded in accomplishing the work performed. Objectively assess accomplishments at the work performance level. Analyze significant variances from the plan, forecast impacts, and prepare an estimate
G-47 Systems Engineering
PRODUCT BRIEFS26AUTP02_172/1/2026
Aircraft Thermal Management System EngineeringAIR5744 (Current)1/21/2026
The intent of this report is to encourage that the thermal management system architecture be designed from a global platform perspective. Separate procurements for air vehicle, propulsion system, and avionics have contributed to the development of aircraft that are sub-optimized from a thermal management viewpoint. In order to maximize the capabilities of the aircraft for mission performance and desired growth capability, overall system efficiency and effectiveness should be considered. This document provides general information about aircraft Thermal Management System Engineering (TMSE). The document also discusses approaches to processes and methodologies for validation and verification of thermal management system engineering. Thermal integration between the air vehicle, propulsion system, and avionics can be particularly important from a thermal management standpoint. Due to these factors, this report is written to encourage the development of a more comprehensive system
AC-9 Aircraft Environmental Systems Committee
Real-Time Range Optimization for Selected Destinations by Dynamic Energy Management Strategy (DEMS) in BEVs2026-26-01681/16/2026
The automotive industry has undergone significant transformation with the adoption of electric vehicles (EVs). However, the inadequate driving range is still a major limitation and to tackle range anxiety, the focus has shifted to energy management strategies for optimal range under different driving conditions. Developing an optimal energy management algorithm is crucial for overcoming range anxiety and gaining a competitive edge in the market. This paper introduces Dynamic Energy Management Strategy (DEMS) for electric vehicles (EVs), designed to optimize battery usage and extend the driving range. Utilizing vehicle digital twin model, DEMS estimates energy consumption across Eco, Normal, and Sports driving modes by analyzing vehicle velocity profiles and pedal inputs. By calculating actual battery consumption and identifying excess power usage, DEMS operates in a closed loop to periodically assess the power gap based on real-time vehicle conditions, including HV components like the
Dey, Supriyo, Venugopal, Karthick Babu, Penta, Amar, Kumar, Rohit, Arya, Harshita
A Data-Centric Approach to Identify Optimal NVH Simulation Tools and Solvers2026-26-03561/16/2026
The world is moving towards data driven evolution with wide usage tools & techniques like Artificial Intelligence, Machine Learning, Digital Twin, Cloud Computing etc. In automotive sector, the large amount of data being generated through physical and digital test evaluations. Computer-Aided Engineering (CAE) is one of the highest contributors for data generation as physical testing involves high cost due to prototypes & test set-up. The Automotive Noise, Vibration & Harshness (NVH) field is advancing exponentially due to new stringent regulatory norms & customer preferences towards comfort, where digitally advanced techniques are playing a key role in the revolution of NVH. Data generation through CAE tool is a crucial aspect of Engineer’s daily activities and selecting such appropriate CAE software and solvers is critical, as it influences user interface experience, accuracy, solution time, hardware requirements, variability expertise, Design of Experiments ability, and integration
Hipparge, Vinod, Masurkar, Nikita, Arabale, Vinand, Billade, Dayanand
Transforming Manufacturing: Increasing Throughput and Reducing Production Complexity with Digital Twins2026-26-04491/16/2026
This paper presents a bidirectional digital twin developed for the Fischertechnik Smart Factory Kit, enabling real-time simulation and validation of production line modifications prior to actual deployment. The digital twin integrates with a Siemens Programmable Logic Controller (PLC) to mirror real-world operations, capturing live production data and visualizing key factory parameters, such as product, process, and resource metrics within a 3D environment. Engineers can test various optimization scenarios by adjusting robot speed and path, conveyor speeds, part & process sequences, and modifying equipment layout sizes to enhance efficiency. Based on the optimization scenarios, the best-performing configurations are identified using metrics such as throughput, cycle time, and resource utilization. Once validated, these changes are directly deployed to the PLC, ensuring seamless implementation. Beyond capacity optimization, this solution enhances overall production efficiency by
Kumar, Rahul, Singh, Randhir
Nexifi11D: A Comprehensive Multidimensional Framework for Futuristic Manufacturing Ecosystems2026-26-02821/16/2026
This paper presents Nexifi11D, a simulation-driven, real-time Digital Twin framework that models and demonstrates eleven critical dimensions of a futuristic manufacturing ecosystem. Developed using Unity for 3D simulation, Python for orchestration and AI inference, Prometheus for real-time metric capture, and Grafana for dynamic visualization, the system functions both as a live testbed and a scalable industrial prototype. To handle the complexity of real-world manufacturing data, the current model uses simulation to emulate dynamic shopfloor scenarios; however, it is architected for direct integration with physical assets via industry-standard edge protocols such as MQTT, OPC UA, and RESTful APIs. This enables seamless bi-directional data flow between the factory floor and the digital environment. Nexifi11D implements 3D spatial modeling of multi-type motor flow across machines and conveyors; 4D machine state transitions (idle, processing, waiting, downtime); 5D operational cost
Kumar, Rahul, Singh, Randhir
Digital Twin for Motor & MCU Incorporating Deep Learning AI-ML Algorithms for Intelligent Prognostics for Electric Vehicles2026-26-04791/16/2026
As electric vehicles (EVs) become more advanced, so ensuring the reliability of critical components like the motor and Motor Control Unit (MCU) is essential. This paper presents a digital twin model designed to predict failures in motor and MCU components using machine learning. The approach focuses on detecting early signs of failure through real-world data and advanced analytics. We collected thermal and performance data from field vehicles, capturing both normal (healthy) and abnormal (faulty) operating conditions. Using this dataset, we developed and trained an Auto Encoder-based machine learning model that learns what “normal” looks like and flags deviations as potential issues. One key outcome of this study is the successful early prediction of Insulated Gate Bipolar Transistor (IGBT) degradation, where the system identified subtle behavioral changes long before any visible failure symptoms appeared. This digital twin acts as a virtual replica of the physical components
Joshi, Pawan, Pandey, Suchit, KONDHARE, Manish, Upadhyay, Abhay, JaganMoahanarao, Vana, Tank, Prabhu
Scalable and Modular Data-Driven Hybrid Chassis Dynamometer Framework for EV Powertrain Evaluation2026-26-03631/16/2026
In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing
Kumar, Akhilesh, V, Yashvati
A Novel Approach to Efficient System Level Validation of Vehicle Interior Systems2026-26-05341/16/2026
Mechatronic systems, which are integral to various automotive applications, enhance both functional criticality and user experience. As the complexity and number of features in automotive systems increase, the volume of test cases for system-level features and their interactions grows exponentially. This necessitates rigorous regression testing with each software update to ensure system reliability and performance. The systems engineering V-model is a crucial framework for the design and development of complex systems, emphasizing the importance of testing at every level, including system, subsystem, and software. Effective validation at the system level involves numerous subsystems and their software interacting, making the testing process resource-intensive and time-consuming. During system-level testing, issues often arise that require fixes within various subsystems. After addressing these issues, retesting is necessary to ensure that the changes do not negatively impact overall
Sureka, Sumit, Rawat, Gautam, Ghosh, Soumik, Vidhu, Nandagopal
Optimizing Vehicle Dynamics: A Methodology for Reducing Correlation Gaps2026-26-00911/16/2026
Final design choices are frequently made early in the product development cycle in the fiercely competitive automotive sector. However, because of manufacturing tolerances design tolerances stiffness element fitment and other noise factors physical prototypes might show variations from nominal specifications. Significant performance differences (correlation gaps) between the digital twin representation produced during the design phase and real-world performance may result from these deviations. Measuring every system parameter repeatedly to take these variations into account can be expensive and impractical. The goal of this study is to identify important system parameters from system characteristic data produced by controlled dynamic testing to close the gap between digital and physical models. Dynamic load cases are carried out with a 4-poster test rig where vehicle responses are captured under controlled circumstances at different suspension locations. An ideal set of digital model
Verma, Rahul Ranjan, Goli, Naga Aswani Kumar, Prasad, Tej Pratap
Conceptual Framework for Real-Time Battery Health Estimation in Automotive Digital Twins Using Reinforcement Learning2026-26-06581/16/2026
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 modelling 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
Pardeshi, Rutuja Rahul, Kondhare, Manish, Sasi Kiran, Talabhaktula
Development of HIL Based Methodology for Over-The-Air Updates Validation2026-26-04801/16/2026
Over-the-Air (OTA) update technology has come forth as a transformative aider in the domain of automotive technology, allowing Original Equipment Manufacturers (OEMs) and Tier-1 suppliers of Electric vehicles (EVs) to frequently make software modifications, enhancements, and bug fixes that are essential to optimize the performance of powertrain components such as the motor controller unit (MCU), Battery Management System (BMS), and Vehicle Control Unit (VCU). This facilitates them to remotely supply updates to the vehicle firmware and software by giving inputs of calibration data without requiring physical access to the vehicle. However, as OTA updates have a direct impact on vehicle’s performance, safety and cybersecurity, a stringent validation methodology is of prime importance prior to deployment process. This paper explores the integration of Hardware-in-Loop (HIL) simulation into the OTA validation pipeline as a means to ensure reliability, safety, and functional correctness of
Khare, Shivani, Karle, Ujjwala, Subramaniam, Anand
AI-Driven Digital Twin for Enhanced Suspension Assembly Testing in Automotive Vehicles2026-26-04451/16/2026
This paper presents the development and implementation of a digital twin (DT) for the suspension assembly of automotive vehicles—an essential subsystem for assessing vehicle performance, durability, ride comfort, and safety. The digital twin, a high-fidelity virtual replica of the physical suspension system, is constructed using advanced simulation methodologies, including Finite Element Analysis (FEA), and enriched through continuous integration of empirical test data. Leveraging machine learning techniques, particularly Artificial Neural Networks (ANNs), the DT evolves into a dynamic and predictive model capable of accurately simulating the behaviour of the physical system under diverse operational conditions. The primary aim of this study is to enhance the precision and efficiency of suspension testing by enabling predictive maintenance, real-time system monitoring, and intelligent optimization of test parameters. The digital twin facilitates early detection of potential failures
Sonavane, Pravinkumar, Patil, Amol
Use Of Digital Wind Tunnel for Improved Aerodynamic Prediction2026-26-03721/16/2026
In the automotive industry, external aerodynamic evaluations in digital environments are commonly conducted using simplified, large box tunnels with vehicle being static. These approaches are computationally efficient and ensure faster turnaround time. To closely replicate physical wind tunnel testing or real-world conditions, these simulations are often augmented with moving ground and rolling tire configurations. While such setups provide valuable directional feedback for aerodynamic drag improvements, they frequently exhibit significant discrepancies when compared to physical wind tunnel test data. It is observed that key factors such as wind tunnel blockage effects, boundary layer suctions, when not properly accounted for, distort the local flow field dynamics and introduce errors in the simulations. With OEMs aiming to accelerate time-to-market for new vehicle launches, many aspire to minimize reliance on physical testing and maximize use of digital methods for design sign-off
Sharma, Sandeep Kumar, Chalipat, Sujit, Maiyya, Sandeep
A Digital Twin Framework for Real-Time Optimization of Solar-Integrated Energy Systems2026-26-04181/16/2026
In the context of increasing global energy demand and growing concerns about climate change, the integration of renewable energy sources with advanced modelling technologies has become essential for achieving sustainable and efficient energy systems. Solar energy, despite its considerable potential, continues to face challenges related to performance variability, limited real-time insights, and the need for reactive maintenance. To overcome these barriers, this work presents a Digital Twin framework aimed at optimizing solar-integrated energy systems through real-time monitoring, predictive analytics, and adaptive control. This work presents a Digital Twin framework designed to address the challenges of designing, operating, maintaining, and estimating renewable energy systems, specifically solar power, based on dynamic load demand. The framework enables real-time forecasting and prediction of energy outputs, ensuring systems operate efficiently and maintain peak performance across
R, Akash, Burud, Priti Raju, Gumma, Muralidhar
Virtual Paint Shop: Automotive E-coating Process2026-26-03651/16/2026
In automotive vehicle manufacturing, paint shop constitutes one of the highest energy intensive processes. This steers automotive OEMs to continuously improve production efficiency and reduce operational costs of the processes involved in paint shop through digital twin technologies. In addition, the push for shorter time-to-market emphasizes the need for simulation-based manufacturing processes, such as virtual testing and CAE simulations. The simulation-based processes enable faster and data-driven decision-making early in the product development cycle, thereby ultimately reducing cost and development time. Among the various stages in the paint shop, two of the important stages are: 1 Electro-dip coating (E-coating), also known as Electro-Deposition coating, which applies a corrosion-resistant primer to the Body-in-White (BIW). 2 Oven curing, which ensures the primer is properly bonded and cured for long-term protection and finish quality. To optimize the processes in these stages
Gundavarapu, V S Kumar, P, Vivekaanandan, Garg, Manish, Navelkar, Tanay, BS, Balachandran
Vehicle Usage Digital Twins: Mobility Analysis Test Case2026-26-03941/16/2026
In the evolving landscape of the automotive industry, this study presents an innovative approach to developing digital twins for driver profiles, establishing a standardized and scalable procedure for collecting and analyzing driving data on a global scale. The proposed methodology centers on the development of a robust cloud infrastructure, including Data Lake and associated services, designed for efficient storage and processing of large volumes of data from multiple markets and vehicle types. The research introduces an adaptable procedure for data collection campaigns, applicable to diverse global markets and encompassing a wide range of vehicles, from internal combustion engines to electric and hybrid models. A key feature of this approach is the establishment of advanced data decoding protocols, enabling precise interpretation of CAN network information from vehicles of different manufacturers and models, even when the CAN structure is not previously known. The study defines
Arturo, Rubio, Marín Saltó, Anna, Diaz, Francisco, Olivencia, Sergio
Testing and Validation of Future Mobility Vehicles using Realistic Digital Twin of Road Corridors and Tires2026-26-05801/16/2026
The automotive industry is rapidly evolving with technologies such as vehicle electrification, autonomous driving, Advanced Driver Assistance Systems (ADAS), and active suspension systems. Testing and validating these technologies under India’s diverse and complex road conditions is a major challenge. Physical testing alone is often impractical due to variability in road surfaces, traffic patterns, and environmental conditions, as well as safety constraints. Virtual testing using high-fidelity digital twins of road corridors offers an effective solution for replicating real-world conditions in a controlled environment. This paper highlights the representation of Indian road corridors as digital twins in ASAM OpenDRIVE and OpenCRG formats, emphasizing the critical elements required for realistic simulation of vehicle, tire, and ADAS performance. The digital twin incorporates detailed 3D road profiles (X-Y-Z coordinates), capturing the geometry and surface variations of Indian roads. The
Joshi, Omkar Prakash, Shinde, Vikram, Pawar, Prashant R
Integrated Quality Assurance Frameworks for Testing Advanced Automotive Systems in the Era of ADAS and E-Mobility2026-26-05681/16/2026
Ensuring the safety and functionality of sophisticated vehicle technologies has grown more difficult as the automotive industry quickly shifts to intelligent, electric, and connected mobility. Software-defined architectures, electric powertrains, and advanced driver assistance systems (ADAS) all require strong quality assurance (QA) frameworks that can handle the multi domain nature of contemporary vehicle platforms. In order to thoroughly assess the functionality and dependability of next generation automotive systems, this paper proposes an integrated QA methodology that blends conventional testing procedures with model-based validation, digital twin environments, and real-time system monitoring. The suggested framework, which includes hardware-in-the-loop (HIL), software-in-the-loop (SIL), and over-the-air (OTA) testing techniques, concentrates on end-to-end traceability from specifications to validation. Simulating intricate situations for ADAS, electric vehicle battery temperature
Komanduri, Arun Srinivas, Srivastava, Anuj
Software-Defined Vehicles: Architecting the Future of Intelligent and Connected Mobility2026-26-06911/16/2026
This paper presents a comprehensive technical review of the Software-Defined Vehicle (SDV), a paradigm that is fundamentally reshaping the automotive industry. We analyze the architectural evolution from distributed Electronic Control Units (ECUs) to centralized zonal compute platforms, examining the critical role of Service-Oriented Architectures (SOA), the AUTOSAR standard, and virtualization technologies in enabling this shift. A comparative analysis of leading High-Performance Computing (HPC) platforms, including NVIDIA DRIVE, Tesla FSD, and Qualcomm Snapdragon Ride, is conducted to evaluate the silicon foundation of the SDV. The paper further investigates key enabling technologies such as Over- the-Air (OTA) updates, Digital Twins, and the integration of Artificial Intelligence (AI) for applications ranging from predictive maintenance to software-defined battery management. We scrutinize the competing V2X communication standards (DSRC vs. C-V2X) and address the paramount
Ahmad, Aqueel, Hemanth, Khimavath, Kumar, Om, Kumar, Rajiv, Haregaonkar, Rushikesh Sambhaji
Achieving Full ASIL-B Level Functional Safety (FuSa) for Automotive Clusters2026-26-00081/16/2026
Integrating advanced technologies into modern vehicles has led to an increasing focus on Functional Safety (FuSa), especially for the Automotive Integrated Cluster Module (ICM) to ensure the safety of the driver and passengers. This paper highlights the need to bring certain ICM components under an Automotive Safety Integrity Level B (ASIL-B) context using Classic AUTOSAR. This paper discusses the challenges faced and the solutions implemented for achieving compliance with ISO 26262 standards along with the Classic AUTOSAR framework. We are proposing a standardized and structured methodology for the design of the components in compliance with the key safety principles, including Freedom from Interference (FFI), execution under privileged levels, and integrity verification, particularly by adopting Classic AUTOSAR frameworks. This paper also presents the Functional Safety (FuSa) goals for these components and also extend to their configuration management and updating strategies within
Singh, Iqbal, Kumar, Praveen
Introducing a Novel System Engineering Framework for the Safe Deployment of Software Defined-Vehicles2026-26-06901/16/2026
The past decade has seen a systemic shift in the automotive landscape and the constituent parts of a vehicle. The automotive industry has shifted from a primarily hardware components industry to a software heavy industry, with software controlling majority of the vehicle functions. Coupled with the ability to fully update or evolve a vehicle’s capabilities or functionalities, post point of sale through software updates, the technical, commercial and service landscape of the automotive industry is rapidly changing. This has brought increasing focus to the concept of Software Defined Vehicle, where the vehicle is not only constantly evolving, but is also becoming more personalised by leveraging data collected through the life of the vehicle. This requires a rethink of the current development and deployment approaches for vehicles, which are software-intensive. In this paper, we introduce a novel four-step system engineering framework for the safe development and deployment of Software
El Badaoui, Halima, Jame-Elizebeth, Mariat, Khastgir, Siddartha, Jennings, Paul
Artificial Intelligence in Passenger Cars: Unlocking Intelligent Mobility and Human-Centric Vehicle Innovation2026-26-06721/16/2026
Artificial Intelligence (AI) is radically transforming the automotive industry, particularly in the domain of passenger vehicles where personalization, safety, diagnostics, and efficiency. This paper presents an exploration of AI/ML applications through quadrant of the key pillars: Customer Experience (CX), Vehicle Diagnostics, Lifecycle Management, and Connected Technologies. Through detailed use cases, including AI-powered active suspension systems, intelligent fault code prioritization, and eco-routing strategies, we demonstrate how AI models such as machine learning, deep learning, and computer vision are reshaping both the user experience and engineering workflow of modern electric vehicles (EVs). This paper combines simulations, pseudo-algorithms and data-centric examples of the combined depth of functionality and deployment readiness of these technologies. In addition to technical effectiveness, the paper also discusses the challenges at field level in adopting AI at scale i.e
Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip
Reverse Engineering and Digital Twins in Powertrain Design: Enhancing Performance and Sustainability2026-26-00651/16/2026
This study explores the application of reverse engineering (RE) and digital twin (DT) technology in the design and optimization of advanced powertrain systems. Traditional approaches to powertrain development often rely on legacy designs with limited adaptability to modern efficiency and emission standards. In this work, we present a methodology combining 3D scanning, computational modeling, and machine learning to reconstruct, analyze, and enhance internal combustion engines (ICEs) and electric vehicle (EV) drivetrains. By digitizing physical components through RE, we generate high-fidelity DT models that enable virtual testing, performance prediction, and iterative improvement without costly physical prototyping. Key innovations include a novel mesh refinement technique for scanned geometries and a hybrid simulation framework integrating finite element analysis (FEA) and multi-body dynamics (MBD). Our case study demonstrates a 12% increase in thermal efficiency for a retrofitted ICE
Bernikov, Mark Alexandrovich, Kurmaev, Rinat
Virtual ECU: Development & Validation Platform2026-26-06831/16/2026
The 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
Singh, Jyotsana, Shaikh, Arshiya, Mane, Rahul, Burangi, Piyush
Architecting ATA 28 with Model-Based Systems Engineering: Center of Gravity Balance and System Performance01-18-03-00151/7/2026
The fuel management system for a fixed-wing aircraft has been developed and explored with the model-based systems engineering (MBSE) methodology for maintaining the center of gravity (CoG) and analyzing flight safety. The system incorporates high-level modeling abstractions that exploit a mix of behaviors and physical detail resembling real-world components. This approach enables analysis for a multitude of system requirements, verification, and failure scenarios at high simulation speed, which is necessary during system definition. Initially, the CoG is maintained by directly accessing the flight deck valves and pumps in both wings and controlling them through the bang-bang control law. In the refinement phase of the fuel system controller, the manual and individual controls of the valves and pumps are replaced with an autonomous fuel transfer scheme. The autonomous scheme achieves no more than a 20 kg difference in fuel between the wings during normal conditions. In the event of
Zaidi, Yaseen, Michalek, Ota
Optimizing Automotive Software Development for Hybrids through the V-Model Integrated with Functional Design and In-the-Loop Validation (SiL/HiL)2025-36-024912/18/2025
This paper presents a comprehensive analysis of advanced methods for optimizing software development in hybrid vehicles, focusing on the V-Model methodology integrated with Model-Based Systems Engineering (MBSE), functional design techniques and In-the-Loop validation processes, and the incorporation of agile methodologies such as SAFe (Scaled Agile Framework). The increasing complexity of embedded systems in hybrid vehicles, driven by electrification and the introduction of autonomous and connected systems, demands systematic and rigorous approaches to ensure reliability, safety, and energy efficiency. Over the next sections, we will explore the fundamental principles of the V-Model, its adaptations to the context of hybrid vehicles, the implementation of functional design processes supported by MBSE, the application of Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) methodologies for system validation, and finally the integration of agile SAFe principles to manage
Gomes, Cleber Willian, Natal, Icarus Lima
Research on Configuration Management of Civil Aircraft Electromechanical System2025-99-033312/17/2025
This paper presents an in-depth study on configuration management for civil aircraft electromechanical systems, grounded in process methodologies and practical experience of configuration management. Beginning with the definition and significance of configuration management, the study analyzes existing configuration management practices in domestic and international aviation enterprises. It systematically examines the requirements and frameworks for configuration management in civil aircraft electromechanical systems, refining critical elements through two primary dimensions: the establishment, refinement and implementation of configuration management processes. Critical refined elements are highlighted to offer actionable insights for civil aviation enterprises in advancing their configuration management practices.
Cai, Yiyang
Requirement-Based Design Verification Processes for Commercial Airplanes2025-99-035012/17/2025
Civil vehicles, commonly seen as complex products, involve many high-tech aspects, several fields working together, many investments spent on projects, and challenging management. Through the entire life-cycle of aircraft development, the application of requirement-driven systems engineering methodologies helps to manage the aircraft development process while addressing the needs of the market and of stakeholders. The operational needs of an aircraft are design inputs for aircraft development, and the precision, authenticity, and comprehensiveness of these needs influence the efficiency of the development processes and the quality of the products. When the design and research-and-development activities are based on accurate and complete needs, the development interval for such projects can be shortened significantly, and the costs of R&D lowered. Especially because it is one of the fundamental phases of establishing whether aircraft meet the design requirements, design verification is
Wang, Yi, Huang, Junkai, Zhang, Xinyu
Efficient Tunnel Modeling in Unity3D with Data-Driven CSG Approach2025-99-034912/17/2025
Tunnels are vital infrastructures in daily life. To utilize digital twin technology for more efficient and convenient tunnel operation and maintenance, tunnel modeling serves as its foundation. However, existing tunnel modeling methods always suffer from high computational complexity, poor generalizability, and low expressive efficiency. This article proposes a data-driven tunnel modeling approach based on the Unity3D platform. Based on the actual engineering drawings, the method obtains the tunnel parameter set through the classification and feature analysis of the tunnel structure. A process-oriented model representation, i.e. a Constructive Solid Geometry (CSG) tree is then employed, enabling the creation of portal models without dependence on specific data structures. Meanwhile, the mesh optimization idea of downward triangulation and the neighbor-edge detection mechanism are introduced to improve the expression efficiency while maintaining the integrity and correctness of the
Wu, Jianjie, Luo, Xingyu, Mei, Hongliang, Lu, Yuxiang, Wang, Zhiyuan, Chen, Weiya
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