Browse Topic: Digital twin
ABSTRACT Digital Engineering practices and ecosystem capabilities [1] optimize designs by providing digital solutions with end-to-end information flows that are consistent from concept development, through test and experimentation, all the way to fully defined capabilities influencing systems across Ground Vehicle Brigade Combat Teams (GVBCT). This approach delivers: 1) improved development, demonstration, and assessment of autonomous vehicle capabilities, technologies, software, algorithms, controls, and performance; 2) a plug and play (PnP) interface for system-of-system and vehicle platform mission thread analysis and interoperability; and 3) 3D gaming technology to support advanced virtual scene generation and world model. The modernization of laboratory facilities to meet research and development (R&D) needs, support advanced technology development, and improved vehicle prototypes. The Brigade Level Integration Laboratory (BLIL) architecture provides a set of views composed using
Effective thermal management is crucial for vehicles, impacting both passenger comfort and safety, as well as overall energy efficiency. Electric vehicles (EVs) are particularly sensitive to thermal considerations, as customers often experience range anxiety. Improving efficiency not only benefits customers by extending vehicle range and reducing operational costs but also provides manufacturers with a competitive edge and potential revenue growth. Additionally, efficient thermal management contributes to minimizing the environmental impact of the vehicle throughout its lifespan. Digital twins have gained prominence across various industries due to their ability to accelerate development while minimizing testing costs. Some applications have transitioned to comprehensive three-dimensional models, while others employ model reduction techniques or hybrid approaches that combine different modeling methods. The discovery of unknown working mechanisms, more efficient and effective control
A digital twin is a virtual model that accurately imitates a physical asset. This can be as complex as an entire vehicle, a subsystem, and down to a small functioning component. The digital twin has a level of fidelity that aligns to the goals of the project team. The usage of a digital twin inside a digital engineering (DE) ecosystem permits architecture and design decisions for optimized product behavior, performance, and interactions. This paper demonstrates a methodology to incorporate the digital twin concept from requirement analysis, low fidelity feature level simulation, rapid prototypes running inside a System Integration Lab, and high fidelity virtual prototypes executing in an entirely virtual environment
The Software Production Factory (SPF) is a cyber physical construct of computers, hardware and software integrated together to serve as an ideation and rapid prototyping environment. SPF is a virtual dynamic environment to analyze requirements, architecture, and design, assess trade-offs, test Ground Vehicle development artifacts such as structural and behavioral features, and deploy system artifacts and operational qualifications. SPF is utilized during the product development as well as during system operations and support. The white paper describes the components of the SPF to build relevant Ground Vehicle Rapid Prototyping (GVRP) models in accordance with the model-centric digital engineering process guidelines. The factory and the processes together ensure that the artifacts are produced as specified. The processes are centered around building, maintaining, and tracing single source of information from source all the way to final atomic element of the built system
Proprietary, black box, and other hard-to-model subsystems are a leading source of schedule and labor cost across simulation supported analysis and lifecycle management. Using AI/ML technologies to rapidly develop and deploy digital twins of Hardware in the Loop (HWIL) and software systems reduces the Non-Recurring Engineering (NRE) in Modeling and Simulation (M&S) and supports validation of existing software digital twins. This approach also allows for portability of obsolete or proprietary components into a broader range of simulations or applications without exposing critical technologies. We present results of multiple case studies applying AI to black box components of interest to the ground vehicle community
Traditional live testing of autonomous ground vehicles can be augmented through use of digital twins of the test environment, the vehicle mobility models, and the vehicle sensors. These digital twins combined with the autonomous software under test allow testers to inject faults, weather, obstacles, find edge case scenarios, and collect information to understand the decision making of the autonomous software under test. With this new capability, autonomous ground vehicles can now be tested in four stages. The first stage is testing the autonomous software using digital twins. In this stage with the help of a High-Performance Computer thousands of scenarios can be run. Once issues are communicated and addressed, stage two, hardware in the loop testing can begin. Hardware in the loop uses simulators that already exist to test systems such as autonomous convoys with a virtual leader and a live follower. Stage three employs a live virtual constructive approach by using one vehicle to test
Thin cylindrical shells are ubiquitous structural elements in aerospace structures, and they experience catastrophic buckling under axial compression. The recent advancements in theoretical and numerical studies aided in realising the role of localisation in shell buckling. However, the instantaneous buckling made it unfeasible for the experimental observations to corroborate the numerical results. This necessitates high-fidelity shell buckling experiments using full-filed measurement techniques. Cutouts are deliberate and inevitable geometrical imperfections in actual structures that could dictate the buckling response. Additive manufacturing makes fabricating shells with tailored imperfections and studying various conceivable designs feasible. Consequently, to comprehend the effect of circular cutout on the buckling response, cylindrical shells are 3D printed in thermoplastic polyurethane (TPU) with a circular cutout of a specific size that could significantly shorten the buckling
To learn about the use of digital twins for machining operations in industry, I interviewed Gisbert Ledvon, VP of Marketing at HEIDENHAIN Corporation, Schaumburg, Illinois
With the advent of this new era of electric-driven automobiles, the simulation and virtual digital twin modeling world is now embarking on new sets of challenges. Getting key insights into electric motor behavior has a significant impact on the net output and range of electric vehicles. In this paper, a complete 3D CFD model of an Electric Motor is developed to understand its churning losses at different operating speeds. The simulation study details how the flow field develops inside this electric motor at different operating speeds and oil temperatures. The contributions of the crown and weld endrings, crown and weld end-windings, and airgap to the net churning loss are also analyzed. The oil distribution patterns on the end-windings show the effect of the centrifugal effect in scrapping oil from the inner structures at higher speeds. Also, the effect of the sump height with higher operating speeds are also analyzed. The net churning losses obtained from the simulations are compared
Accelerated adoption of electric propulsion system in mobility industry has stressed the time and iterations of product development cycle which was traditionally known to go over multiple iterations and phases. Current market demands a timely introduction of compelling products that brings high value to end user. Further, a growing emphasis over reducing mineral content using sustainable options and process, adds further complexity to multi-objective-optimization of electric drive systems. At BorgWarner our engineers use Digital-Twins, physics-based models which closely represent BorgWarner products in greater dept (physics) thus allowing an improved assessment of product design (components and systems) to target application at very early stage in product development. The spring success with Digital-Twin, BorgWarner furthered enhanced the model through introducing Artificial Intelligent (AI) and Machine Learning (ML) technologies in both modelling and virtual sensing. This paper will
The University of Detroit Mercy Vehicle Cyber Engineering (VCE) Laboratory together with The University of Arizona is supporting Secure Vehicle Embedded Systems research work and course projects. The University of Detroit Mercy VCE Laboratory has established several testbeds to cover experimental techniques to ensure the security of an embedded design that includes: data isolation, memory protection, virtual memory, secure scheduling, access control and capabilities, hypervisors and system virtualization, input/output virtualization, embedded cryptography implementation, authentication and access control, hacking techniques, malware, trusted computing, intrusion detection systems, cryptography, programming security and secure software/firmware updates. The VCE Laboratory testbeds are connected with an Amazon Web Services (AWS) cloud-based Cyber-security Labs as a Service (CLaaS) system, which allows students and researchers to access the testbeds from any place that has a secure
The context for real-world emissions compliance has widened with the anticipated implementation of EU7 emissions regulations. The more stringent emissions limits and deeper real-world driving test fields of EU7 make compliance more challenging. While EU6 emissions legislation provided clear boundaries by which vehicle and powertrain Original Equipment Manufacturers (OEMs) could develop and calibrate against, EU7 creates additional challenges. To ensure that emissions produced during any real-world driving comply with legal limits, physical testing conducted in-house and in-field to evaluate emissions compliance of a vehicle and powertrain will not be sufficient. Given this, OEMs will likely need to incorporate some type of virtual engineering to supplement physical testing. In this respect, the HORIBA Intelligent Lab virtual engineering toolset has been created and deployed to produce empirical digital twins of a modern light-duty electrified gasoline Internal Combustion Engine (ICE
The Auto industry has relied upon traditional testing methodologies for product development and Quality testing since its inception. As technology changed, it brought a shift in customer demand for better vehicles with the highest quality standards. With the advent of EVs, OEMs are looking to reduce the going-to-market time for their products to win the EV race. Traditional testing methodologies have relied upon data received from various stakeholders and based on the same tests are planned. The data used is highly subjective and lacks variety. OEMs across the world are betting big on telematics solutions by pushing more and more vehicles with telematics devices as standard fitment. The data from such vehicles which gets generated in high levels of volume, variety and velocity can aid in the new age of vehicle testing. This live data cannot be simply simulated in test environments. The device generates hundreds of signals, frequently in a fraction of seconds. Multiple such signals can
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