Underwater Simulators Analysis for Digital Twinning

A detailed battery pack model has been developed within Simcenter Amesim by Siemens Industry Software. The model illustrates the Battery Management System (BMS) control development process from Model in the Loop (MiL), Software in the Loop (SiL) to Hardware in the Loop (HiL). The battery pack model has been integrated in a validated vehicle model, which corresponds to an existing vehicle developed by Voltia, named the Voltia eVan. This originally diesel engine powered light duty trucks have been electrified. The electrified version has been tested on the roller bench at the Eindhoven University of Technology.The interest of detailing the battery pack model is to have access to a multiple virtual temperature and voltage sensors, which allows validating the balancing methodologies that could be integrated in a BMS. A real-time analysis of the model has been conducted to ensure the model is compatible with the control constraint of the BMS.Finally, the complete model has been connected to a functional BMS in order to validate the approach. For that purpose, several BMS functions have been implemented in the control model developed with MATLAB/Simulink, such as the state of charge (SOC) estimation, the cell balancing, the charge/discharging and the thermal management. Once the cosimulation in SiL environment has been validated, a test on HiL platform has been done in real-time condition in order to reproduce realistic cell balancing and to study charging strategies, which are key functions to ensure better lifetime of the battery.

Digital twins are a new paradigm for our time, offering the possibility of interconnected virtual representations of the real world. The concept is very versatile and has been adopted by multiple communities of practice, policymakers, researchers, and innovators. A significant part of the digital twin paradigm is about interconnecting digital objects, many of which have previously not been combined. As a result, members of the newly forming digital twin community are often talking at cross-purposes, based on different starting points, assumptions, and cultural practices. These differences are due to the philosophical world-view adopted within specific communities. In this paper, we explore the philosophical context which underpins the digital twin concept. We offer the building blocks for a philosophical framework for digital twins, consisting of 21 principles that are intended to help facilitate their further development. Specifically, we argue that the philosophy of digital twins is fundamentally holistic and emergentist. We further argue that in order to enable emergent behaviors, digital twins should be designed to reconstruct the behavior of a physical twin by “dynamically assembling” multiple digital “components”. We also argue that digital twins naturally include aspects relating to the philosophy of artificial intelligence, including learning and exploitation of knowledge. We discuss the following four questions (i) What is the distinction between a model and a digital twin? (ii) What previously unseen results can we expect from a digital twin? (iii) How can emergent behaviours be predicted? (iv) How can we assess the existence and uniqueness of digital twin outputs?

This article proposes a novel methodology aimed at streamlining the system’s development process. By examining existing state-of-the-art approaches and the capabilities inherent in Model-Based Systems Engineering (MBSE) tools, the article introduces a methodology centered around transforming a descriptive Systems Modeling Language (SysML) model into a digital twin. This virtual representation of the physical asset leverages real-time data and simulations to mirror its behavior and characteristics. When integrated with MBSE, this synergy allows for a comprehensive and dynamic approach, enhancing innovation by providing a holistic and adaptable framework for designing, analyzing, and optimizing complex systems throughout their lifecycle. The practical application of this Real-Time Communication and Data Acquisition (RT-CDA) methodology is implemented in a context and operational scenario of an electric unmanned autonomous vehicle employing both Software-in-the-Loop (SITL) and Hardware-in-the-Loop (HITL) approaches. The methodology empowers systems engineers to iteratively update and refine their system model’s fidelity based on real-world testing insights. The article specifically demonstrates the real-time communication capabilities achieved between an electric unmanned autonomous vehicle (a physical asset) and a descriptive (SysML) model, illustrating the real-time data aspect integral to the concept of a digital twin. This study serves as a foundation for future endeavors, envisioning real-time communication among virtual and physical models to construct comprehensive digital twins of complex systems to predict behavior and performance.

The V-cycle has been the primary software development methodology in the automotive sector. However, with the increasing complexity of software, both from an architectural and technological perspective, software verification has become inefficient compared to system verification. This inefficiency results in rework and increased costs due to late error detection. Software deemed functional during verification may prove ineffective when tested in the simulated vehicle environment, as development requirements are ever-expanding, and test simulation environments have not kept pace with this evolution. The simulation environments used in automotive development are based on a guided simulation approach, encompassing Model-in-the-Loop (MiL), Software-in-the-Loop (SiL), Processor-in-the-Loop (PiL), and Hardware-in-the-Loop (HiL) testing. These tests are conducted between system and software verification and must be used in conjunction to achieve comprehensive validation. To address inefficiencies in software verification, techniques such as MiL, SiL, and PiL are excellent techniques. SiL, in particular, plays an essencial role in simulating code before its integration into the system. This rapid review will discuss techniques that make simulations more representative of the real vehicle system, considering the electromechanical structure of sensors and actuators outlined in the software requirements, as well as the network of ECUs, which follows a distributed communication model.

Digital twins are virtual counterparts of objects throughout their entire life cycle. Primarily adopted by NASA, today are a crucial component of the ongoing digital transformation. Civil engineering has spotted the benefits coming from digitization, but the current stage of technological adoption is still in its infancy. Digital twinning can empower the automation and efficiency of civil engineering and prepare it for future challenges. However, for the growth of the digital twinning idea, extended research and practical implementations are needed. Current trends in civil engineering, such as Building Information Modeling and Structural Health Monitoring, prepare civil engineering to adopt the concept of digital twins. Nevertheless, to fulfill the requirements of and benefit from multi-industrial digitization, civil engineering must evolute its methodologies in the digital twinning fashion. Reviewed examples of implementations (focusing on concrete bridges) show practical benefits for automating processes and increasing the resilience of structures. The article describes the key components of a proposed bridge digital twin framework: BIM, SHM, and Artificial Intelligence, and explains their roles in the digital twinning concept.

Digital twinning is a rapidly emerging technique for building virtual replicas of physical artefacts that can be used for a range of engineering purposes from design through to asset management. In this paper, we describe details of work to create a prototype example of a digital twin of a three-storey, small-scale building. The concept is based on combining information from a series of ‘digital components‘. Each component is managed by an ‘agent’ and operated within a software container. The containers are coordinated across a container network. This digital twin architecture allows us to combine information from heterogeneous sources including (but not limited to) computer-aided design, finite element analysis, ordinary differential equations and Bayesian calibration. The information in the digital twin is curated in an overall knowledge model of the structure based on a dynamic knowledge graph. The resulting digital twin can provide the user with a range of information, depending on the context. To illustrate the approach we describe how the digital twin functionalities can be used to answer natural language queries.

Distributed energy systems (DES), such as photovoltaics (PV), heat pumps (HPs), and electric vehicles (EVs), are being rapidly integrated into low-voltage (LV) grids, while measurement coverage remains limited. This paper presents a concept for an LV grid digital twin designed to enable real-time state estimation (SE) and operation-oriented studies under constrained measurement availability. Based on this concept, an exemplary digital twin is developed and demonstrated for a test area with a high PV penetration. The proposed digital twin integrates a topology-aware grid model, realistic parameterization, standardized IEC 61850 data modeling, and a real-time estimation pipeline that processes heterogeneous measurement data, including PV inverter power and voltage as well as transformer and feeder measurements. The approach is demonstrated through software-in-the-loop (SIL) experiments using historical playback and accelerated simulations, as well as hardware-in-the-loop (HIL) tests for real-time operation. The SIL results show that the digital twin enables continuous grid monitoring, enhances transparency for distribution system operators (DSOs), and leverages existing infrastructure to increase the effective PV hosting capacity. Selective PV curtailment mitigates congestion and restores normal operation, indicating a potentially cost-effective alternative to grid reinforcement. The HIL experiments emphasize the importance of high-quality, standardized data. The achieved accuracy depends on data availability and synchronization, highlighting the need for improved data integration. Overall, the proposed approach provides a viable pathway toward data-driven planning and operation of LV grids with high DES penetration.

The concept of Digital Twins has been in the field for a long time, constantly challenging the specification, modeling, design, implementation, and exploitation of complex cyber-physical systems. Despite the various foundations, standards, and platforms in Systems Engineering, there are ongoing challenges with Verification and Validation methodology. This study aims to establish a generic framework that addresses the various aspects of Digital Twinning. The multifaceted nature of the problem requires raising the abstraction level in both the Real (Actual) and Virtual domains, effective dissemination of information resources, and a design inspired by verification and validation. The proposed framework combines the Quintuple Helix model with the Problem and Operational Domains of a Real (Actual) Twin, the Solution and Implementation Domains of a Virtual Twin, and the Execution Domain as the bridge that links them. Verification and Validation dimensions follow the Meta Object Facility abstraction layers (Instance, Model, Meta-model, and Meta-meta-model) mapping over five Helices. Embedding the complexity reduction mechanisms in the proposed framework builds a suite for extendible and verifiable digital twinning in simulation and real-time scenarios.

Test processes in the automotive industry are tool-intensive and affected by technologically heterogeneous test infrastructures. In the industrial practice a product has to pass tests at several levels of abstraction such as Model-in-the-Loop (MIL), Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) tests. Different test systems are applied for this purpose (e.g. dSPACE MTest, dSPACE Automation Desk, National Instruments Teststand) and almost each test system requests its own proprietary test description language. The exchange of tests between different test systems and the reuse of tests between different test levels is normally not possible. Efforts to integrate these heterogeneous test environments, to address test exchange in a general manner and to standardize and harmonize the existing language environment are still at the beginning and not tailored towards the requirements of the automotive domain. To keep the whole development and test process efficient and manageable, the definition of an integrated and seamless approach is required. TestML – the test exchange language we present in this article – is defined to overcome the technological obstacles (different test language syntax and semantics, different data formats and interface descriptions) that almost automatically accompany the application of heterogeneous test tools and test infrastructures. TestML supports the exchange of tests between different test notations in a heterogeneous tool environment. In this paper, we introduce the XML schema of TestML and demonstrate the efficiency of the interchange format by giving examples from the model-based development of electronic control units. Tool support is illustrated by an application with Simulink/Stateflow.KeywordsTest BehaviorTest ExchangeSystem Under TestHybrid AutomatonTest ExecutionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

<div class="section abstract"><div class="htmlview paragraph">Given the current proliferation of active safety features on new vehicles, especially for Advanced Driver Assistance Systems (ADAS) and Highly Automated Driving (HAD) technologies, it is evident that there is a need for testing methods beyond a vehicle level physical test. This paper will discuss the current state of the art in the industry for simulation-based verification and validation (V&V) testing methods. These will include, but are not limited to, "Hardware-in-the-Loop (HIL)", “Software-in-the-Loop (SIL)”, “Model-in-the-Loop (MIL)”, “Driver-in-the-Loop (DIL)”, and any other suitable combinations of the aforementioned (XIL). Aspects of the test processes and needed components for simulation will be addressed, detailing the scope of work needed for various types of testing. The paper will provide an overview of standardized test aspects, active safety software validation methods, recommended practices and standards. The focus will be on trade-offs of cost and performance, as well as providing general guidance for the type of testing necessary for different phases of product development and implementation. Specific example applications, such as Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) functions, will be examined relative to the V&V processes.</div></div>

Digital twins offer a unique opportunity to design, test, deploy, monitor, and control real-world robotic processes. In this paper we present a novel, modular digital twinning framework developed for the investigation of safety within collaborative robotic manufacturing processes. The modular architecture supports scalable representations of user-defined cyber-physical environments, and tools for safety analysis and control. This versatile research tool facilitates the creation of mixed environments of Digital Models, Digital Shadows, and Digital Twins, whilst standardising communication and physical system representation across different hardware platforms. The framework is demonstrated as applied to an industrial case-study focused on the safety assurance of a collaborative robotic manufacturing process. We describe the creation of a digital twin scenario, consisting of individual digital twins of entities in the manufacturing case study, and the application of a synthesised safety controller from our wider work. We show how the framework is able to provide adequate evidence to virtually assess safety claims made against the safety controller using a supporting validation module and testing strategy. The implementation, evidence and safety investigation is presented and discussed, raising exciting possibilities for the use of digital twins in robotic safety assurance.

The paper aims to compare NX Mechatronic Concept Designer (MCD) and Tecnomatix Process Simulate (TPS) and their suitability for simulating mechatronic machines in digital twinning. A Digital Twin (DT) is a virtual model that serves as a real-time digital counterpart of a physical object or process. Compared to a conventional simulation, it differs in its ability to model the behavior of the actual counterpart from many points of view and with much greater complexity. Digital Twins have a crucial role in the Fourth Industrial Revolution but are also used in different areas like meteorology, traffic simulation in smart cities, and civil engineering. Digital Twins in industrial engineering help maintain the optimal pace of assembly lines, flexibly adapt production, increase manufacturing process efficiency, and generate cost-effective products. Increasing usage of IoT solutions drives the Digital Twin market, which is growing exponentially. The paper discusses the two software packages’ possibilities, advantages, and disadvantages and proposes the methodology and philosophy of making DT. The contribution of this work is to compare the possibilities of making mechatronic devices for educational and research purposes from scratch through to their final implementation.

There is an increasing need to perform real-time simulation of power plant performance behaviour using Hardware-in-the-loop (HiL) and/or Software-in-the-loop (SiL), particularly for HDVC grid connected wind power plants. Real-time simulation based on HiL/SiL can help mitigate grid connection challenges by allowing more realistic testing of the target system under different grid, weather and operational conditions, which is either impossible or costly to do on-site; hence, HVDC and wind power plants can be largely de-risked before connecting to the grid and start of operation. In this paper, the methods to develop source code based SiL models (same control code as in real products, such as Wind Turbine Generator) are investigated. Two main real-time simulation platforms are considered, i.e., RTDS and OPAL-RT. A common SiL execution platform based on IntervalZero is introduced, which can interface with both RTDS and OPAL-RT and thus, largely improve the interoperability and scalability of SiL models. In the end, a comparison between HiL and SiL models and between the SiL and PSCAD (offline) models are presented, including discussions about the intended use scenarios of real-time and offline simulation.

Deep-learning-enhanced digital twinning of complex composite structures and real-time mechanical interaction

Climate-smart forestry is a sustainable forest management approach for increasing positive climate impacts on society. As climate-smart forestry is focusing on more sustainable solutions that are resource-efficient and circular, digitalization plays an important role in its implementation. The article aimed to validate an automatic workflow of processing 3D pointclouds to produce digital twins for every tree on large 1-ha sample plots using a GeoSLAM mobile LiDAR scanner and VirtSilv AI platform. Specific objectives were to test the efficiency of segmentation technique developed in the platform for individual trees from an initial cloud of 3D points observed in the field and to quantify the efficiency of digital twinning by comparing the automatically generated results of (DBH, H, and Volume) with traditional measurements. A number of 1399 trees were scanned with LiDAR to create digital twins and, for validation, were measured with traditional tools such as forest tape and vertex. The segmentation algorithm developed in the platform to extract individual 3D trees recorded an accuracy varying between 95 and 98%. This result was higher in accuracy than reported by other solutions. When compared to traditional measurements the bias for diameter at breast height (DBH) and height was not significant. Digital twinning offers a blockchain solution for digitalization, and AI platforms are able to provide technological advantage in preserving and restoring biodiversity with sustainable forest management.