Real-time Simulation Capability Research Articles

Energy harvesting from fuel cell bicycles for home DC grids using soft switched DC–DC converter

Fuel cell vehicles (FCVs) are gaining significance due to their potential to reduce greenhouse gas emissions and dependence on fossil fuels. Their efficient fuel cell cycle makes them ideal for last-mile transportation, offering zero emissions and longer range compared to battery electric vehicles. Additionally, the generation of electricity through fuel cell stacks is becoming increasingly popular, providing a clean energy source for various applications. This paper focuses on utilizing the energy from fuel cycle bicycles when it's not in use and feeding it into the home DC grid. To achieve this, a dual-phase DC to DC converter is proposed to boost stack voltage and integrate with the 24 V DC home grid system. The converter design is simulated using the PSIM platform and tested in a hardware-in-the-loop (HIL) environment with real-time simulation capabilities.

Multi-Electric Aero Engine Control and Hardware-in-the-Loop Verification with Starter Generator Coordination

The starter generator, characterized by controllable starting torque and disturbance in generator load torque, poses challenges for the multi-electric aero engine control. The key to addressing this issue lies in multi-electric aero engine control with the collaboration of a starter generator. Firstly, a multi-electric aero engine model is established, comprising a full-state turbofan engine model to enhance low-speed simulation capability and an external characteristic model of a starter generator to improve real-time simulation capability. Subsequently, the control methods for a multi-electric aero engine with starter generator coordination are proposed in three processes, including the starting process, acceleration/deceleration process, and steady-state process. During the starting process, the acceleration is controlled by coordinating the torque of the starter generator and the fuel of the aero engine. During the acceleration/deceleration process, the fuel limit value is adjusted based on the electrical load of the starter generator. During the steady-state process, the fuel is compensated based on the q-axis current of the starting generator in response to load torque disturbance. Finally, hardware-in-the-loop simulation experiments are conducted for the control of a multi-electric aero engine. The results show that the coordination reduces the oscillation of the acceleration during the startup of a multi-electric aero engine, enhancing its ability to resist disturbances from electrical load fluctuations during power generation.

A Real-Time Capable Simulation of Open Volumetric Receiver Surface Temperatures With Spatially High Resolution

The performance of open volumetric receivers can profit from advanced control of the heliostat aim points and the air mass flow. Advanced control techniques like model predictive control and state observer are based on dynamic system models. A suitable model for this purpose is introduced and validated with data recorded at the solar tower Jülich. The model shows good performance with respect to the dynamics of individual absorber cups. The simulation of the whole receiver requires an advanced optimization of the model parameters.

Advancing Smart Cyber Physical System with Self-Adaptive Software

The proposed integration of DevOps and Digital Twins presents a ground-breaking approach to enhancing the resilience and adaptability of Cyber-Physical Systems in the context of Industry 4.0 and the forthcoming Industry 5.0 era. This research explores the synergistic potential of DevOps principles in fostering collaborative and efficient development and maintenance processes for embedded systems and distributed control systems within CPS. Concurrently, the utilization of Digital Twins offers real-time monitoring and simulation capabilities, heralding a shift towards a human-centric approach to CPS operation. The emphasis on self-adaptive systems within CPS anticipates the ability to address dynamic conditions and unforeseen challenges, paving the way for the evolution of resilient and responsive industrial systems. This research explores the integration of DevOps and Digital Twins in the context of Industry 4.0 and anticipates the requirements of Industry 5.0, emphasizing the need for resilient and human-centric Cyber-Physical Systems. This study investigates the integration of DevOps and Digital Twins to enhance the resilience and adaptability of Cyber-Physical Systems in the context of Industry 4.0 and Industry 5.

An IoT and machine learning enhanced framework for real-time digital human modeling and motion simulation

The Digital Human Model (DHM) is a computational technique employed for simulating human motion and behavior, finding applications across sectors such as manufacturing, healthcare, and education. Despite its potential, current DHM simulations grapple with challenges like high computational costs, significant latency, low precision, and limited realism. Addressing these challenges, this paper introduces a novel DHM simulation approach that synergizes the Kinect motion capture system, Internet of Things (IoT) devices, and advanced machine learning techniques. Distinctively, our method captures real-time human motion data through IoT devices and the Kinect system, followed by data preprocessing and feature extraction. In contrast to traditional methodologies, we harness deep learning to establish time-series models, integrating convolutional neural networks and dilated convolutional kernels to amplify processing capabilities and cater to multi-scale data. Furthermore, we employ virtual reality technology to craft a digital human structural model, streamlining motion simulation and optimization. Experimental evaluations underscore that our approach consistently outperforms conventional methods across all metrics, demonstrating robust real-time simulation capabilities. In essence, this paper pioneers an innovative technological paradigm for DHM simulation, heralding new avenues for research and applications in related domains.

The interactive medical simulation toolkit (iMSTK): an open source platform for surgical simulation

Introduction: Human error is one of the leading causes of medical error. It is estimated that human error leads to between 250,000 and 440,000 deaths each year. Medical simulation has been shown to improve the skills and confidence of clinicians and reduce medical errors. Surgical simulation is critical for training surgeons in complicated procedures and can be particularly effective in skill retention.Methods: The interactive Medical Simulation Toolkit (iMSTK) is an open source platform with position-based dynamics, continuous collision detection, smooth particle hydrodynamics, integrated haptics, and compatibility with Unity and Unreal, among others. iMSTK provides a wide range of real-time simulation capabilities with a flexible open-source license (Apache 2.0) that encourages adoption across the research and commercial simulation communities. iMSTK uses extended position-based dynamics and an established collision and constraint implementations to model biological tissues and their interactions with medical tools and other tissues.Results: The platform demonstrates performance, that is, compatible with real-time simulation that incorporates both visualization and haptics. iMSTK has been used in a variety of virtual simulations, including for laparoscopic hiatal hernia surgery, laparoscopic cholecystectomy, osteotomy procedures, and kidney biopsy procedures.Discussion: iMSTK currently supports building simulations for a wide range of surgical scenarios. Future work includes expanding Unity support to make it easier to use and improving the speed of the computation to allow for larger scenes and finer meshes for larger surgical procedures.

Geometric Mapping Evaluation for Real-Time Local Sensor Simulation.

Medical augmented reality and simulated test environments struggle in accurately simulating local sensor measurements across large spatial domains while maintaining the proper resolution of information required and real time capability. Here, a simple method for real-time simulation of intraoperative sensors is presented to aid with medical sensor development and professional training. During a surgical intervention, the interaction between medical sensor systems and tissue leads to mechanical deformation of the tissue. Through the inclusion of detailed finite element simulations in a real-time augmented reality system the method presented will allow for more accurate simulation of intraoperative sensor measurements that are independent of the mechanical state of the tissue. This concept uses a coarse, macro-level deformation mesh to maintain both computational speed and the illusion of reality and a simple geometric point mapping method to include detailed fine mesh information. The resulting system allows for flexible simulation of different types of localized sensor measurement techniques. Preliminary simulation results are provided using a real-time capable simulation environment and prove the feasibility of the method.

An in-plane dynamic tire model with real-time simulation capability

This article introduces an in-plane dynamic tire model with real-time simulation capabilities. The tire belt is discretized into uniformly distributed mass points, and numerous massless contact elements are added between adjacent mass points. The efficient bending force calculation method and Savkoor dynamic friction coefficient formula are included in the model. Newton’s method and the Newmark-beta method are combined to solve the dynamic equations of the tire model, and the simulation results show that a reasonable model structure could meet the real-time calculation requirements. Particle swarm algorithm was used to identify the model parameters under different conditions. Finally, the model is validated and compared with the test data, showing that the model can express the static, steady-state, and high-frequency dynamic mechanical characteristics of the tire with high accuracy and efficiency.

A high-fidelity real-time capable dynamic discretized model of proton exchange membrane fuel cells for the development of control strategies

Advanced modeling tools are widely applied to enhance control strategies of proton exchange membrane fuel cells. Existing dynamic fuel cell models, however, still face a conflict between computational speed and simulation accuracy. To overcome this contradiction, a novel discretized fuel cell model is presented based on existing segmented modeling approaches. With a new twofold subdivision method and a newly designed interpolation algorithm, this model allows accurate investigation of the dynamic temperature, two-phase water, and current density distribution. Compared to the finite element method, the simulation duration of hours is reduced to minutes, while the characteristic of high-fidelity is maintained. Model validations are performed on both cell-level and stack-level to demonstrate the model's high accuracy and real-time simulation capability, illustrating the high potential for applying the model in the development of fuel cell control strategies.

Development of a novel real-time simulation of human skeleton/muscles

The objective of this research work was to develop a model of human skeleton with the capability of real-time simulation of the physical movements of a person in front of the motion capture hardware (Kinect) in order to analyze the motion data and measure the changes of joint torques. Mevea simulation software has been utilized for this purpose, which is a novel application of this software in the field of biomechanics. The model of the human skeleton was created in Mevea using the graphics built in 3ds Max. Simulink external interface for Mevea was established. Simulink acts as a connection between the Mevea software and Kinect for controlling the model. The developed model has been tested through three case studies involving the elbow joint, thoracic joint, and full body. Changes in torque and angular position of joints based on the input of joints are presented as graphs. The developed real-time model of the human skeleton in Mevea can execute the real-time simulation of a person's movements in front of a motion capture camera and provide the changes of torques, which are dependent on the angular positions of the body joints. This work provides the possibility to use the developed real-time model for physiotherapeutic rehabilitation to identify problematic muscles based on produced torque of the joints in order to specify the therapeutic options. The future research direction would be creating a reference databank by measuring healthy individuals' muscle forces for comparison purposes.

A versatile 3D computational model based on molecular dynamics for real-time simulation of the automatic powder filling processes

A versatile coupled three-dimensional (3D) computational model for real-time simulation of the automatic process of filling a complex shaped container with assorted powder granules from an arbitrary moving outer tank is proposed. Interactive tool for both visualization and physically accurate modelling of the dynamic behaviour of a wide range of granular materials is developed. The model combines molecular dynamics technique with detailed description of the 3D kinematics of a container with non-trivial geometry. The model of interparticle interactions and model of interactions between the particles and the 3D complex shaped moving wall are suggested. The virtual interactive environment enables to specify the number, size distribution and properties of particles, the configuration and law of time-dependent movement of the containers. The computational efficiency and real-time simulation capabilities of the method are demonstrated. An experimental verification of the model is performed.

Novel dynamic conditioning unit for the reproduction of real driving conditions on a test bed

The importance of thermal management has increased with the advent of electrification and fuel cell. The dynamic response required from the thermal circuit has also increased and cannot be reproduced by today’s conditioning systems. This contribution describes a novel, considerably more powerful conditioning concept with three main characteristics: The new conditioning concept is validated via simulation as well as by an application on a powertrain test bed. The system proved to be extremely robust in its function due to the consideration of all influencing parameters and, in addition, it is easy to use: no time-consuming configuration work is required prior to installation, nor when changing the test bed or the unit under test. The foundation for this is the model-based control that is based on a direct relationship between the temperature of the medium and the setpoint value. For the first time, temperature traces previously measured under real operation conditions can be reproduced and even temperature gradients of up to 60 K/s can be followed. The dynamic conditioning unit described here will be extended by a transient, real-time capable simulation model to a thermal emulator. This will enable future thermal management functions to be developed and optimized in ThermoLabs.

Estimation of Internal Gearbox Loads for Condition Monitoring in Wind Turbines Based on Physical Modeling

The share of wind energy in the public electricity supply in Europe is constantly growing, so that reliability and availability of wind turbines are becoming increasingly important. High availability is ensured by continuous condition monitoring, because it allows long downtimes to be avoided by reacting immediately to (imminent) failures. This paper presents a portable and real-time capable simulation model for determining internal loads on components in the mechanical drivetrain. The loads are apt for being utilized for a subsequent generation of a system reliability index in the scope of a decision support tool for demand- and degradation-oriented adjustments of the operational management. Thus, the work contributes to ensuring reliability. By determining the state of degradation of similarly loaded plants, under- or overloading of individual turbines can be proactively prevented. The analysis of the influence of individual model parameters is of particular importance here and provides evidence that even with a restricted parameter set the outputs of the load calculation model are accurate enough as inputs for a reliability calculation.

DPsim—Advancements in Power Electronics Modelling Using Shifted Frequency Analysis and in Real-Time Simulation Capability by Parallelization

Real-time simulation is an increasingly popular tool for product development and research in power systems. However, commercial simulators are still quite exclusive due to their costs and they face problems in bridging the gap between two common types of power system simulation, conventional phasor based, and electromagnetic transient simulation. This work describes recent improvements to the open source real-time simulator DPsim to address increasingly important use cases that involve power electronics that are connected to the electrical grid and increasing grid sizes. New power electronic models have been developed and integrated into the DPsim simulator together with techniques to decouple the system solution, which facilitate parallelization. The results show that the dynamic phasors in DPsim, which result from shifted frequency analysis, allow the user to combine the characteristics of conventional phasor and electromagnetic transient simulation. Besides, simulation speed up techniques that are known from the electromagnetic domain and new techniques, specific to dynamic phasors, significantly improve the performance. It demonstrates the advantages of dynamic phasor simulation for future power systems and the applicability of this concept to large scale scenarios.

Uncertainty-aware state estimation for electrochemical model-based fast charging control of lithium-ion batteries

Fast charging capability is considered a critical factor for the widespread adoption of electric vehicles. High charging currents can, however, severely affect battery health due to the danger of metallic lithium deposition on the anode and consequent degradation reactions. The charging speed should therefore be limited with respect to battery temperature, state of charge, and cell design, governing the onset point of lithium plating. Electrochemical models are a suitable tool providing continuous estimates of the anode potential as the main lithium plating indicator while covering a wide operational range. In this article, we present a novel charging control scheme based on a real-time capable simulation framework with adjustable model resolution. A profound investigation of error sources and modeling uncertainties motivates online state corrections towards a lower bound of the anode potential, which are realized by selective adjustments of the lithium distribution within electrode particles based on the full cell voltage error. Simulations of controlled and conventional CC charging profiles indicate the importance of continuously adapting the charging power for different operating conditions. Further, simulated state and parameter distortions as they might result from initialization and parameterization errors show that our estimation strategy can mitigate the risk of unsafe control operations.

Multi-SGI interconnected real-time HIL simulation of Yu’E MMC-HVDC project

With the interconnection of regional grid and wide application of HVDC and FACTS in power grid, the scale of grid is increasing rapidly, and this makes the power system simulation techniques face new challenges. In this paper, based on decoupling algorithm and high speed optical fiber communication, the interconnection between multi-SGI(multiple SGI supercomputers) is proposed to implement HYPERSIM co-simulation. The HIL test of Yu’E MMC-HVDC project is implemented using the HYPERSIM co-simulation platform, the test results verify the real-time simulation capability of the proposed scheme.

FLIGHTLABTMmodeling for real-time simulation applications

Modeling and simulation are used to support a wide range of applications including design, analysis, operations research, test and evaluation, training, etc. Each application has different fidelity requirements and computational limitations. Consequently, a variety of models are required to support a single aircraft type throughout its life cycle. Validation and configuration management of this array of models is costly. FLIGHTLAB[Formula: see text]is a software tool that supports selective fidelity modeling and simulation to insure trace-ability and commonality between models, ranging from the comprehensive models required for design to the real time models required for training and hardware-in-the-loop testing. Providing a single tool with this range of modeling options greatly enhances the configuration management capability. Also once the highest fidelity, comprehensive, model is validated, it can be used to provide reference data for validation of simpler models, thereby expediting the validation process for all levels of modeling. This paper describes the real-time simulation capability of FLIGHTLAB[Formula: see text]models and their trace-ability to higher level FLIGHTLAB[Formula: see text]models.

Real-time hybrid simulation of structures equipped with viscoelastic-plastic dampers using a user-programmable computational platform

A user-programmable computational/control platform was developed at the University of Toronto that offers real-time hybrid simulation (RTHS) capabilities. The platform was verified previously using several linear physical substructures. The study presented in this paper is focused on further validating the RTHS platform using a nonlinear viscoelastic-plastic damper that has displacement, frequency and temperature-dependent properties. The validation study includes damper component characterization tests, as well as RTHS of a series of single-degree-of-freedom (SDOF) systems equipped with viscoelastic-plastic dampers that represent different structural designs. From the component characterization tests, it was found that for a wide range of excitation frequencies and friction slip loads, the tracking errors are comparable to the errors in RTHS of linear spring systems. The hybrid SDOF results are compared to an independently validated thermalmechanical viscoelastic model to further validate the ability for the platform to test nonlinear systems. After the validation, as an application study, nonlinear SDOF hybrid tests were used to develop performance spectra to predict the response of structures equipped with damping systems that are more challenging to model analytically. The use of the experimental performance spectra is illustrated by comparing the predicted response to the hybrid test response of 2DOF systems equipped with viscoelastic-plastic dampers.

Real-time capable simulation of diesel combustion processes for HiL applications

The complexity of the development processes for advanced diesel engines has significantly increased during the last decades. A further increase is to be expected, due to more restrictive emission legislations and new certification cycles. This trend leads to a higher time exposure at engine test benches, thus resulting in higher costs. To counter this problem, virtual engine development strategies are being increasingly used. To calibrate the complete powertrain and various driving situations, model in the loop and hardware in the loop concepts have become more important. The main effort in this context is the development of very accurate but also real-time capable engine models. Besides the correct modeling of ambient condition and driver behavior, the simulation of the combustion process is a major objective. The main challenge of modeling a diesel combustion process is the description of mixture formation, self-ignition and combustion as precisely as possible. For this purpose, this article introduces a novel combustion simulation approach that is capable of predicting various combustion properties of a diesel process. This includes the calculation of crank angle resolved combustion traces, such as heat release and other thermodynamic in-cylinder states. Furthermore, various combustion characteristics, such as combustion phasing, maximum gradients and engine-out temperature, are available as simulation output. All calculations are based on a physical zero-dimensional heat release model. The resulting reduction of the calibration effort and the improved model robustness are the major benefits in comparison to conventional data-driven combustion models. The calibration parameters directly refer to geometric and thermodynamic properties of a given engine configuration. Main input variables to the model are the fuel injection profile and air path–related states such as exhaust gas recirculation rate and boost pressure. Thus, multiple injection event strategies or novel air path control structures for future engine control concepts can be analyzed.

Action-Level Real-Time Network-on-Chip Modeling

To simulate time-constrained operations and scheduling for Network-on-Chip (NoC) systems, we introduce a new set of component specifications at flit level grounded in Action-Level Real-Time DEVS formalism. These models capture the dynamics of NoC systems through action-based behavior under strict execution time intervals. These DEVS-based models are well-suited for development and simulation of asynchronous NoC architectures. This is achieved by extending the DEVS-Suite simulator to support real-time executions of ALRT-DEVS models. Representative simulation models capturing structure and behavior of prototypical Mesh NoC systems are developed. A set of experiments are designed, implemented, executed, and analyzed to show the kind of real-time simulation capabilities that can be achieved for Network-on-Chip systems.