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Young Ninja Group (ages 3-5)

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Vladimir Lukin
Vladimir Lukin

Powertrain System Analysis Toolkit Software ##HOT## Download


DIgSILENT GmbH is an independent software and consulting company providing highly specialised services in the field of electrical power systems for transmission, distribution, generation, industrial plants and renewable energy. DIgSILENT's innovative product portfolio comprises PowerFactory, StationWare and Monitoring Systems.




Powertrain System Analysis Toolkit Software Download



PowerFactory is a leading power system analysis software application for use in analysing generation, transmission, distribution and industrial systems. It covers the full range of functionality from standard features to highly sophisticated and advanced applications including windpower, distributed generation, real-time simulation and performance monitoring for system testing and supervision.


Ansys Motion is a fully integrated simulation environment that can be used to model Multibody Dynamics (MBD) of components and systems. Moreover, Motion employs a single solver to perform fast and accurate analysis for both stiff and flexible bodies, simultaneously.


Performance of the system, stress-safety analysis, heat transport, vibration, and fatigue are all important. For multibody dynamic system design, Ansys Motion is the most robust and comprehensive simulation solution available.


Ansys Motion is a versatile multibody dynamics-based next-generation engineering solution. It permits the study of stiff and flexible bodies quickly and accurately using a single solver system. Performing system motion performance, stress safety analysis, vibration analysis, and fatigue analysis throughout the design phase, helps reduce time-to-market in a variety of industrial applications. The integrated GUI of Motion provides a robust modeling environment for component and system analysis, which may be done independently or simultaneously, bringing up new possibilities during design and analysis.


The solver was created with the intention of combining the two fields of MBD and finite element (FE) analysis. Consequently, there are multiple connecting elements of rigid and flexible bodies. Because the system utilizes the numerically stable implicit integration method, the system is free from numerical noise and is very smooth and reliable.


This work develops Hardware-in-the-loop (HIL) simulation against cyber attacks. The test setup in Opal-EXata cyber attack example ( paper), is based on the software-in-the-loop (CSIL) MGC, however, the hardware-in-the-loop HIL testing is left for the developer. Thus, we design a light-weight intelligent electronic device (IED) that performs MGC, interfaces are developed based on IEC 61850 GOOSE protocol from/to the real-time simulation and the MGC. They are executed on two equipment stages, FPGA and BeagleBoneBlack. The concept behind using these boards is based on their low cost, flexibility, support for various interfaces/protocols, I/O pins, and ease of configuration. CSIL versus CHIL tests are used to evaluate the MG behavior against different cyber attacks. We also evaluate the MGC designed control function in accordance with IEC 61850 GOOSE protocol. Two scenarios was carried out, In the first scenario, the MG will be islanded in second 1, in this case the MGC will check the power balance and implement the power balance operation emergency condition (the difference not exceeds 3MW). If the check emergency condition becomes true, the MGC attempts to immediately disconnect the sheddable Load 4 to maintain the MG stability. Be that as a delay attack is introduced to the GOOSE trip command packets sent from the MGC to Load 4, the load shedding function may fail to operate in the required timeframe. In this case this will cause severe unbalance between generation/load relationship and oscillations on MG nominal operation parameters such as e.g., frequency, voltages etc. Through the C code available delay function within the MGC initial code, a one-second delay attack is applied to the MGC GOOSE message command. MGC based on its normal operation will receive measurements that is sent from each MG assists via GOOSE. Be that as a Man-in-the-middle attack is introduced to the load measurements data. Before the load measurements data being received by MGC. The data is manipulated in the middle of its way to the MGC. In this case, the MGC may take incorrect actions based on these received non-critical measurements. According to the test scenario 2, the active power measurement from Load 2 is duplicated by applying a packet manipulation attack to the GOOSE message. In this case, the MGC will take the incorrect action (false tripping) because it perceives the controlling operation emergency condition is true (total load will be more than 3MW greater than the total generation). As a result, a trip command is sent to disconnect Load 3. . It also causes oscillations on MG nominal operation parameters such as e.g., frequency, voltages etc. Comparison between both achieving testing results, SIL and HIL will be made within the rest of this work. The results are The development and performance of an MGC against cyber attack control schemes have been implemented in this paper. These are done by design and deployed on a light-weighted intelligent IED. The MGC control solution and its relevant communication system have been designed in compliance with the IEC 61850 and executed on two equipment stages, FPGA and BeagleBoneBlack. CSIL versus CHIL tests are used to evaluate/assess the MG behavior against different cyber attack scenarios. Moreover, we also evaluated IEC 61850 GOOSE protocol implementation, processing and finally control action performance. The obtained results demonstrate that the light-weight MGC approach and data modeling of various IEC 61850 predefined data object LNs are correct for the design of the power balance control/protection function against cyber attack. In addition, they demonstrate the successful implementations of the designed control/protection function and the modeled MGC LNs in various cyber-attack case studies on reliable detection of the emergency condition. Further work on the analysis of the data received by MGC, implementation of different cyber attacks and power balance detection algorithms is needed.


Smart grid applications, especially those focusing on the coordination of distributed flexibilities, include many devices governed by increasingly complex software architectures, all linked together by communication technology. In theory, some of these applications would have the potential to revolutionize the way the grid is being operated. However, in practice they are met with skepticism due to the uncertainties and vulnerabilities that these systems might introduce. Therefore, exhaustive testing and validation steps need to be undertaken before deployment to guarantee reliability. Approaching this task manually is extremely time-consuming and error prone. In this presentation we show an approach to automatically generate cyber-physical test beds which allow the evaluation of such applications. The proposed method uses PSAL (Power System Automation Language) to describe the cyber-physical system under test, i.e., the electrical network, the sensors, the actuators, as well as the various controllers/software components and their interconnections. Several model generators parse the PSAL code, and they automatically build a real-time simulation of the physical system; they establish various interfaces for the controllers to interact with the sensors and actuators; they package the controllers and deploy them to their designated locations; and they configure the data collection framework to enable the recording and analysis of experiment data.


The advancement of technology has allowed the exponential development of electric engineering applications, and several of these fields are: digital simulation in real-time in conjunction with synchro-phasor measurements in electrical power systems; the generation of data applying the Monte Carlo method; and the analysis of data by application of data mining techniques. Research on load-shedding schemes, together with the application of the above-mentioned fields, allows the prediction of certain events that have caused the disconnections of large amounts of load, and even the operating output (blackout) of large power systems, around the world.


As a global leader in virtual test driving technology, IPG Automotive develops innovative software and hardware solutions for the application areas autonomous vehicles, ADAS, e-mobility, Real Driving Emissions (RDE) and vehicle dynamics. In accordance with the automotive systems engineering approach, virtual test driving enables the seamless development, calibration, test and validation of entire systems in the whole vehicle in realistic scenarios.


Abstract:In this paper, we present a transition journey of automotive software architecture design from using legacy approaches and toolchains to employing new modeling capabilities in the recent releases of Matlab/Simulink (M/S). We present the seamless approach that we have employed for the software architecture modeling of a mixed-critical electric powertrain controller which runs on a multi-core hardware platform. With our approach, we can achieve bidirectional traceability along with a powerful authoring process, implement a detailed model-based software architecture design of AUTOSAR system including a detailed data dictionary, and carry out umpteen number of proof-of-concept studies, what-if scenario simulations and performance tuning of safety software. In this context, we discuss an industrial case study employing valuable lessons learned, our experience reports providing novel insights and best practices followed.Keywords: model-driven software engineering; software architecture modeling; systems engineering; modeling tool; best practices; electric vehicle powertrain; AUTOSAR


PSIM also integrates seamlessly with other Altair products(Activate, Embed, Flux/FluxMotor, MotionSolve) and with third-party software, and offers an integrated solution for multi-domain, multi-physics systems.


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