A Study on the Real-Time Modeling Capabilities of the IDS Method

Author(s):  
M. Murakami ◽  
N. Honda
Keyword(s):  
The Real ◽  
Author(s):  
Chong Cao ◽  
Luting Wang ◽  
Bo Chen ◽  
Jason Harper ◽  
Theodore Bohn ◽  
...  

Real-Time simulation and Hardware-in-the-Loop (HIL) testing are increasingly adopted by industry for the development and validation of complex systems. This paper presents the real-time modeling and power management of a Vehicle-Grid Integration (VGI) system. The VGI system consists of six AC level 2 Plug-in Electric Vehicle (PEV) charging stations, a Photovoltaics (PV) farm, a commercial building load, and a switch connecting to 240V single phase power grid. PEV charging activities follow the SAE J1772 standard. An energy management algorithm is designed for the VGI system to coordinate the PEV charging with the building load and PV renewable generation. The coordination maintains the power consumption of the VGI system below utility’s demand charge pricing threshold. A real-time power system simulator, Opal-RT, is used in this study. The OPAL-RT system allows users to build detailed power system models using Matlab Simulink/SimPowerSystems and RT-LAB library, and run the models in real-time. The model-based approach enables the integration of power system models seamlessly with the power management algorithm and power electronics-level controllers. The simulation results show that the VGI model emulates the real system well and the coordinated PEV charging helps to balance the power generation and consumption of the VGI system to meet power management requirement.


2014 ◽  
Vol 17 (3) ◽  
pp. 83-91
Author(s):  
Uyen Thuy Xuan Phan ◽  
Chambers, Edgar IV ◽  
Padmanabhan, Natarajan ◽  
Alavi, Sajid

Shelf life can be simply defined as the duration of that the food remains acceptable for consumption. Determining shelf life of a product, thus, has become essential in quality control because consumer’s demands for safe and high quality products have increased. Accelerated shelf life testing (ASLT), which subjects the food to environments that are more severe than normal to speed up the deterioration process, has long been used in shelf life studies because it can help make decisions more quickly by minimizing time and it minimizes costs. The criterion used to determine shelf life can be the changes in either physical, chemical, biological or sensory characteristics. This study used sensory descriptive properties as the primary criteria to investigate the validity of using Accelerated Shelf Life Testing (ASLT) to determine shelf life of four extruded fortified blended foods (FBFs) compared to a real time model. The real-time environment was set at 300C and 65% relative humidity, based on the weather in Tanzania, the expected location of product use. The ASLT environment was at 500C and 70% relative humidity based on a Q factor of 2, which was equivalent to a one-week ASLT equals onemonth real time. The samples were evaluated for aroma and flavor by a highly trained descriptive panel for 3 time points in each shelf life model. Among the eighteen attributes tested, rancid and painty were the main sensory criteria to determine the shelf life of the products. The ASLT shelf life predictive model was consistent with the real time shelf life for three of the samples. However, it failed to predict the real time shelf life of the fourth similar sample. This affirms the essential use of real time modeling in shelf life study for a new product, even when an accelerated model has been developed for other similar products in the same category. ASLT testing can still be used, but only for early guidance or after validation.


2014 ◽  
Vol 568-570 ◽  
pp. 1036-1040 ◽  
Author(s):  
Hua Cong Li ◽  
Hong An Zhang ◽  
Xiao Bao Han ◽  
Jiang Feng Fu

Since the solving process of hydraulic dynamic simulation is complex and computational ineffectiveness,the aero-engine actuators real-time modeling is presented in this paper. Combined with the precise model, the convergence of the model and flow coefficient is analyzed. The real-time model operates a number of solving processes in one 20ms simulation cycle and the convergence of fix-step algorithm is guaranteed by adjusting the relevant parameters. The simulation shows that the real-time model can improve the computational efficiency with satisfactory real-time performance and precision.


2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Umar Khan ◽  
Jamil Ahmad ◽  
Tariq Saeed ◽  
Sikandar Hayat Mirza

Author(s):  
Francesco Ghigliazza ◽  
Alberto Traverso ◽  
Matteo Pascenti ◽  
Aristide F. Massardo

This paper reports on the latest application of a generic time-dependent real-time simulation tool, originally developed for fuel cell gas turbine hybrid systems, and now applied to an actual micro gas turbine test rig. Real-time modeling is a recognized approach for monitoring advanced systems and improving control capabilities: applications of real-time models are commonly used in the automotive and aircraft fields. The overall objective is improving of calculation time in existing time-dependent simulation models, while retaining acceptable accuracy of results. The real-time modeling approach already applied to fuel cell gas turbine systems has here been validated against the experimental data from the micro gas turbine Turbec T100 test rig in Savona, Italy. The real-time model of the microturbine recuperator has been newly developed to fit such an application. Two representative transient operations have been selected for verification: the heating and cooling phases of the connected volume. The results already show an acceptable agreement with measurements, and they have contributed to a better insight into performance prediction for the entire plant.


2020 ◽  
Author(s):  
Christian Möstl ◽  
Rachel L. Bailey ◽  
Ute V. Amerstorfer ◽  
Tanja Amerstorfer ◽  
Andreas J. Weiss ◽  
...  

<p>We introduce Helio4cast, an open source python package to provide real time solar wind predictions at the Sun-Earth L1 point, and to directly couple them to forecasts of the aurora oval, geomagnetically induced currents and further geomagnetic indices. We present its current status, using a combination of our PREDSTORM solar wind forecast and the real time modeling of the aurora with the OVATION model. The solar wind prediction is driven by data from either STEREO-A, a recurrence model, an empirical background solar wind model or a future L5 mission. For coronal mass ejections (CMEs), we plan to use our semi-empirical 3DCORE model to produce in situ magnetic flux rope signatures constrained by real-time solar observations, or a machine learning approach based on many previous observations of in situ CMEs. We are particularly interested in how the errors in the solar wind prediction propagate to ground-based observations. Challenges and future plans of the real-time implementation are discussed.</p>


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