The Benchmarking of ESP Hardware-in-the-Loop Test Bench with Data from Real Vehicle

2012 ◽  
Vol 482-484 ◽  
pp. 478-482
Author(s):  
Jian Hua Li ◽  
Chuan Xue Song ◽  
Li Qiang Jin
Keyword(s):  
Simulation Model ◽  
Test Bench ◽  
High Accuracy ◽  
Great Benefit ◽  
Hardware In The Loop ◽  
Experiment Data ◽  
Development Period ◽  
The One ◽  
Real Vehicle

The development of ESP Hardware-In-the-Loop(HIL) test bench has brought great benefit to the development of ESP system and could shorten the development period. Therefore the accuracy of ESP HIL bench is crucial to the development of ESP system. The adjustment of vehicle parameters is an important section in the simulation model and it decides the accuracy of the bench to a great extent. The vehicle parameters from actual measurements are limited, so it is very difficult to obtain a high-accuracy simulation model. The article offers a way to solve this problem. With CANoe from Vector Corp., the experiment data were gathered from actual vehicle and returned to simulation model through CAN telecommunication. This will enable the simulation model to operate in the same mode of actual vehicle. By contrasting the output of response, the vehicle parameters will be adjusted step by step, until the response of simulation model is same as the one of actual vehicle.

Application of High-Linearity Analog Optocoupler in DSP Acquisition Circuit

2012 ◽  
Vol 232 ◽  
pp. 944-948 ◽  
Author(s):  
Ying Qi Tan ◽  
Xiang Yang Liu ◽  
Bao Qing Den
Keyword(s):  
High Accuracy ◽  
Least Square ◽  
Experiment Data ◽  
Good Linearity ◽  
High Linearity ◽  
Analog Signals ◽  
Noisy Signals ◽  
Method Of Least Square ◽  
Proper Design ◽  
Hardware Circuit

An applied hardware circuit for detecting the AGC signals isolated with DSP is designed based on a high-linearity analog optocoupler. The problem of narrow measuring scope, low linearity and instability which caused by noisy signals is resolved when collects industrial analog signals into DSP. The practical circuit with proper design of components is designed through repeated experiments. The experiment data are analyzed by the method of least-square. The analyzed results show this circuit has the high accuracy and good linearity.

IDENTIFICATION OF INTERHARMONICS BASED ON WAVELET PACKET TRANSFORM

2021 ◽  
Vol 3 (1) ◽  
pp. 031-036
Author(s):  
S. A. GOROVOY ◽  
◽  
V. I. SKOROKHODOV ◽  
D. I. PLOTNIKOV ◽  
◽  
...  
Keyword(s):  
Fourier Transform ◽  
Simulation Model ◽  
Frequency Domain ◽  
Time Domain ◽  
Wavelet Packet ◽  
High Accuracy ◽  
Wavelet Packet Transform ◽  
Mathematical Apparatus ◽  
Nonlinear Load ◽  
The Time Domain

This paper deals with the analysis of interharmonics, which are due to the presence of a nonlinear load. The tool for the analysis was a mathematical apparatus - wavelet packet transform. Which has a number of advantages over the traditional Fourier transform. A simulation model was developed in Simulink to simulate a non-stationary non-sinusoidal mode. The use of the wavelet packet transform will allow to determine the mode parameters with high accuracy from the obtained wavelet coefficients. It also makes it possible to obtain information, both in the frequency domain of the signal and in the time domain.

scholarly journals Mathematical Models for Predicting the Biodiesel Properties

2020 ◽  
Vol 9 (5) ◽  
pp. 2362-2376
Keyword(s):  
Fatty Acid ◽  
Physical Properties ◽  
Good Accuracy ◽  
Regression Coefficient ◽  
Cetane Number ◽  
High Accuracy ◽  
Good Relationship ◽  
Combine Fatty Acid ◽  
The One ◽  
Future Work

Density, viscosity and cetane number are important physical properties of biodiesel as they participate in one way or another in the fuel metering, calibration and nozzle process during combustion. High and good accuracy of the physical properties of biodiesel will therefore lead to improved combustion and therefore better efficiency. The aim of this study is therefore to seek good and high precision by combining properties and comparing the analysis between ANN and RSM. Studies have been made by researchers to collect data. In this study the combination of properties is exploited. A total of 1360 data from the various studies has been collected and exploited. From this data after elimination and treatment 39 possible combinations were analyzed and compared by ANN and RSM. The result of simulation is: The best combinations: 𝝆 = 𝒇(𝑭𝒂) , 𝝂 = 𝒇(𝑭𝒂) , 𝒄𝒏 = 𝒇(𝑭𝒂) with 𝑹 𝟐 respectively equal to (0.9998, 0.9998 , 0.9987) and R equal to ( 0.9997,0.99971,0.9984) obtained with ANN simulation provide more accuracy than 𝑹 𝟐 ( 0.912 , 0.799 , 0.766 ) and R ( 0.837, 0.739 , 0.920) obtained with RSM simulation in general 𝑹 𝟐 obtained with ANN (0.9998, 0.9998 , 0.9987) provide good accuracy than 𝑹 𝟐 (0.9112,0.799,0.766) obtained with RSM . Also there is a good relationship between fatty acid and others properties since they provide good result. In general the overall regression coefficient R and the correlation coefficient 𝑹 𝟐 values of the combinations obtained in the simulation with the ANN provide better and good accuracy since their values are close to each other and all close to 1, and their mse tend towards 0. While the one obtained with RSM are distant from each other and distant of 0 so they provide an acceptable accuracy.it is also important to note that high accuracy of properties using RSM must have at least combination of three parameters. Also after every combination, the conclusion says there is a good relationship between fatty acid and other properties. Then for the future work, it will be benefit to combine fatty acid with others properties and evaluate result, also use another network to simulate.

scholarly journals Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations

2021 ◽  
Vol 6 ◽  
Author(s):  
Tahani Aljohani ◽  
Alexandra I. Cristea
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Prediction Models ◽  
Short Term Memory ◽  
Methodological Approach ◽  
High Accuracy ◽  
Directional Model ◽  
Textual Representations ◽  
The One

Massive Open Online Courses (MOOCs) have become universal learning resources, and the COVID-19 pandemic is rendering these platforms even more necessary. In this paper, we seek to improve Learner Profiling (LP), i.e. estimating the demographic characteristics of learners in MOOC platforms. We have focused on examining models which show promise elsewhere, but were never examined in the LP area (deep learning models) based on effective textual representations. As LP characteristics, we predict here the employment status of learners. We compare sequential and parallel ensemble deep learning architectures based on Convolutional Neural Networks and Recurrent Neural Networks, obtaining an average high accuracy of 96.3% for our best method. Next, we predict the gender of learners based on syntactic knowledge from the text. We compare different tree-structured Long-Short-Term Memory models (as state-of-the-art candidates) and provide our novel version of a Bi-directional composition function for existing architectures. In addition, we evaluate 18 different combinations of word-level encoding and sentence-level encoding functions. Based on these results, we show that our Bi-directional model outperforms all other models and the highest accuracy result among our models is the one based on the combination of FeedForward Neural Network and the Stack-augmented Parser-Interpreter Neural Network (82.60% prediction accuracy). We argue that our prediction models recommended for both demographics characteristics examined in this study can achieve high accuracy. This is additionally also the first time a sound methodological approach toward improving accuracy for learner demographics classification on MOOCs was proposed.

A computer simulation model of forest fire suppression with air tankers

1979 ◽  
Vol 9 (3) ◽  
pp. 390-398 ◽  
Author(s):  
A. J. Simard
Keyword(s):  
Computer Simulation ◽  
Simulation Model ◽  
Historical Data ◽  
Fire Suppression ◽  
Cost Effective ◽  
Computer Simulation Model ◽  
Fire Dynamics ◽  
Data Output ◽  
The One ◽  
Fire Ground

A computer simulation model which evaluates air tanker productivity and effectiveness is described. Three hundred equations are required to define the model, which consists of five components: administration, the environment, the fire, ground suppression, and air tanker utilization. AIRPRO, a computer program based on the model, tests various combinations of air tanker resources and tactics and selects the one which minimizes suppression cost plus damage caused by fire. The program contains four loops: the fire, the tactic, the event, and fire dynamics (growth and suppression). The environmental, fire, and ground suppression components were validated by comparing model output with historical data. Output of the air tanker component was examined for reasonableness, compared with previous research, and a sensitivity analysis was performed. It is concluded that an assumption of model validity is reasonable. In applying the model in New Brunswick, it was found that medium sized land-based air tankers were the most cost effective, followed by small land-based air tankers. It was also found that a fleet of three or four aircraft would be optimum.

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