Simulation-Dynamic Modeling Of Supply Chains Based On Big Data

Volneikina, E S; Kukartseva, O. I.; Menshenin, Andrew; Tynchenko, V. S.; Degtyareva, Kseniya

doi:10.1109/infoteh57020.2023.10094168

Cited by 37 publications

(8 citation statements)

References 21 publications

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“…In order to determine the charging and discharging currents of the battery pack when driving a standardised cycle [29][30][31], a mathematical model of the traction electrical equipment system of an electric vehicle was developed in this work [32]. The mathematical model of an electric vehicle allows us to obtain the performance characteristics of the battery under different driving cycles [33].…”

Section: Mathematical Modelling Of the Traction Electrical Equipment ...mentioning

confidence: 99%

Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks

Malozyomov,

Martyushev,

Sorokova

et al. 2024

Mathematics

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Electric vehicles are one of the most innovative and promising areas of the automotive industry. The efficiency of traction equipment is an important factor in the operation of an electric vehicle. In electric vehicles, the energy stored in the battery is converted into mechanical energy to drive the vehicle. The higher the efficiency of the battery, the less energy is lost in the conversion process, which improves the overall energy efficiency of the electric vehicle. Determining the performance characteristics of the traction battery of an electric vehicle plays an important role in the selection of the vehicle and its future operation. Using mathematical modelling, it is shown that battery capacity, charging rate, durability and efficiency are essential to ensure the comfortable and efficient operation of an electric vehicle throughout its lifetime. A mathematical model of an electric truck including a traction battery has been developed. It is shown that, with the help of the developed mathematical model, it is possible to calculate the load parameters of the battery in standardised driving cycles. The data verification is carried out by comparing the data obtained during standardised driving with the results of mathematical modelling.

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Section: Mathematical Modelling Of the Traction Electrical Equipment ...mentioning

confidence: 99%

Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks

Malozyomov,

Martyushev,

Sorokova

et al. 2024

Mathematics

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show abstract

“…The results obtained allow us to obtain energy characteristics not only in driving cycles measured as a result of experimental studies, but also to calculate characteristics in standardised driving cycles with maximum reliability [67][68][69].…”

Section: Verification Of the Energy Performance Of An Electric Busmentioning

confidence: 99%

Determination of the Performance Characteristics of a Traction Battery in an Electric Vehicle

Malozyomov,

Martyushev,

Kukartsev

et al. 2024

WEVJ

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Electric vehicles are the most innovative and promising area of the automotive industry. The efficiency of a traction battery is an important factor in the performance of an electric vehicle. This paper presents a mathematical model of an electric truck, including modules for the traction battery to determine the depth of battery discharge during the operation of the electric truck, a traction electric system for the electric truck and a system for calculating traction forces on the shaft in electric motors. As a result of the modelling, the charging and discharging currents of an accumulator battery in a real cycle of movement in peak and nominal modes of operation in electric motors and at different voltages of the accumulator battery are determined. A functional scheme of a generalized model of the electric vehicle traction electrical equipment system is developed. An experimental battery charge degree, torques of asynchronous electric motors, temperature of electric motors and inverters, battery voltage and the speed of electric motors have been measured and analysed. The developed complex mathematical model of an electric vehicle including a traction battery, two inverters and two asynchronous electric motors integrated into an electric portal bridge allowed us to obtain and study the load parameters of the battery in real driving cycles. Data were verified by comparing simulation results with the data obtained during driving.

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“…All these methods of grouping neural networks for weather forecasting require large amounts of data and computational resources. In addition, it is important to carefully select the structure and parameters of neural networks and train them on a sufficient amount of diverse data to achieve good results [56,57].…”

Section: Description Of the Mathematical Model Of Neural Network Grou...mentioning

confidence: 99%

Analysis of a Predictive Mathematical Model of Weather Changes Based on Neural Networks

Malozyomov,

Martyushev,

Sorokova

et al. 2024

Mathematics

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In this paper, we investigate mathematical models of meteorological forecasting based on the work of neural networks, which allow us to calculate presumptive meteorological parameters of the desired location on the basis of previous meteorological data. A new method of grouping neural networks to obtain a more accurate output result is proposed. An algorithm is presented, based on which the most accurate meteorological forecast was obtained based on the results of the study. This algorithm can be used in a wide range of situations, such as obtaining data for the operation of equipment in a given location and studying meteorological parameters of the location. To build this model, we used data obtained from personal weather stations of the Weather Underground company and the US National Digital Forecast Database (NDFD). Also, a Google remote learning machine was used to compare the results with existing products on the market. The algorithm for building the forecast model covered several locations across the US in order to compare its performance in different weather zones. Different methods of training the machine to produce the most effective weather forecast result were also considered.

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Simulation-Dynamic Modeling Of Supply Chains Based On Big Data

Cited by 37 publications

References 21 publications

Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks

Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks

Determination of the Performance Characteristics of a Traction Battery in an Electric Vehicle

Analysis of a Predictive Mathematical Model of Weather Changes Based on Neural Networks

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