Purpose. To develop a methodology for simulating of an electromotive railway rolling stock in terms of power-optimal modes on a track with a given profile and a set motion graph. Methodology. We have used combined genetic algorithm to determine optimum modes of an electromotive railway rolling stock motion: a global search is performed by a genetic algorithm with a one-point crossover and roulette selection. At the final stage of the optimization procedure we have used Nelder-Mead method for the refinement of the optimum. Results. We have obtained that traction motor on a tramcar, while driving on a fixed site, has an excessive power of the cooling system. Its using only in the considered area allows to modernize the cooling system in the way of its power reducing, which in turn provides an opportunity to increase the overall efficiency of the electromotive railway rolling stock. Originality. For the first time, we have obtained the train motion equation in the program-oriented form. This allows to use it for determination of electromotive railway rolling stock optimal control laws according to the Hamilton-Jacobi-Bellman method. Practical value. We have made the computer program to determine optimum modes of an electromotive railway rolling stock motion. The experimental studies of program results for the track section have confirmed the adequacy of the model, which allows to solve the traffic modes optimization problem for the tram track sections and increase the overall efficiency of the electromotive railway rolling stock. References 19, figures 3. Key words: electromotive railway rolling stock, genetic algorithm, cooling system, traction motor, tramcar, control laws, optimization problem, efficiency.Разработана методика моделирования движения асинхронного тягового двигателя при движении электроподвижного состава по энергооптимальным режимам на участке пути с заданным профилем и установленным графиком движения. Определены оптимальные режимы движения электроподвижного состава на основе метода Гамильтона-Якоби-Беллмана. Определение режимов работы тягового привода предложено проводить заранее на основании решения задачи условной оптимизации его режимов. Определение оптимальных режимов работы тягового привода было проведено на основе комбинированных методов условной минимизации функции. Использование предлагаемой методики позволяет повысить общий КПД электроподвижного состава. Библ. 19, рис. 3. Ключевые слова: электроподвижной состав, генетический алгоритм, система охлаждения, тяговый двигатель, вагон трамвая, законы управления, проблема оптимизации, коэффициент полезного действия.

Purpose. To develop the imitation model of the frequency converter controlled high-speed induction motor with a squirrel-cage rotor in order to determine reasons causes electric motor vibrations and noises in starting modes. Methodology. We have applied the mathematical simulation of electromagnetic field in transient mode and imported obtained field model as an independent object in frequency converter circuit. We have correlated the simulated result with the experimental data obtained by means of the PID regulator factors. Results. We have made the simulation model of the high-speed induction motor with a squirrel-cage rotor speed control in AnsysRMxprt, Ansys Maxwell and Ansys Simplorer, approximated to their physical prototype. We have made models modifications allows to provide high-performance computing (HPC) in dedicated server and computer cluster to reduce the simulation time. We have obtained motor characteristics in starting and rated modes. This allows to make recommendations on determination of high-speed electric motor optimal deign, having minimum indexes of vibrations and noises. Originality. For the first time, we have carried out the integrated research of induction motor using simultaneously simulation models both in Ansys Maxwell (2D field model) and in Ansys Simplorer (transient circuit model) with the control low realization for the motor soft start. For the first time the correlation between stator and rotor slots, allows to obtain minimal vibrations and noises, was defined. Practical value. We have tested manufactured high-speed motor based on the performed calculation. The experimental studies have confirmed the adequacy of the model, which allows designing such motors for new high-speed construction, and upgrade the existing ones. References 15, tables 3, figures 15.

Purpose. To develop the theoretical basis of electrical machines object-oriented design, mathematical models and software to improve their design synthesis, analysis and optimization. Methodology. We have applied object-oriented design theory in electric machines optimal design and mathematical modelling of electromagnetic transients and electromagnetic field distribution. We have correlated the simulated results with the experimental data obtained by means of the double-stator screw dryer with an external solid rotor, brushless turbo-generator exciter and induction motor with squirrel cage rotor. Results. We have developed object-oriented design methodology, transient mathematical modelling and electromagnetic field equations templates for cylindrical electrical machines, improved and remade Cartesian product and genetic optimization algorithms. This allows to develop electrical machines classifications models, included not only structure development but also parallel synthesis of mathematical models and design software, to improve electric machines efficiency and technical performance. Originality. For the first time, we have applied a new way of design and modelling of electrical machines, which is based on the basic concepts of the objectoriented analysis. For the first time is suggested to use a single class template for structural and system organization of electrical machines, invariant to their specific variety. Practical value. We have manufactured screw dryer for coil dust drying and mixing based on the performed object-oriented theory. We have developed object-oriented software for design and optimization of induction motor with squirrel cage rotor of AIR series and brushless turbo-generator exciter. The experimental studies have confirmed the adequacy of the developed object-oriented design methodology. References 12, figures 2.

in this paper Ansys Maxwell calculation result of 3D magnetic field in doublestator screw induction motor with hollow outer ferromagnetic rotor is given.

Purpose. To consider problems of electric machines optimization within a wide range of many variables variation as well as the presence of many calculation constraints in a single-criteria optimization search tasks. Results. A structural model for optimizing electric machines of arbitrary type using Microsoft Azure machine learning technology has been developed. The obtained results, using several optimization methods from the Microsoft Azure database are demonstrated. The advantages of cloud computing and optimization based on remote servers are shown. The results of statistical analysis of the results are given. Originality. Microsoft Azure machine learning technology was used for electrical machines optimization for the first time. Recommendations for modifying standard algorithms, offered by Microsoft Azure are given. Practical value. Significant time reduction and resources spent on the optimization of electrical machines in a wide range of variable variables. Reducing the time to develop optimization algorithms. The possibility of automatic statistical analysis of the results after performing optimization calculations. References 20, tables 3, figures 7. Рассмотрены проблемы оптимизации электрических машин при широком диапазоне варьирования многих переменных, наличии большого числа вычисляемых ограничений, в однокритериальных задачах оптимизационного поиска. Разработана структурная модель оптимизации электрических машин произвольного типа с применением технологии машинного обученияMicrosoft Azure. Продемонстрированы результаты, полученные с использованием нескольких методов оптимизации из базы Microsoft Azure. Показаны преимущества облачных расчетов и оптимизации на базе удаленных серверов. Приведенные результаты касаются решения однокритериальной задачи оптимизации с двумя переменными. Даны результаты статистического анализа полученных результатов. Даны рекомендации по применению машинного обучения Microsoft Azure в проектировании и оптимизации электрических машин. Библ. 20, табл. 3, рис. 7. Ключевые слова: электрические машины, оптимизация, алгоритм, набор данных, машинное обучение, Microsoft Azure, облачные расчеты.