Кафедра "Електричні апарати"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/43

Офіційний сайт кафедри http://web.kpi.kharkov.ua/ea

Кафедра "Електричні апарати" була створена в 1931 році при Харківському електротехнічному інституті. Засновником, організатором і першим завідувачем кафедри був видатний фахівець в галузі електротехніки професор Вашура Борис Федорович.

Кафедра входить до складу Навчально-наукового інституту енергетики, електроніки та електромеханіки Національного технічного університету "Харківський політехнічний інститут", веде підготовку фахівців що мають глибокі знання з електромеханіки та різнобічні знання в області комп’ютерної техніки й інформаційних технологій.

У складі науково-педагогічного колективу кафедри працюють: 2 доктора технічних наук, 6 кандидатів технічних наук, 1 кандидат фізико-математичних наук; 5 співробітників мають звання доцента, 1 – старшого наукового співробітника.

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  • Ескіз
    Документ
    Optimization of accurate estimation of single diode solar photovoltaic parameters and extraction of maximum power point under different conditions
    (Національний технічний університет "Харківський політехнічний інститут", 2021) Akbar, Faizan; Mahmood, Tahir; Sadiq, Kamran; Ullah, Mian Farhan
    With the snowballing requirement of renewable resources of energy, solar energy has been an area of key concern to the increasing demand for electricity. Solar photovoltaic has gotten a considerable amount of consideration from researchers in recent years. Purpose. For generating nearly realistic curves for the solar cell model it is needed to estimate unknown parameters with utmost precision. The five unknown parameters include diode-ideality factor, shunt-resistance, photon-current, diode dark saturation current, and series-resistance. Novelty. The proposed research method hybridizes flower pollination algorithm with least square method to better estimate the unknown parameters, and produce more realistic curves. Methodology. The proposed method shows many promising results that are more realistic in nature, as compared to other methods. Shunt-resistance and series-resistance are considered and diode constant is not neglected in this approach that previously has been in practice. The values of series-resistance and diode-ideality factor are found using flower pollination algorithm while shunt-resistance, diode dark saturation current and photon-current are found through least square method. Results. The combination of these techniques has achieved better results compared to other techniques. The simulation studies are carried on MATLAB/Simulink.
  • Ескіз
    Документ
    Determination of railway rolling stock optimal movement modes
    (NTU "KhPI", 2017) Petrenko, O.; Liubarskiy, B.; Pliugin, V.
    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.