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.
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.
