Analysis of optimal operating modes of the induction traction drives for establishing a control algorithm over a semiconductor transducer

Оптимізовано режими роботи тягового асинхронного приводу тепловоза за критерієм ефективності. Ідентифіковано оптимальні режими керування автономного інвертору напруги при різних температурах обмоток тягових двигунів. Проаналізовано оптимальні режими роботи тягового приводу тепловоза та трамваю, що дозволило встановити відмінності розташування точки переходу з просторово-векторної до однократної ШІМ від температури двигуна

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Simulation-based coyote optimization algorithm to determine gains of PI controller for enhancing the performance of solar PV water-pumping system

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on theCanis latransspecies, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler-Nichols and trial-error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities

Simulation and Optimization of Independent Renewable Energy Hybrid System

In this paper the majority of research refers to the optimal configuration of hybrid system that uses renewable energy and wind energy and solar radiation in association with diesel aggregate and batteries. These independent energy systems (hybrid systems) are becoming popular due to increasing energy costs and decreasing prices of turbines and Photo-Voltaic (PV) panels. But the only drawback is that their outputs depend upon the climatic conditions. The main goal to optimization a hybrid system is necessary to obtain the configuration of the system as well as the control strategy that minimizes the total cost through the useful life of the installation to meet the desired consumption and/or the pollutant emissions. The HOGA (Hybrid Optimizations by Genetic Algorithms) program was used to simulate the system operation and calculate technical economic parameters for each configuration. The system configuration of the hybrid is derived based on the data of wind and solar radiation which are related to the southern Croatian coast, as on a theoretical annual load at an observed location. Also, technical data for components are taken from the manufacturer’s specifications (datasheet). In this paper the advantages and disadvantages of commonly used types of generators (synchronous and asynchronous generators) are presented. Results show that the hybrid systems have considerable reductions in carbon emission and cost of the system

Determination of railway rolling stock optimal movement modes

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

Speed Control of Induction Motor using LQG

The electric motor is one of the technological developments which can support the production process. Not only in the manufacturing, but also in the transportation sector. The AC motor is divided into the synchronous and asynchronous motor. One type of asynchronous motor which widely used is the induction motor. In this study, the application of the IFOC control method and the LQG speed control method will be used to control the speed of an induction motor. The PID algorithm is also used as a comparison. Tests were carried out using MATLAB software. The speed variation and load variation are tested to validate the controller performance. PID is superior in terms of settling time and IAE. On the other hand, LQG is better in energy consumption. In terms of IAE, LQG has a higher value compared to PID by up to 56.67%. On the other hand, LQG is superior in terms of energy, which is 8.38% more efficient

A novel strategy for power sources management in connected plug-in hybrid electric vehicles based on mobile edge computation framework

This paper proposes a novel control framework and the corresponding strategy for power sources management in connected plug-in hybrid electric vehicles (cPHEVs). A mobile edge computation (MEC) based control framework is developed first, evolving the conventional on-board vehicle control unit (VCU) into the hierarchically asynchronous controller that is partly located in cloud. Elaborately contrastive analysis on the performance of processing capacity, communication frequency and communication delay manifests dramatic potential of the proposed framework in sustaining development of the cooperative control strategy for cPHEVs. On the basis of MEC based control framework, a specific cooperative strategy is constructed. The novel strategy accomplishes energy flow management between different power sources with incorporation of the active energy consumption plan and adaptive energy consumption management. The method to generate the reference battery state-of-charge (SOC) trajectories in energy consumption plan stage is emphatically investigated, fast outputting reference trajectories that are tightly close to results by global optimization methods. The estimation of distribution algorithm (EDA) is employed to output reference control policies under the specific terminal conditions assigned via the machine learning based method. Finally, simulation results highlight that the novel strategy attains superior performance in real-time application that is close to the offline global optimization solutions