RESUMEN
The rapid development in the field of electric vehicles requires a careful evaluation of the design process. The presence of a simulation model of the electric vehicle can effectively detect many faulty areas during the development process without risks. The MATLAB and Simulink environment is considered one of the most important tools used in the simulation process. In this paper, we will present the model of electric car used for transporting postal parcels (postal cars). The model includes simulating the operation of a permanent magnet synchronous electric motor. We will assume that the car is moving according to a driving cycle. The results will show the torque forces required to achieve the required speed. We will further calculate the traction and the resistance forces during the driving cycle and the engine efficiency in addition. Perhaps the most important problem facing electric car designers is calculating the amount of energy consumed from the battery or hydrogen fuel, and this is what was achieved as the result of the simulation process in this research. In the end, use one of the artificial intelligence tools (fuzzy controller) to improve battery life by providing the electric car driver with an alert system that will increase the ability to monitor the battery condition and thus increase battery life. The benefit of this paper emerges in realizing the importance of modeling and using simulation using artificial intelligence in developing the design of the electric car, specially the electric motor and battery size, and thus achieving one of the most important goals of the United Nations of preserving the environment and reducing carbon emissions.
RESUMEN
The cost of generating electricity in developing countries surpasses the government's ability to sustain it, necessitating the involvement of the private sector in this service provision through public-private partnerships (PPPs) contracts. In Syria, the electricity system has been highly susceptible to damage as a result of the ongoing crisis, leading to frequent and prolonged blackouts. This research focuses on addressing the need for a comprehensive system that aids decision-making for PPPs contracts in the country. By employing a combination of studies, reports, and interviews with domain experts, significant general and exclusive factors that guide decision-makers in PPPs contracts are identified and organized into questionnaires. These questionnaires are then filled out by professionals engaged in PPPs contracts. The collected data is analyzed and validated using SPSS software. However, due to insufficient data collected, generative adversarial neural networks (GAN) are utilized to enhance the research data. Additionally, Expert Choice and the analytic hierarchy process are employed to calculate weights for each factor. Remarkably, the calculated weights for both general and exclusive factors align with real-life strategies. General factors primarily address the financial and commercial considerations associated with PPPs, while exclusive factors primarily focus on the operational aspects of the electrical power system. These factors are arranged in descending order of effectiveness, enabling stakeholders to determine whether the private sector should be engaged in the project or if it should remain within the public sector's purview. The proposed system has demonstrated its reliability and can serve as a promising starting point for PPPs contracts.