Optimisation for Tractions’ Energy Storage System through Artificial Intelligence

Tang, Jie (2020) Optimisation for Tractions’ Energy Storage System through Artificial Intelligence. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

Energy Storage System (ESS) is used to store the regenerative energy generated in the traction system to reduce the power loss and energy consumption. The type of Energy Storage Devices (ESD) used will have a large influence on the performance of ESS and Hybrid Energy Storage System (HESS) in terms of energy and cost efficiency. This project developed a method for the optimum selection to improve the overall efficiency for the traction’s ESS through the use of random forest classifier model. Firstly, parameters of different types of ESS have been studied and tabulated to apply as the input and criteria for the classification and selection process. Then, the random forest classifier model is developed and tested using MATLAB for the decision making process. Next, a user interface is developed and combined with the random forest model to create a user friendly environment where the user interface allows users to input their desired ESD parameters and view the optimal ESD shown by the system on the user interface. The developed system is then tested using the collected data and the result is shown in methodology where it is found that the accuracy of the system is 100% when input data given are complete and within the dataset collected.