An improved energy requirement prediction for queueing applications of electric vehicles based on parameter estimation

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Berkay Sağlam Tez.pdf

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2022-8

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Sağlam, Berkay

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The use of electric vehicles has increased in recent years. Although they have many benefits to the environment such as reduced carbon emissions, charging of vehicles brings some new challenges for power systems such as overloading, reliability problems, etc. Charging of electric vehicles should be managed to overcome these problems. Queueing strategies are one of the management methods. These strategies are applied to obtain a feasible operation that depends on the decisions made considering system properties and the electricity market. Although there are several methods for queueing in the literature, there is a gap in determination of the load demand of the vehicle. The demand of a vehicle is related to the power consumption of that vehicle and can be calculated by using drivetrain models. These models help to calculate the power consumption of the vehicle by using mathematical models which are related to the vehicle parameters. The parameter values change with time due to aging effects. Therefore, they should be estimated to obtain accurate consumption information. This thesis proposes a method to estimate the parameter values and determine the load demand of a vehicle in order to make feasible queue decisions. The proposed method relies on the Least Squares Estimation method for parameters used in the utilized backward simulation based drivetrain model. In addition, the conditions of the route of individuals are concerned while determining the load requirements. Finally, an optimization method is presented for queueing applications to manage the system operation.

Subject Keywords

Parameter estimation for electric vehicles, Energy prediction for charging stations, Electric vehicle drivetrain modelling, Vehicle to grid applications, Linear programming

URI

https://hdl.handle.net/11511/99504

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

B. Sağlam, “An improved energy requirement prediction for queueing applications of electric vehicles based on parameter estimation,” M.S. - Master of Science, Middle East Technical University, 2022.