No abstract

No abstract

No abstract

In this paper the performance of a split-phase motor and a three-phase induction motor drives for soft starting is evaluated. The paper systematically investigates and compares the characteristics of a variable voltage fed induction motor drive for two different types of soft starters; one based on IGBT and another based on Thyristor. Experimental validation is done using analogue circuit based system, developed in the laboratory. The novelty of the work lies in the development of simple and flexible models for simulation purpose and their experimental validation.

Recent changes to greenhouse gas emission policies are catalyzing the electric vehicle (EV) market making it readily accessible to consumers. While there are challenges that arise with dense deployment of EVs, one of the major future concerns is cyber security threat. In this paper, cyber security threats in the form of tampering with EV battery's State of Charge (SOC) was explored. A Back Propagation (BP) Neural Network (NN) was trained and tested based on experimental data to estimate SOC of battery under normal operation and cyber-attack scenarios. NeuralWare software was used to run scenarios. Different statistic metrics of the predicted values were compared against the actual values of the specific battery tested to measure the stability and accuracy of the proposed BP network under different operating conditions. The results showed that BP NN was able to capture and detect the false entries due to a cyber-attack on its network. Index Terms-Electric vehicle, Cyber security, neural network, state of chargeI.