Energy power grid three-phase signal estimation and fault detection for electric vehicles

The increasing stress on the electric power distribution grid exposes the grid to different types of disturbances and faults. Recent technology enables electric vehicles (EVs) to act as a distributed energy storage source, so that the stress on the power grid is reduced. However, unexpected power grid changes may still lead to on-board-chargers (OBCs) damages on EVs. Thus, promptly detecting changes on the three-phase voltage signal coming from the grid is of paramount importance to adapt the grid to the new condition without affecting the OBCs. In this work, we propose a power grid fault detection method able to detect changes on the grid. The method is based on the estimation of the three-phase voltage signal from the grid using an Unscented Kalman Filter (UKF). The method is evaluated on data from a simulated power grid and from a real one, considering different power grid changes.