A Novel Intelligent Controller-Based Power Management System With Instantaneous Reference Current in Hybrid Energy-Fed Electric Vehicle

Nowadays, more than one power source is needed to fulfil the power demand for electric vehicles. The multiple sources enhance reliability regarding the cruising range and decrease the charging cost. However, the inclusion of multi-sources generally gives rise to issues in the controller unit, such as slow response due to the immediate changes in load and power conversion complexity while switching the sources. This paper presents a novel intelligent control scheme based on fuzzy logic to mitigate this issue. The proposed controller includes a solar panel, a fuel cell, and a battery as input source. In this work, to examine the instantaneous reference currents from the sources and to manage power for the electric vehicle motor, a permanent magnet synchronous machine (PMSM) is considered. The proposed controller performs real-time power management, Maximum power point tracking (MPPT) for the PV system, and load calculations based on vehicle dynamics. The proposed work explores power management techniques for efficient control by utilizing real-time irradiance data from the Solcast website and drive cycle data collected at a university campus. Finally, the proposed controller was developed using MATLAB/Simulink and implemented as a hardware investigation with the LabVIEW tool and FPGA controller for a 1 kW PMSM to validate that the controller enables consistent power split operation in different load conditions.