Performance Evaluation of Solar-Battery Powered PMSM Driven LEV Drive Using Improved SMO with AQF-PLL Under Partial Shading Condition

Abstract

The range extension and sensor reduction are the key objectives for improving of practical feasibility of electrical vehicle (EV). In this paper, PV- battery powered permanent magnet synchronous motor (PMSM) is presented using improved sliding mode observer (SMO) with adaptive quadrant filter (AQF) phase locked loop (PLL) for light electric vehicle (LEV). For photovoltaic (PV) integrated EV, the problem of partial shading during running as well as stand still condition is high, which diminishes the performance of conventional maximum power point tracking (MPPT) algorithm. In this work, particle swarm optimization (PSO) based MPPT algorithm is used for PV panel operation under partial shading condition. In addition, this work aims to enhance the performance of the system by sensorless speed and position estimation using an improved SMO with AQF-PLL. Effectiveness of the system is demonstrated in MATLAB/ Simulink and obtained results for PMSM EV drive system are presented and discussed in detail.