This paper presents an advanced hybrid control approach combining Adaptive Neuro-Fuzzy Inference System (ANFIS) and Finite Control Set Model Predictive Current Control (FCS-MPCC) for a T-type multilevel inverter (T-MLI)-driven Permanent Magnet Synchronous Motor (PMSM) for Electric Vehicle (EV) application. The proposed Hybrid ANFIS-FCS-MPCC technique, alongside the T-MLI, is designed to enhance the power quality and improve the motor response by reducing the torque ripples, noise-vibration harshness (NVH), and improving the transient and steady-state response. The proposed technique resulted in a notable reduction, including a 66% drop in torque oscillations, a 50% reduction in speed overshoots, and a 33% minimization of current harmonic distortion, in comparison to the conventional MPCC methodology. MATLAB/SIMULINK platform is used to simulate the proposed technique and a prototype is developed in the laboratory to validate the efficacy of the proposed technique, Further, a comparative analysis is performed with the conventional techniques to show the effectiveness of the proposed technique in terms of motor speed, torque ripples, and stator current response.