Electric vehicles (EVs) are an environmental solution providing no harmful gases with low noise. High performance EV systems require high energy-efficiency traction motors such as permanent magnet synchronous motors (PMSMs). PMSMs according to its relative advantages are commonly used for high-performance EV drive systems. PMSMs have merits of high power-to-weight ratio, high torque per ampere ratio and high efficiency. For high performance EV system, the field-oriented control (FOC) based on PI-controllers is used with a lot of hardness such as the PI-controller tuning and operating constraints. Model predictive control (MPC) can overcome such problems in FOC. In this paper, FOC and finite-set model predictive control (FS-MPC) techniques for an interior permanent magnet synchronous motor (IPMSM) are analyzed under different operating modes. For EV applications, IPMSMs are operated under maximum torque per ampere (MTPA) and field weakening (FW) operating modes. FS-MPC depends on the on-line solution of a Quadratic programming (QP) problem cost function to overcome problems of the cascaded structure of PI-controllers loops in FOC. The performance of the proposed two controllers is compared under the same operating conditions. Simulation results show that the proposed FS-MPC technique enhances the performances compared with the common ordinary cascaded structure FOC.