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Electric vehicles are regarded as a significant way to mitigate the global energy crisis and the environmental pollution problem. Motor control is a very important part for electric vehicles. As for hardware, a motor controller usually has components such as a power module, microprocessor unit, IGBT driver, sensors, and resolver-to-digital convertor. As for software, a field-oriented control (FOC) with space vector pulse width modulation (SVPWM) is a popular method, while model predictive control (MPC) has recently shown great potential in motor drives. In this paper, both FOC and MPC are discussed and the performances are compared based on experiments. As the implementation is on a digital processor, the discretization and normalization are addressed, and the flux observer and speed estimation are discussed. Some practical issues for implementation are also talked about, such as field weakening control, overmodulation, etc. This paper focuses on how to implement the improved motor control for electric vehicles as industrial applications. The steady-state torque performances of this motor controller are verified by motor test-bench experiments. MPC shows as good performance as FOC in these experiments.