[Objective] To address the issues of poor steady-state control performance and stagnation of current increment updates in the model-free predictive current control (MFPCC) for permanent magnet synchronous motor, an improved MFPCC method based on discrete space vector modulation (DSVM) is proposed. [Methods] Firstly, DSVM technology was introduced to expand the voltage vector set. By dividing one control cycle into three equal segments to synthesize 37 virtual voltage vectors, the steady-state control performance of the system was effectively enhanced. Secondly, by defining unit voltage vectors and representing the voltage vector in a coordinate form, the current increment update was transformed into unit current increment establishment, thereby resolving the issue of current increment update stagnation in traditional methods. Furthermore, the theoretical coordinate range of the optimal voltage vector was analytically derived using the reference current increment to achieve voltage vector pre-screening, reducing the candidate vectors from 37 to 4. This significantly mitigated the sharp increase in computational burden caused by evaluating all voltage vectors. Finally, systematic experimental validation was conducted on a 2 kW experimental platform to verify the feasibility and effectiveness of the proposed method. [Results] Experimental results demonstrated that, compared with conventional MFPCC, the proposed method reduced the dq-axis current ripple from 5.4 A and 5.0 A to 3.1 A and 3.0 A under steady-state conditions at 900 r/min and 5 N·m load. The phase current total harmonic distortion was reduced from 17.36% to 7.43%, and torque ripple was effectively suppressed. Under dynamic conditions with speed stepping from 500 r/min to 1 000 r/min, the dynamic adjustment time was approximately 60 ms, which was comparable to that of traditional MFPCC. The execution time of the proposed method was 29.5 μs, only 1.9 μs longer than that of traditional MFPCC, supporting inverter switching frequencies up to 30 kHz. [Conclusion] The proposed improved MFPCC effectively enhances the steady-state performance of the MFPCC while maintaining low computational load.