An improved model-free predictive current control (IMFPCC) method for synchronous reluctance motor (SynRM) drives is presented in this paper. The main advantages of previous MFPCC are that it does not require specific SynRM models and it requires neither motor parameters nor back-EMF estimations. However, this approach has two disadvantages: 1) two current measurements are required in each sampling period, which may lead to the detection of undesirable current spikes caused by instantaneous switching inside the inverter, and 2) an unresolved problem of stagnant current-variation updates, which undermines the prediction performance. This paper intends to eliminate these two drawbacks while retaining all the merits of MFPCC. The proposed IMFPCC is simple and easy to realize. Furthermore, no pulsewidth modulation (PWM) technique is required. A 32-bit microprocessor, TMS320F2809, is utilized to implement both the proposed IMFPCC and the model-based predictive current control (MBPCC) for a performance comparison. Experiment results are provided to validate the proposed method and verify its feasibility.

The four-switch three-phase (FSTP) inverters are known for their cost-effective advantages and minimal switching losses. However, such inverter topology's progress is lagging due to control constraints and requirements, including voltage vector limitations and parameter perturbations. To overcome the issue, this paper proposes a triple-voltage-vector model-free predictive current control (TVV-MFPCC) for FSTP inverter-fed surface permanent magnet synchronous motor (SPMSM) drives. The proposed TVV-MFPCC uses the principle of discrete-space-vector modulation (DSVM) to increase the voltage vector selections. Three primary voltage vectors, either the same or distinct, are linearly combined to yield the synthesized voltage vectors. A redundant voltage vector reduction scheme is also introduced to lessen calculations by optimally reducing the candidate voltage vectors to sixteen equivalent hybrid switching modes. To improve prediction accuracy, the TVV-MFPCC performs three different current readings and three current difference calculations in each sampling period. Experiments using a TMS320F28379D microcontroller are conducted to compare the performance of the proposed TVV-MFPCC against conventional MFPCC (C-MFPCC) and validate the scheme.

A novel model‐free predictive current control (MFPCC) approach for three‐phase AC/DC converters is proposed, which only measures the input currents and calculates their differences under different switching states. Existing model‐based predictive current control (MBPCC) methods are based on converter models and thus require the knowledge of input current, input and terminal voltages, resistance, and inductance. Compared to the MBPCC, the main advantages of the proposed MFPCC include eliminations of the converter model, multiplication operations, and tuning of system parameters. Simulation results show that the proposed MFPCC controls the input current slightly better than does the MBPCC. Experimental results are provided to validate the effectiveness of the proposed method, which are obtained from a three‐phase AC/DC converter under the specifications of 380 V output voltage, 220 V/AC input voltage, and 1000 W output power. The measured harmonics orders 2–19 are shown to meet the IEC61000‐3‐2 Class A standard under 1000 W of output power. To the authors’ best knowledge, it is the first MFPCC for such applications.

Model-free predictive current control (MFPCC) is a promising substitute for model predictive current control (MPCC). However, the performance of the MFPCC, to a large extent, hinges on the update frequency of its lookup table. Conventionally, the update is only performed when two successive switching states applied by the controller are identical, causing a stagnation problem to the current difference of those switching states that are not applied. To address the stagnation problem, this paper proposes a novel mechanism called synchronized current difference update for model-free predictive current control (SCDU-MFPCC). The presented scheme uses the model of permanent-magnet synchronous motor (PMSM) to construct equivalent differential stator currents corresponding to seven basic voltage vectors. To that end, current slope will be defined from the current difference of two successively applied voltage vectors. An updating factor associated with the current slope is then introduced into the prediction scheme to correct the enforced response of all switching states. This scheme is applied on every current measurement to update the stored information regardless of the successive switching states applied are distinct or not. Finally, experiments are conducted to assess the performance of the new approach using a TMS320F28379D microcontroller. Experimental results demonstrate that the proposed method substantially reduces the stagnation effect under steady-state and dynamic operations.

A simplified model‐free predictive current control (SMFPCC) for an interior permanent magnet synchronous motor (IPMSM) drive system is presented. The SMFPCC requires neither pulse width modulation nor a regulator. Unlike existing model‐based predictive current controllers (MBPCCs), the proposed method is based on stator current detection, meaning that system parameters such as stator resistance, stator inductance, and back‐EMF are not needed. In each sampling period, the stator current is detected only once, rather than twice, thus simplifying the process. Furthermore, to reduce both the switching losses of the inverter and the time consumed, one of four (rather than eight) candidate switching states is selected via the minimisation of a cost function. To compare their performance, both the SMFPCC and the MBPCC are realised on an IPMSM drive system and implemented through a digital signal processor.

A model-free predictive current control for synchronous reluctance motor drives based on triple-voltage-vector with optimized duty ratio modulation is presented in this paper. The proposed scheme introduces an effective and low complexity strategy of selecting candidate voltage vectors to largely reduce computational loadings. First, the basic voltage vectors are organized to apportion six regions, representing six composite switching modes. Each region comprises two active voltage vectors and a zero voltage vector modulated by distinct duty ratios. The scheme starts from the selection of an initial basic voltage vector corresponding to a predefined cost function. The second candidate voltage vector then follows, which is chosen from the region adjacent to the initial one. The third vector is a default zero voltage vector. As a result, voltage vectors outside the selected regions are excluded from the process. Moreover, the adjustable feature makes the optimization of duty ratios adaptive. Finally, the proposed method is experimentally put to tests under various operating conditions utilizing the synchronous reluctance motor drives. Experimental results are presented to demonstrate the effectiveness of the proposal.