This article proposes a new duty-ratio regulation-based strategy to improve the torque performance for the direct torque control (DTC) of three-phase permanent magnet synchronous motors (PMSMs). The conventional DTC schemes utilize two hysteresis regulators that are hard to be tuned to satisfy proper torque performance for wide speed ranges because of the contrary change in the positive and the negative torque deviations of the converter's voltage vectors with the rotational speed variations. In contrast, the proposed method uses a duty-ratio regulator that considers the operating speed impact on the torque deviation of the active voltage vectors and avoids triggering those of them that produce high torque deviations, therefore reducing the torque ripple of the DTC system. Moreover, it proposes a virtual reference generator to mitigate the steady-state torque error. The proposed method provides enhanced torque control performance, meanwhile maintaining the main advantages of the conventional DTC techniques, including simple structure, fast transient response, and good robustness. The feasibility and effectiveness of the proposed strategy are verified through a detailed comparative assessment with the conventional DTC scheme and two existing duty regulation-based methods using experimental results obtained from a 0.75-kW PMSM drive system.

This paper investigates an adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) technique applied to a reconfigurable photovoltaic (PV)-based battery charger. The proposed method uses training data collected from a dynamic model of the PV module to train the ANFIS to locate the maximum power point (MPP) under different environmental conditions. Based on the estimated MPP, the proposed method can select the optimal configuration of a PV array and the corresponding global MPP under the non-uniform distribution of the temperature and irradiance. In this way, the proposed method can guarantee the highest possible power harvesting to charge a lithium-ion battery under either partial shading conditions or characteristics mismatch, achieving a high system efficiency. The proposed method is compared with the conventional MPPT scheme to verify its feasibility and effectiveness. The verification results show that the proposed method provides higher accuracy, faster response and better tracking efficiency.

This paper proposes a modulated model predictive torque and flux control (M2PTFC) method with low complexity for a two-level voltage source inverter (2L-VSI) fed permanent magnet synchronous motor (PMSM). The proposed strategy aims to reduce the computation burden and simplify the control implementation of the conventional M2PTFC scheme by (1) reducing the number of candidate voltage vectors at every control sample to the minimum (i.e., only two candidates), and (2) eliminating the weighting factor of the cost function and its corresponding tuning procedures. For these purposes, the proposed method devotes different control objectives to the duty-modulation and the cost-function-evaluation processes while executing them sequentially. First, aiming at the torque-ripple reduction, a duty modulation strategy is proposed based on analysis of the torque deviations produced by different voltage vectors, which ensures proper selection of the two candidates and restricts the active voltage vectors that cause high deviations. Then, these candidates are evaluated based on a cost function assigned to achieve the stator-flux control objective. The effectiveness of the proposed control scheme is verified through a comparative assessment with the conventional M2PTFC and two existing simplified methods by means of simulation and experimental results.

Photovoltaic (PV) energy is one of the most important renewable energies because it is clean, requires very little maintenance. However, the relatively high costs and low conversion efficiency are still the major challenge to a larger and faster spread of PV systems. Therefore, the maximum power point tracker (MPPT) is essential in a PV system for maximizing the conversion efficiency of the solar array. Because of the nonlinear behavior of the PV systems, various techniques of the MPPT are employed in order to continuously operate the solar array at their MPP, despite the unavoidable changes in solar irradiance and temperature. This paper presents an assessment of five widely used MPPT techniques. These techniques are simulated in Matlab/Simulink environment in order to provide a comparison in terms of sensors required, ease of implementation, efficiency, the dynamic response of the PV system to variations in temperature and irradiance, and their appropriateness for the different applications of PV system. This can be used as a reference for future research related to the PV power generation.

In this paper, a flexible switching table (FST) for direct torque control (DTC) of permanent magnet synchronous motors (PMSMs) was proposed to enhance the steady-state and dynamic performances of the drive system. First, the influence of each converter output voltage vectors on the torque and stator flux deviation rates was analyzed to assess the voltage selection strategies of the conventional STs and their impact on the DTC system’s performance. Then, a new flexible ST was proposed which uses a simple algorithm to adaptively select the appropriate voltage vector for two of its states according to the system operating condition. The effectiveness and feasibility of the proposed FST were verified through a comparative evaluation with the conventional STs using experimental results obtained from a 0.75 kW PMSM drive system.