In this article, an optimized design for a dual-coupled inductor–capacitor–capacitor-series ( LCC -S)-compensated wireless power transfer (WPT) system with zero-phase angle (ZPA) input condition and load-independent constant current (CC) output is presented. To this end, based on the misalignment characteristics of the reversed-series compensation coil structure, a novel design method for determination of the compensation parameters is proposed. By introducing a stability factor, any restriction on the variation correlation of the mutual inductances between the transmitter and receiver coils, and between the compensation and receiver coils within the range of misalignment tolerant design, is eliminated, thereby increasing the degree of freedom in the coil structure. According to a predetermined misalignment tolerant range, the proposed method can limit the fluctuation of the output current within a certain range and maintain the ZPA input condition. A 200-W/85.3-kHz prototype based on the proposed method is implemented and its performance is experimentally validated. The system can operate in ZPA input and load-independent CC output with a misalignment tolerance factor of 4, as the load varies from 5 to 20 $\Omega$ .

A practical secondary frequency control (SFC) strategy for virtual synchronous generator (VSG) with predicta-ble rotor frequency response is proposed in this letter. The rela-tionship between rotor inertia, damping factor, integral coeffi-cient and the time constant of low-pass filter is revealed, moreo-ver, the complexity of parameter design is reduced obviously. Finally, the proposed concept is verified by Simulation results.

Compared with the traditional passive- and active-damping techniques for mitigating the impedance mismatch between the input impedance of constant power loads (CPLs) and the output impedance of the dc link within dc microgrids, there is a growing interest in leveraging model predictive control (MPC). MPC is proven to have the advantage of addressing the impedance mismatch issue, which leads to system instability and oscillations, owing to its constant handling, multivariable control, predictive capabilities, and optimization-based control. Nevertheless, the generalized MPC faces some technical challenges as it involves intricate enumeration and operations in switching state selection and observer design, thereby increasing computational complexity. Moreover, issues such as variable switching frequency and a lack of protection mechanisms impede its widespread application. To overcome these challenges, this article proposes an MPC technique employing a nonlinear inductor (NI) in the dc cascaded system to enable its faster and more stable transitions. The proposed controller utilizes the dead-beat principle to simplify the predictive process and alleviate the digital implementation burden in the control stage. The incorporation of the NI extends the stability range of the control-to-output transfer characteristics of the power conversion stage with CPL. Subsequently, two Luenberger observers are introduced, capable of handling load uncertainty and adapting to changes in system parameters. The selection criteria and stability analysis of the observer parameters are discussed. The proposed MPC is simple to implement and operates at a fixed switching frequency. Validation through simulation and experimental results confirms the effectiveness of the technique in improving system stability.

Compared with the single-vector-based model predictive control (MPC) technique, the multiple-vector-based MPC technique gains interests in improving the total harmonic distortion (THD) of the stator currents and reducing electromagnetic torque and stator flux ripples for a three-phase surface permanent magnet synchronous motor (SPMSM). However, the complicated enumeration and operation in vector selection and duty cycle calculation increase the computational burden and limit its penetration. Hence, in this article, a simplified virtual-vector-based MPC with a control factor for a three-phase SPMSM is proposed. Without sector identification and enumeration operations, the proposed technique utilizes the control factor to automatically generate a large number of virtual vectors to achieve equivalent performance effectiveness with a multiple-vector-based MPC technique with a lower sampling frequency. Subsequently, regardless of the number of virtual vectors, the candidate virtual vectors are directly identified in an $x-y$ coordinate system to greatly reduce the computational burden. In addition, the duration of the selected optimal virtual vector and the resultant switching sequences are easily obtained and arranged to even the switching losses among the switching devices and further optimize the THD of the stator current. The proposed technique is simplified and flexible. Its control effectiveness is verified by experimental results.

There is a trend to use artificial neural networks (ANNs) as approximation models to implement explicit model-predictive control (EMPC) on hardware. However, the vanilla ANN-based EMPC scheme requires an overredundant ANN structure for achieving better fitting performance but at the expense of increasing the online implementation resources, such as computation time, memory cost, etc. This article proposes a light implementation scheme for ANN-based EMPC (LISABE). It shows much superior control performance than the vanilla scheme with reduced online computation time and memory resources under a combination of an optimized data generation process and an improved ANN structure. On the one hand, attention-based tree-search sampling is proposed to help enhance the ANN's fitting performance by optimizing the distribution of the offline laws of EMPC. On the other hand, by taking advantage of the bilaterally bounded property of the offline law distribution in power converter applications, a dual-rectified-linear-unit ANN is proposed as the approximation model for EMPC. It significantly improves the fitting performance with a reduced ANN structure. Simulations and experiments verify that the LISABE addresses the challenge of performing online computation of EMPC with a long prediction horizon using low-cost microprogrammed control units and can further save around 84% of online computation and memory for the current-mode boost converter and around 50% of online computation and memory for the voltage-mode buck converter compared with the vanilla ANN-based EMPC.

The H-bridge (HB) converters are essential components in various power typologies, offering dual energy flow, increasing power density, and enhancing extensibility. For the HB converters, the dead zone plays a crucial role in avoiding power semiconductors against shoot-through phenomenon in the phase leg of an HB converter. However, it also negatively affects the quality of the output ac currents, impacting system performance. This letter introduces a simplified digital logic-based scheme that effectively compensates for the dead zone in HB converters. Initially, the scheme examines the repercussions of dead zones in HB converter. Subsequently, it adjusts pulsewidth modulation signal waveforms by either delaying the leading edge or the lagging edge for the dead-zone compensation, irrespective of the control and modulation methods employed. Furthermore, extensibility of the proposed scheme to other power converters, such as a neutral-point-clamped converter is discussed. The effectiveness of the proposed scheme is validated by experimental results.