arXiv subjects

Zhenbin Zhang

Publications and source records attributed to Zhenbin Zhang.

6 recordsLinked to original sources

arXiv2026

Grid-Constrained State-Adaptive Particle Swarm Optimization: A Discrete and Efficient Heuristic Solver for Precise Harmonic Programming

Harmonic programmed pulse width modulation (HPPWM), offering flexible harmonic regulation, is a promising solution for high-power energy conversion systems. However, most existing methods solve HPPWM in a continuous space while ignoring the finite timer resolution of practical digital controllers. This leads to a potential optimality deviation during deployment. Motivated by this, this paper proposes a Grid-Constrained State-Adaptive Particle Swarm Optimization (GCSA-PSO) strategy. By matching the solution space with practical timer constraints, GCSA-PSO directly searches for implementable pulse sequences in the discrete solution space, thereby improving deployment consistency while reducing the search burden. Moreover, a state-adaptive evaluation strategy is developed to assign different cost evaluations according to particle states, avoiding unnecessary evaluations and improving computational efficiency. Experimental data confirm that, compared with the classical method, the proposed method reduces the computational time while achieving higher control accuracy under practical digital-controller deployment.

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arXiv2026

A Simple and Extremely Efficient Predictive Control for Power Converters

Classical finite control set based model predictive control (FCS-MPC) reduces the optimal problems to an enumerated searching algorithm, which is very simple and effective to control power converters. However, it requires a large amount of enumeration operations, increasing its computational load and hardware costs. In this work, we propose a new and simple predictive control technique with extreme efficiency. The proposal directly selects the optimal vector via determined visual maps, abstained solely requiring a rearrangement of the cost function and a simple fitting law, without any enumeration. It has been validated under a lab-constructed power converter and a set of commercialized low-cost digital controllers. Experimental data confirm that the proposal achieves the same control performance as classical MPC, with significant computational burden reduction (up to 88\% for one-step prediction of two-level converters)

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arXiv2025

Class E/EF Inductive Power Transfer to Achieve Stable Output under Variable Low Coupling

This paper develops an inductive power transfer(IPT)system with stable output power based on a Class E/EF inverter. Load-independent design of Class E/EF inverter has recently attracted widespread interest. However, applying this design to IPT systems has proven challenging when the coupling coefficient is weak. To solve this issue, this paper uses an expanded impedance model and substitutes the secondary side's perfect resonance with a detuned design. Therefore, the system can maintain stable output even under a low coupling coefficient. A 400 kHz experimental prototype validates these findings. The experimental results indicate that the output power fluctuation remains within 15% as the coupling coefficient varies from 0.04 to 0.07. The peak power efficiency achieving 91%

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arXiv2025

Conveniently Identify Coils in Inductive Power Transfer System Using Machine Learning

High-frequency inductive power transfer (IPT) has garnered significant attention in recent years due to its long transmission distance and high efficiency. The inductance values L and quality factors Q of the transmitting and receiving coils greatly influence the system's operation. Traditional methods involved impedance analyzers or network analyzers for measurement, which required bulky and costly equipment. Moreover, disassembling it for re-measurement is impractical once the product is packaged. Alternatively, simulation software such as HYSS can serve for the identification. Nevertheless, in the case of very high frequencies, the simulation process consumes a significant amount of time due to the skin and proximity effects. More importantly, obtaining parameters through simulation software becomes impractical when the coil design is more complex. This paper firstly employs a machine learning approach for the identification task. We simply input images of the coils and operating frequency into a well-trained model. This method enables rapid identification of the coil's L and Q values anytime and anywhere, without the need for expensive machinery or coil disassembly.

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arXiv2024

An Effective Current Limiting Strategy to Enhance Transient Stability of Virtual Synchronous Generator

VSG control has emerged as a crucial technology for integrating renewable energy sources. However, renewable energy have limited tolerance to overcurrent, necessitating the implementation of current limiting (CL)strategies to mitigate the overcurrent. The introduction of different CL strategies can have varying impacts on the system. While previous studies have discussed the effects of different CL strategies on the system, but they lack intuitive and explicit explanations. Meanwhile, previous CL strategy have failed to effectively ensure the stability of the system. In this paper, the Equal Proportional Area Criterion (EPAC) method is employed to intuitively explain how different CL strategies affect transient stability. Based on this, an effective current limiting strategy is proposed. Simulations are conducted in MATLAB/Simulink to validate the proposed strategy. The simulation results demonstrate that, the proposed effective CL strategy exhibits superior stability.

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arXiv2020

A Sphere Decoding Algorithm for Multistep Sequential Model Predictive Control

This paper investigates the combination of two model predictive control concepts, sequential model predictive control and long-horizon model predictive control for power electronics. To achieve sequential model predictive control, the optimization problem is split into two subproblems: The first one summarizes all control goals which linearly depend on the system inputs. Sequential model predictive control generally requires to obtain more than one solution for the first subproblem. Due to the mixed-integer nature of finite control set model predictive control power electronics a special sphere decoder is therefore proposed within the paper. The second subproblem consists of all those control goals which depend nonlinearly on the system inputs and is solved by an exhaustive search. The effectiveness of the proposed method is validated via numerical simulations at different scenarios on a three-level neutral point clamped permanent magnet synchronous generator wind turbine system and compared to otherlong-horizon model predictive control methods

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