Chengming Zhang

In AC motor field-oriented control systems, employing a single DC-bus current sensor with a phase-shifting strategy can effectively reduce system complexity and hardware costs. The vector-symmetry-based phase shift (VSPS) strategy has been shown to offer advantages in extending the linear modulation range and reducing the total harmonic distortion (THD) of phase currents. However, the harmonic suppression mechanism and the effective operating region of this method remain unclear. To fill this theoretical gap, this article develops a time-domain current ripple model for the VSPS method, analyzes the relationship between ripple distribution and vector symmetry, and reveals that VSPS reduces the root-mean-square value of the current ripple through improved PWM waveform symmetry. Furthermore, the boundary conditions under which VSPS can effectively reduce THD over a range of modulation indices are derived. Simulation results validate the correctness of the theoretical model. Experimental results show that the variation trend in the THD difference between VSPS and conventional phase shift compensation with modulation index agrees with the theoretical predictions, although the numerical improvement is relatively small. This work provides a theoretical basis and practical guidance for the engineering application of the VSPS method.

Stator winding reconfiguration technology has attracted increasing attention because it can modify the torque–speed output characteristics of motors online and extend the high-efficiency operating region. However, conventional winding switching methods suffer from several limitations, including long transient duration, typically at the millisecond level; difficulty in precise control; current interruption or asymmetric operation during the transient process; and the resulting torque loss and torque fluctuation. To address these issues, this paper first proposes a seamless winding switching method. The core idea is to complete the switching within the zero-vector interval of a single SVPWM period, thereby eliminating potential surge voltage without requiring a snubber circuit. The proposed method reduces the transient duration to only 5 μs, eliminates current interruption and current asymmetry, and suppresses the associated torque ripple. Furthermore, a deadbeat predictive control strategy is employed. By directly controlling the voltage vector, the proposed strategy enables fast and accurate current tracking within one sampling period after reconfiguration, thereby avoiding current overshoot, oscillation, and the corresponding torque and speed fluctuations. In addition, a voltage feedforward compensation method is proposed to pre-compensate the voltage applied during the PWM period in which the winding reconfiguration is performed, thereby preventing the application of voltage vectors that are inconsistent with the actual motor winding connection. With these three innovative measures, fast, smooth, and robust winding reconfiguration is achieved. The mechanisms and implementation procedures of the proposed strategies are described in detail, and their feasibility and effectiveness are verified through experiments.

This article proposes an optimized real-time commutation algorithm aiming to achieve high-precision force/torque decoupling as much as possible while preventing the coil current amplitude and its slew rate from exceeding predefined limits. First, an electromagnetic force/torque and coil array current commutation model is established for the studied concentric winding moving-coil Maglev planar motor (CWMPM), along with a complete decoupling control method. Next, an improved commutation algorithm based on active set algorithm (ASA) was proposed, and its performance differences with traditional pseudoinverse (PI), fast iterative peak shrinkage algorithm (FIPSA), and redistributed pseudoinverse (RPI) were analyzed through simulation in terms of electromagnetic force/torque decoupling error, current amplitude and its slew rate, iteration computation, and power loss and its uniformity. Finally, real-time closed-loop servo control is implemented on the constructed CWMPM prototype platform using all of the aforementioned current commutation methods. Experimental results demonstrate that the proposed algorithm achieves precise electromagnetic force/torque decoupling while effectively limiting current amplitude and its slew rate, and avoids excessive computational resource consumption, which has significant practical engineering value.

A robust model predictive current control (MPCC) strategy is proposed for motor drive systems, in which a cascaded architecture is innovatively constructed by integrating a noise-resilient augmented observer (NAO) with an adaptive data-driven iterative harmonic identification (ADIHI) mechanism. Firstly, to address dominant aperiodic disturbances in the ultra-local motor model, an enhanced NAO is developed, where the integral of noisy measured current is deliberately introduced as an augmented state variable. This novel augmented state effectively decouples the adverse interaction between high observer gains and high-frequency current measurement noise, enabling inherent low-pass filtering properties of the integrator operator and significantly improving noise immunity without sacrificing the disturbances estimation accuracy. Secondly, based on the NAO-estimated disturbances and ultra-local model, a high-pass-filtered harmonic internal-model component is extracted and further refined through proposed ADIHI scheme. By incorporating an adaptive forgetting factor and an iterative identification mechanism, ADIHI achieves accurate online harmonics extraction. Moreover, an adaptive forgetting factor updating strategy driven by the variation rate of harmonic identification error is designed to enhance robustness against operating condition variations. Finally, overall closed-loop system stability of the proposed MPCC framework is rigorously established using the Nyquist stability criterion. Explicit analytical expressions for control parameters are derived under stability constraints, and systematic stability regions and parameters tuning guidelines are provided. Extensive experimental results on a motor test bench demonstrate the effectiveness and superiority of proposed current control strategy.

The n-coil (n+1)-leg inverter serves as a key hardware solution for independent-coil-based permanent magnet linear synchronous motors (ICPMLSM) due to its simple circuit structure. However, the demand for independent drive of each coil under asymmetric phase quantities makes most conventional modulation strategies inapplicable. Meanwhile, the research on the modulation strategy for output current harmonic suppression based on this inverter is still lacking. This paper proposes a carrier-based modulation strategy for the n-coil (n+1)-leg inverter. By zero-sequence voltage injection to all legs, each coil is decoupled from the auxiliary leg, enabling independent drive. Instead of treating zero-sequence voltage injection as a waveform-shaping technique, it is reformulated as a system-level harmonic minimization problem. A harmonic metric is derived and the optimal zero-sequence voltage is obtained by minimizing the aggregated harmonic content of all energized coils, applicable to arbitrary quantity of energized coils. The DC-link utilization under different quantities of energized coils is analyzed, revealing an inherent trade-off between harmonic suppression and linear modulation range. Furthermore, robustness of the proposed method is also analyzed. Finally, the effectiveness of the proposed method is verified by detailed experiments under different quantities of energized coils.

With the accelerated transition of the global energy system towards low carbonisation, new energy vehicles and large-scale energy storage systems place greater demands on the safety and reliability of lithium-ion batteries. However, throughout their life cycle, these batteries remain susceptible to risks such as manufacturing defects, increased internal resistance, dendrite formation, capacity degradation, and thermal runaway, necessitating high-precision and real-time state monitoring as well as fault diagnosis technologies. At present, detection methods based on electrical, thermal, acoustic, mechanical, and optical signals have been extensively studied and have proven effective for battery state assessment and safety warning. However, the limited engineering applicability of some studies constrains their large-scale deployment. In recent years, magnetic field detection has attracted growing attention as a non-invasive technique. This approach indirectly characterises battery state and abnormal behaviour by monitoring external magnetic field perturbations induced by internal current distribution and variations in material magnetism within the cell. Building on a review of traditional detection methods, this paper systematically elaborates on the physical principles of magnetic field detection technology and its applications in state estimation and fault diagnosis. It summarises its advantages, including non-invasiveness, real-time responsiveness, and high sensitivity to localised defects, and analyses its main challenges, such as interference suppression and engineering integration. Finally, the future development trend of integrating magnetic field detection with multi-signal fusion is outlined. Magnetic field detection is expected to become a key approach for next-generation online battery monitoring and safety warning.

With the growing emphasis on sustainable development in the aviation industry, aircraft electrification has become a pivotal pathway toward achieving green and efficient air transportation. Within this trend, the dual active bridge (DAB) converter has emerged as a key interface technology in energy storage systems, capable of accommodating wide voltage variations while ensuring high power density, system stability, and reliable operation. This paper, based on a neutral-point-clamped flying-capacitor full bridge DAB (NFFB-DAB) converter capable of optimizing switching loss characteristics under light-load conditions, presents a novel modulation strategy to minimize the root-mean-square (RMS) value of the inductor current and reduce conduction losses. The fundamental operating principles of the proposed scheme are analyzed, and its main operating modes and soft-switching constraint expressions are derived. By classifying operating conditions based on different voltage conversion ratio ranges, analytical expressions for control variables are obtained through a global optimization criterion targeting RMS current minimization. A simulation model is established with an input voltage of 1000 V and an output voltage range of 500–750 V. Under identical power transfer conditions, the proposed strategy achieves more than 20% reduction in RMS current compared with the conventional single phase shift (SPS) modulation. The results verify that the proposed approach significantly improves converter efficiency under wide voltage variation scenarios, making it a promising solution for high-power aircraft onboard energy storage applications.

Conventional motor drives are subjected to extensive disturbances and uncertainties across entire frequency spectrum, which significantly deteriorate current control performance within electric propulsion system. To address this issue, this paper proposes a discrete-time composite control strategy that integrates an improved equivalent-input-disturbance (IEID) approach with a dynamic decoupled adaptive damping (DDAD) regulator, aiming to suppress external disturbances and improve the transient current response. Specifically, a proportional-integral augmented observer (PIAO) is introduced into the IEID framework, where the integral of the measured current is treated as an augmented variable. This modification enhances both the estimation accuracy of internal states and the system’s resilience to the current measurement noise. Furthermore, a modified causal filter, constructed building upon an integral-resonant internal model structure, is incorporated into the IEID estimator to achieve simultaneous and effective attenuation of both disturbances and harmonics. Finally, an improved adaptive damping function that is adjustably updated with load current as well as motor speed and the associated dynamic decoupled control law are systematically designed using poles placement techniques, enabling the superior transient dynamics and the flexible damping characteristics. Comparative experimental results validate the practical applicability of the proposed control method.

To enhance the triaxial contour trajectory tracking performance of maglev planar motors (MPMs), this article proposes an analytical contouring error estimation (CEE) method based on third-order Taylor expansion and designs a contouring error controller (CEC) using the fixed-time high-order sliding mode (FxT-HOSM) algorithm with modified feedback. Initially, a state-space model of the MPM incorporating concentrated disturbances in each degree of freedom (DOF) is derived using a static decoupling control algorithm. Subsequently, accounting for the curvature and torsion of 3-D reference trajectories, a third-order Taylor expansion-based CEE algorithm is introduced to enable accurate real-time estimation and compensation. Furthermore, the CEC design based on the FxT-HOSM principle comprises: 1) a nonsingular fixed-time sliding surface (NFxTSM); 2) a fixed-time high-order reaching law; 3) a fixed-time contouring error differentiator; and 4) a fixedtime disturbance observer. This combination ensures highprecision contour tracking while mitigating chattering. Ul-timately, experimental results under various spatial trajectories with varying curvature and torsion confirm that the proposed FxT-HOSM controller achieves excellent performance in both contouring and tracking errors.