This paper proposes a novel transient high-power electrical drive system (THPEDS) based on a dual-rotor induction motor (DRIM) to address the limitations of conventional flywheel energy storage systems, which require separate components for energy storage and conversion, leading to large system size and mass. The DRIM integrates energy storage and mechanical drive functions into a single device, utilizing an outer rotor for inertial energy storage and an inner rotor for direct load driving, thereby eliminating additional electromechanical conversion stages. Steady-state performance, analyzed via 2D finite element method (FEM), reveals magnetic field distribution and torque characteristics under varying excitation currents and slip speeds. A dynamic torque control strategy, derived from fitted torque curves, is implemented and validated through field-circuit co-simulation, demonstrating effective torque regulation and stable operation. The proposed system offers a compact, efficient solution for applications such as UAV-assisted takeoff, enhancing power density and simplifying system structure.

Long-stator linear induction motor (LSLIM) with unequal-length stator segment (ULSS) can significantly reduce system power supply capacity and construction costs, with crucial application value in fields like aerospace high-speed equipment testing. However, the ULSS configuration exacerbates the nonlinear and fast time-varying characteristics of motor parameters, causing severe current control instability during operation, which bottlenecks the performance enhancement of advanced electromagnetic launch equipment. To address this, a sixth-order nonlinear state-space model incorporating the coverage ratio factor an and stator length coefficient bn is established. Research shows that while the traditional Jacobian-based local linearization criterion indicates a stable equilibrium point, time-domain simulations reveal intense instability at the full coupling point. To uncover the mechanism, bifurcation theory is introduced; via bifurcation diagrams and maximum Lyapunov exponent (MLE), the system’s chaotic evolution under full coupling is confirmed. A stability boundary heatmap is then constructed via two-dimensional parameter scanning to define critical control parameters. Simulink simulations demonstrate that selecting parameters within this boundary effectively suppresses current oscillations. This validates the instability mechanism interpretation and the effectiveness of the defined parameters, providing theoretical guidance for controller parameter selection.

The long primary double-sided linear induction motor (LP-DSLIM) is widely applied in high-speed electromagnetic propulsion systems. However, the coupling between the teeth slot effect, longitudinal static end effect, and dynamic end effect significantly degrades its performance. The coupling mechanism of the teeth slot effect and longitudinal end effects is investigated and a fast analytical model of the coupled magnetic field is established. The mathematical expressions for air-gap magnetic fields, secondary eddy current and electromagnetic thrust are derived. A transient finite element method (FEM) model is also developed and compared with that of the proposed analytical model. Finally, the longitudinal static end effect is suppressed by adding a shielding layer in the gap between the segments. All these demonstrate that the coupling effects notably exacerbate the inhomogeneity of the air-gap magnetic field and directly affect thrust stability, and the effectiveness of the segmented gap with a shielding layer is verified using FEM. The results provide theoretical support for optimizing LP-DSLIM design.

This paper addresses the challenge encountered by segmented-power-supply supersonic linear induction motors (LIMs, >340m/s) under supply-section commutation and severe current-impact conditions, where key parameters (e.g., mutual inductance and resistance) undergo nonlinear and abrupt variations within an extremely short time and are difficult to observe in real time. Conventional model-based observers typically exhibit slow convergence during fast transients, whereas data-driven machine-learning approaches suffer from high-dimensional data, strong feature coupling among parameters, and limited interpretability. To overcome these issues, a physics-guided feature extraction method is proposed based on parameter-sensitivity analysis of proportional-integral (PI) controller residuals. First, a dynamic mathematical model of a segmented-supply LIM is established using a virtual-mover formulation, and a steady-state voltage feedforward equation is derived. Second, under a small-parameter-error assumption, an analytical mapping between parameter perturbations and the residual of the current-loop PI controller output is formulated, based on which a sensitivity matrix is constructed and its coupling mechanism is analyzed. Furthermore, a feature orthogonalization transformation is proposed to generate a reactive residual and an active compensation residual, thereby achieving bidirectional decoupling between the identification results of stator resistance and mutual inductance. Finally, an online parameter identification scheme is developed using a damped Newton iterative law based on the inverse sensitivity model, and learning-rate scheduling and low-pass filtering are introduced to suppress measurement noise and higher-order nonlinear errors. Full-system MATLAB/Simulink simulations demonstrate that, under high-speed mover entry/exit and abrupt parameter-change conditions, the proposed method can separate aliased residual signals into clear trajectories of parameter-mismatch features and accurately track the trend of actual parameter variations. Without requiring additional sensors or constructing extra observer models, the method provides highly interpretable feature inputs for subsequent low-cost, small-sample machine-learning-based parameter identification, and thus has significant engineering value.

The segmented long-primary double-sided linear induction machine (SLPDSLIM) exhibits time-varying parameter characteristics, rendering the traditional methods ineffective in achieving stable primary current regulation. To address this issue, this article first establishes a unit machine primary current loop model, followed by an analysis of the constant-coefficient proportional-integral control (CCPIC) method's limitations under the influence of time-varying parameters. Subsequently, a novel variable-coefficient complex vector control method with active damping (VCCVC-AD) is proposed. This method not only achieves strong robust decoupling control of the primary current but also confines the system's dominant pole within the left half of the complex plane, significantly enhancing the current control stability. Finally, comprehensive experimental results fully demonstrate the effectiveness and superiority of the proposed method.

Wireless power transfer (WPT) technology can be applied to autonomous underwater vehicles (AUVs) as a promising alternative. Conventional planar coils often fail to perfectly adapt to the cylindrical hull structure of AUVs, usually requiring additional mounting structures that increase the vehicle's size and weight. This paper analyzes flexible coupling coils for application in underwater inductive power transfer (U-IPT) system, which is compatible with the hull structure without other modifications. Under the flexible configuration, the inductance characteristics and the strength and distribution of the magnetic field of the coupling coils will change. Two configurations of flexible coupling coils suitable for U-IPT system are proposed. One is flat transmitting platform-curved receiver, another is curved transmitting platform-curved receiver. The characteristics of coil self-inductance and coupling coefficient under bending conditions are analyzed, and design, optimization, and comparison of the two coil configurations are conducted.

To address the issue that the mover position of the long primary segmented linear induction machines (SLPLIMs) cannot be directly estimated using flux linkages and back electromotive forces (EMFs) due to the slip ratio. A novel sensorless control strategy is proposed for SLPLIMs, utilizing the amplitude variation of coupled mover flux linkages. The method is built upon a proposed fused flux-amplitude space vector (FFASV), which is synthesized from multiple estimated flux linkages. The phase of this vector directly indicates the mover position. The system architecture comprises flux observers based on the model reference adaptive system (MRAS), the FFASV observer, and a dedicated position observer, whose design is derived from phase-locked loop (PLL) principles. To address the issue of inconsistent parameters among different stator segments in the SLPLIM, flux observers based on MRAS identify motor parameters before the mover enters the powered stator segment. To address the complexity of the inductance matrix caused by the asymmetric distribution of the motor windings, the form of the inductance matrix is simplified by optimizing the selection method of the alpha beta-axis in the Clarke transformation, thereby reducing the number of parameters to be identified. Only the alpha-axis or beta-axis- flux linkages are used to construct the orthogonal coupled flux linkage independently, thereby decreasing the number of signals that require processing and lowering the overall computational burden. The effectiveness of the proposed sensorless control strategy is verified on an experimental platform with a SLPLIM powered by three inverters.

To address the problems that ultra-high-speed segmented power-supply long-stator linear induction motors are prone to switch open-circuit faults during power-supply transitions, leading to phase current distortion, instantaneous thrust fluctuations, and possible protection-triggered shutdowns, a spatiotemporal precision fault ride-through method based on the principle of "space as the primary factor and time as the secondary factor" is proposed. This method first establishes a spatial coupling relationship using the real-time position of the mover and the coverage ratio of stator segments, enabling rapid localization of the faulty segment and faulty switch, and implements selective temporary blocking of the faulty segment. Subsequently, the power-supply switching instant is taken as a key temporal node for secondary fault discrimination. Specifically, when the motor operates to the power-supply switching moment of a stator segment, a secondary state assessment of the faulty segment is triggered. If the fault persists and the accumulated number of occurrences reaches a preset threshold, it is identified as a permanent fault and permanent blocking is executed. If the fault is cleared, power supply is restored. Verification on a Matlab/Simulink simulation platform demonstrates that, compared with traditional fixed-delay reclosing strategies, the proposed method significantly shortens the outage duration of faulty segments, reduces the impact on the system’s continuous traction capability, and effectively avoids blind reclosing on permanent faults. As a result, the method achieves rapid fault localization, precise blocking and unblocking, and accurate fault-type identification for open-circuit faults, thereby enhancing the continuous operation capability, stability, and reliability of ultra-high-speed linear motor drive systems under fault disturbances.

Active noise control (ANC) is an effective method for suppressing unwanted noise. While most commercial ANC products rely on pre-trained fixed-filters for noise attenuation due to their high computational efficiency and stability, the noise reduction (NR) performance is prone to variations in the direction of incident noise and noise spectral content mismatch. In this paper, a selective fixed-filter ANC algorithm based on parallel structure and Bayesian tracking (SFANC-PSBT) is proposed to mitigate these problems. Bayesian tracking is applied to deal with the noise source direction uncertainties and to select the grid-based fixed filter with the largest posterior probability. Moreover, the parallel broadband fixed-filter adaptive gain (PBFAG) approach is proposed to improve NR performance for off-grid directions, and the parallel narrowband fixed-filter adaptive gain (PNFAG) approach is proposed to further attenuate noise and to mitigate the noise spectral content mismatch issue. Besides, stochastic analysis of the proposed methods is provided. Experimental results demonstrate that the proposed methods achieve better NR performance, faster convergence rate and higher robustness against noise variations under changing primary path conditions. The PNFAG and PBFAG methods yield NR improvements of 23.71% and 18.67%, respectively, over the conventional fixed-filter method. Some before/after ANC sound samples under different noise conditions can be found in https://zhchengcq.github.io/ANCdemo/.

Teeth slot effect (TSE) and longitudinal end effect (LEE) are the key factors affecting the characteristics of linear induction motors. This paper takes the long primary double-sided linear induction motor as an example. The TSE and LEE are considered on the coupling effect of the motor characteristics. Firstly, the main coupling relationship between TSE and LEE is analyzed. Second, a method is proposed to analyze the coupled magnetic field under the two effects. Then, the analytical expressions of the air-gap magnetic field, the secondary eddy current density and the electromagnetic thrust under the coupling influence are derived. Finally, the corresponding ANSYS simulation models are established to verify the accuracy of the proposed method.

Since the transverse edge-end effect has impacts on the performance of the long primary bilateral linear induction motor (LP-DSLIM), especially the electromagnetic thrust, a 3D FE model of LP-DSLIM is established to simulate the performance of LP-DSLIM. In order to weaken the transverse edge-end effect, a new secondary structure is proposed, which normalizes the eddy current path by increasing the resistance of the primary and secondary coupling regions. In addition, this secondary structure can also be filled with magnetic permeable materials to reduce the electromagnetic air gap of the motor, which can greatly increase the electromagnetic thrust. In this paper, the superiority of the new secondary structure is verified by comparing and analyzing the LP-DSLIM with the traditional secondary structure and the new secondary structure.

The existing control methods for segmented parallel-connected long primary double-sided linear induction machine (LPDSLIM) driven by a single inverter have the problems of low parameter robustness, large thrust fluctuation and inaccurate flux estimation. In response to these drawbacks, a primary total flux orientation control method is proposed in this article. Firstly, the mathematical model of LPDSLIM is analyzed, and a dual three-order generalized integrator (DTOGI) with frequency locking loop (FLL) is designed to improve the estimation accuracy of the primary flux. Next, the thrust and flux control system is constructed, in which the primary total flux and total thrust are respectively controlled by the d-axis and q-axis components of the primary total current. Then, a voltage compensation method is proposed to realize the decoupling control of the d-axis and q-axis components of the primary total current. Finally, the simulation results verify the effectiveness and superiority of the proposed method.

The performance of personal sound systems is often degraded by inaccurate acoustic measurements. To achieve robust control while balancing acoustic contrast and signal distortion, this work proposes a robust hybrid optimization method that exploits both acoustic contrast control and pressure matching (ACC-PM). The method addresses perturbations caused by uncertainties in the acoustic transfer functions such as temperature changes, head movement, etc, modeled as norm-bounded uncertainties. Although the resulting worst-case optimization is inherently non-convex, it is reformulated as a second-order cone programming problem, which can be efficiently solved. Numerical simulations demonstrate the effectiveness of the proposed robust ACC-PM algorithm, showing an improvement over 18% in terms of AC compared to vanilla ACC-PM.

This paper proposes a sensorless velocity observation method for ultra-high-velocity linear induction motors (LIMs) based on multi-voltage data fusion. The study addresses the critical challenges in velocity measurement encountered during high-velocity LIM operation, where rapid mechanical stress, environmental factors, and transonic unsteady aerodynamic characteristics induce severe disturbances in mover position/velocity measurements and electromagnetic mechanisms. These disturbances may further damage costly velocity measurement equipment. To overcome these limitations, a mathematical model correlating multi-voltage data with mover velocity is established, and a data fusion algorithm is introduced to enhance the precision of velocity observation. Compared to conventional single-voltage-based velocity observation methods, the proposed multi-voltage fusion approach significantly reduces the number of required parameters and computational complexity while achieving higher accuracy. Simulation results validate that the average error between the multi-voltage fusion-based velocity observation method and the actual velocity is less than 5‰. Experimental tests on a prototype further demonstrate that the maximum average error of the synchronous voltage-based velocity observation method remains below 9‰, confirming its practical applicability in engineering scenarios.

Linear induction motors (LIMs) with segmented stators are commonly used in long-stroke electromagnetic propulsion platforms, Due to the thermal effect of high current, the resistance of the motor’s mover deviates from the measured value, making it difficult to stably output the maximum thrust. Therefore, accurate online identification of the mover resistance is crucial for maximizing the thrust output of LIM. The motor parameters estimated by traditional adaptive identification methods fluctuate significantly between segments. This paper proposes an adaptive parameter identification method based on stator voltage and current reconstruction. In this method, the coupled parts of each stator segment covered by the mover are equivalently summed up. A mathematical model of a virtual LIM is then reconstructed, which is immune to the effects of stator segmentation and switch switching. Subsequently, a voltage-model-based flux observer and a current-model-based flux observer are established to observe the mover’s magnetic flux, enabling online identification of the mover resistance. Simulation results show that the proposed identification method can quickly and accurately identify the mover resistance, ensuring that the motor operates at the maximum thrust point.

When the segmented long primary linear induction motor (LPLIM) is powered by segments series-fed method, the motor parameters do not vary with the rotor movement even during the mover crossing the two stator segments. However, the segments series-fed method may results in the switch layout complexities, especially during the switching process. To address this, the transient switching process of the dual three-phase linear induction motor is analyzed and a corresponding phase-domain model is developed by introducing a coupling matrix and current constraint matrix. The model and control effectiveness are validated through simulation results based on a test platform of LP-DSLIM in our Lab.

The power supply system for medium-speed maglev train using power rail and collector shoes has the defects of causing friction, heat generation, noise, vibration and so on. Making use of inductive Wireless Power Transfer (WPT) system can overcome the above drawbacks and can realize the complete separation of the vehicle from the ground. In the WPT system the high frequency current in the ground coil generates magnetic field and induces voltages in the receiving coils on the vehicle. This paper introduces the basic structure of the 60kW WPT for medium-speed maglev train. The efficiency model of the WPT system is setup and the efficiency curves are depicted. The WPT system is installed on a medium-speed maglev vehicle. The system efficiencies for different output power under the constant primary current control are measured, and the correctness of the system efficiency model is verified. The system efficiency is 87.7% for the rated 60kW output power, but it is reduced under light load. In the future the adaptive control of primary current may be employed to increase the light-load efficiency.

The phase inductance of segmented linear motor is unbalanced, and the dynamic disturbance cannot be ignored for back electromotive force (EMF) when the mover enters and exits the stator segment. At the same time, the current and thrust control become more difficult because of the mismatch of the model parameters. To solve the above problems, this paper proposes a current control strategy based on model-free predictive current control (MFPCC). A hyperlocal model of dual three-phase permanent magnet linear synchronous motor (PMLSM) with stator segment is constructed. A predictive current controller is designed based on the deadbeat principle, and a disturbance observer is designed to compensate the effects of unbalance inductance, dynamic disturbance of back EMF and parameter mismatch. Finally, it is verified by experiments that MFPCC can effectively weaken the influence of unbalanced inductance, and suppress the disturbance of back EMF and parameter mismatch. The proposed method improves the robustness and current tracking performance, and thrust fluctuation is reduced.

In order to study the characteristics of the long stator section on high-speed electromagnetic suspension (EMS) Maglev trains, a lumped-parameter model was derived based on the equivalent circuit theory in this paper for calculating the performances of the iron-core synchronous linear motor within one stator section. The German Transrapid 08 type Maglev train was selected as a typical example for studying, the section parameters in the equivalent model were obtained by the analytical method and the electromotive force, as well as propulsion force were solved by a 3-D finite element method. Via the proposed lumped-parameter model, the characteristics of driven current, terminal voltage and acceleration distance, etc. of the stator section could be solved, also the potential of applying the current configuration to a higher train speed was discussed. Finally, taking the key parameters of stator sections and the characteristics of acceleration/ power factor as dominant variables and design targets, respectively. Based on the derived model, Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) was employed for solving its multi-objective optimization problem, and some typical Pareto solutions were chosen for investigating the optimal targets under different configurations.

Linear motors with stator segmented powered are widely used in high-speed electromagnetic propulsion applications. And fast and smooth segment switching is required to achive higer propulsion speed. In this paper, the dynamic characteristics of the current during the segment switching process are analyzed. And the upper and lower limits of the electrical angle required to complete the segment switching at any speed are obtained by calculation. Then, a novel segment switching method is proposed, which achieves fast switching without overcurrent at any speed. Simulation results verify the effectiveness of the proposed segment switching method.