To address the long-term operational challenges of space environment monitoring buoys under extreme Arctic conditions, this paper proposes an energy management optimization method based on deep reinforcement learning (DRL). By constructing a buoy system model that integrates renewable energy sources, a primary lithium battery power supply, and a battery energy storage unit, combined with an Arctic environmental model incorporating low-temperature efficiency degradation, a reward function was designed to minimize power supply deficits while ensuring system reliability. The Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm was employed to optimize energy scheduling strategies. Simulation results based on real Arctic data (August 2024-January 2025) demonstrate that integrating wind turbines significantly reduces reliance on primary lithium batteries. Specifically, the required lithium battery capacity was reduced by 87.5% (from 61.44 kWh to 7.685 kWh), and procurement costs were lowered by approximately $68,830 compared to non-rechargeable schemes1. This method significantly enhances the buoy's endurance and scheduling intelligence, offering valid insights into energy management in intelligent polar observation equipment.

A novel buck-boost power converter is proposed to improve the performance of switched reluctance generator (SRG) system in an electric vehicle. In the proposed topology, the energy conversion part is formed by a buck-boost circuit and additional switches, with which, it is flexible to significantly boost the magnetization voltage and demagnetization voltage, thereby the output power range is improved and the power losses are reduced. The basic structure of the proposed converter is presented first and the attached operating modes are analyzed. The control strategy of the SRG system is then made to control the output voltage and the boost capacitor voltage. The simulation results show that compared to the conventional buck-boost converter, the proposed converter enhances the efficiency and reduces the power losses.

Subglacial Lake Qilin (SLQ), in the center of Princess Elizabeth Land (PEL), East Antarctica, is a potential drilling target for detecting extreme-life and studying ice sheet evolution, due to its tectonic origin, stability, thick sediments and isolation by 3600 m thick ice. Prior to drilling, an ideal site is needed to meet scientific goals, requiring characterization of water circulation and subglacial hydrology-related basal melting/refreezing. This study quantifies SLQ's basal melt rate using an optimized 1D steady-state thermodynamic model and multi-source remote sensing/geophysical data. The model improves accuracy via dynamic thermal boundaries and a temperature gradient correction. Results show the lake center has a high annual mean basal melt rate of 2.195 mm a-1, increasing northward. Sensitivity analysis indicates geothermal heat flux has the most significant effect on melt rate, compared to ice thickness and temperature gradient.

This paper introduces a novel control strategy aimed at reducing power losses in switched reluctance motors (SRMs) with a ring winding structure by implementing a speed-scheduling mechanism for circuit switching. Unlike traditional methods that utilize a three-phase inverter with an additional voltage source, this new approach switches the driving circuit from a DC-DC converter to a single diode circuit in the high-speed region, enhancing efficiency. The minimum speed for operating mode switching is determined by analyzing the amplitude and direction of the winding currents. The paper presents comparative evaluations of power losses before and after implementing the new operating mode switching strategy, including a comparison with the pulse current method used in an asymmetric half-bridge (AHB) driven system. Simulation and experimental results demonstrate that the proposed method significantly reduces power losses in ring structure circuits and improves operational efficiency. Compared to the conventional AHB circuit, it lowers torque ripple and reduces manufacturing costs of the hardware circuit. This strategy provides a practical solution for boosting the energy efficiency of SRMs, especially in high-speed applications.

Switched reluctance motor (SRM) with ring winding structures exhibits significant current and torque ripple due to their nonlinear electromagnetic characteristics. To address this issue, this paper proposes an adaptive fractional-order (PID)-D-lambda ((FOPID)-D-lambda) controller with a parameter tuning method that dynamically adjusts control parameters based on DC voltage, nonlinear inductance, and delay time. A Simulink-based simulation of a single-phase inductive circuit verifies the feasibility of the proposed method. The adaptive (FOPID)-D-lambda controller is further applied to an SRM control system, with simulation and experimental results demonstrating its effectiveness. Compared to the traditional hysteresis current controller, the proposed approach significantly reduces current and torque ripple across different operating conditions.

Energy is one of the most critical factors influencing national development, serving as a driving force for societal progress. Compared with conventional power generation, thermoelectric power generation technology that utilizes the thermoelectric potential of materials through temperature differences represents a clean energy generation approach. In the waste heat recovery process of new energy vehicles, non-uniform temperature distribution causes thermoelectric generator (TEG) arrays to exhibit output characteristic curves with multiple local and a single global maximum power points. This study focuses on optimizing thermoelectric generation technology in range-extended electric vehicle waste heat recovery systems. Adopting a combined theoretical and simulation approach, we first establish theoretical models of thermoelectric modules based on fundamental principles and derive performance parameter calculation methods. Experimental investigations reveal output characteristics and analyze the generation mechanism of multi-peak P-V characteristics in centralized TEG systems under nonuniform temperature distribution. A BP-IPSO hybrid algorithm is proposed for maximum power point tracking (MPPT), with simulation verification demonstrating its superior efficiency and accuracy compared with P&O, PSO, and GWO algorithms in achieving MPPT. Additionally, considering the voltage characteristics of thermoelectric modules, a DC/DC converter controlled by STM32F334 is designed, featuring real-time monitoring of TEG operational status through an OLED display. An experimental test platform is established for performance analysis.

This article explores enhancing switched reluctance motor (SRM) performance through integration with inverters, comparing two electric drive structures: the established ring topology and the newly proposed tail topology. These topologies are tailored to delta-connected and star-connected SRMs using a unified control strategy, maintaining essential operating characteristics and accommodating various inverter-related control strategies. The research applies trapezoidal current control and space vector control (SVPWM) methods, providing a detailed derivation and comparison of their parameters. Control schemes for these topologies are also contrasted with the traditional asymmetric H-bridge (AHB) driven pulse current control through simulations and experimental validations. This article also introduces a novel operating principle for the tail structure circuit based on independent neutral current control. Our comprehensive analysis pits this circuit against the ring and AHB circuits. Findings indicate that the conventional AHB circuit exhibits the highest levels of torque pulsation and noise, while the ring topology is optimal for minimizing power losses, and the tail topology effectively mitigates torque ripples. These results offer a theoretical and empirical foundation for choosing optimal topologies for SRMs in various applications.

Ocean tidal observation is the most direct data for studying sea level change, and it is also the basic data for establishing regional elevation datums; it is particularly important to build a tide gauge system in the coastal areas of Antarctica to obtain tidal observation data. The overall and software and hardware design of the tide gauge system of Qinling Station in Antarctica, which is mainly composed of a high-strength thermal insulation cabin, a monitoring module, a data transmission module, an unmanned autonomous operation control module and a photovoltaic and storage complementary power supply module. The unmanned autonomous operation control module, the energy management and working mode switching of the whole system are realized; the photovoltaic and storage complementary power supply module, the photovoltaic power generation and the full utilization of the energy storage battery configuration capacity are realized to ensure the stable operation of the tide measurement system. In December 2023, relying on China’s 40th Antarctic scientific expedition, the tide gauge system was built and installed in the area of Qinling Station in Antarctica, and successfully obtained tidal observation data in the sea area near Qinling Station, verifying the reliability and stability of the system in the harsh polar environment. Based on the tidal observation data transmitted back by the system, the tidal harmony constants of 170 sub-tides in the sea area near Qinling Station were obtained, and the tidal types in the sea area near Qinling Station were judged to be regular all-day tides by the eight main tidal sub-tides, and the tidal forecast was carried out, and the error between the tidal observation data and the tidal forecast was ± 4.6cm, which made up for the gap in tidal observation in the sea area near Qinling Station in Antarctica.

This paper proposes a fault detection algorithm addressing both common open-circuit faults and unique continuous current faults in threephase full-bridge switches for SRM with ring winding structure. By employing a decoupling computation of three-phase winding currents, fault signatures independent of operational state variations are derived. Following fault detection, adaptive thresholds dynamically adjusted with motor operating conditions are implemented for current analysis, enabling precise identification of fault types and locations through advanced signal processing. The developed methodology achieves online automatic diagnosis of conventional open-circuit failures and SRM-specific continuous faults in the power conversion system. Experimental validation under varying speed and load conditions demonstrates the algorithm's rapid response, diagnostic accuracy, and robust performance consistency, confirming its effectiveness for real-time fault monitoring in SRM drive applications.

This paper proposes a scheme for applying space vector control method to a Switched Reluctance Generator (SRG) system with a ring winding structure. This paper focuses on the rectification system of SRG system, primarily analyzing the simulation model of the proposed system and the dual closed-loop control strategy for voltage and current. A solution has been developed to handle the strongly nonlinear and tightly coupled structure of the SRG when adopting the inner current loop control, and the issue of sector abrupt change that occurs when traditional control strategies are applied to the SRG system has been resolved. The performance of the SRG with a ring winding structure under different control strategies is compared in Simulink, verifying the effectiveness of the control strategy. Finally, the authenticity of the proposed control strategy is further validated on an experimental platform.

In this paper, we investigate the target-approaching control problem for a discrete-time first-order vehicle system where the target area is modeled as a static circular region. In the absence of absolute bearing or position information, we propose a simple local controller that relies solely on range measurements to the target obtained at two consecutive sampling instants. Specifically, if the measured distance decreases between two successive samples, the vehicle maintains a constant velocity; otherwise, it rotates its velocity vector by an angle of π/2 in the clockwise direction. This control strategy guarantees convergence to the target region, ensuring that the vehicle’s velocity direction remains unchanged in the best-case scenario and is adjusted at most three times in the worst case. The effectiveness of the proposed method is theoretically established and further validated through outdoor experiments with a mobile vehicle.

In the dense-medium coal preparation process magnetite powder is used, however, due to poor recovery of the magnetite, the consumption of magnetite increases which ultimately reflects in the economics. In order to continuously and efficiently recover the magnetite, a novel three-phase conical magnetic separator based on the principle of an alternating magnetic field generated by a three-phase linear motor, was developed. The distribution law of the magnetic field in the separation chamber was studied, and the magnetic separator’s basic structure and parameters were determined. By varying the feed rate, coil current, coil turns, and particle size, magnetic separation experiments were conducted and compared with traditional magnetic separators. The results confirmed the excellent sorting performance of the conical AC magnetic separator.

A flat bottom current control method is introduced in this article for torque tipple and power loss reduction in a switched reluctance motor (SRM). The proposed driving method operates on the basis of a ring structure driving topology, which drives an SRM by a full-bridge inverter instead of a conventional asymmetric H-bridge, to reduce the cost of the driving system and improve the performance of the SRM. The proposed driving method generates the winding currents with flat bottom waveform, by injecting an additional second and fourth harmonic in the sinusoidal waveform currents, the equations of the flat bottom winding currents are then obtained. Based on the theoretical analysis and calculation, the flat bottom driving method reduces the copper loss, compared with the space vector PWM (SVPWM) driving method and the direct torque control (DTC) method, and generates smoother current commutation than the conventional pulse current driving method. The proposed driving method is validated with a 6/4 SRM through simulation and experimental system, of which the results are compared to that of the SVPWM driving method, conventional pulse current driving method, and DTC method, under different speed and load conditions.

Aiming at the problem of high failure rate of full-bridge inverter with ring-winding structure SRM, an open circuit fault detection method for full-bridge inverter with ring-winding of switched reluctance motor is proposed in this paper. The inductance of three-phase winding is sampled, calculated and analyzed, and the change of the median value of inductance before and after fault is judged. Identify the fault type of power converter and locate the fault bridge arm and switch tube accurately. Finally, the simulation results verify the feasibility of the proposed fault diagnosis method.

A direct torque control (DTC) strategy tailored for switched reluctance motor (SRM) with ring winding structure is proposed. In the proposed topology, stator voltage vectors are reconstructed, and explain the working modes of the SRM. Estimating the reference circulating current by a neural network, that flux magnitude and torque as inputs. With which, ensuring consistent direction of the three-phase winding currents. Circulating current control system and DTC control system of SRM with ring winding structure. Compared the performance of the SRM under various operating conditions in Simulink, validating the effectiveness of the control system.

This paper proposes a voltage-controllable switched reluctance generator (SRG) system with a ring winding structure driven by a fullbridge power converter, which is the first application of a full-bridge power converter to drive the SRG. The proposed topology inherits the advantage of low copper loss of the ring winding that combines AC and DC currents together. It connects the equivalent DC power provided by a DC-DC halfbridge circuit to the ring winding to provide circulating DC and partial excitation energy. This paper provides a detailed description of the proposed system's feedback loops and operating principle. The proposed topology is compared with the uncontrollable Circulating-Current-Excited Switched Reluctance Generator (CCEG). The comparative study is validated through simulation and experimental platform, and the results highlight the output voltage performance of the proposed topology and control method.

To use modular full-bridge power converter to drive switched reluctance motors (SRMs) while maintaining the SRM operation principle, this article proposes a tail structure driving system and a corresponding trapezoidal current control method. The three-phase windings of an SRM are connected in a star configuration, and an additional power switch leg controls the neutral point current, ensuring that the windings are excited within the working area. This allows the SRM to be driven by a full-bridge power converter. The trapezoidal current control method is used to analyze the winding currents and tail current in the SRM, calculating the reference value of the tail current that minimizes the winding copper losses while enabling SRM operation. Simulation tool is employed to validate the proposed driving system and its control method. The results are compared with those of an SRM driven by an asymmetric half-bridge power converter using the pulse current control method. The findings indicate that the proposed driving system structure and control method can effectively drive the SRM, reducing torque and speed ripples.

The power-voltage (P-V) characteristic curve of the centralized thermoelectric generation (TEG) system under nonuniform temperature distribution (NTD) exhibits multiple extreme point characteristics, and the traditional maximum power point tracking (MPPT) algorithm is prone to fall into the local maximum power point (LMPP) and takes a long time to track. This paper designs a BP-IPSO algorithm based on back propagation neural network (BPNN) and improved particle swarm optimization (IPSO) for MPPT. The algorithm firstly utilizes the good nonlinear function fitting ability of BPNN to obtain the fitting curve of the relationship between system control input and power output to establish the TEG array power prediction model. Then, the dynamic learning factor and weight coefficient are introduced into the traditional particle swarm optimization (PSO) algorithm to search the output power prediction model and realize MPPT control. MATLAB/Simulink experiment results show that BP-IPSO algorithm can effectively avoid falling into LMPP, quickly and accurately track the global maximum power point (GMPP), and effectively suppress the oscillation of voltage and power during the tracking process. Especially in the start-up test experiment, compared with perturb and observe (P&O), PSO, and grey wolf optimizer (GWO), the energy generated by BP-IPSO increased by 12.84%, 3.18%, and 4.75%, respectively, which improved the system power generation efficiency.

Since the thermoelectric generation (TEG) sheets will be placed in places with different temperature gradients, it leads to multiple peaks in the duty-power (D-P) characteristic curve of a centralized TEG system under non-uniform temperature distribution (NTD). For this reason, this paper proposes an ENN-ISSA control algorithm, which combines the Elman neural network (ENN) with the sparrow search algorithm (SSA) by adding firefly perturbation. The ENN obtains the centralized TEG system’s single-input and single-output fitting curves, after which the firefly perturbation is introduced into the SSA algorithm. Then the improved SSA algorithm is used to realize the maximum power point tracking (MPPT) control based on the fitted curves. Based on building a centralized TEG system Simulink model and analyzing the output characteristics of the TEG module, temperature constancy experiments, temperature change experiments, and accuracy analysis were conducted. The results of these simulation experiments all show that the algorithm can track the global maximum power point (GMPP) quickly and accurately in the duty-power (D-P) curve with multiple peaks compared with the perturbation observation method and particle swarm algorithm.