The catenary insulator is a critical component of the traction power supply system for high-speed railways. It not only provides electrical control insulation but also plays an essential role in supporting the catenary arm structure. Therefore, the operational safety of the insulator is directly related to the stability of the entire high-speed railway system. However, the detection of insulator defects is often subject to various interferences due to the complex and dynamic railway environment, resulting in low detection accuracy. Moreover, traditional detection methods generally only identify the presence of defects but fail to provide specific semantic descriptions of these defects. This limitation significantly hampers the efficiency of fault diagnosis and maintenance operations. To address these challenges, this paper proposes a defect description method for insulators based on a diffusion model. This method optimizes existing detection technologies in several ways, enabling the model to not only detect insulator defects more accurately but also generate detailed textual descriptions of these defects.
Firstly, we designed a large-kernel spatial selection feature extraction network. Compared to traditional feature extraction networks, this network captures the feature information of insulator defects through larger spatial convolution kernels, significantly enhancing the model's ability to extract insulator defect features. The model can accurately identify potential defects in the insulator, even in complex backgrounds. Secondly, we proposed a detection decoder with a fusion diffusion mechanism based on the diffusion model. This decoder generates noise boxes and uses inverse Bayesian diffusion to restore predictions of the insulator's true bounding box, significantly improving the model's resistance to background interference. This innovation allows the model to more effectively isolate background noise in complex environments, thereby improving the accuracy of defect detection. Finally, to address the limitations of traditional detection models in semantic description, we designed an encoder and decoder based on a cross-attention mechanism to achieve cross-modal mapping between images and text. By using the BLIP model driven by a text filtering mechanism, the model can generate corresponding textual descriptions of the defects based on the detection results. The functionality not only provides maintenance personnel with more intuitive references but also greatly enhances the efficiency of fault handling. Experimental results validate the effectiveness of our method. The proposed insulator defect detection model achieved the mAP_0.5 of 93.04% and the AR and F1-score of up to 83.22% and 82.91%. The BLEU achieved 83.51%, with CIDEr of 1.94, ROUGE-L of 81.59%, METEOR of 51.50%, and SPICE of 37.88%.
The experimental results lead to the following conclusions: (1) Utilizing a large-kernel spatial selection feature extraction network as the image encoder enhances the insulator defect detection network's ability to focus on key features, thereby improving the model's detection accuracy. (2) To address the issue of insulator defect detection being easily disturbed by complex background environments, a detection decoder with a fusion diffusion mechanism was designed. This decoder performs inverse Bayesian diffusion on the noise boxes generated by the decoder, restoring the prediction of the insulator's true bounding box. The model's ability to resist background interference reduces the loss of semantic information related to insulator defects, and enhances the accuracy of the predicted bounding boxes. (3) A cross-modal mapping module was designed to map the relationship between insulator image defect features and text features. The language modeling encoder outputs a textual description of the insulator defects, completing the detection task. Thus, the proposed model not only offers higher detection accuracy but also generates accurate and detailed semantic descriptions of the defects, meeting the actual needs for insulator defect detection and description.

Battery energy storage (BES) is widely used in various applications in the power system as a flexible regulation resource. One of the key applications is peak shaving. BES can charge and discharge to capture the price difference between peak and valley periods in the electricity market. However, due to the inherent operational characteristics of BES, peak shaving behavior results in irreversible aging loss, leading to a reduction in lifespan and available capacity. Establishing an accurate aging model for BES is fundamental for simulating its peak shaving behavior and evaluating investment benefits. The aging characteristics of BES are state-dependent at different stages of its lifespan. However, aging models with fixed parameters fail to consider the variation in aging parameters over time during long-term peak shaving simulations.
A state-dependent aging model for BES is proposed, based on the Arrhenius empirical model, which accounts for the impact of lifespan on aging characteristics. This model can represent the full aging behavior of BES throughout its lifespan. A discrete form of the model is developed to meet the application requirements of power system optimization. The discrete variables are adapted to those of the power system, enabling their integration. Furthermore, the discrete aging model is embedded in a peak shaving optimization model. To address the challenge of solving the highly nonlinear discrete aging model, linearization techniques are employed to facilitate model computation. A dynamic parameter updating mechanism for BES is also designed and incorporated into the discrete aging model, enabling dynamic updates of the aging loss rate and available capacity during long-term peak shaving simulations, thus accurately capturing the full aging process throughout the lifespan.
To validate the effectiveness of the proposed method in investment benefits evaluation, historical locational marginal prices from the Southern Power Pool (SPP) electricity market are used as inputs to simulate the daily peak shaving operations of BES. The results of the daily simulations are used to update BES parameters via the dynamic updating mechanism, and the peak shaving benefits are then calculated. By updating boundary conditions, long-term peak shaving simulations of BES throughout its lifespan are performed, and the cumulative net present value (NPV) of investing in BES for peak shaving is computed. The results show that the proposed method allows for considering aging loss variation over time, reflecting the impact of state-dependent aging characteristics on the peak shaving performance of BES. This method enables accurate evaluation of BES investment benefits.
From the analysis, the following conclusions can be drawn: (1) The state-dependent aging model of BES, based on the Arrhenius empirical model and after discretization and linearization, can accurately capture the aging characteristics throughout the entire lifespan of BES. It also facilitates effective application in power system peak shaving simulations. (2) The state-dependent aging characteristics influence the charge and discharge behavior decisions of BES under electricity price signals. Using the state-dependent aging model allows for precise quantification of the aging costs arising from BES’s peak shaving behavior, enabling accurate evaluation of the investment benefits of BES in peak shaving applications.

In the existing energy storage system, pumped storage units have the advantages of large capacity, flexible operation, rapid start and stop, etc., and play an important role in the peak frequency regulation of the power system, and pumped storage units and wind power, photovoltaic power generation, etc. with the use of the power system can promote the new energy consumption level. However, the complex frequency domain characteristics presented by the multi-timescale control of the power electronic devices are prone to interacting with the power grid and triggering the oscillation phenomenon. Currently, there are relatively few studies on impedance modeling of the variable-speed pumped storage unit with full-size converter and their stability analysis based on impedance criterion. The impedance modeling of the variable-speed pumped storage unit with full-size converter and its analysis are of great significance for the future stability analysis of large-scale pumped storage units connected to the power grid. Therefore, this paper establishes an impedance model of the variable-speed pumped storage unit with full-size converter taking into account the frequency coupling effect, and analyzes the stability of the grid-connected system of the pumped storage unit based on the impedance model.
In the process of establishing the equivalent impedance model of the variable-speed pumped storage unit with full-size converter, the state-space model of the hydraulic turbine and the synchronous motor are firstly established, and the impedance model in the dq coordinate system is obtained on the basis of the model. After that, the impedance models of the machine-side converter and the grid-side converter are established respectively, and finally the equivalent impedance model of the variable-speed pumped storage unit with full-size converter considering the frequency coupling effect is established taking into account the effect of the grid impedance.
Further, the correctness of the impedance model of the variable-speed pumped storage unit with full-size converter was verified using the frequency scanning method. Based on the established impedance model, the grid-connected stability of the pumped storage unit under different grid impedance conditions is investigated by using Nyquist stability criterion. And the effects of key turbine and governor parameters as well as common control loop parameters such as phase-locked loop, DC voltage outer loop and current loop parameters of the full-power converter on the impedance characteristics of the unit as well as on the grid-connected stability are also investigated.
This study draws the following conclusions: (1) A more accurate equivalent impedance model of the variable-speed pumped storage unit with full-size converter that takes into account the frequency coupling effect is established. (2) As the grid impedance increases, i.e., the grid strength becomes weaker, the stability of the unit deteriorates. (3) Under the same grid strength, the bandwidths of the phase-locked loop and the current loop have a greater impact on the system stability, while the bandwidth of the DC voltage loop has a smaller impact on its stability. In addition, the values of the key parameters of the turbine as well as the governor have no significant effect on the impedance characteristics of the unit and very little effect on the stability of the system.

Sulfur hexafluoride (SF₆), which has strong electronegativity and self-recovery, exhibits excellent insulation and arc-extinguishing capabilities and is widely used in the field of power insulation. However, SF₆ is a strong greenhouse effect gas, and its global warming potential is 23 500 times that of CO₂, and its degradation can significantly reduce the pollution and harm of SF₆ to the atmosphere. Then, there are many kinds of toxic and harmful substances in SF₆ degradation products, among which sulfuryl fluoride (SO₂F₂), as the main decomposition product of SF₆, still has the greenhouse effect and huge toxicity and stable nature. The degradation of SO₂F₂ can improve the harmless degradation process of SF₆ and realize the harmless emission of SF₆. At present, many scholars at home and abroad for the treatment of SO₂F₂ waste gas treatment methods mainly include the alkali treatment method, adsorption method, Non-temperature plasma method, etc., in which the Non-temperature plasma method has the advantages of simple structure, ease of control, high efficiency, etc. Still, there is a problem of poor regulation of the product. By filling the catalyst, the degradation rate can be increased and the product selectivity can be improved. In this paper, the degradation of SO₂F₂ by dielectric barrier discharge (DBD) plasma synergistic filling materials was investigated, and the effects of γ-Al₂O₃, ZSM-5, and glass beads on the degradation of SO₂F₂ with different input powers were investigated.
The experimental platform for SO₂F₂ degradation by DBD plasma synergistic filler materials was first constructed. GC-MS was used to quantify SO₂F₂ and its degradation products, and the SO₂F₂ degradation rate and product content were calculated and detected. The experiments found that the addition of filling materials can improve the discharge conditions of the system, enhancing discharge voltage and current. Furthermore, the filling materials can effectively improve the SO₂F₂ degradation rate and energy efficiency (degradation rate: glass beads>γ-Al₂O₃>ZSM-5>no filler), and also change the decomposition path and product selectivity of SO₂F₂ to produce SO₂ that is easy to handle. 2% SO₂F₂ at a flow rate of 150 mL/min and a power of 100 W. As the input power increases, the degradation rate of SO₂F₂ gradually rises, while the energy efficiency shows an overall decreasing trend. With the filling of glass beads, the degradation rate and energy efficiency of SO₂F₂ were 99.5% and 7.69 g/(kW·h), respectively, and the concentration of SO₂ product was 9 278.56×10^-4%, under the same experimental conditions, the degradation rate of SO₂F₂ was lower than that of γ-Al₂O₃ and glass bead filling when ZSM-5 was filled, but the ZSM-5 filling could make SO₂F₂ decompose completely and directionally to SO₂, at which time the content of SO₂ The SO₂F₂ decomposition products are mainly SO₂, SOF₂, SOF₄ and SiF₄, etc. The results of the study show that the SO₂F₂ degradation rate is lower than that of γ-Al₂O₃ and γ-Al₂O₃ filling, but ZSM-5 filling can almost completely directional decomposition of SO₂F₂ to SO₂, at which time the content of SO₂ is 16 908×10^-4%. The results of the study provide reference solutions for the efficient degradation of SO₂F₂ and the harmless treatment of SF₆. The main decomposition products of SO₂F₂ include SOF₂, SO₂, SOF₄, and OF₂. The addition of a catalyst can alter the decomposition pathway of SO₂F₂, facilitating the generation of the more manageable SO₂. The degradation products also contain a significant amount of SiF₄, indicating that etching reactions have occurred.

Renewable energy systems have gained continuous attention for achieving “carbon peak” and “carbon neutrality”, especially DC conversion technologies for renewable energy conversions. Multi-port converter (MPC) has been widely applied in renewable energy systems and electric vehicles due to the characteristics of low cost, high efficiency, and high power density. The non-isolated MPC suffers poor stability due to insufficient electrical isolation between ports. In contrast, isolated converters are often more complex and less flexible. Wireless power transfer (WPT) technology offers convenience, safety, flexibility, and the ability to charge multiple devices, effectively achieving electrical isolation between input and load ports. Thus, combined with WPT and MPC technologies, this paper proposes a three-port DC-DC converter with integrated wireless power transfer capability. The proposed topology facilitates DC power transfer between multiple DC sources with the same or different voltage levels. It enables wireless power transfer between DC sources and load by introducing WPT coupling technologies. The system achieves non-contact hot plug & play between DC loads and the power grid side, which indirectly isolates the impact of the load on the power grid.

The system employs a hybrid power flow control method, with dual half-bridge micro-inverters providing the dual input ports. The load port is wirelessly coupled through an LCL-LCL-type resonant coupling network connected to a full-bridge rectifier. This three-port topology is simple and highly flexible, allowing free power transmission between dual input sources, with the two sources sharing one LCL resonant tank for power transmission to the load without any additional circuit components. System control strategies can be divided into two phases: Phase1: pulse width modulation (PWM) controls the power flow between two DC sources by controlling the average DC offset current in the LCL resonant tank, enabling bidirectional power transmission; Phase 2: phase shift modulation (PSM) control method adjusts the wireless output power for DC load. These two control loops can operate independently or be combined for comprehensive control. The absence of coupling between these methods enhances the stability and effectiveness of each control function. Additionally, the system allows for dual input ports with unbalanced voltage levels.

Firstly, a dual-sided LCL resonant coupling network model is established based on the AC impedance method to analyze its frequency limitations under constant voltage and constant current output characteristics. Secondly, the system topology’s various operating states are analyzed based on switching modes. The overall system model is developed using time-domain analysis, and a small-signal model of the resonant coupling network is established to determine the primary-side PWM control and secondary-side PSM control strategies. Thirdly, a simulation model is built in PSIM to verify the system’s functionality. Matlab/Simulink is used to optimize the parameters of the compensation network. Finally, an experimental platform is set up in a microgrid and energy storage interconnected system to evaluate the system's dynamic characteristics under different voltage levels and load conditions, efficiency variations, steady-state control performance of the closed-loop controller, and dynamic response characteristics.

Experimental results show that under dual inputs of DC 36 V with only wireless output, the system achieves a peak efficiency of 93.6% and load-independent constant current output performance. The system effectively controls the power flow direction and magnitude between the primary-side energy ports, and the designed controller maintains stable load power even under sudden changes in load resistance and voltage levels at the dual half-bridge energy ports. The controller also demonstrates good robustness and dynamic response performance.

Magnetically coupled resonant wireless power transfer (MCR-WPT) technology has received significant attention due to its ability to realize mid-range power transfer. However, the transmission characteristics of MCR-WPT systems are susceptible to variations in coupling coefficients and loads. Parity-time (PT) symmetry has been introduced into the WPT system (PT-WPT) to achieve constant power and high-efficiency transmission over medium distances. This paper provides a comprehensive review of the PT-WPT technology.

First, the paper introduces the PT-WPT system’s basic structure and operating mechanism. It analyzes how the system balances energy gain and loss through the nonlinear saturated negative resistor, allowing it to maintain stable power transmission under varying coupling conditions. Coupled-mode and circuit models are used to construct the PT-WPT system. The two models’ similarities and differences in the energy transmission mechanism, PT symmetry conditions, and system characteristics are described. In addition, PT-WPT can be considered a novel wireless power transfer technology.

Next, the paper discusses the construction methods of nonlinear saturated negative resistors, which can be divided into two categories based on the components used: operational amplifiers and power converters. While operational amplifiers provide a simple and low-cost solution, they are limited in power output. In contrast, power converters, such as half-bridge, full-bridge, and class E inverters, enable higher power output and efficiency but require more complex control strategies. Then, the advantages and disadvantages of these methods are discussed, and directions for improving the design of negative resistors are given.

This paper introduces the different types of coupling mechanisms and the implementation of charging functions. Among the topologies of PT-WPT systems, single-transmitter-single-receiver is the most basic structure; high-order compensation networks and the introduction of relay coils are commonly used to extend the transmission distance of the PT-WPT system. Multi-transmitter/multi-receiver can also improve the system’s reliability and realize stable power transmission in multi-load systems. Furthermore, the charging control strategies are investigated to realize the constant power and constant current/voltage functions independent of the coupling coefficient and load variation, further promoting the practicalization of PT-WPT systems.

Finally, this paper summarizes the existing research on PT-WPT systems and future research issues. PT-WPT technology is expected to find broader applications in the future and promote the development of wireless charging technology.

Wireless charging technology is safer and more convenient than traditional wired charging, and has been widely used in the field of electric vehicles. However, wireless charging systems have the characteristic of separating the ground end and the vehicle end, and there are issues with the selection and measurement of power metering points. The mainstream approach is to set the measurement position of the wireless charging system on the transmitting coil. However, the current and voltage of the transmitting coil are relatively high, so that directly using sensors for measurement can lead to high sensor costs. To address the aforementioned issues, this paper proposed a non-contact measurement method for output power of transmitting coil of wireless charging systems using multi coil collaboration. This method did not require specialized high-power high-frequency current and voltage sensors, and adapted well to practical scenarios such as different power levels, horizontal and vertical ground displacement of cars, and shielding materials, and had high measurement accuracy.

The paper utilized the law of electromagnetic induction to measure the output power of transmitting coil by setting sensing coils. Firstly, it was inferred that there was a relationship between the output power of transmitting coil and the voltage product of the sensing coil. Secondly, the fitting coefficient was used to fit this relationship, and it was derived that when the positions of detection coils and transmission coil were fixed, the fitting coefficient did not shift with the receiving coil. After obtaining the fitting coefficient, only the terminal voltage of the sensing coil needed to be measured. Finally, by constructing the voltage matrix of sensing coils and the standard output power of transmitting coil matrix, the fitting coefficients were obtained, and a coupling matrix model was established between the voltage phasor of each sensing coil and the output power of transmitting coil considering horizontal offset, vertical offset, and power variation.

The experimental results show that under different power levels, the maximum measurement error of the proposed method is within 1.5% when the wireless charging system undergoes offset in both horizontal and vertical ground directions. Under the condition of 2 square sensing coils, the maximum error in power measurement was 47%. When the number of sensing coils increased to 6, the maximum error decreased to within 1.5%. This result indicates that as the number of sensing coils increases, the accuracy will further improve. Meanwhile, research has found that when the transmitting and receiving coil are square, using a square sensing coil results in more ideal accuracy. In addition, with the use of 6 detection coils, 3, 5, and 9 power sampling points were used within the measured power range. The maximum errors in power measurement were 7.8%, 3.6%, and 1.5%, respectively, indicating that the more sampling points are, the more accurate the model is. Finally, further exploration is conducted on the practical scenario of placing multiple sensing coils horizontally, which can avoid the problem of vertical stacking height affecting the short distance power measurement.

This method has been proven to be effective through simulation and experimental analysis. Through comparative analysis of the results, the following conclusions can be drawn: (1) The size and quantity of detection coils are key to ensuring the accuracy of the model. A sufficient number of sensing coils will bring higher model accuracy, but at the same time, it will also increase the number of samples in the model solving process. Therefore, in practice, a reasonable selection can be made based on the measured power error requirements. (2) For coupling devices where both the transmitting and receiving coils are square coils, the measurement accuracy using square sensing coils is more ideal compared to circular sensing coils. (3) A sufficient number of sampling points in model solving can also affect the accuracy of the entire system model. In practice, a reasonable selection can be made based on the measured power error requirements. (4) Horizontal placement of multiple sensing coils can achieve high-precision power measurement, just like vertical stacking. In practical scenarios, placing multiple sensing coils horizontally can avoid the problem of vertical stacking height affecting the short distance measurement of the transmitting and receiving coils.

As the demand for flexibility and efficiency in modern industrial equipment increases, motors often operate under variable speed conditions in real-world industrial applications. This poses challenges for traditional time-domain and frequency-domain fault diagnosis methods. These challenges arise primarily due to the non-linear and non-stationary characteristics of signals under variable speed conditions, which can affect fault feature extraction. Single deep learning models generally require training and test data to follow the same distribution, and domain adaptation or multi-source domain generalization methods are difficult to apply in the absence of target domain and multi-source domain data, limiting their ability to enhance the generalization of single-source domain models. To address these challenges, this study proposes a motor rolling bearing fault transfer diagnosis method that integrates angular domain resampling and feature enhancement.

First, to mitigate the issue of time-frequency characteristic offsets in vibration signals under different rotational speeds, angular domain resampling is employed. This technique processes vibration signals at varying speeds, obtaining angular domain vibration signals to minimize the offsets caused by speed changes. Second, to address the generalization limitations of deep learning models, fault data from constant speed conditions are used as the source domain for training the neural network. Covariance loss is introduced to amplify the feature differences among various classes in the source domain data. This allows the network to focus on more informative features for the classification task, thereby improving its generalization capability. Finally, the angular domain vibration signals under variable speed conditions are input into the trained model for fault classification.

The effectiveness of the proposed method is validated through several experiments. Initially, the time-frequency characteristics of vibration signals from an actual bearing inner ring fault are examined before and after angular domain resampling. Before resampling, the vibration signal intervals under variable speed conditions show significant variability. However, after resampling, the variability in the vibration intervals is significantly reduced. Furthermore, using t-SNE visualization, the study observes that networks without feature enhancement show slow gradient updates and minimal changes in feature distribution. In contrast, networks with feature enhancement exhibit continuous changes in feature distribution, even as the classification loss decreases, with increasing feature distances. The study also conducts four cross-working condition fault diagnosis experiments, comparing the proposed method with other methods. The results demonstrate that the proposed method improves fault identification accuracy by 35.04% compared to methods without angular domain resampling, especially in rolling element fault identification. When compared to methods without feature enhancement, the proposed method improves accuracy by 7.45%. Additionally, in transfer diagnosis tasks under different load conditions, the proposed method demonstrates high accuracy, recall, and F1 scores.

In conclusion, the study finds that: (1) Angular domain resampling effectively reduces time-frequency distribution differences caused by speed variations, proving its applicability and rationality in data preprocessing at different speeds. (2) The feature enhancement strategy, by increasing covariance loss between different class features, amplifies feature differences between various health status signals, enabling the network to capture more distinctive features and significantly improving generalization capability. (3) The proposed method, without requiring target domain data, achieves fault identification accuracy of up to 97.29% under variable speed conditions, demonstrating good robustness under variable load conditions.

AC-DC converters are key equipment to interface the AC grid, DC loads, and renewable generation sources. Efficiency and power density are the main factors in the design and implementation of AC-DC converters. The two-stage power conversion has low system efficiency and high cost. A single-stage AC-DC converter achieves AC-side current regulation, DC-side voltage regulation, and high-frequency galvanic isolation simultaneously through only one stage of high-frequency power conversion, which has the potential advantages of high efficiency and power density. However, the design and implementation of single-stage AC-DC converters are difficult.

This paper presents a resonant single-stage isolated AC-DC converter based on a fixed frequency pulse width modulation strategy. When the switching frequency of the converter is set to the resonant frequency of the series-resonant tank, the impedance of the resonant tank always features zero impedance. Therefore, in steady-state, the total voltage applied on the resonant tank must also be zero, which means the fundamental voltage generated by the primary-side and secondary-side switching bridges must be equal. Following this idea, the converter can operate in both voltage step-down and step-up modes, and the equivalent voltage gain of the converter is continuously adjustable in a wide range by adjusting the pulse width of the high-frequency excitation voltages applied on the resonant tank. Hence, the voltage and current regulation requirements of the single-stage AC-DC converter can be satisfied. Voltage step-down regulation can be achieved by adjusting the primary-side duty ratio D_p, while the voltage step-up regulation can be achieved by adjusting the secondary-side duty ratio D_s.

In order to realize the soft-switching of all switches within a wide voltage range, the soft-switching characteristics of the converter are analyzed in detail. It is found that the magnetizing inductance L_m and quality factor Z_r of the resonant tank must be small enough within the entire AC voltage range, leading to much higher conduction losses. When the instantaneous AC voltage is low, the switching losses of switches are also low. Therefore, it is unnecessary to achieve soft-switching within the entire AC voltage range, and trade-offs between switching loss and conduction loss must be made to design the converter’s parameters. Therefore, an optimized parameters design method is proposed for the resonant single-stage AC-DC converter.

An experimental prototype is built and tested. The experimental results indicate that through the fixed-frequency pulse-width modulation strategy, step-up and step-down power conversions, the AC and DC side voltage and current regulation, and high power factor can be realized. With the proposed parameter optimization design method, soft switching of switches can be achieved in a wide input voltage range. The efficiency of the converter is up to 94.2%. In addition, experimental results indicate that the converter has excellent dynamic and steady-state performance.

In the application of new energy, energy storage, and emerging power loads, the power supply architecture using the DC bus has more advantages than the AC bus, which is the development direction of the future power supply system. Bipolar DC microgrid systems are often used to connect various renewable energy sources and emerging loads due to their higher reliability, flexibility, and efficiency. This paper proposes a synthesis method for non-isolated bipolar output DC-DC converters. A series of bipolar output DC-DC converter topologies are deduced. In order to further improve the performance of bipolar output converter, a novel high-voltage-gain DC-DC converter with a three-winding coupled-inductor is proposed by introducing coupled- inductor and switched-capacitor step-up technology to Boost bipolar output DC-DC converter.

Based on the characteristics of the bipolar output converter, the topology synthesis principle of the proposed bipolar output DC-DC converter is given. The input ends of a positive output DC-DC converter and a negative output DC-DC converter are connected in parallel, and the output ends are in series. This paper gives a series of bipolar output DC-DC converters by classifying and combining traditional DC-DC converters. However, the boost capacity of these converters is limited, and the positive and negative output voltages are only regulated by the duty cycle of the switch. Thus, a bipolar high-voltage-gain DC-DC converter with a three-winding coupled-inductor is proposed. The bipolar output voltages can be adjusted flexibly by the turns ratio of the coupled inductor and the duty ratio. This paper gives the construction principle, operating mode, voltage gain, and stress derivation of the high-voltage-gain bipolar output converter. Compared with the converters in the literature, the proposed converter has apparent advantages in voltage gain and device voltage stress. An experimental prototype with a rated power of 200 W is designed. Experimental results show that the input current ripple is small, and the actual voltage gain of the converter is 380/32=11.875, slightly lower than the calculated (3+n₁+n₂)/(1-D)=12, which is caused by parasitic resistance and control signal delay. The efficiency of the proposed converter is 95.5% at full load and 96.7% at half load.

The following conclusions can be drawn. (1) High voltage gain can be achieved with low input current ripple and small switching device voltage spikes. (2) Symmetrical bipolar output voltage can be achieved, reducing the need for high voltage gain of power supply and load. (3) The converter power is distributed on two DC bus bars, which makes the system more efficient. (4) Part of the diode realizes zero voltage switching turn-off, reduces the diode reverse recovery loss, and improves the efficiency of the proposed bipolar output converter.