The thermal characteristic modeling of silicon carbide (SiC) power devices is a key aspect in their design and development. The structure function method is crucial for characterizing the devices’ thermal characteristics, focusing on acquiring the time-constant spectrum of input data via deconvolution algorithms. However, the environmental noise inevitably affects actual tests, thereby demanding more sophisticated deconvolution algorithms for the structure function. Therefore, a deconvolution structure function algorithm based on improved Wiener filtering is proposed, effectively addressing the noise problem in the measurement data during the transient thermal analysis. First, a structure function model based on Wiener filtering deconvolution is put forward, and the algorithm’s effectiveness is validated through analyzing the TDIM-Master benchmark problem. Second, different levels of noise are added to the benchmark problem to explore the signal quality and peak thermal resistance of the time-constant spectrum across various noise conditions. The accuracy and superiority of the improved method when dealing with noises are verified through a comparison with the conventional algorithm. Finally, the transient thermal resistance of two different types of SiC power devices were measured under conditions with or without thermal silicone grease, and the structure function analysis was also performed, thus verifying the stability and applicability of the proposed algorithm under real measurement environment.

The calculation of high-frequency transformer winding losses is crucial for optimizing the efficiency of CLLC converters. However, there remains a lack of accurate and efficient methods for calculating the winding losses, particularly the winding losses in Litz wire. A mutual-impedance equivalent circuit-based method for calculating the winding losses in Litz wire high-frequency transformers is proposed. First, the analytical approaches for calculating the Litz wire winding losses based on a one-dimensional Dowell model and a two-dimensional Bessel function method are comparatively analyzed. Then, a mutual-impedance equivalent model is established to simplify the calculation of winding losses. A specific case study is given, and the values calculated using the proposed method are compared with the impedance matrix results derived from two-dimensional finite element simulations. Results demonstrate that the relative error between the equivalent series resistances calculated using the proposed method and the results based on the finite element method does not exceed 6%, validating the effectiveness and accuracy of the proposed method. Finally, a high-frequency transformer prototype for the CLLC converter was constructed, and experimental measurements verified the feasibility of the proposed method.

A low-ripple DC-DC converter with quasi-Z-source coupled inductance is proposed, which integrates a quasi-Z-source network, a coupled inductor and voltage doubler cells. The quasi-Z-source network has functions of Boost voltage and passive clamp. While the converter achieves a high gain, the switching tube realizes passive clamp and recovers leakage energy from the coupled inductors. When the duty cycle is in the range of 0–0.5, the high gain, high efficiency and low ripple of input current required by new energy power generation can be achieved, avoiding the influence of an extreme duty cycle. The steady-state analysis, efficiency analysis and experimental verification for the converter were carried out, and its performance was compared with those of similar converters. A 200 W prototype was fabricated in a laboratory, and experimental results were basically consistent with the theoretical analysis.

An enhanced extended phase shift modulation strategy for an LCL-type full-half bridge resonant converter is proposed, which can achieve zero voltage switching (ZVS) for all the switches while eliminating the backflow power on the primary side. Meanwhile, the half-bridge structure on the secondary side enhances the cost-effectiveness of the converter under low-power conditions. The steady-state analysis of the converter is performed by using fundamental harmonic approximation, so as to derive a power model and the corresponding ZVS conditions. In addition, simulations are conducted using the software PSIM. Finally, a 300 W experimental prototype was built, and results verified the feasibility of the theory.

A SiC/Si hybrid five-level inverter and its optimized modulation strategy are proposed. The proposed topology consists of four SiC MOSFETs and four Si IGBTs, and it utilizes DC-link split capacitors to achieve a five-level structure. Under the proposed modulation strategy, all the high-frequency switching loss is distributed to the four SiC MOSFETs, while the four Si IGBTs only generate conduction losses and part of the junction capacitor charging and discharging losses. The analysis results of loss modeling show that the proposed SiC/Si hybrid modulation strategy can optimize the loss distribution, fully utilize the low-switching-loss advantage of SiC MOSFET and the low-conduction-loss advantage of Si IGBT under large current conditions. Compared with the full Si scheme, the proposed SiC/Si hybrid scheme significantly improves the conversion efficiency while only slightly adding the hardware cost. Compared with the full SiC topology, the proposed SiC/Si hybrid scheme achieves a similar efficiency while obviously reducing the hardware cost. In addition, under heavy load conditions, the proposed SiC/Si hybrid scheme achieves a higher efficiency than the full SiC scheme. An experimental platform of 4 kW SiC/Si hybrid five-level inverter was built to validate the feasibility and effectiveness of the proposed SiC/Si hybrid five-level inverter topology and its optimized modulation strategy.

An improved power balance modulation strategy based on carrier stacking modulation is proposed to address the issue of output power imbalance caused by different modulation methods used in low-voltage units in hybrid cascaded H-bridge inverters under the traditional modulation strategies. Based on the topology of an asymmetric hybrid cascaded H-bridge 11-level inverter, the symmetrical characteristics of the low-voltage unit control pulse signal under carrier stacking modulation were analyzed. Moreover, the low-voltage unit pulse control signal was segmented using T/4 or T/2 as cycles, and all the control pulse combinations under each segmentation method were given. The optimal working mode was selected based on the minimum carrier shift times and the shortest power balance time. As a result, the output voltage between low-voltage units was symmetrical, and the output power of low-voltage units was self-balanced. Finally, the proposed modulation strategy was validated through simulation and experiments.

Aimed at an offshore wind power flexible DC transmission project, the problems of the large mass and volume of modular multilevel converters (MMCs) and the high construction cost of offshore converter stations need to be solved urgently. Therefore, the lightweight research of MMC is one of the research hotspots at present. First, an optimized configuration MMC (OC-MMC) is proposed, and its configuration method is given. In addition, a voltage balancing strategy is designed based on the nearest level modulation. The novel converter improves the number of output voltage levels on the AC side by introducing two submodules whose capacitance values are the same but the rated voltage values are proportional by a factor of K. Then, through the simulation results on a MATLAB/Simulink platform and experimental results, it is found that the novel converter can successfully complete the voltage conversion process. The steady-state operation characteristics of the system are similar to those of a conventional MMC, and the dynamic characteristics are good. On the premise that the numbers of AC voltage levels of the two converters are the same, the proposed OC-MMC can indirectly reduce the number of submodule assembly and reduce the mass, volume and construction cost of the converter stations compared with the conventional MMC, so as to achieve the goal of lightweight.

A typical configuration of a DC solid-state transformer is formed by connecting standardized power conversion cells in an input-series output-parallel (ISOP) arrangement to achieve DC transformation from medium voltage to low voltage. To provide redundancy for the power conversion cells, a thyristor bypass circuit is typically required. While DC solid-state transformers generally employ SiC MOSFET devices, the high dv/dt characteristic of SiC MOSFETs can readily false triggering in the thyristor bypass circuit. The issue of false triggering in thyristor bypass circuits is focused on, and a co-design methodology involving the thyristor snubber circuit and the gate-parallel resistor is explored. The proposed approach aims to enhance the operational reliability of the thyristor bypass circuit in high dv/dt environments, and experimental validation is provided.

The high common-mode voltage (CMV) generated by pulse-width modulation in a power converter will cause overvoltage on the motor shaft and further lead to the high-frequency high-amplitude current therein, thereby damaging the motor insulation and increasing the electromagnetic interference. To reduce the CMV of a neutral point clamped (NPC) three-level converter, a CMV suppression strategy based on the framework of algebraic modulation was proposed. First, the issue of duty-cycle assignment was transformed into a problem of solving non-homogeneous linear equations. Second, the degrees of freedom for modulation were properly selected to realize the objective of neutral point voltage (NPV) balance. Third, according to the duty-cycle constraints, the offset signals were selected to obtain the final duty-cycle. Finally, the switches in the phase with intermediate voltage values adopted inverse carrier to obtain a new combination of switching states, so as to reduce the CMV. The proposed modulation strategy can be easily implemented without additional controllers. On the premise of ensuring that the NPV of the NPC three-level converter has good balance characteristics, the CMV can be reduced to the range of one-sixth of the DC-side voltage. The effectiveness and feasibility of the proposed modulation strategy were validated by experimental results.

In an islanded microgrid, the inverter filter circuit parameter perturbation and the insufficient steady-state performance of a PI controller will cause steady-state errors in the output signal, and the unbalanced loads, nonlinear loads and load switching will cause the degradation of dynamic performance. A performance compensation control structure based on a residual generator is proposed, and the gradient descent method is used to optimize the compensation controller in real time to enhance the system’s steady-state and dynamic performances. First, the transfer function model of an inverter under double closed-loop control is established, and the effects of filter circuit parameter perturbation, insufficient steady-state performance of the proportional-integral (PI) controller and load disturbance on the inverter’s output voltage performance are analyzed. Second, the performance compensation controller Q(s) in a quasi-resonant form is designed based on the real-time residual values obtained from the residual generator. Third, an optimization objective function is constructed based on the PI controller current-voltage error and the control input signal, and the compensation controller is optimized in real time using the gradient descent method. Finally, experiments were conducted using a DSP control board with a PXI semi-physical simulation platform to verify the effectiveness of the proposed method.

LLC converters are widely applied in the fields of household energy storage and distributed energy storage owing to their excellent features such as a good soft-switching range and a high power density. In the modulation design of LLC converters, to achieve a high efficiency, it is necessary to meet the conditions for resonant soft-switching based on the design of hardware parameters with a low overall power loss of the converter. The commutation process during the dead-time is analyzed to explore the influences of the parasitic parameters of switching devices on the realization of soft-switching in the converter. By optimizing the switching timing sequence during the dead-time and utilizing the circuit mechanism where the parasitic parameters of switching devices participate in resonance, the realization of soft-switching is facilitated, ensuring a higher operation efficiency. Considering the loss distribution during the dead-time, the impact of not changing the modulation under bidirectional power flow conditions on the efficiency is analyzed. Finally, verification was performed by building a 4 kW LLC prototype to carry out a bidirectional power transmission experiment.

To meet the requirements of long life, high efficiency, low ripple and intelligence of a high-power LED light source, based on an in-depth analysis of the characteristics of low-frequency secondary ripple compensation of a Boost asymmetric half-bridge (AHB) converter LED constant-current driver without an electrolytic capacitor, an adaptive low-frequency ripple compensation control algorithm for an AHB LED constant-current driver in digital predictive current mode was proposed. MATLAB simulation results show that the proposed control algorithm can adapt to the changes in input voltage and load and effectively reduce the low-frequency secondary ripple current flowing through the LED in the whole dimming range.

The grid-forming cascaded H-bridge energy storage system is an optimal solution for mitigating large-scale renewable energy power fluctuations and providing grid support. However, the power control of the system is coupled with line impedance, and the coupling effect intensifies under weak grid, leading to output power inaccuracy and increasing risk of instability. To solve this problem, an adaptive power decoupling control strategy based on reactive voltage compensation is proposed. First, based on the small-signal model of a virtual synchronous generator and through the introduction of power coupling coefficients which take into account closed-loop feedback, a quantitative analysis is conducted on the power coupling effects between line impedance angle and power angle, revealing the mechanism of effect of active power on reactive power control. Second, an adaptive reactive power compensation channel is constructed, and a proportional-integral voltage compensation link in the reactive power control is designed, which dynamically modifies the output voltage references to mitigate the power coupling without the identification of line parameters. As a result, dynamic decoupling control is realized in a wide range of impedance angle with strong adaptability. Finally, validation tests based on a simulation platform and an RT-LAB platform verified the proposed method.

Aimed at the problem of insufficient inertia and damping of a microgrid resulting from a large number of power electronic converters connected to power grid, a virtual DC machine enhanced inertia control strategy suitable for DC microgrid is proposed. First, based on the frequency division control of the hybrid energy storage unit, the virtual DC machine technology is introduced to control the energy storage converter. Second, according to the instantaneous power balance characteristics of DC microgrid, the fluctuation of load or photovoltaic output controlled by first-order high-pass filtering is taken as an additional amount of rated power controlled by the conventional virtual DC machine. Third, a regulation factor related to the auxiliary voltage regulation power and the state-of-charge of the supercapacitor is introduced to adaptively optimize its working state. Finally, the control strategy was verified by constructing an experimental platform, and results show that this strategy can improve the transient stability of DC bus voltage.

Aimed at the problem that the traditional droop control allocates load power based on a fixed droop coefficient without considering the influence of line impedance or the information about energy storage unit capacity, as well as the problems of high system communication pressure and complex control structure, a control strategy for the coordinated operation of multi-energy storage without voltage observers is proposed. First, the proposed strategy introduces a convergence function including the capacity of distributed energy storage units (DESUs) and state-of-charge (SOC) to correct the initial droop coefficient, and it gives constraints on the adjustment coefficient, thereby promoting the rapid SOC equilibrium of the energy storage unit. Second, by introducing a virtual rated power, the unit output power is configured and balanced to overcome the effect of line impedance on the load sharing of DESUs. Through the construction of a product of maximum allowable bus voltage deviation and average unit power, the bus voltage compensation amount is obtained, so as to realize voltage regulation without the need of communicating and exchanging the node voltage information about the energy storage unit or the design of the corresponding voltage observer and PI controller. Finally, the effectiveness of the proposed strategy was verified by simulation tests using MATLAB/Simulink.

With the development of offshore wind power in China advancing to the deep sea, there are no buoys in the deep sea area, the wind speed near the coast is not large and unstable, and the flotation device is affected by complex factors including extreme environmental conditions (e.g., waves and ocean currents), so there exist problems such as the poor control effect of floating offshore wind turbines due to the low accuracy of wind speed measurement data. Under this background, an intelligent power control method for the converter in a deep-sea floating offshore wind turbine is proposed, which is based on a neural network effective wind speed estimator. The control system is composed of a proportional-integral-derivative (PID) controller, lookup table, a neural network estimator and a virtual sensor, in which the neural network estimator is trained online to adapt to the transformation of the environment, so as to estimate the effective wind speed of the floating offshore wind turbine and predict its future value. In addition, the current and future wind speed data are combined and further provided to the controller. The virtual sensor can also provide measurement of the effective wind speed based on other available factors (e.g., the pitch angle and angular velocity of a fan) related to the power generation of the fan. Finally, the effectiveness of the proposed control method is verified by simulation analysis. Compared with the traditional PID, this method can improve the accuracy of sinusoidal wind measurement by about 16%, and the average improvement rate is about 8%.

An optimized control scheme for a single-phase grid-forming photovoltaic-supercapacitor system considering dynamic response improvement and double-line frequency power decoupling is proposed. Compared with the conventional scheme, this scheme integrates the supercapacitor energy storage with double-line frequency power decoupling, and there is no need for additional power decoupling circuits. The DC-link proportional integral resonant control, virtual rotor kinetic energy feedforward control and photovoltaic power feedforward control suitable for this topology are studied, so that the capacitance of the DC-link capacitor and supercapacitor is reduced. In addition, a small-signal linearized model for the second-order generalized integrator-based power calculation part is established, and a sector-based state feedback damping control scheme is put forward to improve the dynamic performance of the system. Experimental results verified the effectiveness of the proposed control scheme.

Aimed at the problem of over-smoothing in the process of wind power fluctuation smoothing by means of traditional wavelet packet decomposition, an improved wavelet packet decomposition method is proposed based on the time-frequency analysis by introducing the smoothing coefficients of high-frequency components. First, the set of time when the power fluctuation crosses the limit is found, and the components ineach frequency band are obtained using the traditional wavelet packet decomposition. Then, the optimal smoothing coefficients are determined based on an objective function and constraints, and the power components in the set of limit-crossing time are suppressed in turn, starting from the highest-frequency components until the fluctuation limits under the two time windows are satisfied. Finally, the smoothing effect is evaluated. Through the simulation analysis of an example, it is verified that under the premise of satisfying the fluctuation limits, the improved wavelet packet method can reduce the charge and discharge accumulation of energy storage and maintain the power output level of energy storage in a better state under different scenarios.

Based on the equivalent circuit model of proton exchange membrane fuel cell (PEMFC) and the electrochemical reaction theory, a fuel cell power generation efficiency calculation model is established to study the influences of operating conditions (e.g., working temperature and working humidity) on the internal resistance characteristics, output characteristics and power generation efficiency of the fuel cell stack. The principle of minimizing the total DC internal resistance inside the stack is adopted to obtain the optimum operating conditions under the output of different current densities. Experiments on AC impedance characteristics and U-I output characteristics are designed to verify the accuracy and effectiveness of the model. Simulation and experimental results indicate that the internal resistance characteristics and output current density are important factors affecting the variation in fuel cell power generation efficiency. The operating conditions corresponding to the minimum DC total internal resistance inside the stack can optimize the output performance of the stack and improve the power generation efficiency. The fuel cell power generation efficiency model established can accurately reflect the internal characteristics of the fuel cell stack, and the calculation results are effective and reliable.

To solve the inconsistency problem of series battery packs, a dual-layer topological structure with an improved Cuk chopper circuit in the outer layer and a single-inductor balanced topology in the inner layer is proposed. The improved Cuk chopper circuit is adopted, and a dual-layer switch is used to connect the balanced battery pack to the Cuk equalizer, so as to shorten the energy transfer path and improve the energy transfer efficiency. The use of the zero voltage switch technology ensures continuous balanced current and small fluctuations therein. The single-inductor balanced topology is used, which has a simple structure and high accuracy. The proposed dual-layer balanced topology can achieve energy transfer between any individual cells within one pack and that between any battery packs. With the state-of-charge of the battery as an equilibrium evaluation indicator, a balanced circuit simulation model is set up in MATLAB/Simulink, which is further compared with the traditional balanced topology in terms of static equilibrium and discharge equilibrium. Results show that the proposed balanced topology shortens the balancing time and improves the balanced efficiency. A battery balancing experimental platform was established, and discharge experiments were carried out on 12 batteries, verifying the accuracy of the hierarchical balanced topology.

To accurately determine the battery capacity, long short-term memory (LSTM) neural network was used to estimate the battery capacity. First, the life-cycle curves for different battery parameters were analyzed. The Pearson correlation coefficients between the parameters and battery capacity were calculated, and the battery voltage, internal resistance, equal voltage drop time and other parameters were selected as health factors to construct a battery capacity estimation model. Then, the Center for Advanced Life Cycle Engineering (CALCE) battery data set was used for model training and capacity estimation, and the average percentage error of the estimation model was 1.19%. The causes of estimation errors were analyzed, and the model was optimized by revising the battery’s initial capacity and aging parameters. The optimization results show that the estimation error of the model constructed using battery voltage, internal resistance, constant-current charging time and 4.0–3.4 V equal voltage drop time was about 0.55%.

To ensure the long-term safe and stable operation of electric vehicles and reduce the failure rate of lithium-ion batteries, aimed at the issue of whether the battery management system of electric vehicles can accurately and effectively detect the two important parameters of batteries, i.e., state-of-charge (SOC) and state-of-health (SOH), an improved convolutional neural networks-sequence-to-sequence (CNN-Seq2Seq) neural networks joint estimation method for the SOC and SOH of lithium-ion batteries based on CNN-long short-term memory (CNN-LSTM) neural networks was proposed. The results of comparative experiments on the public data set show that the proposed method improves the stability and accuracy of SOC and SOH estimation results for lithium-ion batteries.

The state-of-health (SOH) of batteries is an important indicator for evaluating their performance. Aimed at the difficulty in accurately estimating the SOH of batteries, a novel SOH estimation method for lithium-ion batteries was proposed by combining the hunter-prey optimizer (HPO) algorithm and long short-term memory (LSTM) neural network. Through the analysis of influences of current and temperature on the incremental capacity (IC) curve, the peak value of the highest peak in the IC curve and the corresponding voltage, temperature and current were introduced as the model input, and the dynamic parameters of LSTM neural network were adjusted using the HPO algorithm. Finally, the battery charging and discharging data under the condition of peak cutting and valley filling in the environment of energy storage were used for experimental verification. Results indicate that the SOH estimation method for lithium-ion batteries based on HPO-LSTM neural network has higher estimation accuracy compared with the traditional LSTM network methods, and it also has good robustness under different network training amounts.

With the widespread applications of energy storage plants in new power systems, improving the prediction accuracy of lithium-ion battery state-of-charge (SOC) is of significance for enhancing the safety and stability of energy storage plants and power systems. A battery SOC prediction method is proposed, which combines a multi-scale convolutional neural network (CNN) and a residual long short-term memory (LSTM) network. First, the multi-scale CNN is employed to automatically extract different types of features from the sensor data. Then, the features are fed into an LSTM network to mine the correlation in the time dimension. Meanwhile, residual connections are added at both ends of the LSTM network to avoid model overfitting. The comparative experiments on the measured data of the energy storage system show that the proposed model achieves the best prediction results in terms of all the indicators. In particular, the key features can be extracted better when the battery is under complex operating conditions, resulting in a better prediction performance.

During the normal utilization of a lithium-ion battery, its capacity will be regenerated in a short term due to factors such as internal chemical reactions and external environment. Aimed at the problems including the inaccurate estimation of state-of-health (SOH) which results from the ignorance of capacity regeneration, an optimal variational mode decomposition (OVMD) strategy based on the number of optimal layers is proposed. The low-frequency stable capacity sequence reflects the overall aging trend, while the high-frequency non-smooth capacity sequence reflects the local capacity regeneration. With the consideration of high- and low-frequency components and by introducing the weighted mean of vectors (INFO) algorithm to improve the support vector regression (SVR), a short-term SOH estimation model for lithium-ion battery is established. With the selection of NASA battery aging data sets, contrast schemes for short-term lithium-ion battery SOH estimation experiment are designed based on BP (back propagation), SVR, INFO-SVR and OVMD-INFO-SVR. Results indicate that in the case of reducing the capacity training sets, the OVMD-INFO-SVR model based on high- and low-frequency components has higher accuracy when it is used in short-term SOH estimation of lithium-ion batteries.

As a black-start power supply, distributed generation exhibits higher flexibility in terms of structure, and it is also more rapid in response speed. However, during the system restoration and construction process, the PV-storage black-start power supply based on self-synchronous voltage source control may experience frequency fluctuations, posing a risk of failure in the subsequent black-start process of power grid. To enhance the suppression effect on frequency fluctuations during the construction process, an improved self-synchronous voltage source control strategy for an interface inverter in the PV-storage black-start power supply is proposed. This improved control strategy improves the stability of the PV-storage black-start power supply, laying a foundation for the smooth implementation of subsequent black-start process. Meanwhile, simulation analysis and experimental verification were also presented, providing a detailed validation of the proposed control strategy and theoretical results.

Towards the goal of a high percentage of friendly consumption of offshore wind power, a novel control method for the parallel operation of a high-voltage direct current (HVDC) transmission system based on diode rectifier (DR) and an HVDC transmission system based on voltage source converter (VSC) is proposed. Both of the two transmission lines are connected to offshore wind farms (OWFs). The VSC-HVDC controls the voltage and frequency of the offshore AC power grid, i.e., the voltage of OWFs is controlled based on the active power balance of the AC busbar of VSC-HVDC. When the injected power of OWFs exceeds the active power reference value of VSC-HVDC, the voltage of OWFs will increase, and the DR-HVDC will be activated. In this case, the offshore AC power grid transmits the required power value of OWFs through the DR-HVDC line, while the system frequency is controlled by VSC-HVDC by meeting the reactive power balance. When the power transmitted by VSC-HVDC is the same as the set value, the DR-HVDC will be automatically shut down. The significant advantage of the proposed method is that the capacity of VSC-HVDC is only used to support the normal operation of the system. Once the OWFs are put into operation, the DR-HVDC will be automatically activated. Finally, simulation results demonstrate the effectiveness and super- iority of the proposed method.

To improve the test and evaluation technology system for fuel cell buses and effectively ensure their widespread applications, a comprehensive performance evaluation method for the power train of fuel cell buses is proposed, which combines the combination weighting method and subjective scoring method. First, a comprehensive performance evaluation system for the powertrain of fuel cell buses is constructed, and the test methods for each index are given. Then, the analytic hierarchy process and coefficient of variation are used to determine the subjective and objective weights of evaluation indexes, and the combination weighting method based on the game theory is used to obtain the comprehensive weights. On this basis, the subjective scoring method is used to score the test results of vehicles to be evaluated. At last, the comprehensive scores are obtained by weighted calculation with the comprehensive weight, which are further rated. The calculation result of an example shows that the comprehensive weight combining the subjective and objective weights over-comes the limitation of calculating the weight by only one single method and makes the evaluation results more objective and accurate, thus verifying the scientific nature and rationality of the evaluation system and method.

To improve the responsiveness, system efficiency and operation economy of a fuel cell/supercar-pacitor/lithium-ion battery hybrid energy storage system for trams, a multi-threshold energy management strategy for the hybrid energy storage system based on the operation states of trains is proposed. First, according to the actual operation states oftrains, different working conditions of tram driving are divided and multiple thresholds are set, so as to realize multi-media and multi-scenario power exchange and achieve real-time control of power allocation among energy sources of the energy storage system. At the same time, according to the physical characteristics of each energy storage medium, the supercapacitor is set to start as priority, thus reducing the number of cycles of lithium-ion batteries and extending the service life of the energy storage system. Second, the life cycle cost of the hybrid energy storage system is taken as an optimization objective, and the power of the energy storage system, energy demand and state-of-charge (SOC) of the lithium-ion battery and supercapacitor are used as constraints, so as to optimize the capacity configuration of the energy storage system and obtain the optimized capacity configuration parameters. Finally, the proposed strategy is compared with the fixed-threshold strategy and traditional equivalent consumption minimization strategy (ECMS). Results show that the proposed strategy is more reasonable in terms of power allocation of the hybrid energy storage system, and it can improve the system response speed. The SOC offset ranges of lithium-ion battery and supercapacitor are significantly improved. The hydrogen consumption is reduced by 1.47 kg and 0.81 kg compared with those under the fixed-threshold and ECMS strategies, respectively, indicating that the fuel economy is improved.

The power supply system in a data center is its critical infrastructure, which provides stable and reliable power support for all the power-driven equipment therein to ensure itsnormal operation. With the rapid development of technologies such as big data, cloud computing and 5G, the number and scale of data centers in China are increasing rapidly, requiring higher reliability of power supply and increasing the overall power consumption. In addition, the problem of high carbon emissions is even more obvious because the data centers at present mainly use electricity from the traditional energy sources. Therefore, how to achieve a green, energy-saving and low-carbon power supply and distribution mode is the focus of the development of data center power supply systems. The functions and characteristics of typical power supply architectures of data center power supply system are analyzed, and the development and evolution of power supply architectures of data center are introduced. On this basis, “carbon peaking and carbon neutrality” is taken as the background, and a prospect for the power supply architectures of data center in the future is given combined with the problems encountered in the development of power supply system of data center, providing reference for its in-depth research and subsequent development.

In the medium- and high-speed operation ranges, the sliding mode observer (SMO) usually obtains the rotational speed and rotor position of a permanent magnet synchronous motor (PMSM) based on a formula method or phase-locked loop. However, the phase delay caused by a low-pass filter, the parameter variation in the phase-locked loop itself and the sliding mode chattering remain the key issues that need to be addressed. Under this background, a position sensorless control method for PMSM based on an improved SMO is proposed. First, a variable sliding mode gain related to the rotational speed is designed, which can achieve adaptive adjustment of the sliding mode gain parameter when the rotational speed changes, thereby reducing the system chattering and improving the system stability and dynamic performance. Second, based on the mechanical motion equation, a method for estimating the rotational speed and rotor position is put forward, which not only simplifies the estimation process but also effectively reduces the influence of changes in rotational speed on the estimation accuracy and enhances the system’s anti-interference capability. Finally, the feasibility and effectiveness of the proposed method were verified based on bench experiments.

The dual permanent magnet linear synchronous motors (PMLSMs) under synchronized feed servo control are susceptible to disturbances such as parameter variations, external interference and friction, so they are not synchronous in positions. Aimed at this problem, an improved cross-coupled synchronization control algorithm for dual linear motors is proposed, which is based on linear active disturbance rejection control (LADRC). On the basis of the structure of this algorithm, LADRC controllers based on position average and position difference are designed, respectively, ensuring the high-precision control of each linear motor position and effectively reducing the synchronization errors between the two linear motors. Simulation and experimental results demonstrate that the proposed control method can achieve high-precision synchronization control of the two linear motors.

Discharge-pumped excimer laser has some unique applications in the biomedical field. However, there still exist some practical problems to be solved in the process of engineering, such as machine heating and electromagnetic compatibility. The discharge-pumped circuit structure of excimer laser was introduced, the electromagnetic radiation and heat generation of the laser head and high-voltage charging power supply were analyzed, and the working states of an LC series resonant high-voltage capacitor charging power supply in different modes were compared. In addition, the heating and electromagnetic radiation of each part in the high-voltage capacitor charging power supply in different working modes were compared through experiments. Experimental results show that when the circuit switch tube worked in the mode of f_s=f_r/2, the IGBT junction temperature decreased by 16.8 ℃ compared with that in the mode of f_s≥f_r, and the IGBT loss was also reduced by 83.7 W (i.e., 82.8% in proportion) in the meantime, thus effectively reducing the temperature of the high-voltage charging power supply and improving the machine’s electro-optical conversion efficiency. Moreover, the peak value of magnetic field intensity was reduced by 16.53 dB, and the peak value of electric field intensity was reduced by 20.05 dB, effectively suppressing the electromagnetic radiation interference.

The electromagnetic propulsion unit requires precise control of the armature end-of-rail velocity. A closed-loop control strategy for the armature end-of-rail velocity is proposed based on an inertial energy storage pulsed power supply system. Under this strategy, the actual armature end-of-rail velocity is controlled by detecting the armature velocity at the key position of the guiderail and adjusting the number of triggered pulsed alternators in the pulsed alternator array. Simulation results show that when the desired armature end-of-rail velocity is 850 m/s and if the field current of the pulsed alternator and the armature mass of load simultaneously change in the perturbation of 2%, the relative error of the armature end-of-rail velocity will be 0.376% without closed-loop regulation. However, the armature end-of-rail velocity error can be reduced to 0.020% after using the closed-loop control strategy.

Due to its advantages such as low cost and high space utilization, the electric-drive-reconstructed vehicle-to-grid (V2G) system has become a research hotspot recently. The open-phase fault is inevitable during the operation of the electric-drive-reconstructed V2G system, under which the grid-side current will fail to keep balance and the motor torque may even increase sharply. Therefore, there are many potential safety problems. Aimed at these problems, an electric-drive-reconstructed V2G system based on an asymmetric six-phase permanent magnet synchronous motor is constructed, and its fault tolerant control scheme under open-phase fault is proposed. First, the circuit topology of the six-phase electric-drive-reconstructed V2G system is analyzed. Second, the relationship between the grid-side current and the motor’s x-y space current is deduced, so that the working mechanism of the system during its normal operation is obtained. Third, a fault tolerant operation scheme for the six-phase electric-drive-reconstructed V2G system under open-phase fault is put forward by injecting current to the o₁-o₂ space of the motor, so as to produce zero torque and balanced grid-side current and ensure the system’s normal operation under open-phase fault. Finally, a 270 W experimental prototype was built, and experimental results verified the feasibility of the system and its fault tolerant operation scheme.