With the rapid development of new energy technology, the performance of DC-DC converters continuously increases. In this paper, a novel high-gain DC-DC converter is proposed, which is improved based on the quasi-Z-source topology. Owing to the use of the topology in which three capacitors discharge together to the load, a higher voltage gain is obtained while the voltage stress of capacitors is reduced. The proposed converter has advantages of the traditional quasi-Z-source converter such as simple control, continuous current and small current ripple. The working principle for this converter is analyzed. In addition, its performance was verified through simulation experiments and prototype experiments.
A novel single-switch high-gain converter with no transformers and no coupled inductors is studied in this paper. Since the voltage lifting unit is added to the Boost converter, the voltage gain of the converter is improved, the voltage stresses of the switch and diodes are reduced, and the conduction loss of the switch is reduced under the condition of a small duty cycle. As a result, the efficiency of the converter is improved. To further improve the dynamic performance and anti-disturbance capability of the converter, the immune feedback mechanism is introduced based on the analysis of a single neuron controller. A fuzzy immune-single neuron PID control strategy is studied in this paper, in which the fuzzy immune control is combined with the single neuron smart controller to realize self-tuning of the single neuron proportional coefficient. Finally, a simulation study of the proposed converter and control strategy was carried out, and an prototype with an output of 200 V/0.5 A was designed for experimental verification. Both the simulation and experimental results show that the proposed converter can obtain a higher voltage gain under a smaller duty cycle. Compared with the traditional PID control strategy, the proposed fuzzy immune-single neuron PID control strategy can more effectively suppress system disturbances and improve the dynamic performance of the converter, indicating a stronger adaptive
In order to improve the DC voltage gain and reduce the electrical stress,a novel high voltage gain DC-DC converter based on Z-source is proposed. Theoretically, the ratio of output voltage to input voltage can reach (2-D)/( 1-2D). Compared with the traditional diode capacitor filter Z-source DC-DC converter, the proposed topology can provide a higher DC voltage gain at the same duty cycle. It has lower voltage stress and inductance current stress when the DC voltage gain is the same. In addition, the input port and output port of the proposed DC-DC converter share the common ground, which helps to reduce the electromagnetic interference of the system. On this basis, the steady-state principle and characteristics of the proposed DC-DC converter are introduced, and the parameter design and theoretical efficiency calculation are also carried out. Finally, an experimental prototype with a power level of 200 W was fabricated, and experimental results proved the feasibility and superiority of the proposed circuit topology.
Owing to their merits including continuous input and output current, high efficiency and high power density, non-isolated Superboost converters are widely applied in spacecraft power systems. However, the switching loss of the device will increase in a scenario with a high step-up ratio, resulting in a decrease in the converter efficiency. To solve this problem, a zero-voltage switching pulse-width modulation (ZVS-PWM) Superboost converter with low voltage stress is proposed. By introducing a resonant tank, the main switch can be turned on or off under ZVS, and the auxiliary switch can be turned on under zero current switching and turned off under ZVS. Besides, all the diodes are operating under soft-switching. As a result, the switching loss is reduced effectively, and the converter efficiency is improved without increasing the voltage and current stress of the main power device. The operation principle, soft-switching conditions and device stress are analyzed in detail, and the state-space averaging approach is used to estimate the steady-state and dynamic characteristics of the proposed converter. In addition, its feasibility was verified by a prototype with 100 kHz and 400 W.
The active-clamped soft-switching inverter can realize the soft-switching of power devices, which is conducive to improving the power density and dynamic performance of the inverter. However, when overcurrent occurs, if the conventional cycle-by-cycle(CBC) current limit strategy(i.e., a strategy under which power devices will be blocked once overcurrent occurs) is adopted, the DC bus current will change its direction from flowing to the inverter bridge to flowing to the DC side. Due to the existence of a resonant inductor, both the DC bus current and the current flowing through the resonant inductor flow through the auxiliary switch, so there is high current stress on the auxiliary switch. In this paper, an improved CBC current limit strategy is proposed. By changing the switching state of the inverter bridge after the CBC current limit strategy is triggered, the DC bus current flowing to the DC side is reduced, thus significantly suppressing the current stress. In addition, the protection strategy was verified by an experiment of 3 kW active-clamped soft-switching inverter.
Aimed at the problem that the particle swarm optimization (PSO) algorithm has a poor global search capability and is easy to fall into local optimum when it is applied to the selective harmonic elimination pulse width modulation (SHEPWM) of an inverter, an improved PSO algorithm is proposed. The vertical crossover operation of genetic algorithm is introduced to the search process, and the elite retention strategy is used to improve the global and local search capabilities of the algorithm and retain excellent individuals, thereby increasing the accuracy of switching angle and improving the performance of SHEPWM. This algorithm is used to solve the SHEPWM nonlinear transcendental equation of a novel asymmetric cascaded switched capacitor multi-level inverter, which overcomes problems such as the high dependence of traditional numerical methods on initial value and the low accuracy of the traditional PSO algorithm in solving the switching angle. Finally, the feasibility of the proposed topology and the effectiveness of the proposed algorithm applied to SHEPWM were verified by simulation and experimental results.
Aimed at the problem that the converter current ripple and electromagnetic interference (EMI) noise will increase due to the increasing switching frequency of a three-level neutral point clamped (NPC) converter, a variable switching frequency modulation strategy based on current ripple prediction is proposed to reduce the current ripple, harmonic noise and EMI noise of the three-level NPC converter. According to the requirements of current ripple, the switching cycle and sampling cycle are calculated to synthesize the latest switching cycle and form feedback, so as to realize variable frequency modulation. The random cycle is distributed around the expected cycle, so that the harmonic noise and electromagnetic noise of the converter are more evenly distributed in a wide frequency band. As a result, the electromagnetic noise of the converter is reduced, and the output inductance current ripple is improved. The relevant simulation and experimental results verified that compared with those under the traditional modulation strategy, the common mode noise was reduced by about 20 dB/μV under the proposed modulation strategy, the differential mode noise was reduced by about 10 dB/μV, and the amplitude of output inductance current ripple was also reduced accordingly.
A novel nine-level inverter topology with double boost and reduced components is proposed by combining the voltage boost capacity of switched capacitors with the voltage halving characteristics of a coupling inductor. This inverter consists of 12 switches, 2 switched capacitors and 1 reverse polarity coupling inductor. The charging and discharging of each capacitor in the inverter can maintain a self-balance, so the additional balance circuit is not needed. Compared with the topologies of most of the existing nine-level inverters that are based on switched capacitors, the proposed topology has a smaller capacity of switched capacitor. The output voltage levels are greatly increased by the adoption of the reverse polarity coupling inductor, and the current stresses on some switches are reduced by half, which can further reduce the switching loss. The working modes, modulation strategy, design of switched capacitors and loss analysis of the proposed topology are discussed in detail. In addition, the proposed topology is compared with those of other nine-level inverters, and its advantages are introduced. Finally, simulation and experimental results verified the effectiveness of the proposed topology.
For an LCL-type inverter connected to weak grid, the appearance of grid impedance often results in a decrease in the phase margin, serious distortion of grid-connected current and even system instability. To solve this problem, an improved grid-connected current control strategy is proposed, in which a multi-resonance controller is introduced in the voltage feedforward loop to suppress the voltage background harmonics and a phase compensator is added to the current feedforward loop to improve the system's phase margin, so as to avoid the risk that the resonance peak of the multi-resonance link intersects with the -180° line. Theoretical analysis and simulation results show that the proposed strategy can effectively suppress the harmonics of LCL-type grid-connected current, improve the current quality and enhance the stability of the grid-connected system.
The smooth switching between grid-connected and islanded microgrid operation modes and the stability of system frequency are important guarantees for the safe and stable operation of a master-slave microgrid system. Combined with the operating characteristics of the microgrid system, an off-grid switching method based on phase angle switching is proposed, and a pre-synchronization control module is added to make sure that the grid phase is quickly tracked and compensated when the islanded mode is switched to the grid-connected mode, thereby solving the problem of shocks in the output voltage and current from master and slave inverters in switching. To ensure the frequency stability of the microgrid system, a V-F frequency control strategy based on fuzzy droop control is proposed and further applied to the smooth switching based on phase angle switching, so that the system frequency is basically maintained at 50 Hz and the problems of large oscillations in voltage and current and frequency shocks in switching are avoided. Finally, an experimental platform was built to verify the effectiveness and stability of the proposed method.
The cascaded H-bridge is considered as one of the most suitable topologies for photovoltaic (PV) power generation. Aimed at the problems of the traditional three-phase cascaded H-bridge PV inverter such as a large capacitor volume, a short service life, inter-phase power mismatch and a complex control communication system, a novel modular three-phase PV inverter and its distributed control strategy are proposed based on the principle of magnetic flux cancellation. First, the basic structure of the proposed modular topology is introduced. Then, the basic principle of magnetic flux cancellation power decoupling and the influencing factors of double-line frequency voltage ripple are analyzed in detail, and a distributed control strategy is proposed to suppress the double-line frequency voltage ripple and ensure the balance of three-phase output power. Finally, the correctness of theoretical analysis and the feasibility of the proposed control strategy were verified by simulation and experimental results.
The traditional maximum power point tracking (MPPT) method is prone to falling into a local optimum under partial shading conditions and failing, while the common intelligent optimization algorithms often have disadvantages such as a low convergence accuracy, a slow convergence speed, and a low system stability. Aimed at these problems, a maximum power tracking strategy for photovoltaic (PV) system is proposed, which is based on the hybrid control of sailfish optimization (SFO) algorithm and perturbation and observation (P&O) method. The SFO algorithm uses two populations of sailfish (predator) and sardine (prey) at the same time to ensure the exploration of particles in the global space. The hybrid algorithm uses the SFO algorithm to quickly track the neighborhood of maximum power point at first, and then it uses the P&O method with a small step size to finely search for the maximum power point. In this way, it takes advantage of the piecewise step method to meet the requirements of MPPT search speed and search accuracy. Simulation results show that the hybrid control strategy effectively improves the response speed and tracking accuracy of the control system, as well as its stability.
When a grid-connected inverter (unit) is connected to a weak grid, the wide range of grid impedance variation may lead to system instability. To solve this problem, a centralized active damping device is configured in parallel at the point of common coupling (PCC) to simulate the external characteristics of damping resistance, thus realizing the suppression of resonance between the grid-connected inverter and grid. In this paper, an adaptive adjustment method for virtual impedance value based on active damping device is proposed, which not only ensures the system stability, but also minimizes the current flowing in the active damping device. At the same time, a current harmonic reference compensation method is proposed, which can reduce the influence of current closed-loop on the virtual impedance characteristics and further improve the damping effect. A 5 kW grid-connected inverter and a 1 kW active damping device were built in a laboratory to verify the effectiveness of the proposed control scheme.
Aimed at the 5th, 7th, 11th, 13th and other low-order harmonics which account for a large proportion in a voltage source converter based high-voltage direct current (VSC-HVDC) AC system, on the basis of proportional integral (PI) control, a selective harmonic current control strategy based on a vector proportional integral (VPI) regulator in dq coordinate system is proposed, in which PI is used to control the DC component of current error while VPI is used to suppress the frequency doubling fluctuation of current error. Different from the proportional integral resonance (PIR) regulator, VPI contains a second-order numerator, which can achieve an ideal 0° phase delay of the closed-loop transfer function of the control system at the resonance frequency point. As a result, its control accuracy of harmonic current is better than that of PIR. A two-terminal VSC-HVDC system is established by using the Simulink software, and the AC current on two sides of VSC in three control modes of traditional PI, PIR and PI parallel VPI is simulated. Through a comparison of harmonic content, the superior harmonic suppression performance of VPI is verified.
When the improved droop control based on virtual impedance is adopted in island microgrid, the problem of inaccurate distribution of reactive power and reactive power circulation will still occur with the changing line impedance due to the fixed value of virtual impedance. To solve this problem, a virtual impedance prediction model based on partial least squares regression (PLSR) is proposed, which uses the line impedance value and the system impedance value before compensation to predict the virtual impedance value and realizes the adaptive virtual impedance, thus overcoming the problem in the improved droop control based on virtual impedance. There is no need to detect the real-time power value and circulation value, and the use of communication network is not required. Furthermore, from a comparison with the prediction results obtained by neural network models, it is proved that the prediction accuracy of the virtual impedance prediction model based on PLSR is better. At last, a simulation system of microgrid is constructed in MATLAB/Simulink to verify the adaptive virtual impedance, and simulation results show the superiority of the proposed model.
To satisfy the low sampling frequency, low computational cost and high accuracy requirements of renewable energy generation systems in the grid voltage detection link, a high-precision discrete-time frequency-locked loop (FLL) which does not need to call trigonometric functions is proposed. First, the open-loop transfer function of discrete-time reduced-order generalized integrator (d-ROGI) is derived according to the expression of voltage based on complex numbers under the static coordinate system. Then, a d-ROGI with a low approximation error is derived according to the relationship between the unknown parameter of the open-loop transfer function and frequency. On this basis, the FLL for estimating the unknown parameter is constructed, the second-order small-signal model of the FLL is established, and the corresponding parameter tuning method is given. Finally, experimental results show that the FLL has a higher detection accuracy at a low sampling frequency than the most commonly used third-order numerical integrator discretization method. At the same time, it has a lower computational cost and requires less storage according to the comparison of computation cost.
When the grid voltage is unbalanced, the phase-locked loop (PLL) needs to retrack the grid voltage. At this moment, an inaccurate phase lock or an overlong phase lock time will cause the degradation of control performance for the subsequent flexible DC transmission system. Therefore, to avoid the adverse effects caused by PLL, an improved control strategy for converter without PLL is proposed. First, the difference between the traditional PLL scheme and the proposed scheme without PLL is analyzed, and an instantaneous positive- and negative-sequence component extraction scheme is put forward in an environment without PLL. Second, a converter control system without PLL is designed, and the compensation of negative-sequence current is taken as its control target. Finally, the validity and correctness of the proposed strategy was verified by the experimental results of a prototype.
Since the existing capacity load ratio calculation methods do not take into account the impact of different voltage levels on AC grid, they cannot ensure the optimization of the reliability and economy of AC grid at the same time. To solve this problem, a capacity load ratio calculation method for AC grid at multiple voltage levels is proposed on the basis of considering voltage levels. The power supply capacities of AC grid in high- and low-voltage modes are calculated, respectively. According to the power supply capacity, the discrete particle swarm optimization algorithm is used to calculate the particle number of capacity load ratio at different voltage levels, and the optimal capacity load ratio calculation results of AC grid at multiple voltage levels are obtained, so as to realize the capacity configuration optimization of AC grid at multiple voltage levels. Experimental results show that the proposed method can optimize the transformer's capacity load ratio, and the power supply reliability, economy and satisfaction score of AC grid are higher.
To solve the problem of performance degradation in automotive lithium-ion batteries at low tempera- tures, a self-heating method based on electric vehicle traction motor and inverter reconfiguration was developed, in which the traction motor windings were utilized as energy storage units to realize AC heating of batteries at low temperatures without additional hardware. First, a detailed mathematical description of AC heating topology was given, and the analytical relationship among the battery voltage, current and heating control parameters was obtained. Then, an adaptive fuzzy PI controller was designed to regulate both the heating current and the charge/discharge voltages of batteries dynamically, so that the heating rate can be guaranteed while avoiding the aging of batteries. In addition, in order to relieve the mechanical vibration and noise from the traction motor during internal heating, a torque ripple canceling scheme based on the clamped rotor position was also proposed, thus ensuring the passenger comfort and the motor durability. Experimental results demonstrate that under the proposed strategy, the tested batteries warmed up from -20 ℃ to above 0 ℃ within 403 s without permanently damaging the battery life.
Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is of significance for improving the safety of working environment and the reliability of equipment. To improve the stability and accuracy of RUL prediction, a battery RUL prediction method based on the combination of denoising technology and hybrid data-driven model is proposed. First, the original data is decomposed by variational mode decomposition, and the noise components are filtered by the analysis of correlation. The residual error is combined with the components which have a strong correlation to complete the sequence reconstruction process. Second, with the combination of Tent chaotic mapping, sine cosine algorithm and Levy flight strategy, the sparrow search algorithm (SSA) is optimized, and the optimal weight threshold of extreme learning machine (ELM) is obtained. Finally, the improved SSA-ELM model is trained by using the smoothed denoised data, and the RUL prediction is completed. The NASA data sets are used to verify the effectiveness of the proposed method. Experimental results show that the average absolute error and root mean square error of the prediction result obtained using this method are controlled within 1.58% and 2.14%, respectively, indicating that this method has a high robustness and a high prediction accuracy. Therefore, the proposed method can be applied to battery RUL prediction.
In the actual operation of a battery, its temperature will vary with the ambient temperature, which undoubtedly increases the difficulty in estimating its state-of-charge (SOC). To address this problem, the relationship of temperature with the charge and discharge capacities, internal resistance and open circuit voltage of the battery is studied, and an equivalent circuit model considering temperature is established accordingly. The battery SOC is estimated based on this model by combining the extended Kalman filter algorithm, which can update the temperature-dependent variables in real time and adapt to the temperature change of the battery. In addition, this method is validated at variable temperatures. Results show that the proposed method can quickly and accurately estimate the battery SOC with an estimation error within 2%.
In view of the flat hysteresis characteristics of open circuit voltage(OCV) and state of charge(SOC) of LiFePO4 batteries, the OCV estimated by using the traditional equivalent circuit model has the problem of low accuracy under the charge-discharge switching conditions, so the hysteresis modeling of battery is proposed. To highlight the necessity of considering the hysteretic characteristics of LiFePO4 batteries, three battery models are compared to comprehensively evaluate their complexity, accuracy and applicability. Results show that the first-order RC model is only suitable for pure charge or pure discharge conditions without considering the influence of hysteresis. The first-order RC hysteresis model adds a hysteresis on the basis of the first-order RC model. Although the influence of hysteresis characteristics is considered, the hysteresis is greatly affected by parameter identification and the OCV estimation fluctuates. The Preisach model has a good accuracy under the charge-discharge switching conditions, but the corresponding training data and time cost are high. Under the new European driving cycle(NEDC) charging and discharging conditions, SOC estimation is carried out for different models combined with algorithms, and the estimation errors are all within 5%, among which the Preisach error is within 3%.
To address the difficulty in predicting the state-of-charge (SOC) of a Li-ion battery pack, an SOC prediction model based on kernel extreme learning machine (KELM) optimized by the improved sparrow search algorithm (ISSA) is proposed. First, Logistic chaotic mapping is introduced to improve the standard SSA and acquire the best population individuals. Second, the improved algorithm is used to optimize the kernel function parameter S and penalty coefficient C of KELM to create an ISSA-KELM prediction model. The simulation is carried out utilizing the historical data from an energystorage device, and the results predicted by ELM, KELM and ISSA-ISSA-KELM models were compared and analyzed.In addition, the robustness of the model was verified using data under other working conditions. Results show that the root mean square error and mean absolute error of predicted SOC decreased to 2.06% and 1.54%, respectively. The proposed model improved the prediction accuracy, and its convergence, generalization and robustness were also satisfying.
According to the demand of enterprises which produce UPS, a condition based maintenance(CBM) management system of UPS based on extended Kalman filter(EKF)-Markov is designed. Under the permission of users, the status data of online position and real-time operation of the equipment is visualized by using the geographic information system. Compared with the traditional post-maintenance scheme, the weighted method is used in data preprocessing to model the CBM of the data-driven collected information and reduce differences caused by different types of data. The EKF is used to eliminate the influence of noise on the sampling results, and the average error of state-of-charge(SOC)predicted using the algorithm is 0.434 3%. Combined with the Markov decision process, the UPS battery state is analyzed, the health management and CBM strategy in charge-change mode is implemented, and the maintenance time is reduced by 57.12% on average. Results show that compared with the traditional maintenance, the state prediction and health management system can improve the maintenance efficiency and accelerate the transformation from traditional planned maintenance to CBM mode.
At present, the physical parameters of a lithium battery cycle life model are difficult to obtain, and the parameter identification process needs a lot of experimental data and a long test time. In addition, it is difficult and expensive to simulate the cycling effect of lithium-ion batteries. On this basis, in order to explore the electrical stimulation of lithium-ion battery aging (due to cycling) and its effect on the battery capacity and internal resistance, a novel cycle life model of lithium-ion battery is proposed. First, a simple physical equation is established based on the fatigue theory and equivalent cycle counting. The parameter identification process is simple, requiring only a small amount of data in the battery data table and a limited (or short) cycle test. The proposed model is general and can represent the effects of common cycle life factors such as depth-of-discharge, temperature and C rate. Finally, two kinds of lithium-ion batteries (i.e., LFP-LiFePO4 and NMC-LiNiMnCoO2) are used to verify the model. The simulation results are close to the actual situation, and the error is within 1.5% compared with the experimental results.
The energy storage battery pack consists of a large number of low-voltage battery cells. The states-of-charge (SOC) of cells are different due to the difference in their characteristics, which causes some cells to be over-discharged during the charging process. To avoid this phenomenon, a equalizing charger based on multi-winding transformer and cascaded double-voltage rectifiers is proposed, and its characteristics are compared with those of a centralized passive equalizing charger. Its operation principle is analyzed, and its equivalent circuit is obtained. The buffer inductance of the novel equalizing charger and the turn ratio of the transformer are also optimized. A control strategy of single voltage-loop is put forward, which can guarantee the charging at two stages, i.e., constant-current and constant-voltage. In addition, the influence of the voltage difference between cells on the transformer operation is analyzed. Simulation results show that the proposed charger can achieve a high charging efficiency while satisfying the requirement of voltage equalization between cells.
Aimed at the thermal runaway accident of lithium-ion batteries in the process of civil aviation transportation, through the simulation of a low-temperature and low-pressure environment during the civil aircraft flight, the thermal runaway of a lithium-ion battery is triggered by contact heating of an external heat source, and the thermal runaway characteristics of lithium-ion battery in a variable pressure and variable temperature environment are explored. Resultsshow that the thermal runaway time of lithium-ion battery advances with an increase in the flight altitude. Within a certain temperature range, temperature has a greater impact on the thermal runaway time than air pressure. When the ambient temperature decreases to a certain extent, it will no longer affect the peak temperature of thermal runaway. The CO concentration increases with an increase in the flight altitude. The solid particles produced by thermal runaway are different at a limit of 0 ℃. When the flight altitude is 8 km (80 kPa, 10 ℃), the combustion of thermal runaway products is stronger.
To better compensate for the voltage drop of DC-side bus in an electric vehicle (EV) fast charging station and limit the power ramp rate of power grid, a nonlinear control strategy of flywheel energy storage system for the DC fast charging station is proposed based on the immersion and invariance theory. First, considering the power balance relationship of the power supply system in the fast charging station, the impact characteristics caused by the charging load instantaneous access under the traditional control strategy of flywheel energy storage system are analyzed, and the voltage stability of DC-side bus is determined as the optimization objective. Then, the effect of bus voltage control and the control accuracy of energy storage output current are considered, an affine nonlinear model of flywheel energy storage is established, the manifold surface and control law are constructed using the immersion and invariance method to provide the capability to quickly respond to the charging load current mutation and flywheel speed change, and a charging and discharging control strategy for the energy storage system is designed. Finally, a simulation model is built to compare and analyze different control strategies under single- and multi-EV access, and results show that the proposed control strategy can effectively suppress the influence of electric vehicle access and flywheel speed change on the bus voltage, thereby alleviating the impact on the distribution network.
A direct control strategy is proposed for a suspension winding DC excitation double- inding bearingless flux switching permanent magnet motor (BFSPMM) with 12/10 pole U-type stator core. First, the influence of rotor eccentricity on the mathematical model of the motor is analyzed, and a double-winding BFSPMM mathematical model under the condition of eccentricity is constructed. Then, a mathematical model of the torque of double-winding bearingless flux switching motor is derived according to the principle of electromechanical energy conversion, and the direct torque control based on space vector pulse width modulation (SVPWM) is constructed. Finally, the virtual displacement method is used to obtain the mathematical model of suspension force, and the voltage vector synthesized by SVPWM is used to precisely control the flux of suspension winding, thus realizing the direct control of suspension force. Experimental results show that the rotor can be suspended stably, and the suspension force and torque can be controlled independently, indicating that the system has good dynamic and static characteristics.
To maximumly protect the medium-voltage motor in a back-to-back medium-voltage motor driving system without transformer based on modular multilevel converter (MMC) from the influence of asymmetric grid faults and switching actions, a control strategy for minimizing the common-mode voltage of the front-end transformerless grid-connected MMC is designed. The common-mode voltage caused by the asymmetric grid fault can be canceled by the MMC counterpart voltage, and the switching ripples caused by the switching action of the MMC can be suppressed by arranging the arm-voltage pulses end-to-end. In addition, the influence of MMC common-mode voltage suppression on the single-phase power deviation is analyzed, and the feedforward control is proposed accordingly. Tests were carried out using a grid-connected MMC prototype system, and experimental results verified that the maximum common-mode voltage of the grid-connected system under severe asymmetric grid conditions can be reduced to 1/3N of its original value by the proposed control strategy, where N is the per-arm submodule number. Meanwhile, the unity power factor, constant DC voltage, and balanced single-phase power were also realized.
To study the influence of electron irradiation on the reliability of silicon carbide metal-oxide- semiconductor field-effect transistor(SiC MOSFET) with different aging degrees of the gate oxide, the electrical characteristics of SiC MOSFET were analyzed by combining high-temperature gate bias and electron irradiation experiments. The influence of electron irradiation on the threshold voltage of SiC MOSFET after the gate oxide was stressed by high temperature and a strong electric field was discussed. To avoid the impact of the packaging material on the threshold voltage under high temperature and electron irradiation, the device under test was exposed to air during the experiment. Experimental results show that the threshold voltage after the high-temperature positive gate bias experiment was more sensitive to electron irradiation. The exponential relationship of the influence of electron irradiation on the threshold voltage of SiC MOSFET after the high-temperature gate bias aging was proposed. The threshold voltage after the high-temperature gate bias at 39 V and 150 ℃ for 2 h can be restored to the initial value by 0.2 MeV and 300 kGy electron irradiation. A basic numerical model of SiC MOSFET was established in the Sentaurus TCAD simulator. By setting the electron concentration and hole traps in the oxide, the effect of high-temperature gate bias and electron irradiation on the threshold voltage of the device was simulated, and the threshold voltage recovery mechanism was discussed.
Temperature sensitive electrical parameter method has characteristics such as strong online capacity, non-invasiveness, and rapid response, so it has become a research hotspot at present. The on-state voltage drop is taken as a temperature sensitive electrical parameter, and an online monitoring method for IGBT junction temperature is studied based on the on-state voltage drop. First, the data of on-state voltage drop, collector current, and junction temperature of IGBT is obtained through the double-pulse test circuit. Then, based on the measured data, a three-dimensional mapping representation model of IGBT collector current, junction temperature, and on-state voltage drop is constructed. Finally, a novel on-state voltage drop sampling circuit was designed, and an online monitoring experimental of IGBT junction temperature was conducted. Experimental results verified the accuracy and validity of the obtained three-dimensional junction temperature representation model.
A novel low delay and low power consumption low-to-high level shift circuit with a logic correction function is proposed, which uses a low delay level shift circuit and a low power consumption level shift circuit to work in parallel. After the logic is corrected, the low level between 1 V and 1.5 V is converted to a high level of 5 V, so this circuit can be widely applied in GaN driver circuits. Based on the 0.5 μm BCD process, 1.5 V power supply low voltage and 5 V power supply high voltage, the circuit is verified at 5 MHz. Results show that although the layout area of this circuit increases as a whole, the rise and fall delays are reduced to 2.3 ns and 1.8 ns, respectively, with a total power consumption current of only 11 μA.
Aimed at the problem that the simulation of electromagnetic radiation interference of a switching power supply module is not combined with its actual working conditions, a method combined with near-field scanning was proposed. First, a simulation model of the switching power supply was built by software Cadence Allegro, and the software Cadence Sigrity was used to obtain the near-field radiation image and data by performing eletromagnetic radiation simulations of the switching power supply module. Then, a near-field scanning system of electromagnetic radiation was built to test the electromagnetic radiation interference of the switching power supply module, and its near-field electromagnetic radiation cloud map and electric field distribution data were obtained. Finally, by comparing the electromagnetic radiation distribution data obtained from near-field scanning and simulations, the simulation results were verified, and the MOSFET switch tube device and the surrounding circuit in the switching module were determined to be the source of electromagnetic radiation with the highest intensity.
The three-phase inverter is an important part of the motor drive system in an electric vehicle (EV). When a fault occurs, the fault sample size will be limited due to the short occurrence time, resulting in sample imbalance. To solve this problem, an inverter fault diagnosis method combining conditional generative adversarial network (CGAN) and convolutional neural network (CNN) is proposed in this paper. First, the phase current is taken as a fault sensitive signal, its frequency-domain characteristics are obtained by fast Fourier transform, and normalized preprocessing is carried out. Then, each sample is labeled and input into the CGAN model for countermeasure training to generate new samples in each fault mode. Finally, the CNN model is used to distinguish various fault modes of inverter. Through experimental research, it is found that the fault diagnosis accuracy based on CGAN- CNN can reach more than 98%, indicating that the proposed sample generation method is better than the traditional Smote and GAN methods. The results in this paper provide theoretical support for the intelligent operation and maintenance of new energy EVs.
Sponsored by: China Power Supply Society Edited by: Editorial Department of JOURNAL OF POWER SUPPLY Distribution in China: Local Post Offices or Online subscription Editor-in-Chief: Jiaxin Han Acting Editor-in-Chief: Xinbo Ruan Co-Editor-in-Chief: Xiong Du and Wu Chen Editorial Manager: Guozhen Chen CN: 12-1420/TM ISSN: 2095-2805 Postal Code in China: 6-273 International Postal Code: BM8665