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 °C 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.

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%.

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.

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.

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.

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.

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 capability and a stronger robustness.

Aimed at new energy combined power supply systems such as photovoltaic and fuel cells, a non-isolated dual-input high step-up DC-DC converter is proposed. This converter is based on a dual-input Boost circuit, and the two input sources and output, as well as each switch tube, share a common ground. A diode capacitor network is introduced at the later stage to achieve high voltage gain and reduce the voltage stress of switching devices. The two input sources can supply power at the same time, and any one of them can supply power independently without adding extra switch tubes. In addition, the voltage gain can be further improved by expanding the booster unit to adapt to different application scenarios. The working principle for the converter and its extended circuit and the corresponding performance such as voltage gain characteristics and voltage stress of switching devices in three power supply modes are analyzed in detail, and its performance is compared with those of the existing similar converters. Finally, an experimental prototype was built to verify its feasibility.

Owing to its advantages such as simple structure, strong robustness and good dynamic and static performances, model predictive control (MPC) has been widely applied to three-phase voltage source PWM rectifier systems. However, the PI linear regulator adopted in the voltage outer loop of MPC affects the dynamic performance of DC-side voltage. Aimed at this problem, a virtual torque impulse balance control strategy is proposed to achieve a rapid convergence of DC-side voltage through only one time of regulation. To realize this strategy, the expression of virtual torque is derived based on the mathematical model at first. Second, the virtual torque impulse balance control equation under load mutation is analyzed and established according to the fact that the DC-side output voltage will remain unchanged before and after load mutation while combining the principle of power conservation. Afterwards, the acting time of zero and forward vectors can be obtained. Finally, the virtual torque impulse balance control of the three-phase voltage source PWM rectifier system under load mutation is realized through simulations and experiments, which verifies the correctness and effectiveness of the proposed algorithm.

Aimed at the problem of wide frequency range and large circulating current with the traditional frequency-controlled LLC resonant converter in wide output voltage applications, a fixed-frequency PWM controlled hybrid bridge dual-LLC resonant converter is studied. According to the difference in the primary-side structure, the converter has three forms of topology, i.e., half-bridge-half-bridge, half-bridge-full-bridge and full-bridge-full-bridge, in which the primary-side structure is in parallel and the two transformers on the secondary-side are in series. Compared with the traditional frequency-controlled LLC converter, the three topologies always work at the resonant frequency, which reduces the switching frequency range. In addition, under the PWM control strategy, the three topologies can achieve 2, 3 and 4 times voltage gain, respectively, thereby adapting to wide voltage scenarios. At the same time, the circuit has a low circulating current loss and a good soft switching performance. Simulink simulation and experimental results verified the feasibility of the proposed scheme.