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. Results show 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 °C. When the flight altitude is 8 km (80 kPa, 10 °C), 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 °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.