Along with the widespread applications of lithium batteries in industry and daily life, the efficiency and speed under balanced charging strategies for lithium battery packs have become increasingly important. A modular cell-to-pack-to-cell(CPC) balanced charging system is constructed to solve the problem of fast equalization charging for lithium battery packs. First, the equalization system is modularized, and the equalization circuits within and between modules are established. Then, an optimization strategy for balanced charging is proposed, under which the proposed model is solved hierarchically, i.e., the charging time is calculated using the binary method in the top layer, and the charging current is optimized using the gradient descent method in the bottom layer. Finally, through a comparison with the charging time, equalization time, cell terminal voltage and equalizer voltage under the non-modular balanced charging strategy, the feasibility and effectiveness of the proposed strategy are verified.

The lithium-ion battery equalizer based on switched inductor is still of strong practical value in low-power portable electrical equipment. However, the switching devices in the equalizer operate in a hard-switching state under traditional control strategies. A soft-switching implementation algorithm for battery equalizer based on switched inductor in continuous current mode is proposed. The determinants of the inductor current of the equalizer and the charging and discharging current of a battery cell are analyzed. Then, a soft-switching implementation algorithm for the switching devices in the equalizer is proposed, and its control accuracy is analyzed. The equivalent impedance and open-circuit voltage of the battery cell can be obtained in real time by detecting the change rate of battery cell voltage and charging current, which further ensures the accuracy of the algorithm. Experimental results show that the proposed soft-switching control algorithm has a good performance.

Virtual DC motor(VDCM) control has been widely applied in suppressing the power fluctuations of DC microgrid and improving the voltage stability of DC bus. Due to the randomness and uncertainty of distributed generations in microgrid, as well as the load switching in microgrid, the DC bus voltage will fluctuate greatly. To improve the regulation capability of bus voltage, a virtual energy storage control strategy based on the coordination of VDCM control and controllable load is proposed by using the regulation capability of controllable load and the virtual motor control of load converter. By adjusting the angular speed of the virtual motor, the power consumption of the controllable load can be adjusted to compensate the fluctuation of bus power and improve the stability of bus voltage. In addition, the relationship between the rotational kinetic energy of VDCM and the charging and discharging energy of the DC capacitor is established. Finally, a simulation model is built on the MATLAB/Simulink platform to verify the effectiveness of the proposed control strategy.

To improve the state-of-charge(SOC) prediction accuracy of lithium battery, a prediction method based on the fusion model of Attention mechanism and convolution neural network-long short-term memory(CNN-LSTM) is proposed. This model uses one-dimensional CNN and LSTM neural network to learn the nonlinear relationship between SOC and lithium battery discharge data, as well as the long-term dependence existing in SOC sequences. At the same time, it adopts a "many-to-one" structure and establishes a mapping relationship between the SOC at the present moment and the discharge data at multiple historical moments, and pays attention to the historical discharge data which has a greater influence on the SOC at the present moment through the Attention mechanism, thus further improving the SOC prediction accuracy. The SOC prediction experiments under dynamic conditions show that the average prediction error of the proposed method is 0.89% under different temperature conditions, which is 81.2%, 66.7% and 56.5% lower than those of SVM, GRU and XGBoost algorithms, respectively. In addition, this method is also superior to LSTM and CNN-LSTM models that do not combine the Attention mechanism, showing a higher prediction accuracy and higher application values.

Since lithium-ion batteries have been widely applied in energy storage systems and electric vehicles, the accurate estimation of their state-of-health(SOH) is a necessary condition for ensuring the reliable and safe operation of the system. SOH is analyzed from the perspective of capacity, with seven health indicators which are extracted from the constant current-constant voltage charging voltage and temperature curves as input. Based on the data-driven method, a sparrow search algorithm-back propagation neural network(SSA-BPNN) SOH estimation method for lithium-ion batteries is proposed, and data enhancement is applied to further improve the model's robustness. Finally, this method is verified on the NASA Randomized Battery Usage Dataset. Compared with the traditional BP neural network without data enhancement, the SOH estimation accuracy of the proposed method is significantly improved. The maximum absolute error and root mean square error of SOH estimation on the test set are less than 3% and 1.32%, respectively. Experimental results show that this method has advantages of small error, fast convergence, global search capability and adaptation to different characteristics of battery aging.

The adjustment of energy structure is an important issue for China's energy development in the 21st century, in which the development of renewable new energy is an important means to optimize the energy structure and reduce environmental pollution. Nowadays, lithium-based batteries are still the main devices that can achieve reversible storage of renewable energy, whose electrochemical performance is often affected under harsh environmental conditions such as different temperatures, mechanical stress and humidity. As a result, problems including the damage of battery components, capacity fading, short-circuit explosion, and thermal runaway will occur. The failure mechanism of lithium-based batteries under harsh environmental conditions is systematically analyzed. Then, the main methods for improving their electrochemical and safety performance are reviewed. Finally, the urgent problems to be solved are summarized. This paper provides ideas for the failure mechanism research on lithium-based batteries as well as the development and applications under harsh environmental conditions.

With the development of industrial demand, higher requirements are put forward for the reliability of power transistors. The real-time measurement of device junction temperature can ensure the normal operation of the device, so it is very important. Through the research on the on-line measurement method for turn-on delay time, a measurement circuit is designed. By measuring the turn-on delay time at different junction temperatures, the relationship between them is established, the on-line measurement of device junction temperature is realized by measuring the turn-on delay time under actual working conditions, and the device junction temperature is deduced. The results measured using the proposed method are similar to those obtained by an infrared temperature gun. In this way, an on-line measurement method for MOSFET junction temperature based on turn-on delay time is proposed, providing a new idea for the on-line measurement of junction temperature in the future.

In the case of high switching frequency, the bridge arm crosstalk caused by the parasitic parameters of SiC MOSFET in the traditional drive are more serious. However, most of the existing crosstalk suppression drive circuits suppress the crosstalk at the expense of increasing the switching loss, prolonging the switching delay and adding the control complexity. Therefore, based on the idea of reducing the impedance of the drive loop in the process of crosstalk generation, a novel active Miller clamp gate drive design is proposed by adding PNP triodes connected in series with diodes and capacitors between the gate and source, and its working principle is analyzed. The parallel capacitance parameters of the improved drive circuit are also calculated and designed. Finally, an experimental platform of double-pulse test for a synchronous Buck converter with DC bus voltage of 300 V was built, and the novel crosstalk suppression drive circuit was compared with the traditional and typical crosstalk suppression circuits in terms of the positive and negative crosstalk voltage spike suppression effects and the turn-on and turn-off speeds. Experimental results show that compared with those of the traditional and typical crosstalk suppression circuits, the positive and negative voltage spikes of the proposed crosstalk suppression drive circuit were reduced by 80% and 40%, respectively, and the switching delay of the device was reduced by 32% in the meantime.

The stability of an urban rail transit traction power supply system is related to the safety of urban power grid and the stable operation of traffic. Due to the large amounts of cables and a series of power electronic devices which have been put into use, problems such as harmonics and reactive power will arise and seriously damage the safety of the traction power supply system. As the core equipment of the traction power supply system, the traction transformer has important functions such as transmitting power supply and filtering nonlinear load harmonics. DC bias is a widespread phenomenon adversely affecting the traction transformer, and it may directly threaten the safe and stable operation of the traction transformer. Based on PSCAD/EMTDC and ANSYS, the UMEC model and finite element model of a novel traction transformer are established, respectively. By means of multi-platform hybrid simulation, the electromagnetic, loss and other excitation characteristics of this traction transformer under DC bias are observed and analyzed. With a comparison with the traditional traction transformer, the excitation situation of the novel traction transformer under DC bias is evaluated.

Since there is only one working mode of continuous wave or pulse after the design of a traditional spaceborne travelling wave tube(TWT) amplifier is finished and the output power at the saturated working point is fixed, a novel design scheme for space TWT power supply is proposed, which is compatible with multiple working modes including continuous wave and pulse. The TWT power supply and multi-mode TWT designed through this scheme are integrated into a multi-mode TWT amplifier, which have functions of continuous wave mode, low repetition rate pulse mode, high repetition rate pulse mode and adjustable on-orbit power. As a result, it can be applied to communication, navigation, data transmission and remote sensing observation satellites, thus making the on-orbit reconfigurable load possible. Through a simulation test, it is found that the power efficiency of the multi-mode space TWT reaches 94%, the repetition frequency range covers the continuous wave up to 10 kHz, and the adjustable output power ranges between 47 and 53 dBm.