In an energy storage system, the voltage level on the DC bus side is usually higher, while the voltage level on the battery side is lower with a wide variation range. Under this background, a three-level bidirectional full-bridge multi-resonant DC-DC converter topology is proposed, in which a three-level structure is adopted on the high-voltage side to reduce the voltage stress of the switch. The resonant cavity is designed as an LLCLC multi-resonant structure with auxiliary inductance, so that the left and right sides of the equivalent circuit is symmetrical, thus realizing the peer-to-peer driving control of forward and reverse operations and the bidirectional transmission of power. An improved synchronous pulse-frequency-modulation control strategy is adopted, so that the full-range zero-voltage-switch can be realized for switches on the high- and low-voltage side regardless of the forward or reverse operation. Compared with the traditional LLC resonant topologies, the proposed topology can achieve a wider range of voltage gain in a narrower frequency range. Through the optimization design of resonant cavity parameters, the converter can transmit the current fundamental wave and third harmonic power at the same time, thereby improving the energy transmission efficiency. Finally, a 2 kW experimental prototype was built, and experimental results verified the theoretical analysis.

In the traditional power module automatic layout optimization algorithm, the electrical evaluation is inefficient and takes up a lot of computing time. To solve this problem, lattice Boltzmann method (LBM) is used to replace the traditional evaluation method. Since LBM does not need to solve multiple invertible matrices, it can quickly judge the rationality of electrical interconnection and calculate the voltage/current. With the program of automatic layout design based on the genetic algorithm, an evaluation method of two-dimensional layout is established by using a D2Q4 lattice type, and the accuracy of the evaluation result under the layout scheme is verified by ANSYS Q3D software simulation. A comparative test was conducted in Python 3.10, and results show that LBM reduces the total time of scheme evaluation by 75.4% on average. Moreover, the more the number of loops in the evaluation scheme, the greater the computing advantage of LBM.

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.

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.

To solve the problem of performance degradation in automotive lithium-ion batteries at low temperatures, 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 °C to above 0 °C within 403 s without permanently damaging the battery life.

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.

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.

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.

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.

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%.