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.

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.

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%.

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.

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.

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.

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.

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.

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.

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.