The flying capacitor clamped three-level converter has many advantages, e.g., it can reduce the voltage stress of a switch and the volume of a filter inductor. Under its operation, it is necessary to stabilize the flying capacitor voltage at half of the high-voltage side voltage, so a control strategy of adjusting the duty cycle is often used. However, this method has the problem of coupling control between flying capacitor voltage and output voltage, resulting significant fluctuations of inductance current in the process of flying capacitor voltage regulation. To solve this problem, the advantages of using the phase-shifting control strategy to realize the decoupling control of flying capacitor voltage and output volt-age are analyzed, and the corresponding control characteristics are also studied. Through the establishment of a harmonic model of flying capacitor voltage, the relationship between flying capacitor voltage and phase-shifting angle is given. A low-order harmonic function relationship is constructed, which indicates that the flying capacitor voltage is affected by the switch duty cycle D and phase-shifting angle ∆φ. The effective duty cycle interval of phase-shifting control and the duty cycle that optimizes the performance of phase-shifting control are delimited by combining with a time-domain model. A simulation model was established, and an experimental prototype with 3.6 kW was built. The control strategies of adjusting flying capacitor voltage based on phase-shifting angle and duty cycle are compared to verify the decoupling advantages and control characteristics of phase-shifting control.

To improve the capability of microgrid in coping with new energy output and load uncertainty, an optimal control strategy for microgrid considering flexible resources is proposed. According to the source-storage-load characteristics of various flexible resources, a two-layer optimal scheduling model for microgrid is established. In the user layer, user-side flexibility resources are introduced, with an optimization goal of minimizing the difference between user costs and net load and decision variables of electric vehicles and output power of translatable loads. In the source-storage layer model, flexible resources are added to the energy storage and power generation sides, with an optimization goal of minimizing the microgrid operators’ cost and load loss rate and decision variables of gas turbines, main network tie-line and output power of energy storage unit. A case study based on scenario-reduced seasonal typical daily data is simulated, and the improved MOEA/D(multi-objective evolutionary algorithm based on decomposition) algorithm is used to solve the two-layer optimal scheduling model. Results show that the average annual user cost is reduced by 6.85%, the average annual total cost of operators is reduced by 14.68%, and the average annual load loss rate is reduced by 6.65%. The results verified the correctness and effectiveness of the proposed method.

To study the conducted common-mode (CM) electromagnetic interference (EMI) characteristics of a single-switch forward converter and reduce its CM noise, the analysis of the transmission mechanism of conducted CM noise in the single-switch forward converter is necessary. On this basis, a CM noise transmission path model is established, and a calculation method is proposed to determine the specific external capacitance to reduce the CM noise. In addition, aimed at the defects of the traditional calculation model of induced charge on the secondary side, an improved calculation model is put forward, and simulation results show that the accuracy of the improved model is higher under ideal conditions. Afterwards, the balanced winding method was used to reduce the CM noise flowing through the transformer, and a prototype of single-switch forward converter power supply was used for experimental verification. Results show that the method of calculating the external capacitance was effective, and the accuracy of charge calculated by the improved calculation model was higher when the windings were close or when the number of turns per unit length was relatively large.

In an energy storage system, the current-fed dual-active-bridge converter has a large current stress and the corresponding soft-switching range is limited, which limits the converter’s efficiency and power density. To solve these problems, combined with the coupled inductor technology, a current-fed dual-active-bridge converter with a low current ripple on the energy storage side and a wide soft-switching range is proposed. Two current-fed full bridges are connected in parallel on the energy storage side, thus effectively reducing the current stress of switches therein. By adjusting the phase shift angle between the two parallel full bridges on the energy storage side, the current ripple is reduced. By reasonably designing the coupling filter inductance, the obtained mutual inductance current is large enough to satisfy the soft-switching conditions for switches. The working principle and steady-state analysis of the converter were given in detail, and a 400 W experimental prototype was designed to verify the superiority and feasibility of the proposed converter.

To ensure the motor drive performance while saving cost in the field of electric industrial vehicles, low-precision encoders are often adopted. Although these encoders can measure the rotor’s accurate mechanical position, they introduce a long delay and large errors to the measured speed information. Therefore, the traditional load torque observers cannot obtain the accurate load torque information, and when the inaccurate information is used as feedforward of the current loop, the motor speed fluctuation cannot be effectively suppressed. To solve this problem, a second-order sliding-mode load torque observer based on a low-precision encoder is proposed, which can obtain the accurate load torque information based on the rotor position information and thus improve the anti-interference performance of the system. Finally, the correctness and effectiveness of the proposed method was verified by simulation and experimental results.

The accurate estimation of the state-of-charge (SOC) and state-of-health (SOH) of lithium-ion batteries is always a key scientific prob-lem that needs to be solved urgently. In this paper, based on a second-order fractional-order equivalent circuit model, the state space equation of a lithium-ion battery is established, and the discretization expressions of fractional-order differential and integral equations of battery parameters and SOC are derived. Then, a dual fractional-order extended Kalman filter method is studied to estimate the equivalent circuit parameters, SOC and battery capacity simultaneously. In addition, a time weighting sequence method based on estimated SOC and battery capacity is proposed, different discharge currents and cumulative time are monitored, and the available capacity of the battery is calculated online, thus achieving real-time estimation of the SOH of the battery at any discharge depth and any discharge rate. Finally, under the conditions of dynamic stress test, three lithium iron phosphate batteries of the same manufacturer, the same model and different aging degrees were used for experimental verification.

A fast and accurate estimation of the state-of-charge (SOC) of lithium batteries is critical for the battery management system. Aimed at the problem that the Kalman filter algorithm lacks reasonable constraints on the resistance-capacitance (RC) parameters when estimating the SOC of lithium batteries, an optimization method of RC parameters filtering is proposed, and it is combined with unscented Kalman filter (UKF) to achieve the fast and accurate convergence of lithium battery SOC estimation. First, an equivalent circuit model of lithium battery is established by combing the polynomial equation. Then, forgetting factor recursive least squares is used to obtain the time-varying and time-invariant model RC parameters. The expression of RC parameters filtering relationship is established by setting the Kalman gain threshold, and an RC optimization UKF algorithm is proposed for lithium battery SOC estimation. Finally, hybrid pulse-power characteristic experiment, intermittent constant-current discharge experiment and dynamic stress test experiment were designed to verify the convergence and robustness of the proposed algorithm. The maximum estimation error of SOC was less than 1.0%, and the reference range of gain threshold was also given.

To improve the accuracy and efficiency of diagnosis when a converter fails, an active current limiting method is applied to realize the converter fault diagnosis in a power system. Active current limiting control is used to limit the output DC current from the converter to 1.2 times of rated current and limit the fault current, thus improving the stability of fault diagnosis. Based on a prediction model, the fault current distribution characteristics of the converter in the power system are diagnosed, and the bridge arm current is taken as the diagnosis parameter. The difference between the measured bridge arm current and predicted value is compared. If the difference is greater than the threshold value, it is judged that the converter has a fault. Experimental results show that the proposed method had a high accuracy and a high diagnosis efficiency in diagnosing the converter faults in an experimental power system, and the rates of false diagnosis and missed diagnosis were low, indicating that the converter diagnosis effect was satisfying.

The control system for hybrid distributed energy storage virtual synchronous generator (VSG) composed of a battery and a supercapacitor is improved. A principle for the power allocation of hybrid energy storage is proposed, and a frequency division sliding filter method is designed according to different frequency bands. In view of the power fluctuations of different frequencies, the virtual moment of inertia is piecewise improved to achieve the coordination between the battery and the supercapacitor. Aimed that the problem that the traditional VSG cannot suppress the frequency oscillations, the virtual damping coefficient is modified, and adaptive virtual damping is used to improve the regulation capability of the control system when the frequency oscillations occur. MATLAB is used to verify the proposed control strategy through simulations. Results show that the hybrid energy storage VSG can be controlled in terms of frequency, i.e., when the load fluctuates irregularly, the supercapacitor responds to the high-frequency power fluctuation in time while the battery suppresses the low-frequency power, thus realizing the coordination between the battery and the supercapacitor. When faced with a sudden decrease or increase of 10 kW load, adaptive virtual damping can be used to deal with the frequency oscillations of active output caused by load power fluctuations of hybrid energy storage, and the frequency overshoot is controlled within 0.06 Hz. As a result, the proposed control strategy can adjust the small deviation of frequency regardless of the sudden increase or decrease of power.

The switching speed and switching frequency of converters keep increasing, and higher requirements are also imposed on the DC-side decoupling capacitors. To solve the problems of overvoltage spikes and decoupling capacitor losses caused by voltage and current oscillations during the switch-off process, a transient circuit model considering the system’s stray parameters is established, and the evolution of overvoltage and decoupling capacitor current oscillation is analyzed. On this basis, a loss model considering the parasitic parameters of the main circuit and the equivalent series resistance of the decoupling capacitor is proposed. The limiting factors for the selection of decoupling capacitors in practical engineering are quantitatively analyzed, and an optimal selection method for the decoupling capacitance and loss limit condition is obtained. Finally, the proposed model and analysis method were verified by simulation and experimental results.