With the increasing penetration of renewable energy, the integration of power electronic equipment has fundamentally re-shaped the dynamic characteristics of modern power grids. Due to the lack of support from the main grid, islanded microgrids (MGs) are prone to losing synchronization stability under large signal disturbances. Existing stability studies often focus on single-inverter systems, which have limited performance in multi-inverter scenarios due to the extended computational burden. Therefore, this paper proposes a method for evaluating the large signal stability of MGs composed of grid-forming (GFM) inverters based on the networked oscillator model. Firstly, the equivalent oscillator model of the GFM inverter is established to accurately characterize both the inherent and interactive dynamics of a single GFM inverter, thereby enabling the construction of a networked oscillator model for islanded MGs with a general topological structure. The large signal stability analysis of the system is then carried out analytically, and the frequency stability domain is explicitly derived. Finally, the effectiveness of the proposed method is verified through time-domain simulation and Controller Hardware-in-the-Loop (C-HIL) experiments.

Virtual Power Plants (VPPs) have gained prominence as an effective approach to enhance renewable energy utilization and optimize power market mechanisms in recent years. To address the inherent uncertainties of renewable energy generation and improve the economic performance of VPPs in electricity markets, this paper proposes a two-stage economic dispatch model that explicitly incorporates renewable energy output forecasting errors. The day-ahead stage employs a data-driven chance-constrained approach to handle renewable uncertainties, ensuring reliable day-ahead scheduling. The real-time stage compensates for deviations between actual and scheduled generation outputs. The proposed coordinated two-stage optimization achieves optimal day-ahead bidding strategies that enhance VPP profitability and reduce real-time power deviations, as validated through case studies.

Capacity configuration optimization is one of the primary tasks in the construction of the integrated energy system (IES). the uncertainties of renewable energy sources and loads deepen the coupling relationship between the capacity configuration and energy dispatching of IES, which makes optimizing the capacity difficult. This paper proposes a two stage GA-MILP-based capacity sizing allocation method for off- grid IES. Firstly, a double-layer capacity configuration framework based on Leader-Follower is constructed. Secondly, the genetic algorithm (GA) is used to randomly generate the initial configuration in the Leader layer and use it as the input of the Follower layer. In the Follower layer, the system investment cost, operation cost, and maintenance cost are comprehensively considered, the mixed integer linear programming (MILP) method is used to obtain the minimum operating cost and energy dispatching scheme and then return to the Leader layer. The optimal capacity configuration scheme is obtained through multiple iterative optimizations. Finally, the proposed method is applied to an Off-grid island to confirm the rationality and effectiveness of the optimization results.

Distributed electric propulsion (DEP) has been proven to be the next-generation propulsion technology for full-electric aircraft and all-electric aircraft. To take advantage of the redundancy of the DEP system, the distributed control method and its related performance have been extensively studied. However, due to the characteristics of the distributed structure, faults of a single agent could propagate through the communication links, making the whole system fail. This paper proposes a fault-tolerant control method to stabilize the DEP system when an inverter single-phase open-circuit fault occurs. The proposed method adopts a distributed structure and could effectively depress the fluctuation of the rotation speed of each thruster without additional requirements for the increase in hardware amount and computational performance. Controller-hardware-in-the-loop (C-HIL) experiments have been conducted, and the corresponding results validate the effectiveness of the proposed control method.

Mismatch faults of photovoltaic (PV) modules causing by partial shading in series PV system will lead to a serious drop in power generation. Unless the full power processing converters handling all the generated power, the differential power processing converters only deals with the mismatched power between PV modules, thus, differential power processing (DPP) converters usually have low power loss, high efficiency and relatively low cost. Nevertheless, a DPP converter is usually an additional device to the existing PV system and will introduce extra power losses and expense. In this paper, a single stage boosting inverter integrated with a multi-winding type DPP converter is proposed. The functions of voltage step-up, inversion and power equalization are achieved in one power stage. The operating principle and control method of the proposed topology is described in detail. The feasibility of the topology is verified by simulation with a 17.13% and 66.99% power increment under two different partial shading conditions and good quality sinusoidal output.

There are many disturbances and uncertainties in the DC microgrid system. Therefore, it is required that the converter control strategy has strong robustness. Active disturbance rejection control (ADRC) has been proven to be a very effective method. However, the rejection of time-varying disturbance by traditional ADRC needs to be improved. To this end, first, a universal expression for the output characteristics of ADRC with different disturbance observers is provided in this paper, which facilitates the comparison of performance between ADRCs. Then two kinds of ADRCs based on higher-order extended state observer (HESO) and cascaded extended state observer (CESO) are studied to improve the disturbance rejection characteristics of the converter. Finally, the effectiveness of the proposed controller is verified by the simulation results.

For the fuel cell/battery UAV hybrid power system, an energy management strategy(EMS) based on fuzzy logic control(FLC) is proposed in this paper, which is optimized to reduce the system's hydrogen consumption, maintain the state of charge(SOC) of lithium battery, and stabilize the bus voltage. In order to verify the effectiveness of the EMS, a fuel cell UAV hardware experimental platform is built and a finite state machine(FSM) strategy is designed for comparison. Experimental comparison results verify the effectiveness of the proposed fuzzy logic control strategy in stabilizing the bus voltage, maintaining the SOC of the lithium battery, and improving the system fuel economy.

The mismatch of module characteristics due to partial shading can lead to serious power loss in series-connected photovoltaic (PV) systems. Various differential power processing (DPP) converters have been employed to improve the generated energy during partial shading conditions (PSCs). However, conventional DPP converters have poor scalability, low balancing efficiency and high cost for PV substring-level applications. This paper proposes a modified switched-capacitor converter (SCC)-based DPP converter for substring-level PV application. The proposed converter has reduced components and therefore has the advantages of compact size, low cost and simple control, which can be easily integrated into the junction box of PV panels. The proposed architecture inherits the benefits of conventional SCC-based DPP topologies, allowing the PV system to be easily extended without the usage of bulky transformers. Simulation results show that the proposed architecture can significantly enhance power generation in complicated PSCs. Compared with existing state-of-the-art SCC-based DPP converters, the proposed architecture can achieve comparable balancing performance with reduced components.

In this paper, a real-time Energy Management Strategy (EMS) based on Particle Swarm Optimization (PSO) and virtual inductor is proposed for hybrid electric Unmanned Aerial Vehicle (UAV) powered by fuel cells and lithium batteries. For comparative analysis, EMS-based Finite-State Machine (FSM) and Dynamic Programming (DP) are also designed in this paper. Though simulating on MATLAB, the results demonstrate that the proposed EMS can effectively reduce the hydrogen consumption of the system, thereby improving fuel economy. Additionally, the EMS smooths the output power of the fuel cell with the aid of the virtual inductor.

This paper proposes a novel motor synchronization method for unmanned aerial vehicles with distributed electric propulsion system (DEP-UAV). Compared with conventional aircraft with a single motor, propeller management in DEP-UAV is more delicate and represents unique challenges. Specifically, motors with asynchronous rotating speed would generate asymmetric thrusts along the DEP-UAV, which could result in undesired moment imbalance on the aircraft. A model-based distributed control algorithm is developed, which synchronizes the rotating speed of multiple motors to the desired value. The proposed method runs on a sparse communication network, which avoids the system's single-point-of-failure; additionally, the control gains are customized regarding each motor's mechanical characteristics, which ensures the system's dynamic performance without introducing excessive computational cost. The convergence of the proposed method has been analytically proved and its dynamic performance has been validated using a Controller Hardware-in-the-Loop (C-HIL) testbed for DEP-UAV application.

Energy Management Strategy (EMS) is a crucial part of More-Electric Aircraft (MEA) and aims at improving the efficiency of whole hybrid energy system. In this paper, fuzzy neural network trained by dynamic programming (FNDP) is proposed to solve the problem that dynamic programming (DP) cannot be used online. FNDP can obtain the optimal distribution scheme using DP and extract the rule from the data through fuzzy neural network (FNN). Compared to fuzzy control strategy based on power follow (PFF) in two different load profiles, it can be found that FNDP can attain a satisfied rule without manual setting and have a better performance than PFF.

This paper proposed an energy management strategy (EMS) based on genetic algorithm (GA) for a hybrid energy system consisting of photovoltaic array (PV), fuel cell, electrolyzer, hydrogen storage system and battery. Considering the economy of the system, the equivalent hydrogen consumption of the system is the main part of the objective function, and the fluctuation of fuel cell output power is employed as an auxiliary part. The simulation is implemented in the MATLAB environment. After verification, the light abandon rates of the system under two different conditions are 0.000557% and 1.38%, respectively, which proves the effectiveness and adaptability of the proposed strategy.

In this paper, a FC/Bat-based on-board DC microgrid is adopted. The FC provides the average power demand, and the battery provides the instantaneous increased power and absorbs the feedback power through virtual inductance and resistor droop control. Furthermore, the state of charge of the battery is take into consideration. The reference voltage of the battery unit Vrefis adjusted by ΔV, which achieves the control of the charge and discharge current and maintains the stability of the battery SOC. Afterwards, analyze the large signal stability of the FC/Bat-based on-board DC microgrid based on the mixed potential theory. Then the large signal stability criterion is obtained. It is verified by simulation that the virtual resistance and inductance droop control can realize the power distribution and the large-signal stability criterion is correct.

In this paper, the hybrid power system of fuel cell Unmanned Aerial Vehicle (UAV) is established on the platform of Matlab/Simulink whose system architecture is fuel cell with lithium battery, and the overall scheme of the system is designed. In addition, the required power curves under two typical working conditions are obtained by establishing the aircraft dynamics model. An optimization energy management strategy based on dynamic programming is designed to achieve the least hydrogen consumption. For comparison, another two energy management strategies are designed under the same working condition. Finally, it is proved that dynamic programming has optimal fuel economy than the other two strategies. Moreover, each strategy has its own characteristics, which provides suggestions for selection of energy management strategies under different objectives.

In order to mitigate the environmental pollution problem, the fuel cell electric vehicle (FCEV), as one kind of renewable energy industry, is researched and developed. The performance of FCEV is deeply relied on the energy management strategy (EMS), an inappropriate EMS may cause the bad performance of FCEV. Strategies designed under specific work condition have poor adaptability to complex work conditions. What’s more, these strategies give little concern on the volatility of fuel cell’s output power, which will cause a loss of fuel cell’s life. Aiming at decreasing the hydrogen consumption of FCEV and the volatility of the output power of fuel cell, an optimized fuzzy logic control energy management strategy based on work condition recognition is proposed. In order to achieve a better performance, this strategy can recognize instant driving condition, and pick the corresponding parameters of fuzzy logic control system from the preset database of the parameters. The database is obtained by offline optimization with genetic algorithm. A simulation result based on the MATLAB/Simulink platform is obtained to demonstrate that this strategy has a better performance than a conventional fuzzy logic controller with fixed parameters under mixed work conditions.

This paper presents an observer based power switch open-circuit fault diagnosis method for a two-phase interleaved boost converter (IBC). Motivated by the simplicity and robustness of immersion and invariant (I&I) theory, I&I observers are adopted for residual generation. The inductor current and output voltage used in controllers are selected for input voltage estimation, which avoids the use of extra sensors. Furtherly, to eliminate the unexpected effects, which are caused by parameter uncertainty, an adaptive threshold is designed. The simulation results obtained under different operation situations have demonstrated that the preselected threshold has a strong robustness against internal and external disturbances with no false alarms. What' more, the simulation results also show that the switch open-circuit diagnosis is equal to one switch period under various conditions. Thus, the effectiveness of the proposed diagnosis method is validated rigorously.

Based on differential geometry theory, a nonlinear PI and global finite-time controller (PI+FTC) under exact feedback linearization (EFL) is proposed in this paper. Firstly, the coordinate transformation equation is derived by the affine nonlinear model of the buck converter, and the Brunovsky canonical form of the buck converter is obtained. Then, according to the canonical form, PI+FTC is designed. Furthermore, the Lyapunov stability principle is applied to prove that the control strategy is stable. Finally, the results of simulation and experiment indicate that the proposed method has a shorter setting time and stronger robustness than the linear PI controller when the input voltage and load are disturbed. The proposed control strategy realizes time optimal control and is also applicable for the stabilization of other dc-dc converters.

Li-ion batteries as a source of energy in electric vehicles (EV) and hybrid electric vehicles (HEV) are receiving more attention with the worldwide demand for energy conservation and environmental protection. In this paper, an improved State-of-Charge (SOC) co-estimation algorithm based on the second-order RC equivalent circuit model is proposed. Firstly, Forgetting Factor Recursive Least Squares (FFRLS) algorithm is adopted to realize on-line parameter identification of the model. Secondly, SOC is estimated with identified parameters by adaptive extended Kalman filter carrier tracking (AEKF) algorithm based on innovations and residuals. The results of two discharge experiments in different conditions show that the co-estimation algorithm has a higher estimation accuracy, convergence speed and robustness compared with off-line AEKF SOC estimation algorithm, which is more suitable for on-line estimation of electric vehicle SOC.

Nowadays distribution power systems are used in different applications such as aircraft, ships, submarines and hybrid electric vehicles. However, the interaction between individually designed power subsystems may cause instability. Moreover, in these applications, the constant power load (CPL) also poses challenges for system dynamic response and stability. Thus, the main objective is to stabilize the cascaded system supplying the CPL. An interconnection and damping assignment (IDA) passivity-based control (PBC) scheme for LC filter cascaded with buck converter supplying CPL is proposed. The plant is described by port-controlled Hamiltonian (PCH) form. Particularly, an adaptive interconnection matrix is developed to achieve internal links in PCH system. A modified IDA-PBC and its proof are presented to perfect the implementation for the CPL application. Simulation results are given to illustrate the effectiveness of the proposed approach.

In order to reduce the complexity of the high-frequency AC power supply of the wireless power transfer (WPT) system in small and medium power applications, the class D amplifier is adopted in this paper. The class D amplifier, which has fewer components than traditional full-bridge and half-bridge inverter, simplifies the structure of the WPT system and can realize the zero-voltage turn-on of MOSFETs. Meantime, a primary-sided CLC compensation network is proposed to achieve load-independent constant voltage output of the WPT system. The analysis and design procedure for the WPT system are provided and a prototype is built. Simulation results validate the load-independent voltage output characteristic of the circuit topology. Experiment is executed at a transfer distance of 10cm and the results show that when the load resistor changes by 233 % from 15Ω to 50Ω, the output voltage only fluctuates by 2.6V from 33.2V to 35.8V. The fluctuation rate is only 7.8%, which indicates that the output voltage of the WPT system is robust to the load variation. With a load resistor of 25Ω, the experimental prototype reaches a dc-dc efficiency of 87.57% at 48.16-W output power.

This paper presents a systematic derivation of a small signal model of current-fed half bridge isolated dc/dc converter for the hybrid electric vehicle based on the lithium battery and fuel cell. The reflected output voltage across the power semiconductor devices can naturally be clamped at Vo/n by a secondary-modulation strategy without any additional circuit, which can reduce footprints and cost. Moreover, the soft switch of all can be achieved resulting in low switching losses and higher efficiency due to ZCS/ZVS. In order to maintain the constant bus voltage and the balanced two-way inductor current, a small signal model using state-space averaging technique is deduced and the dual closed loop controller is designed in detail. The co-simulation of PSIM and MATLAB/SIMULINK is used to verify the effectiveness of the controller when the load step-changes in case of the different input voltage.

A novel control scheme for two phases floating interleaved boost DC-DC converter (FIBC) is presented in this paper. The proposed controller is based on second order sliding mode method combined with an extend state observer (ESO), which comprises two loops: the outer loop is a voltage regulation loop whereas the inner loop is an instantaneous current regulation loop. The outer loop is accomplished by SOSM and ESO, which aims to regulate the output voltage of the converter and reject the disturbance of the load variations. The SOSM strategy is also applied to inner loop to make the current track its reference accurately. Through the proposed approach, the system can obtain a stronger robustness, and the chattering problem is also suppressed. Both theoretical analysis and simulation results are demonstrated. Moreover, in order to verify the effectiveness of the proposed control scheme, comparisons with dual loops super-twisting control scheme (ST + ST) and outer active disturbance reject control plus inner super-twisting control scheme (ADRC + ST) in case of parameter uncertainties and loads disturbances have been made in this paper.

As an important part of multiple-function and intelligent single-phase grid-connected Photovoltaic (PV) system, fault ride-through (FRT) has attracted extensive attention in the recent years. According to the continuously updated grid-connected requirements, the inverters should remain connected with grid under grid faults even the grid voltage dips to zero, and provide reactive current injection to support the grid recovery. In this paper, a contrastive evaluation of two intuitive and simple flexible power control methods, which are implemented in two different reference frame, are presented in the case of zero-voltage ride-through (ZVRT) operation. Only the dq-rotating reference frame power control method provides an acceptable ability of ZVRT. In addition, the performance is verified in both the simulation and experiment results.

An effective optimization of proportional integral observer for SOC estimation of lithium ion batteries is done in order to get a very high accuracy. During experimentation, a negligible error band of just 0.6% was found which is the quite high efficiency yet reported in the research area of state of charge estimation of Li-ion batteries. The worth mentioning improvements covered in this paper are the variable selection of value of coulombic efficiency instead of constant one to minimize the error, intelligent identification of parameters for more accurate modeling of nature of Li-ion battery, and non-linear gain scheduling for SOC and open circuit voltage relationship to boost the efficiency. Firstly, the simple PI observer is implemented and tested; then, after specific optimization and improvement, the optimized proportional integral observer is designed. The real time calculated data of Li-ion battery is used to compare the results, and to verify the high efficiency and robustness of proposed design. The most prominent features of new optimized PI observer include the very high efficiency, enhanced robustness and an immediate estimation of current SOC without any requirements of initial value of SOC.

Owing to the energy shortage and the increasingly serious environmental pollution, fuel cell electric vehicles (FCEV) with zero-emission and high-efficiency have been expected to be the most potential candidate to substitute the conventional vehicles. The DC/DC converter is the interface between the fuel cell (FC) and the driveline of FCEV. It not only needs high voltage gain to convert the wide FC voltage into an appropriate voltage level, but also needs the capacity of fault tolerance to enhance the reliability of the system. For this reason, floating interleaved boost converters (FIBC) seem to be the optimal selection. Despite this topology can continue operating without interruption under the action of the proper control scheme in the case of power switch open circuit fault (OCF), operating in degraded mode has adverse impacts on the component stress and the input current ripple. Hence, this paper aims to design an effective controller to maintain the dc bus voltage constant and to demonstrate thorough theoretical analysis and simulation verification of these undesirable effects.

It is well know that the interaction between poorly damped LC input filter with dc-dc converter lead to degradation of dynamic performance and fault scenario of the system. This problem also often occurs in fuel cell systems. Due to the relatively low and unregulated output voltage, the high gain boost converter is need in such application. A floating interleaved boost converter (FIBC) is selected as a good candidate to achieve this desired effect. In order to ensure the system stability, this paper addresses a method which permits to design a fault-tolerant stabilizing system for the proposed converter and the filter. It consists in implementing an active stabilizer for each switch. Afterward, a method to design fault-tolerant stabilizing system is developed. The simulation results are reported to verify the effectiveness of the proposed method.

In the DC distributed power system of the more electric aircraft (MEA), it is necessary to have a LC filter in the input of boost converter due to electromagnetic interference (EMI) and sharp input impulse voltage. Whereas, the interaction between boost converter and poorly damping filter may cause instability throughout the system., The problem may be solved by adding resistor or increasing capacitance, but it also increases the power consumption, volume and weight. However, the volume and weight are important performance indexes in the MEA. In this paper, we will introduce a virtual capacitor to solve the above problem without extra volume and weight. Firstly, the closed-loop control parameters of boost converter are designed by SISOTOOL of MATLAB. Then, the model, which is used to analyze the stability of cascade system with LC filter, is derived based on the Takagi-Sugeno (TS) fuzzy theory, and then a public Lyapunov function is found by (linear matrix inequation) LMI tool of MATLAB to estimate the stability of the system. Finally, the simulation results confirm the validity of the proposed stability analysis and control method.

The electric vehicle technology has been adopting PEM fuel cells for hybrid applications over the past decades. Fuel cell systems are often low voltage systems. The key requirements of a boost converter for such application are need of high-voltage. The second-order low-pass filter is often used to filter the high frequency current ripple. It is known that the interaction between the poorly damped filter with the converter leads to degradation of dynamic performance and instability of the system. This paper addresses a novel wide stability control strategy to solve this problem without increasing the weight and size. In this paper, the mathematical model of the system is built. The dynamic stability of the system is investigated based on root locus and Lyapunov first method. The simulation results are reported to verify the effectiveness of the proposed method.

This paper presents a novel fault diagnosis approach for three-phase full-bridge inverter, which is the most popular used in the brushless DC motor (BLDCM) system and the permanent magnet synchronous motor (PMSM) system. The short or open circuit fault diagnosis of the six power switches of the inverter is accomplished by only four simple resistor divider networks and one sampling resistor. By comparing the divided voltages with the reference voltage, the faults are detected and identified under a set of special judgment rules. The proposed method is designed to be used before system running. Compared with the existed methods, the proposed approach works with only weak current passing, which is more safe. Finally, the effectiveness is verified by simulation.

This paper aims to focus on the smooth output of Buck converters under the input perturbations and load disturbances using the high-order sliding mode controller with a differentiator (HOSMD) based on the only measurement of output voltage. Theoretical analysis and design procedures of the controller designed by prescribed control law, one of the high-order sliding modes, are presented in detail. As well as the differentiator with the super-twisting. Comparison of numerical simulation results between traditional sliding mode control (SMC) and HOSMD under steady state, input voltage perturbations, output load disturbances have been presented. And it validates the effectiveness and robustness of the method proposed in this paper, which would reduce the hard-ware cost and increase the superiority.

In the process of power generation by hydrogen energy, the application of fuel cell has been used widely. As we all known, it often appears that the randomness of hydrogen, oxygen input and power output load, which puts forward higher requirements for the robust design of power converters. The power converter based on traditional sliding mode due to its discrete control law exist inevitable chattering phenomenon. In order to conquer the serious problem, this paper presents a novel avoidance chattering Flyback converter based on the super-twisting sliding modes. To remove the intermittent disturbance in the new energy power generation, especially in fuel cell system, this paper compare the effect of the converter controlled by super-twisting sliding mode controller with the classic PI controller in a Flyback converter as an example. The simulation results show that: Under the condition of large disturbances in input and output, the converter controlled by super-twisting sliding mode has stronger robustness.

This paper presents hardware-in-the-loop (HIL) validation of an air supply method for the fuel cell in automotive applications. A 12 kW proton exchange membrane fuel cell (PEMFC) model is developed and implemented in dSPACE. The performances of the fuel cell stack and compressor during a classic European Driving Cycle are tested. The experimental results show that the compressor consumes up to 25 % of the fuel cell generated power in the worst operating point, whereas only 4.2 % on average.