In this paper, a robust voltage control is designed for a floating interleaved boost converter with high voltage gain. The proposed controller has an inner loop based on super-twisting sliding mode algorithm, who has continuous control signal and the sliding surface is defined for the inductor current. The reference current value is generated by active disturbance rejection control (ADRC) algorithm in the outer loop, based on the output voltage error. The stability of the sliding mode inner loop and the ADRC outer loop are proven using Lyapunov stability theorem and Routh-Hurwitz criteria, respectively. The robustness of the proposed controller is analyzed in depth and validated by the simulations and experimental results obtained with a 100W prototype converter.

Unmanned aerial vehicles (UAVs) can be regarded as one of the most emerging technologies. Compared with piloted aerial vehicles, UAVs qualify for higher safety and lower cost, and they are more suitable for dangerous missions. Recently, fuel cell (FC) UAVs have obtained more and more attention due to their relatively higher energy density. However, their propulsion system still needs to be further improved to meet different requirements of performing difficult tasks. This article aims to give a comprehensive review of the key technologies of FC UAVs. First, various architectures of the propulsion system and corresponding advantages and disadvantages are introduced. Then, three kinds of management strategies for FC UAVs are reviewed. Next, some special applications and considered design procedures are summarized. Compared with other review articles, this article tries to cover more aspects of FC UAVs. Since these aspects have a tight relationship with each other, giving a comprehensive review can be more beneficial to us to understand the state-of-the-art development of propulsion systems for FC UAVs. The conclusions show that advanced propulsion architectures, efficient online energy management strategies, and professional design procedures are still in urgent demand in the commercial process of FC UAVs.

In the More Electric Aircraft (MEA) context, dc distribution systems have a time-varying structure due to the flexible distributed loads and complex operation conditions. This feature poses challenges for system stability and increases the difficulty of the stability analysis. Besides, the risk of instability may be increased under Constant Power Load (CPL) condition due to the negative incremental impedance characteristic. To this end, this paper proposes an improved Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) scheme. Particularly, an adaptive interconnection matrix is developed to establish the internal links in Port-Controlled Hamiltonian (PCH) models, and to generate the unique control law. The damping assignment technique is addressed to tune the dynamic characteristic. In order to meet the load requirements of different voltage levels, the design procedures were given for determining the control law in both boost converter and buck converter cases. The simulation and experimental results are performed to demonstrate the validity of the proposed control approach.

As the global environmental pollution and energy crisis become more serious, lithium-ion batteries (LIB) received an increasing research interest due to their low self-discharge rates, long cycle life and high power-density for the transportation applications. Battery management system (BMS) play an essential part for the LIB system, can guarantee an efficient and stable operation through LIB state of charge (SOC) estimation. In this paper, a nonlinear observer with terminal voltage feedback injection (VFNO) is designed based on electrochemical single particle (SP) model to monitor the SOC of LIB. The convergence of the SP-VFNO system in consideration of measurement error is proved in terms of Lyapunov stability theory. The current, the terminal voltage and the SOC reference value are measured in battery testing system. Besides, the extended Kalman filter (EKF) based on both the SP model and the second-order resistor-capacitor (SORC) model to estimate SOC are adopted for comparison. The experimental results indicate that the proposed SP-VFNO method has superiority with a faster convergence rate and a higher estimation precision, which can help the accurate SOC estimation for BMS in practical application.

For finding a balance between fuel economy and durability of fuel cell hybrid power systems, this article proposes an improved real-time energy management strategy (EMS) based on Pontryagin's minimum principle (IM-PMP). We introduce the fuel cell output change rate with weighted coefficient into the Hamiltonian function to limit frequent power fluctuations so as to improve the durability of the fuel cell. In addition, a real-time costate updating method is proposed for unknown driving conditions. This method determines the optimal value of costate according to the real-time state of charge (SOC), which can ensure the online implementation of the EMS and control the SOC of the lithium battery within a certain range. By constructing the hardware-in-the-loop experimental platform, the proposed strategy is compared with the finite state machine (FSM) strategy. Compared with FSM, the hydrogen consumption of the IM-PMP strategy is reduced by 10.1%, and the fuel cell operating stress is reduced by 38.3%. The SOC of the lithium battery is maintained at around 0.6. The experimental results verify the superiority of the proposed EMS.

A novel method for Li-ion battery state of charge (SOC) estimation based on a super-twisting sliding mode observer (STSMO) is proposed in this paper. To design the STSMO, the state equation of a second-order RC equivalent circuit model (SRCECM) is derived to represent the dynamic behaviors of the Li-ion battery, and the model parameters are determined by the pulse current discharge approach. The convergence of the STSMO is proven by Lyapunov stability theory. The experiments under three different discharge profiles are conducted on the Li-ion battery. Through comparisons with a conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF), the superiority of the proposed observer for SOC estimation is validated.