This paper addresses the fault isolation, estimation, and fault-tolerant control scheme for the aircraft electric anti-skid braking system (EABS) in the presence of actuator and sensor faults. First, the inherently nonlinear dynamics of EABSs are represented by a Takagi-Sugeno (T-S) fuzzy model, incorporating immeasurable antecedent variables to capture the time-varying characteristics. Second, based on the output equivalence principle, a fuzzy observer with unmatched antecedent variables is proposed to achieve isolation and estimation of actuator and sensor faults. The designed observer can guarantee the sensitivity to specific faults while enhancing the robustness to disturbances. The estimated fault information is then utilized to develop a fault-tolerant control strategy, ensuring effective fault compensation and tracking performance. Subsequently, the design of separate and integrated frameworks for the estimation and control units is considered, taking their interaction into account to achieve state and fault isolation, estimation, fault compensation, and tracking control. Finally, hardware-in-the-loop experimental results verify the effectiveness and real-time performance of the proposed fault isolation and fault-tolerant control method, demonstrating the practical applicability of the proposed framework. Note to Practitioners—The aircraft anti-skid braking system (ABS) is crucial for ensuring the safety during landing, taxiing, and other ground movements. This paper focuses on developing reliable fault isolation and fault-tolerant control strategies to maintain ABS performance and efficiency in the presence of faults. The proposed approach employs a fuzzy model to analyze the effects of various faults on system outputs, enabling precise fault isolation and estimation for simultaneous multiple faults. The reconstructed fault information is then integrated to enhance the fault-tolerant control mechanism. This ensures that braking performance can be maintained, even in the presence of multiple simultaneous faults, thereby enhancing system robustness and safety. Moreover, the proposed strategy holds potential applications in other safety-critical domains, such as rail transportation and aerospace vehicles. Future research will explore the integration of historical data to further enhance the accuracy of the fault diagnostic and accommodation units.

The droop control method is usually employed in the DC microgrids to share the load current demand among multiple sources due to its advantage of being independent of a communication network. However, the performance of the droop control method is affected by the mismatched transmission line resistance and the offset in the nominal voltage reference. This paper presents the design and optimization of the droop coefficient of converters, using the genetic algorithm to enhance the current sharing and the DC bus voltage regulation performance. The proposed approach is tested on the single bus multi-source electrical power system (EPS) for the more electric aircraft (MEA) applications. The effectiveness of the proposed approach is validated using a detailed simulation model of the MEA EPS developed in MATLAB Simulink.

A high speed nine phase permanent magnet synchronous machine (PMSM) has been designed for more electric aircraft (MEA) for the sake of high power density and fault-tolerant capability. This paper addresses the speed loop design of the high speed PMSM by comparing three speed loop designs. For MEA, fast dynamic is not the primary demand, robustness against parameter variation and noise is the key requirement. For high speed machine, field weakening is not avoidable, therefore, maintaining the speed control during field weakening is also an important feature. This paper analyses the frequency response, stiffness and performance of the speed control with the three speed controllers, while the three controllers are tuned to provide the same control bandwidth. Simulation results validate the analysis. The pros and cons of each control design are summarised in the conclusion.

A Half-bridge-active-clamp (HBAC) converter is used as an alternative to replace Dual active bridge (DAB) converter for 540V/28V on-board grid in more electric aircraft applications. The HBAC converter provides an opportunity to reduce the turn-ratio of the high frequency transformer compared to DAB converter with reduced current stress on the low voltage side benefit from a current-fed LV bridge. HBAC converter shows a much better performance both on efficiency and volume compared to conventional DAB converter. In addition, a Model Predictive Control (MPC) method for LV output current regulation is proposed based on HBAC converter with the aim of achieving fast dynamic performance.

Most of the existing methods used to estimate the cable resistance require the use of many hardware devices and the injection of perturbations to the system. Therefore, they are time-consuming, costly and prone to errors. In addition, the injection of perturbations has the potential of degrading the power quality of the system. In this paper, a new artificial neural network (ANN) aided cable resistance estimation approach is proposed. The ANN model is trained by simulation data. The trained ANN model can quickly and effectively map the current sharing ratios between the converters to the droop coefficients of the converters. In this way, the optimal droop coefficient combination that will yield the desired accurate current sharing ratio between the converters can be predicted by the trained ANN model. Subsequently, the optimal droop coefficient combination can be used in the estimation of the corresponding subsystem cable resistance by solving an equation set. The estimated cable resistance is compared with the simulated cable resistance and an excellent match is observed.

Full-bridge current doubler rectifier topology is used to restrict the ripple of output current and quicken the dynamic response. However, mass and power loss of filter composed of passive components are large. To optimize the output filter parameters, this paper adopts machine learning (ML) methods to train a support vector machine (SVM) model and an artificial neural network (ANN) model using data samples collected from simulation. SVM is used to judge the feasibility of filter design parameters, and the trained ANN serves as a dedicated surrogate model mapping from the design variables to the two optimization objectives (mass and power loss). After the ML aided filter optimization, the filter prototype based on the optimal design point is manufactured and tested on an experiment platform for the method validation.

This paper presents an enhanced modulation technique for dual converters with isolated supplies. This unified modulation technique is applicable for any positive voltage ratio between the isolated supplies. The modulation technique enhances the quality of converter output voltage. The effectiveness of the proposed technique is validated and results are presented for an open-end winding induction motor to demonstrate the advantages.

This paper explores the possibility of a semiconductor-based over-current bypass circuit for high current solid-state power controllers (SSPCs). Therefore, two different topologies of the bidirectional DC SSPCs: a. without over-current bypass circuit b. with an over-current bypass circuit are presented for the same power ratings. The first SSPC consists of a parallel matrix connection of the discrete MOSFET devices (conducts during nominal and over-current conditions) and the second one is designed with fewer MOSFET loops (conducts during nominal condition) and additional IGBT modules matrices to bypass the over-current. The thermal performances of both the SSPCs are evaluated analytically and compared during the nominal and over-current situations. Later, the PLECS simulation models of the SSPCs are developed and the junction temperature of the devices are estimated. The overall weight, power density, and cost of these two SSPCs are approximated for the comparison. It is found that the SSPC topology with bypass circuit exhibits better power density and lower cost. Therefore, it can be employed to replace the tradition circuit breakers for the more electric aircraft (MEA) in the near future.

Mechanically-driven actuators, compressors and pumps are being replaced by the aircraft manufacturers that shift the trend towards “More Electric Aircraft” and hence reducing the mechanical linkages within the aircraft system. This elevates the dependence of the electrical power on the main engine, deicing and cabin environmental system which originates from the starter-generator. This paper presents a trade-off study for the design of high-performance starter-generator, surface-mounted permanent magnet machines, considering slot-pole combination, winding configuration and geometrical layout as degrees of freedom while satisfying the output power and strict volume requirements. 18S/12P combination seems a promising candidate for starter generator application which satisfy all the given requirements, giving the output power of 32kW at 14kRPM within the volume of 1407cm3.

Multi-source DC power systems have been widely used in electric transportations, including more-electric aircraft, electric ship and electric vehicles. These systems normally involve in power electronic converters whose switching actions may cause current fluctuation on DC-bus capacitors. Eliminating certain order harmonics can help the system potentially reduce the volume and weight of the capacitor. In this paper, a simplified model to estimate 2nd carrier harmonic of DC current in two-level converters is proposed. In derived model, magnitude of the harmonic is only determined by the DC-bus current and modulation index of the converter. Meanwhile, the phase angle of it is determined by angle of carrier signals. Based on this model, a new harmonic cancellation method is proposed. The method has high robustness and can work under any fundamental frequency and power sharing ratio. Simulation results are presented in this paper to verify the validation of proposed harmonic model and the enhanced cancellation method.

This paper studies strategies to minimize the electromechanical interaction (EMI) within aircraft power systems. With the growth of electrical power on-board aircraft, the interaction between the electrical systems and the engine core will become significant. The behaviour of electrical loads (on/off, transient etc.) will have significant impacts on the engine shaft, such as producing transient vibrations, creating stability problems and reducing the efficiency etc. To avoid these problems, an advanced electrical power management system (PMS) is required. This paper introduces novel loading methods for PMS applications to minimize the interactions between electrical and mechanical systems. The strategies, referred as Single Level Multi-edge Switching Loads (SLME), Multilevel Loading (MLL), and Multi-load Single Level Multi-edge Switching Loads (MSLME) are developed based on the Posicast method. An insight look of the developed technique has been studied using the zero-pole root locus. It is demonstrated that the excited poles in the system are cancelled by the addition of zeros, and thus suppressed the EMI vibrations.