Based on the thermohydraulic calculation model verified in this study and Non-dominated Sorted Genetic Algorithm-II (NSGA-II), a multi-objective configuration optimization method is proposed, and the performances of shell-and-tube heat exchanger with disc-and-doughnut baffles (STHX-DDB) and shell-and-tube heat exchanger with segmental baffles (STHX-SB) are compared after optimization. The results show that, except in the high range of heat transfer capacity of 16.5–17 kW, the thermohydraulic performance of STHX-DDB is better. Tube bundle diameter, inside tube bundle diameter, number of baffles of STHX-DDB and tube bundle diameter, baffle cut, number of baffles of STHX-SB are chosen as design parameters, and heat transfer capacity maximization and shell-side pressure drop minimization are considered as common optimization objectives. Three optimal configurations are obtained for STHX-DDB and another three are obtained for STHX-SB. The optimal results show that all the six selected optimal configurations are better than the original configurations. For STHX-DDB and STHX-SB, compared with the original configurations, the heat transfer capacity of optimal configurations increases by 6.26% on average and 5.16%, respectively, while the shell-side pressure drop decreases by 44.33% and 19.16% on average, respectively. It indicates that the optimization method is valid and feasible and can provide a significant reference for shell-and-tube heat exchanger design.

In order to calculate heat transfer capacity and air-side pressure drop of an annular radiator (AR), one performance calculation method was proposed combining heat transfer unit (HTU) simulation and plate-and-fin heat exchanger (PFHX) performance calculation formulas. This method can obtain performance data with no need for meshing AR as a whole, which can be convenient and time-saving, as grid number is reduced in this way. It demonstrates the feasibility of this performance calculation method for engineering applications. In addition, based on the performance calculation method, one configuration optimization method for AR using nondominated sorted genetic algorithm-II (NSGA-II) was also proposed. Fin height (FH) and number of fins in circumferential direction (NFCD) were optimized to maximize heat transfer capacity and minimize air-side pressure drop. Three optimal configurations were obtained from the Pareto optimal points. The heat transfer capacity of the optimal configurations increased by 22.65% on average compared with the original configuration, while the air-side pressure drop decreased by 33.99% on average. It indicates that this configuration optimization method is valid and can provide a significant guidance for AR design.

In this paper, we introduce a health parameter and estimation algorithm to assess the severity of stator turn-to-turn/inter-turn short-circuit (TTSC) faults in wound-rotor synchronous generators (WRSG). Our methodology establishes criteria for evaluating the severity of stator TTSC faults in WRSG and provides a specific solution for estimating both the severity of these faults and the resultant power loss. Our assessment methodology directly reflects the intrinsic impact of stator TTSC faults on the WRSG, offering enhanced efficiency, accuracy, and resilience to interference compared with traditional methods in estimating and gauging the TTSC severity. First, we demonstrate that it is impossible to determine the two fault parameters of the WRSG stator TTSC faults solely based on the voltage and current measurements. Subsequently, we introduce a novel health parameter for the WRSG stator TTSC faults and show that for a given generator and load, the dynamics of voltage and current during these faults as well as the resulting power loss are determined by this health parameter. We then detail the characteristics of the proposed health parameter and criteria for evaluating the severity of the WRSG stator TTSC faults. Furthermore, we present an estimation algorithm that is capable of accurately estimating the health parameter and power loss, demonstrating its minimal estimation error. Finally, we provide a comprehensive set of simulation results, including Monte Carlo results, to validate our proposed methodology and illustrate that our approach offers significant improvements in terms of the efficiency, accuracy, and robustness of the WRSG stator TTSC fault detection and isolation (FDI) over conventional methods.

Distributed control architecture can bring many benefits to the engine control system, but the delay and packet dropout introduced by network communication will bring negative effects to the control system. The aging and deterioration of the engine are also obstacles in the design of the engine control system. This paper is concerned with the problem of guaranteed cost control for a distributed engine control system (DECS) with these negative constraints. Firstly, a model of DECS with multiple delays, packet dropouts and uncertainties is built. Secondly, a multiple delay-dependent guaranteed cost controller design method is proposed in the form of a set of linear matrix inequalities (LMIs). The non-convex optimal controller design problem is transformed into a convex optimization problem through the cone complementarity linearization (CCL) method, and the suboptimal controller is designed iteratively. Thirdly, turboshaft engine aging and deterioration are treated as sources of uncertainties, and the norm-bounded uncertain model of the turboshaft engine is modeled. Finally, the numerical simulations demonstrate the effectiveness and applicability of the guaranteed cost controller designed for DECS with multiple delays, packet dropouts, engine aging and deteriorations.

This study proposes a novel paradigm for enhancing the fault detection and isolation (FDI) of gas generators in all-electric auxiliary power unit (APU) by utilizing shaft power information from the starter/generator. First, we conduct an investigation into the challenges and opportunities for FDI that are brought about by APU electrification. Our analysis reveals that the electrification of APUs opens new possibilities for utilizing shaft power estimates from starters/generators to improve gas generator FDI. We then provide comprehensive theoretical and analytical evidence demonstrating why, how, and to what extent the shaft power information from the starter/generator can fundamentally enhance the estimation accuracy of system states and health parameters of the gas generator, while also identifying key factors influencing these improvements in FDI performance. The effectiveness of the proposed paradigm and its theoretical foundations are validated through extensive Monte Carlo simulation runs. The research findings provide a unique perspective in addressing three fundamental questions—why joint fault diagnosis of the starter/generator and gas generator in all-electric APUs is essential, how it can be implemented, and what factors determine its effectiveness—thereby opening up promising new avenues for FDI technologies in all-electric APU systems.

This paper presents a joint system modeling approach for fault simulation of all-electric auxiliary power unit (APU), integrating starter/generator turn-to-turn short circuit (TTSC) faults with gas generator gas-path faults.To address challenges in electromechanical coupling, simulation precision and computational efficiency balance, we propose a multi-rate continuous-discrete hybrid simulation architecture. This architecture treats the starter/generator as a continuous system with variable step size in Simulink, while modeling the gas generator as a discrete system with fixed step size in a dynamic-link library (DLL) environment. For the starter/generator fault modeling, a multi-loop approach is deployed to accurately simulate TTSC faults. For the gas generator, we develop an improved GasTurb-DLL modeling method (IGDM) that enhances uncertainty modeling, state-space representation, and tool chain compatibility. Finally, the proposed methodology above was implemented in a case study based on the APS5000 all-electric APU structure and parameters. Model validation was conducted by comparing simulation results--covering steady-state, transients, healthy, and fault conditions--with reference data from third-party software and literature. The close agreement confirms both the model's accuracy and the effectiveness of our modeling methodology. This work establishes a modeling foundation for investigating the opportunities and challenges in fault detection and isolation (FDI) brought by the all electrification of the APU, including joint fault estimation and diagnosis, coupled electromechanical fault characteristics.