Joint System Modeling Approach for Fault Simulation of Start-er/Generator and Gas Generator in All-Electric APU

TL;DR

This paper introduces a hybrid simulation approach for fault modeling in all-electric APU systems, combining continuous and discrete models to improve accuracy and efficiency in fault detection and diagnosis.

Contribution

It develops a multi-rate hybrid simulation architecture and an improved gas generator model for accurate fault simulation in all-electric APUs.

Findings

Model validation shows high accuracy with reference data.

The approach effectively simulates steady-state and transient fault conditions.

Provides a foundation for fault detection and diagnosis in electrified APUs.

Abstract

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.