The application of model-based diagnosis schemes to real systems introduces many significant challenges, such as building accurate system models for heterogeneous systems with complex behaviors, dealing with noisy measurements and disturbances during system operation, and producing valuable results in a timely manner with limited information and computational resources. The Advanced Diagnostics and Prognostics Testbed (ADAPT), deployed at NASA Ames Research Center, is a representative spacecraft electrical power distribution system that embodies a number of these challenges for developing realistic diagnosis and prognosis algorithms. ADAPT contains a large number of interconnected components, along with a number of circuit breakers and relays that enable a number of different power distribution configurations. The system includes electrical dc and ac loads, mechanical subsystems, such as motors, and fluid systems, such as pumps. The system components are susceptible to different types of faults that include unexpected changes in parameter values, discrete faults in switching elements, and sensor faults. This paper presents Hybrid TRANSCEND, a comprehensive model-based diagnosis scheme to address these challenges. The scheme uses the hybrid bond graph modeling language to systematically develop computational models and algorithms for hybrid state estimation, robust fault detection, and efficient fault isolation. The computational methods are implemented as a suite of software tools that enables analysis and testing through simulation, diagnosability studies, and deployment on the experimental testbed. Simulation and experimental results demonstrate the effectiveness of this methodology in efficient diagnosis of heterogeneous components for an embedded system.