Anticipation of a revolution in personal travel fueled by electric vertical take-off and landing aircraft is leading to the development highly innovative platforms. Health management systems and technologies, such as digital twins, physics-based models, and machine learning-based models, will play key roles as OEMs and operators manage safety and reliability of these brand-new platforms. Key to enabling health management is capture and storage of appropriate data streams. For distributed electric propulsion aircraft, it is anticipated that algorithms based on electrical signals, especially electrical current signatures, provides a pathway towards diagnosing a myriad of mechanical, electrical, and magnetic faults within key aircraft subsystems. Maturing the prognostics capability of health management algorithms will further enable the adoption and growth of urban air mobility, as have knowledge into future component health state enables robust decision making for operations, sustainment, and supply chain management support of these vehicles.