Eco-friendly energy management strategy for turbo-electric eVTOLs: Coupling fuel economy, battery health and life-cycle emissions via improved TD3

To achieve sustainable and green aerospace propulsion, energy management strategies (EMS) must evolve beyond simple fuel efficiency to address the synergistic optimization of battery health and life-cycle emissions. This paper proposes an eco-friendly multi-objective EMS for turbo-electric hybrid eVTOLs. A unified optimization framework is established to couple conflicting objectives—fuel economy, battery State-of-Health (SOH), and environmental impact. To solve this complex continuous control problem, an improved Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is developed, incorporating a pyramidal feature extraction structure and state-machine-guided priors to filter noise and accelerate convergence. Simulation results demonstrate that the proposed strategy improves energy economy by 4% over rule-based methods and approaches the global optimum (Dynamic Programming) within a 0.91% margin. Furthermore, Hardware-in-the-Loop (HIL) validation confirms real-time feasibility on embedded avionics with an inference latency under 5.5 ms, proving its potential for deployment in sustainable urban air mobility.