Cesar Diaz-Londono, Liu Zhang, Jorge De La Cruz et al.
The rapid growth of electric vehicles (EVs) is increasing the need to accurately quantify their flexibility as a resource for power system operation. However, most existing approaches rely on simplified or power-controllable models that overlook the intrinsic constraints of fast and ultra-fast DC charging. In practice, flexibility is fundamentally shaped by battery management system (BMS) behavior, connection time availability, and battery-protection limits. This paper introduces a trajectory-aware data-driven framework to quantify EV charging flexibility as an energy-bounded and time-constrained process. Based on 252 real charging sessions, 141 representative Power-SoC profiles are reconstructed to capture real-world charging dynamics. Unidirectional flexibility is defined through bounds on the maximum shiftable charging energy, while bidirectional flexibility is quantified as the bounds of the maximum extractable discharge energy under feasibility constraints. Results show that flexibility depends on charging state and connection time. Charging beyond 80% SoC increases duration with limited gains, while higher charger power saturates due to BMS limits. Charging time in the 20%-80% range drops by over 60%, and mean power increases by up to 40%. The maximum extractable bidirectional energy can exceed twice its value depending on the point at which flexibility is activated. These results highlight that EV flexibility is not a controllable resource, but a bounded and time-dependent capability. As such, the proposed framework provides actionable limits that can be directly used by system operators and aggregators for scheduling, peak shaving, and short-duration flexibility services.