predict_hybrid_modes

predict_hybrid_modes(start_stop_hybrid, ems_data, drive_battery_model, times, motive_powers, accelerations, after_treatment_warm_up_duration, after_treatment_cooling_duration, start_stop_activation_time, min_time_engine_on_after_start, is_cycle_hot)[source]

Predicts the hybrid mode status (0: EV, 1: Parallel, 2: Serial).

Parameters:
  • start_stop_hybrid (StartStopHybrid) – Start stop model for hybrid electric vehicles.
  • ems_data (dict) – EMS decision data.
  • drive_battery_model (DriveBatteryModel) – Drive battery current model.
  • times (numpy.array) – Time vector [s].
  • motive_powers (numpy.array) – Motive power [kW].
  • accelerations (numpy.array) – Acceleration [m/s2].
  • after_treatment_warm_up_duration (float) – After treatment warm up duration [s].
  • after_treatment_cooling_duration (float) – After treatment cooling duration [s].
  • min_time_engine_on_after_start (float) – Minimum time of engine on after a start [s].
  • start_stop_activation_time (float) – Start-stop activation time threshold [s].
  • is_cycle_hot (bool) – Is an hot cycle?
Returns:

Hybrid mode status (0: EV, 1: Parallel, 2: Serial).
Return type:

numpy.array