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Introduction to SPARK Simulator

Purpose and Scope

The SPARK simulator is a comprehensive techno-economic evaluation tool designed specifically for 19-passenger regional hybrid-electric aircraft. As the aviation industry pivots towards sustainable solutions, understanding the interplay between novel powertrain architectures, flight physics, and operating economics becomes critical. SPARK provides a robust framework to model these interactions, allowing engineers and stakeholders to evaluate the feasibility, performance, and financial viability of hybrid-electric regional aviation.

The Cascade Logic Workflow

The SPARK simulator operates on a strictly sequential, cascade-based logic architecture. Each module's output serves as the input for the subsequent module, ensuring physical consistency throughout the simulation process:

  1. Input Definition: The simulation begins by parsing user-defined parameters, including mission profiles, aircraft specifications, and battery characteristics.
  2. Atmosphere Model: Based on the flight altitude, the simulator computes the localized environmental conditions (temperature, pressure, density) using the standard atmosphere model.
  3. Aerodynamics: Utilizing the computed air density and aircraft geometry, the aerodynamic module calculates the forces of lift and drag acting on the airframe.
  4. Power Requirements: The aerodynamic drag and thrust requirements are translated into the mechanical power needed at the propeller shaft, and subsequently the electrical power demanded from the powertrain.
  5. Battery Model: The electrical power demand is fed into the battery module, which evaluates dynamic discharge, state of charge (SoC) tracking, thermal constraints, and potential voltage crash scenarios.
  6. Economics: The mission's energy consumption, flight time, and battery degradation (lifecycle) are assessed to calculate direct operating costs (DOC) and other economic metrics.
  7. Optimization: Finally, the system can iterate this cascade to optimize for specific targets, such as minimizing mass, maximizing range, or minimizing operational costs.