Model Predictive Control and Optimization of The Power Management System for A Hybrid Electric UAV

Over the past decade, global warming has been greatly concerned and efforts to reduce the consumption of fossil fuel in transportation have been widely pursued. Due to the low energy density of current batteries compared to fuels, electrification of aircraft propulsion system maintaining its endurance is not possible. Therefore, hybrid propulsion systems (HPS) are an alternative to ensure fuel consumption reduction. The complexity induced by adding an additional power source also requires sophisticated control system and optimization. In this paper, the optimization problem of a series hybrid electric propulsion system for a VTOL UAV is considered and the effect of battery degradation and temperature on the optimal degree of hybridization (DoH) for minimum cost in studied. A predictive model based on manufacturer data is constructed for different components and numerical results obtained using MATLAB/Simulink. The results showed that the battery degradation greatly affect the total cost of one mission and decreased the optimal DoH due to high cost of battery replacement. Also, it has been shown that state of health of the battery is greatly depend on the temperature and achieving higher DoH requires appropriate cooling system for the battery.

کلیدواژه ها:

Optimization ، Degree of hybridization ، Battery state of health ، Hybrid propulsion system