Research On Trajectory Planning And Energy Management For Fuel Cell Hybrid Power Of Multi-Rotor UAV

Due to their compact size and high degree of flexibility,multi-rotor UAVs have recently seen extensive usage in many other spheres of life.As a result,their core technologies have also attracted a lot of interest.One of them is the endurance of multi-rotor UAVs,which needs to be solved.Today’s multi-rotor UAVs typically run on lithium-ion batteries,which are insufficient for long-term endurance.Although the energy density of fuel cells is larger than that of lithium batteries,their power density is small,and it is difficult to meet the maneuverability of UAVs,so it is often used in the form of fuel cells and lithium battery hybrid power supplies to improve endurance.This paper investigates the trajectory planning and energy management strategy of fuel cell hybrid power of multi-rotor UAV based on the main scientific and technological research project of Jilin Provincial Science and Technology Department:rapid response,rescue and disaster relief vertical take-off and landing UAV system equipment development and application development(project number20190303061SF).The following is the article’s main contribution:(1)Firstly,different coordinate systems and rotation matrices are established,and the position dynamics and attitude dynamics of quadcopter UAVs are modeled and appropriately simplified.Then,the model of each component of the fuel cell hybrid power system is established,in which the battery model adopts the PNGV equivalent circuit model and the fuel cell model adopts the mechanism model.The established model provides theoretical support for subsequent trajectory planning and energy management strategy.At the same time,through the demonstration of various topological schemes of UAV hybrid power supply,one of the structures is determined as the structure of UAV hybrid power supply system.(2)The map modeling approach of UAV trajectory planning is expanded with a focus on the problem of quadrotor UAV trajectory planning,and the flight space model is created using the digital elevation method.A quadcopter UAV multi-target trajectory optimization model is created using the global flight energy consumption and flight distance as the objective functions.The multi-objective optimization model is solved using the NSGA-II algorithm,and then an ideal flight trajectory is found.At the same time,the traditional genetic algorithm is compared and analyzed with the NSGA-II algorithm,and the results show that the NSGA-II algorithm converges faster than the traditional genetic algorithm and has a smaller flight distance of the searched trajectory.Lastly,the optimization model considering the flight distance is compared with the multi-objective optimization model,and it is verified that the multi-objective optimization model can not only save 0.37% energy consumption,but also shorten the flight distance by 7.86%.(3)In order to boost the endurance of hybrid power quadcopter,this paper develops a class-conscious model prophetical management strategy to comprehend the affordable distribution of power between hybrid power sources of quadcopter UAVs and improve the economy of the facility system.Through simulation comparison,the hierarchical model predictive control strategy can save hydrogen consumption better than the fuzzy logic control strategy and the equivalent fuel consumption minimum strategy.At the same time,in order to improve the accuracy and rapidity of power prediction in the hierarchical model predictive control method,this paper proposes a grey Markov prediction method.The grey Markov prediction method has less prediction error than the grey prediction model,Markov prediction model and autoregressive integrated moving average model,and is more suitable as a power prediction method for UAV loads.Finally,the above energy management strategy is simulated and hardware-in-the-loop experiments are carried out.The experimental results show that the hierarchical model predictive control has better fuel economy,and can save 3.8% and 5.51% of hydrogen consumption respectively compared with fuzzy logic control and equivalent fuel consumption minimum strategy.The research results show that the flight energy consumption and flight distance are used as multi-objective optimization in the trajectory planning algorithm,and the optimal flight trajectory is searched for less energy consumption than that of singletarget optimization of flight distance,and reasonable energy management strategy can improve the endurance and economy of UAV hybrid power system.