Research On Hybrid Energy Management Strategy Of Unmanned Marine Vehicles Based On Fuzzy Control

With the exploration of the ocean,applications of unmanned marine vehicles are gradually expanding.Unmanned marine vehicles carry very limited energy due to size limitations.A fuel cell is a potential energy source,and fuel cells are widely used due to their high energy conversion efficiency and non-pollution characteristics.However,the response of fuel cells output power is too slow to make the output voltage fluctuate greatly and the stability.Therefore,DC converters and auxiliary energy storage devices are necessary to form a hybrid energy system.One of the key technologies for hybrid energy systems is to develop a suitable energy management strategy,for improving the working efficiency of the fuel cell,increasing the economy of the system,and extending the service life of the battery.In the thesis,we provide a theoretical reference for the design and optimization of the energy management strategies of fuel cell hybrid power systems.The specific research contents are as follows:Firstly,a hybrid energy system is established,where hydrogen fuel cells are used as the main energy source and lithium batteries and supercapacitors are used as auxiliary energy storage devices.By analyzing several typical topology forms of the hybrid energy system,the topology and working mode of the hybrid energy system is determined.According to the composition of the hybrid power system,a hybrid unmanned marine vehicle simulation model is established based on MATLAB/Simulink simulation,and the fuel cell,lithium battery,supercapacitor,and DC/DC converter are modeled respectively.Then,for the hybrid energy system proposed in this thesis,a two-input and one-output fuzzy controller is designed.The input parameters are the state of charge of the lithium battery and the load demand power,and the output parameter is the reference power of the fuel cell.Since the design of the fuzzy control strategy is subjective to some extent,a genetic algorithm is used to optimize the fuzzy control rules in the fuzzy controller.The results show that the fuzzy control strategy optimized by the genetic algorithm can effectively improve the system economy under the simulated working conditions compared with the control strategy before optimization.The results of the genetic algorithm optimized control strategy are compared with the energy management results of the equivalent consumption minimization strategy and the finite state machine control strategy.The simulation results verify the effectiveness of the optimized fuzzy control strategy designed in this thesis.The fuel cells can cover the main power when the SOC of the lithium battery is low.The lithium battery can be charged when there is surplus energy,avoiding over-discharge.The lithium batteries take up more load demand power when the SOC of the lithium battery is high.Thus,the over-charging phenomenon caused by the fuel cell continuously charging the lithium battery can be avoided,and the hydrogen consumption of the fuel cell can be reduced to improve the system economy and extend the service life of the battery.