一种水下推进器配置的氢燃料电池能量管理优化方法
By building a simulation model and optimizing the neural network, combined with a closed-loop control system, precise output power control of hydrogen fuel cell powered ships was achieved, solving the problems of short driving range and low energy efficiency in existing technologies, and improving the driving range and energy efficiency of underwater propulsion.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN UNIV
- Filing Date
- 2023-03-29
- Publication Date
- 2026-07-17
AI Technical Summary
Existing hydrogen fuel cell-powered ships struggle to accurately predict remaining battery power and the resistance experienced by the vessel, making it difficult to achieve optimal control of the electric motor's output power. Furthermore, traditional control methods are unable to adapt to complex operating conditions, impacting range and energy efficiency.
By building simulation models of hydrogen fuel cells and underwater thrusters, BP neural networks are used to predict the optimal energy-saving output power, and genetic algorithms are combined for optimization. A closed-loop control system and a PID controller are used to adjust the motor speed, thereby achieving precise regulation of the motor.
It increases the range of underwater thrusters by 30% and can retrain neural networks based on data from different thrusters and fuel cells to meet complex requirements, achieving stable output power and good energy-saving performance.
Smart Images
Figure CN116344871B_ABST