Power Management System For Multi-Energy Complementary Power Supply

In recent years,China’s oceanic energy research has made significant progress,particularly in the development of power supply for new marine energy sensing equipment that can function in the deep sea.The application of new energy to attain in situ and online stable work of marine view monitoring equipment has become a popular area of research.However,there are still issues such as difficulty in land-based power supply and the unstable power of single ocean energy generation,which are limiting the research and exploration of observation and monitoring equipment in deep and distant seas.To address these problems,this study aims to develop a high-efficiency power supply for marine observation and monitoring equipment by creating a power management system that employs multi-energy complementary power supply to efficiently collect,store,and use energy.The paper provides an overview of wave energy and solar photovoltaic cells and their development,as well as the current state of power management research in clean energy technology.Based on the system’s overall functional requirements,the paper formulates an overall design scheme for a power management system with multi-energy complementary power supply.The paper develops mathematical modeling and simulation of wave energy power generation,solar photovoltaic cell array,and lithium battery energy storage,as well as other key technical characteristics of the system.The paper establishes mathematical models for permanent magnet synchronous linear motors and photovoltaic batteries and selects an equivalent model of lithium battery.The paper builds a wave energy generation simulation model of permanent magnet synchronous linear motors and develops an energy tracking control strategy under a two-phase dq rotation coordinate system.The paper studies the output characteristic curve of PV cells and the maximum power tracking(MPPT)algorithm.The paper proposes an adaptive duty cycle perturbation control tracking algorithm,and simulation results show that this method has fast tracking speed,high accuracy,and small power ripple,which can achieve solar maximum power tracking and improve PV cell conversion efficiency.The paper also proposes a traceless Kalman filter(UKF)estimation algorithm based on the improved second-order Thevenin model,which is verified for reliability under hybrid pulse power characteristic test(HPPC)and dynamic stress test(DST)conditions.This algorithm achieves accurate estimation of the battery state of charge(SOC).Finally,the paper tests the system functions and compares and analyzes the design algorithm.The results show that the system modules can cooperate with the design algorithm to realize energy collection,accurate SOC estimation,and load power management adjustment strategy.The algorithm comparison includes the analysis of the MPPT algorithm and the lithium battery SOC estimation algorithm.The simulation results show that the adaptive duty cycle perturbation observation method takes into account the dynamic response and steady-state error,and the UKF estimation algorithm error is basically kept within 2%,verifying the reliability and stability of the system overall.