Research On Optimization Of Energy Management Control Strategy For Diesel Electric Hybrid Ship Based On Swarm Intelligence Algorithm

Energy crisis and environmental pollution are two major problems facing the shipbuilding industry,and new energy ships are considered to be an effective way to solve these two problems.Diesel electric hybrid ship combines the advantages of long navigation mileage of traditional internal combustion engine ship and energy saving and environmental protection of pure electric ship,and has become a research hotspot in the field of new energy ship.This paper takes a parallel diesel electric hybrid ship as the research object.On the premise of meeting the navigation demand power,how to effectively distribute the output power of diesel engine and motor in real time,so as to obtain the optimal fuel economy.Aiming at the existing problems of energy management strategy of diesel electric hybrid ship,combined with typical swarm intelligence optimization algorithms,namely ant colony optimization(ACO)algorithm and particle swarm optimization(PSO)algorithm,this paper deeply studies the energy management strategy and puts forward optimization.The main contents and conclusions are as follows:(1)The parallel diesel electric hybrid system model was established.Firstly,the structure of parallel diesel electric hybrid system was analyzed;Secondly,the modular modeling idea was used to establish the component model;Finally,according to the main mathematical models such as diesel engine mathematical model,motor mathematical model,battery mathematical model,transmission system mathematical model and propeller mathematical model,the simulation model of parallel diesel electric hybrid system was established.The correctness and accuracy of the model are verified with the help of ship design data on the MATLAB /Simulink simulation platform.Then a rule-based charge depleting/charge sustaining,(CD-CS)strategy was established for simulation verification,which lays the foundation for the later research.(2)Aiming at the problems of poor real-time performance and low battery power utilization of the minimum equivalent fuel consumption strategy,a discrete adaptive equivalent consumption minimization strategy(DA-ECMS)was proposed.For the diesel electric hybrid drive mode,the constraint conditions of the optimal torque are obtained by deriving the approximate analytical equation of the equivalent fuel consumption,so as to realize the numerical calculation of the whole feasible region.Only five discrete points need to be calculated,and the strategy of minimizing the discrete equivalent consumption minimization strategy(D-ECMS)was proposed.Aiming at the problem of low battery power utilization,a linear descent state of charge trajectory planning method with voyage is proposed for the case of known voyage mileage;for unknown mileage,the interval average value based on the maximum distribution probability of historical mileage was proposed as the reference mileage for state of charge(SOC)planning.In order to select a more appropriate initial equivalent factor,the improved secant method was used to calculate the optimal equivalent factor for different mileage and SOC initial values.The simulation results show that the proposed strategy can reasonably distribute the torque of diesel engine and motor,improve the working efficiency of diesel engine and motor and reduce fuel consumption.(3)Aiming at the problems that the clutch separation or combination in the mode switching process was easy to lead to the power interruption or torque fluctuation of the transmission system,produce large clutch sliding work,and affect the smoothness of the transmission system and the service life of the clutch,a mode switching coordinated control method based on cascade predictive control is proposed.This method includes model predictive control(MPC)and PID control.Firstly,through the analysis of the mode switching process,the control objectives of each stage of mode conversion are determined,and the limiting conditions of torque change rate were designed to limit the impact of each stage.Then,considering the dynamic characteristics of the engine and the control objectives of this stage,a coordinated control algorithm based on cascade prediction was proposed.In MPC,the optimal required torque of motor,engine and clutch was obtained by designing the state constraints to limit the impact and the objective function to minimize the slip and wear work of clutch.In order to respond to the engine torque control command more accurately,the PID controller with high sampling frequency was used to compensate the engine output torque and realize smooth mode conversion.The simulation results show that the proposed strategy can effectively reduce the sliding work,ensure the smoothness of mode switching and improve the quality of mode switching.(4)In order to achieve the dual objectives of reducing the energy consumption of the whole ship and controlling the battery power,an ECMS strategy based on ant colony optimization algorithm and considering mode switching was proposed.The strategy adopts two-layer structure: inner layer and outer layer.In the inner layer,the engine control module considering mode switching was adopted to optimize the working mode and working point,so as to reduce fuel consumption;In the outer layer,aiming at the shortcomings of traditional ACO algorithm,heuristic factor and adaptive volatilization factor are introduced,and an improved Ant Colony Optimization was proposed to optimize the equivalent factor,so as to reduce the deviation between the final SOC value and the target value.The simulation results show that the proposed strategy can achieve the dual goals of reducing the fuel consumption of the whole ship and controlling the battery power.(5)With the aging of the battery,the SOC estimation accuracy of the battery becomes lower and lower,the service life of the power battery was shortened,and the fuel economy of the whole ship becomes worse,a multi-objective energy management strategy considering the degradation characteristics of the battery was proposed.The strategy was divided into two layers: the upper layer and the lower layer.In the upper layer,D-ECMS strategy considering mode switching based on adaptive PSO was adopted to reduce fuel consumption;in the lower layer,the strong tracking adaptive unscented Kalman filter algorithm was used to estimate the battery SOC online and in real time.By applying the battery aging model to the whole ship energy management control strategy,the goal of optimizing the fuel economy of the whole ship and prolonging the service life of the battery was realized at the same time.The simulation results show that the proposed strategy can achieve the accurate estimation of SOC and the optimization of fuel economy in the whole battery life,alleviate the capacity attenuation rate of power battery pack and prolong the service life of battery.