The invention provides a hybrid power ship energy optimization method based on working condition recognition. The control process comprises the steps that ship working condition data are collected; according to the ship working condition data, adopting a convolutional network to identify ship working condition types; optimizing energy control of the ship through rolling optimization characteristics of a nonlinear model prediction controller; the decision information of the nonlinear model prediction controller comprises the current ship speed of the ship and the power level of the ship demand power; the optimized energy control mode comprises energy output of a diesel generator and energy output of an energy storage battery, and specific control targets comprise current of the energy storage battery and the rotating speed of a main engine in the diesel generator; and the constraint condition and the cost function in the nonlinear model prediction controller are adaptively adjusted through the ship working condition type. According to the method, parameters can be adaptively adjusted along with changes of working conditions, so that the method adapts to different operation working conditions of the ship.
本发明提供一种基于工况识别的混合动力船舶能量优化方法,控制过程包括:采集船舶工况数据;根据船舶工况数据,采用卷积网络识别船舶工况类型;通过非线性模型预测控制器的滚动优化特性优化船舶的能量控制;非线性模型预测控制器的决策信息包括当前的船舶的船速和船舶需求功率所处的功率等级;优化能量控制的方式包括控制柴油发电机的能量输出和储能电池的能量输出,具体控制目标包括储能电池的电流、柴油发电机中主机的转速;通过船舶工况类型自适应调整所述非线性模型预测控制器中的约束条件、成本函数。该方法可以跟随工况的变化对参数进行自适应调整,从而适应船舶不同的操作工况。
Hybrid power ship energy optimization method based on working condition identification
一种基于工况识别的混合动力船舶能量优化方法
27.09.2024
Patent
Elektronische Ressource
Chinesisch
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