船舶主机冷却水系统的建模与节能型控制研究

Study on Modeling and Control of Marine Main Engine Cooling Water System for Energy Saving

在对船舶主机高温淡水冷却水系统的各主要器件建立各自的数学模型的基础上,对其整个系统建立了数学模型。然后以主机高温淡水冷却水系统作为研究对象,提出了在此系统中采用神经元自适应控制方式替代传统的PID(比例积分微分)控制方式进行水温调节,以达到改善控制并节约能源的目的。最后以仿真结果说明了神经元自适应控制方式具有良好的适应性与抗干扰性,它比PID控制方式更适用于主机冷却水温度调节系统。

The cooling water system of marine main engine is always designed as three-level-cooling pattern to cool the main engine′s cylinders. And the most important section among the three-level-cooling system is the high temperature fresh water cooling system which also is the most complex part with the largest amount of related factors. The main devices with the function of thermal energy exchange, being contained in the high temperature fresh water cooling system, are cylinders (the main heat generator), desalination machine of seawater (acted as a refrigerant), remaining steam condenser and main cooler. In this paper, mathematical models of main devices of marine main engine high temperature fresh water cooling system are established separately at first, and then the mathematical model of the whole system is estabished according to the working principle of the high temperature fresh water cooling system. Afterwards, the aforementioned cooling water temperature regulation system is chosen as the research object and a neuron-based adaptive control system is employed to regulate the temperature of cooling water. According to the control algorithm of the applied control system, the neuron makes self-organizing through modification of its weighted values. And the weighted values are determined through correlative search. In this adaptive control system, a smoothing factor is applied during the modification of the weighted values, which makes the procedure of the weighted value modification more smoothly. Then a proportional-integral-differential (PID) control system is employed to substitute the aforementioned neuron-based adaptive control system in order to compare the results of their application to the improvement of control and energy saving. The simulation results show that the properties of neuron-based adaptive control system is better than that of traditional PID control system, and the neuron-based adaptive control system is more suitable for control of main engine cooling water temperature.