Intelligent control system for cooling water temperature of ship power device

Abstract

According to the ship power device cooling water temperature intelligent control system, the water temperature is monitored in real time through the temperature sensor arranged at the cooling water inlet, and the electric three-way flow regulating valve with the stepping motor is used for changing the mixing proportion of low temperature and bypass fresh water for control; a cooperative control framework is adopted; an upper-layer model prediction control module performs rolling time domain optimization based on a time-delay thermodynamic model which is identified and updated on line, and outputs a feedforward signal; and the lower-layer fuzzy self-adaptive PID controller dynamically adjusts parameters according to the temperature deviation and the change rate of the temperature deviation to generate compensation control quantity. And the two outputs are linearly superposed and then converted into a valve accurate action signal through the driving module. The cooperation method effectively fuses the feedforward optimization capability of the MPC and the strong robustness of the fuzzy PID to model mismatch and disturbance, significantly improves the control precision and stability of the water temperature of the main engine under the inertia and time-varying working conditions, reduces the equipment damage caused by temperature fluctuation, prolongs the service life of the main engine, and improves the navigation safety and the energy efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ship engineering and intelligent control technology, in particular, especially relates to a ship power plant cooling water temperature intelligent control system. BACKGROUND

[0002] The ship cooling water system is a key component of the normal operation of the ship, and its key function is to provide reliable cooling for the main engine, generator, heat exchanger and other heat load equipment of the ship, to ensure that these devices can work normally in a high temperature environment. In the system, the main engine cylinder liner cooling water inlet temperature is an important thermal control parameter, and too high temperature can easily lead to rapid evaporation of the cylinder wall inner surface oil film and damage the lubrication, aggravate the wear between the cylinder liner and the piston ring, and in extreme cases, may cause local vaporization of the cooling water cavity to form hot spots, inducing cylinder liner crack risk; too low temperature will unnecessarily increase heat loss and reduce diesel engine thermal efficiency. Precise control of cooling water temperature is of great significance to reducing thermal stress and improving the power performance and service life of the diesel engine.

[0003] The main engine cylinder liner cooling water temperature of the ship is a key thermal parameter affecting the operation efficiency and reliability of the ship power system. During the operation of the ship, the high temperature generated by the diesel engine combustion needs to be effectively dissipated through the cylinder liner cooling water system to maintain the main engine within the optimal working temperature range. If the cooling water temperature is too high (such as more than 95±2℃), it may cause the cylinder wall lubricating oil film to evaporate, the piston ring and cylinder liner to wear, and even cause the cylinder liner to crack; while too low temperature (such as lower than 75±2℃) will increase the heat loss and reduce the thermal efficiency, and shorten the service life of the main engine due to increased thermal stress. Therefore, high-precision control of the cooling water temperature is of great significance to optimizing the combustion efficiency of the main engine, reducing mechanical loss, improving navigation safety and energy economy; The main engine cylinder liner cooling water temperature control system is a nonlinear system with large inertia, pure lag and time-varying characteristics. Currently, the ship cooling water temperature control mainly uses traditional PID control or model predictive control (MPC) method. The traditional PID controller is based on error feedback adjustment and performs well when the working condition is stable, but it relies on the "after-regulation" mechanism, and the response of the cooling system with large inertia and pure lag characteristics is slow, and in the case of ship variable working conditions (such as sudden change of main engine load, fluctuation of environmental temperature), it is easy to have overshoot or long regulation time. Although MPC control can perform feedforward optimization based on the prediction model, its control performance is highly dependent on the accurate system mathematical model, and factors such as heat exchanger fouling and cooling medium flow fluctuation in the actual operation of the ship can easily lead to model mismatch, resulting in decreased control accuracy. SUMMARY

[0004] According to the technical problems proposed above, a ship power plant cooling water temperature intelligent control system is provided.The application adopts high-precision temperature sensors, combines model predictive control and fuzzy adaptive PID, solves the time delay compensation and model mismatch problems through real-time parameter identification and rolling optimization mechanism, breaks through the limitations of single control method, significantly improves the system robustness and control accuracy, prolongs the service life of the equipment, improves the safety of navigation, and provides intelligent support for ship energy efficiency management.

[0005] The technical means adopted by the application are as follows: A ship power plant cooling water temperature intelligent control system comprises: A temperature detection unit is configured to monitor the temperature of the cooling water of the main engine cylinder liner cooler in real time. A flow regulation execution unit is configured to dynamically regulate the fluid distribution ratio of at least two parallel branches in the cooling water system. A double-layer collaborative control unit comprises an upper-layer model predictive control module and a lower-layer adaptive feedback control module, wherein the model predictive control module calculates the future state of the system through a rolling optimization algorithm, minimizes the deviation between the set value and the predicted output, and generates a feedforward control signal; the adaptive feedback control module online corrects the PID parameters according to the real-time temperature deviation and outputs a final composite control signal to the driving unit. The driving unit converts the composite control signal into a driving instruction of the stepper motor and sends it to the flow regulation execution unit.

[0006] Further, the temperature detection unit comprises a temperature sensor, which is arranged at the inlet of the cooling water of the main engine cylinder liner cooler, has a measurement accuracy of not less than ±0.5℃, and a response time of not more than 2 seconds.

[0007] Further, the flow regulation execution unit comprises an electric flow regulation valve, which is arranged at the inlet of the cooling water branch, is a three-way regulation valve with a stepper motor, adjusts the opening degree of the valve through the driving of the stepper motor, adjusts the mixing ratio of the low-temperature fresh water and the bypass water by changing the resistance of each branch, and realizes the control of the temperature of the main engine cylinder liner cooling water.

[0008] Further, the model predictive control module calculates the future state of the system through a rolling optimization algorithm, specifically comprising: Real-time acquisition of cooling water temperature historical data updates the parameters of the model predictive control module, and a thermodynamic transfer function containing time delay characteristics is used for modeling; The future temperature change trajectory is calculated through multi-step prediction, and the influence of sea water temperature disturbance and main engine power change is considered when optimizing the generation of the control sequence.

[0009] Further, the thermodynamic transfer function containing time delay elements is specifically as follows:

[0010] wherein, represents system gain, represents lag time, represents main inertia time constant, represents secondary inertia time constant.

[0011] Further, the model predictive control module realizes online identification of parameters according to a working condition adaptive mechanism, for describing dynamic response characteristics of the cooling water temperature, and specifically as follows: When the main engine power changes by more than a preset threshold, a step response test is triggered to update the system gain in real time ; When the daily average fluctuation of seawater temperature exceeds a set range, the secondary inertia time constant is automatically updated to cope with model mismatch caused by environmental disturbance.

[0012] Further, the adaptive feedback control module online corrects PID parameters according to a combination state of a prediction error and an error change rate , and specifically as follows: When the temperature deviation significantly exceeds a set threshold and shows an accelerating deviation trend, the proportional coefficient is significantly increased ; When the temperature deviation approaches the set threshold, but there is a one-way cumulative trend, the integral coefficient is moderately reduced ; When the temperature fluctuates slightly and the change tends to be stable, the differential coefficient is maintained unchanged.

[0013] Further, a dead zone compensation algorithm is integrated in the driving unit to eliminate the nonlinear error between the valve position and the flow.

[0014] Compared with the prior art, the present application has the following advantages: 1. The present application solves the problems of large overshoot and long regulation time of traditional PID control caused by large inertia and pure lag through the cooperative control means of MPC feedforward optimization and fuzzy PID real-time feedback, improves the cooling water temperature control precision, shortens the regulation time, significantly reduces the cylinder liner thermal stress and wear risk, and prolongs the service life of the main engine.

[0015] 2. The present application realizes real-time correction of the gain, lag time and secondary inertia time constant in the MPC model through online parameter identification and working condition adaptive update mechanism, overcomes the model mismatch problems caused by heat exchanger fouling, seawater temperature fluctuation and the like, maintains the control precision under complex working conditions, and improves the system robustness.

[0016] 3. The application eliminates the nonlinear error caused by the mechanical gap and friction of the electric three-way valve, improves the flow regulation resolution, ensures the accurate control of the cooling water mixing ratio, and reduces energy consumption through the intelligent dead zone compensation algorithm and high-precision driving technology of the stepper motor.

[0017] 4. The application realizes the high-precision, strong robustness and full-condition adaptability of the ship cooling water temperature control through the deep integration of model prediction and fuzzy adaptive control, the optimization design of high-precision actuators and the online adaptive mechanism, provides intelligent support for ship energy efficiency management, and has significant economic benefits and engineering application value.

[0018] In summary, the application realizes the high-precision, strong robustness and full-condition adaptability of the ship cooling water temperature control through the deep integration of model prediction and fuzzy adaptive control, the optimization design of high-precision actuators and the online adaptive mechanism, provides intelligent support for ship energy efficiency management, and has significant economic benefits and engineering application value. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0020] Figure 1 It is a structural schematic diagram of the ship cooling system of the application.

[0021] Figure 2 It is a flow chart of the cooperative prediction control system of the application.

[0022] Figure 3 It is a heat transfer relationship diagram of the main engine cylinder liner cooling of the application.

[0023] In the figure: 1, electric flow regulating valve; 2, controller; 3, temperature sensor; 4, main engine; 5, water maker; 6, main engine cylinder liner water cooler; 7, central cooler; 8, other coolers; 9, low-temperature fresh water pump; 10, high-temperature fresh water pump. DETAILED DESCRIPTION

[0024] In order to make the person skilled in the art better understand the application scheme, the technical solutions in the embodiments of the application will be described clearly and completely in the following with reference to the drawings of the embodiments of the application. Obviously, the described embodiments are only a part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the application.

[0025] It is to be understood that the terms "including", "comprising", "having" and "with" and variations thereof used in the specification and claims of the application and the above summary are intended to cover both the inclusive and exclusive cases, e.g., a process, method, system, product, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly identified as being included in the process, method, system, product, or device, but can include additional steps or elements that are not expressly identified as being included in the process, method, system, product, or device.

[0026] As shown in Figure 1 The ship cooling system structure schematic diagram related to the present application is shown. In order to focus on the core temperature control problem and establish a decoupled analysis model, the actual complex system is simplified in principle and the following assumptions are made in this embodiment: Low-temperature freshwater system flow total control: it is assumed that the circulating total flow of the low-temperature freshwater system is stable (guaranteed by the low-temperature freshwater pump), and the core heat exchange is focused on the high-temperature freshwater cooling link.

[0027] Key heat exchanger selection: in the low-temperature freshwater system, only the main engine cylinder liner cooler 6 and the front central cooler 7 which play a decisive role in the temperature control of the main engine cylinder liner are reserved. Other secondary coolers 8 are equivalent to a plate cooler, and the total heat dissipation power is equivalent to the sum of the actual multi-device heat dissipation.

[0028] High-temperature freshwater loop temperature control core: the core task of the high-temperature freshwater loop is to effectively cool the high-temperature combustion chamber components (cylinder liner, cylinder head, supercharger, etc.) and maintain them in the optimal working temperature window. This loop is self-contained and operates independently because of the high temperature setting and relatively independent flow demand.

[0029] For the high-temperature freshwater loop, when the main engine 4 is working normally, the high-temperature freshwater pump 10 sends high-temperature freshwater to the main engine for cooling the cylinder liner, cylinder head, supercharger and other components. The cooled water flows out from the main engine, and part of the water flows through the water generator through the control valve 5. By adjusting the opening of the electric three-way valve 1, the proportion of the freshwater flowing to the main engine cylinder liner cooler 6 (cooling branch) and the bypass (straight-through branch) is dynamically changed. By changing the proportion of hot water entering the cooler 6, the temperature of the freshwater entering the main engine 4 inlet (temperature ) after mixing is closed-loop precisely adjusted. Finally, the adjusted high-temperature freshwater returns to the high-temperature freshwater pump 10, completing the loop circulation.

[0030] The ship power plant cooling water temperature intelligent control system provided in this embodiment comprises: A temperature detection unit is configured to monitor the temperature of the cooling water of the main engine cylinder liner cooler in real time. A flow regulation execution unit is configured to dynamically adjust the fluid distribution proportion of at least two parallel branches in the cooling water system. The double-layer cooperative control unit adopts Figure 2 The double-layer cooperative control architecture is shown in the figure, the upper layer is a model predictive control module (MPC), and the lower layer is an adaptive feedback control module. The model predictive control module calculates the future state of the system through a rolling optimization algorithm, minimizes the deviation between the set value and the predicted output, and optimizes the generation of the control sequence while considering the influence of seawater temperature disturbance and main engine power change, to generate a feedforward control signal. The adaptive feedback control module fuses the prediction information of the MPC and real-time feedback, online corrects the PID parameters according to the real-time temperature deviation, and outputs the final composite control signal to the driving unit. In this embodiment, the output variable of the adaptive feedback control module is pulse frequency The controller transmits the pulse signal to the driver of the stepper motor to accurately control the rotation angle of the stepper motor. The output pulse frequency calculation formula of the fuzzy adaptive PID controller is as follows:

[0031] The driving unit converts the composite control signal into the driving instruction of the stepper motor and sends it to the flow regulation execution unit.

[0032] In specific implementation, as a preferred embodiment of the present application, the temperature detection unit includes a temperature sensor, which is arranged at the inlet of the main engine cylinder liner cooler cooling water, and has a measurement accuracy of not less than ±0.5℃ and a response time of not more than 2 seconds. In this embodiment, a platinum resistance (Pt100 or Pt1000) or a temperature measuring element with the same accuracy level is selected to ensure real-time feedback of the true value of the inlet temperature.

[0033] In specific implementation, as a preferred embodiment of the present application, the flow regulation execution unit includes an electric flow regulation valve, which is arranged at the inlet of the cooling water branch and is a three-way valve with a stepper motor. The opening degree of the valve is adjusted by the driving of the stepper motor, the mixing ratio of low-temperature fresh water and bypass water is adjusted by changing the resistance of each branch, and the temperature of the main engine cylinder liner cooling water is controlled. In this embodiment, the step angle of the stepper motor is 1.8°, and the response time is not more than 50 milliseconds.

[0034] In specific implementation, as a preferred embodiment of the present application, the model predictive control module calculates the future state of the system through a rolling optimization algorithm, specifically including: Real-time acquisition of cooling water temperature historical data updates the parameters of the model predictive control module, and a thermodynamic transfer function model containing time delay characteristics is adopted; The future temperature change trajectory is calculated through multi-step prediction, and the control sequence is optimized while considering the influence of seawater temperature disturbance and main engine power change.

[0035] In a preferred embodiment of the present application, the thermodynamic transfer function including time delay is specifically as follows:

[0036] wherein, represents system gain, represents lag time, represents main inertia time constant, represents secondary inertia time constant.

[0037] In a preferred embodiment of the present application, the model predictive control module realizes online identification of parameters according to working conditions adaptive mechanism, and is used for describing dynamic response characteristics of cooling water temperature, and is specifically as follows: When the main machine power changes by more than a preset threshold, a step response test is triggered to update the system gain in real time ; When the daily average fluctuation of seawater temperature exceeds a set range, the secondary inertia time constant is automatically updated to cope with model mismatch caused by environmental disturbance.

[0038] In a preferred embodiment of the present application, the adaptive feedback control module is online corrected PID parameters according to the combination state of prediction error and error change rate , and is specifically as follows: When the temperature deviation significantly exceeds a set threshold and shows an accelerating deviation trend, the proportional coefficient is significantly increased ; When the temperature deviation approaches the set threshold, but there is a one-way cumulative trend, the integral coefficient is moderately reduced ; When the temperature fluctuates slightly and the change tends to be stable, the differential coefficient is maintained unchanged .

[0039] In a preferred embodiment of the present application, a dead zone compensation algorithm is integrated in the driving unit to eliminate the nonlinear error between the valve position and the flow. The algorithm overcomes the dead zone influence caused by mechanical clearance and friction of the valve by pre-modeling or real-time learning of the valve flow characteristic curve, significantly eliminates the nonlinear error between the valve position instruction and the actual flow / pressure drop, and realizes high linearity control of opening-flow. Through precise rotation of the stepping motor, the valve core is moved to change the flow resistance between the low-temperature fresh water cooling branch and the bypass. According to the hydraulic characteristics of the parallel pipeline: the sum of the flow rates of each parallel branch is equal to the total inlet flow (mass balance). The resistance loss of each parallel branch is eventually equal (energy balance). The flow of each branch and the impedance of the branch satisfy the following formula:

[0040] where, , and represent the flow rate of each branch, , and represent the impedance of each branch. Thus, by dynamically adjusting the effective impedance (controlled by the valve opening) of the two branches, the precise proportional distribution of the flow rate of the two branches can be achieved, and the final control of the mixed inlet temperature is realized.

[0041] It should be noted that the main cooling object of the cylinder liner of the marine main engine mainly includes: cooling of the cylinder liner part near the combustion chamber of the upper part of the cylinder liner, cooling of the cylinder head, and cooling of the exhaust valve. For the study of the marine high-temperature fresh water circuit, it is not necessary to deeply study the heat exchange process of the cylinder liner of the main engine, so the model of the cylinder liner cooling of the marine main engine is appropriately simplified, that is, the cylinder liner of the marine main engine is regarded as a heat source, and the cylinder liner water is used to cool it. As Figure 3 Fig. 1 shows a simplified diagram of the heat transfer relationship of the cylinder liner cooling of the main engine, and thus the heat transfer relationship of the marine main engine is obtained as follows: Change of heat storage of the cooling water in the cylinder liner and the cylinder liner per unit time Heat transferred to the cylinder liner due to diesel combustion per unit time Heat taken away by the cooling water per unit time, and thus the following equation is obtained:

[0042] In the formula, is the total heat capacity of the cooling water in the cylinder liner and the cylinder liner, where, and are the mass of the cooling water in the cylinder liner and the cylinder liner, respectively; and are the specific heat of the cooling water and the cylinder liner, respectively; is the outlet temperature of the cylinder liner cooling water of the main engine, is the inlet temperature of the cylinder liner cooling water of the diesel engine; is the flow rate of the cylinder liner cooling water, is the heat added to the cooling water per unit time by diesel combustion. The equation illustrates how the load, the inlet cooling water temperature, and the flow rate jointly affect the outlet water temperature and the thermal inertia of the system, and provides a physical basis for the identification of macroscopic thermodynamic parameters by MPC and the basic model characteristics of the control object. Indirectly affecting the internal thermal state and the metal wall temperature by adjusting the inlet temperature is the core logic of the control strategy.

[0043] In summary, the embodiments of the present application elaborated in detail, around the core technology architecture of "model-based predictive feedforward and fuzzy adaptive feedback collaborative control", the establishment of a complete system consisting of high-performance sensors, precision electric regulating valve and control software module. The system creatively combines the model predictive control of the future state of forward-looking optimization ability and fuzzy PID real-time robust adaptive ability to nonlinear error, effectively solve the large low-speed diesel engine cylinder liner cooling water system due to large inertia, pure lag, time-varying and disturbance diversity of the resulting complex temperature control problem.

[0044] Finally, it should be noted that: the above examples are used to illustrate the technical solutions of the present application, rather than limit them; although the present application is described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still be modified to the technical solutions recorded in the foregoing examples, or part or all of the technical features are replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. An intelligent control system for cooling water temperature of a ship power plant, characterized in that: include: Temperature detection unit, used to monitor the temperature of cooling water in the main engine cylinder liner cooler in real time; A flow regulation execution unit, used to dynamically adjust the fluid distribution ratio of at least two parallel branches in the cooling water system; A two-layer collaborative control unit, with the upper layer being the model predictive control module and the lower layer being the adaptive feedback control module. The model predictive control module calculates the future state of the system using a rolling optimization algorithm, generating a feedforward control signal with the goal of minimizing the deviation between the setpoint and the predicted output. The adaptive feedback control module corrects the PID parameters online according to the real-time temperature deviation and outputs the final composite control signal to the drive unit; The driving unit converts the composite control signal into a driving instruction of the stepping motor and sends the instruction to the flow regulation execution unit.

2. The intelligent control system for cooling water temperature of a marine power plant according to claim 1, characterized in that: The temperature detection unit includes a temperature sensor, which is deployed at the inlet of the cooling water of the main engine cylinder liner cooler. The measurement accuracy is not less than ±0.5°C and the response time is no more than 2 seconds.

3. The intelligent control system for cooling water temperature of a marine power plant according to claim 1, characterized in that: The flow regulation execution unit includes an electric flow regulating valve, which is arranged at the inlet of the cooling water branch. It is a three-way regulating valve with a stepper motor. The valve opening is adjusted by driving the stepper motor. By changing the resistance of each branch, the mixing ratio of low-temperature fresh water and bypass water is adjusted to achieve control of the main engine cylinder liner cooling water temperature.

4. The intelligent control system for cooling water temperature of a marine power plant according to claim 1, characterized in that: The model predictive control module calculates the future state of the system through a rolling optimization algorithm, specifically including: Real-time collection of cooling water temperature historical data to update the parameters of the model predictive control module, using a thermodynamic transfer function with time-lag characteristics for modeling; Through multi-step prediction and calculation of future temperature change trajectories, the effects of seawater temperature disturbances and main engine power changes are taken into account when optimizing and generating control sequences.

5. The intelligent control system for cooling water temperature of a marine power plant according to claim 4, characterized in that: The thermodynamic transfer function including the time-delay link is as follows: in, represents the system gain, Indicates the lag time, represents the principal inertia time constant, represents the sub-inertia time constant.

6. The intelligent control system for cooling water temperature of a marine power plant according to claim 5, characterized in that: The model predictive control module implements online parameter identification based on the operating condition adaptive mechanism to describe the dynamic response characteristics of the cooling water temperature, as follows: When the host power change exceeds the preset threshold, the step response test is triggered to update the system gain in real time ; When the daily average fluctuation of seawater temperature exceeds the set range, the sub-inertia time constant is automatically updated , to cope with model mismatch caused by environmental disturbances.

7. The intelligent control system for cooling water temperature of a marine power plant according to claim 1, characterized in that: The adaptive feedback control module is based on the prediction error and error rate of change The PID parameters are corrected online based on the combined state, as follows: When the temperature deviation significantly exceeds the set threshold and shows an accelerating deviation trend, the proportional coefficient is significantly increased. ; When the temperature deviation is close to the set threshold, but there is a unidirectional accumulation trend, moderately reduce the integral coefficient ; When the temperature fluctuates slightly and the change tends to be stable, maintain the differential coefficient constant.

8. The intelligent control system for cooling water temperature of a marine power plant according to claim 1, characterized in that: The drive unit is integrated with a dead zone compensation algorithm to eliminate the nonlinear error between valve position and flow.

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