Gas water heater, simulation model optimization method thereof and computer readable storage medium
By matching actual and simulated data of gas water heaters, the component models in the simulation model were optimized, solving the problem of insufficient accuracy of the simulation model under different environments, and achieving good operating performance of gas water heaters.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- WUHU MIDEA KITCHEN & BATH APPLIANCES MFG CO LTD
- Filing Date
- 2024-11-27
- Publication Date
- 2026-05-29
AI Technical Summary
Simulation models of gas water heaters cannot accurately reflect their behavior in the actual working environments of different households, leading to deviations in operating performance and affecting the operating effect of gas water heaters.
By matching actual working data of gas water heaters with simulated working data, mismatched datasets are filtered out, the working characteristic curves of component models in the simulation model are optimized, and a target simulation model is generated to improve accuracy.
This improves the accuracy of the simulation model of the gas water heater in the actual working environment, ensuring that the gas water heater can achieve good operating performance.
Smart Images
Figure CN122113336A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of gas water heater control technology, and in particular to a gas water heater and its simulation model optimization method, and a computer-readable storage medium. Background Technology
[0002] Gas water heaters are commonly used hot water production equipment in households, and are favored by users for their high energy efficiency, fast heating speed and simple installation process.
[0003] To ensure that gas water heaters achieve good operating performance, a simulation model of the gas water heater can be used to simulate its operation and simulate optimal control parameters.
[0004] However, due to physical factors such as geographical location and installation conditions, the operation of gas water heaters varies in different households. This means that the simulation model of the gas water heater built under standard conditions cannot accurately reflect the behavior of the gas water heater in the actual working environment. The simulation results will deviate from the actual operating results of the gas water heater, thus affecting the operating performance of the gas water heater. Summary of the Invention
[0005] The main purpose of this application is to provide a gas water heater and its simulation model optimization method, as well as a computer-readable storage medium, which aims to improve the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model, so as to enable the gas water heater to achieve good operating performance.
[0006] To achieve the above objectives, this application provides a simulation model optimization method for a gas water heater, the method comprising:
[0007] At least one set of actual working data of the gas water heater is obtained, and the simulated working data of the gas water heater is obtained. The actual working data and the simulated working data are matched pairwise to filter out the simulated working data that do not match the actual working data, so as to obtain the working dataset.
[0008] Based on the working dataset, at least one component model to be optimized in the simulation model is determined, and the working characteristic curve image of each component model to be optimized is optimized to optimize the simulation model of the gas water heater and obtain the target simulation model.
[0009] The gas water heater is controlled based on the target simulation model.
[0010] In one embodiment, where the actual working data includes actual running data and the simulated working data includes simulated running data, the working dataset is a running dataset;
[0011] The step of determining at least one component model to be optimized in the simulation model based on the working dataset includes:
[0012] For any running data in the running dataset, the component model used in the simulation model to simulate the running data is taken as the component model to be optimized.
[0013] In one embodiment, the operating characteristic curve image includes operating characteristic curves, and the step of optimizing the operating characteristic curve images of each of the component models to be optimized includes:
[0014] For any of the component models to be optimized, obtain the actual operating data associated with the component model to be optimized from the actual operating data, and use them as the associated operating data.
[0015] Based on the associated operational data, the target operating characteristic curve of the component model to be optimized is generated;
[0016] The working characteristic curve of the component model to be optimized is adjusted to the target working characteristic curve.
[0017] In one embodiment, where the actual working data includes actual performance data and the simulated working data includes simulated performance data, the working dataset is a performance dataset;
[0018] The step of determining at least one component model to be optimized in the simulation model based on the working dataset includes:
[0019] For any performance data in the performance dataset, the target operating data corresponding to the performance data is obtained based on the preset mapping relationship between the performance data and the operating data of the gas water heater.
[0020] The component models used in the simulation model to simulate the target running data are taken as the component models to be optimized.
[0021] In one embodiment, the step of optimizing the working characteristic curve images of each of the component models to be optimized includes:
[0022] For any of the component models to be optimized, adjust the target operating data simulated by the component model to optimize the working characteristic curve image of the component model.
[0023] In one embodiment, prior to the step of obtaining at least one set of actual operating data of the gas water heater, the method further includes:
[0024] The ratio of the feedback control quantity to the feedforward control quantity of the gas water heater is obtained to get the control quantity ratio.
[0025] If the control ratio is greater than the preset control ratio threshold, then the step of obtaining at least one set of actual working data of the gas water heater is executed.
[0026] In one embodiment, prior to the step of obtaining at least one set of actual operating data of the gas water heater, the method further includes:
[0027] Obtain the target operating performance index value of the gas water heater;
[0028] If the target operating performance index value is less than or equal to the preset performance index threshold, then the step of obtaining at least one set of actual operating data of the gas water heater is executed.
[0029] In one embodiment, the step of obtaining the target operating performance index value of the gas water heater includes:
[0030] Obtain the current operating data of the gas water heater;
[0031] The current running data is input into a pre-trained running performance evaluation model to obtain the current running performance index value;
[0032] The target operating performance index value is determined based on the current operating performance index value and the historical operating performance index values of the gas water heater within a preset period.
[0033] In addition, to achieve the above objectives, this application also provides a gas water heater, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the simulation model optimization method for the gas water heater as described above.
[0034] In addition, to achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the simulation model optimization method for a gas water heater as described above.
[0035] In addition, to achieve the above objectives, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the simulation model optimization method for gas water heaters as described above.
[0036] This application provides a method for optimizing a simulation model of a gas water heater. First, at least one set of actual operating data of the gas water heater and at least one set of simulated operating data of the simulation model of the gas water heater are obtained. Then, each set of actual operating data and each set of simulated operating data are matched pairwise to identify which gas water heater operating data is not accurately reflected by the simulation model, thus obtaining a working dataset. Next, based on the working dataset, at least one component model in the simulation model is identified as needing optimization; that is, the component model causing the working dataset to be inaccurately reflected is selected from the component models in the simulation model. Then, by optimizing the operating characteristic curves of each component model to be optimized, the simulation model of the gas water heater can be optimized to obtain a target simulation model, thereby improving the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model. Finally, based on the target simulation model, the operation of the gas water heater is controlled, enabling the gas water heater to achieve good operating performance. Attached Figure Description
[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0038] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0039] Figure 1 A flowchart illustrating the simulation model optimization method for a gas water heater provided in the first embodiment of this application;
[0040] Figure 2 A flowchart illustrating the preprocessing of actual working data provided in the first embodiment of this application;
[0041] Figure 3 A schematic diagram showing the working characteristic curves of the gas proportional valve provided in the embodiments of this application before and after optimization;
[0042] Figure 4 A schematic diagram showing the working characteristic curves of the fan provided in the embodiments of this application before and after optimization;
[0043] Figure 5 A schematic diagram illustrating the interaction principle between the runtime data and the simulation model provided in the embodiments of this application;
[0044] Figure 6 The optimized principle diagram of the simulation model provided in the embodiments of this application;
[0045] Figure 7 This is a schematic diagram of the hardware operating environment involved in the embodiments of this application.
[0046] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0047] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.
[0048] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.
[0049] Gas water heaters are commonly used hot water production equipment in households, and are favored by users for their high energy efficiency, fast heating speed and simple installation process.
[0050] To ensure that gas water heaters achieve good operating performance, a simulation model of the gas water heater can be used to simulate its operation and simulate optimal control parameters.
[0051] However, due to physical factors such as geographical location and installation conditions, the operation of gas water heaters varies in different households. This means that the simulation model of the gas water heater built under standard conditions cannot accurately reflect the behavior of the gas water heater in the actual working environment. The simulation results will deviate from the actual operating results of the gas water heater, thus affecting the operating performance of the gas water heater.
[0052] Based on this, this application provides a method for optimizing a simulation model of a gas water heater. First, at least one set of actual operating data of the gas water heater and at least one set of simulated operating data of the simulation model of the gas water heater are obtained. Then, each set of actual operating data and each set of simulated operating data are matched pairwise to identify which gas water heater operating data are not accurately reflected by the simulation model, thus obtaining a working dataset. Next, based on the working dataset, at least one component model to be optimized in the simulation model is identified, that is, the component model that causes the working dataset to be inaccurately reflected is selected from the component models in the simulation model. Then, by optimizing the operating characteristic curves of each component model to be optimized, the simulation model of the gas water heater can be optimized to obtain a target simulation model, thereby improving the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model. Finally, based on the target simulation model, the operation of the gas water heater is controlled, enabling the gas water heater to achieve good operating performance.
[0053] The subject of the simulation model optimization method for gas water heaters in this application can be a gas water heater, household appliance, industrial equipment, etc., with data processing, network communication and program operation functions, or a control system, control circuit, etc., that can realize the above functions. This embodiment does not specifically limit it.
[0054] The following description uses a gas water heater as the main implementer to illustrate the various embodiments.
[0055] Based on this, this application proposes a simulation model optimization method for a gas water heater according to the first embodiment. Please refer to [link / reference]. Figure 1 The simulation model optimization method for gas water heaters includes steps S10 to S40:
[0056] Step S10: Obtain at least one set of actual working data of the gas water heater, and at least one set of simulated working data of the simulation model of the gas water heater;
[0057] It should be noted that a set of actual working data may include multiple sets of actual working data, which refers to the working data fed back by the gas water heater in actual operation; a set of simulated working data may include multiple sets of simulated working data, which refers to the working data of the gas water heater simulated by the simulation model of the gas water heater; working data may include, but is not limited to, the operating data of the gas water heater (i.e., data used to feed back the operating status of the gas water heater, such as the opening degree of the gas proportional valve, the fan speed, etc.) and / or performance data (i.e., data used to feed back the performance status of the gas water heater, such as the outlet water temperature of the gas water heater, etc.).
[0058] Additionally, it should be noted that the actual operating data of the gas water heater can be obtained from the local device (i.e., the gas water heater) or from other devices connected to the local device; this embodiment does not specifically limit this. The actual operating data obtained from other devices connected to the local device is usually data that has undergone some preprocessing (e.g., data cleaning, standardization, and normalization); while the actual operating data obtained from the local device is usually unprocessed. Therefore, to improve data usability and ensure the accuracy of the matching results when performing pairwise data matching later, please refer to... Figure 2 After obtaining the actual working data of the gas water heater, the actual working data can be cleaned first (including missing value handling and outlier handling) to eliminate abnormal data and delete duplicate data. Then, the cleaned actual working data can be organized (including data standardization and normalization, data partitioning and analysis) to obtain the final actual working data.
[0059] In the preprocessing of actual work data, the equipment used to perform preprocessing operations can divide the data processing area into multiple sub-areas, each capable of performing different operations on the data. For example, it could be divided into area A and area B, where area A is used for data cleaning and area B for data organization. Furthermore, data query efficiency can be improved by creating data indexes, and security can be ensured through regular data backups.
[0060] Step S20: Match each actual working data with each simulated working data pairwise to filter out each simulated working data that does not match the actual working data, and obtain the working dataset.
[0061] It should be noted that the working dataset can include simulation data that does not match the actual working data. A mismatch means that two sets of data are inconsistent. For example, suppose the actual working data shows an outlet water temperature of 40℃, while the simulation data shows an outlet water temperature of 35℃. These two are inconsistent, therefore they do not match.
[0062] Step S30: Based on the working dataset, determine at least one component model to be optimized in the simulation model, and optimize the working characteristic curve image of each component model to be optimized in order to optimize the simulation model of the gas water heater and obtain the target simulation model.
[0063] It should be noted that the simulation of a gas water heater consists of multiple component models, which are used to simulate the operation of real components. The component model to be optimized, as the component model in the simulation model, refers to the component model that causes the working data set to be inaccurately reflected, i.e., the problematic component model. The operating characteristic curve image includes the operating characteristic curve of the component model to be optimized. The operating characteristic curve is used to characterize the mapping relationship between the operating data and characteristic data of the component model to be optimized. For example, assuming the component model to be optimized is a gas proportional valve, its operating data can include the opening degree of the gas proportional valve, and its characteristic data can include gas flow rate and / or gas pressure, etc.; as another example, assuming the component model to be optimized is a fan, its operating data can include the fan speed, and its characteristic data can include air volume, air force, and / or pressure difference, etc. The target simulation model refers to the optimized simulation model of the gas water heater.
[0064] Step S40: Control the operation of the gas water heater based on the target simulation model.
[0065] This embodiment provides a method for optimizing a simulation model of a gas water heater. First, at least one set of actual operating data of the gas water heater and at least one set of simulated operating data of the simulation model of the gas water heater are obtained. Then, each set of actual operating data and each set of simulated operating data are matched pairwise to identify which gas water heater operating data is not accurately reflected by the simulation model, thus obtaining a working dataset. Next, based on the working dataset, at least one component model in the simulation model is identified as needing optimization; that is, the component model that causes the working dataset to be inaccurately reflected is selected from the component models in the simulation model. Then, by optimizing the operating characteristic curves of each component model to be optimized, the simulation model of the gas water heater can be optimized to obtain a target simulation model, thereby improving the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model. Finally, based on the target simulation model, the operation of the gas water heater is controlled, enabling the gas water heater to achieve good operating performance.
[0066] Based on the first embodiment described above, a second embodiment of the simulation model optimization method for gas water heaters of this application is proposed. In the second embodiment, when the actual working data includes actual operating data and the simulated working data includes simulated operating data, the working dataset is the operating dataset; step S30 may include step S31:
[0067] Step S31: For any running data in the running dataset, the component model used in the simulation model to simulate the running data is taken as the component model to be optimized.
[0068] It is understandable that the simulation model includes component models, each used to simulate the operation of different components in a gas water heater. Therefore, this embodiment uses a forward derivation approach to directly identify which specific gas water heater operating data are not accurately reflected in the simulation model. The component models used to simulate this operating data are then designated as the component models to be optimized. This allows for the accurate identification of which specific component models in the simulation model are causing the model to fail to accurately reflect the behavior of the gas water heater in its actual operating environment.
[0069] Furthermore, the working characteristic curve image includes working characteristic curves, and the step of optimizing the working characteristic curve image of each component model to be optimized may include steps S301 to S303:
[0070] Step S301: For any component model to be optimized, obtain the actual operating data associated with the component model to be optimized from the actual operating data, and use them as the associated operating data.
[0071] Step S302: Based on the associated operational data, generate the target working characteristic curve of the component model to be optimized;
[0072] It should be noted that during the process of generating the target operating characteristic curve of the component model to be optimized based on the associated operating data, the simulation model can use the associated operating data and the corresponding characteristic data to re-analyze the mapping relationship between the operating data and characteristic data of the component model to be optimized. Then, the re-analyzed mapping relationship between the operating data and characteristic data of the component model to be optimized is represented by a curve, thus obtaining the target operating characteristic curve. However, considering that some component models (such as fans, gas proportional valves, etc.) are mainly modeled using mechanistic data fusion, the mapping relationship between the operating data and characteristic data of these component models usually cannot be represented by relevant mathematical functions. In this case, data interpolation can be used to construct the operating characteristic curve of these component models (i.e., a curve composed of multiple data points).
[0073] Step S303: Adjust the working characteristic curve of the component model to be optimized to the target working characteristic curve.
[0074] Understandably, when using the forward derivation method, since it is possible to determine which specific operational data are problematic, the correct operational data (i.e., actual operational data) can be directly used to regenerate the working characteristic curves of the component model to be optimized.
[0075] For example, to help understand the optimization process of the working characteristic curve of the component model to be optimized, taking the component model to be optimized as a gas proportional valve, the operating data of the gas proportional valve as the opening degree of the gas proportional valve, and the characteristic data of the gas proportional valve as the gas flow rate as an example, please refer to... Figure 3 ;
[0076] By utilizing a set of actual operating data containing the opening degree of each gas proportional valve and the gas flow rate corresponding to each opening degree, it is possible to regenerate... Figure 3 The target operating characteristic curve of the gas proportional valve shown (i.e. Figure 3 (The black curve in the image). Therefore, by changing the operating characteristic curve of the gas proportional valve from... Figure 3 By adjusting the red curve in the curve to a black curve, the operating characteristic curve of the gas proportional valve can be optimized.
[0077] For example, taking the model of the component to be optimized as a fan, the fan's operating data as fan speed, and the fan's characteristic data as air volume as an example, please refer to... Figure 4 :
[0078] By utilizing a set of actual operating data containing the fan speeds and corresponding air volumes for each fan speed, it is possible to regenerate... Figure 4 The target operating characteristic curve of the wind turbine is shown in Figure 4 (i.e., the black curve in 4). Therefore, by changing the operating characteristic curve of the wind turbine from... Figure 4 By adjusting the red curve in the image to the black curve, the operating characteristic curve of the fan can be optimized.
[0079] Please refer to Figure 5 After the feedback data (i.e. actual working data) of the gas water heater is input into the simulation model, the simulation model will first collect statistics on each actual working data 1 to k. After the statistics are completed, the data will be integrated to determine the characteristic data corresponding to the feedback data, and the integrated data will be input into the corresponding component model (i.e. the component model to be optimized).
[0080] Further, please refer to Figure 6 After inputting the feedback data from the gas water heater into the simulation model, you can view the component data (i.e., the simulated operating data) and characteristic data of each component model in the simulation model. For example, in the figure, N_MF_0 and N_MF_1 represent the component data and characteristic data of the fan, respectively, and mf_dp_0 and mf_dp_1 represent the component data and characteristic data of the gas proportional valve, respectively. Furthermore, you can access the parameter setting interface for each component model within the simulation model.
[0081] It should be noted that this example is only for the purpose of assisting in understanding this application and does not constitute a limitation on the simulation model optimization method of the gas water heater in this application. Any simple modifications based on this technical concept are within the protection scope of this application.
[0082] Based on the first embodiment described above, a third embodiment of the simulation model optimization method for gas water heaters of this application is proposed. In the third embodiment, when the actual working data includes actual performance data and the simulated working data includes simulated performance data, the working dataset is a performance dataset; step S30 may include steps S32 to S33:
[0083] Step S32: For any performance data in the performance dataset, obtain the target operating data corresponding to the performance data based on the preset mapping relationship between the performance data and the operating data of the gas water heater.
[0084] It should be noted that target operating data refers to operating data that has a mapping relationship with performance data. For example, if the performance data is the outlet water temperature, then the corresponding target operating data could be the opening degree of the gas proportional valve. A relational table can be used to record the mapping relationship between the performance data and the operating data of the gas water heater. Therefore, step S32 can include: using the performance data as an index to find the target operating data corresponding to the performance data in a preset relational table; alternatively, a key-value storage system (such as Redis or Memcached) can be used to record the mapping relationship between the performance data and the operating data of the gas water heater, where the performance data is the key and the operating data is the value. This embodiment does not impose specific limitations on this.
[0085] Step S33: The component models used in the simulation model to simulate the target running data are taken as the component models to be optimized.
[0086] In this embodiment, a reverse derivation approach is used to first identify the specific performance issues of the gas water heater. Then, based on these problematic performance issues, it's deduced which operational data of the gas water heater affects those performance factors. Finally, the component models used in the simulation model to simulate these operational data are used as component models to be optimized. For example, assuming the gas water heater has a problem with excessively high outlet water temperature, reverse derivation reveals that the excessive outlet water temperature is caused by excessive gas flow in the gas water heater. Since the opening degree of the gas proportional valve affects the gas flow, the gas proportional valve can be used as a component model to be optimized.
[0087] It is understandable that, compared to the second embodiment described above, this embodiment demonstrates higher accuracy in determining the component models to be optimized. Specifically, assuming that the simulation model's inability to accurately reflect the behavior of the gas water heater in the actual working environment is due to component models A, B, and C, the second embodiment could accurately analyze that all three components (A, B, and C) should be considered as component models to be optimized. However, this embodiment attributes all causes to component model A, thus only analyzing that component model A needs to be optimized, without considering that component models B and C also need to be optimized.
[0088] Furthermore, the step of optimizing the working characteristic curve images of each component model to be optimized may include step S304:
[0089] Step S304: For any component model to be optimized, adjust the target running data simulated by the component model to optimize the working characteristic curve image of the component model.
[0090] Understandably, the essence of using the reverse derivation method is to analyze whether the target operating data simulated by the model of the component to be optimized is too large or too small. Therefore, by directly adjusting the target operating data simulated by the model of the component to be optimized (if the target operating data is too large, then decrease the target operating data; if the target operating data is too small, then increase the target operating data), the working characteristic curve image of the model of the component to be optimized can be optimized.
[0091] Based on the first, second, and / or third embodiments described above, a fourth embodiment of the simulation model optimization method for gas water heaters is proposed. In the fourth embodiment, before step S10, the simulation model optimization method for gas water heaters may further include steps S01 to S02:
[0092] Step S01: Obtain the ratio of the feedback control quantity to the feedforward control quantity of the gas water heater to obtain the control quantity ratio;
[0093] It should be noted that the feedback control quantity refers to the control quantity in the feedback control of a gas water heater. In a gas water heater, feedback control is a control method that monitors the deviation between the actual output (i.e., the actual outlet water temperature) and the desired output (i.e., the target outlet water temperature) of the gas water heater, and adjusts the opening of the gas proportional valve accordingly to make the actual output of the gas water heater closer to the desired output. The feedback control quantity can be calculated using the difference between the actual outlet water temperature and the target outlet water temperature (i.e., the outlet water temperature that the gas water heater needs to achieve). The specific calculation process can be found in Formula 1 below:
[0094]
[0095] Where u1 is the feedback control quantity, L is the gain coefficient, r is the target outlet water temperature, z1 is the actual outlet water temperature, z2 is the disturbance term, and b is the proportional coefficient.
[0096] Additionally, it should be noted that the feedforward control quantity refers to the control quantity in the feedforward control of a gas water heater. In gas water heaters, feedforward control typically refers to adjusting the opening of the gas proportional valve in advance based on preset water demand (such as set water temperature, water flow rate, etc.) to compensate for water temperature fluctuations caused by changes in water demand. The feedforward control quantity of a gas water heater can be calculated using the water flow rate of the gas water heater and the temperature difference between the set temperature and the inlet water temperature. The specific calculation process can be found in Formula 2 below:
[0097] u2=γ(T set -T in Formula 2
[0098] Where u2 is the feedforward control quantity, γ is the proportional coefficient, and Tset To set the temperature, T in Where is the inlet water temperature, and F is the water flow rate.
[0099] Step S02: If the control ratio is greater than the preset control ratio threshold, then execute the step of obtaining at least one set of actual working data of the gas water heater.
[0100] It should be noted that the preset control quantity ratio threshold is used as the basis for determining whether the simulation model of the gas water heater needs to be optimized. The preset control quantity ratio threshold can be a default value or can be flexibly set by the user according to the actual situation. This embodiment does not impose specific limitations on this.
[0101] Understandably, when a gas water heater operates well, its feedback control quantity will remain around a stable value, and therefore the ratio of the feedback control quantity to the feedforward control quantity will also tend towards a stable value. When the gas water heater's operating performance deteriorates, its feedback control quantity will continuously increase in one direction, so the ratio of the feedback control quantity to the feedforward control quantity will gradually increase as well. Therefore, this embodiment, by utilizing the ratio of the gas water heater's feedback control quantity to its feedforward control quantity, can accurately assess the gas water heater's operating performance, thereby accurately evaluating whether the simulation model of the gas water heater needs optimization.
[0102] In other embodiments, it can also be determined directly whether the feedback control quantity is too large to assess whether the simulation model of the gas water heater needs to be optimized. Specifically, if the feedback control quantity of the gas water heater is greater than a preset control quantity threshold, then the step of obtaining at least one set of actual operating data of the gas water heater is executed. The preset control quantity threshold serves as the basis for determining whether the simulation model of the gas water heater needs to be optimized. The preset control quantity threshold can be a default value or can be flexibly set by the user according to actual conditions; this embodiment does not impose specific limitations on this.
[0103] Based on the first, second, third, and / or fourth embodiments described above, a fifth embodiment of the simulation model optimization method for gas water heaters of this application is proposed. In the fifth embodiment, before step S10, the simulation model optimization method for gas water heaters may further include steps S03 to S04:
[0104] Step S03: Obtain the target operating performance index value of the gas water heater;
[0105] It should be noted that the target operating performance index value is used to characterize the overall operating performance of the gas water heater over a certain period of time; the target operating performance index value is positively correlated with the operating performance of the gas water heater, that is, the larger the target operating performance index value, the better the operating performance of the gas water heater, and the smaller the target operating performance index value, the worse the operating performance of the gas water heater.
[0106] In one possible implementation of step S03, steps S031 to S033 may be included:
[0107] Step S031: Obtain the current operating data of the gas water heater;
[0108] It should be noted that the current operating data refers to the operating data of the gas water heater at the current moment. The operating data of the gas water heater may include, but is not limited to, the opening degree of the gas proportional valve, the fan speed, etc. This embodiment does not make specific limitations on this.
[0109] Step S032: Input the current running data into the pre-trained running performance evaluation model to obtain the current running performance index value;
[0110] It should be noted that the operational performance evaluation model is used to evaluate the operational performance of gas water heaters. The current operational performance index value is used to characterize the operational performance of the gas water heater at the current operating moment.
[0111] Additionally, it should be noted that multiple training samples can be constructed. Each training sample includes an input feature and a corresponding training label. The input feature can be constructed from the historical operating data of the gas water heater, and the training label can include the heating rate and / or constant temperature duration of the gas water heater. Then, the model is iteratively trained using each training sample to obtain the operating performance evaluation model.
[0112] Step S033: Determine the target operating performance index value based on the current operating performance index value and the historical operating performance index values of the gas water heater within the preset period.
[0113] It should be noted that the preset period can be a default period, such as one week (i.e., seven days); or it can be flexibly set by the user according to the actual situation, and this embodiment does not impose specific limitations on it. The historical operating performance index value is used to characterize the operating performance of the gas water heater at historical operating times.
[0114] When determining the target operating performance index value based on the current operating performance index value and the historical operating performance index values of the gas water heater within a preset period, the target operating performance index value can be the average of the current operating performance index value and the historical operating performance index values of the gas water heater within the preset period; alternatively, the operating performance index value that appears most frequently among the current operating performance index value and the historical operating performance index values of the gas water heater within the preset period can be used as the target operating performance index value; or the average of the maximum and minimum operating performance index values among the current operating performance index value and the historical operating performance index values of the gas water heater within the preset period can be used as the target operating performance index value. This embodiment does not specifically limit the specific implementation of step S033.
[0115] In determining the target operating performance index value, this embodiment simultaneously refers to the current operating performance index value of the gas water heater and the historical operating performance index values of the gas water heater within a preset period. Therefore, it can ensure that the determined target operating performance index value can reflect the overall operating performance of the gas water heater within a certain period of time, thereby ensuring the accuracy of the determined target operating performance index value and ensuring that the simulation model of the gas water heater can be accurately evaluated subsequently to determine whether optimization is needed.
[0116] Step S04: If the target operating performance index value is less than or equal to the preset performance index threshold, then execute the step of obtaining at least one set of actual operating data of the gas water heater.
[0117] It should be noted that the preset performance index threshold is used as the basis for determining whether the simulation model of the gas water heater needs to be optimized. The preset performance index threshold can be a default value, such as 85; or it can be flexibly set by the user according to the actual situation. This embodiment does not make specific limitations on this.
[0118] This embodiment directly utilizes the target operating performance index value, which characterizes the overall operating performance of a gas water heater over a certain period of time, to evaluate whether the simulation model of the gas water heater needs to be optimized. This ensures that when the operating performance of the gas water heater is poor, the simulation model of the gas water heater can be optimized in a timely manner.
[0119] Based on the first, second, third, fourth, and / or fifth embodiments described above, a sixth embodiment of the simulation model optimization method for gas water heaters is proposed. In this sixth embodiment, to ensure that the final simulation model used to control the operation of the gas water heater can accurately reflect the behavior of the gas water heater in the actual working environment, after step S30, the gas water heater can be simulated using the target simulation model to obtain new simulated working data. Then, the new simulated working data is compared and verified with the actual working data of the gas water heater to verify whether the optimized simulation model can accurately reflect the behavior of the gas water heater in the actual working environment (it can be verified whether the deviation between the simulation results and the actual operating results of the gas water heater is less than a certain value). If not, the simulation model of the gas water heater is iteratively optimized.
[0120] This application also provides a gas water heater, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to execute the simulation model optimization method for the gas water heater in the above embodiments.
[0121] The following is for reference. Figure 7 It shows a structural schematic diagram of a gas water heater suitable for implementing the embodiments of this application. Figure 7 The gas water heater shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.
[0122] like Figure 7As shown, the gas water heater may include a processing device 101 (e.g., a central processing unit, a graphics processor, etc.) that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 102 or a program loaded from a storage device 103 into a random access memory (RAM) 104. The RAM 104 also stores various programs and data required for the operation of the gas water heater. The processing device 101, ROM 102, and RAM 104 are interconnected via a bus 105. An input / output (I / O) interface 106 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 106: input devices 107 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 108 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 103 including, for example, magnetic tape, hard disk, etc.; and communication devices 109. Communication device 109 allows the gas water heater to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show gas water heaters with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.
[0123] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 103, or installed from ROM 102. When the computer program is executed by processing device 101, it performs the functions defined in the methods of the embodiments of this application.
[0124] The gas water heater provided in this application embodiment employs the simulation model optimization method for gas water heaters described in the above embodiments. This improves the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model, enabling the gas water heater to achieve good operating performance. Compared with the prior art, the beneficial effects of the gas water heater provided in this application embodiment are the same as those of the simulation model optimization method for gas water heaters provided in the above embodiments. Furthermore, other technical features of this gas water heater are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.
[0125] It should be understood that various parts of the embodiments of this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.
[0126] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the above claims.
[0127] This application also provides a computer-readable storage medium storing a computer program that can run on a processor. The computer program is used to execute the simulation model optimization method for a gas water heater in the above embodiments.
[0128] The computer-readable storage medium provided in this application embodiment may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.
[0129] The aforementioned computer-readable storage medium may be included in the gas water heater; or it may exist independently and not be installed in the gas water heater.
[0130] The aforementioned computer-readable storage medium carries one or more programs. When the gas water heater executes the aforementioned one or more programs, the gas water heater causes the gas water heater to: acquire at least one set of actual operating data of the gas water heater, and acquire at least one set of simulated operating data of the simulation model of the gas water heater; match each set of actual operating data with each set of simulated operating data pairwise to filter out each set of simulated operating data that does not match the actual operating data, thereby obtaining a working dataset; based on the working dataset, determine at least one component model to be optimized in the simulation model, and optimize the operating characteristic curve image of each component model to be optimized, thereby optimizing the simulation model of the gas water heater and obtaining a target simulation model; and control the operation of the gas water heater based on the target simulation model.
[0131] Computer program code for performing the operations of this disclosure can be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, and C++, and conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0132] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0133] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.
[0134] The computer-readable storage medium provided in this application embodiment stores computer-readable program instructions for executing the above-described simulation model optimization method for gas water heaters. This improves the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model, enabling the gas water heater to achieve good operating performance. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application embodiment are the same as those of the simulation model optimization method for gas water heaters provided in the above embodiments, and will not be repeated here.
[0135] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the simulation model optimization method for a gas water heater as described above.
[0136] The computer program product provided in this application can improve the accuracy of the gas water heater's behavior in the actual working environment as reflected by the simulation model, thereby enabling the gas water heater to achieve good operating performance. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the gas water heater simulation model optimization method provided in the above embodiments, and will not be repeated here.
[0137] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.
Claims
1. A method for optimizing a simulation model of a gas water heater, characterized in that, The method includes: Obtain at least one set of actual operating data of the gas water heater, and obtain at least one set of simulated operating data of the simulation model of the gas water heater; The actual working data and the simulated working data are matched pairwise to filter out the simulated working data that do not match the actual working data, thus obtaining the working dataset. Based on the working dataset, at least one component model to be optimized in the simulation model is determined, and the working characteristic curve image of each component model to be optimized is optimized to optimize the simulation model of the gas water heater and obtain the target simulation model. The gas water heater is controlled based on the target simulation model.
2. The simulation model optimization method for gas water heaters as described in claim 1, characterized in that, In the case where the actual working data includes actual operating data and the simulated working data includes simulated operating data, the working dataset is the operating dataset; The step of determining at least one component model to be optimized in the simulation model based on the working dataset includes: For any running data in the running dataset, the component model used to simulate the running data in the simulation model is taken as the component model to be optimized.
3. The simulation model optimization method for gas water heaters as described in claim 2, characterized in that, The operating characteristic curve image includes operating characteristic curves, and the step of optimizing the operating characteristic curve images of each of the component models to be optimized includes: For any of the component models to be optimized, obtain the actual operating data associated with the component model to be optimized from the actual operating data, and use them as the associated operating data. Based on the associated operational data, the target operating characteristic curve of the component model to be optimized is generated; The working characteristic curve of the component model to be optimized is adjusted to the target working characteristic curve.
4. The simulation model optimization method for gas water heaters as described in claim 1, characterized in that, In the case where the actual working data includes actual performance data and the simulated working data includes simulated performance data, the working dataset is a performance dataset; The step of determining at least one component model to be optimized in the simulation model based on the working dataset includes: For any performance data in the performance dataset, the target operating data corresponding to the performance data is obtained based on the preset mapping relationship between the performance data and the operating data of the gas water heater. The component models used in the simulation model to simulate the target running data are taken as the component models to be optimized.
5. The simulation model optimization method for a gas water heater as described in claim 4, characterized in that, The step of optimizing the working characteristic curve images of each of the component models to be optimized includes: For any of the component models to be optimized, adjust the target operating data simulated by the component model to optimize the working characteristic curve image of the component model.
6. The simulation model optimization method for a gas water heater as described in any one of claims 1 to 5, characterized in that, Before the step of obtaining at least one set of actual operating data of the gas water heater, the method further includes: The ratio of the feedback control quantity to the feedforward control quantity of the gas water heater is obtained to get the control quantity ratio. If the control ratio is greater than the preset control ratio threshold, then the step of obtaining at least one set of actual working data of the gas water heater is executed.
7. The simulation model optimization method for a gas water heater as described in any one of claims 1 to 5, characterized in that, Before the step of obtaining at least one set of actual operating data of the gas water heater, the method further includes: Obtain the target operating performance index value of the gas water heater; If the target operating performance index value is less than or equal to the preset performance index threshold, then the step of obtaining at least one set of actual operating data of the gas water heater is executed.
8. The simulation model optimization method for a gas water heater as described in claim 7, characterized in that, The step of obtaining the target operating performance index value of the gas water heater includes: Obtain the current operating data of the gas water heater; The current running data is input into a pre-trained running performance evaluation model to obtain the current running performance index value; The target operating performance index value is determined based on the current operating performance index value and the historical operating performance index values of the gas water heater within a preset period.
9. A gas water heater, characterized in that, The gas water heater includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the simulation model optimization method for the gas water heater according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the simulation model optimization method for the gas water heater as described in any one of claims 1 to 8.