Defrosting air temperature optimization method and device, storage medium and electronic equipment

Abstract

This disclosure relates to a method, apparatus, storage medium, and electronic device for optimizing defrosting air temperature in a defrosting system. The method includes: setting an initial value for a variable to be optimized; simulating the defrosting process of the defrosting system using a defrosting simulation model based on the current value of the variable to be optimized, to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized; if the obtained defrosting efficiency does not meet a preset defrosting efficiency requirement, calculating the next value of the variable to be optimized using an online gradient descent algorithm based on the rate of change of the defrosting efficiency corresponding to each iteration of the variable to be optimized, and iteratively executing the step of simulating the defrosting process of the defrosting system using a defrosting simulation model based on the current value of the variable to be optimized, until the simulated defrosting efficiency meets the preset defrosting efficiency requirement; and setting the defrosting parameters of the defrosting system based on the final value of the variable to be optimized.

Description

Technical Field

[0001] This disclosure relates to the field of defrosting systems, and more specifically, to a method, apparatus, storage medium, and electronic device for optimizing defrosting air temperature in a defrosting system. Background Technology

[0002] With the introduction of the concepts of carbon emissions and carbon neutrality, international and domestic requirements for improving environmental quality are constantly being upgraded, and vehicle manufacturers are facing more stringent requirements for vehicle emissions and energy consumption. In low-temperature environments, new energy vehicles need to use PTC (Power Transmission Control) to consume electricity to provide defrosting heat, and the vehicle defrosting performance must meet the requirements of national regulations or enterprise design standards. Existing defrosting systems have the problem that their defrosting efficiency cannot meet the defrosting efficiency requirements of national regulations or enterprise design standards. Summary of the Invention

[0003] The purpose of this disclosure is to provide a method, apparatus, storage medium, and electronic device for optimizing defrosting air temperature in a defrosting system, in order to solve the problem that the defrosting efficiency of the defrosting system cannot meet the defrosting efficiency requirements of national regulations or enterprise design standards.

[0004] To achieve the above objectives, the first aspect of this disclosure provides a method for optimizing defrost air temperature in a defrost system, the method comprising:

[0005] Set the initial value of the variable to be optimized, which is a preset variable among the parameters that affect the defrosting efficiency of the defrosting system;

[0006] Based on the current value of the variable to be optimized, the defrosting process of the defrosting system is simulated using a defrosting simulation model to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized.

[0007] If the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, the next value of the variable to be optimized is calculated by using an online gradient descent algorithm based on the rate of change of defrosting efficiency corresponding to each value of the variable to be optimized. Then, the process of simulating the defrosting process of the defrosting system by using a defrosting simulation model based on the current value of the variable to be optimized is returned and executed iteratively until the defrosting efficiency obtained by simulation meets the preset defrosting efficiency requirement.

[0008] The defrosting parameters of the defrosting system are set according to the final value of the variable to be optimized.

[0009] Optionally, the step of calculating the next value of the variable to be optimized using an online gradient descent algorithm based on the rate of change of defrosting efficiency corresponding to each value of the variable to be optimized includes:

[0010] If the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, the defrosting change rate corresponding to the current value is calculated based on the difference between the defrosting efficiency corresponding to the previous value of the variable to be optimized and the defrosting efficiency corresponding to the current value, and the difference between the previous value and the current value, and the calculated defrosting change rate is recorded.

[0011] Based on the defrosting change rate recorded this time and the defrosting change rate in the historical records, the change value of the variable to be optimized is calculated, and the change value is subtracted from the current value to obtain the next value of the variable to be optimized.

[0012] Optionally, the step of calculating the change value of the variable to be optimized based on the defrosting change rate recorded this time and the defrosting change rate in historical records, and subtracting the change value from the current value to obtain the next value of the variable to be optimized, includes:

[0013] The next value of the variable to be optimized is calculated using the following formula:

[0014]

[0015] in, k is the iteration number, C1 and C2 are preset constants, and n i This represents the defrosting change rate calculated in this study. To calculate the norm for the vector formed by the historical defrosting change rate, The values ​​to be taken for the variable to be optimized in this instance. The next value of the variable to be optimized.

[0016] Optionally, the variable to be optimized is the heating power of the heater core;

[0017] Alternatively, the variable to be optimized is the inlet water temperature and water flow rate of the warm air core in the defrosting system;

[0018] Alternatively, the variable to be optimized is the maximum temperature T in the defrosting system. max and a time constant τ, wherein the defrosting system calculates the defrosting air temperature based on the following formula:

[0019]

[0020] Wherein, T is the defrosting air temperature, t is the defrosting time, and Tfrosting is the defrosting time. amb is the ambient temperature constant.

[0021] Optionally, the defrosting efficiency includes a defrosting ratio value within a preset time period, and the defrosting efficiency requirement includes a defrosting ratio requirement value within the preset time period. The method further includes:

[0022] Calculate the difference between the defrost ratio value and the required defrost ratio value;

[0023] If the ratio between the difference and the defrost ratio is greater than zero and less than or equal to a preset threshold, it is determined that the defrost efficiency meets the defrost efficiency requirement.

[0024] If the ratio between the difference and the defrost ratio is less than zero, equal to zero, or greater than the preset threshold, it is determined that the defrost efficiency does not meet the defrost efficiency requirement.

[0025] Optionally, the defrosting efficiency requirements include a defrosting ratio requirement value set for the driver's side glass area A, a defrosting ratio requirement value set for the passenger side glass area A', and a defrosting ratio requirement value set for the windshield glass area B.

[0026] Optionally, the simulation parameters of the defrosting simulation model include window glass parameters, air properties, transient physical parameters, and boundary conditions. The defrosting simulation model is used to simulate the defrosting environment of the defrosting system according to the simulation parameters, take the current value of the variable to be optimized as the value of the variable in the defrosting system, simulate the defrosting process of the defrosting system, and output the defrosting efficiency of the defrosting system in the simulated defrosting process.

[0027] A second aspect of this disclosure provides a defrost air temperature optimization device for a defrost system, the device comprising:

[0028] The assignment module is used to set the initial value of the variable to be optimized, which is a preset variable among the parameters affecting the defrosting efficiency of the defrosting system.

[0029] The simulation calculation module is used to simulate the defrosting process of the defrosting system through a defrosting simulation model based on the value of the variable to be optimized for each time, and to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized.

[0030] The iterative module is used to calculate the next value of the defrosting variable to be optimized based on the rate of change of the defrosting efficiency corresponding to each value of the defrosting system obtained by the simulation calculation module for each simulation of the defrosting system, if the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement. This process continues until the defrosting efficiency obtained by the simulation calculation module for the next value meets the preset defrosting efficiency requirement.

[0031] The parameter setting module is used to set the defrosting parameters of the defrosting system according to the final value of the variable to be optimized.

[0032] A third aspect of this disclosure provides a non-transitory computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the above-described method.

[0033] A fourth aspect of this disclosure provides an electronic device, comprising:

[0034] A memory on which computer programs are stored;

[0035] A processor for executing the computer program in the memory to implement the steps of the above method.

[0036] Using the above method, when the variable to be optimized in the defrosting system does not meet the preset defrosting efficiency requirements, the next value of the variable to be optimized can be calculated based on the rate of change of defrosting efficiency using an online gradient algorithm. In this way, during the iterative update of the value of the variable to be optimized, the value of the variable to be optimized can quickly approach the value that meets the defrosting efficiency requirements. In other words, the defrosting air temperature optimization method provided in this disclosure does not require manual intervention and can automatically and quickly optimize the variable to be optimized in the defrosting system, thereby automatically adjusting the defrosting efficiency of the defrosting system and ensuring that the defrosting parameters of the defrosting system can meet the preset defrosting efficiency of the defrosting system.

[0037] In the application scenario of the defrosting system as a vehicle defrosting system, the above-mentioned defrosting air temperature optimization method can obtain defrosting parameters of the defrosting system that meet the defrosting efficiency requirements of the vehicle. These defrosting parameters can serve as an important basis for the vehicle's thermal management strategy, ensuring that the vehicle can perform internal defrosting in a timely and efficient manner.

[0038] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0039] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0040] Figure 1 This is a schematic flowchart of a defrosting air temperature optimization method provided in an embodiment of this disclosure;

[0041] Figure 2 This is a schematic flowchart of another defrosting air temperature optimization method provided in this embodiment of the disclosure;

[0042] Figure 3 This is a schematic diagram of the structure of a defrosting air temperature optimization device provided in an embodiment of this disclosure;

[0043] Figure 4This is a schematic diagram of another defrosting air temperature optimization device provided in this embodiment. Detailed Implementation

[0044] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0045] The current method for determining defrosting parameters for a defrosting system involves first providing a defrosting air-temperature curve based on past experience. Then, a defrosting simulation model is used to simulate the defrosting process of the system under this curve to obtain the defrosting efficiency. If the defrosting efficiency meets the design requirements, the defrosting air-temperature curve is adopted; otherwise, the curve needs to be modified, and the simulation repeated until the design requirements are met. Since the air-temperature curve consists of a series of temperature points corresponding to time, adjusting the temperature at a single point can lead to discrepancies with physical phenomena. Therefore, researchers need to adjust a series of temperature points based on experience, which is extremely time-consuming and labor-intensive.

[0046] In view of this, embodiments of this disclosure provide a method for optimizing defrost air temperature in a defrost system, such as... Figure 1 As shown, the method includes:

[0047] S101. Set the initial value of the variable to be optimized, wherein the variable to be optimized is a preset variable among the parameters that affect the defrosting efficiency of the defrosting system;

[0048] S102. Based on the current value of the variable to be optimized, the defrosting process of the defrosting system is simulated using a defrosting simulation model to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized.

[0049] S103. If the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, calculate the next value of the variable to be optimized by using an online gradient descent algorithm based on the rate of change of defrosting efficiency corresponding to each value of the variable to be optimized, and return to iteratively execute the step of simulating the defrosting process of the defrosting system by using a defrosting simulation model based on the current value of the variable to be optimized, until the defrosting efficiency obtained by simulation meets the preset defrosting efficiency requirement.

[0050] S104. Set the defrosting parameters of the defrosting system according to the final value of the variable to be optimized.

[0051] Using the above method, when the variable to be optimized in the defrosting system does not meet the preset defrosting efficiency requirements, the next value of the variable to be optimized is calculated using an online gradient algorithm based on the influence relationship of the variable to be optimized on the defrosting efficiency and the rate of change of the value of the variable to be optimized in this iteration, thus rapidly approaching the value of the variable to be optimized that meets the defrosting efficiency requirements of the defrosting system. By iteratively optimizing the value of the variable to be optimized until the final value of the variable to be optimized meets the defrosting efficiency requirements of the defrosting system, the defrosting air temperature optimization method disclosed herein does not require manual intervention and can automatically and quickly optimize the variable to be optimized in the defrosting system, thereby automatically adjusting the defrosting efficiency of the defrosting system and ensuring that the defrosting parameters of the defrosting system can meet the preset defrosting efficiency of the defrosting system.

[0052] In the application scenario of the defrosting system as a vehicle defrosting system, the above-mentioned defrosting air temperature optimization method can obtain defrosting parameters of the defrosting system that meet the defrosting efficiency requirements of the vehicle. These defrosting parameters can serve as an important basis for the vehicle's thermal management strategy, ensuring that the vehicle can perform internal defrosting in a timely and efficient manner.

[0053] The aforementioned preset defrosting efficiency requirements can be defrosting efficiency requirements stipulated by national regulations or enterprise design standards, or defrosting performance requirements set by experimental personnel for the defrosting system. The aforementioned defrosting air temperature optimization method can be applied to vehicle defrosting systems or air conditioning defrosting systems, and this disclosure does not limit it.

[0054] The step of calculating the next value of the variable to be optimized using an online gradient descent algorithm based on the rate of change of defrosting efficiency corresponding to each value of the variable to be optimized includes:

[0055] If the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, the defrosting change rate corresponding to the current value is calculated based on the difference between the defrosting efficiency corresponding to the previous value of the variable to be optimized and the defrosting efficiency corresponding to the current value, and the difference between the previous value and the current value, and the calculated defrosting change rate is recorded.

[0056] Based on the defrosting change rate recorded this time and the defrosting change rate in the historical records, the change value of the variable to be optimized is calculated, and the change value is subtracted from the current value to obtain the next value of the variable to be optimized.

[0057] It is worth noting that by combining the defrost change rate and the defrost change rate in historical records to calculate the change value of the variable to be optimized, the next value of the variable to be optimized is reasonably optimized so that the defrost efficiency corresponding to the next value of the variable to be optimized can be closer to the preset defrost change rate.

[0058] The step of calculating the change value of the variable to be optimized based on the defrosting change rate recorded in the current record and the defrosting change rate in the historical record, and subtracting the change value from the current value to obtain the next value of the variable to be optimized, includes:

[0059] The next value of the variable to be optimized is calculated using the following formula:

[0060]

[0061] in, k is the iteration number, C1 and C2 are preset constants, and n i This represents the defrosting change rate calculated in this study. To calculate the norm for the vector formed by the historical defrosting change rate, The values ​​to be taken for the variable to be optimized in this instance. The next value of the variable to be optimized.

[0062] It is worth noting that, for the variable update step size, the adaptive step size method is used to calculate the variable update step size in the above calculation formula. In other embodiments, the variable update step size can also be calculated using methods such as the fixed step size method, the random method, or the momentum method. The defrost change rate is the gradient of the influence relationship between the variable to be optimized and the defrost efficiency when the variable to be optimized takes that value. The ratio of the norm of the vector formed by the defrost change rate obtained in this calculation and the historical defrost change rate ensures that the iteration of the variable to be optimized has convergence.

[0063] Specifically, the variable to be optimized is the heating power of the heater core;

[0064] Alternatively, the variable to be optimized is the inlet water temperature and water flow rate of the warm air core in the defrosting system;

[0065] Alternatively, the variable to be optimized is the maximum temperature T in the defrosting system. max and a time constant τ, wherein the defrosting system calculates the defrosting air temperature based on the following formula:

[0066]

[0067] Wherein, T is the defrosting air temperature, t is the defrosting time, and Tfrosting is the defrosting time. amb is the ambient temperature constant.

[0068] It is worth noting that in the application scenario where the defrosting system is a vehicle defrosting system, in the above formula for calculating the defrosting air temperature, T amb To conform to the environmental temperature constants stipulated by the regulations of various countries, the defrosting air temperature curve can be derived solely from the maximum temperature T. max The defrosting system is determined by two parameters: time constant τ and time constant τ. Different variables can be selected for optimization in different application scenarios. The selection of these variables is not limited to the three forms mentioned above; they can be any variable that affects defrosting efficiency.

[0069] The defrosting efficiency includes a defrosting ratio value within a preset time period, and the defrosting efficiency requirement includes a defrosting ratio requirement value within the preset time period. The method further includes:

[0070] Calculate the difference between the defrost ratio value and the required defrost ratio value;

[0071] If the ratio between the difference and the defrost ratio is greater than zero and less than or equal to a preset threshold, it is determined that the defrost efficiency meets the defrost efficiency requirement.

[0072] If the ratio between the difference and the defrost ratio is less than zero, equal to zero, or greater than the preset threshold, it is determined that the defrost efficiency does not meet the defrost efficiency requirement.

[0073] The aforementioned preset threshold is a quantity greater than zero, used to indicate the maximum margin that the defrosting ratio value can exceed the required defrosting ratio value. When the difference between the defrosting ratio value and the required defrosting ratio value is greater than the preset threshold, it will result in excessive defrosting performance and energy waste. Therefore, if the ratio between the difference and the defrosting ratio value is less than zero, equal to zero, or greater than the preset threshold, it is determined that the defrosting efficiency does not meet the defrosting efficiency requirement, and the variable to be optimized needs to be further optimized so that the final defrosting efficiency can simultaneously meet the defrosting performance requirement without generating excessive performance and energy waste.

[0074] The preset defrosting efficiency requirement may also include other constraints, such as the defrosting air temperature rise rate or the maximum defrosting air temperature. By adding constraints, the variables to be optimized can be further optimized, and this disclosure does not limit this.

[0075] Specifically, the defrosting efficiency requirements include the defrosting ratio requirement set for the driver's side glass area A, the defrosting ratio requirement set for the passenger side glass area A', and the defrosting ratio requirement set for the windshield area B.

[0076] The defrosting efficiency corresponding to the final value of the variable to be optimized needs to simultaneously meet the defrosting ratio requirements set for the driver's side glass area A, the passenger side glass area A', and the windshield area B of the vehicle, in order to ensure good defrosting performance.

[0077] Specifically, the simulation parameters of the defrosting simulation model include window glass parameters, air properties, transient physical parameters, and boundary conditions. The defrosting simulation model is used to simulate the defrosting environment of the defrosting system according to the simulation parameters, take the current value of the variable to be optimized as the value of the variable in the defrosting system, simulate the defrosting process of the defrosting system, and output the defrosting efficiency of the defrosting system in the simulated defrosting process.

[0078] To enable those skilled in the art to better understand the technical solutions provided in the embodiments of this disclosure, the defrosting air temperature optimization method for a defrosting system provided in the embodiments of this disclosure will be described in detail below, taking the defrosting efficiency as the defrosting ratio value within a preset time as an example.

[0079] Figure 2 This disclosure provides another method for optimizing defrost air temperature in a defrost system, the method comprising:

[0080] S201. Set the initial value of the variable to be optimized.

[0081] The variable to be optimized is a preset variable among the parameters that affect the defrosting efficiency of the defrosting system.

[0082] S202. Based on the current value of the variable to be optimized, the defrosting process of the defrosting system is simulated using a defrosting simulation model to obtain the defrosting ratio of the defrosting system within a preset time under the current value of the variable to be optimized.

[0083] S203. Calculate the difference between the defrost ratio value and the preset defrost ratio requirement value, and determine whether the ratio between the difference and the defrost ratio value is greater than zero and less than or equal to a preset threshold.

[0084] The preset defrosting ratio requirements may include, for example, an 80% defrosting ratio for area A of the driver's side window over a period of 1200 seconds, an 80% defrosting ratio for area A' of the passenger side window over a period of 1500 seconds, and a 95% defrosting ratio for area B of the windshield over a period of 2400 seconds.

[0085] If the ratio between the difference and the defrost ratio is greater than zero and less than or equal to a preset threshold, execute S204; if the ratio between the difference and the defrost ratio is less than zero, equal to zero, or greater than the preset threshold, execute S205 to S206.

[0086] S204. Set the defrosting parameters of the defrosting system according to the final value of the variable to be optimized.

[0087] S205. Based on the difference between the defrosting ratio value corresponding to the previous value of the variable to be optimized and the defrosting ratio value corresponding to the current value, and the difference between the previous value and the current value, calculate the defrosting change rate corresponding to the current value, and record the calculated defrosting change rate.

[0088] S206. Calculate the next value of the variable to be optimized using the following formula:

[0089]

[0090] in, k is the number of iterations, C1 and C2 are preset constants, and ni is the defrosting change rate calculated in this iteration. To calculate the norm for the vector formed by the historical defrosting change rate, The values ​​to be taken for the variable to be optimized in this instance. The next value of the variable to be optimized.

[0091] Using the above method, when the variable to be optimized in the defrosting system does not meet the preset defrosting efficiency requirements, the next value of the variable to be optimized can be calculated based on the rate of change of defrosting efficiency using an online gradient algorithm. In this way, during the iterative update of the value of the variable to be optimized, the value of the variable to be optimized can quickly approach the value that meets the defrosting efficiency requirements. In other words, the defrosting air temperature optimization method provided in this disclosure does not require manual intervention and can automatically and quickly optimize the variable to be optimized in the defrosting system, thereby automatically adjusting the defrosting efficiency of the defrosting system and ensuring that the defrosting parameters of the defrosting system can meet the preset defrosting efficiency of the defrosting system.

[0092] In addition, regarding the above Figure 2 The method embodiments shown are described as a series of actions for the sake of simplicity. However, those skilled in the art should understand that this disclosure is not limited to the described order of actions. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this disclosure.

[0093] This disclosure also provides a defrost air temperature optimization device 300 for a defrost system, which is used to implement the method steps provided in the above-described method embodiments, such as... Figure 3 As shown, the device 300 includes:

[0094] The assignment module 301 is used to set the initial value of the variable to be optimized, wherein the variable to be optimized is a preset variable among the parameters affecting the defrosting efficiency of the defrosting system;

[0095] The simulation calculation module 302 is used to simulate the defrosting process of the defrosting system through a defrosting simulation model based on the value of the variable to be optimized for each time, and to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized.

[0096] The iteration module 303 is used to calculate the next value of the defrosting variable to be optimized by using an online gradient descent algorithm, based on the rate of change of the defrosting efficiency corresponding to each value of the defrosting system obtained by the simulation calculation module for the next value, if the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement.

[0097] The parameter setting module 304 is used to set the defrosting parameters of the defrosting system according to the final value of the variable to be optimized.

[0098] Specifically, the device 300 further includes:

[0099] The first calculation module is used to calculate the defrosting change rate corresponding to the current value based on the difference between the defrosting efficiency corresponding to the previous value of the variable to be optimized and the defrosting efficiency corresponding to the current value, and the difference between the previous value and the current value, when the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, and to record the calculated defrosting change rate.

[0100] The iteration module 303 also includes a second calculation module, which is used to calculate the change value of the variable to be optimized based on the defrosting change rate recorded this time and the defrosting change rate in the historical records, and subtract the change value from the current value to obtain the next value of the variable to be optimized.

[0101] Specifically, the second calculation module is also used to: calculate the next value of the variable to be optimized using the following formula:

[0102]

[0103] in, k is the iteration number, C1 and C2 are preset constants, and n i This represents the defrosting change rate calculated in this study. To calculate the norm for the vector formed by the historical defrosting change rate, The values ​​to be taken for the variable to be optimized in this instance. The next value of the variable to be optimized.

[0104] Specifically, the device 300 further includes a calculation and judgment module, which is used to calculate the difference between the defrost ratio value and the defrost ratio requirement value;

[0105] If the ratio between the difference and the defrost ratio is greater than zero and less than or equal to a preset threshold, it is determined that the defrost efficiency meets the defrost efficiency requirement.

[0106] If the ratio between the difference and the defrost ratio is less than zero, equal to zero, or greater than the preset threshold, it is determined that the defrost efficiency does not meet the defrost efficiency requirement.

[0107] Regarding the apparatus 300 in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0108] This disclosure also provides an electronic device, including: a memory storing a computer program thereon; and a processor for executing the computer program in the memory to implement the steps of the above method.

[0109] Figure 4 This is a block diagram illustrating an electronic device 400 according to an exemplary embodiment. Figure 4 As shown, the electronic device 400 may include a processor 401 and a memory 402. The electronic device 400 may also include an input / output (I / O) interface 403.

[0110] The processor 401 controls the overall operation of the electronic device 400 to complete all or part of the steps in the above-described method for optimizing the defrost air temperature of the defrost system. The memory 402 stores various types of data to support the operation of the electronic device 400. This data may include, for example, instructions for any application or method operating on the electronic device 400, as well as application-related data such as variables to be optimized, window glass parameters, air properties, transient physical parameters, and boundary conditions. The memory 402 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The I / O interface 403 provides an interface between the processor 401 and other interface modules.

[0111] In an exemplary embodiment, the electronic device 400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described defrosting air temperature optimization method for a defrosting system.

[0112] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the method steps of the above-described method for optimizing defrost air temperature for a defrost system.

[0113] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0114] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0115] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method for optimizing defrosting air temperature in a defrosting system, characterized in that, The method includes: Set the initial value of the variable to be optimized, which is a preset variable among the parameters that affect the defrosting efficiency of the defrosting system; Based on the current value of the variable to be optimized, the defrosting process of the defrosting system is simulated using a defrosting simulation model to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized. If the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, the next value of the variable to be optimized is calculated using an online gradient descent algorithm based on the rate of change of defrosting efficiency corresponding to each value of the variable to be optimized. Then, based on the next value of the variable to be optimized, the process of simulating the defrosting process of the defrosting system using a defrosting simulation model is iteratively executed until the simulated defrosting efficiency meets the preset defrosting efficiency requirement. The next value of the variable to be optimized is obtained by calculating the change value of the variable to be optimized based on the current recorded rate of change and the historical rate of change of defrosting efficiency, and then subtracting the change value from the current value. The defrosting parameters of the defrosting system are set according to the final value of the variable to be optimized; The next value of the variable to be optimized is calculated using the following formula: ； in, k is the number of iterations, C1 and C2 are preset constants, and n i This represents the defrosting change rate calculated in this study. To calculate the norm for a vector consisting of historical defrosting change rates, The values ​​to be taken for the variable to be optimized in this instance. The next value of the variable to be optimized.

2. The method according to claim 1, characterized in that, The defrosting change rate was obtained in the following way: If the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement, the defrosting change rate corresponding to the current value is calculated based on the difference between the defrosting efficiency corresponding to the previous value of the variable to be optimized and the defrosting efficiency corresponding to the current value, as well as the difference between the previous value and the current value, and the calculated defrosting change rate is recorded.

3. The method according to claim 1, characterized in that, The variable to be optimized is the heating power of the heater core; Alternatively, the variable to be optimized is the inlet water temperature and water flow rate of the warm air core in the defrosting system; Alternatively, the variable to be optimized is the maximum temperature in the defrosting system. and a time constant τ, wherein the defrosting system calculates the defrosting air temperature based on the following formula: Among them, the t represents the defrosting air temperature, and t represents the defrosting time. is the ambient temperature constant.

4. The method according to any one of claims 1-3, characterized in that, The defrosting efficiency includes a defrosting ratio value within a preset time period, and the defrosting efficiency requirement includes a defrosting ratio requirement value within the preset time period. The method further includes: Calculate the difference between the defrost ratio value and the required defrost ratio value; If the ratio between the difference and the defrost ratio is greater than zero and less than or equal to a preset threshold, it is determined that the defrost efficiency meets the defrost efficiency requirement. If the ratio between the difference and the defrost ratio is less than zero, equal to zero, or greater than the preset threshold, it is determined that the defrost efficiency does not meet the defrost efficiency requirement.

5. The method according to claim 4, characterized in that, The defrosting efficiency requirements include the defrosting ratio requirement set for the driver's side glass area A, the defrosting ratio requirement set for the passenger side glass area A', and the defrosting ratio requirement set for the windshield area B.

6. The method according to any one of claims 1-3, characterized in that, The simulation parameters of the defrosting simulation model include window glass parameters, air properties, transient physical parameters, and boundary conditions. The defrosting simulation model is used to simulate the defrosting environment of the defrosting system according to the simulation parameters, take the current value of the variable to be optimized as the value of the variable in the defrosting system, simulate the defrosting process of the defrosting system, and output the defrosting efficiency of the defrosting system in the simulated defrosting process.

7. A defrosting air temperature optimization device for a defrosting system, characterized in that, The device includes: The assignment module is used to set the initial value of the variable to be optimized, which is a preset variable among the parameters that affect the defrosting efficiency of the defrosting system; The simulation calculation module is used to simulate the defrosting process of the defrosting system through a defrosting simulation model based on the value of the variable to be optimized for each time, and to obtain the defrosting efficiency of the defrosting system under the current value of the variable to be optimized. The iterative module is used to calculate the next value of the defrosting variable to be optimized based on the rate of change of the defrosting efficiency corresponding to each value of the defrosting system obtained by the simulation calculation module for each simulation of the defrosting system, if the obtained defrosting efficiency does not meet the preset defrosting efficiency requirement. This process continues until the defrosting efficiency obtained by the simulation calculation module for the next value meets the preset defrosting efficiency requirement. The iteration module includes a second calculation module, which is used to calculate the change value of the variable to be optimized based on the defrost change rate recorded this time and the defrost change rate in the historical records, and subtract the change value from the current value to obtain the next value of the variable to be optimized. The parameter setting module is used to set the defrosting parameters of the defrosting system according to the final value of the variable to be optimized. The second calculation module is also used for: The next value of the variable to be optimized is calculated using the following formula: ； in, k is the number of iterations, C1 and C2 are preset constants, and n i This represents the defrosting change rate calculated in this study. To calculate the norm for a vector consisting of historical defrosting change rates, The values ​​to be taken for the variable to be optimized in this instance. The next value of the variable to be optimized.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method described in any one of claims 1-6.

9. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-6.

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