Multi-mode switching control method and system for smoothie preparation

Abstract

The application relates to the field of ice maker control, and discloses a multi-mode switching control method and system for smoothie preparation, which comprises the following steps: acquiring a smoothie preparation relationship curve of different ice hardness, smoothie preparation parameters and smoothie fineness; acquiring an ice hardness value and a smoothie fineness adjustment value; determining a smoothie preparation adjustment parameter according to the ice hardness value and the smoothie fineness adjustment value through the smoothie preparation relationship curve; acquiring a corrected smoothie fineness adjustment value corresponding to the smoothie preparation adjustment parameter; and when the corrected smoothie fineness adjustment value is greater than or equal to a preset corrected smoothie fineness adjustment value, adjusting ice block preparation parameters of an ice making module to adjust the ice hardness; wherein the difference between a smoothie fineness target value after the smoothie preparation adjustment parameter is determined and an actual smoothie fineness value is taken as the corrected smoothie fineness adjustment value. The application can keep the smoothie fineness stable.

Description

Technical Field

[0001] This application relates to the field of ice maker control technology, and more specifically, to a multi-mode switching control method and system for shaved ice preparation. Background Technology

[0002] With the increasing demand for diverse ice products in both home and commercial settings, integrated ice makers have emerged on the market. These machines combine an ice-making module and a slush-making module. The ice-making module uses components such as a compressor and evaporator to cool and condense water into ice cubes, while the slush-making module is equipped with crushing blades or grinding components to crush and grind the ice cubes produced by the ice-making module to create slush. Furthermore, these ice makers are equipped with a function switching mechanism, allowing users to switch between ice-making and slush-making modes via a control panel. These ice makers are widely used in home kitchens, milk tea shops, convenience stores, and other settings to meet users' immediate needs for different forms of ice products.

[0003] In existing integrated ice makers, slush preparation relies on the crushing blades or grinding components to process the ice blocks generated by the ice-making module. However, the hardness of the ice blocks generated by the ice-making module varies depending on factors such as ice-making time and cooling temperature. The crushing blades or grinding components of existing slush preparation modules typically operate with fixed parameters such as rotation speed and crushing time, failing to adapt to changes in ice hardness. This results in fluctuations in the fineness of the slush due to the influence of ice hardness, making it difficult to maintain stability and meet users' requirements for consistent slush quality. Summary of the Invention

[0004] The purpose of this application is to provide a multi-mode switching control method and system for shaved ice preparation, which solves the technical problem that the fineness of the shaved ice fluctuates due to the influence of the hardness of the ice, and achieves the technical effect of maintaining the fineness of the shaved ice.

[0005] This application provides a multi-mode switching control method for slush preparation. The method includes: acquiring slush preparation relationship curves with preset different ice hardness, slush preparation parameters, and slush fineness; acquiring ice hardness values ​​and slush fineness adjustment values; wherein the slush preparation parameters include ice hardness values, crushing speed, and crushing time; determining the ice hardness value of the ice block to be crushed through a correlation model of ice-making temperature and ice-making time; determining the difference between the target value and the actual value of slush fineness as the slush fineness adjustment value; and using the slush preparation relationship curves, adjusting the slush fineness based on the ice hardness... The ice-making module determines the ice-making adjustment parameters based on the ice-making adjustment values ​​and the ice-smoothness adjustment values. These parameters include the crushing adjustment speed and crushing adjustment time. The ice-making process is adjusted using these parameters. A corrected ice-smoothness adjustment value is obtained corresponding to the adjusted parameters. When the corrected ice-smoothness adjustment value is greater than or equal to the preset corrected ice-smoothness adjustment value, the ice-making module's ice-making parameters are adjusted to adjust the ice hardness. The difference between the target ice-smoothness value and the actual ice-smoothness value after determining the adjusted parameters is used as the corrected ice-smoothness adjustment value.

[0006] In one possible implementation, when the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, the ice preparation parameters of the ice-making module are adjusted to adjust the ice hardness, including: obtaining an ice preparation relationship curve; determining an adjusted ice hardness value based on the ice hardness value and the corrected slush coarseness adjustment value using the slush preparation relationship curve; wherein the ice preparation relationship curve includes the correspondence between ice-making temperature, ice-making time, and ice hardness; and determining the adjusted ice preparation parameters based on the adjusted ice hardness value using the ice preparation relationship curve to adjust the ice hardness.

[0007] In another possible implementation, the method further includes: when the corrected slush coarseness adjustment value is less than the preset corrected slush coarseness adjustment value, determining the slush preparation adjustment parameters based on the ice hardness value and the corrected slush coarseness adjustment value through the slush preparation relationship curve; and adjusting the slush preparation process through the slush preparation adjustment parameters.

[0008] In another possible implementation, the method further includes: sieving the slush through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture; determining the maximum weight of the slush among the weights of the slush corresponding to each sieve aperture; obtaining the aperture of the sieve corresponding to the maximum weight of the slush as the actual value of the slush coarseness; and determining the difference between the target value of the slush coarseness and the actual value of the slush coarseness as the slush coarseness adjustment value.

[0009] In another possible implementation, the method further includes: determining the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module; determining the ratio of the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module to the product of the reciprocal of the minimum ice-making temperature, the maximum ice-making quantity, and the maximum ice-making time, as the ice quantity coefficient; obtaining a minimum ice quantity coefficient threshold and an optimal ice quantity coefficient threshold, wherein the optimal ice quantity coefficient threshold is greater than the minimum ice quantity coefficient threshold; when the slush preparation process is started, obtaining the real-time ice quantity coefficient of the ice-making module; when the real-time ice quantity coefficient is less than the minimum ice quantity coefficient threshold, extending the ice-making time according to a first proportional value and increasing the compressor speed according to a second proportional value to increase the real-time ice quantity coefficient; when the real-time ice quantity coefficient is greater than or equal to the minimum ice quantity coefficient threshold and less than the optimal ice quantity coefficient threshold, increasing the compressor speed according to the second proportional value to increase the real-time ice quantity coefficient; when the real-time ice quantity coefficient is greater than or equal to the optimal ice quantity coefficient threshold, switching to the slush preparation process.

[0010] In another possible implementation, the method further includes: when the corrected slush fineness adjustment value is greater than or equal to the preset corrected slush fineness adjustment value, increasing the ice-making time and compressor speed to increase the ice quantity coefficient according to the preset increase, and adjusting the ice preparation parameters of the ice-making module to adjust the ice hardness.

[0011] In another possible implementation, the method further includes: when the slush preparation process is started, obtaining the real-time ice quantity coefficient of the ice-making module and obtaining historical ice preparation parameters for adjusting ice hardness; when the real-time ice quantity coefficient is less than the minimum ice quantity coefficient threshold, extending the ice-making time according to a first proportional value and increasing the compressor speed according to a second proportional value to increase the real-time ice quantity coefficient, and adjusting the ice preparation parameters according to the product of the historical ice preparation parameters and a third proportional value; when the real-time ice quantity coefficient is greater than or equal to the minimum ice quantity coefficient threshold and less than the optimal ice quantity coefficient threshold, increasing the compressor speed according to a second proportional value to increase the real-time ice quantity coefficient, and adjusting the ice preparation parameters according to the product of the historical ice preparation parameters and a fourth proportional value.

[0012] In another possible implementation, the method further includes: sieving the slush through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture; determining the weight increment of the slush corresponding to each sieve aperture; and determining the ice preparation parameters to adjust the ice hardness by using a slush preparation adjustment parameter mapping table, based on the target value of slush coarseness and the weight increment of the slush corresponding to each sieve aperture.

[0013] In another possible implementation, the method further includes: when the fineness adjustment value of the shaved ice is greater than or equal to the preset fineness adjustment value, the prepared shaved ice is transported to the shaved ice melting chamber to melt and then enter the ice-making cycle; when the fineness adjustment value of the shaved ice is less than the preset fineness adjustment value, the prepared shaved ice is output from the shaved ice outlet.

[0014] This application also provides a multi-mode switching control system for slush preparation, including a unit for implementing the above-described multi-mode switching control method for slush preparation.

[0015] The beneficial effects of the embodiments of this application compared with the prior art are:

[0016] This application provides a multi-mode switching control method for slush preparation. The method includes: acquiring slush preparation relationship curves with preset different ice hardness, slush preparation parameters, and slush coarseness; acquiring ice hardness values ​​and slush coarseness adjustment values; determining slush preparation adjustment parameters based on the ice hardness values ​​and slush coarseness adjustment values ​​using the slush preparation relationship curves; acquiring corrected slush coarseness adjustment values ​​corresponding to the slush preparation adjustment parameters; and adjusting the ice preparation parameters of the ice-making module to adjust the ice hardness when the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value. The method in this application obtains the corrected slush coarseness adjustment value corresponding to the slush preparation adjustment parameters. When the corrected slush coarseness adjustment value is greater than or equal to the preset value, the ice preparation parameters of the ice-making module are adjusted for further optimization. Through closed-loop feedback, the ice-making process is continuously adjusted, and the slush coarseness is continuously calibrated, significantly improving the consistency of different batches of slush products. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating the first multi-mode switching control method for smoothie preparation provided in this application embodiment;

[0019] Figure 2 A schematic diagram illustrating the workflow of the first multi-mode switching control method for smoothie preparation provided in this application embodiment;

[0020] Figure 3 A flowchart illustrating the second multi-mode switching control method for smoothie preparation provided in this application embodiment;

[0021] Figure 4 A schematic diagram illustrating the workflow of the second multi-mode switching control method for smoothie preparation provided in this application embodiment;

[0022] Figure 5 A schematic diagram illustrating the workflow of the third multi-mode switching control method for smoothie preparation provided in this application embodiment;

[0023] Figure 6 A flowchart illustrating the fourth multi-mode switching control method for smoothie preparation provided in this application embodiment;

[0024] Figure 7 This is a schematic diagram of the logic structure of a multi-mode switching control system for smoothie preparation provided in an embodiment of this application. Detailed Implementation

[0025] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0026] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0027] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0028] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0029] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0030] In existing integrated ice makers that can simultaneously make ice cubes and slushies, the fineness of the slushies fluctuates due to the hardness of the ice cubes, making it difficult to maintain stability and meet users' demand for consistent slushie quality.

[0031] Based on the above reasons, this application provides a multi-mode switching control method for slush preparation. The method includes: acquiring slush preparation relationship curves with preset different ice hardness, slush preparation parameters, and slush fineness; acquiring ice hardness values ​​and slush fineness adjustment values; wherein, the slush preparation parameters include ice hardness values, crushing speed, and crushing time; determining the ice hardness value of the ice block to be crushed through a correlation model of ice-making temperature and ice-making time; determining the difference between the target slush fineness value and the actual slush fineness value as the slush fineness adjustment value; and using the slush preparation relationship curves, adjusting the slush fineness based on the ice hardness value and the actual slush fineness value. The method in this application determines the slush preparation adjustment parameters by using the block hardness value and the slush coarseness adjustment value. These parameters include the crushing adjustment speed and crushing adjustment time. The slush preparation process is adjusted using these parameters. A corrected slush coarseness adjustment value is obtained corresponding to the adjusted parameters. When the corrected slush coarseness adjustment value is greater than or equal to a preset corrected slush coarseness adjustment value, the ice block preparation parameters of the ice-making module are adjusted to adjust the ice block hardness. The difference between the target slush coarseness value and the actual slush coarseness value after determining the adjusted parameters is used as the corrected slush coarseness adjustment value. The method in this embodiment obtains the corrected slush coarseness adjustment value corresponding to the slush preparation adjustment parameters. When the corrected slush coarseness adjustment value is greater than or equal to a preset value, the ice block preparation parameters of the ice-making module are further optimized. Through closed-loop feedback, the ice-making process is continuously adjusted, and the slush coarseness is continuously calibrated, significantly improving the consistency of different batches of finished slush products.

[0032] In some scenarios, the multi-mode switching control method for slush preparation according to an embodiment of this application can be applied to the slush preparation of ice makers that can simultaneously make ice cubes and slush, thereby improving the stability of slush production by the ice maker and enhancing the performance of the ice maker.

[0033] The following describes in detail, with specific examples, a multi-mode switching control method for smoothie preparation provided in the embodiments of this application.

[0034] Figure 1 A flowchart illustrating the first multi-mode switching control method for smoothie preparation provided in this application embodiment is shown below. Figure 1 As shown in the embodiment of this application, a multi-mode switching control method for shaved ice preparation is provided, including S110 to S130. S110 to S130 will be described in detail below.

[0035] S110. Obtain the relationship curves of ice slush preparation with different preset ice hardness, slush preparation parameters, and slush fineness. Obtain the ice hardness value and slush fineness adjustment value. The slush preparation parameters include ice hardness value, crushing speed, and crushing time. The ice hardness value of the ice block to be crushed is determined through a correlation model between ice-making temperature and ice-making time. The difference between the target slush fineness value and the actual slush fineness value is used as the slush fineness adjustment value.

[0036] Figure 2 A schematic diagram of the workflow of the first multi-mode switching control method for smoothie preparation provided in this application embodiment is shown below. Figure 2 As shown, in this implementation, ice slush preparation relationship curves with different preset ice hardness, ice slush preparation parameters and ice slush fineness can be obtained. The ice slush preparation relationship curves are used to characterize the correspondence between ice hardness, crushing speed, crushing time and ice slush fineness.

[0037] In this implementation, the ice hardness value and the fineness adjustment value of the slush can also be obtained. The slush preparation parameters include the ice hardness value, crushing speed and crushing time.

[0038] For example, during the operation of the slush machine, a slush preparation relationship curve can be established in advance through experimental data. The slush preparation relationship curve can reflect the crushing speed and crushing time required to obtain a specific slush fineness under different ice hardness. The preparation parameters matching the current ice hardness can be quickly determined through the slush preparation relationship curve.

[0039] In this implementation, there is a correlation between ice-making temperature, ice-making time, and ice hardness during ice preparation. The ice hardness value of the ice to be crushed can be determined by the correlation model between ice-making temperature and ice-making time. The ice-making temperature and ice-making time can be recorded and obtained by the control system of the ice blender.

[0040] For example, the correlation model between ice-making temperature and ice-making time can be a table showing the correspondence between ice-making temperature, ice-making time, and ice hardness. The ice-making temperature, ice-making time, and ice hardness can be stored in the control system of the smoothie machine in tabular form.

[0041] In this implementation, the difference between the target value and the actual value of the fineness of the slush can be used as the fineness adjustment value of the slush. The slush preparation process can then be adjusted using the fineness adjustment value.

[0042] S120. Using the slush preparation relationship curve, determine the slush preparation adjustment parameters based on the ice hardness value and slush fineness adjustment value. These parameters include the crushing adjustment speed and crushing adjustment time.

[0043] In this implementation, the ice slush preparation adjustment parameters can be determined based on the ice hardness value and the ice slush fineness adjustment value through the ice slush preparation relationship curve. Then, the ice slush preparation parameters can be adjusted through the ice slush preparation adjustment parameters to make a preliminary adjustment to the ice slush fineness.

[0044] For example, when determining the slush preparation adjustment parameters based on the ice hardness value and the slush coarseness adjustment value, the target slush preparation parameters can be determined by using the slush preparation relationship curve based on the ice hardness value and the target slush coarseness adjustment value. The difference between the target slush preparation parameters and the current slush preparation parameters can be determined as the slush preparation adjustment parameters.

[0045] In this implementation, the parameters for preparing shaved ice include the crushing speed and the crushing time. By adjusting the crushing speed and the crushing time, the crushing parameters of the crushing process can be adjusted to adjust the particle size of the shaved ice.

[0046] S130. Adjust the slush preparation process by adjusting the slush preparation parameters. Obtain the corrected slush coarseness adjustment value corresponding to the slush preparation adjustment parameters. When the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, adjust the ice preparation parameters of the ice-making module to adjust the ice hardness. The difference between the target slush coarseness value after determining the slush preparation adjustment parameters and the actual slush coarseness value is used as the corrected slush coarseness adjustment value.

[0047] like Figure 2 As shown, in this implementation, the slush preparation process can be adjusted by adjusting the slush preparation parameters to achieve a preliminary adjustment of the slush particle size.

[0048] After adjusting the slush preparation process, the corrected slush coarseness adjustment value corresponding to the slush preparation adjustment parameters can be obtained. The corrected slush coarseness adjustment value can also be obtained by re-evaluating the slush coarseness, thereby realizing the evaluation of the adjustment effect of slush coarseness.

[0049] For example, the difference between the target value of the fineness of the smoothie after adjusting the parameters and the actual value of the fineness of the smoothie can be determined as the corrected fineness adjustment value.

[0050] In this implementation, when the corrected fineness adjustment value of the slush is greater than or equal to the preset corrected fineness adjustment value of the slush, the ice preparation parameters of the ice-making module can be adjusted to adjust the ice hardness, and then the particle size of the slush preparation can be adjusted according to the ice hardness.

[0051] For example, during the preparation of shaved ice, when the corrected shaved ice fineness adjustment value is greater than or equal to the preset corrected shaved ice fineness adjustment value, parameters such as the ice-making temperature or ice-making time of the ice-making module can be adjusted to change the hardness characteristics of the ice blocks prepared subsequently. Furthermore, by adjusting the hardness of the ice blocks through depth, it can be ensured that the fineness of the shaved ice is always kept within the ideal range.

[0052] This method obtains a preset curve showing the relationship between ice hardness, slush preparation parameters, and slush coarseness. Then, it obtains the ice hardness value and slush coarseness adjustment value, determines the slush preparation adjustment parameters based on the curve, and achieves precise parameter correspondence through preset relationships. Ultimately, it can quickly match different ice hardness and slush coarseness requirements, improving the accuracy of slush preparation parameter settings.

[0053] This method determines the hardness value of the ice block to be crushed by the correlation between ice-making temperature and ice-making time. It then obtains an adjustment value by combining the target value and the actual value of the slush coarseness. The preparation process is adjusted by adjusting the slush preparation parameters, dynamically capturing key parameters and controlling them in real time. This achieves dynamic optimization of the slush preparation process, reduces preparation deviations, and ensures the stability of the preparation process.

[0054] This implementation method obtains the corrected fineness adjustment value of the slush preparation adjustment parameters. When the corrected fineness adjustment value is greater than or equal to the preset value, the ice preparation parameters of the ice making module are further optimized. Through closed-loop feedback, the ice making process is continuously adjusted, the fineness of the slush is continuously calibrated, and the consistency of different batches of slush products is greatly improved.

[0055] In some implementations, S130 above includes adjusting the ice block preparation parameters of the ice-making module to adjust the ice block hardness when the corrected ice slush fineness adjustment value is greater than or equal to the preset corrected ice slush fineness adjustment value. It also includes S131 to S132, which will be explained in detail below.

[0056] S131. Obtain the ice preparation relationship curve. Based on the ice hardness value and the adjusted slush coarseness value, determine the adjusted ice hardness value using the ice preparation relationship curve. The ice preparation relationship curve includes the correspondence between ice-making temperature, ice-making time, and ice hardness.

[0057] In this implementation, when the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, the ice preparation parameters of the ice-making module are further adjusted to adjust the ice hardness. This can be achieved by obtaining the ice preparation relationship curve, which contains the correspondence between ice-making temperature, ice-making time, and ice hardness. These parameters can reflect the intrinsic relationship between key control variables and the physical properties of ice during the ice-making process.

[0058] For example, during the process of making ice blocks and ice slush simultaneously in an ice slush machine, the ice-making temperature and ice-making time can be recorded by temperature sensors and timers. Then, the ice-making temperature and ice-making time can be controlled by the corresponding curve of ice-making temperature, ice-making time and ice hardness.

[0059] In this implementation, the ice hardness adjustment value can be determined based on the ice hardness value and the modified ice fineness adjustment value using the ice slush preparation relationship curve in S120. The ice slush preparation relationship curve characterizes the intrinsic relationship between ice hardness, ice fineness, and preparation parameters. The ice hardness adjustment amount required to meet the target ice fineness can be determined through the ice slush preparation relationship curve. When calculating the ice hardness adjustment amount, the target ice hardness value can be determined first, and then the difference between the target ice hardness value and the ice hardness value can be determined as the ice hardness adjustment amount.

[0060] For example, when the adjusted value for the fineness of the smoothie is detected to exceed a preset standard, the degree of matching between the current ice hardness value and the target fineness of the smoothie can be analyzed using the smoothie preparation relationship curve, thereby calculating the required adjusted ice hardness value. This calculation can take into account the influence mechanism of ice hardness on the particle size of the finished smoothie.

[0061] S132. By using the ice preparation relationship curve, adjust the ice preparation parameters according to the ice hardness value to adjust the ice hardness.

[0062] In this implementation, the ice preparation parameters can be adjusted to adjust the ice hardness by using the ice preparation relationship curve and adjusting the ice hardness value. The ice preparation relationship curve can provide a mapping relationship between ice making temperature, ice making time and ice hardness. The combination of ice making parameters that need to be adjusted can be derived from the target ice hardness value.

[0063] For example, when determining the ice preparation parameters based on the ice preparation relationship curve and the ice hardness value, the target ice preparation parameters can be determined based on the target ice hardness. Subsequently, the difference between the target ice preparation parameters and the current ice preparation parameters can be determined as the ice preparation parameters to be adjusted.

[0064] For example, based on the calculated ice hardness adjustment value, the corresponding ice-making temperature adjustment amount and ice-making time adjustment amount can be determined by querying the ice preparation relationship curve. These adjustment parameters can be directly applied to the control system of the ice-making module to achieve precise control of ice hardness.

[0065] This method obtains the ice preparation relationship curve, combines it with the slush preparation relationship curve, determines the ice hardness adjustment value based on the ice hardness value and the adjusted slush coarseness value, and then determines the adjusted ice preparation parameters through the ice preparation relationship curve. By using the two curves, the ice making and slush preparation parameters are accurately matched, enabling more precise control of the ice preparation parameters and significantly improving the control accuracy of ice hardness.

[0066] This implementation method establishes a parameter correlation between the ice-making and ice-sand preparation stages by using an ice block preparation relationship curve when the adjustment value for the fineness of the ice slush does not meet the standard. First, the adjustment value for the hardness of the ice block is determined, and then the adjustment scheme for the ice-making parameters is derived. Through the parameter linkage logic between the ice-making and ice-sand preparation stages, precise coordination between ice-making and ice-sand preparation is achieved, reducing the lag in parameter adjustment and improving the coherence of the overall preparation process.

[0067] This method precisely controls the relationship between ice temperature, ice-making time, and ice hardness using the ice preparation relationship curve. It also optimizes the ice hardness value by combining it with the shaved ice preparation relationship curve, thereby adjusting the ice-making parameters. Through dual-curve calibration, it ensures that the ice hardness matches the shaved ice preparation requirements, significantly reducing the probability of exceeding the standard for adjusting the fineness of the shaved ice and improving the stability and consistency of the fineness of the finished shaved ice.

[0068] In some implementations, the above method further includes: when the corrected slush coarseness adjustment value is less than the preset corrected slush coarseness adjustment value, determining slush preparation adjustment parameters based on the ice hardness value and the corrected slush coarseness adjustment value using the slush preparation relationship curve. The slush preparation process is then adjusted using these parameters.

[0069] In this implementation, the corrected smoothie coarseness adjustment value reflects the actual smoothie coarseness adjustment effect of the smoothie coarseness adjustment parameter. The preset corrected smoothie coarseness adjustment value can be used as a reference benchmark to judge whether the calibration effect meets the standard. When the corrected smoothie coarseness adjustment value is less than the preset corrected smoothie coarseness adjustment value, the smoothie preparation parameters can be fine-tuned by adjusting the corrected smoothie coarseness adjustment value to adjust the smoothie preparation process.

[0070] For example, during the preparation of smoothies in a smoothie machine, if the corrected smoothie coarseness adjustment value is detected to be less than the preset corrected smoothie coarseness adjustment value, it indicates that the current smoothie coarseness adjustment parameter calibration effect has not reached the expected target. Further fine-tuning of the smoothie preparation process can be used to improve the smoothie preparation effect.

[0071] For example, when determining the slush preparation adjustment parameters based on the ice hardness value and the corrected slush coarseness adjustment value using the slush preparation relationship curve, the target slush preparation parameters can be determined based on the ice hardness value and the target slush coarseness using the slush preparation relationship curve. The difference between the target slush preparation parameters and the slush preparation adjustment parameters can be used as the corrected slush coarseness adjustment value, which can further fine-tune the slush preparation process.

[0072] After determining the adjustment parameters for smoothie preparation, the smoothie preparation process can be adjusted using these parameters. These parameters can include the crushing speed and crushing time, which in turn allow for real-time adjustment of the crushing speed and crushing time of the stirring motor, thereby achieving precise control over the smoothie preparation process.

[0073] With this implementation method, when the corrected fineness adjustment value of the slush is less than the preset corrected fineness adjustment value, the corrected fineness adjustment value of the slush is first obtained, and then the slush preparation adjustment parameter is determined by combining the slush preparation relationship curve with the ice hardness value. The slush preparation process is adjusted with this parameter, and precise parameter calibration is still performed for cases that do not meet the standard, so as to achieve dynamic optimization of slush preparation parameters across the entire range and improve the accuracy of parameter matching with requirements.

[0074] This implementation method re-matches parameters and adjusts the preparation process by correcting the insufficient coarseness of the shaved ice when the fineness of the shaved ice does not meet the standard. By constructing a complete closed-loop control logic that covers parameter calibration in all scenarios, the closed-loop control process of shaved ice preparation is improved, process parameter fluctuations are reduced, and the consistency and stability of the preparation process are enhanced.

[0075] In some implementations, the above method also includes S121 to S122, which will be explained in detail below.

[0076] S121. Sieve the slush through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture. Determine the maximum weight of the slush among the weights corresponding to the multiple sieve apertures. Obtain the aperture of the sieve corresponding to the maximum weight of the slush as the actual value of the slush coarseness.

[0077] In this implementation, slush can be sieved through a screen with multiple apertures installed on an inclined slush conveying pipe. The multiple aperture screens correspond to different weighing units, and the weight of the slush corresponding to each of the multiple aperture screens can be obtained through the weighing units. The multiple aperture screens can cover different particle size ranges. Through the sieving operation, the slush can be classified according to different particle sizes. The weight of the slush corresponding to each aperture screen reflects the distribution of slush within that particle size range.

[0078] After weighing the slush, the maximum slush weight can be determined among the slush weights corresponding to the multiple sieve sizes. The maximum slush weight indicates the sieve that collects the largest slush weight among the multiple sieves. The particle size range corresponding to this maximum slush weight represents the particle size distribution that accounts for the largest proportion in the slush.

[0079] In this implementation, the aperture of the sieve corresponding to the maximum weight of the slush can be obtained as the actual value of the slush coarseness, so that the actual value of the slush coarseness can be quantitatively characterized by the sieve aperture corresponding to the maximum weight of the slush.

[0080] For example, when preparing shaved ice in a shaved ice machine, the shaved ice sample is sieved through multiple sieves with different apertures. The weight of the shaved ice trapped by each sieve is recorded, and the sieve with the largest weight is found. The aperture of the sieve with the largest weight is the actual value of the fineness of the shaved ice.

[0081] S122. Determine the difference between the target value and the actual value of the fineness of the shaved ice as the fineness adjustment value.

[0082] In this implementation, the difference between the target value and the actual value of the slush coarseness can be used as the slush coarseness adjustment value. The target value of the slush coarseness represents the desired degree of slush particle coarseness, while the actual value of the slush coarseness represents the currently measured degree of slush particle coarseness. By calculating the difference between the two, the slush coarseness adjustment value can be obtained.

[0083] This method involves sieving the slush through sieves of multiple apertures to obtain the weight of the slush corresponding to each sieve aperture. The maximum weight of the slush is determined, and the mesh count of the sieve corresponding to this maximum weight is obtained as the actual value of the slush fineness. The difference between the target value of the slush fineness and the actual value of the slush fineness is then determined as the slush fineness adjustment value. By using multi-sieve quantitative sieving, the actual value of the slush fineness is accurately collected, providing an accurate basis for subsequent parameter adjustments and optimizing the slush preparation effect.

[0084] This method first obtains the precise actual value of the fineness of the ice slush by sieving it through a sieve with multiple apertures, calculates the fineness adjustment value of the ice slush, and then determines the ice slush preparation adjustment parameters by combining the ice slush preparation relationship curve and the ice hardness value. The precise quantification of the ice slush fineness data matches the preparation parameters, making the ice slush preparation adjustment parameters more in line with the actual preparation needs, reducing parameter deviations, and improving the precise control capability of ice slush preparation.

[0085] Figure 3 This is a flowchart illustrating the second multi-mode switching control method for smoothie preparation provided in this application embodiment. Figure 3As shown, in some implementations, the above method also includes S210 to S220, which will be described in detail below.

[0086] S210. Determine the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module. Determine the ratio of this product to the product of the minimum ice-making temperature, the maximum ice-making quantity, and the maximum ice-making time, and use this ratio as the ice quantity coefficient. Obtain the minimum ice quantity coefficient threshold and the optimal ice quantity coefficient threshold, where the optimal ice quantity coefficient threshold is greater than the minimum ice quantity coefficient threshold.

[0087] Figure 4 A schematic diagram of the workflow of the second multi-mode switching control method for smoothie preparation provided in this application embodiment is shown below. Figure 4 As shown, the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module can be determined. At the same time, the product of the reciprocal of the minimum ice-making temperature, the maximum ice-making quantity, and the maximum ice-making time can also be determined. Furthermore, the ratio of the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module to the product of the reciprocal of the minimum ice-making temperature, the maximum ice-making quantity, and the maximum ice-making time can be determined as the ice quantity coefficient. The ice quantity coefficient can comprehensively reflect the degree of completion of the current ice-making state of the ice-making module relative to the ideal ice-making state.

[0088] For example, the ice-making temperature is the cooling temperature of the refrigeration module in the current ice-making process.

[0089] For example, the ice production capacity can be the existing weight of the ice blocks stored in the ice maker, which can be determined by the weight of the ice blocks in the ice storage compartment.

[0090] For example, the ice-making time is the ice-making time required to complete the preparation of one ice block in the current ice-making process.

[0091] At the same time, the minimum ice quantity coefficient threshold and the optimal ice quantity coefficient threshold can be obtained. The optimal ice quantity coefficient threshold is greater than the minimum ice quantity coefficient threshold. The minimum ice quantity coefficient threshold represents the minimum ice quantity standard required to start slush preparation, and the optimal ice quantity coefficient threshold represents the best ice quantity standard to start slush preparation.

[0092] S220. When the slushie preparation process is started, the real-time ice quantity coefficient of the ice-making module is obtained. When the real-time ice quantity coefficient is less than the minimum ice quantity coefficient threshold, the ice-making time is extended by a first proportional value, and the compressor speed is increased by a second proportional value to increase the real-time ice quantity coefficient. When the real-time ice quantity coefficient is greater than or equal to the minimum ice quantity coefficient threshold but less than the optimal ice quantity coefficient threshold, the compressor speed is increased by a second proportional value to increase the real-time ice quantity coefficient. When the real-time ice quantity coefficient is greater than or equal to the optimal ice quantity coefficient threshold, the process switches to the slushie preparation process.

[0093] like Figure 4 As shown, when the slush preparation process is started, the real-time ice quantity coefficient of the ice-making module can be obtained. The real-time ice quantity coefficient reflects the actual state of the ice quantity in the ice-making module, which can then provide a basis for subsequent control decisions.

[0094] In this implementation, when the real-time ice quantity coefficient is less than the minimum ice quantity coefficient threshold, the ice-making time can be extended by a first proportional value, and the compressor speed can be increased by a second proportional value to increase the real-time ice quantity coefficient. This dual adjustment method can quickly improve ice-making efficiency and ensure that the ice quantity meets the requirements.

[0095] For example, when a slush machine has both ice-making and slush-making functions, if the real-time ice quantity coefficient is detected to be lower than the minimum ice quantity coefficient threshold, the ice-making cycle can be automatically extended and the compressor's workload increased to ensure that the ice quantity is quickly accumulated to a level that can be used to start slush preparation.

[0096] In this implementation, when the real-time ice quantity coefficient is greater than or equal to the minimum ice quantity coefficient threshold but less than the optimal ice quantity coefficient threshold, the compressor speed can be increased according to the second proportional value to increase the real-time ice quantity coefficient. This method achieves further optimization of the ice quantity by adjusting a single parameter while ensuring the basic ice quantity.

[0097] For example, during the operation of a smoothie maker, when the amount of ice has reached the minimum requirement but not yet the optimal state, the ice-making process can be accelerated simply by increasing the compressor speed, thus avoiding excessively extending the ice-making time and affecting the efficiency of smoothie preparation.

[0098] In this implementation, when the real-time ice quantity coefficient is greater than or equal to the optimal ice quantity coefficient threshold, the process can be switched to the shaved ice preparation process. This indicates that the current ice quantity has met the optimal preparation conditions and the shaved ice making process can begin immediately.

[0099] For example, when the slush machine detects that the real-time ice volume coefficient has reached the optimal ice volume coefficient threshold, the system will automatically switch from ice-making mode to slush preparation mode and begin the slush crushing process.

[0100] This implementation calculates the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module. Then, it normalizes the product relative to the reciprocal of the minimum ice-making temperature, the maximum ice-making quantity, and the maximum ice-making time to obtain the ice quantity coefficient. The minimum ice quantity coefficient threshold and the optimal ice quantity coefficient threshold are obtained. When starting the slushie preparation process, the status is judged based on the real-time ice quantity coefficient, which realizes accurate quantitative judgment of ice quantity, avoids the problem of insufficient or excessive ice quantity, ensures stable start of the slushie preparation process, and reduces abnormal preparation situations.

[0101] With this implementation, when the ice-making process is started, if the real-time ice quantity coefficient is less than the minimum ice quantity coefficient threshold, the ice-making time is extended by a first proportion and the compressor speed is increased by a second proportion; if it is between the two thresholds, the compressor speed is increased only by the second proportion; if the optimal threshold is reached, the process is switched. This allows for the adjustment of ice-making parameters as needed, avoiding ineffective high-load operation of the compressor, and reducing energy consumption while meeting the ice quantity requirements.

[0102] This implementation method quickly determines the ice quantity status by using the real-time ice quantity coefficient and takes corresponding ice replenishment measures such as extending the ice-making time and increasing the compressor speed. Once the optimal ice quantity coefficient threshold is reached, it immediately switches to the slush preparation process without waiting for the ice quantity to accumulate naturally, thus shortening the ice replenishment time, improving the overall efficiency of slush preparation, and reducing user waiting time.

[0103] In some implementations, the above method also includes: when the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, increasing the ice-making time and compressor speed to increase the ice quantity coefficient according to the preset increase, and adjusting the ice preparation parameters of the ice-making module to adjust the ice hardness.

[0104] In the process of making shaved ice in the shaved ice machine, after determining the correction value for the fineness of the shaved ice in S130 above, when the correction value for the fineness of the shaved ice is greater than or equal to the preset correction value for the fineness of the shaved ice, it indicates that the hardness of the ice needs to be adjusted to improve the shaved ice preparation effect. This can be achieved by increasing the ice-making time and the compressor speed to increase the ice quantity coefficient according to the preset increase, and by adjusting the ice preparation parameters of the ice-making module to adjust the ice hardness, so as to ensure that there is a sufficient amount of ice that meets the ice hardness requirements for shaved ice preparation.

[0105] For example, when the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, the ice-making time and compressor speed are increased to increase the ice quantity coefficient according to the preset increase. The corrected slush coarseness adjustment value and the preset increase of the ice quantity coefficient can be determined by a preset empirical value table, which can be stored and retrieved by the ice maker's control system.

[0106] For example, in the multi-mode operation of the slush machine, which simultaneously makes ice blocks and slush, when the control unit detects that the correction value for slush coarseness adjustment has reached or exceeded the preset correction value for slush coarseness adjustment, the control unit can automatically extend the ice-making time and increase the compressor speed, thereby increasing the ice quantity coefficient and the ice block preparation parameters of the ice-making module according to the preset increase, so as to ensure that the ice hardness and ice quantity during the slush preparation process are adapted to the current coarseness adjustment target.

[0107] This implementation method adjusts the ice cube preparation parameters of the ice-making module to adjust the ice cube hardness when the corrected ice cube fineness adjustment value is greater than or equal to the preset corrected ice cube fineness adjustment value. At the same time, it increases the ice-making time and compressor speed by a preset increment to increase the ice quantity coefficient, providing ice cubes with suitable hardness and sufficient quantity for ice cube preparation. This avoids ice cube fineness adjustment failure due to insufficient ice quantity, reduces poor ice cube preparation adjustment effect due to insufficient hardness or ice quantity, and improves the quality of ice cube preparation.

[0108] In some implementations, the above method further includes: when the slush preparation process is started, obtaining the real-time ice volume coefficient of the ice-making module and obtaining historical ice preparation parameters for adjusting ice hardness. When the real-time ice volume coefficient is less than the minimum ice volume coefficient threshold, extending the ice-making time by a first proportional value and increasing the compressor speed by a second proportional value to increase the real-time ice volume coefficient, and adjusting the ice preparation parameters by the product of the historical ice preparation parameters and a third proportional value. When the real-time ice volume coefficient is greater than or equal to the minimum ice volume coefficient threshold but less than the optimal ice volume coefficient threshold, increasing the compressor speed by a second proportional value to increase the real-time ice volume coefficient, and adjusting the ice preparation parameters by the product of the historical ice preparation parameters and a fourth proportional value.

[0109] Figure 5 A schematic diagram of the workflow of the third multi-mode switching control method for smoothie preparation provided in this application embodiment is shown below. Figure 5 As shown, when the slush preparation process is started, the real-time ice quantity coefficient of the ice-making module can be obtained, as well as the historical ice preparation parameters for adjusting the ice hardness. The real-time ice quantity coefficient reflects the current ice reserve in the ice-making module, and the historical ice preparation parameters record the preparation parameters previously set to adjust the ice hardness. By obtaining these data, a basis can be provided for subsequent adjustments to the ice preparation parameters.

[0110] For example, when the slush machine starts making slush, the ice quantity coefficient in the ice-making module can be monitored in real time by the built-in ice quantity detection sensor, and the preparation parameter records used to adjust the hardness of the ice cubes in history can be retrieved from the storage unit.

[0111] For example, the historical adjustment parameters for ice preparation can be the historical adjustment parameters from the previous ice smoothie preparation, in order to ensure the effect of ice smoothie preparation.

[0112] For example, the historical adjustment of ice preparation parameters can be the average of the three historical adjustments of ice preparation parameters in the historical slush preparation process, in order to ensure the effect of slush preparation.

[0113] In this implementation, such as Figure 5As shown, when the real-time ice quantity coefficient is less than the minimum ice quantity coefficient threshold, the ice-making time can be extended according to the first proportional value, and the compressor speed can be increased according to the second proportional value to increase the real-time ice quantity coefficient. The ice-making parameters can be adjusted according to the product of the historical ice-making parameters and the third proportional value. This multi-parameter coordinated adjustment method can solve the problems of insufficient ice quantity and ice hardness adjustment at the same time.

[0114] For example, during the preparation of shaved ice, if the real-time ice volume coefficient is detected to be lower than the minimum requirement, the ice volume can be increased by extending the ice-making time and increasing the compressor speed. At the same time, the preparation parameters can be adjusted based on historical parameters and the third ratio value to ensure that the ice hardness meets the requirements.

[0115] In this implementation, such as Figure 5 As shown, when the real-time ice quantity coefficient is greater than or equal to the minimum ice quantity coefficient threshold and less than the optimal ice quantity coefficient threshold, the compressor speed can be increased according to the second proportional value to increase the real-time ice quantity coefficient. The ice preparation parameters can be adjusted according to the product of the historical ice preparation parameters and the fourth proportional value. Through the graded adjustment strategy, targeted parameter adjustment schemes can be adopted according to the specific range of the ice quantity coefficient.

[0116] For example, when the ice quantity coefficient is at a medium level, the ice quantity can be increased simply by increasing the compressor speed, while the preparation parameters are adjusted based on historical parameters and the fourth ratio value, so as to achieve simultaneous increase in ice quantity and adjustment of hardness.

[0117] For example, the third ratio value can be from 0.8 to 1.2, and the fourth ratio value can be from 0.6 to 0.8.

[0118] This implementation method, when initiating the slush preparation process, obtains the real-time ice quantity coefficient of the ice-making module and the historical ice preparation parameters for adjusting ice hardness. Based on the range of the real-time ice quantity coefficient, the historical ice preparation parameters are multiplied by the corresponding proportional value to adjust the ice preparation parameters. This allows for pre-adjustment of ice-making parameters to achieve adjustment of ice hardness. By leveraging historical data, the adjustment of ice preparation parameters is made more closely aligned with actual needs, effectively improving the accuracy of ice hardness adjustment and reducing the impact of hardness deviation on the fineness of the slush. It also ensures that the increase in ice quantity coefficient and the adjustment of ice hardness are carried out in a coordinated manner, avoiding slush preparation adaptation problems caused by asynchronous parameter adjustments and enhancing process stability.

[0119] With this implementation, after starting the slush preparation process, the historical ice preparation parameters for adjusting ice hardness are directly called. The current ice preparation adjustment parameters are quickly determined by multiplying them with the corresponding proportional values. There is no need to retest and explore the parameters, which can greatly simplify the process of adjusting ice preparation parameters and thus improve the overall efficiency of slush preparation.

[0120] Figure 6A flowchart illustrating the fourth multi-mode switching control method for smoothie preparation provided in this application embodiment is shown below. Figure 6 As shown, in some implementations, the above method also includes S310 to S320, which will be described in detail below.

[0121] S310. Sieve the slush through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture. Determine the weight increment of the slush corresponding to each sieve aperture.

[0122] In this implementation, the slush can be sieved through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture. The sieving process can obtain the distribution of slush with different particle sizes. The weight of the slush corresponding to each sieve aperture reflects the distribution characteristics of slush particles in different particle size ranges.

[0123] For example, when preparing slushies in a slushie machine, sieves with different pore sizes can be used to grade and sieve the prepared slushie samples. By recording the weight of the slushie retained on each sieve, the particle size distribution data of the slushie particles can be obtained.

[0124] In this implementation, the weight increment of slush corresponding to screens with multiple apertures can be determined. The weight increment of slush represents the change in slush weight corresponding to different screens, which can reflect the concentration of slush particles in a specific particle size range.

[0125] For example, by calculating the difference in weight between adjacent screens, the weight increment of the ice in each particle size range can be obtained. These increments help to analyze the distribution characteristics of the ice particles.

[0126] S320. By using the ice slush preparation adjustment parameter mapping table, determine the ice preparation parameters to adjust the ice hardness based on the target value of ice slush coarseness and the ice slush weight increment value corresponding to the sieves with multiple aperture sizes.

[0127] In this implementation, the ice preparation parameters can be adjusted to adjust the ice hardness by using a slush preparation adjustment parameter mapping table, based on the target value of slush coarseness and the slush weight increment value corresponding to the sieves with multiple aperture sizes. The slush preparation adjustment parameter mapping table establishes the correspondence between slush particle size characteristics and ice preparation parameters.

[0128] For example, the slush preparation adjustment parameter mapping table can be an empirical value table obtained by summarizing experimental data. The empirical value table can analyze the correlation between the slush weight increment value and the slush coarseness target value, and output the corresponding ice cube preparation parameter adjustment scheme.

[0129] In this implementation, after determining the ice preparation parameters that need to be adjusted, the parameter settings in the ice-making process can be adjusted accordingly. By changing the hardness of the ice, the particle fineness of the ice slush can be affected during the subsequent preparation of the slush, making the coarseness of the slush closer to the target requirements.

[0130] For example, if the shaved ice is detected to be too coarse, the hardness of the ice can be increased by lowering the ice-making temperature or extending the ice-making time. Harder ice will produce finer shaved ice particles when broken, thus improving the coarseness of the shaved ice.

[0131] This method first sieves the slush with multiple apertures to obtain the weight increment of the slush corresponding to each sieve. Then, using a slush preparation adjustment parameter mapping table, the ice preparation parameters are determined by combining the target value of slush coarseness and the weight increment value of the slush. This allows for precise control of ice hardness to optimize the slush coarseness, accurately matching the slush coarseness requirements, significantly improving the accuracy and consistency of slush preparation, and enhancing the stability of slush quality.

[0132] This method first sieves the slush to obtain the weight increment value of the slush corresponding to each sieve. Based on the slush preparation parameter adjustment mapping table, the target value of slush coarseness and the weight increment value of slush are associated. The ice preparation parameters are then adjusted in a targeted manner to optimize the ice hardness, achieving dynamic and precise optimization of the ice preparation parameters. This makes the ice hardness more suitable for the needs of slush preparation, reduces the deviation of slush coarseness, improves the continuity and adaptability of the process, and reduces the failure rate of slush preparation.

[0133] In some implementations, the above method further includes: when the fineness adjustment value of the slush is greater than or equal to the preset fineness adjustment value, the prepared slush is transported to the slush melting chamber for melting and then enters the ice-making cycle. When the fineness adjustment value of the slush is less than the preset fineness adjustment value, the prepared slush is output from the slush outlet.

[0134] During the preparation of smoothies, the fineness adjustment value of the smoothie can be continuously monitored. The fineness adjustment value reflects the deviation between the current particle size of the smoothie and the target fineness standard. By continuously monitoring this parameter, the quality status of the smoothie preparation can be understood in a timely manner.

[0135] In this implementation, when the fineness adjustment value of the slush is greater than or equal to the preset fineness adjustment value, it indicates that the currently prepared slush particles are too coarse or too fine and do not meet the output standard. At this time, the prepared slush can be transported to the slush melting chamber for melting. After the slush is heated and melted in the melting chamber, the resulting liquid can re-enter the ice-making circulation system and participate in the slush preparation process again as a raw material.

[0136] For example, when making smoothies, if the smoothie particles are detected to be too large and the smoothie coarseness adjustment value exceeds the preset standard, the unqualified smoothie can be sent to the melting chamber. The melted water can then re-enter the ice-making system, undergo refreezing and crushing to ensure that the final smoothie achieves the ideal smooth texture.

[0137] In this implementation, when the fineness adjustment value of the shaved ice is less than the preset fineness adjustment value, it indicates that the particle size of the shaved ice being prepared meets the quality requirements. At this time, the prepared shaved ice can be directly output from the shaved ice outlet for user use. This judgment mechanism ensures that only shaved ice that meets the fineness standard will be finally output.

[0138] This method ensures that the output smoothies meet the fineness requirements by reprocessing substandard smoothies, significantly improving the smoothie quality pass rate and stability; it also enables the recycling and reuse of substandard smoothies; and it improves the closed-loop process of smoothie preparation, enhancing the process's error correction capabilities and automation level.

[0139] This application also provides a multi-mode switching control system for slush preparation, including a unit for implementing the above-described multi-mode switching control method for slush preparation.

[0140] Figure 7 This application provides a schematic diagram of the logic structure of a multi-mode switching control system for smoothie preparation, as shown in the embodiment. Figure 7 As shown, the system 1 of this embodiment includes a processing unit 11, a storage unit 12, and a transceiver unit 13. The processing unit 11 is used to process data, the storage unit 12 is used to store data, and the transceiver unit 13 is used to send and receive data. The processing unit 11, the storage unit 12, and the transceiver unit 13 cooperate with each other to implement the above-described method. The beneficial effects of the embodiments of this application have been described in the above-described method and will not be repeated here.

[0141] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0142] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0143] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0144] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0145] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0146] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0147] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0148] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A multi-mode switching control method for smoothie preparation, characterized in that, The method includes: Obtain the ice slush preparation relationship curves for different preset ice hardness, ice slush preparation parameters, and ice slush fineness; obtain the ice hardness value and ice slush fineness adjustment value; wherein, the ice slush preparation parameters include ice hardness value, crushing speed and crushing time, the ice hardness value of the ice to be crushed is determined by the correlation model of ice making temperature and ice making time, and the difference between the target value of ice slush fineness and the actual value of ice slush fineness is determined as the ice slush fineness adjustment value; Based on the ice preparation relationship curve, the ice preparation adjustment parameters are determined according to the ice hardness value and the ice fineness adjustment value; among them, the ice preparation adjustment parameters include the crushing adjustment speed and the crushing adjustment time; The slush preparation process is adjusted by adjusting the slush preparation parameters; the corrected slush coarseness adjustment value corresponding to the slush preparation adjustment parameters is obtained; when the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, the ice block preparation parameters of the ice making module are adjusted to adjust the ice block hardness; wherein, the difference between the target value of slush coarseness after determining the slush preparation adjustment parameters and the actual value of slush coarseness is used as the corrected slush coarseness adjustment value.

2. The method according to claim 1, characterized in that, When the corrected smoothie coarseness adjustment value is greater than or equal to the preset corrected smoothie coarseness adjustment value, the ice preparation parameters of the ice-making module are adjusted to adjust the ice hardness, including: Obtain the ice preparation relationship curve; based on the ice hardness value and the adjusted ice fineness value, determine the ice hardness value using the ice preparation relationship curve; the ice preparation relationship curve includes the correspondence between ice making temperature, ice making time and ice hardness. By using the ice preparation relationship curve, and adjusting the ice hardness value according to the ice preparation parameters, the ice hardness can be adjusted.

3. The method according to claim 2, characterized in that, The method further includes: When the corrected fineness adjustment value of the shaved ice is less than the preset corrected fineness adjustment value, the shaved ice preparation adjustment parameters are determined based on the ice hardness value and the corrected fineness adjustment value through the shaved ice preparation relationship curve; the shaved ice preparation process is then adjusted using the shaved ice preparation adjustment parameters.

4. The method according to claim 3, characterized in that, The method further includes: The slush is sieved through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture; the maximum weight of the slush among the weights of the slush corresponding to each sieve aperture is determined; the aperture of the sieve corresponding to the maximum weight of the slush is obtained as the actual value of the slush coarseness. The difference between the target value and the actual value of the smoothie coarseness is determined as the smoothie coarseness adjustment value.

5. The method according to claim 4, characterized in that, The method further includes: Determine the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module. Determine the ratio of the product of the reciprocal of the ice-making temperature, the ice-making quantity, and the ice-making time of the ice-making module to the product of the reciprocal of the minimum ice-making temperature, the maximum ice-making quantity, and the maximum ice-making time, and use this ratio as the ice quantity coefficient. Obtain the minimum ice quantity coefficient threshold and the optimal ice quantity coefficient threshold, where the optimal ice quantity coefficient threshold is greater than the minimum ice quantity coefficient threshold. When the slush preparation process is started, the real-time ice volume coefficient of the ice-making module is obtained. When the real-time ice volume coefficient is less than the minimum ice volume coefficient threshold, the ice-making time is extended by a first proportion, and the compressor speed is increased by a second proportion to increase the real-time ice volume coefficient. When the real-time ice volume coefficient is greater than or equal to the minimum ice volume coefficient threshold but less than the optimal ice volume coefficient threshold, the compressor speed is increased by a second proportion to increase the real-time ice volume coefficient. When the real-time ice volume coefficient is greater than or equal to the optimal ice volume coefficient threshold, the slush preparation process is switched to start.

6. The method according to claim 5, characterized in that, The method further includes: When the corrected slush coarseness adjustment value is greater than or equal to the preset corrected slush coarseness adjustment value, the ice-making time and compressor speed are increased to increase the ice quantity coefficient according to the preset increase, and the ice preparation parameters of the ice-making module are adjusted to adjust the ice hardness.

7. The method according to claim 6, characterized in that, The method further includes: When the slush preparation process is started, the real-time ice volume coefficient of the ice-making module is obtained, and the historical ice preparation parameters for adjusting ice hardness are also obtained. When the real-time ice volume coefficient is less than the minimum ice volume coefficient threshold, the ice-making time is extended according to the first ratio, and the compressor speed is increased according to the second ratio to increase the real-time ice volume coefficient. The ice preparation parameters are then adjusted according to the product of the historical ice preparation parameters and the third ratio. When the real-time ice volume coefficient is greater than or equal to the minimum ice volume coefficient threshold but less than the optimal ice volume coefficient threshold, the compressor speed is increased according to the second ratio to increase the real-time ice volume coefficient. The ice preparation parameters are then adjusted according to the product of the historical ice preparation parameters and the fourth ratio.

8. The method according to claim 7, characterized in that, The method further includes: The slush is sieved through a sieve with multiple apertures to obtain the weight of the slush corresponding to each sieve aperture; the weight increment of the slush corresponding to each sieve aperture is determined. By using the slush preparation parameter adjustment mapping table, the ice preparation parameters are determined to adjust the ice hardness based on the target value of slush coarseness and the slush weight increment value corresponding to the sieves with multiple aperture sizes.

9. The method according to claim 8, characterized in that, The method further includes: When the fineness adjustment value of the shaved ice is greater than or equal to the preset fineness adjustment value, the prepared shaved ice is transported to the shaved ice melting chamber to melt and then enters the ice-making cycle; when the fineness adjustment value of the shaved ice is less than the preset fineness adjustment value, the prepared shaved ice is output from the shaved ice outlet.

10. A multi-mode switching control system for smoothie preparation, characterized in that, Includes units for implementing the method of any one of claims 1 to 9.

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