Power dynamic distribution method and system of three-dimensional heating coil

Abstract

The embodiment of the invention discloses a dynamic power distribution method and system for a three-dimensional heating coil. The method comprises the following steps: acquiring temperature information of each heating area corresponding to the three-dimensional heating coil; determining a thermal imbalance index according to the temperature information, and determining a corresponding thermal risk coefficient grade according to the thermal imbalance index; evaluating the health state of each heating coil; calculating the power distribution proportion of each heating coil based on the thermal risk coefficient grade and the health state of each heating coil, and driving each heating coil to heat according to the power distribution proportion; and when the virtual thermal center deviates from a preset target area, correcting the power distribution proportion. The problems of local overheating and uneven heating can be effectively solved, and the overall heating uniformity and operation safety are improved.

Description

Technical Field

[0001] This invention relates to the field of rice cooker technology, specifically to a method and system for dynamic power distribution of a three-dimensional heating coil, an electronic device, and a storage medium. Background Technology

[0002] In existing rice cookers, 3D heating cookware, or multi-heating coil heating devices, heating control is typically achieved by applying a fixed proportion or preset power to the bottom heating coil or multiple heating coils. This type of solution often adjusts power based on feedback from a single temperature point or the overall temperature, making it difficult to reflect the true heat distribution in different spatial locations such as the bottom, side walls, and transition areas of the pot.

[0003] In actual use, due to differences in pot structure, uneven food distribution, and aging of heating coils, significant temperature imbalances can easily occur between different heating zones, leading to problems such as localized overheating, scorching, insufficient sidewall heating, or decreased energy efficiency. Even with the introduction of multiple temperature sensors in existing technologies, only simple temperature comparisons or averaging are typically performed, lacking a comprehensive assessment of the spatial directionality of heat distribution and the degree of risk. Summary of the Invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a method and system for dynamic power distribution of a three-dimensional heating coil, as well as an electronic device, which can effectively suppress local overheating and uneven heating, and improve overall heating uniformity and operational safety.

[0005] To address the aforementioned problems, the first aspect of this invention discloses a method for dynamic power distribution of a three-dimensional heating coil, comprising the following steps: Obtain temperature information for each heating region corresponding to the three-dimensional heating coil; each heating region includes at least a bottom region, a sidewall region, and a transition region, wherein the bottom region, sidewall region, and transition region correspond to the bottom heating coil, the sidewall heating coil, and the R-angle heating coil domain of the transition region between the bottom and the sidewall, respectively; Based on the temperature information, a thermal imbalance index is determined; the thermal imbalance index is used to characterize the degree of temperature dispersion in different heating areas. The corresponding thermal risk coefficient level is determined based on the aforementioned thermal imbalance index; The health status of each heating coil is assessed based on its resistance variation parameters and / or thermal response characteristics. Based on the thermal risk coefficient level and the health status of each heating coil, the power allocation ratio of each heating coil is calculated, so as to drive each heating coil to perform heating according to the power allocation ratio; Based on the power distribution ratio, the virtual thermal center position of the three-dimensional heating coil is calculated in real time. When the virtual thermal center deviates from the preset target area, the power distribution ratio is corrected to adjust the power output of each heating coil.

[0006] Optionally, determining the thermal imbalance index based on the temperature information includes: Based on the spatial positional relationship between the heating zones, the spatial temperature gradient components between adjacent heating zones are calculated. Based on the spatial temperature gradient components, a spatial gradient vector is constructed to characterize the distribution of heat along the spatial direction inside the pot body; the spatial temperature gradient components are determined by the ratio of the temperature difference between different heating areas to their equivalent spatial distance in the pot body structure. The thermal imbalance index is calculated based on the spatial gradient vector.

[0007] Optionally, determining the corresponding thermal risk coefficient level based on the thermal imbalance index includes: The initial thermal risk range is determined based on the thermal imbalance index; The dominant direction of the spatial gradient vector is used as a constraint condition; the dominant direction of the spatial temperature gradient is determined by the spatial direction corresponding to the spatial gradient component with the largest numerical value or the highest weighted contribution rate in the spatial gradient vector. Based on the initial thermal risk range and the dominant direction of the spatial temperature gradient, the final thermal risk coefficient level is determined, and the final thermal risk coefficient level is used as the thermal risk coefficient level corresponding to the thermal imbalance index.

[0008] Optionally, calculating the power allocation ratio of each heating coil based on the thermal risk factor level and the health status of each heating coil includes: A risk channel mapping table is pre-established between thermal risk coefficient levels and power allocation optimization channels. Based on the thermal risk coefficient levels, the set of power allocation optimization channels participating in power allocation decisions within the current control cycle is determined from the risk channel mapping table. Based on the health status of each heating coil, a health constraint is applied to the power allocation optimization channel set to obtain a constrained power allocation optimization channel set. In the constrained power allocation optimization channel set, the power allocation ratio of each heating coil is determined according to the power requirements of each heating coil.

[0009] Optionally, applying health constraints to the power allocation optimization channel set based on the health status of each heating coil includes: When the health status of a heating coil is lower than a preset health threshold, the maximum allowable output power of the heating area corresponding to that heating coil in the current control cycle is limited, and / or its priority in participating in power allocation decisions is reduced.

[0010] Optionally, in the constrained power allocation optimization channel set, determining the power allocation ratio of each heating coil based on the power demand of each heating coil includes: Based on the risk participation level of each heating zone, a risk suppression factor is applied to the power demand of the corresponding heating zone of each heating coil to obtain the risk-corrected power demand; Based on the constrained power allocation optimization channel set, the maximum allowable output power of each heating zone in the current control cycle is determined, and the risk correction power demand exceeding the maximum allowable output power is limited. The power demand for risk correction after limiting is normalized to obtain the power allocation ratio of each heating coil.

[0011] Optionally, the real-time calculation of the virtual thermal center position of the three-dimensional heating coil includes: The actual power output value of each heating coil and the real-time temperature information of the corresponding heating area are obtained within the current control cycle, and the equivalent spatial position parameters of each heating coil are preset or calibrated. Based on the actual power output value of each heating coil and the temperature information of its corresponding heating area, the thermal contribution weight of each heating coil in the current control cycle is calculated. The thermal contribution weight is the product of the actual power output value and the temperature weight. The temperature weight is obtained based on the real-time temperature information of the heating area. Based on the thermal contribution weight of each heating coil and its corresponding equivalent spatial position parameters, the virtual thermal center position within the current control cycle is calculated.

[0012] A second aspect of this invention discloses a dynamic power distribution system for a three-dimensional heating coil, comprising: The acquisition unit is used to acquire temperature information of each heating region corresponding to the three-dimensional heating coil; each heating region includes at least a bottom region, a side wall region, and a transition region, and the bottom region, side wall region, and transition region correspond to the bottom heating coil, the side wall heating coil, and the R-angle heating coil domain of the transition region between the bottom and the side wall, respectively. The index unit determines the thermal imbalance index based on the temperature information; the thermal imbalance index is used to characterize the degree of temperature dispersion in different heating areas. Risk unit, used to determine the corresponding thermal risk coefficient level based on the thermal imbalance index; A status unit is used to assess the health status of each heating coil based on the resistance change parameters and / or thermal response characteristics of each heating coil. The distribution unit is used to calculate the power distribution ratio of each heating coil based on the thermal risk coefficient level and the health status of each heating coil, so as to drive each heating coil to heat according to the power distribution ratio; The adjustment unit is used to calculate the virtual thermal center position of the three-dimensional heating coil in real time based on the power distribution ratio. When the virtual thermal center deviates from the preset target area, the power distribution ratio is corrected to adjust the power output of each heating coil.

[0013] A third aspect of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the power dynamic allocation method for a three-dimensional heating coil disclosed in the first aspect of the present invention.

[0014] A fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the power dynamic allocation method for a three-dimensional heating coil disclosed in the first aspect of the present invention.

[0015] Compared with the prior art, the beneficial effects of the embodiments of the present invention are as follows: This invention acquires temperature information from multiple heating zones corresponding to a three-dimensional heating coil, constructs a thermal imbalance index reflecting the degree of temperature dispersion in different heating zones, and determines the corresponding thermal risk coefficient level based on this index, thereby assessing the spatial thermal distribution state inside the pot. Simultaneously, it assesses the health status of the heating coils by combining the resistance change parameters and / or thermal response characteristics of each heating coil. Based on this, it dynamically calculates the power distribution ratio by integrating the thermal risk coefficient level and the health status of the heating coils, and further adjusts the power output of each heating coil through real-time calculation and offset correction of the virtual thermal center position, causing the overall thermal distribution to converge towards a preset target area. This effectively suppresses local overheating or underheating problems in multi-heating coil three-dimensional heating scenarios, improves heating uniformity and thermal safety, and reduces the risk of failure due to heating coil performance degradation, demonstrating significant engineering practical effects. This invention introduces temperature information from multiple heating zones and a thermal imbalance index, enabling the overall quantification of the bottom region and transition zone. The temperature dispersion between the regional and sidewall regions avoids misjudgments of heat distribution caused by relying solely on single-point or average temperatures. By mapping the thermal imbalance index to the thermal risk coefficient level, the system can distinguish the risk level under different heating states. This introduces a risk-oriented adjustment mechanism in the power allocation stage, rather than static or fixed ratio allocation. The health status is assessed by combining the resistance change parameters and / or thermal response characteristics of the heating coils. This ensures that the power allocation strategy is not only based on the current temperature state but also reflects the long-term reliability and performance degradation of each heating coil, effectively reducing the overload risk to deteriorated coils. The power allocation ratio is calculated jointly based on the thermal risk coefficient level and the health status of the heating coils, achieving coordinated control of thermal safety constraints and equipment health constraints. This improves the system's operational stability and service life. At the same time, through the real-time calculation and feedback correction mechanism of the virtual thermal center position, the overall heat distribution is guided to converge towards the preset target area from a spatial perspective, avoiding long-term overheating or undercooling of local areas, thereby significantly improving the consistency of three-dimensional heating and cooking effect. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for dynamic power distribution of a three-dimensional heating coil according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the power dynamic distribution system of a three-dimensional heating coil according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. Detailed Implementation

[0017] This specific embodiment is merely an explanation of the embodiments of the present invention and is not intended to limit the embodiments of the present invention. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but as long as they are within the scope of the claims of the embodiments of the present invention, they are protected by patent law.

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the embodiments of the present invention.

[0019] The term "comprising" and any variations thereof in the specification and claims of this application are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product or device.

[0020] In embodiments of the present invention, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in embodiments of the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0021] This invention constructs a thermal imbalance index to characterize the degree of temperature dispersion in the internal space of the pot and introduces a thermal risk coefficient level to assess the thermal distribution state in a three-dimensional heating scenario. It also dynamically calculates the power distribution ratio by combining the health status of each heating coil and forms a closed-loop adjustment mechanism through real-time calculation and offset correction of the virtual thermal center position. This can effectively suppress local overheating and uneven heating problems, and improve the overall heating uniformity and operational safety.

[0022] Example 1 Please refer to Figure 1-3 As shown, a method for dynamic power distribution of a three-dimensional heating coil is as follows: Figure 1 As shown, it includes the following steps: Step S110: Obtain the temperature information of each heating area corresponding to the three-dimensional heating coil; each heating area includes at least the bottom heating coil, the side wall heating coil, and the R-angle heating coil in the transition area between the bottom and the side wall; The temperature information includes temperature information representing the bottom heating coil, the side wall heating coil, and the R-angle heating coil in the transition region between the bottom and the side wall.

[0023] In practice, temperature information of the area corresponding to the bottom heating coil can be obtained by a temperature acquisition unit set at the bottom of the pot; temperature information of the area corresponding to the side wall heating coil can be obtained by a temperature acquisition unit distributed along the height direction of the side wall of the pot; and temperature information of the area corresponding to the R-angle heating coil can be obtained by a temperature acquisition unit set in the transition area between the bottom of the pot and the side wall.

[0024] The acquired temperature information is time-synchronized and filtered, and thermal inertia compensation is performed in combination with the thermal response characteristics of each heating zone to obtain temperature information that reflects the actual thermal state of different spatial areas of the pot.

[0025] Specifically, the acquired temperature information of each heating zone is processed for time synchronization, and sensor noise and transient fluctuations are suppressed by moving average, low-pass filtering or Kalman filtering. Then, according to the thermal response characteristics of the heating coil corresponding to each heating zone, the temperature information is thermally inertial compensated to obtain an equivalent temperature value that reflects the actual heating effect.

[0026] Step S120: Based on the temperature information, determine the thermal imbalance index, which is used to characterize the degree of temperature dispersion in different heating areas; In specific implementation, a set of regional temperatures is constructed, consisting of the bottom region temperature, the side wall region temperature, and the transition region temperature. The spatial thermal distribution state composed of the set of regional temperatures is not a single temperature value, but a set of state variables used to comprehensively characterize the temperature levels and relative differences of different spatial regions of the pot. The regional temperatures are then spatially calibrated and normalized. Based on the processed regional temperatures, a thermal imbalance index is calculated to characterize the degree of temperature dispersion in different heating regions.

[0027] In this embodiment, the thermal unevenness index is based on a spatial temperature set constructed from multiple heating zones, and combined with the spatial attributes of the zones and the temperature gradient relationship between adjacent zones, to quantitatively characterize the overall thermal distribution state inside the pot, and is used to reflect the spatial concentration or dispersion trend of heat.

[0028] As one embodiment, step 120 specifically includes: Step 1201: Based on the spatial positional relationship between the heating regions, calculate the spatial temperature gradient components between adjacent or associated heating regions; Step 1202: Based on the spatial temperature gradient components, construct a spatial gradient vector characterizing the distribution of heat along the spatial direction inside the pot; the spatial temperature gradient components are determined by the ratio of the temperature difference between different heating areas to their equivalent spatial distance in the pot structure. The equivalent spatial distance is determined based on the curvature of the bottom of the pot, the height of the side walls, and the geometry of the transition area.

[0029] For example, at a certain moment t1 during the heating process, the temperature is collected as follows: The bottom area is 135°C, the transition area is 149°C, and the side wall area is 123°C.

[0030] The equivalent spatial distance within the pot body structure is as follows: Bottom area → Transition area: 5mm; Transition area → Sidewall area, 25mm; Bottom area → side wall area, 40mm.

[0031] The spatial temperature gradient components are calculated as follows: The gradient component G1 from the bottom region to the transition region is G1 = (149) 135) / 15 = 0.93℃ / mm; The gradient component G2 of the transition region to the sidewall region is G2 = (149) 123) / 25 = 1.04℃ / mm; The gradient component G3 from the bottom region to the sidewall region is G3 = (135) 123) / 40 = 0.30℃ / mm.

[0032] The constructed spatial gradient vector is G = [0.93, 1.04, 0.30].

[0033] The spatial gradient vector includes at least multiple gradient components along the direction from the bottom to the transition region, along the direction from the transition region to the sidewall, and along the direction from the bottom to the sidewall, in order to distinguish the risk of heat concentration in different spatial directions.

[0034] It should be noted that this application is used to assess the risk of heat concentration between different heating areas in the boiler structure. Since each gradient component is defined to correspond one-to-one with the structural direction of the specific heating area, its positive or negative sign does not affect the judgment of whether heat migrates along the high-risk channel. Therefore, using the gradient magnitude as the main evaluation parameter in the risk level determination stage helps to improve the stability and engineering applicability of the control rules.

[0035] Step 1203: Calculate the thermal imbalance index based on the spatial gradient vector; Specifically, the thermal imbalance index is determined by a weighted combination of the spatial gradient vectors, wherein the weight of each gradient component is preset according to the risk of burning, coking, or thermal accumulation in the corresponding spatial direction.

[0036] For example, the weights of each gradient component can be set as follows: G1 (bottom region → transition region), weight 0.4; G2 (transition region → sidewall region), weight 0.4; G3 (bottom region → sidewall region), weight 0.2.

[0037] The thermal imbalance index is a weighted sum of the spatial gradient vectors. For example, the thermal imbalance index Ug is calculated as Ug = 0.4 × 0.93 + 0.4 × 1.04 + 0.2 × 0.30 = 0.848.

[0038] In practice, when calculating the thermal imbalance index, the spatial temperature gradient parameter exceeding the preset threshold is subjected to amplitude limiting or nonlinear compression to suppress the impact of temperature anomalies on thermal risk assessment.

[0039] In this embodiment, based on the three-dimensional heating structure of the pot body, the concentration trend of heat along the direction of the pot body structure is characterized by the spatial temperature gradient parameter, and the heat imbalance index is used to determine the thermal risk coefficient level and then used for the power distribution control of the heating coil.

[0040] Step S130: Determine the corresponding thermal risk coefficient level based on the thermal imbalance index; As an example, the thermal risk coefficient level is determined by combining thermal risk interval mapping with thermal imbalance index constraints. Specifically, this includes: normalizing the thermal imbalance index to obtain a normalized thermal imbalance index Un, and determining the corresponding thermal risk interval based on the interval in which the normalized thermal imbalance index Un is located.

[0041] For example, the mapping relationship between the normalized thermal imbalance index Un and the thermal risk coefficient level is as follows: When 0 ≤ Un < 0.4, the thermal risk level is determined to be in the low-risk range; When 0.4 ≤ Un < 0.8, the thermal risk level is determined to be in the medium risk range; When Un ≥ 0.8, the thermal risk coefficient is determined to be in the high-risk range.

[0042] In another embodiment, step S130 may specifically include: Step S1301: Determine the initial thermal risk range based on the thermal imbalance index; Specifically, the initial thermal risk range can be obtained by the mapping relationship between the pre-set thermal imbalance index and the thermal risk coefficient level. For example, a thermal imbalance index of 0.3 corresponds to a low-risk range in the initial thermal risk range.

[0043] Step S1302: Use the dominant direction of the spatial gradient vector as a constraint condition; the dominant direction of the spatial temperature gradient is determined by the spatial direction corresponding to the spatial gradient component with the largest numerical value or the highest weighted contribution rate in the spatial gradient vector. Step S1303: Based on the initial thermal risk range and the dominant direction of the spatial temperature gradient, determine the final thermal risk coefficient level, and use the final thermal risk coefficient level as the thermal risk coefficient level corresponding to the thermal imbalance index.

[0044] Specifically, when the gradient components of the bottom region → transition region and the bottom region → sidewall region in the spatial gradient vector are the dominant components, even if the thermal imbalance index is in the medium-risk range, the thermal risk coefficient level will be raised by one level. This overcomes the problem that local high risks are masked by the spatial averaging effect when relying solely on the thermal imbalance scalar index for risk assessment.

[0045] When the gradient component of the transition region → sidewall region in the spatial gradient vector is the dominant component, the risk level corresponding to the current risk interval is maintained. This ensures a sensitive response to critical high-risk heating areas while avoiding unnecessary risk level increases caused by temperature gradient changes in non-critical directions, thereby improving the accuracy and stability of risk assessment.

[0046] For example, suppose the temperatures of the bottom region, transition region, and sidewall region at a certain moment are 135℃, 149℃, and 123℃, respectively. The corresponding gradient components calculated from the bottom to the transition region are 0.93℃ / mm, from the transition region to the sidewall are 1.04℃ / mm, and from the bottom to the sidewall are 0.30℃ / mm. Although the gradient component from the transition region to the sidewall is relatively large, this direction corresponds to a slow-release path of heat diffusion towards the sidewall. In contrast, the gradient component from the bottom to the transition region reflects the trend of heat concentration from the high heat source region to the heat retention region. Therefore, the dominant direction of the spatial gradient vector is determined to be from the bottom to the transition region, and the thermal risk coefficient level is upgraded accordingly. That is, even if the thermal imbalance is in the medium risk range, the level should be forcibly upgraded.

[0047] In this embodiment, the dominant direction of the spatial gradient vector is introduced as a constraint. When the spatial temperature gradient component is mainly concentrated at the bottom or in the transition region, the risk level can be raised in advance even if the region is still in the medium-risk range, thereby effectively avoiding burnt bottom, charring, or pot damage caused by localized heat concentration. At the same time, when the spatial temperature gradient is mainly concentrated in the side wall region, the original risk level is maintained, avoiding misjudgments caused by temperature changes in non-critical directions, and improving the accuracy of thermal risk assessment and the stability of system control.

[0048] Step 140: Evaluate the health status of each heating coil based on the resistance change parameters and / or thermal response characteristics of each heating coil; In this embodiment, the resistance change parameters include, but are not limited to, the rate of resistance change or the amount of resistance change before and after heating is started and stopped. The thermal response characteristics are the temperature response behavior of the region where the heating coil is located over time under a given power input condition, including but not limited to the temperature rise rate, response time, and cooling characteristics.

[0049] In this embodiment, the rate of change of the instantaneous resistance value of each heating coil during the heating process is used to determine whether there are any abnormalities in the coil's electrical parameters. At the same time, the thermal response characteristics are evaluated by monitoring the temperature rise rate, response time, and cooling characteristics of the heating area corresponding to each heating coil under a given power input condition. The resistance change parameters and thermal response characteristics are fused and analyzed to generate health status parameters for each heating coil.

[0050] For example, the health status levels of each heating coil can be specifically categorized into three types: healthy coil, sub-healthy coil, and risky coil.

[0051] When a heating coil, under the same heating power, deviates from its historical calibration range by more than a first threshold in terms of resistance change rate or steady-state resistance change, the electrical parameters of the heating coil are deemed to be in poor health, indicating abnormal resistance change. When a heating coil, under the same power input conditions, experiences a temperature rise rate in its corresponding heating area that is lower than the historical average or a significantly prolonged response time, the heating coil is deemed to have thermal response hysteresis, indicating abnormal thermal response; or, when the temperature rise rate abnormally increases, the heating coil is deemed to have a risk of localized heat concentration, indicating abnormal thermal response. When both abnormal resistance change and abnormal thermal response exist simultaneously, the heating coil is deemed to be in a risky state; when only one abnormality exists, it is deemed to be in a sub-healthy state.

[0052] For example, the resistance change parameter and thermal response characteristics of the heating coil are fused and analyzed to generate corresponding coil health status parameters. These parameters are continuous health values, which are further mapped to discrete health levels. A resistance health factor is constructed based on the resistance change parameter (e.g., a resistance health factor of 1 when the resistance change parameter is less than or equal to 5%; and a resistance health factor of 0.4 when the resistance change parameter is between 10% and 40%). A thermal response health factor is then constructed based on the thermal response characteristics. Finally, the health value is obtained based on the resistance health factor and the thermal response health factor.

[0053] For example, the resistance health factor = 0.4, the response health factor = 0.3, and the health value is the weighted sum of the resistance health factor and the response health factor. In this example, the health value is the weighted sum of the resistance health factor and the response health factor, which is 0.35.

[0054] Step 150: Based on the thermal risk coefficient level and the health status of each heating coil, calculate the power distribution ratio of each heating coil, so as to drive each heating coil to heat according to the power distribution ratio.

[0055] As one embodiment, step 150 specifically includes: Step 1501: Establish a risk channel mapping table between thermal risk coefficient level and power allocation optimization channel in advance; and determine the set of power allocation optimization channels participating in power allocation decision in the current control cycle from the risk channel mapping table according to the thermal risk coefficient level. In this embodiment, the power distribution optimization channel corresponds to the bottom area, transition area and side wall area of ​​the pot body, respectively. It is a control logic channel used to constrain the way and magnitude of power distribution in each heating area. Its configuration can be dynamically changed with the thermal risk coefficient level.

[0056] For example, the heating area corresponds to channel C1, the transition area corresponds to channel C2, and the sidewall area corresponds to channel C3. The risk channel mapping table data is as follows: The thermal risk level is low, and the corresponding power allocation optimization channels are: channels C1 + C2 + C3; The thermal risk level is medium risk, and the corresponding power allocation optimization channel is: channel C1 + C2; The thermal risk level is high, and the corresponding power allocation optimization channel is: Channel C1; For example, if the thermal risk coefficient level is high risk, only channel C1 (for the domestic bottom region) will enter the power allocation optimization channel set in this control cycle.

[0057] In this embodiment, by establishing a risk channel mapping relationship between the thermal risk coefficient level and the power allocation optimization channel, the power allocation decision has clear structured constraints, avoiding all heating areas from participating in power allocation indiscriminately under any risk state, thereby improving the interpretability and safety of the control strategy.

[0058] Step 1502: Apply health constraints to the power allocation optimization channel set according to the health status of each heating coil to obtain the constrained power allocation optimization channel set; Specifically, step 1502 includes: When the health status of a heating coil is lower than a preset health threshold, the maximum allowable output power of the heating area corresponding to that heating coil in the current control cycle is limited, and / or its priority in participating in power allocation decisions is reduced.

[0059] For example, the preset health threshold is 0.8, and the actual measured health status is as follows: the health value of the heating coil corresponding to the C1 channel in the bottom area is 0.92; the health value of the heating coil corresponding to the C2 channel in the transition area is 0.75 (lower than the preset health threshold); and the health value of the heating coil corresponding to the C3 channel in the side wall area is 0.88.

[0060] It can be seen that the health status of the heating coil corresponding to the transition region C2 channel is lower than the preset health threshold. Its health constraint can be mapped to power limiting through linear derating or empirical table mapping. For example, the maximum allowable output power of the transition region C2 channel is limited from 600W to 300W.

[0061] Step 1503: In the constrained power allocation optimization channel set, determine the power allocation ratio of each heating coil according to the power requirements of each heating coil.

[0062] In this embodiment, the power requirement is calculated based on the deviation between the target temperature and the current temperature of each heating zone, and is used to characterize the theoretical power required to maintain the thermal state of each heating zone without considering constraints.

[0063] Specifically, the power requirement can be determined by the deviation between the target temperature and the current temperature of each heating zone. The thermal response coefficient is obtained, i.e., power demand = (target temperature - current temperature). The thermal response coefficient indicates "how much more power is needed for this heating area".

[0064] Example: Bottom area = 400W, transition area = 200W, side wall area = 100W.

[0065] Specifically, step 1503 includes: Step 15031: Based on the risk participation level of each heating zone, apply a risk suppression factor to the power demand of the corresponding heating zone of each heating coil to obtain the risk-corrected power demand; In this embodiment, after determining the thermal risk level of the system, the risk participation degree of each heating region is determined according to the contribution rate of each gradient component in the spatial gradient vector, and a regionalized risk suppression factor is applied to the power demand based on the risk participation degree.

[0066] For example, the gradient component G1 from the bottom region to the transition region is G1 = (149) 135) / 15 = 0.93℃ / mm; Gradient component G2 of transition region → sidewall region G2 = (149) 123) / 25 = 1.04℃ / mm; The gradient component G3 from the bottom region to the sidewall region is G3 = (135) 123) / 40 = 0.30℃ / mm.

[0067] G1 (bottom region → transition region), weight 0.4; G2 (transition region → sidewall region), weight 0.4; G3 (bottom region → sidewall region), weight 0.2.

[0068] Therefore, the contribution rate of G1 (bottom region → transition region) is C1 = (0.4 × 0.93) / 0.848 ≈ 43.8%; The contribution rate of G2 (transition region → sidewall region) is C2 = (0.4 × 1.04) / 0.848 ≈ 49.1%. The contribution rate of G3 (bottom region → sidewall region) is C3 = (0.2 × 0.30) / 0.848 ≈ 7.1%. The risk participation of each heating region is equal to the sum of the contribution rates of the spatial gradient components it participates in. For example, the bottom region participates in the contribution rates of G1 (bottom region → transition region) and G3 (bottom region → side wall region). Therefore, the risk participation of the bottom region is approximately 43.8% + 7.1% = 50.9%.

[0069] In this embodiment, the imbalance index is a system-level index, and its corresponding thermal risk coefficient level is used to reflect the overall thermal risk level under the current heating state. Based on this, by analyzing the contribution of each gradient component in the spatial gradient vector to the thermal imbalance index, the degree of participation of different heating regions in the overall thermal risk is further determined, and differentiated risk suppression is applied to the power demand of each heating region accordingly.

[0070] A risk inhibition factor is preset based on the risk participation level. The risk inhibition factor ranges from 0 to 1. Specifically, it can be mapped to a proportion of 0 to 1 based on the risk participation level.

[0071] For example, the risk participation rate in the bottom region is 50.9%, and the corresponding risk inhibition factor is 1.0.

[0072] In the sidewall region, the risk participation rate is 56.2%, the mapped risk suppression factor is 0.5, and the power requirement for risk correction in the sidewall region is 200W. 0.5 = 100W; Step 15032: Based on the constrained power allocation optimization channel set, determine the maximum allowable output power of each heating zone in the current control cycle, and limit the risk correction power demand that exceeds the maximum allowable output power; Step 15033: Normalize the risk-corrected power demand after the limiting process to obtain the power allocation ratio of each heating coil.

[0073] For example, the power requirements are: C1: 800W; C2: 500W; C3: 400W; High-risk inhibitory factors: C1: 1.0; C2: 0.6; C3: 0.5; Risk-adjusted demand: C1: 800W; C2: 300W; C3: 200W For example, if the maximum allowable output power of the optimized power allocation channel set after constraints is: C1: 900W; C2: 300W; C3: 0W.

[0074] The purpose of the normalization step is to allocate power proportionally when the total power demand (the sum of risk-corrected power) exceeds the available power or is limited by channel constraints, so as to ensure that the total power is within the allowable range.

[0075] All power demands are proportionally normalized within the allowable output range to obtain the power allocation ratio, and the sum of the power allocation ratios is 1.

[0076] For example, the normalized power allocation ratio is as follows: The power distribution ratio in the bottom region = 800 / (800+300+0) = 72.7%; The power allocation ratio in the transition region = 300 / (800+300+0) = 27.3%; The power distribution ratio in the sidewall region is 0%.

[0077] If the available power is 1000W < the total power requirement of 1100W (800 + 300 + 0 = 1100), assuming the current power in the bottom area is 500W, then the actual driving power in the bottom area = 500W + 800W. 72.7% = 1082 W; Assuming the current power in the transition region is 300W, then the actual driving power in the transition region = 300W + 300W. 27.3% = 382 W; Assuming the current power of the sidewall area is 200W, then the actual driving power of the sidewall area = 200W + 0 = 200W.

[0078] In the above implementation process, by applying a risk suppression factor to the power demand and combining it with the maximum allowable output power for limiting and normalization, the final power allocation ratio can maintain the overall coordination of energy allocation while meeting thermal risk and health constraints, thus avoiding control instability problems caused by simple truncation or abrupt changes.

[0079] Step S160: Based on the power distribution ratio, calculate the virtual thermal center position of the three-dimensional heating coil in real time. When the virtual thermal center deviates from the preset target area, correct the power distribution ratio to adjust the power output of each heating coil.

[0080] Step 160 specifically includes: Step S1601: Based on the spatial geometric position parameters of the heating area corresponding to each heating coil and the actual power output value in the current control cycle, calculate the virtual thermal center position of the three-dimensional heating coil system. In practice, the virtual thermal center location can be calculated through weighted calculation, which is based on the actual power output of each heating coil and the temperature information of that heating coil.

[0081] In this example, the actual power output of each heating coil can be the actual driving power of each heating coil.

[0082] Step S1601 specifically includes: Step S16011: Obtain the actual power output value of each heating coil in the current control cycle and the real-time temperature information of the corresponding heating area, and preset or calibrate the corresponding equivalent spatial position parameters for each heating coil.

[0083] The equivalent spatial position parameter is used to characterize the relative spatial distribution position of the corresponding heating area in the pot structure. The equivalent spatial position of each heating area is not the actual geometric height of the pot, but the equivalent spatial coordinates determined by taking the bottom area of ​​the pot as the reference zero point and based on the relative spatial distribution of each heating area in the pot structure, the main heat conduction path and the intensity of heat action. It is used to characterize the spatial contribution of different heating areas to the overall heat distribution.

[0084] Step S16012: Based on the actual power output value of each heating coil and the temperature information of its corresponding heating area, calculate the thermal contribution weight of each heating coil in the current control cycle. The thermal contribution weight is the product of the actual power output value and the temperature weight. The thermal contribution weight characterizes the relative influence of the heating coil on the overall heat distribution; the temperature weight is obtained based on the real-time temperature information of the heating area.

[0085] For example, calculate the temperature weights: the total temperature of each region = 140 + 155 + 120 = 415℃; T1, T2, and T3 are the temperatures of the bottom region, transition region, and sidewall region, respectively.

[0086] The temperature weights of each heating coil are f(T1) = 140 / 415 = 0.337, f(T2) = 0.373, and f(T3) = 0.289; f(T1), f(T2), and f(T3) are the temperature weights of the bottom region, transition region, and side wall region, respectively.

[0087] The heat contribution weight Wi of each heating coil is calculated as follows: Thermal contribution weight Wi=f(Ti) Pi,i represents the i-th heating coil, i=1,2,3. Among them, W(T1), W(T2), and W(T3) are the heat contribution weights of the bottom region, transition region, and sidewall region, respectively, and P1, P2, and P3 are the actual power output values ​​of the bottom region, transition region, and sidewall region, respectively.

[0088] For example, W1 = 500 × 0.337 = 168.5; W2 = 300 × 0.373 = 111.9; W3 = 200 × 0.289 = 57.8.

[0089] Step S16013: Calculate the virtual thermal center position within the current control cycle based on the thermal contribution weight of each heating coil and its corresponding equivalent spatial position parameters.

[0090] In this step, the virtual thermal center position is a weighted calculation of the thermal contribution weight of each heating coil and its corresponding equivalent spatial position parameters.

[0091] For example, the equivalent spatial position parameters for the bottom region (as the reference zero point), the transition region, and the sidewall region are 0, 15, and 50 mm, respectively; The virtual thermal center location Zc = (168.5×0 + 111.9×15 + 57.8×50) / (168.5 + 111.9 + 57.8) ≈ 15.2 mm.

[0092] Step S1602: Compare the virtual thermal center position with the center position of the preset target area to obtain the thermal center offset; Step S1603: When the thermal center offset exceeds the preset allowable offset threshold, the power distribution ratio of at least one heating coil is corrected according to the thermal center offset direction and offset magnitude, so that the virtual thermal center returns to the preset target area.

[0093] For example, assuming the center of the preset target area is 15mm, the target area is near the transition zone, the current virtual thermal center position Zc = 15.2mm, and the offset is |15.2|. 15 | = 0.2 mm, no adjustment is needed. If the offset is > 3 mm, then power adjustment is required.

[0094] For example, before adjustment: bottom heating coil: 500W, side wall heating coil: 300W, rounded corner heating coil: 200W; after adjustment (assuming heat needs to be concentrated from the side walls and bottom to the transition area): bottom heating coil: 350W (reduce bottom power), side wall heating coil: 450W (increase transition area power), rounded corner heating coil: 200W (maintain side wall power).

[0095] In this embodiment, by introducing a virtual thermal center position as an equivalent representation of spatial heat distribution, and by using the offset of the virtual thermal center position to perform feedback correction on the power distribution of multiple heating areas, the power output and temperature information of multiple heating coils are mapped to the spatial position dimension, enabling the control system to intuitively reflect the spatial center of gravity change of the overall heat distribution, further improving the precision of the three-dimensional heating control, and realizing the self-balancing control of the three-dimensional heating system in the spatial dimension.

[0096] Example 2 This invention discloses a dynamic power distribution system for a three-dimensional heating coil, such as... Figure 2 As shown, Figure 2 It is a dynamic power distribution system for a three-dimensional heating coil, comprising: The acquisition unit 210 is used to acquire temperature information of each heating region corresponding to the three-dimensional heating coil; each heating region includes at least a bottom region, a side wall region, and a transition region, and the bottom region, side wall region, and transition region correspond to the bottom heating coil, the side wall heating coil, and the R-angle heating coil domain of the transition region between the bottom and the side wall, respectively. The index unit 220 determines the thermal imbalance index based on the temperature information; the thermal imbalance index is used to characterize the degree of temperature dispersion in different heating areas. Risk unit 230 is used to determine the corresponding thermal risk coefficient level based on the thermal imbalance index; The status unit 240 is used to assess the health status of each heating coil based on the resistance change parameters and / or thermal response characteristics of each heating coil. The allocation unit 250 is used to calculate the power allocation ratio of each heating coil based on the thermal risk coefficient level and the health status of each heating coil, so as to drive each heating coil to heat according to the power allocation ratio; The adjustment unit 260 is used to calculate the virtual thermal center position of the three-dimensional heating coil in real time based on the power distribution ratio. When the virtual thermal center deviates from the preset target area, the power distribution ratio is corrected to adjust the power output of each heating coil.

[0097] Example 3 Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. For example... Figure 3 As shown, the electronic device may include: Memory 310 storing executable program code; Processor 320 coupled to memory 310; The processor 320 calls the executable program code stored in the memory 310 to execute some or all of the steps in the dynamic power distribution method for a three-dimensional heating coil in Embodiment 1.

[0098] This invention discloses a computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps in a dynamic power distribution method for a three-dimensional heating coil as described in Embodiment 1.

[0099] This invention also discloses a computer program product, wherein when the computer program product is run on a computer, the computer executes some or all of the steps in the power dynamic distribution method for a three-dimensional heating coil in Embodiment 1.

[0100] This invention also discloses an application publishing platform, which is used to publish computer program products. When the computer program products are run on a computer, the computer executes some or all of the steps in the power dynamic allocation method for a three-dimensional heating coil in Embodiment 1.

[0101] In various embodiments of the present invention, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0102] 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; they can 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, depending on actual needs.

[0103] Furthermore, the functional units in the various embodiments of the present invention 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.

[0104] 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-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of the present invention.

[0105] In the embodiments provided by this invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0106] Those skilled in the art will understand that some or all of the steps in the various methods of the embodiments described can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0107] The above provides a detailed description of a dynamic power distribution method, apparatus, electronic device, and storage medium for a three-dimensional heating coil disclosed in the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for dynamic power distribution of a three-dimensional heating coil, characterized in that, It includes the following: Obtain temperature information for each heating region corresponding to the three-dimensional heating coil; each heating region includes at least a bottom region, a sidewall region, and a transition region, wherein the bottom region, sidewall region, and transition region correspond to the bottom heating coil, the sidewall heating coil, and the R-angle heating coil domain of the transition region between the bottom and the sidewall, respectively; Based on the temperature information, a thermal imbalance index is determined; the thermal imbalance index is used to characterize the degree of temperature dispersion in different heating areas. The corresponding thermal risk coefficient level is determined based on the aforementioned thermal imbalance index; The health status of each heating coil is assessed based on its resistance variation parameters and / or thermal response characteristics. Based on the thermal risk coefficient level and the health status of each heating coil, the power allocation ratio of each heating coil is calculated, so as to drive each heating coil to perform heating according to the power allocation ratio; Based on the power distribution ratio, the virtual thermal center position of the three-dimensional heating coil is calculated in real time. When the virtual thermal center deviates from the preset target area, the power distribution ratio is corrected to adjust the power output of each heating coil.

2. The power dynamic distribution method for a three-dimensional heating coil according to claim 1, characterized in that, The step of determining the thermal imbalance index based on the temperature information includes: Based on the spatial positional relationship between the heating zones, the spatial temperature gradient components between adjacent heating zones are calculated. Based on the spatial temperature gradient components, a spatial gradient vector is constructed to characterize the distribution of heat along the spatial direction inside the pot body; the spatial temperature gradient components are determined by the ratio of the temperature difference between different heating areas to their equivalent spatial distance in the pot body structure. The thermal imbalance index is calculated based on the spatial gradient vector.

3. The power dynamic distribution method for a three-dimensional heating coil according to claim 2, characterized in that, The step of determining the corresponding thermal risk coefficient level based on the thermal imbalance index includes: The initial thermal risk range is determined based on the thermal imbalance index; The dominant direction of the spatial gradient vector is used as a constraint condition; the dominant direction of the spatial temperature gradient is determined by the spatial direction corresponding to the spatial gradient component with the largest numerical value or the highest weighted contribution rate in the spatial gradient vector. Based on the initial thermal risk range and the dominant direction of the spatial temperature gradient, the final thermal risk coefficient level is determined, and the final thermal risk coefficient level is used as the thermal risk coefficient level corresponding to the thermal imbalance index.

4. The power dynamic distribution method for a three-dimensional heating coil according to claim 1, characterized in that, The calculation of the power distribution ratio of each heating coil based on the thermal risk factor level and the health status of each heating coil includes: A risk channel mapping table is pre-established between thermal risk coefficient levels and power allocation optimization channels. Based on the thermal risk coefficient levels, the set of power allocation optimization channels participating in power allocation decisions within the current control cycle is determined from the risk channel mapping table. Based on the health status of each heating coil, a health constraint is applied to the power allocation optimization channel set to obtain a constrained power allocation optimization channel set. In the constrained power allocation optimization channel set, the power allocation ratio of each heating coil is determined according to the power requirements of each heating coil.

5. The power dynamic distribution method for a three-dimensional heating coil according to claim 4, characterized in that, The step of applying health constraints to the power allocation optimization channel set based on the health status of each heating coil includes: When the health status of a heating coil is lower than a preset health threshold, the maximum allowable output power of the heating area corresponding to that heating coil in the current control cycle is limited, and / or its priority in participating in power allocation decisions is reduced.

6. The power dynamic distribution method for a three-dimensional heating coil according to claim 4, characterized in that, In the constrained power allocation optimization channel set, determining the power allocation ratio of each heating coil based on its power requirement includes: Based on the risk participation level of each heating zone, a risk suppression factor is applied to the power demand of the corresponding heating zone of each heating coil to obtain the risk-corrected power demand; Based on the constrained power allocation optimization channel set, the maximum allowable output power of each heating zone in the current control cycle is determined, and the risk correction power demand exceeding the maximum allowable output power is limited. The power demand for risk correction after limiting is normalized to obtain the power allocation ratio of each heating coil.

7. The power dynamic distribution method for a three-dimensional heating coil according to claim 1, characterized in that, The real-time calculation of the virtual thermal center position of the three-dimensional heating coil includes: The actual power output value of each heating coil in the current control cycle and the real-time temperature information of the corresponding heating area are obtained, and the equivalent spatial position parameters of each heating coil are preset or calibrated. Based on the actual power output value of each heating coil and the temperature information of its corresponding heating area, the thermal contribution weight of each heating coil in the current control cycle is calculated. The thermal contribution weight is the product of the actual power output value and the temperature weight. The temperature weight is obtained based on the real-time temperature information of the heating area. Based on the thermal contribution weight of each heating coil and its corresponding equivalent spatial position parameters, the virtual thermal center position within the current control cycle is calculated.

8. A dynamic power distribution system for a three-dimensional heating coil, characterized in that, It includes: The acquisition unit is used to acquire temperature information of each heating zone corresponding to the three-dimensional heating coil; Each heating region includes at least a bottom region, a sidewall region, and a transition region. The bottom region, sidewall region, and transition region correspond to the bottom heating coil, the sidewall heating coil, and the R-angle heating coil domain of the transition region between the bottom and the sidewall, respectively. The index unit determines the thermal imbalance index based on the temperature information; the thermal imbalance index is used to characterize the degree of temperature dispersion in different heating areas. Risk unit, used to determine the corresponding thermal risk coefficient level based on the thermal imbalance index; A status unit is used to assess the health status of each heating coil based on the resistance change parameters and / or thermal response characteristics of each heating coil. The distribution unit is used to calculate the power distribution ratio of each heating coil based on the thermal risk coefficient level and the health status of each heating coil, so as to drive each heating coil to heat according to the power distribution ratio; The adjustment unit is used to calculate the virtual thermal center position of the three-dimensional heating coil in real time based on the power distribution ratio. When the virtual thermal center deviates from the preset target area, the power distribution ratio is corrected to adjust the power output of each heating coil.

9. An electronic device, characterized in that, It includes: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the power dynamic distribution method of the three-dimensional heating coil according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program, wherein the computer program causes a computer to execute the power dynamic distribution method of the three-dimensional heating coil according to any one of claims 1-7.

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