Graphene carbon nanotube heating film partition temperature control method

Abstract

The application provides a graphene carbon nanotube heating film partition temperature control method, which comprises collecting real-time temperatures and target temperatures of each heating partition, calculating temperature change rates, and combining partition identifiers, temperature data and change rates to generate a composite state key; a telescopic hash table is constructed to store a mapping of the composite state key and a heating power parameter, and a storage address is determined through double-hash value bit rotation XOR and modulo operation; when a conflict occurs, a control urgency is calculated according to an absolute value of a temperature difference and a deterioration change rate component, so that a high-urgency key occupies a current address preferentially; meanwhile, a reconstruction threshold is dynamically adjusted based on an average temperature, a temperature variance and a time gradient, and when the threshold exceeds a limit, a hash table length is updated according to a safety target filling factor and a prime number rule; finally, a power parameter is obtained through the composite state key table lookup to realize partition power regulation.

Description

Technical Field

[0001] This application belongs to the field of control, and particularly relates to a method for zoned temperature control of a graphene carbon nanotube heating film. Background Technology

[0002] In practical applications, graphene carbon nanotube heating films are often affected by factors such as changes in the external environment, differences in heat absorption of the heat transfer medium, and inconsistent installation contact conditions, which can easily lead to uneven temperature distribution. To achieve precise control of large-area heating films, it is usually necessary to divide the heating film into multiple independent heating zones and implement array-style temperature control for each zone. This type of multi-zone temperature control mode not only requires the system to acquire the real-time temperature, target temperature, and temperature change trend of each zone separately, but also requires the control system to complete state identification, parameter matching, and power output within a short control cycle in order to respond promptly to external disturbances or changes in local thermal load.

[0003] However, when there are many partitions, high sampling frequencies, and complex state dimensions, traditional temperature control data processing methods often rely on fixed lookup tables, static index structures, or conventional retrieval mechanisms, making it difficult to adapt to rapid changes in the temperature state of each partition. When multiple partitions simultaneously request state mapping, mapping conflicts, extended retrieval paths, or unreasonable parameter scheduling can easily increase the delay in obtaining control commands. Furthermore, existing mechanisms typically lack a comprehensive assessment of the degree of temperature difference deviation and temperature deterioration trends, making it difficult to prioritize partitions with localized overheating, temperature loss, or significant deviations from the target trend. In addition, conventional storage and retrieval structures usually do not dynamically adjust based on the average level, dispersion, and rate of change of the overall thermal field of the heating film, resulting in insufficient adaptability during rapid changes in the thermal field. This affects the response efficiency, partition coordination, and operational stability of multi-partition heating film temperature control. Summary of the Invention

[0004] To address the problems in existing technologies such as conflicting state mappings of multi-zone heating films, delayed response to urgent temperature control zones, increased delay in acquiring control commands, and difficulty in adaptively adjusting the retrieval structure to changes in the thermal field, the present invention provides a method for zoned temperature control of graphene carbon nanotube heating films, comprising the following steps:

[0005] Obtain the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film; calculate the temperature change rate, and combine the zone identifier, quantified current temperature value, target temperature value and temperature change rate into a composite state bond; A scaling hash table is constructed to store the mapping relationship between composite status keys and heating power control parameters. The hash value of the composite status key is calculated using a first hash algorithm, and the hash value of the partition identifier is calculated using a second hash algorithm. The two hash values ​​are then subjected to a bit-rotation XOR operation, and the hash address is obtained by taking the modulo of the current hash table length. When a conflict occurs, the control urgency of the newly inserted key and the existing key is calculated based on the absolute value of the error between the current temperature and the target temperature, as well as the temperature change rate component that causes the error to increase. The key with higher urgency is retained at the current hash address, and the key with lower urgency is migrated along a preset detection path. When the preset maximum detection length is reached and the writing is not completed, the current detection length is recorded, and the composite status key is marked as pending relocation. A global state descriptor containing average temperature, temperature variance, and time gradient is constructed, and the fill factor threshold and probe length threshold are dynamically adjusted according to the global state descriptor to set the hash table reconstruction trigger condition. When the actual fill factor or probe length exceeds the corresponding threshold, a new hash table length is calculated. The composite state key is used to retrieve control parameters in the hash table for power output control.

[0006] On the other hand, the present invention also provides a zoned temperature control system for a graphene carbon nanotube heating film, comprising the following modules: The combination module is used to obtain the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film; calculate the temperature change rate; and combine the zone identifier, the quantified current temperature value, the target temperature value and the temperature change rate into a composite state key. The calculation module is used to construct a retractable hash table to store the mapping relationship between composite status keys and heating power control parameters. It uses a first hash algorithm to calculate the hash value of the composite status key and a second hash algorithm to calculate the hash value of the partition identifier. After performing a bit-rotation XOR operation on the two hash values, it takes the modulo of the current hash table length to obtain the hash address. When a conflict occurs, it calculates the control urgency of the newly inserted key and the existing key based on the absolute value of the error between the current temperature and the target temperature, as well as the temperature change rate component that causes the error to increase. The key with higher urgency is retained at the current hash address, and the key with lower urgency is migrated along the preset detection path. When the preset maximum detection length is reached and the writing is not completed, the current detection length is recorded and the composite status key is marked as pending relocation. The control module is used to construct a global state descriptor containing average temperature, temperature variance, and time gradient, and dynamically adjust the fill factor threshold and probe length threshold according to the global state descriptor to set the hash table reconstruction trigger condition. When the actual fill factor or probe length exceeds the corresponding threshold, a new hash table length is calculated. The control parameters are retrieved from the hash table using a composite state key to control power output.

[0007] This invention combines the current temperature, target temperature, temperature change rate, and partition identifier into a composite status key to characterize the real-time control status of each heating partition. A dual hash algorithm combined with bit-rotation XOR operations is used to determine the hash address, which helps improve the hash distribution of the status data. During hash collision handling, a control urgency evaluation mechanism based on temperature error and deterioration rate of change components is introduced, allowing partitions with larger temperature differences or obvious deviation trends to be preferentially retained in shorter retrieval paths. Furthermore, the reconstruction trigger threshold is dynamically adjusted by combining average temperature, temperature variance, and time gradient, and the new table length is determined based on the safety target fill factor and prime number rules, thereby achieving rapid retrieval and output of partition power parameters and improving the response efficiency and operational stability of the heating film temperature control. Attached Figure Description

[0008] Figure 1 A flowchart of a method for zoned temperature control of a graphene carbon nanotube heating film; Figure 2 The temperature versus rate characteristic graph is shown. Figure 3 A priority calculation chart for controlling urgency. Detailed Implementation

[0009] 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.

[0010] 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.

[0011] 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.

[0012] References to "one embodiment" or "some embodiments" as described in this application 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 another embodiment," "in yet another embodiment," etc., appearing in different parts of this application 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 all mean "including but not limited to," unless otherwise specifically emphasized.

[0013] In this application, a method for zoned temperature control of a graphene carbon nanotube heating film is disclosed, such as... Figure 1 As shown, the method includes: S1, obtain the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film; calculate the temperature change rate, and combine the zone identifier, quantified current temperature value, target temperature value and temperature change rate into a composite state bond.

[0014] The STM32F103 microcontroller reads temperature sampling signals from thermistors or thin-film platinum resistance thermometers distributed in each heating zone through a multiplexed sampling circuit. After analog-to-digital conversion, the current temperature value of each zone is obtained. The current temperature value of each zone is obtained as a floating-point number, and the target temperature value sent by the host computer is received through UART serial communication.

[0015] The temperature change rate is obtained by subtracting the current temperature value of the previous sampling period from the current temperature value of the current sampling period, and then dividing by the sampling time interval obtained by the system timer, using a differential algorithm.

[0016] An interval offset quantization encoding method is adopted. The current temperature value and the target temperature value are each subtracted from a preset lower limit value, multiplied by a scaling factor, and then converted into unsigned eight-bit integers. Preferably, the preset lower limit value is set to 35℃, and the scaling factor is set to 10. When the temperature range is 35℃ to 60℃, the quantized current temperature value or target temperature value is between 0 and 250, falling within the representation range of an unsigned eight-bit integer. When the temperature value is lower than the preset lower limit value, it is treated as the preset lower limit value; when the temperature value is higher than the preset upper limit value, it is treated as the preset upper limit value before quantization encoding. The temperature change rate is multiplied by the corresponding scaling factor 10 and then added with a preset offset of 127, mapped to an unsigned eight-bit integer, and the mapping result is subjected to a limiting processing within the range of 0 to 255.

[0017] Using bitwise shift operations, the 8-bit zone identifier is shifted left by 24 bits, the quantized current temperature value is shifted left by 16 bits, and the quantized target temperature value is shifted left by 8 bits. These four parameters are then bitwise ORed with the quantized temperature change rate, concatenating them into a 32-bit unsigned integer variable, which serves as the composite status key. The zone identifier is represented as an 8-bit unsigned integer at runtime; the string-type zone name in the display interface or configuration file, such as "Zone_03," is converted to a corresponding numerical zone identifier (e.g., the value 3) using a preset zone mapping table before participating in the composite status key concatenation and hash calculation.

[0018] In some implementations, obtaining the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film includes: The system uses a timer inside the hardware to send periodic sampling signals, which control the temperature sensors configured at the intersection of each heating grid to collect analog temperature electrical signals. The signals are then input to the microprocessor through an analog-to-digital converter to obtain the current temperature value in the current sampling period. The steady-state operating target value, which is pre-written into the memory and associated with the corresponding partition address code, is read through the communication interface and used as the desired target temperature value.

[0019] The underlying hardware architecture of the graphene carbon nanotube heating film includes a microprocessor with a high-precision timer set to send sampling trigger signals with a period of 100ms to 500ms, preferably 200ms. The graphene carbon nanotube heating film is physically divided into several heating zones, such as 64 grid zones. High-precision thermistors or thin-film platinum resistance thermometers are mounted on the center and intersection areas of each zone.

[0020] When the timer trigger signal arrives, the temperature sensors in each zone are selected by a multiplexer. The acquired 0-3.3V analog voltage signals are smoothed and denoised by the signal conditioning circuit before being input to the microprocessor's built-in ADC module for analog-to-digital conversion. For example, when the sampling voltage is 1.65V, the corresponding 12-bit ADC conversion value is 2048, which is converted to the current temperature value using the built-in resistance-temperature conversion lookup table.

[0021] When acquiring the target temperature value, the microprocessor reads a pre-stored configuration file from an external EEPROM or internal Flash memory via the I2C or SPI communication bus. The data structure in the memory stores data in key-value pairs: "zone address code - target temperature". For example, the target temperature value for zone "Zone_03" is read as 45.5℃. This process enables each heat-generating zone to have an independent temperature regulation reference, allowing the target value to be reloaded according to environmental requirements.

[0022] In some implementations, the calculation of the rate of temperature change includes: Read the historical temperature reference reading of the same heating zone in the memory from the previous sampling period; The temperature change is obtained by subtracting the current temperature value obtained in this cycle from the historical temperature reference reading. Obtain the actual time interval step size between two consecutive sampling operations; Divide the temperature change by the time interval step size to calculate the temperature change rate, which represents the rate of temperature change of the heating zone within the specified time period.

[0023] The microprocessor's RAM working area maintains a circular buffer to cache the historical temperature data of each heat-generating zone for the most recent 3 to 5 sampling periods. After obtaining the current temperature value of a zone in the current sampling period, for example, 42.3℃, the historical temperature reference reading of that zone in the previous sampling period, for example, 41.8℃, is read from the buffer via pointer addressing.

[0024] Calculate the temperature change within the sampling period, for example, if the temperature change is 0.5℃. If the difference is greater than 0, it indicates a heating state; if it is less than 0, it indicates a cooling state. Using the internal high-precision system tick timer, obtain the absolute timestamps of two samples and calculate the difference to obtain the actual sampling time interval between the two consecutive sampling operations. For example, it is 0.202 seconds.

[0025] Dividing the calculated 0.5℃ temperature change by the 0.202-second sampling time interval yields a temperature change rate of 2.475℃ / s. This parameter is encoded and incorporated into the composite status key. The time sequence of temperature and rate of change for a single heating zone during the heating phase is as follows: Figure 2 As shown.

[0026] S2, construct a scaling hash table to store the mapping relationship between composite status keys and heating power control parameters. Calculate the hash value of the composite status key using the first hash algorithm and the hash value of the partition identifier using the second hash algorithm. Perform a bitwise XOR operation on the two hash values ​​and then take the modulo of the current hash table length to obtain the hash address. When a conflict occurs, calculate the control urgency of the newly inserted key versus the existing key based on the absolute value of the error between the current temperature and the target temperature, and the temperature change rate component that causes the error to increase. The key with higher urgency is retained at the current hash address, while the key with lower urgency migrates along a preset detection path. If the writing is not completed after reaching the preset maximum detection length, record the current detection length and mark the composite status key as pending relocation.

[0027] An array is allocated and encapsulated as a hash table structure. Array elements contain composite state keys and corresponding PWM (Pulse Width Modulation) duty cycle control parameters. These PWM duty cycle control parameters are generated by preset power control rules. Specifically, the microprocessor calculates the difference between the target temperature value and the current temperature value to obtain the temperature control error; multiplies the temperature control error by a preset error adjustment coefficient to obtain a first duty cycle adjustment amount; multiplies the temperature change rate by a preset rate of change suppression coefficient to obtain a second duty cycle adjustment amount; using a preset base duty cycle as a reference, the first duty cycle adjustment amount is added to the base duty cycle, and the second duty cycle adjustment amount is subtracted to obtain the initial PWM duty cycle parameters. Subsequently, the initial PWM duty cycle parameters are restricted between a preset minimum duty cycle and a preset maximum duty cycle to obtain the final PWM duty cycle control parameters. For example, with a base duty cycle of 40%, a preset error adjustment coefficient of 3% / ℃, and a preset rate of change suppression coefficient of 2% / (℃ / s), when the target temperature is 45℃, the current temperature is 42℃, and the temperature change rate is 1℃ / s, the initial PWM duty cycle is 40%+3×3%-2×1%=47%, which, after being limited, is used as the PWM duty cycle control parameter corresponding to the composite state key.

[0028] The first preset hash algorithm, such as MurmurHash3, is invoked to perform bit obfuscation and multiplicative hashing on the 32-bit composite status key, generating a 32-bit first hash value. The second preset hash algorithm, such as FNV1a, is then invoked to perform XOR and multiplication operations on the eight-bit numeric partition identifier using the prime number 16777619, generating a 32-bit second hash value. The hash address is determined based on the first and second hash values.

[0029] The first hash value is cyclically shifted left by a preset number of bits and then XORed bitwise with the second hash value. The result is then modulo the current hash table length to obtain the initial hash address. When this initial hash address is already occupied by another composite state key, a hash collision is determined, and the control urgency of the partition corresponding to the current composite state key is calculated. The control urgency is determined based on the absolute value of the error between the current temperature and the target temperature, and the temperature change rate component that causes this error to continue to increase. Specifically, when the direction of the temperature change rate causes the current temperature to deviate further from the target temperature, the absolute value of the temperature change rate is used as the temperature change rate component; otherwise, the temperature change rate component is set to zero. After normalizing the absolute value of the error and the temperature change rate component respectively, they are weighted and summed according to preset weights to obtain the control urgency value.

[0030] The control urgency of the newly inserted key is compared with that of an existing key at the same address. If the urgency of the newly inserted key is greater than that of the existing key, the newly inserted key is written to the current hash address, replacing the original key, which then becomes a low-urgency key. For low-urgency keys, a quadratic probing algorithm (square probing) is used, calculating a new offset address by incrementing the step size by the square of one and the square of two, respectively, to find an available position. If the current probe length reaches the preset maximum probe length without completion, the probe length is recorded, and the corresponding composite state key and its corresponding heat dissipation power control parameters are temporarily stored as a record to be relocated. If the control urgency of the newly inserted key is not greater than that of the existing key, the existing key remains occupied at the current hash address, and the newly inserted key continues to probe along the preset probe path as a low-urgency key.

[0031] In some implementations, the step of performing a bitwise XOR operation on the two hash values ​​and then taking the modulo of the current hash table length to obtain the hash address includes: The binary data string corresponding to the hash value of the composite state key calculated using the first hash algorithm is circularly shifted left by five bits to obtain the first derived data string. Perform a bitwise XOR operation between the first derived data string and the hash value of the partition identifier of the composite state key calculated using the second hash algorithm to generate a fused feature code. The fused feature code is moduloed by the current hash table length, and the remainder is used as the hash address.

[0032] The composite state key is hashed using the first hash algorithm, outputting a 32-bit unsigned integer as the first hash value. This 32-bit data is then circularly shifted left by 5 bits, moving the most significant 5 bits to the least significant bit, generating the first derived data string. This operation alters the weight distribution of the original hash value across its bits, improving the spatial hashability of the key value.

[0033] The second hash algorithm is used to separately calculate the numerical partition identifier of the heat-generating partition, resulting in another 32-bit second hash value. For example, the partition displayed as "Zone_03" in the configuration file is first mapped to the numerical partition identifier 3 at runtime, and then participates in the FNV1a operation. The processor executes a bitwise XOR instruction to XOR the first derived data string with the second hash value bit by bit, generating a fused feature code where corresponding bits are 0 if they are the same and 1 if they are different.

[0034] To obtain the current length of the hash table maintained by the system, for example, if the current length is 1009 after using a prime number expansion strategy, perform a modulo operation on the length value 1009 using the decimal value corresponding to the fused feature code. The resulting remainder, for example, 452, is the hash address in the hash table storing the power control parameters corresponding to the current state of this partition.

[0035] In some implementations, calculating the control urgency of the newly inserted key versus the existing key based on the absolute value of the error between the current temperature and the target temperature, and the temperature change rate component that causes the error to increase, includes: Calculate the absolute value of the difference between the current temperature value and the target temperature value at the current detection moment, and use it as the first urgency component; Determine whether the direction of the current rate of temperature change causes the absolute value of the difference to increase. If so, take the absolute value of the rate of temperature change as the second urgency component; otherwise, set the second urgency component to zero. After normalizing the first urgency component and the second urgency component respectively, they are weighted and summed using preset weighting coefficients to obtain the total value representing the intensity of power regulation demand, which is used as the control urgency.

[0036] When an address collision occurs in the hash table, the current temperature value of the partition involved in the collision (e.g., 38.5℃) and the target temperature value (e.g., 45.0℃) are obtained. The absolute value of the error between the two (6.5℃) is calculated as the first urgency component. The trend of the temperature change rate is evaluated. Assuming the current temperature change rate of the partition is -1.2℃ / s, and given that it is currently at 38.5℃ and continues to cool, this change direction will cause the temperature to deviate from the target value.

[0037] After confirming this deviation trend, the absolute value of the temperature change rate, 1.2℃ / s, is extracted as the second urgency component. If the current temperature is trending towards the target value, the second urgency component is set to 0. Maximum and minimum normalization is then applied to the first and second urgency components. Assuming the maximum temperature difference benchmark set in the system is 20.0℃ and the maximum temperature change rate benchmark is 5.0℃ / s, the normalized values ​​are 0.325 and 0.240, respectively.

[0038] Using preset weights, with the first urgency weighted at 0.6 and the second urgency weighted at 0.4, a weighted sum is obtained, resulting in a control urgency value of 0.291. During conflict resolution, the control urgency of the newly inserted key is compared with that of existing keys in the hash table. The key with the higher control urgency occupies the hash position, and the existing key is shifted to the next available position. The composition and priority calculation results of control urgency under multiple conflict events are as follows: Figure 3 As shown.

[0039] S3. Construct a global state descriptor containing average temperature, temperature variance, and time gradient. Dynamically adjust the fill factor threshold and probe length threshold based on the global state descriptor to set the hash table reconstruction trigger condition. When the actual fill factor or probe length exceeds the corresponding threshold, calculate a new hash table length. Use the composite state key to retrieve control parameters in the hash table for power output control.

[0040] Define a structure as the global state descriptor. Iterate through the current temperature values ​​of all partitions and sum them up, then divide by the total number of partitions to calculate the average temperature. Calculate the square of the difference between the temperature of each partition and the average temperature, sum all the squared values, and divide by the total number of partitions to calculate the temperature variance. Subtract the average temperature of the previous period from the average temperature of the current period, and then divide by the difference in period duration recorded by the timer to obtain the time gradient.

[0041] The basic fill factor threshold is set to 0.75, and the basic detection length threshold is set to 5. The deviation of the average temperature from the mean target temperature of each zone is calculated, and the deviation is normalized. Simultaneously, the temperature variance and the absolute value of the time gradient are normalized. Based on the normalized average temperature deviation, the normalized temperature variance, and the normalized absolute value of the time gradient, the fill factor threshold and the detection length threshold are jointly adjusted.

[0042] Specifically, when at least one of the average temperature deviation, temperature variance, and absolute value of the time gradient increases, the fill factor threshold and probe length threshold are lowered, so that the hash table triggers reconstruction earlier when the overall temperature deviation, the temperature dispersion of the partitions is high, or the thermal field changes rapidly. For example, the fill factor threshold is obtained by subtracting the sum of the products of the three normalized parameters and their corresponding preset adjustment coefficients from the basic fill factor threshold; the probe length threshold is obtained by subtracting the sum of the products of the three normalized parameters and their corresponding preset adjustment coefficients from the basic probe length threshold and rounding down. The preset adjustment coefficients are obtained by calibration using historical temperature control experimental data and are used to characterize the influence of the average temperature deviation, temperature variance, and absolute value of the time gradient on the hash table reconstruction requirements. The fill factor threshold is limited to between a preset lower limit and a preset upper limit, for example, between 0.30 and 0.85; the probe length threshold is limited to between a preset lower limit and a preset upper limit, for example, between 2 and 8.

[0043] The actual fill factor is obtained by dividing the total number of keys currently stored in the hash table by the current hash table length. Hash table reconstruction is triggered when the actual fill factor is greater than the fill factor threshold, or when the probe length recorded during key insertion is not less than the probe length threshold. During reconstruction, a security target fill factor not greater than the fill factor threshold is used as the target load level after expansion; the total number of keys currently stored in the hash table is divided by the security target fill factor and rounded up to obtain a base length integer value; primality testing is performed starting from the base length integer value, and the first detected prime number is used as the new hash table length, and the hash table array is reallocated accordingly. After reallocating the hash table array, the microprocessor traverses the valid composite state keys and records to be relocated in the original hash table, recalculates the hash address according to the new hash table length, and writes each composite state key and its corresponding heat dissipation power control parameters into the new hash table.

[0044] In the system control loop, the latest sensor status is acquired and a composite status key for retrieval is generated. The MurmurHash3 and FNV1a algorithms are reused, combining bit-rotation XOR and modulo operations to locate the hash address. If the current composite status key matches in the hash table, the stored PWM duty cycle parameter is retrieved; if the current composite status key does not match, the PWM duty cycle parameter is generated according to the current temperature value, target temperature value, and temperature change rate, based on a preset power control rule, and the composite status key and PWM duty cycle parameter are written into the hash table. This parameter is then passed to the CCR comparator register of the STM32F103 microcontroller's advanced control timer TIM1, changing the duty cycle of the output PWM signal, thereby controlling the on-time ratio of the field-effect transistors and completing the power output control of each heating zone.

[0045] In some implementations, calculating a new hash table length includes: Count the total number of keys currently stored in the hash table; The safety target fill factor is determined based on the current fill factor threshold, and the safety target fill factor is not greater than the fill factor threshold. Divide the total number of stored keys by the security target fill factor, and round the result up to obtain the base length integer value; Starting from the integer value of the base length, increment by natural numbers sequentially upwards, and perform primality testing on each increment value; When the first value that is divisible only by 1 and itself is detected, that value is confirmed as the new hash table length.

[0046] When the hash table resizing trigger condition is met, the microprocessor traverses the valid bitmap of the current hash table and counts the total number of keys currently stored in the hash table, for example, if the current total number of keys is 435. A security target fill factor is determined based on the current fill factor threshold; for example, if the fill factor threshold is 0.50, the security target fill factor is set to 0.40. The current total number of keys is divided by the security target fill factor, and the result is rounded up to obtain the integer value of the base length after resizing; for example, 435 divided by 0.40 equals 1087.5, and rounded up, it equals 1088. This base length integer value is used to determine the lower limit of the hash table length after resizing.

[0047] After determining the base length integer value, the hash table increments sequentially by natural numbers with a step size of 1, starting from the base length integer value. For each increment value, a primality detection algorithm is used to check for even numbers and numbers divisible by 3. This involves first excluding even numbers and numbers divisible by 3, then performing factorization checks, ensuring the maximum number of factors tested does not exceed the square root of the value. For example, when the base length integer value is 1088, natural numbers not less than 1088 are checked sequentially, and the first detected prime number is used as the new hash table length. The microprocessor then uses this prime number as the new hash table length and allocates a corresponding contiguous space in memory to complete the hash reconstruction. This reduces subsequent hash collisions and lowers the probability of excessively long probe paths, while also reducing the risk of triggering resizing immediately after reconstruction.

[0048] In this application, a zoned temperature control system for a graphene carbon nanotube heating film is disclosed, the system comprising: The combination module is used to obtain the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film; calculate the temperature change rate; and combine the zone identifier, the quantified current temperature value, the target temperature value and the temperature change rate into a composite state key. The calculation module is used to construct a retractable hash table to store the mapping relationship between composite status keys and heating power control parameters. It uses a first hash algorithm to calculate the hash value of the composite status key and a second hash algorithm to calculate the hash value of the partition identifier. After performing a bit-rotation XOR operation on the two hash values, it takes the modulo of the current hash table length to obtain the hash address. When a conflict occurs, it calculates the control urgency of the newly inserted key and the existing key based on the absolute value of the error between the current temperature and the target temperature, as well as the temperature change rate component that causes the error to increase. The key with higher urgency is retained at the current hash address, and the key with lower urgency is migrated along the preset detection path. When the preset maximum detection length is reached and the writing is not completed, the current detection length is recorded and the composite status key is marked as pending relocation. The control module is used to construct a global state descriptor containing average temperature, temperature variance, and time gradient, and dynamically adjust the fill factor threshold and probe length threshold according to the global state descriptor to set the hash table reconstruction trigger condition. When the actual fill factor or probe length exceeds the corresponding threshold, a new hash table length is calculated. The control parameters are retrieved from the hash table using a composite state key to control power output.

[0049] In some implementations, obtaining the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film includes: The system uses a timer inside the hardware to send periodic sampling signals, which control the temperature sensors configured at the intersection of each heating grid to collect analog temperature electrical signals. The signals are then input to the microprocessor through an analog-to-digital converter to obtain the current temperature value in the current sampling period. The steady-state operating target value, which is pre-written into the memory and associated with the corresponding partition address code, is read through the communication interface and used as the desired target temperature value.

[0050] In some implementations, the calculation of the rate of temperature change includes: Read the historical temperature reference reading of the same heating zone in the memory from the previous sampling period; The temperature change is obtained by subtracting the current temperature value obtained in this cycle from the historical temperature reference reading. Obtain the actual time interval step size between two consecutive sampling operations; Divide the temperature change by the time interval step size to calculate the temperature change rate, which represents the rate of temperature change of the heating zone within the specified time period.

[0051] In some implementations, the step of performing a bitwise XOR operation on the two hash values ​​and then taking the modulo of the current hash table length to obtain the hash address includes: The binary data string corresponding to the hash value of the composite state key calculated using the first hash algorithm is circularly shifted left by five bits to obtain the first derived data string. Perform a bitwise XOR operation between the first derived data string and the hash value of the partition identifier of the composite state key calculated using the second hash algorithm to generate a fused feature code. The fused feature code is moduloed by the current hash table length, and the remainder is used as the hash address.

[0052] In some implementations, calculating the control urgency of the newly inserted key versus the existing key based on the absolute value of the error between the current temperature and the target temperature, and the temperature change rate component that causes the error to increase, includes: Calculate the absolute value of the difference between the current temperature value and the target temperature value at the current detection moment, and use it as the first urgency component; Determine whether the direction of the current rate of temperature change causes the absolute value of the difference to increase. If so, take the absolute value of the rate of temperature change as the second urgency component; otherwise, set the second urgency component to zero. After normalizing the first urgency component and the second urgency component respectively, they are weighted and summed using preset weighting coefficients to obtain the total value representing the intensity of power regulation demand, which is used as the control urgency.

[0053] In some implementations, calculating a new hash table length includes: Count the total number of keys currently stored in the hash table; The safety target fill factor is determined based on the current fill factor threshold, and the safety target fill factor is not greater than the fill factor threshold. Divide the total number of stored keys by the security target fill factor, and round the result up to obtain the base length integer value; Starting from the integer value of the base length, increment by natural numbers sequentially upwards, and perform primality testing on each increment value; When the first value that is divisible only by 1 and itself is detected, that value is confirmed as the new hash table length.

[0054] 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 method for zoned temperature control of a graphene carbon nanotube heating film, characterized in that, include: Obtain the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film; Calculate the temperature change rate and combine the zone identifier, quantified current temperature value, target temperature value, and temperature change rate into a composite status key; A scaling hash table is constructed to store the mapping relationship between composite status keys and heating power control parameters. The hash value of the composite status key is calculated using the first hash algorithm, and the hash value of the partition identifier is calculated using the second hash algorithm. The two hash values ​​are then subjected to a bit-rotation XOR operation, and the hash address is obtained by taking the modulo of the current hash table length. When a conflict occurs, the control urgency of the newly inserted key and the existing key is calculated based on the absolute value of the error between the current temperature and the target temperature, as well as the temperature change rate component that causes the error to increase. The key with higher urgency is retained at the current hash address, while the key with lower urgency migrates along the preset detection path. When the preset maximum detection length is reached and the writing is not completed, the current detection length is recorded, and the composite state key is marked as a state to be relocated. A global state descriptor containing average temperature, temperature variance, and time gradient is constructed, and the fill factor threshold and probe length threshold are dynamically adjusted according to the global state descriptor to set the hash table reconstruction trigger condition. When the actual fill factor or probe length exceeds the corresponding threshold, a new hash table length is calculated. The composite state key is used to retrieve control parameters in the hash table for power output control.

2. The method according to claim 1, characterized in that, The step of obtaining the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film includes: The system uses a timer inside the hardware to send periodic sampling signals, which control the temperature sensors configured at the intersection of each heating grid to collect analog temperature electrical signals. The signals are then input to the microprocessor through an analog-to-digital converter to obtain the current temperature value in the current sampling period. The steady-state operating target value, which is pre-written into the memory and associated with the corresponding partition address code, is read through the communication interface and used as the desired target temperature value.

3. The method according to claim 2, characterized in that, The calculation of the rate of temperature change includes: Read the historical temperature reference reading of the same heating zone in the memory from the previous sampling period; The temperature change is obtained by subtracting the current temperature value obtained in this cycle from the historical temperature reference reading. Obtain the actual time interval step size between two consecutive sampling operations; Divide the temperature change by the time interval step size to calculate the temperature change rate, which represents the rate of temperature change of the heating zone within the specified time period.

4. The method according to claim 1, characterized in that, The step of performing a bitwise XOR operation on the two hash values ​​and then taking the modulo of the current hash table length to obtain the hash address includes: The binary data string corresponding to the hash value of the composite state key calculated using the first hash algorithm is circularly shifted left by five bits to obtain the first derived data string. Perform a bitwise XOR operation between the first derived data string and the hash value of the partition identifier of the composite state key calculated using the second hash algorithm to generate a fused feature code. The fused feature code is moduloed by the current hash table length, and the remainder is used as the hash address.

5. The method according to claim 1, characterized in that, The step of calculating the control urgency of the newly inserted key versus the existing key based on the absolute value of the error between the current temperature and the target temperature, and the temperature change rate component that causes the error to increase, includes: Calculate the absolute value of the difference between the current temperature value and the target temperature value at the current detection moment, and use it as the first urgency component; Determine whether the direction of the current rate of temperature change causes the absolute value of the difference to increase. If so, take the absolute value of the rate of temperature change as the second urgency component; otherwise, set the second urgency component to zero. After normalizing the first urgency component and the second urgency component respectively, they are weighted and summed using preset weighting coefficients to obtain the total value representing the intensity of power regulation demand, which is used as the control urgency.

6. The method according to claim 1, characterized in that, The calculation of a new hash table length includes: Count the total number of keys currently stored in the hash table; The safety target fill factor is determined based on the current fill factor threshold, and the safety target fill factor is not greater than the fill factor threshold. Divide the total number of stored keys by the security target fill factor, and round the result up to obtain the base length integer value; Starting from the integer value of the base length, increment by natural numbers sequentially upwards, and perform primality testing on each increment value; When the first value that is divisible only by 1 and itself is detected, that value is confirmed as the new hash table length.

7. A zoned temperature control system for a graphene carbon nanotube heating film, characterized in that, include: The combined module is used to obtain the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film; Calculate the temperature change rate and combine the zone identifier, quantified current temperature value, target temperature value, and temperature change rate into a composite status key; The calculation module is used to construct a retractable hash table to store the mapping relationship between the composite status key and the heating power control parameters. It uses the first hash algorithm to calculate the hash value of the composite status key and the second hash algorithm to calculate the hash value of the partition identifier. After performing a bit-rotation XOR operation on the two hash values, it takes the modulo of the current hash table length to obtain the hash address. When a conflict occurs, the control urgency of the newly inserted key and the existing key is calculated based on the absolute value of the error between the current temperature and the target temperature, as well as the temperature change rate component that causes the error to increase. The key with higher urgency is retained at the current hash address, while the key with lower urgency migrates along the preset detection path. When the preset maximum detection length is reached and the writing is not completed, the current detection length is recorded, and the composite state key is marked as a state to be relocated. The control module is used to construct a global state descriptor containing average temperature, temperature variance, and time gradient, and dynamically adjust the fill factor threshold and probe length threshold according to the global state descriptor to set the hash table reconstruction trigger condition. When the actual fill factor or probe length exceeds the corresponding threshold, a new hash table length is calculated. The control parameters are retrieved from the hash table using a composite state key to control power output.

8. The system according to claim 7, characterized in that, The step of obtaining the current temperature value and target temperature value of each heating zone in the graphene carbon nanotube heating film includes: The system uses a timer inside the hardware to send periodic sampling signals, which control the temperature sensors configured at the intersection of each heating grid to collect analog temperature electrical signals. The signals are then input to the microprocessor through an analog-to-digital converter to obtain the current temperature value in the current sampling period. The steady-state operating target value, which is pre-written into the memory and associated with the corresponding partition address code, is read through the communication interface and used as the desired target temperature value.

9. The system according to claim 7, characterized in that, The calculation of the rate of temperature change includes: Read the historical temperature reference reading of the same heating zone in the memory from the previous sampling period; The temperature change is obtained by subtracting the current temperature value obtained in this cycle from the historical temperature reference reading. Obtain the actual time interval step size between two consecutive sampling operations; Divide the temperature change by the time interval step size to calculate the temperature change rate, which represents the rate of temperature change of the heating zone within the specified time period.

10. The system according to claim 7, characterized in that, The step of performing a bitwise XOR operation on the two hash values ​​and then taking the modulo of the current hash table length to obtain the hash address includes: The binary data string corresponding to the hash value of the composite state key calculated using the first hash algorithm is circularly shifted left by five bits to obtain the first derived data string. Perform a bitwise XOR operation between the first derived data string and the hash value of the partition identifier of the composite state key calculated using the second hash algorithm to generate a fused feature code. The fused feature code is moduloed by the current hash table length, and the remainder is used as the hash address.

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