Temperature control system, method and control chip for an aerosol-generating device

Abstract

The application relates to a temperature control system, method and control chip for an aerosol generating device. The system comprises a temperature measurement module, a heating element, a temperature control chip and a power output module. The temperature measurement module simultaneously collects the terminal voltage and loop voltage of the heating element, and attenuates the terminal voltage and loop voltage by the same proportion respectively to output two voltage signals suitable for the temperature control chip. This design simplifies the calculation of the temperature control chip based on the ASIC chip when calculating the resistance of the heating element. The temperature control chip determines the real-time resistance value of the heating element according to the two voltage signals, and then determines the real-time temperature. In combination with a prediction model and a PID control algorithm, the temperature control chip generates a temperature control signal to realize advance compensation. The power output module drives the heating element to heat the aerosol generating substrate according to the temperature control signal. Through hardware optimization and algorithm optimization, the system significantly improves the temperature control precision, response speed and reduces the power consumption.

Description

Technical Field

[0001] This application relates to the field of electronic control technology, and in particular to a temperature control system, method, control chip, computer-readable storage medium, and computer program product for an aerosol generation device. Background Technology

[0002] With the development of aerosol-related products, the demand for aerosol generating devices is expanding. These devices produce inhalable aerosols by precisely heating an aerosol generating substrate. In this process, precise temperature control is crucial; excessively high temperatures may lead to the formation of harmful substances, while excessively low temperatures affect the amount of aerosol released and the taste. Therefore, a high-precision, high-response temperature control system is key to improving the performance and user experience of aerosol generating devices.

[0003] In traditional technologies, common aerosol generation devices often employ a scheme that combines a microcontroller unit (MCU) with a temperature sensor. The MCU receives temperature data collected by the sensor, executes control logic, and adjusts the heating power to maintain the target temperature range. This approach was widely used in early aerosol generation devices due to its mature technology and low cost.

[0004] However, as consumers' requirements for devices increase, the shortcomings of the above-mentioned MCU-based temperature control solutions have gradually become apparent: First, the processing power of MCUs is limited, making it difficult to meet the computational requirements of high-precision temperature control; second, MCUs need to execute complex instruction sets, resulting in a large temperature response delay and an inability to quickly adapt to temperature changes; third, MCUs consume a lot of power during long-term operation, which seriously affects the portable user experience of aerosol generation devices. These problems have become the main bottlenecks restricting product upgrades. Summary of the Invention

[0005] Therefore, it is necessary to provide a temperature control system, method, control chip, computer-readable storage medium, and computer program product for an aerosol generation device to address the above-mentioned technical problems.

[0006] In a first aspect, this application provides a temperature control system for an aerosol generating device, comprising a temperature measurement module, a heating element, a temperature control chip, and a power output module, wherein:

[0007] The temperature measurement module includes a voltage divider circuit. The temperature measurement module is used to simultaneously acquire the terminal voltage and loop voltage of the heating element through the voltage divider circuit, and attenuate the terminal voltage and the loop voltage by the same ratio to output two voltage signals suitable for the temperature control chip. The voltage divider circuit includes two sets of matched resistor networks, and the voltage division coefficients of the two sets of resistor networks are the same.

[0008] The temperature control chip is an ASIC-based chip used to obtain the current resistance value of the heating element based on the two voltage signals provided by the temperature measurement module, obtain the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, and input the difference between the current temperature and the preset target temperature into the PID control algorithm, and generate a temperature control signal for the current temperature in combination with the preset prediction model.

[0009] The power output module is used to drive the heating element to work according to the temperature control signal, so as to heat the aerosol generating substrate in the aerosol generating device.

[0010] In one embodiment, the temperature measurement module further includes a timing control unit, wherein:

[0011] The timing control unit is used to cut off the working path of the heating element for heating the aerosol generating substrate by means of a preset level signal during the non-heating stage, so that the voltage divider circuit can collect the terminal voltage and loop voltage of the heating element when the heating element is not heated.

[0012] In one embodiment, the two voltage signals include a first voltage signal and a second voltage signal; the two sets of resistor networks include a first resistor network and a second resistor network; the first voltage signal is obtained by inputting the terminal voltage of the heating element into the first resistor network; the second voltage signal is obtained by inputting the loop voltage detected by the current sampling resistor into the second resistor network, wherein the current sampling resistor is connected in series in the working circuit of the heating element; wherein:

[0013] The process by which the temperature control chip obtains the current resistance value of the heating element based on the two voltage signals is as follows:

[0014] Rt=(VB_ADC*R_s) / VOR_ADC

[0015] Wherein, Rt is the current resistance value of the heating element; VB_ADC is the first voltage signal; R_s is the resistance value of the current sampling resistor; and VOR_ADC is the second voltage signal.

[0016] In one embodiment, the temperature control chip is further configured to perform time series analysis based on historical temperature data using the preset prediction model to obtain a predicted temperature value for a future target time; compare the predicted temperature value with a preset target temperature value and generate a compensation signal based on the comparison result; and use the compensation signal to adjust the temperature control signal output by the PID control algorithm to suppress temperature overshoot or undershoot in advance.

[0017] In one embodiment, the temperature control chip obtains the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, as shown in the formula:

[0018] Rt=R0×(1+TCR×(T-T0))

[0019] Wherein, Rt is the current resistance value of the heating element; R0 is the reference resistance value of the heating element at the preset standard temperature; TCR is the temperature coefficient; T is the current temperature of the heating element; and T0 is the preset standard temperature reference value of the heating element.

[0020] In one embodiment, the PID control algorithm is implemented in a digital circuit using a second-order discretization method.

[0021] Secondly, this application provides a temperature control method for an aerosol generation device, applied to a temperature control chip in the system described in the first aspect, comprising:

[0022] Two voltage signals are obtained by attenuating the terminal voltage and loop voltage of the heating element by a voltage divider circuit in the same proportion.

[0023] The current resistance value of the heating element is obtained based on the two voltage signals, and the current temperature of the heating element is obtained based on the current resistance value and the temperature-resistance characteristic relationship of the heating element.

[0024] The difference between the current temperature and the preset target temperature is input into the PID control algorithm, and a temperature control signal for the current temperature is generated by combining it with the preset prediction model.

[0025] The temperature control signal is sent to the power output module so that the power output module responds to the temperature control signal and drives the heating element to work, so as to heat the aerosol generating substrate in the aerosol generating device.

[0026] Thirdly, this application also provides a control chip, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the second aspect.

[0027] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the second aspect.

[0028] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in the second aspect.

[0029] In the aforementioned temperature control system, method, control chip, computer-readable storage medium, and computer program product for an aerosol generation device, the temperature measurement module includes a voltage divider circuit. The temperature measurement module simultaneously acquires the terminal voltage and loop voltage of the heating element through the voltage divider circuit, and attenuates the terminal voltage and loop voltage by the same proportion to output two voltage signals suitable for the temperature control chip. The voltage divider circuit includes two sets of matched resistor networks with the same voltage division coefficient. The temperature control chip is an ASIC-based chip used to obtain the current resistance value of the heating element based on the two voltage signals provided by the temperature measurement module, obtain the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, and input the difference between the current temperature and a preset target temperature into a PID control algorithm. This algorithm, combined with a preset prediction model, generates a temperature control signal for the current temperature. The power output module is used to drive the heating element to operate according to the temperature control signal, thereby heating the aerosol generation substrate in the aerosol generation device. This application reduces noise and errors in the signal processing link through customized ASIC chip design; the matched voltage divider circuit achieves proportional attenuation to simplify calculations and ensure high efficiency in resistance measurement; and the PID algorithm combined with the predictive model effectively suppresses overshoot, collectively achieving temperature control accuracy far exceeding that of traditional MCU solutions. The hardware parallel processing capability of the ASIC is far superior to the sequential instruction execution of the MCU; the matched voltage divider circuit eliminates complex floating-point operations; these factors result in extremely short latency throughout the entire link from signal acquisition to control signal output, significantly improving response speed. The ASIC chip is optimized for a fixed algorithm, resulting in extremely high energy efficiency; simplified calculations also reduce the active time of the arithmetic unit. Both of these significantly reduce system power consumption, which is particularly beneficial for the extended battery life of portable aerosol generation devices. The integrated predictive model gives the system "predictive" capabilities, allowing for advance power adjustments to prevent temperature overshoot or undershoot, resulting in a smoother temperature curve and improved consistency in aerosol generation. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of the temperature control system for an aerosol generation device in one embodiment.

[0032] Figure 2 This is a schematic flowchart of a temperature control method for an aerosol generation device in one embodiment;

[0033] Figure 3 This is a schematic diagram of the voltage divider circuit in one embodiment;

[0034] Figure 4 This is a schematic diagram of the closed-loop control process based on an ASIC-based temperature control chip in another embodiment;

[0035] Figure 5 This is a data illustration of the technical effect of an automatic temperature measurement and calibration system for temperature control of an aerosol generation device in one embodiment;

[0036] Figure 6 This is an internal structure diagram of a temperature control chip in one embodiment. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0038] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0039] The temperature control system for the aerosol generating device provided in this application can be applied to portable, instant-heating aerosol generating devices with extremely high temperature control requirements, so as to accurately control the temperature of the heating element in the aerosol generating device and atomize the aerosol generating substrate at the optimal temperature.

[0040] In one exemplary embodiment, such as Figure 1 As shown, a temperature control system for an aerosol generating device is provided, including a temperature measurement module 101, a heating element 102, a temperature control chip 103, and a power output module 104, wherein:

[0041] The temperature measurement module includes a voltage divider circuit. The temperature measurement module is used to simultaneously acquire the terminal voltage and loop voltage of the heating element through the voltage divider circuit, and attenuate the terminal voltage and the loop voltage by the same ratio to output two voltage signals suitable for the temperature control chip. The voltage divider circuit includes two sets of matched resistor networks, and the voltage division coefficients of the two sets of resistor networks are the same.

[0042] The temperature control chip is an ASIC-based chip used to obtain the current resistance value of the heating element based on two voltage signals provided by the temperature measurement module, obtain the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, and input the difference between the current temperature and the preset target temperature into the PID control algorithm, which combines the preset prediction model to generate a temperature control signal for the current temperature.

[0043] The power output module is used to drive the heating element to work according to the temperature control signal, so as to heat the aerosol generating substrate in the aerosol generating device.

[0044] In this embodiment, the temperature control system for the aerosol generation device mainly uses an ASIC-based dedicated chip as the control core, employs a matched voltage divider circuit with consistent resistance ratios for voltage signal acquisition, and uses a PID algorithm that incorporates a predictive model.

[0045] The temperature measurement module refers to the functional unit in the system responsible for acquiring the raw electrical signal reflecting the operating status of the heating element. The voltage divider circuit refers to a circuit composed of a resistor network, whose basic function is to proportionally reduce (attenuate) the higher input voltage to suit the input range of the back-end chip. The terminal voltage of the heating element refers to the voltage directly applied between the two electrodes of the heating element. The loop voltage of the heating element refers to the voltage at a specific measurement point in a closed working loop containing the heating element. In this embodiment, this "loop voltage" can refer to the voltage drop across a small-value current sampling resistor connected in series in the loop. According to Ohm's law, under the premise that the resistance is known and constant, this voltage drop is proportional to the current flowing through the heating element. Therefore, "acquiring the loop voltage" is essentially an indirect measurement of the operating current. The two matched resistor networks can refer to two independent voltage divider branches within the voltage divider circuit. Matching here means that the resistance ratios in the two branches are the same. For example, the resistance ratio of branch 1 is R1up:R1down, and the resistance ratio of branch 2 is R2up:R2down, where R1up:R1down = R2up:R2down. Thus, the voltage division factor, determined by the specific resistance ratios of the resistor networks, is the same. The voltage division factor is the ratio of the output voltage to the input voltage of the voltage divider circuit. This is the hardware foundation for simplifying subsequent calculations. The two voltage signals can refer to the two voltage values ​​output after attenuation processing by the voltage divider circuit, serving as the raw data for calculating the resistance of the heating element.

[0046] The temperature control chip is an ASIC (Application-Specific Integrated Circuit) based chip, meaning its circuitry is custom-designed for the specific task of temperature control, rather than a general-purpose processor (MCU). This offers advantages such as high speed, low power consumption, and high reliability. The current resistance value refers to the resistance of the heating element calculated in real-time by the chip based on two voltage signals. Due to the voltage divider network matching, this calculation can be simplified, eliminating the need for complex floating-point operations. The temperature-resistance characteristic relationship refers to the physical law governing the change in resistance of the heating element material with temperature, which can be described by a formula. The current temperature refers to the real-time temperature of the heating element calculated by the chip using the above characteristic relationship. The preset target temperature refers to the desired temperature value set by the user or system. The difference is the error in control theory, serving as the direct input for closed-loop feedback control. The PID control algorithm is a classic proportional-integral-derivative feedback control algorithm. In this embodiment, a predictive model capable of predicting future temperature trends based on historical data is integrated to achieve advance compensation. The temperature control signal refers to the signal ultimately output by the chip used to adjust the power of the heating element; it can be a PWM (Pulse Width Modulation) signal. The power output module can refer to the actuator of this system, which is responsible for converting the low-power logic signal output by the temperature control chip into a high-power current that can drive the heating element.

[0047] Specifically, the temperature measurement module can simultaneously acquire two original high-voltage signals—the terminal voltage and the loop voltage of the heating element—using its internal voltage divider circuit. It then uses two sets of resistor networks with identical voltage division coefficients to attenuate these two original high-voltage signals proportionally, outputting two low-voltage signals suitable for sampling by the analog-to-digital converter (ADC) in the temperature control chip. The hardware design of the voltage divider circuit ensures consistency in amplitude scaling between the two signals. The ASIC-based temperature control chip first synchronously reads the two ADC signals. The voltage divider circuit contains two sets of matched resistor networks with identical voltage division coefficients. Thanks to this design of the preceding matched voltage divider circuit, the chip can quickly calculate the current resistance value of the heating element through simple arithmetic operations. Subsequently, the chip can call upon a pre-stored temperature-resistance characteristic relationship (e.g., look up a table or solve a linear formula) to convert the current resistance value into the current temperature of the heating element. Next, the chip can calculate the deviation between the current temperature and the preset target temperature. This deviation is fed into a PID control algorithm that incorporates a predictive model: the predictive part of the algorithm analyzes recent temperature sequences to predict temperature trends in the near future; the PID algorithm calculates based on current and historical deviations; and the two are combined to dynamically generate an optimized temperature control signal (e.g., a PWM signal with a specific duty cycle). The power output module receives the temperature control signal, such as a PWM signal, from the temperature control chip. Based on the duty cycle of the PWM signal, the module controls the on and off times of the switching devices, thereby adjusting the average electrical power applied to the heating element, achieving precise control of the heating intensity, and ultimately heating the aerosol-generating substrate.

[0048] In the temperature control system for the aforementioned aerosol generation device, the temperature measurement module includes a voltage divider circuit. This module simultaneously acquires the terminal voltage and loop voltage of the heating element via the voltage divider circuit, and attenuates both voltages by the same ratio to output two voltage signals suitable for the temperature control chip. The voltage divider circuit includes two sets of matched resistor networks with identical voltage division coefficients. The temperature control chip is an ASIC-based chip used to obtain the current resistance value of the heating element based on the two voltage signals provided by the temperature measurement module. It then obtains the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, and inputs the difference between the current temperature and a preset target temperature into a PID control algorithm. This algorithm, combined with a preset prediction model, generates a temperature control signal for the current temperature. The power output module drives the heating element to operate according to the temperature control signal, thereby heating the aerosol generation substrate in the aerosol generation device. This application reduces noise and errors in the signal processing link through customized ASIC chip design; the matched voltage divider circuit achieves proportional attenuation to simplify calculations and ensure high efficiency in resistance measurement; and the PID algorithm combined with the predictive model effectively suppresses overshoot, collectively achieving temperature control accuracy far exceeding that of traditional MCU solutions. The hardware parallel processing capability of the ASIC is far superior to the sequential instruction execution of the MCU; the matched voltage divider circuit eliminates complex floating-point operations; these factors result in extremely short latency throughout the entire link from signal acquisition to control signal output, significantly improving response speed. The ASIC chip is optimized for a fixed algorithm, resulting in extremely high energy efficiency; simplified calculations also reduce the active time of the arithmetic unit. Both of these significantly reduce system power consumption, which is particularly beneficial for the extended battery life of portable aerosol generation devices. The integrated predictive model gives the system "predictive" capabilities, allowing for advance power adjustments to prevent temperature overshoot or undershoot, resulting in a smoother temperature curve and improved consistency in aerosol generation.

[0049] In an exemplary embodiment, the temperature measurement module further includes a timing control unit, wherein: the timing control unit is used to cut off the working path of the heating element for heating the aerosol generation substrate by means of a preset level signal during the non-heating stage, so that the voltage divider circuit can collect the terminal voltage and loop voltage of the heating element when the heating element is not being heated.

[0050] The timing control unit can refer to a logic control section within the temperature measurement module, used to manage the timing of heating and temperature measurement. The non-heating phase can refer to a specifically designated time window within the periodic temperature control cycle for pure temperature sampling, during which the main heating current is cut off. The preset level signal can refer to a digital signal used to control the on / off state of switching devices (such as MOSFETs). The working path can refer to the heating path, i.e., the entire high-current path from the power output module to the heating element and then to the power supply circuit.

[0051] Specifically, within each control cycle, the timing control unit first outputs a preset level signal to control a switch to open, thereby cutting off the heating path. In the subsequent non-heating phase, the system can apply a small detection current. At this time, the signal collected by the voltage divider circuit only reflects the true resistance (temperature) of the heating element and is not affected by the strong heating current. This pure signal is then output to the temperature control chip for calculation.

[0052] In this embodiment, a timing control unit is used to cut off the working path of the heating element for heating the aerosol-generating substrate through a preset level signal during the non-heating stage. This allows the voltage divider circuit to output two voltage signals to the ASIC-based temperature control chip when the heating element is not being heated. Based on the above, the interference of the heating current on the temperature measurement signal is eliminated, making the calculation of the current resistance value of the heating element based on the two voltage signals more accurate. Then, the accurate current temperature of the heating element can be obtained based on the accurate current resistance value, which further improves the accuracy of temperature sampling and provides a more reliable feedback signal for high-precision closed-loop control.

[0053] In an exemplary embodiment, the two voltage signals include a first voltage signal and a second voltage signal; the two sets of resistor networks include a first resistor network and a second resistor network; the first voltage signal is obtained by inputting the terminal voltage of the heating element into the first resistor network; the second voltage signal is obtained by inputting the loop voltage detected by the current sampling resistor into the second resistor network, and the current sampling resistor is connected in series in the working circuit of the heating element; wherein: the process by which the temperature control chip obtains the current resistance value of the heating element based on the two voltage signals is as follows:

[0054] Rt=(VB_ADC*R_s) / VOR_ADC

[0055] Wherein, Rt is the current resistance value of the heating element; VB_ADC is the first voltage signal; R_s is the resistance value of the current sampling resistor; and VOR_ADC is the second voltage signal.

[0056] For example, the operating voltage of the heating element is divided by a first resistor network to obtain a first voltage signal. The detected voltage across the current sampling resistor connected in series in the circuit is divided by a second resistor network to obtain a second voltage signal. The temperature control chip calculates the resistance according to the above formula. Since the resistance ratios of the two networks are identical, the implicit voltage division ratio in the formula is eliminated.

[0057] This embodiment provides a specific and preferred hardware architecture for achieving high-precision resistance / temperature measurement using the dual sampling method. The core calculation formula is simplified through matching design, achieving fast and low-power calculation.

[0058] In an exemplary embodiment, the temperature control chip is further configured to perform time series analysis based on historical temperature data using a preset prediction model to obtain a predicted temperature value for a future target time; compare the predicted temperature value with a preset target temperature value and generate a compensation signal based on the comparison result; and use the compensation signal to adjust the temperature control signal output by the PID control algorithm to suppress temperature overshoot or undershoot in advance.

[0059] Historical temperature data can refer to the sequence of temperature values ​​sampled over a past period stored in the temperature control chip. Time series analysis can be a statistical method that analyzes data points arranged sequentially over time to uncover patterns and predict the future. The predicted temperature value at a future target time can be the temperature estimate calculated by a prediction model for a specific point in the future (e.g., 0.5 seconds later). The compensation signal can be the adjustment amount generated based on the prediction results to correct the original PID output signal.

[0060] For example, the prediction module inside or outside the temperature control chip continuously stores historical temperature data and runs a time series analysis algorithm (i.e., a preset prediction model) to calculate the predicted temperature value at a future target time. The chip compares this predicted value with the preset target temperature value; if the predicted temperature will exceed the target temperature value, a negative compensation signal is generated, and vice versa. This compensation signal is superimposed on the original PID output signal to form the final control signal.

[0061] In this embodiment, the temperature control chip is also used to perform time series analysis based on historical temperature data and a preset prediction model to obtain the predicted temperature value for the future target time. The predicted temperature value is compared with the preset target temperature value, and a compensation signal is generated based on the comparison result. The compensation signal is used to adjust the temperature control signal output by the PID control algorithm to suppress temperature overshoot or undershoot in advance. Based on the above, the system is endowed with the ability to predict and respond to temperature change trends in advance, actively suppressing overshoot and undershoot, significantly shortening the time for the temperature to reach and stabilize at the target value, and improving the smoothness and robustness of control. This is a fundamental improvement over the traditional passive feedback PID algorithm.

[0062] In an exemplary embodiment, the temperature control chip obtains the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, as shown in the formula:

[0063] Rt=R0×(1+TCR×(T-T0))

[0064] Where Rt is the current resistance value of the heating element; R0 is the reference resistance value of the heating element at the preset standard temperature; TCR is the temperature coefficient; T is the current temperature of the heating element; and T0 is the preset standard temperature reference value of the heating element. The preset standard temperature can refer to the standard temperature indicated in the general definition of room temperature, such as 25℃.

[0065] For example, after obtaining the current resistance value of the heating element, the temperature control chip uses the pre-stored R0, TCR, and T0 parameters to calculate the current temperature T using the above formula.

[0066] In one exemplary embodiment, the PID control algorithm is implemented in a digital circuit using a second-order discretization method.

[0067] The second-order discretization method can refer to a method that transforms continuous PID control equations into difference equations suitable for processing by digital computers or digital circuits, where second-order precision approximations are used for differential terms, etc. The digital circuit can refer to the circuit implemented within the temperature control chip using digital components such as logic gates and registers, used to execute the discretization algorithm.

[0068] For example, the PID control algorithm is transformed into a set of difference equations, for instance, calculated using error values ​​from multiple historical cycles, and implemented in hardware logic via digital circuitry (such as adders, multipliers, and register arrays) within the temperature control chip, rather than being executed via software instructions.

[0069] In this embodiment, the PID control algorithm is directly implemented through digital hardware, eliminating the operating system overhead and instruction latency of software operation, and achieving the highest execution speed and determinism. At the same time, digital implementation avoids the inherent problems of temperature drift and aging of analog circuits, improving the long-term stability and consistency of the system.

[0070] In one exemplary embodiment, such as Figure 2 As shown, a temperature control method for an aerosol generation device is provided, which is applied to... Figure 1 Taking the temperature control chip in the image as an example, the explanation includes the following steps:

[0071] Step S202: Obtain two voltage signals obtained by passing the terminal voltage and loop voltage of the heating element through a voltage divider circuit and attenuating them in the same proportion.

[0072] Step S204: Obtain the current resistance value of the heating element based on the two voltage signals, and obtain the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element.

[0073] Step S206: Input the current temperature and the preset target temperature into the PID control algorithm, and generate a temperature control signal for the current temperature by combining it with the preset prediction model.

[0074] In step S208, a temperature control signal is sent to the power output module so that the power output module responds to the temperature control signal and drives the heating element to work, thereby heating the aerosol generating substrate in the aerosol generating device.

[0075] The solution provided by the temperature control method for the aerosol generating device described above is similar to the solution described in the above system. Therefore, the specific limitations in the embodiments of the temperature control method for the aerosol generating device can be found in the limitations of the temperature control system for the aerosol generating device described above, and will not be repeated here.

[0076] In one exemplary embodiment, this application also provides an automatic temperature measurement and calibration system for temperature control of an aerosol generating device, employing an ASIC-based temperature control chip to overcome the shortcomings of related technologies. Specifically, an automatic temperature measurement and calibration system for temperature control of an aerosol generating device includes a heating element, a temperature measurement module, a power output module, and a temperature control chip.

[0077] The temperature measurement module acquires the temperature data of the heating element (i.e., the heating component) in real time and sends it to the temperature control chip. The temperature measurement module collects the electrical signal from the heating element and transmits the signal to a voltage divider circuit for conversion. The voltage divider circuit contains two sets of matched resistor networks with identical resistance ratios, used to convert the acquired voltage signal into a reference voltage value according to a fixed ratio, thereby directly reflecting the operating voltage and current characteristics of the heating element. Specifically, the circuit structure corresponding to the voltage divider circuit is as follows: Figure 3As shown in the circuit, the heating element's operating voltage is first input via node B+1 (the first voltage divider network can be electrically connected to the heating element's measured point via port 1 or port 3) to the first voltage divider network composed of resistors R18 and R19, i.e., the first resistor network. Its voltage divider output, VB_ADC, is connected to the first ADC channel of the temperature control chip to reflect the heating element's terminal voltage. Simultaneously, the heating element is connected in series with a current sampling resistor R_s. The voltage drop across R_s, i.e., the current detection voltage, is input via node O (the second voltage divider network can be electrically connected to the relevant detection point of the current sampling resistor connected in series with the heating element via port 2) to the second voltage divider network composed of resistors R52 and R53. Its voltage divider output, VOR_ADC, is connected to the second ADC channel of the temperature control chip to reflect the heating current flowing through the heating element. The resistance ratios of the first and second voltage divider networks are strictly designed to be consistent, i.e., R18:R19 = R52:R53. Therefore, the two ADC inputs obtain VB_ADC and VOR_ADC with the same scaling factor, respectively. Through this matching design, the temperature control chip can directly set the following when calculating the resistance of the heating element:

[0078] Rt=(VB_ADC*R_s) / VOR_ADC

[0079] Where Rt is the current resistance value of the heating element; VB_ADC is the first voltage signal, i.e. the voltage divider output of the first voltage divider network; R_s is the resistance value of the current sampling resistor; and VOR_ADC is the second voltage signal, i.e. the voltage divider output of the second voltage divider network.

[0080] This matching design cancels out the voltage divider ratio, allowing the ASIC-based temperature control chip to obtain the real-time resistance value of the heating element without performing floating-point division. The ASIC-based temperature control chip, combined with the temperature coefficient of performance (TCR) model of the heating element: R_t = R_0(1 + TCR*(T - T_0)), can quickly calculate the real-time temperature of the heating element. By leveraging the above hardware structure and mathematical relationships, the ASIC-based temperature control chip avoids the latency and power consumption caused by MCU floating-point operations, while ensuring high-precision temperature detection performance, significantly improving temperature control response speed and system efficiency.

[0081] in, Figure 3The branch consisting of port 4, R14, R16, and C6 can be considered as a third voltage divider network, serving as a backup or supplement to the first or second voltage divider network. Port 4 is the original voltage node being measured (on the load side, a key node voltage point in the heating / temperature measurement main circuit, used for electrical connection to the output port of the heating circuit, independent of port 2 used for connecting the output of the temperature measurement circuit). R14 / R16 are used to perform voltage division sampling on the measured node at port 4 separately: reducing the voltage of port 4 to the measurable range of the ADC: VO_ADC = V(port 4) × R16 / (R14 + R16), which is consistent with the function of R18 / R19, except that the sampling object is a different voltage node. C6 (low-pass filter): together with the voltage divider equivalent resistor, it forms an RC low-pass filter. It suppresses spikes and ripples caused by PWM / MOS switching, making the ADC sampling more stable and the error smaller. VO_ADC (ADC sampling point): This is the ADC input terminal provided to the temperature control chip / main control MCU. Overall, the temperature control chip or main controller, combined with VB_ADC and VOR_ADC (or VO_ADC) and the known circuit topology / resistance ratio, can deduce the real-time resistance Rt of the heating element, thereby obtaining the temperature of the heating element.

[0082] The following is combined with Figure 3 The circuit shown illustrates that the voltage division coefficients of the two voltage divider networks are equal. VOR_ADC and VB_ADC are the output voltages of their respective branches (provided by the preceding circuit). R18 and R19 are connected in series, and the total resistance is R18 + R19. According to the voltage divider theorem, the output voltage VB_ADC is:

[0083]

[0084] make (i.e., partial pressure coefficient), then we can obtain: .

[0085] Similarly, for the branch composed of R52 and R53, with input voltage VO, the output voltage VOR_ADC is:

[0086]

[0087] make (i.e., partial pressure coefficient), then we can obtain: .

[0088] Because R18:R19 = R52:R53, therefore in the above process... and They are equal.

[0089] The aforementioned temperature measurement module also includes a timing control unit, which cuts off the heating path through a preset level signal during the non-heating phase to ensure that only temperature detection is performed. At this time, the voltage value output by the voltage divider circuit is sampled and processed by the temperature control chip to avoid measurement errors caused by heating interference. Through the above hardware design, the temperature control chip can quickly complete the temperature conversion without performing floating-point operations, significantly reducing the consumption of computing resources and improving the response speed.

[0090] The following explains the chip's working principle and functional framework:

[0091] Closed-loop control process as follows Figure 4 As shown, the chip performs the following steps in each temperature control cycle (typically 0.1 seconds): Temperature sampling: At the beginning of a temperature control cycle, relevant port data is read, and the temperature of the heating element is calculated according to a specific formula, thus obtaining the real-time temperature data of the heating element. The temperature is then substituted into the temperature control chip (PID algorithm combined with ARIMA model) to calculate the control code. The temperature control chip controls the duty cycle of the PWM wave within the temperature control cycle. The PWM wave controls the on / off state of the heating element to control the heating power within the temperature control cycle, enabling the temperature to quickly converge to the target range.

[0092] Specifically, the PID algorithm processing also includes an ASIC-based temperature control chip analyzing historical temperature data to predict temperature change trends over a short period (e.g., 0.5 seconds) and adjusting the PID output in advance to suppress overshoot or undershoot. Its core components include: an ARIMA time series prediction model (i.e., a pre-defined prediction model): predicting future values ​​based on historical temperature data; hardware acceleration design: implementing low-latency prediction calculations in the ASIC; and dynamic compensation logic: superimposing the prediction results with the PID output to achieve proactive control.

[0093] The ARIMA time series forecasting model uses ARIMA(1,1,1) (first-order differencing + first-order autoregression + first-order moving average), and its discretization equation is:

[0094] ΔT[ti]=φ·ΔT[ti-1]+θ·ε[ti-1]+ε[ti]

[0095] Where: ΔT[ti]=T[ti]-T[ti-1] (first-order temperature difference); φ: autoregressive coefficient (calibrated using historical data); θ: moving average coefficient; ε: white noise error term; i: time step; ti: time; ΔT[ti-1]: the difference between the temperature at the previous time and the temperature at the time before that; ΔT[ti]: the difference between the current temperature and the temperature at the previous time.

[0096] The prediction formula, i.e., the predicted value T[ti+k] for the k-th step in the future:

[0097] T[ti+k]=T[ti]+∑j=1k

[0098] ΔT[ti+j] is calculated recursively using the ARIMA model.

[0099] Compensation output, that is, incorporating the predicted value into the PID control input:

[0100] ucompensated[ti]=uPID[ti]+Kpred·(T[ti+k]-Ttarget)

[0101] Where ucompensated[ti] is the compensated control signal; Kpred is the prediction gain (calibrated experimentally); k is the prediction step size (e.g., corresponding to 0.5 seconds); uPID[ti] is the original PID output, which is adjusted by the ARIMA model to make the control more precise; Ttarget is the target temperature.

[0102] Specifically, the execution steps based on the aforementioned ARIMA time series forecasting model include:

[0103] Step 1, Data Acquisition and Preprocessing. Historical Temperature Sampling: Store the most recent... Each temperature value (e.g., N=20, corresponding to 2 seconds of data, sampling rate 10Hz). First-order difference calculation: real-time calculation. .

[0104] Step 2, online update of model parameters. Coefficient calibration: initialization. , These are empirical values. Updated online using the least squares method (can be refreshed every 10 seconds). Noise estimation: Calculate the residuals. .

[0105] Step 3: Real-time Prediction and Compensation. Predicting future temperature: Recursively calculate the temperature k steps ahead. , :

[0106]

[0107] Accumulation In this prediction process, the missing ε[ti+j] corresponding to ε[ti] (the white noise error term of the original discretization equation) in the discretization equation is due to the unpredictability of white noise. The discretization equation of the ARIMA model is "a description of the generation logic of historical actual difference data", while the recursive prediction is "inferring future trends based on historical data". Since the random error of the future cannot be predicted, it is assumed to be 0 and omitted.

[0108] Generate compensation signal: if the predicted temperature If the target value is exceeded, the PID output is reduced (overshoot is suppressed in advance). The target value is the temperature that the temperature controller initially needs to maintain, such as 350°C.

[0109] The above process will be described in detail below with reference to some embodiments.

[0110] In one exemplary embodiment, a specific implementation of an ASIC chip-based closed-loop control process is provided (adapted to a temperature control range of 345~355℃). The basic parameters are set as follows: target temperature T_target = 350℃; temperature control period Δt = 0.1s; reference resistance R0 = 1Ω for the heating element at room temperature (T0 = 25℃); temperature coefficient TCR = 0.003 / ℃; ID parameters: proportional coefficient Kp = 3.0, integral coefficient Ki = 1.2, derivative coefficient Kd = 0.5; PWM signal frequency: 1kHz (period 1ms).

[0111] I. Temperature Sampling (First Step in Closed-Loop Control). The resistance signal of the heating element is directly acquired, and the real-time temperature T_meas is calculated using the temperature-resistance characteristic formula: Temperature-resistance correlation formula: Rt = R0 × [1 + TCR × (Tmeas - T0)]. Where Rt is the real-time resistance of the heating element, R0 is the room temperature reference resistance, TCR is the temperature coefficient, Tmeas is the measured temperature, and T0 is the room temperature reference value.

[0112] The sensor collected the real-time resistance of the heating element, Rt = 1.969Ω. Substituting these values ​​into the formula, the real-time temperature is calculated as follows: 1.969 = 1 × [1 + 0.003 × (Tmeas - 25)]. 0.969 = 0.003 × (Tmeas - 25). Tmeas = 25 + (0.969 ÷ 0.003) = 348℃.

[0113] II. Error Calculation (Second Step of Closed-Loop Control). Using the difference between the target temperature and the measured temperature as the control input, the formula is as follows: Error Calculation Formula: e(t) = Ttarget - Tmeas. Where e(t) is the temperature error of the current cycle, Ttarget is the target temperature, and Tmeas is the measured temperature. Substituting Ttarget = 350℃ and Tmeas = 348℃: e(t) = 350 - 348 = 2℃ (Positive error: the measured temperature is lower than the target, requiring a slight increase in heating power).

[0114] III. PID Algorithm Processing (Third Step of Closed-Loop Control). A discretized PID algorithm is adopted, using proportional (P), integral (I), and derivative (D) paths for coordinated calculation. The formula is as follows: PID output formula: u(ti) = Kp × e(ti) + Ki × Σe(tj) × Δt + Kd × [e(ti) - e(ti-1)] / Δt. Where u(ti) is the PID output for the current cycle, Kp / Ki / Kd are the PID coefficients, e(ti) is the current error, e(ti-1) is the error of the previous cycle, Σe(tj) is the cumulative sum of historical errors, and Δt is the temperature control cycle. Then, additional parameters are added: the error of the previous cycle e(ti-1) = 3℃ (the previous cycle Tmeas = 347℃); the current cycle is the 4th cycle, and the errors of the previous 3 cycles were 5℃, 4℃, and 3℃ respectively. Next, the terms are calculated separately: Proportional term: Kp × e(ti) = 3.0 × 2 = 6. Integral term: Ki×(5+4+3+2)×0.1=1.2×1.4=1.68. Differential term: Kd×(2-3)÷0.1=0.5×(-10)=-5. Total PID output: u(ti)=6+1.68-5=2.68 (positive control quantity: heating power needs to be increased).

[0115] IV. PWM Modulation Output (Fourth Step of Closed-Loop Control). Map the PID output to a PWM duty cycle (range 0~100%). Mapping rule: u=5 corresponds to 100% duty cycle (maximum heating), u=-5 corresponds to 0% duty cycle (heating stopped). The formula is as follows: PWM duty cycle formula: D=50%+[u(ti)÷5]×50%. Where D is the PWM duty cycle, and u(ti) is the PID output of the current cycle.

[0116] Substituting u(ti)=2.68, we calculate: D=50%+(2.68÷5)×50%=50%+26.8%=76.8%. The ASIC chip outputs a PWM signal with a duty cycle of 76.8%: within a 1kHz period (1ms), the heating path is on for 1ms×76.8%=0.768ms. By extending the heating time, the power is slightly increased, causing the temperature to converge towards 350℃ in the next cycle.

[0117] V. Periodic Iteration Verification (Closed-Loop Temperature Control Stability). The process for the next 0.1s temperature control cycle is as follows:

[0118] Temperature sampling: Rt = 1.973Ω, Tmeas = 25 + (1.973 - 1) ÷ (1 × 0.003) = 349.3℃. Error calculation: e(ti+1) = 350 - 349.3 = 0.7℃ (error significantly reduced). PID processing: u(ti+1) ≈ -2.636 (negative control input: power needs to be reduced). PWM output: Mapped to D ≈ 23.64%, shortening heating time to suppress temperature overshoot. Ultimately, Tmeas is stabilized within the range of 350℃ ± 0.5℃, achieving high-precision closed-loop temperature control.

[0119] The following section explains the recursive calculation of the ARIMA model and the meaning of its parameters:

[0120] The above embodiments use the ARIMA(1,1,1) model (first-order differencing + first-order autoregression + first-order moving average) to achieve recursion. The core is based on historical temperature difference data and model parameters (autoregression coefficient φ, moving average coefficient θ). The specific steps are as follows:

[0121] 1. Basic preparations before recursion.

[0122] (1) Data basis: Store the most recent 20 temperature values ​​(corresponding to 2 seconds of data, sampling rate 10Hz), that is, the historical data are T[ti-19], T[ti-18], ..., T[ti-1], T[ti] (ti is the current time), and calculate the first difference ΔT[tj]=T[tj]-T[tj-1] (j from ti-19 to ti).

[0123] (2) Parameter basis: The model parameters φ (autoregressive coefficient) and θ (moving average coefficient) are updated online using the least squares method (refreshed every 10 seconds), and the initial values ​​are empirical values.

[0124] (3) Error term processing: The white noise error term ε[tj] is estimated by residual (residual = actual difference data - model fitting difference data), and the future error term ε[ti+j] = 0 (the mean of white noise is 0) during recursion.

[0125] 2. Specific recursive formulas and steps.

[0126] ARIMA(1,1,1) discretization equation: ΔT[tj]=φ·ΔT[tj-1]+θ·ε[tj-1]+ε[tj].

[0127] Step 1 (j=1, predict ΔT[ti+1]): ΔT[ti+1]=φ·ΔT[ti]+θ·ε[ti]+ε[ti+1], because ε[ti+1]=0, it is simplified to: ΔT[ti+1]=φ·ΔT[ti]+θ·ε[ti].

[0128] Step 2 (j=2, predict ΔT[ti+2]): ΔT[ti+2]=φ·ΔT[ti+1]+θ·ε[ti+1]+ε[ti+2], because ε[ti+1]=ε[ti+2]=0, it is simplified to: ΔT[ti+2]=φ·ΔT[ti+1].

[0129] Step j (j≥2, predict ΔT[ti+j]): Unified recursive formula: ΔT[ti+j]=φ·ΔT[ti+j-1].

[0130] Using the above logic, all ΔT[ti+j] for the next k steps (j=1 to k) can be calculated sequentially.

[0131] Explanation of the physical meaning of k-step ΔT[ti+j]. ΔT[ti+j] is the predicted temperature change (unit: °C) between the j-th future sampling time and the previous sampling time. Its specific meaning is as follows:

[0132] If ΔT[ti+j]>0: the temperature at the j-th time in the future is predicted to increase compared to the previous time, with an amplitude of ΔT[ti+j]; if ΔT[ti+j]<0: the temperature at the j-th time in the future is predicted to decrease compared to the previous time, with an amplitude equal to its absolute value; if ΔT[ti+j]=0: the temperature at the j-th time in the future is predicted to remain the same as the previous time.

[0133] Example: If ΔT[ti+1]=2℃, it means that the predicted temperature at time ti+1 is 2℃ higher than that at time ti; if ΔT[ti+2]=-1℃, it means that the predicted temperature at time ti+2 is 1℃ lower than that at time ti+1.

[0134] Explanation of the time parameters ti and ti+j (using 2 seconds of historical data): ti: Current sampling moment. This is the time reference point for the prediction process, corresponding to the "latest data moment" among the 20 stored historical data points. It is also the moment after the temperature control chip completes the current cycle sampling and error calculation. ti+j: The j-th future sampling moment. j represents the future sampling step number. The sampling rate is 10Hz (period 0.1 seconds), therefore ti+j is the sampling moment j × 0.1 seconds after the current moment: ti+1: 0.1 seconds after the current moment; ti+2: 0.2 seconds after the current moment; -ti+k (k=5): 0.5 seconds after the current moment (typical prediction step size in the document). In short, ti is "now," and ti+j is "the j-th 0.1-second future moment." The recursive ΔT[ti+j] is the temperature change within each 0.1 seconds in the future. After accumulation, the predicted temperature for the next k steps can be obtained: T[ti+k]=T[ti]+Σ(j=1 to k)ΔT[ti+j], which provides a basis for PID compensation and advance control.

[0135] The technical effects and data of the above-mentioned automatic temperature measurement and calibration system for temperature control of aerosol generation devices can be referenced. Figure 5 As shown, the PID+ARIMA method outperforms the original PID method in both overshoot and steady-state arrival time. Specifically, the original PID method has an overshoot of 11°C and a normalized steady-state arrival time of 0.23 seconds. In this application, the PID+ARIMA method has an overshoot of 0°C and a normalized steady-state arrival time of 0.18 seconds.

[0136] For example, in this embodiment, the temperature control chip based on ASIC uses digital circuits to implement PID control, and the continuous algorithm is discretized by second-order differential approximation.

[0137] The transfer function of the PID controller is as follows:

[0138]

[0139] The relationship between input and output is as follows:

[0140]

[0141] The corresponding expression in the time domain is:

[0142]

[0143] Where, u′ I (t), e′(t) and u′ D (t) represents u P (t), e(t) and u D The derivatives of (t) can be expressed as follows (a second-order approximation):

[0144]

[0145]

[0146]

[0147] Where Δt=t i -t i-1 Let be the time interval between adjacent discretized data, the magnitude of which is equal to the clock period TCLK of the temperature control signal generator. This allows us to derive the PID algorithm's time interval at t... i The output at time t is as follows:

[0148]

[0149] Among them, e[t i ] is the "current error input". P and I are obtained through "experience + experimentation + online fine-tuning", uD[t i ] is the "trend prediction output".

[0150] The core advantages of the second-order discretized PID compared to analog circuits used in this embodiment can be summarized in the following table:

[0151]

[0152] This embodiment simplifies computational complexity, significantly reduces reliance on analog components such as resistors and capacitors, reduces chip area (core area only 0.135mm²) and power consumption (maximum current ≤29.5mA), while improving robustness to process deviations.

[0153] The aforementioned automatic temperature measurement and calibration system for temperature control of aerosol generation devices can improve temperature control accuracy: the highly integrated ASIC chip design enables higher precision temperature control; accelerate response speed: the ASIC chip shortens calculation and execution time through customized circuit design; and reduce power consumption: the ASIC chip consumes less energy in specific tasks, making it suitable for portable aerosol generation devices.

[0154] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0155] In one exemplary embodiment, a temperature control chip is provided, the internal structure of which can be shown in the figure below. Figure 6 As shown. The temperature control chip includes a memory and a processor, the memory storing a computer program. When executed by the processor, the computer program implements a temperature control method for an aerosol generating apparatus.

[0156] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0157] In one embodiment, a temperature control chip is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0158] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0159] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0160] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0161] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0162] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A temperature control system for an aerosol generating device, characterized in that, It includes a temperature measurement module, a heating element, a temperature control chip, and a power output module, among which: The temperature measurement module includes a voltage divider circuit. The temperature measurement module is used to simultaneously acquire the terminal voltage and loop voltage of the heating element through the voltage divider circuit, and attenuate the terminal voltage and the loop voltage by the same ratio to output two voltage signals suitable for the temperature control chip. The voltage divider circuit includes two sets of matched resistor networks, and the voltage division coefficients of the two sets of resistor networks are the same. The temperature control chip is an ASIC-based chip used to obtain the current resistance value of the heating element based on the two voltage signals provided by the temperature measurement module, obtain the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element, and input the difference between the current temperature and the preset target temperature into the PID control algorithm, and generate a temperature control signal for the current temperature in combination with the preset prediction model. The power output module is used to drive the heating element to work according to the temperature control signal, so as to heat the aerosol generating substrate in the aerosol generating device.

2. The system according to claim 1, characterized in that, The temperature measurement module also includes a timing control unit, wherein: The timing control unit is used to cut off the working path of the heating element for heating the aerosol generating substrate by means of a preset level signal during the non-heating stage, so that the voltage divider circuit can collect the terminal voltage and loop voltage of the heating element when the heating element is not heated.

3. The system according to claim 2, characterized in that, The two voltage signals include a first voltage signal and a second voltage signal; the two sets of resistor networks include a first resistor network and a second resistor network; the first voltage signal is obtained by inputting the terminal voltage of the heating element into the first resistor network; The second voltage signal is obtained by inputting the loop voltage detected by the current sampling resistor into the second resistor network, wherein the current sampling resistor is connected in series in the working circuit of the heating element; wherein: The process by which the temperature control chip obtains the current resistance value of the heating element based on the two voltage signals is as follows: Rt=(VB_ADC*R_s) / VOR_ADC Wherein, Rt is the current resistance value of the heating element; VB_ADC is the first voltage signal; R_s is the resistance value of the current sampling resistor; and VOR_ADC is the second voltage signal.

4. The system according to claim 1, characterized in that, The temperature control chip is also used to perform time series analysis based on historical temperature data and the preset prediction model to obtain the predicted temperature value at the future target time; compare the predicted temperature value with the preset target temperature value, and generate a compensation signal based on the comparison result; and use the compensation signal to adjust the temperature control signal output by the PID control algorithm to suppress temperature overshoot or undershoot in advance.

5. The system according to any one of claims 1 to 4, characterized in that, The process by which the temperature control chip obtains the current temperature of the heating element based on the current resistance value and the temperature-resistance characteristic relationship of the heating element is as follows: Rt=R0×(1+TCR×(T-T0)) Wherein, Rt is the current resistance value of the heating element; R0 is the reference resistance value of the heating element at the preset standard temperature; TCR is the temperature coefficient; T is the current temperature of the heating element; and T0 is the preset standard temperature reference value of the heating element.

6. The system according to any one of claims 1 to 4, characterized in that, The PID control algorithm is implemented in digital circuits using a second-order discretization method.

7. A temperature control method for an aerosol generating device, characterized in that, The method, applied to a temperature control chip in any one of claims 1 to 6, comprises: Two voltage signals are obtained by attenuating the terminal voltage and loop voltage of the heating element by a voltage divider circuit in the same proportion. The current resistance value of the heating element is obtained based on the two voltage signals, and the current temperature of the heating element is obtained based on the current resistance value and the temperature-resistance characteristic relationship of the heating element. The difference between the current temperature and the preset target temperature is input into the PID control algorithm, and a temperature control signal for the current temperature is generated by combining it with the preset prediction model. The temperature control signal is sent to the power output module so that the power output module responds to the temperature control signal and drives the heating element to work, so as to heat the aerosol generating substrate in the aerosol generating device.

8. A control chip, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method of claim 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method of claim 7.

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