Control optimization method and system based on cold disc temperature conduction lag system

Abstract

The invention discloses a control optimization method and system based on a cold disc temperature conduction lag system, relates to the technical field of temperature control of temperature controllers, and aims to solve the problem that an obtained result deviates from a current actual condition due to temperature conduction lag in a current temperature control method. Comprising the steps of calculating a real-time error according to a current temperature and a set temperature of a cold disc; calculating to obtain proportional output Up (t) according to the real-time error, judging whether the absolute value of the Up (t) is greater than the absolute value of the maximum output power, if so, adopting an integral separation control algorithm, and if not, adopting a temperature control algorithm; integrating the output control quantities to obtain a total output control quantity U (t), if accumulation of Up (t) and integral output is in the same direction as differential output, performing accumulation and summation, and if the accumulation of Up (t) and integral output is in the reverse direction, taking 0 as the control quantity; and performing output amplitude adjustment on the U (t) according to actual conditions, and inputting the final output control quantity into a cold disc for control. Temperature conduction lag is subjected to optimization control, the temperature control oscillation condition is relieved, and temperature control curve convergence is accelerated.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology, specifically to a control optimization method and system based on a cold plate temperature conduction hysteresis system. Background Technology

[0002] Currently, the conventional algorithm in the field of temperature control for thermostats is still the classic PID algorithm. However, in operating conditions with severe conduction lag, the temperature data collected by the temperature sensor for calculation is subject to a certain lag due to the significant temperature conduction delay. Therefore, the results obtained often deviate from the actual situation.

[0003] When controlling temperature, if the current temperature is lower than the target temperature, the thermostat needs to output appropriate power for heating to maintain the target temperature. However, due to the lag in temperature conduction, the temperature data collected by the sensor lags behind the actual temperature, which is already higher than the target temperature. This necessitates reducing the heating power or even outputting cooling power. But because the collected temperature data is still lower than the target temperature, the traditional PID algorithm's output strategy remains heating, leading to further heating of the controlled object and causing the actual temperature to deviate even further from the target temperature. When the sensor's sampling data shows that the temperature has reached the target temperature, the actual temperature has already severely overshooted. Cooling follows this overshoot, but due to the lag in actual temperature conduction, the temperature data collected by the sensor will continue to rise during cooling, causing the cooling power to increase step by step, ultimately leading to cooling overshoot and thus cyclical oscillation. For example, Chinese patent CN112783229A exhibits the aforementioned problem. Summary of the Invention

[0004] This invention addresses the problem that current temperature control methods cause results to deviate from actual conditions due to temperature conduction lag. It proposes a control optimization method and system based on the temperature conduction lag system of cold plates, which optimizes the control of temperature conduction lag and provides a corresponding optimization method to alleviate temperature control oscillation and accelerate the convergence of the temperature control curve.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a control optimization method based on a cold plate temperature conduction hysteresis system, comprising the following steps: S1 calculates the real-time error based on the current temperature and set temperature of the cold plate; S2, calculate the proportional output Up(t) based on the real-time error, and determine whether the absolute value of Up(t) is greater than the absolute value of the maximum output power. If yes, use the integral separation control algorithm; otherwise, use the temperature control algorithm. S3, integrate the output control quantities to obtain the total output control quantity U(t). If the sum of Up(t) and the integral output is in the same direction as the derivative output, then sum them up. If they are in opposite directions, the control quantity is 0. S4, adjust the output amplitude of U(t) according to the actual situation, and input the final output control quantity into the cold plate for control.

[0006] In this technical solution, firstly, the temperature data is collected and the real-time error is calculated. Then, the proportional output Up(t) is calculated. By comparing the absolute value of Up(t) with the absolute value of the maximum output power, it is determined whether to use a temperature control algorithm or an integral separation control algorithm. After obtaining each output control quantity, these output control quantities are integrated to obtain the total output control quantity. The control quantity is determined by judging whether the sum of Up(t) and the integral output is in the same direction as the derivative output. Finally, the amplitude of the control quantity is adjusted to obtain the final output control quantity, which is input to the cold plate for temperature control.

[0007] The present invention is further configured such that: the temperature control algorithm includes performing mathematical operations on the real-time error e(t) and preset PID parameters to obtain the output control quantity, including proportional output Up(t), integral output Ui(t), and derivative output Ud(t).

[0008] In this technical solution, both the proportional output Up(t) and the derivative output Ud(t) are calculated using conventional methods.

[0009] The present invention is further configured such that the process of obtaining the integral output Ui(t) is as follows: Determine whether the absolute value of the product of the real-time error and the PID integral parameter is less than or equal to the absolute value of the integral anti-saturation parameter. If yes, the integral output Ui(t) is the product of the PID integral parameter and the real-time error. If no, further determine whether the product of the real-time error and the PID integral parameter is greater than the integral anti-saturation parameter. If yes, Ui(t) is the integral anti-saturation parameter. If no, Ui(t) is the negative of the integral anti-saturation parameter.

[0010] In this technical solution, based on the relationship between the real-time error and the product of the PID integral parameters and the integral anti-saturation parameter, the integral output Ui(t) can be determined in three cases.

[0011] The present invention is further configured such that: the proportional output Up(t) is the product of the real-time error and the PID proportional parameter, and the differential output Ud(t) is the product of the real-time error with respect to time and the PID differential parameter.

[0012] The present invention is further configured such that step S4 includes: Determine whether the absolute value of the total output control quantity U(t) is within the range of the absolute value of the maximum power that the controlled module can withstand. If yes, the final output control quantity Uo(t) is U(t). If no, further determine whether the total output control quantity U(t) is greater than the maximum power that the controlled module can withstand. If yes, Uo(t) is the maximum power that the controlled module can withstand. If no, Uo(t) is the negative of the maximum power that the controlled module can withstand.

[0013] In this technical solution, the amplitude adjustment process depends on the relationship between the total output control quantity U(t) and the maximum power that the controlled module can withstand, and finally obtains the values ​​of Uo(t) in three cases.

[0014] The present invention is further configured such that step S4 includes: adjusting the PID derivative parameter in real time and feeding it back to the PID calculation module; when the condition that |Uo(t)| equals |Uomax| is met in two consecutive temperature control cycles, the PID derivative parameter is multiplied by 2 on the original basis; when the condition that |Uo(t)| equals |Uomax| is broken, the PID derivative parameter is restored to its initial value.

[0015] In this technical solution, Kd is adjusted using the algorithm described above.

[0016] The present invention is further configured such that: the real-time error is the difference between the set temperature and the current temperature of the cold plate, the current temperature is obtained by a temperature acquisition device, and the set temperature is set according to the actual situation.

[0017] In this technical solution, the temperature acquisition device is not limited.

[0018] The present invention is further configured such that: the integral separation control algorithm is that the temperature controller is controlled only by P, and the high power output is used to accelerate the reduction of the temperature difference, at which time the integral action is not effective.

[0019] High power output can accelerate the reduction of temperature difference. At this time, the integral action is not effective, which effectively controls the overshoot and settling time.

[0020] A control optimization system based on a cold plate temperature conduction hysteresis system, applicable to the aforementioned control optimization method based on a cold plate temperature conduction hysteresis system, includes: The error calculation module calculates the real-time error using the current temperature and the set temperature. The PID calculation module performs logical judgments based on the magnitude of the real-time error and ultimately obtains the output control quantity. The output control module integrates and calculates the total output control quantity from each output control quantity, adjusts the amplitude of the total output control quantity, and adjusts the PID derivative parameters in real time.

[0021] In this technical solution, the combined effect of the aforementioned error calculation module, PID calculation module, and output control module enables optimized control of the temperature conduction hysteresis system.

[0022] The present invention is further configured such that: the output control module includes an integration unit, which performs integrated calculations on each output control quantity; the integration unit is also connected to an amplitude adjustment unit, which is connected to a parameter adjustment unit.

[0023] In the above technical solution, the amplitude adjustment unit can adjust the output amplitude of the total output control quantity U(t).

[0024] The present invention can bring the following beneficial effects: This application optimizes the output of the thermostat through an output control module, and makes flexible improvements to address the phenomenon of temperature oscillation caused by the thermostat frequently switching between cooling and heating at critical temperatures, thereby achieving a smooth transition between heating and cooling during temperature control. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the overall process of a control optimization method based on a cold plate temperature conduction hysteresis system according to this application.

[0026] Figure 2 This is a flowchart illustrating step S4 of the control optimization method based on a cold plate temperature conduction hysteresis system according to this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only one preferred embodiment of this invention and are only used to explain this invention. They do not limit the scope of protection of this invention. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0028] Currently, the conventional algorithm in the field of temperature control for thermostats is still the classic PID algorithm, including positional and incremental algorithms.

[0029] Under conditions of severe conduction lag, the temperature data collected by the temperature sensor for calculation will have a certain lag due to the severe lag in temperature conduction. Therefore, the results obtained will often deviate from the current actual situation, resulting in long-term oscillations around the target temperature that are difficult to converge.

[0030] For example, when controlling temperature, if the current temperature is lower than the target temperature, the thermostat needs to output appropriate power for heating to bring the temperature to the target. However, due to the lag in temperature conduction, the temperature data collected by the sensor lags behind the actual temperature, which is already higher than the target temperature. This necessitates reducing the heating power or even outputting cooling power. But because the collected temperature data is still lower than the target temperature, the traditional PID algorithm's output strategy remains heating, leading to further heating of the controlled object and causing the actual temperature to deviate even further from the target temperature. When the sensor's sampling data shows that the temperature has reached the target temperature, the actual temperature has already severely overshooted. After overshooting comes cooling, but due to the lag in actual temperature conduction, the temperature data collected by the sensor will continue to rise during cooling, causing the cooling power to increase step by step, ultimately leading to cooling overshoot and thus causing cyclical oscillation.

[0031] Example 1 To address the shortcomings of existing technologies, this embodiment proposes a control optimization method based on a cold plate temperature conduction hysteresis system, referencing... Figure 1 and Figure 2 It includes the following steps.

[0032] Step S1: Calculate the real-time error using the current temperature of the cold plate and the set temperature.

[0033] The real-time error e(t) is specifically the difference between the set temperature SV and the current temperature PV of the cold plate. After calculating the real-time error e(t), the error result is output to the PID calculation module.

[0034] The above-mentioned step S1 is specifically performed in the error calculation module.

[0035] The current temperature PV is acquired through a temperature acquisition device. The specific type of temperature acquisition device is not limited here, as long as it has the function of acquiring and caching temperature.

[0036] The set temperature SV is determined through comprehensive analysis based on the user's actual needs and the actual conditions of the scenario.

[0037] After completing step S1, proceed to step S2, where the proportional output Up(t) is obtained by using the real-time error calculated in step S1. After obtaining the proportional output Up(t), take the absolute value of the proportional output Up(t) and compare it with the absolute value of the maximum output power supported by the module.

[0038] If the absolute value of Up(t) is greater than the absolute value of the maximum output power supported by the above module, then the integral separation control algorithm is adopted, that is, the temperature controller is only controlled by P, and the strong power output is used to accelerate the reduction of temperature difference. At this time, the integral action is not effective, effectively controlling the overshoot and the settling time.

[0039] If the absolute value of Up(t) is less than or equal to the absolute value of the maximum output power supported by the above module, then the temperature control algorithm is used.

[0040] For the temperature control algorithm, the process mainly involves performing corresponding mathematical operations on the real-time error e(t) and the pre-set PID parameters to obtain the output control quantities, which are the proportional output Up(t), integral output Ui(t) and derivative output Ud(t).

[0041] For the proportional output Up(t), the result is the real-time error e(t) multiplied by the PID proportional parameter.

[0042] For the differential output Ud(t), the result is the product of the derivative of the real-time error e(t) with respect to time and the PID differential parameter.

[0043] The process of obtaining the integral output Ui(t) is more complex than that of the proportional output Up(t) and the derivative output Ud(t) mentioned above.

[0044] The calculation of the integral output Ui(t) first requires comparing the absolute value of the product of the real-time error e(t) and the PID integral parameter with the absolute value of the integral anti-saturation parameter |Uimax|. If the absolute value of the product of the real-time error e(t) and the PID integral parameter is less than or equal to the absolute value of the integral anti-saturation parameter, then the integral output Ui(t) is equal to the product of the real-time error e(t) and the PID integral parameter. If the absolute value of the product of the real-time error e(t) and the PID integral parameter is greater than the absolute value of the integral anti-saturation parameter, then it is necessary to further compare the relationship between the product of the real-time error e(t) and the PID integral parameter and the integral anti-saturation parameter. If the product of the real-time error e(t) and the PID integral parameter is greater than the integral anti-saturation parameter, then the value of Ui(t) is equal to the integral anti-saturation parameter. If the product of the real-time error e(t) and the PID integral parameter is not greater than the integral anti-saturation parameter, then the value of Ui(t) is the negative of the integral anti-saturation parameter.

[0045] In this technical solution, based on the relationship between the real-time error and the product of the PID integral parameters and the integral anti-saturation parameter, the integral output Ui(t) can be determined in three cases.

[0046] Step S3 is performed after obtaining each output control quantity in step S2. Step S3 integrates the above output control quantities to obtain the total output control quantity U(t). Specifically, if the sum of the proportional output Up(t) and the integral output Ui(t) and the derivative output Ud(t) are in the same direction, then the above three are summed. If they are in opposite directions, then the control quantity is directly set to 0.

[0047] The output control module integrates and calculates the total output control quantity U(t) based on each output control quantity; when the sum of Up(t) and Ui(t) is in the same direction as Ud(t), the three are summed; when the sum of Up(t) and Ui(t) is in the opposite direction to Ud(t), the output control quantity is 0.

[0048] More specifically, when the sum of the proportional output Up(t) and the integral output Ui(t) is greater than or equal to the negative of the derivative output Ud(t) and the negative of the derivative output Ud(t) is greater than 0, the control quantity is the sum of the three. When the sum of the proportional output Up(t) and the integral output Ui(t) is less than the negative of the derivative output Ud(t) and the sum of the proportional output Up(t) and the integral output Ui(t) is greater than 0, the control quantity is 0. When the negative of the sum of the proportional output Up(t) and the integral output Ui(t) is less than the derivative output Ud(t) and the negative of the sum of the proportional output Up(t) and the integral output Ui(t) is greater than 0, the control quantity is 0.

[0049] Step S4: Adjust the output amplitude of the total output control quantity U(t) according to the actual situation of the cold plate, and input the final output control quantity into the cold plate for control.

[0050] For step S4 regarding the amplitude adjustment of the total output control quantity U(t), it specifically includes: firstly, comparing the absolute value of the total output control quantity U(t) with the absolute value of the maximum power that the controlled module can withstand, determining whether the absolute value of the total output control quantity U(t) is less than or equal to the absolute value of the maximum power that the controlled module can withstand; if the absolute value of the total output control quantity U(t) is less than or equal to the absolute value of the maximum power that the controlled module can withstand, then the final output control quantity Uo(t) is directly taken as the total output control quantity U(t); if the absolute value of the total output control quantity U(t) is less than or equal to the absolute value of the maximum power that the controlled module can withstand, then the final output control quantity Uo(t) is directly taken as the total output control quantity U(t); If the absolute value of the total output control quantity U(t) is greater than the absolute value of the maximum power that the controlled module can withstand, further judgment is required. It is necessary to judge the relationship between the total output control quantity U(t) and the maximum power that the controlled module can withstand. If the total output control quantity U(t) is greater than the maximum power that the controlled module can withstand, |Uomax|, then the final output control quantity Uo(t) is directly taken as |Uomax|; if the total output control quantity U(t) is not greater than the maximum power that the controlled module can withstand, |Uomax|, then the final output control quantity Uo(t) is directly taken as -|Uomax|.

[0051] In this technical solution, the amplitude adjustment process depends on the relationship between the total output control quantity U(t) and the maximum power that the controlled module can withstand, and finally obtains the values ​​of Uo(t) in three cases.

[0052] Simultaneously, step S4 also involves the dynamic real-time adjustment of the PID derivative parameter Kd: when the condition |Uo(t)| equals |Uomax| is met for two consecutive temperature control cycles, the PID derivative parameter is multiplied by 2; when the condition |Uo(t)| equals |Uomax| is broken, the PID derivative parameter returns to its initial value. This process adjusts the PID derivative parameter in real time and feeds it back to the PID calculation module.

[0053] In this embodiment, firstly, the temperature data is collected and the real-time error is calculated. Then, the proportional output Up(t) is calculated. By comparing the absolute value of Up(t) with the absolute value of the maximum output power, it is determined whether to use a temperature control algorithm or an integral separation control algorithm. After obtaining each output control quantity, these output control quantities are integrated to obtain the total output control quantity. The control quantity is determined by judging whether the sum of Up(t) and the integral output is in the same direction as the derivative output. Finally, the amplitude of the control quantity is adjusted to obtain the final output control quantity, which is input to the cold plate for temperature control.

[0054] Example 2 This embodiment proposes a control optimization method based on a cold plate temperature conduction hysteresis system, which includes the following steps.

[0055] Step S1: Calculate the real-time error using the current temperature of the cold plate and the set temperature.

[0056] The real-time error e(t) is specifically the difference between the set temperature SV and the current temperature PV of the cold plate. After calculating the real-time error e(t), the error result is output to the PID calculation module.

[0057] The above-mentioned step S1 is specifically performed in the error calculation module.

[0058] The current temperature PV is acquired through a temperature acquisition device. The specific type of temperature acquisition device is not limited here, as long as it has the function of acquiring and caching temperature.

[0059] The set temperature SV is determined through comprehensive analysis based on the user's actual needs and the actual conditions of the scenario.

[0060] After completing step S1, proceed to step S2, where the proportional output Up(t) is obtained by using the real-time error calculated in step S1. After obtaining the proportional output Up(t), take the absolute value of the proportional output Up(t) and compare it with the absolute value of the maximum output power supported by the module.

[0061] If the absolute value of Up(t) is greater than the absolute value of the maximum output power supported by the above module, then the integral separation control algorithm is adopted, that is, the temperature controller is only controlled by P, and the strong power output is used to accelerate the reduction of temperature difference. At this time, the integral action is not effective, effectively controlling the overshoot and the settling time.

[0062] If the absolute value of Up(t) is less than or equal to the absolute value of the maximum output power supported by the above module, then the temperature control algorithm is used.

[0063] For the temperature control algorithm, the process mainly involves performing corresponding mathematical operations on the real-time error e(t) and the pre-set PID parameters to obtain the output control quantities, which are the proportional output Up(t), integral output Ui(t) and derivative output Ud(t).

[0064] For the proportional output Up(t), the result is the real-time error e(t) multiplied by the PID proportional parameter.

[0065] For the differential output Ud(t), the result is the product of the derivative of the real-time error e(t) with respect to time and the PID differential parameter.

[0066] The process of obtaining the integral output Ui(t) is more complex than that of the proportional output Up(t) and the derivative output Ud(t) mentioned above.

[0067] The calculation of the integral output Ui(t) first requires comparing the absolute value of the product of the real-time error e(t) and the PID integral parameter with the absolute value of the integral anti-saturation parameter |Uimax|. If the absolute value of the product of the real-time error e(t) and the PID integral parameter is less than or equal to the absolute value of the integral anti-saturation parameter, then the integral output Ui(t) is equal to the product of the real-time error e(t) and the PID integral parameter. If the absolute value of the product of the real-time error e(t) and the PID integral parameter is greater than the absolute value of the integral anti-saturation parameter, then it is necessary to further compare the relationship between the product of the real-time error e(t) and the PID integral parameter and the integral anti-saturation parameter. If the product of the real-time error e(t) and the PID integral parameter is greater than the integral anti-saturation parameter, then the value of Ui(t) is equal to the integral anti-saturation parameter. If the product of the real-time error e(t) and the PID integral parameter is not greater than the integral anti-saturation parameter, then the value of Ui(t) is the negative of the integral anti-saturation parameter.

[0068] In this technical solution, based on the relationship between the real-time error and the product of the PID integral parameters and the integral anti-saturation parameter, the integral output Ui(t) can be determined in three cases.

[0069] Step S3 is performed after obtaining each output control quantity in step S2. Step S3 integrates the above output control quantities to obtain the total output control quantity U(t). Specifically, if the sum of the proportional output Up(t) and the integral output Ui(t) and the derivative output Ud(t) are in the same direction, then the above three are summed. If they are in opposite directions, then the control quantity is directly set to 0.

[0070] The output control module integrates and calculates the total output control quantity U(t) based on each output control quantity; when the sum of Up(t) and Ui(t) is in the same direction as Ud(t), the three are summed; when the sum of Up(t) and Ui(t) is in the opposite direction to Ud(t), the output control quantity is 0.

[0071] More specifically, when the sum of the proportional output Up(t) and the integral output Ui(t) is greater than or equal to the negative of the derivative output Ud(t) and the negative of the derivative output Ud(t) is greater than 0, the control quantity is the sum of the three. When the sum of the proportional output Up(t) and the integral output Ui(t) is less than the negative of the derivative output Ud(t) and the sum of the proportional output Up(t) and the integral output Ui(t) is greater than 0, the control quantity is 0. When the negative of the sum of the proportional output Up(t) and the integral output Ui(t) is less than the derivative output Ud(t) and the negative of the sum of the proportional output Up(t) and the integral output Ui(t) is greater than 0, the control quantity is 0.

[0072] Step S4: Adjust the output amplitude of the total output control quantity U(t) according to the actual situation of the cold plate, and input the final output control quantity into the cold plate for control.

[0073] For step S4 regarding the amplitude adjustment of the total output control quantity U(t), it specifically includes: firstly, comparing the absolute value of the total output control quantity U(t) with the absolute value of the maximum power that the controlled module can withstand, determining whether the absolute value of the total output control quantity U(t) is less than or equal to the absolute value of the maximum power that the controlled module can withstand; if the absolute value of the total output control quantity U(t) is less than or equal to the absolute value of the maximum power that the controlled module can withstand, then the final output control quantity Uo(t) is directly taken as the total output control quantity U(t); if the absolute value of the total output control quantity U(t) is less than or equal to the absolute value of the maximum power that the controlled module can withstand, then the final output control quantity Uo(t) is directly taken as the total output control quantity U(t); If the absolute value of the total output control quantity U(t) is greater than the absolute value of the maximum power that the controlled module can withstand, further judgment is required. It is necessary to judge the relationship between the total output control quantity U(t) and the maximum power that the controlled module can withstand. If the total output control quantity U(t) is greater than the maximum power that the controlled module can withstand, |Uomax|, then the final output control quantity Uo(t) is directly taken as |Uomax|; if the total output control quantity U(t) is not greater than the maximum power that the controlled module can withstand, |Uomax|, then the final output control quantity Uo(t) is directly taken as -|Uomax|.

[0074] In this technical solution, the amplitude adjustment process depends on the relationship between the total output control quantity U(t) and the maximum power that the controlled module can withstand, and finally obtains the values ​​of Uo(t) in three cases.

[0075] Simultaneously, step S4 also involves the dynamic real-time adjustment of the PID derivative parameter Kd: when the condition |Uo(t)| equals |Uomax| is met for two consecutive temperature control cycles, the PID derivative parameter is multiplied by 2; when the condition |Uo(t)| equals |Uomax| is broken, the PID derivative parameter returns to its initial value. This process adjusts the PID derivative parameter in real time and feeds it back to the PID calculation module.

[0076] Based on this, this embodiment also includes a control optimization system based on the cold plate temperature conduction hysteresis system, which mainly includes an error calculation module, a PID calculation module, and an output control module. The error calculation module is connected to the PID calculation module. The error calculation module can calculate the real-time error by using the difference between the current temperature and the set temperature. The specific process can be found in step S1 above.

[0077] For the PID calculation module, it uses the real-time error obtained above to make logical judgments, and finally obtains each output control quantity. The specific process can be referred to step S2 above.

[0078] The output control module functions as follows: it integrates various output control quantities to obtain a total output control quantity, adjusts the amplitude of the total output control quantity, and adjusts the PID derivative parameters in real time. The specific process can be found in steps S3 and S4 above.

[0079] In this technical solution, the combined effect of the aforementioned error calculation module, PID calculation module, and output control module enables optimized control of the temperature conduction hysteresis system.

[0080] The output control module includes an integration unit, an amplitude adjustment unit, and a parameter adjustment unit. The integration unit can perform integrated calculations on each output control quantity. The integration unit is also connected to the amplitude adjustment unit, which is connected to the parameter adjustment unit.

[0081] In the above technical solution, the amplitude adjustment unit can adjust the output amplitude of the total output control quantity U(t).

[0082] Example 3 Based on Example 1 or Example 2, this example uses a specific implementation case to further illustrate the present invention.

[0083] 1. First, use a temperature controller to control the temperature of the cold plate, which is experiencing lag in temperature conduction due to poor sensor contact. The current temperature of the cold plate is 25℃, and the target temperature is 15℃.

[0084] 2. When temperature control begins, since the target temperature deviates significantly from the current temperature, according to step S2, the temperature controller adopts an integral separation temperature control strategy, using only P control for rapid cooling.

[0085] 3. When the temperature is rapidly reduced to the controlled temperature range by P, the temperature control module intervenes as described in step S2. In the initial stage, the deviation between the target temperature and the current temperature remains large, so the output is still dominated by P control. At the same time, I gradually accumulates to compensate for the steady-state error, and D predicts the temperature control trend and adjusts the output accordingly.

[0086] 4. As the error between the current temperature and the target temperature gradually decreases, P control gradually weakens and is replaced by I control. At the same time, due to the lag in temperature conduction, the actual temperature will be closer to the target temperature than the current sampling temperature. Therefore, with the lag in temperature conduction, the cooling rate will still maintain a certain rate. At this time, D predicts the temperature control trend and suppresses the cooling to a certain extent.

[0087] 5. If the absolute value of the output of Ud(t) is greater than the absolute value of the sum of the outputs of Up(t) and Ui(t) and the two are in opposite directions, unlike the brute-force suppression of conventional PID, in this algorithm, Uo(t) takes the value of 0, that is, the output stops instead of the output is reversed. By extending the conduction time, the temperature is fully conducted, and finally the sampled temperature is restored to its true value.

[0088] 6. If the absolute value of the output of Ud(t) is smaller than the absolute value of the sum of the outputs of Up(t) and Ui(t) and the two are in opposite directions, Uo(t) takes the sum of the two, that is, the output is reduced to slow down the output of the temperature control quantity, so that the temperature can be fully conducted and the sampled temperature can be restored to its true value.

[0089] 7. If the absolute value of the output of U(t) is equal to the maximum output of Uomax and continues for more than 2 temperature control cycles, the value of the Kd parameter will be adjusted in real time to enhance the derivative effect and prevent temperature overshoot to the greatest extent.

[0090] Under this algorithm scheduling, even if there is overshoot in the current temperature due to the lag in temperature conduction, the temperature control direction will not be forcibly adjusted (i.e., heating will not be forcibly used to suppress cooling during the cooling process), and the differential action will be enhanced in a timely manner to counteract the overshoot. Therefore, the problem of the difficulty in converging the temperature control cycle oscillation under the lag in temperature conduction is well solved.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A control optimization method based on a cold plate temperature conduction hysteresis system, characterized in that, Includes the following steps: S1 calculates the real-time error based on the current temperature and set temperature of the cold plate; S2, calculate the proportional output Up(t) based on the real-time error, and determine whether the absolute value of Up(t) is greater than the absolute value of the maximum output power. If yes, use the integral separation control algorithm; otherwise, use the temperature control algorithm. S3, integrate the output control quantities to obtain the total output control quantity U(t). If the sum of Up(t) and the integral output is in the same direction as the derivative output, then sum them up. If they are in opposite directions, the control quantity is 0. S4, adjust the output amplitude of U(t) according to the actual situation, and input the final output control quantity into the cold plate for control.

2. The control optimization method based on a cold plate temperature conduction hysteresis system according to claim 1, characterized in that, The temperature control algorithm includes performing mathematical operations on the real-time error e(t) and preset PID parameters to obtain the output control quantity, including proportional output Up(t), integral output Ui(t) and derivative output Ud(t).

3. The control optimization method based on a cold plate temperature conduction hysteresis system according to claim 2, characterized in that, The process of obtaining the integral output Ui(t) is as follows: Determine whether the absolute value of the product of the real-time error and the PID integral parameter is less than or equal to the absolute value of the integral anti-saturation parameter. If yes, the integral output Ui(t) is the product of the PID integral parameter and the real-time error. If no, further determine whether the product of the real-time error and the PID integral parameter is greater than the integral anti-saturation parameter. If yes, Ui(t) is the integral anti-saturation parameter. If no, Ui(t) is the negative of the integral anti-saturation parameter.

4. The control optimization method based on a cold plate temperature conduction hysteresis system according to claim 2, characterized in that, The proportional output Up(t) is the product of the real-time error and the PID proportional parameter, and the differential output Ud(t) is the product of the real-time error with respect to time and the PID differential parameter.

5. The control optimization method based on a cold plate temperature conduction hysteresis system according to claim 1, characterized in that, Step S4 includes: Determine whether the absolute value of the total output control quantity U(t) is within the range of the absolute value of the maximum power that the controlled module can withstand. If yes, the final output control quantity Uo(t) is U(t). If no, further determine whether the total output control quantity U(t) is greater than the maximum power that the controlled module can withstand. If yes, Uo(t) is the maximum power that the controlled module can withstand. If no, Uo(t) is the negative of the maximum power that the controlled module can withstand.

6. A control optimization method based on a cold plate temperature conduction hysteresis system according to claim 1 or 5, characterized in that, Step S4 further includes: adjusting the PID derivative parameter in real time and feeding it back to the PID calculation module; when the condition that |Uo(t)| equals |Uomax| is met in two consecutive temperature control cycles, the PID derivative parameter is multiplied by 2 based on the original value; when the condition that |Uo(t)| equals |Uomax| is broken, the PID derivative parameter is restored to its initial value.

7. A control optimization method based on a cold plate temperature conduction hysteresis system according to claim 1, 2, or 3, characterized in that, The real-time error is the difference between the set temperature and the current temperature of the cold plate. The current temperature is obtained by a temperature acquisition device, and the set temperature is set according to the actual situation.

8. A control optimization method based on a cold plate temperature conduction hysteresis system according to claim 1, 2, or 3, characterized in that, The integral separation control algorithm means that the temperature controller is controlled only by P, with high power output to accelerate the reduction of temperature difference, at which time the integral action is not effective.

9. A control optimization system based on a cold plate temperature conduction hysteresis system, applicable to the control optimization method based on a cold plate temperature conduction hysteresis system according to any one of claims 1-8, characterized in that, include: The error calculation module calculates the real-time error using the current temperature and the set temperature. The PID calculation module performs logical judgments based on the magnitude of the real-time error and ultimately obtains the output control quantity. The output control module integrates and calculates the total output control quantity from each output control quantity, adjusts the amplitude of the total output control quantity, and adjusts the PID derivative parameters in real time.

10. A control optimization system based on a cold plate temperature conduction hysteresis system according to claim 9, characterized in that, The output control module includes an integration unit that performs integrated calculations on various output control quantities; the integration unit is also connected to an amplitude adjustment unit, which is connected to a parameter adjustment unit.

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