Heat dissipation assembly control method, heat dissipation system and electronic equipment

Abstract

The invention discloses a heat dissipation assembly control method, a heat dissipation system and electronic equipment, and relates to the technical field of heat dissipation, and the method comprises the steps: in each control period, obtaining a current first temperature value of a target part and current operation state information of a corresponding heat dissipation assembly; based on the first temperature value and the current operation state information, utilizing a control model to predict second temperature values of the target part in a plurality of time steps in the future; determining a target rotating speed of the heat dissipation assembly based on the second temperature value; adjusting the heat dissipation assembly based on the target rotating speed; determining fault diagnosis information of the heat dissipation assembly based on the current operation state information; and adjusting the control model based on the fault diagnosis information. The technical problem that the reliability of the electronic equipment is reduced by a heat dissipation equipment adjusting mode in the related technology is solved, and the technical effect of improving the reliability of the electronic equipment is achieved.

Description

Technical Field

[0001] The present application relates to the field of heat dissipation technology, and in particular to a heat dissipation component control method, a heat dissipation system, and an electronic device. Background Art

[0002] As data center energy consumption continues to rise, cooling systems have become critical to their operations. Currently, electronic equipment cooling control primarily relies on closed-loop control technologies based on temperature feedback, such as the Proportional-Integral-Derivative (PID) control algorithm. This algorithm maintains system stability by detecting electronic device temperature, calculating errors, and adjusting cooling devices.

[0003] However, this approach cannot adjust the heat dissipation device in combination with the operating status information of the heat dissipation device, resulting in poor adjustment accuracy and reduced reliability of the electronic equipment. Summary of the Invention

[0004] The present application provides a heat dissipation component control method, a heat dissipation system, and an electronic device to at least solve the problem in the related art that the heat dissipation device adjustment method has poor adjustment accuracy, resulting in low reliability of the electronic device.

[0005] The present application provides a heat dissipation component control method, comprising: In each control cycle, obtaining a current first temperature value of the target component and current operating state information of the corresponding heat dissipation component; Based on the first temperature value and the current operating state information, using the control model to predict a second temperature value of the target component at multiple future time steps; determining a target rotational speed of the heat dissipation component based on the second temperature value; Adjust the cooling components based on the target speed; Determining fault diagnosis information of the heat dissipation component based on current operating status information; Adjust the control model based on fault diagnosis information.

[0006] The present application provides a heat dissipation system, comprising: a target component, a heat dissipation assembly, a sensing assembly, and a heat dissipation assembly control device; The heat dissipation component is used to dissipate heat from the target component during its operation; The sensing component is used to collect the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component in each control cycle, and send the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component to the heat dissipation component control device; The heat dissipation component control device is used to control the speed of the heat dissipation component using a control model based on the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component in each control cycle; and adjust the control model based on the current operating status information of the heat dissipation component.

[0007] The present application also provides an electronic device, comprising: any one of the above-mentioned heat dissipation systems.

[0008] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned heat dissipation component control methods are implemented.

[0009] The present application also provides a computer program product, including a computer program, which implements the steps of any of the above-mentioned heat dissipation component control methods when executed by a processor.

[0010] Through the present application, within each control cycle, the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component are obtained; based on the first temperature value and the current operating status information, the second temperature value of the target component in multiple future time steps is predicted using a control model; based on the second temperature value, the target speed of the heat dissipation component is determined; based on the target speed, the heat dissipation component is adjusted; based on the current operating status information, the fault diagnosis information of the heat dissipation component is determined; and based on the fault diagnosis information, the control model is adjusted. By using the current operating status information of the heat dissipation component to adjust the control model, and then adjusting the speed of the heat dissipation component, the adjustment accuracy of the heat dissipation component is improved. Therefore, the technical problem in the related art that the heat dissipation device adjustment method reduces the reliability of the electronic device can be solved, and the technical effect of improving the reliability of the electronic device can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0012] Figure 1 This is a flow chart of using a PID control algorithm to control heat dissipation in electronic equipment in related technologies; Figure 2 A schematic diagram of a process for fault monitoring of heat dissipation equipment in related art; Figure 3 A schematic structural diagram of a heat dissipation system provided in an embodiment of the present application; Figure 4 A schematic flow chart of a heat dissipation component control method provided in an embodiment of the present application; Figure 5 A flow chart of another heat dissipation component control method provided in an embodiment of the present application; Figure 6 A schematic diagram of a process for determining a bearing wear rate according to an embodiment of the present application; Figure 7 A schematic diagram of a process for determining a coil aging rate according to an embodiment of the present application; Figure 8 A schematic diagram of a flow chart for determining a magnetic gap unbalance rate according to an embodiment of the present application; Figure 9 A schematic diagram of a process for determining an efficiency factor according to an embodiment of the present application; Figure 10 A schematic structural diagram of another heat dissipation system provided in an embodiment of the present application; Figure 11 A schematic diagram of a process for adjusting an MPC model based on fault diagnosis information of a heat dissipation device according to an embodiment of the present application; Figure 12 A flowchart for updating the average efficiency factor provided in an embodiment of the present application; Figure 13 A flow chart of another heat dissipation component control method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0013] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0014] It should be noted that, in the description of this application, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. The terms "first," "second," etc., in this application are used to distinguish similar objects, and are not used to describe a particular order or sequence.

[0015] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0016] With the rapid development of cloud computing, artificial intelligence, and edge computing, data center energy consumption continues to rise, with cooling systems accounting for a significant portion of this energy consumption. Therefore, cooling systems have become critical to data center operations. Currently, electronic equipment cooling control primarily relies on closed-loop control technologies based on temperature feedback, such as PID control algorithms. Figure 1 This is a flow chart of using PID control algorithm to control the heat dissipation of electronic equipment in related technologies, such as Figure 1 As shown in the figure, the core logic of the PID control algorithm is "detect temperature → calculate error → adjust heat dissipation device". Specifically, after the load of the electronic device suddenly changes, the temperature of the electronic device components increases. After the temperature sensor collects the temperature data of the electronic device components, the PID controller generates a control instruction based on the fixed response parameters and outputs a pulse width modulation (PWM) signal based on the control instruction to adjust the heat dissipation device. Due to the hysteresis of the temperature change of the electronic device components, the PID control algorithm outputs a PWM signal based on the control instruction with a hysteresis, that is, the response delay is 2 to 5 seconds. During this period, the component temperature may soar by 6 to 8 degrees Celsius, and the temperature fluctuates greatly. Due to the fixed response parameters of the PID control algorithm and the hysteresis of the output PWM signal, the system's dynamic adjustment capability is insufficient, which reduces the reliability of the electronic device.

[0017] Furthermore, to prevent temperature overshoot, the PID control algorithm needs to maintain 15% to 25% redundant air volume, resulting in energy waste.

[0018] It should be noted that the related art uses a PID control algorithm to adjust the heat dissipation devices when all heat dissipation devices are operating normally. If at least one heat dissipation device is detected to have a fault, the other heat dissipation devices are directly controlled to maintain full speed operation, resulting in a waste of resources. Figure 2 FIG. 1 is a flow chart of a related art method for monitoring a heat dissipation device for a fault. Figure 2 As shown, heat dissipation device fault monitoring primarily relies on comparing data from a speed sensor with a threshold comparator to determine if the device is faulty. Specifically, the speed sensor collects the fan rotation signal (i.e., speed) of the heat dissipation device in real time. This speed is then fed into the threshold comparator for speed threshold determination. If the speed is below the threshold, an alarm is triggered, confirming a heat dissipation device fault. If the speed is above the threshold, a normal status indication is output, confirming that the heat dissipation device is functioning properly.

[0019] In the related art, when using the PID control algorithm to adjust the heat dissipation device, it is impossible to adjust the heat dissipation device in combination with the operating status information of the heat dissipation device, and the method of fault monitoring of the heat dissipation device in the related art only monitors whether the rotational speed is lower than a fixed threshold, so it can only detect a complete stop fault, and cannot detect progressive faults such as bearing wear and coil aging, resulting in poor adjustment accuracy and reduced reliability of the electronic equipment.

[0020] To solve the above technical problems, an embodiment of the present application provides a heat dissipation component control method, a heat dissipation system, and an electronic device. The heat dissipation component control method includes: obtaining the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component in each control cycle; based on the first temperature value and the current operating status information, using a control model to predict the second temperature value of the target component in multiple future time steps; based on the second temperature value, determining the target speed of the heat dissipation component; adjusting the heat dissipation component based on the target speed; determining the fault diagnosis information of the heat dissipation component based on the current operating status information; and adjusting the control model based on the fault diagnosis information. The method provided by the above scheme improves the adjustment accuracy of the heat dissipation component and thereby improves the reliability of the electronic device by adjusting the control model using the current operating status information of the heat dissipation component in each control cycle, so that the adjusted control model is used to control the speed of the heat dissipation component in the next control cycle.

[0021] In conjunction with the specific application environment architecture or specific hardware architecture on which the execution of the heat dissipation component control method depends, the specific application environment architecture or specific hardware architecture is described herein.

[0022] The embodiment of the present application provides a heat dissipation system, Figure 3 A schematic diagram of the heat dissipation system provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the heat dissipation system includes a target component, a heat dissipation component, a sensor component and a heat dissipation component control device.

[0023] The heat dissipation component is used to dissipate heat from the target component during operation. The target component can be a heat-generating component in an electronic device, such as a central processing unit (CPU), a graphics processing unit (GPU), or a memory module. In other words, the target component includes at least a CPU, a GPU, and a memory module.

[0024] The heat dissipation assembly includes a plurality of heat dissipation devices, and the heat dissipation devices may be heat dissipation fans.

[0025] The sensing component is used to collect the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component in each control cycle, and send the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component to the heat dissipation component control device.

[0026] The current operating status information includes the current speed of the heat dissipation device, the current bearing vibration signal, the current motor current signal, the current coil temperature value, the current vibration signal of the rotating plane, etc. The corresponding heat dissipation component is the heat dissipation component corresponding to the target component, that is, the heat dissipation component for the target component.

[0027] The input end of the sensing component is connected to the target component and the heat dissipation component, the output end of the sensing component is connected to the heat dissipation component control device, and the air outlet of the heat dissipation component is set corresponding to the target component.

[0028] The sensing assembly includes a temperature sensor, a speed sensor, a vibration sensor, and a current sensor. The temperature sensor is used to collect the current first temperature value of the target component and the current coil temperature value of the heat sink during each control cycle. The speed sensor is used to collect the current speed of the heat sink during each control cycle. The vibration sensor is used to collect the current bearing vibration signal and the current vibration signal of the rotating plane of the heat sink during each control cycle. The current sensor is used to collect the current motor current signal of the heat sink during each control cycle.

[0029] The heat dissipation component control device is used to control the speed of the heat dissipation component using a control model based on the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component in each control cycle; and adjust the control model based on the current operating status information of the heat dissipation component.

[0030] It is understood that the heat sink control device adjusts the control model based on the current operating status of the heat sink during each control cycle, and then uses the adjusted control model to control the heat sink speed during the next control cycle. The heat sink control device may be a microcontroller unit (MCU) in the heat sink control board. The control model may be a model predictive control (MPC) model.

[0031] The heat dissipation system provided by the present application uses a model predictive control model to determine the rotational speed of the heat dissipation component, shortening response time and enabling timely adjustment of the heat dissipation component. By adjusting the control model using the current operating status information of the heat dissipation component during each control cycle, the adjusted control model is used to control the heat dissipation component's rotational speed during the next control cycle. This improves the heat dissipation component's adjustment accuracy and, in turn, enhances the reliability of the electronic device.

[0032] An embodiment of the present application provides an electronic device, which includes the heat dissipation system provided in the above embodiment. The electronic device may be a switching node, a computing node, a storage node, a cabinet server, etc.

[0033] The embodiment of the present application provides a heat dissipation component control method, which is applied to the heat dissipation component control device in the above heat dissipation system. Figure 4 A flow chart of a heat dissipation component control method provided in an embodiment of the present application is shown as follows: Figure 4 As shown, the heat dissipation component control method includes the following steps: Step S401 : obtaining a current first temperature value of a target component and current operating status information of a corresponding heat dissipation component in each control cycle.

[0034] The control period may be 1 second. The heat dissipation assembly includes multiple heat dissipation devices. During each control period, a temperature sensor collects in real time the current first temperature value of a target component of the electronic device and the current coil temperature value of the heat dissipation device. A speed sensor collects in real time the current speed of the heat dissipation device. A vibration sensor collects in real time the current bearing vibration signal and the current vibration signal of the rotating plane of the heat dissipation device. A current sensor collects in real time the current motor current signal of the heat dissipation device.

[0035] Step S402 : Based on the first temperature value and the current operating state information, a control model is used to predict a second temperature value of the target component in a plurality of future time steps.

[0036] As mentioned above, the control model is an MPC model.

[0037] Step S403: determining a target rotation speed of the heat dissipation component based on the second temperature value.

[0038] Based on the second temperature value, the target rotational speeds of the plurality of heat dissipation devices in the heat dissipation assembly are determined using the MPC model.

[0039] Step S404: adjusting the heat dissipation component based on the target rotation speed.

[0040] After determining the target rotation speeds of multiple heat dissipation devices, a PWM signal corresponding to any heat dissipation device is generated based on the target rotation speed of the heat dissipation device, and the heat dissipation device is adjusted based on the PWM signal to enable the heat dissipation device to operate at the target rotation speed.

[0041] Step S405: determining fault diagnosis information of the heat dissipation component based on the current operating status information.

[0042] Among them, the fault diagnosis information includes bearing wear rate, coil aging rate and magnetic gap imbalance rate.

[0043] Step S406: Adjust the control model based on the fault diagnosis information.

[0044] It can be understood that in the next control cycle, based on the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component, the adjusted MPC model is used to predict the second temperature value of the target component in multiple time steps in the future, and based on the second temperature value, the target speed of the heat dissipation component is determined.

[0045] The heat dissipation assembly control method provided in the embodiments of the present application uses a model predictive control model to predict temperature and determine the target speed of the heat dissipation assembly, thereby shortening response time and enabling timely adjustment of the heat dissipation device. By using the current operating status information of the heat dissipation assembly to adjust the control model, the adjusted control model is used to control the heat dissipation assembly speed during the next control cycle, thereby improving the adjustment accuracy of the heat dissipation assembly and thereby enhancing the reliability of the electronic device.

[0046] The embodiment of the present application provides a heat dissipation component control method, which is applied to the heat dissipation component control device in the above heat dissipation system. Figure 5 A flow chart of a heat dissipation component control method provided in an embodiment of the present application is shown as follows: Figure 5 As shown, the heat dissipation component control method includes the following steps: Step S501: In each control cycle, obtain the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation component. Figure 4 Step S401 of the illustrated embodiment will not be described in detail here.

[0047] Step S502 : Based on the first temperature value and the current operating state information, a control model is used to predict a second temperature value of the target component in a plurality of future time steps.

[0048] Specifically, the above step S502 includes: Step S5021: determining an average rotation speed of the plurality of heat dissipation devices in the heat dissipation assembly based on the current rotation speeds of the plurality of heat dissipation devices.

[0049] It can be understood that after obtaining the current rotational speeds of multiple heat dissipation devices in the heat dissipation assembly corresponding to the target component, the current rotational speeds of the multiple heat dissipation devices are summed, and the summed value is divided by the number of heat dissipation devices in the heat dissipation assembly to obtain the average rotational speed of the multiple heat dissipation devices.

[0050] Step S5022: Determine the temperature change rate of the target component based on the thermodynamic model. The thermodynamic model is: dT / dt = a·(P heat - η·k·rpm^3) / (M·c p ) Where dT / dt is the temperature change rate of the target component, a is the heat exchange coefficient of the target component in the previous control cycle, P heat is the current power of the target component, η is the average efficiency factor of the previous control cycle of multiple heat dissipation devices, k is the startup constant of the heat dissipation device, rpm is the average speed of multiple heat dissipation devices, M is the heat capacity of the radiator, c p is the specific heat capacity of air.

[0051] Among them, the initial heat exchange coefficient of the target component is obtained by performing an initial calibration after a 50% speed thermal balance test on multiple heat dissipation devices corresponding to the target component, which reflects the heat transfer efficiency from the target component to the environment. After that, it is updated online in each control cycle according to the update of the average efficiency factor of the current control cycle of the multiple heat dissipation devices corresponding to the target component.

[0052] The aforementioned sensing assembly may also include a power sensor, which can be used to directly obtain the current power of the target component. The startup constant of the heat sink is determined by its design parameters. The heat capacity of the heat sink is an inherent property of the heat sink, determined during the design phase or factory testing. The specific heat capacity of air is also an inherent property of air.

[0053] Step S5023: Based on the temperature prediction model, predict the second temperature value of the target component in multiple time steps in the future. The temperature prediction model is:

[0054] in, is the second temperature value of the target component in the future i-th time step, is the current first temperature value of the target component, is the time step.

[0055] The time step can be any value between 0.5 seconds and 1 second, which is set by the technician.

[0056] It should be noted that the model predictive control model includes a thermodynamic model and a temperature prediction model.

[0057] Step S503: Determine the target rotation speed of the heat dissipation component based on the second temperature value. Figure 4 Step S403 of the illustrated embodiment will not be described in detail here.

[0058] Step S504: Adjust the heat dissipation component based on the target speed. Figure 4 Step S404 of the illustrated embodiment will not be described in detail here.

[0059] Step S505: Determine the fault diagnosis information of the heat dissipation component based on the current operating status information. Figure 4Step S405 of the illustrated embodiment will not be described in detail here.

[0060] Step S506: Adjust the control model based on the fault diagnosis information. Figure 4 Step S406 of the illustrated embodiment will not be described in detail here.

[0061] The heat dissipation component control method provided in the embodiment of the present application predicts the second temperature value of the target component in multiple future time steps through a model predictive control model, thereby achieving accurate prediction of the temperature value, and further achieving accurate determination of the target speed of the heat dissipation device, avoiding energy waste and shortening the response time.

[0062] In some optional implementations, the above step S503 includes: Step A1, with the goal of minimizing the calculated result of the cost function, based on the target speed constraints of the multiple heat dissipation devices and the second temperature value, determines the target speed prediction value of each heat dissipation device in the future multiple time steps. The cost function is:

[0063] in, is the calculation result of the cost function; N is the number of predicted time steps; and is the weight coefficient, obtained through offline calibration; is the second temperature value of the target component in the future i-th time step; The reference temperature threshold of the target component is the target temperature at which the temperature of the target component can be controlled to stabilize after the system is pressurized, that is, the normal operating temperature of the target component; It is the predicted value of the target rotational speed of the j-th heat dissipation device in the i-th time step in the future among the multiple heat dissipation devices corresponding to the target component.

[0064] The target rotation speed constraints of the multiple heat dissipation devices corresponding to the target component are:

[0065] in, is the lower limit of the speed of the j-th heat dissipation device, is the upper limit of the speed of the jth heat sink. The bearing wear rate and coil aging rate of the heat sink will dynamically adjust this constraint, thereby changing the target speed of the cooling fan calculated by the MPC model.

[0066] It should be noted that the MPC model includes a cost function and target speed constraints for the multiple heat sinks corresponding to the target component. By minimizing the cost function, the MPC model calculates predicted target speed values ​​for each of the multiple heat sinks corresponding to the target component over multiple future time steps based on the target speed constraints and the second temperature values ​​of the target component over multiple future time steps, thereby balancing temperature control and energy consumption.

[0067] Step A2: based on the target speed prediction values ​​of each heat dissipation device in multiple future time steps, determine the target speed prediction value of each heat dissipation device in the first future time step as the target speed of the heat dissipation device.

[0068] For any heat dissipation device among the multiple heat dissipation devices, based on the target speed prediction values ​​of the heat dissipation device in multiple future time steps, the target speed prediction value of the heat dissipation device in the first future time step is determined as the target speed of the heat dissipation device.

[0069] The heat dissipation component control method provided in the embodiment of the present application determines the target speed prediction values ​​of the multiple heat dissipation devices corresponding to the target component in multiple future time steps based on the constraint conditions of the target speeds of the multiple heat dissipation devices corresponding to the target component and the second temperature values ​​of the target component in multiple future time steps, by taking the calculation result of the cost function as the goal of minimizing the cost function, thereby achieving accurate prediction of the target speed of the heat dissipation device.

[0070] In some optional implementations, the above step S505 includes: Step B1: for any heat dissipation device in the heat dissipation assembly, amplify, filter, analog-to-digital convert, and fast Fourier transform the current bearing vibration signal of the heat dissipation device to obtain a bearing frequency domain vibration signal of a target characteristic frequency band.

[0071] Figure 6 A flow chart of determining the bearing wear rate provided in the embodiment of the present application is shown as follows: Figure 6 As shown, a vibration sensor, such as a micro-electro-mechanical system (MEMS) vibration sensor, is used to collect the current bearing vibration signal of the heat dissipation device in real time. The vibration sensor is an acceleration signal, collected over a 10-millisecond window with 100 sampling points. The sampling rate is greater than or equal to 10 kHz to capture high-frequency characteristics. This ensures that the sampling rate strictly adheres to the Nyquist sampling theorem: the sampling rate must be greater than or equal to twice the highest frequency of the bearing vibration signal.

[0072] The heat sink's current bearing vibration signal undergoes signal preprocessing. Specifically, it is amplified and filtered using a differential amplifier and an active filter. The filter parameters are set to 0.5kHz-1kHz. It should be noted that these filter parameters are based on the typical bearing defect frequency band, which is derived from the cutoff frequency in the bearing design manual and is 0.5kHz-1kHz. As can be seen, signal preprocessing can eliminate noise interference.

[0073] After amplification and filtering, the filtered signal is digitized using an analog-to-digital converter (ADC) to obtain the bearing's time-domain vibration signal. Fast Fourier Transform (FFT) processing, or FFT spectrum analysis, is performed on the bearing's time-domain vibration signal to obtain the bearing's frequency-domain vibration signal within the target characteristic frequency band, which is 0.5 kHz to 1 kHz.

[0074] Step B2: Determine the energy integral value of the bearing frequency domain vibration signal in the target characteristic frequency band based on the first formula. The first formula is:

[0075] Among them, E measured is the energy integral value of the bearing frequency domain vibration signal in the target characteristic frequency band; X(P) is the bearing frequency domain vibration signal at the Pth frequency point in the target characteristic frequency band. It can be understood that there are 100 frequency points in total; f min is the lower limit of the target characteristic frequency band, i.e. 0.5kHz, f max The upper limit of the target characteristic frequency band is 1kHz.

[0076] like Figure 6 As shown, after obtaining the bearing frequency domain vibration signal of the target characteristic frequency band, the energy integral value of the bearing frequency domain vibration signal of the target characteristic frequency band is calculated using the first formula.

[0077] Step B3: Determine the warning energy threshold of the bearing frequency domain vibration signal in the target characteristic frequency band based on the second formula. The second formula is: E threshold =Baseline energy × [0.8 + 0.4 × (current speed of the heat sink / rated speed of the heat sink)] Among them, E thresholdThe baseline energy is the reference energy value of the bearing frequency-domain vibration signal in the target characteristic frequency band of the heat dissipation device in a healthy state. Specifically, the baseline energy is measured after the system is powered on and in healthy operation, representing the spectral energy when there are no faults. The values ​​of 0.8 and 0.4 are empirical sensitivity coefficients, obtained through experiments.

[0078] By adaptively adjusting the threshold, the influence of the rotation speed of the heat dissipation device on the vibration energy is taken into account, thus avoiding the limitation of a fixed threshold.

[0079] Step B4: Determine the bearing wear rate of the heat dissipation device based on the third formula. The third formula is: α = min(1, (E measured -E threshold ) / E range ) Among them, α is the bearing wear rate of the heat dissipation device, E range The effective wear energy range span of the heat dissipation device is obtained through accelerated life testing, which is the span of the energy range of the heat dissipation device from healthy to failure.

[0080] The heat dissipation component control method provided in the embodiment of the present application focuses on the target characteristic frequency band by amplifying, filtering, analog-to-digital conversion and fast Fourier transform processing of the bearing vibration signal, effectively filtering out irrelevant noise and interference signals, ensuring that the signal analyzed subsequently contains only core information directly related to bearing wear, thereby improving the accuracy of the bearing wear rate.

[0081] In some optional implementations, the above step S505 includes: Step C1 : for any heat dissipation device in the heat dissipation assembly, amplify and perform analog-to-digital conversion on the current motor current signal of the heat dissipation device to obtain the motor current value to be corrected.

[0082] Figure 7 A schematic diagram of a process for determining the coil aging rate provided in an embodiment of the present application is shown in FIG. Figure 7As shown in the figure, the process includes establishing a cold baseline (initialization phase): After the system is powered on, the heat sink is operated at 50% speed and allowed to wait for 5 minutes to reach thermal equilibrium. The cold baseline motor current and cold baseline coil temperature values ​​of the heat sink are then recorded. This step is performed only once at power-on or reset and serves as the basis for subsequent comparisons. The cold baseline motor current value is acquired using a current sensor (using a sampling resistor to measure the motor current), and the cold baseline coil temperature value is acquired using a negative temperature coefficient thermistor (NTC) sensor. The requirement that the heat sink be operated at 50% speed and allowed to wait for 5 minutes to reach thermal equilibrium is empirically determined to ensure thermal equilibrium and avoid transient effects.

[0083] Real-time acquisition of the heat dissipation device's current motor current signal and coil temperature: A sampling resistor is used to continuously monitor the heat dissipation device's current motor current signal and simultaneously acquire its coil temperature. To ensure data reliability, the motor current signal undergoes median filtering and sliding average filtering, ensuring a signal-to-noise ratio greater than 35dB (decibels) to meet diagnostic requirements. The median filter removes abnormal spikes, such as power supply ripple; the sliding average filter uses a 10 millisecond window to smooth out random fluctuations.

[0084] Signal preprocessing: The current amplifier amplifies the collected motor current signal of the heat dissipation device to improve resolution and signal quality. The ADC performs analog-to-digital conversion on the amplified current motor current signal to obtain the motor current value to be corrected.

[0085] Step C2: Determine the target motor current value based on the temperature compensation model. The temperature compensation model is: I comp = I meas × (1 + b·(T now - T cold )) Among them, I comp is the target motor current value; I meas is the motor current value to be corrected; b is the coil temperature coefficient, which is a fixed material coefficient; T now is the current coil temperature value, T cold It is the coil reference temperature value, that is, the cold reference coil temperature value.

[0086] It should be noted that the temperature compensation model corrects the motor current to eliminate the effect of temperature on the copper wire resistance, which increases with temperature. The copper wire resistance refers to the resistance of the copper wire in the motor coil of the heat sink. It should be understood that the coil refers to the motor coil of the heat sink.

[0087] Temperature compensation calculations correct for temperature drift (at high temperatures, copper wire resistance increases and current drops may be misinterpreted as aging), ensuring that the calculated coil aging rate reflects actual degradation.

[0088] Step C3: Determine the coil aging rate of the heat dissipation device based on the fourth formula. The fourth formula is: β = max(0,(I cold -I comp ) / I cold ) Among them, β is the coil aging rate of the heat dissipation device, I cold It is the motor reference current value, that is, the cold reference motor current value.

[0089] The fourth formula, based on differential analysis logic, states that the current drop directly reflects the increase in coil resistance. This formula quantifies the degree of motor coil aging. When β > 0, the motor current has dropped, suggesting an increase in coil resistance, likely due to aging coil insulation or damage to the winding structure.

[0090] The heat dissipation component control method provided in the embodiment of the present application corrects the motor current value through a temperature compensation model, effectively eliminating the influence of coil temperature changes on the current measurement value, so that the corrected target motor current value more truly reflects the actual electrical state of the coil, and improves the accuracy of the coil aging rate.

[0091] In some optional implementations, the above step S505 includes: Step D1 : for any heat dissipation device in the heat dissipation assembly, filtering, amplifying and analog-to-digital conversion are performed on the current vibration signal of the rotation plane of the heat dissipation device to obtain a target vibration signal of the rotation plane.

[0092] Figure 8 A flow chart of determining the magnetic gap unbalance rate provided in an embodiment of the present application is shown in FIG. Figure 8 As shown in the figure, the process includes real-time acquisition of three-axis vibration signals: A three-axis accelerometer is used to collect vibration signals in the heat sink's rotational plane (X and Y axes) and axial direction (Z axis), covering the entire rotation cycle. The sampling rate is no less than 10kHz, satisfying the Nyquist theorem to ensure the capture of high-frequency vibrations. The current vibration signals of the heat sink in the rotational plane and axial direction, or time-domain vibration signals, are obtained.

[0093] Signal preprocessing: The current vibration signals in the rotation plane and the axial direction are filtered through filters to obtain filtered vibration signals in the rotation plane and the axial direction. The filter frequency band is set to 0.5-2kHz, which is determined based on the rotation frequency of the heat dissipation device.

[0094] The filtered vibration signals in the rotating plane and the axial direction are amplified by a signal amplifier to obtain amplified vibration signals in the rotating plane and the axial direction.

[0095] The ADC performs analog-to-digital conversion on the amplified vibration signals in the rotational plane and axial direction to obtain the target vibration signals in the rotational plane and axial direction. Signal preprocessing can improve resolution and eliminate noise.

[0096] Step D2: Determine the peak-to-peak value of the X-axis vibration and the peak-to-peak value of the Y-axis vibration of the heat dissipation device based on the fifth formula. The fifth formula is: X pp = max(x(t)) - min(x(t)) Y pp = max(y(t)) - min(y(t)) Among them, X pp is the peak-to-peak value of X-axis vibration, Y pp is the peak-to-peak value of the Y-axis vibration, x(t) is the target vibration signal of the X-axis, y(t) is the target vibration signal of the Y-axis, and the target vibration signal of the rotating plane includes the target vibration signal of the X-axis and the target vibration signal of the Y-axis.

[0097] The vibration intensity is reflected by calculating the peak-to-peak value of the vibration. The difference in the peak-to-peak value of the vibration on the X / Y axis indicates the uneven magnetic gap.

[0098] Step D3: Determine the magnetic gap unbalance rate of the heat dissipation device based on the sixth formula. The sixth formula is: γ = |X pp - Y pp | / (( X pp + Y pp ) / 2) Where γ is the magnetic gap imbalance ratio of the heat sink. This formula is based on vibration analysis standards (peak-to-peak difference method) and reflects the asymmetric vibration caused by rotor eccentricity.

[0099] In some optional implementations, the above step S506 includes: Step E1 : determining an average efficiency factor of a current control cycle of a plurality of heat dissipation devices based on fault diagnosis information of the plurality of heat dissipation devices in the heat dissipation assembly.

[0100] Step E2: updating the thermodynamic model based on the average efficiency factors of the current control cycle of the plurality of heat dissipation devices.

[0101] The average efficiency factor indicates the efficiency of converting electrical energy to mechanical energy and then to airflow kinetic energy.

[0102] Step E3, based on the fault diagnosis information of multiple heat dissipation devices, updates the constraint conditions of the target speeds of multiple heat dissipation devices and / or determines the compensation value of the second temperature value of the target component in multiple future time steps, so as to determine the target speeds of multiple heat dissipation devices in the next control cycle based on the updated thermodynamic model, the updated constraint conditions of the target speeds of multiple heat dissipation devices and / or the compensation value of the second temperature value of the target component in multiple future time steps.

[0103] The model predictive control model includes a thermodynamic model and constraint conditions of target rotational speeds of a plurality of heat dissipation devices corresponding to a target component.

[0104] The heat dissipation component control method provided in the embodiment of the present application adjusts the thermodynamic model and the constraint conditions of the target speed in combination with fault diagnosis information, so that the temperature value predicted by the MPC model is more accurate, thereby improving the accuracy of the determined target speed, improving the adjustment accuracy of the heat dissipation device, and improving the reliability of the electronic equipment.

[0105] In some optional embodiments, the above step E1 includes: Step E11: For any heat dissipation device among the multiple heat dissipation devices, determine the efficiency factor of the current control cycle of the heat dissipation device based on the seventh formula. The seventh formula is: = η0 × [1 - q1×α - q2×β - q3×γ] in, 1 is the efficiency factor of the current control cycle of the heat dissipation device, η0 is the initial efficiency factor of the heat dissipation device, α is the bearing wear rate of the heat dissipation device, β is the coil aging rate of the heat dissipation device, γ is the magnetic gap imbalance rate of the heat dissipation device, and q1, q2 and q3 are fault sensitivity coefficients.

[0106] The initial efficiency factor of the heat sink is the factory-calibrated value of the efficiency factor of the heat sink, which is usually in the range of 0.65 to 0.75 and is determined based on actual conditions. q1 can be set to 0.4, q2 can be set to 0.3, and q3 can be set to 0.3, which are determined based on experiments.

[0107] Figure 9 A schematic diagram of a process for determining an efficiency factor according to an embodiment of the present application is shown in FIG. Figure 9As shown, the process includes: determining the fault diagnosis information of the heat dissipation device based on the current operating status information of the heat dissipation device, and obtaining the efficiency factor of the current control cycle of the heat dissipation device through the seventh formula based on the bearing wear rate, coil aging rate and magnetic gap imbalance rate in the fault diagnosis information.

[0108] Step E12 : determining an average efficiency factor of the current control period of the plurality of heat dissipation devices based on the efficiency factor of the current control period of each heat dissipation device in the plurality of heat dissipation devices corresponding to the target component.

[0109] It can be understood that the efficiency factors of the current control period of each heat dissipation device in the multiple heat dissipation devices corresponding to the target component are added and averaged to obtain the average efficiency factors of the current control period of the multiple heat dissipation devices corresponding to the target component.

[0110] In some optional embodiments, the above step E2 includes: Step E21: Determine the heat exchange coefficient of the target component in the current control cycle based on the eighth formula. The eighth formula is: a new = a + R×(η new -η) Among them, a new is the heat exchange coefficient of the current control cycle of the target component, a is the heat exchange coefficient of the previous control cycle of the target component; R is the adjustment coefficient, which is set by the technician; η new is the average efficiency factor of the current control cycle of the multiple heat dissipation devices corresponding to the target component, and η is the average efficiency factor of the previous control cycle of the multiple heat dissipation devices corresponding to the target component.

[0111] Step E22 : updating the thermodynamic model based on the average efficiency factors of the current control period of the plurality of heat dissipation devices corresponding to the target component and the heat exchange coefficient of the current control period of the target component.

[0112] It is understandable that the a in the thermodynamic model is updated to a new , η is updated to η new For the target component, the updated thermodynamic model is: dT / dt = a new ·(P heat - η new ·k·rpm^3) / (M·c p ) In the next control cycle, the second temperature value of the target component in multiple future time steps is predicted based on the updated thermodynamic model, and is used for the MPC model to optimize and solve the target rotational speeds of multiple heat dissipation devices corresponding to the target component.

[0113] The update of η will lead to a change in the heat dissipation efficiency of the heat dissipation device, which will also affect the heat exchange coefficient of the target component, that is, the update of a is based on the update of η.

[0114] Integrating fault diagnosis information from heat dissipation equipment into MPC control, updating η and a, ensures that the thermodynamic model adapts to faults and reflects them in real time, thereby improving temperature prediction accuracy, energy efficiency, and safety. Through fault-adaptive adjustments, MPC avoids full-speed operation and reduces energy consumption. This closed-loop architecture, encompassing sensor monitoring, fault diagnosis, and model adaptation, enables real-time optimization of control parameters under fault conditions, significantly enhancing system robustness.

[0115] In some optional implementations, the above step E3 includes: Step E31: For any heat dissipation device in the heat dissipation assembly, if the bearing wear rate of the heat dissipation device is greater than the preset wear rate threshold, the upper speed limit of the heat dissipation device is updated based on the ninth formula. The ninth formula is: max_rpm new =max_ rpm old × (1-0.8×the bearing wear rate of the heat dissipation device) Among them, max_ rpm new The upper limit of the speed of the cooling device after this update, max_ rpm old This is the upper limit of the cooling device's rotation speed before this update.

[0116] It is understandable that when the bearing wear rate of the heat dissipation device is greater than the preset wear rate threshold, the upper speed limit is appropriately lowered to limit the heat dissipation device to operate in a high wear state to avoid further deterioration of damage by mechanical stress.

[0117] The preset wear rate threshold may be 0.15, which is set by a technician and is not specifically limited here.

[0118] It should be noted that if the bearing wear rate of the heat dissipation device is greater than a preset wear rate threshold, a bearing wear abnormality warning is triggered.

[0119] Step E32: determining an average bearing wear rate of the plurality of heat dissipation devices based on the bearing wear rate of each heat dissipation device in the plurality of heat dissipation devices.

[0120] Step E33: Determine the compensation value of the second temperature value of the target component at multiple future time steps based on the tenth formula. The tenth formula is: T offset = 1.5×average bearing wear rate of multiple heat dissipation devices Among them, T offset The compensation value for the second temperature value of the target component at a number of future time steps.

[0121] It is understandable that when the bearings of the heat dissipation device are worn, the heat dissipation efficiency of the heat dissipation device decreases, the airflow is reduced at the same speed, and the heat dissipation capacity decreases. By setting the temperature margin and adding it to the second temperature value of the target component in multiple future time steps, the MPC control model can predict the temperature change more conservatively and trigger a higher speed in advance.

[0122] It should be noted that the compensation value is added to the second temperature value of the target component in multiple future time steps, that is, after the second temperature value of the target component in multiple future time steps is predicted by using the model predictive control model, the compensation value is added to the predicted second temperature values ​​of the target component in multiple future time steps, and then based on the temperature value after adding the compensation value, the target speed of the multiple heat dissipation devices corresponding to the target component is determined.

[0123] In some optional implementations, the above step E3 includes: Step F1: For any heat dissipation device in the heat dissipation assembly, if the coil aging rate of the heat dissipation device is greater than the preset aging rate threshold, the lower speed limit of the heat dissipation device is updated based on the eleventh formula. The eleventh formula is: min_rpm new =min_rpm old × (1 + 0.5 × the cooling device's coil aging rate) Among them, min_rpm new The lower limit of the speed of the cooling device after this update, min_rpm old This is the lower speed limit of the cooling device before this update.

[0124] The preset aging rate threshold can be 0.15. This value is set by the technician and is not limited here. By increasing the lower speed limit, the problem of reduced heat dissipation efficiency of the heat dissipation device caused by current aging can be compensated.

[0125] It should be noted that if the coil aging rate of the heat dissipation device is greater than the preset aging rate threshold, a coil failure warning is triggered.

[0126] In some optional implementations, the above step E3 includes: Step G1: For any heat dissipation device in the heat dissipation assembly, if the magnetic gap imbalance rate of the heat dissipation device is greater than a preset imbalance rate threshold, then based on the twelfth formula, the target rotation speed of the adjacent heat dissipation device of the heat dissipation device is updated. The twelfth formula is:

[0127] in, is the updated target speed of the adjacent heat dissipation device, is the target speed of the adjacent heat dissipation device before updating, is the compensation coefficient, is the rated speed of the adjacent heat dissipation equipment.

[0128] The preset imbalance rate threshold may be 0.4, which is set by technicians and is not specifically limited here. An adjacent heat sink is a heat sink that belongs to the same heat sink array and is located to the left or right or above or below the heat sink.

[0129] The target rotation speed of the adjacent heat dissipation device is updated by the twelfth formula to compensate for the airflow loss of the heat dissipation device. It can be a value between 0.2 and 0.5, which is determined by technicians based on the layout of the heat dissipation device array.

[0130] It is understandable that The target rotational speed of the adjacent heat sink device is obtained using the MPC model when the constraint condition is not added. The constraint condition is that when the magnetic gap imbalance rate of the heat sink device is greater than the preset imbalance rate threshold, the target rotational speed of the adjacent heat sink device of the heat sink device is updated based on the twelfth formula.

[0131] Magnetic gap imbalance causes uneven airflow (increased vibration and 10-20% decrease in air volume). Speed ​​compensation of adjacent heat dissipation devices ensures stable overall heat dissipation and prevents localized heating.

[0132] It should be noted that if the magnetic gap imbalance rate of the heat dissipation device is greater than a preset imbalance rate threshold, a magnetic gap imbalance warning is triggered.

[0133] In some optional implementations, the above step S504 includes: Step H1: If the heat dissipation components corresponding to the first target component and the second target component are the same, then after using the model predictive control model to determine the target speed of the heat dissipation component corresponding to the first target component and the target speed of the heat dissipation component corresponding to the second target component, for any heat dissipation device in the heat dissipation component, according to the target speed of the heat dissipation device corresponding to the first target component and the target speed of the heat dissipation device corresponding to the second target component, determine the higher target speed as the speed to be adjusted of the heat dissipation device, and adjust the heat dissipation device based on the speed to be adjusted of the heat dissipation device.

[0134] In some optional implementations, the heat dissipation component control method further includes: In step I1 , if the current first temperature value of the target component exceeds a preset temperature threshold, the target rotational speeds of the plurality of heat dissipation devices in the heat dissipation assembly corresponding to the target component are determined to be the rated rotational speeds of the plurality of heat dissipation devices.

[0135] The current first temperature value of the target component exceeds the preset temperature threshold, indicating that the target component has approached or reached a critical state that may affect hardware stability.

[0136] It is understandable that if the current first temperature value of the target component does not exceed the preset temperature threshold, the target rotational speeds of the plurality of heat dissipation devices in the heat dissipation assembly are determined according to the contents of step S502 and step S503.

[0137] The heat dissipation component control method provided in the embodiment of the present application can instantly maximize the heat dissipation capacity of the heat dissipation device, quickly reduce the temperature of the target component, block the risk of the target component's temperature continuing to rise, and fundamentally avoid hardware failure or life degradation caused by overheating by directly setting the target speed of multiple heat dissipation devices corresponding to the target component to the rated speed when the current first temperature value of the target component exceeds the preset temperature threshold.

[0138] The embodiment of the present application provides a heat dissipation system. Figure 10 A schematic diagram of the heat dissipation system provided in an embodiment of the present application is shown in FIG. Figure 10 As shown, the heat dissipation system includes a target component, a sensor component, a heat dissipation component and an MCU. The target component, the sensor component and the heat dissipation component are described in the above Figure 3 The description of the illustrated embodiment will not be repeated here. The MCU includes a fault diagnosis module and an MPC controller, wherein an MPC model is run on the MPC controller. Based on the data collected by the sensor component, the MCU uses the MPC model to perform multi-step temperature prediction of the target component, optimizes the target speed of the heat dissipation device using a cost function, and outputs a speed control signal, wherein the speed control signal is a PWM signal, and the time of this process is generally 0.6 seconds. The MCU is also used to input the data collected by the sensor component into the fault diagnosis module after outputting the speed control signal using the MPC model. The fault diagnosis module determines the fault diagnosis information of the heat dissipation device based on the data collected by the sensor component, evaluates the health status of the heat dissipation device based on the fault diagnosis information of the heat dissipation device, issues an early warning, and sends the fault diagnosis information of the heat dissipation device to the MPC controller, so that the MPC controller adjusts the MPC model based on the fault diagnosis information of the heat dissipation device. In the next control cycle, the MPC controller performs multi-step temperature prediction of the target component based on the adjusted MPC model, optimizes the target speed of the heat dissipation device using a cost function, and outputs a speed control signal.

[0139] Figure 11 A flow chart of adjusting the MPC model based on the fault diagnosis information of the heat dissipation device provided in the embodiment of the present application is shown as follows: Figure 11 As shown, within the 0.4 second idle window after the speed control signal is output by the MPC model, the fault diagnosis module performs real-time fault detection based on the data collected by the sensor component to determine the fault diagnosis information of the heat dissipation device.

[0140] Based on the fault diagnosis information of the heat dissipation device, the thermodynamic model in the MPC model is updated, and the target speed constraint condition of the heat dissipation device in the MPC model is updated, so that in the next control cycle, the target speed of the heat dissipation device can be determined using the updated MPC model to perform optimal control.

[0141] It can be understood that updating the thermodynamic model in the MPC model is mainly achieved by updating the average efficiency factor. Figure 12 The update flow chart of the average efficiency factor provided in the embodiment of the present application is as follows: Figure 12 As shown, the process includes: The sensing assembly transmits the current first temperature value of the target component and the current operating status information of the corresponding heat dissipation assembly, i.e., the collected data, to an MPC controller and a fault diagnosis module. The MPC controller first determines the target rotational speeds of the multiple heat dissipation devices in the heat dissipation assembly, and adjusts the heat dissipation devices based on the target rotational speeds of the heat dissipation devices. The fault diagnosis module then calculates the bearing wear rate, coil aging rate, and magnetic gap imbalance rate of the multiple heat dissipation devices in the heat dissipation assembly. Based on the bearing wear rate, coil aging rate, and magnetic gap imbalance rate of the multiple heat dissipation devices in the heat dissipation assembly, the latest average efficiency factor is calculated. The latest average efficiency factor, the bearing wear rate, coil aging rate, and magnetic gap imbalance rate of the multiple heat dissipation devices in the heat dissipation assembly, are then transmitted to the MPC controller. The MPC controller updates a thermodynamic model based on the latest average efficiency factor and updates the target rotational speed constraints of the heat dissipation devices based on the bearing wear rate, coil aging rate, and magnetic gap imbalance rate of the multiple heat dissipation devices in the heat dissipation assembly. In the next control cycle, the MPC controller determines the target rotational speeds of the heat dissipation devices based on the updated thermodynamic model and the target rotational speed constraints of the heat dissipation devices.

[0142] The embodiment of the present application provides a heat dissipation component control method, Figure 13 This is a flow chart of the heat dissipation component control method provided in the embodiment of the present application, such as Figure 13 As shown, the process includes the following steps: Sensor data acquisition: During each control cycle, the sensor component acquires the current first temperature value of the target component and the current operating status of the corresponding heat sink in real time. This data forms the basis of closed-loop control. The temperature sampling rate must reach 1kHz to ensure control accuracy, and the vibration signal sampling rate must be ≥10kHz to capture the bearing's characteristic frequency.

[0143] Information Preprocessing: To ensure that the sensor data meets real-time requirements and a high signal-to-noise ratio, the collected information undergoes signal preprocessing. For details, refer to the descriptions of steps B1, C1, and D1 above and are omitted here. For temperature values, such as those of the target component and the coil temperature of the heat sink, a first-order lag filter is used to eliminate transient noise and ensure stable temperature inputs to the MPC controller, suitable for thermodynamic model calculations.

[0144] The MPC controller determines the target rotational speed of the heat dissipation device by predicting the second temperature value of the target component in multiple future time steps based on the current first temperature value of the target component after information preprocessing and the current operating status information of the corresponding heat dissipation assembly. Based on the second temperature value of the target component in multiple future time steps, the target rotational speed of multiple heat dissipation devices in the heat dissipation assembly is determined.

[0145] The MPC controller adjusts the heat dissipation device: based on the target speed of the heat dissipation device, it outputs a control signal and adjusts the heat dissipation device based on the control signal.

[0146] The fault diagnosis module determines the fault diagnosis information of the heat dissipation device: based on the current operating status information of the heat dissipation component after information preprocessing, fault feature extraction is performed to obtain the magnetic gap imbalance rate, coil aging rate and bearing wear rate of multiple heat dissipation devices in the heat dissipation component.

[0147] The fault diagnosis module determines an average efficiency factor: based on a magnetic gap imbalance rate, a coil aging rate, and a bearing wear rate of the multiple heat dissipation devices in the heat dissipation assembly, the average efficiency factor of the multiple heat dissipation devices in the heat dissipation assembly is determined.

[0148] The MPC controller updates the MPC model: It updates the thermodynamic model based on the average efficiency factor and updates the target speed constraints for the heat sinks based on the magnetic gap imbalance rate, coil aging rate, and bearing wear rate of the multiple heat sinks in the heat sink assembly.

[0149] The heat dissipation assembly control method provided in the embodiments of the present application uses a model predictive control model to predict temperature and determine the target speed of the heat dissipation assembly, thereby shortening response time and enabling timely adjustment of the heat dissipation device. By using the current operating status information of the heat dissipation assembly to adjust the control model, the adjusted control model is used to control the heat dissipation assembly speed during the next control cycle, thereby improving the adjustment accuracy of the heat dissipation assembly and thereby enhancing the reliability of the electronic device.

[0150] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method.

[0151] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above-mentioned heat dissipation component control method embodiments when running.

[0152] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0153] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of any of the above-mentioned heat dissipation component control method embodiments are implemented.

[0154] An embodiment of the present application also provides another computer program product, including a non-volatile computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of any of the above-mentioned heat dissipation component control method embodiments.

[0155] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0156] The above is a detailed introduction to a heat dissipation component control method, heat dissipation system and electronic device provided by the present application. This article uses specific examples to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core ideas. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

Claims

1. A heat dissipation component control method, characterized in that: include: In each control cycle, obtaining a current first temperature value of the target component and current operating state information of the corresponding heat dissipation component; Based on the first temperature value and the current operating state information, using a control model to predict a second temperature value of the target component at multiple future time steps; determining a target rotational speed of the heat dissipation component based on the second temperature value; adjusting the heat dissipation component based on the target speed; Determining fault diagnosis information of the heat dissipation component based on the current operating state information; The control model is adjusted based on the fault diagnosis information.

2. The method according to claim 1, characterized in that The current operating state information includes a current rotational speed, the control model includes a thermodynamic model and a temperature prediction model, the heat dissipation assembly includes a plurality of heat dissipation devices, and predicting a second temperature value of the target component at a plurality of future time steps using the control model based on the first temperature value and the current operating state information includes: determining an average rotational speed of the plurality of heat dissipation devices in the heat dissipation assembly based on current rotational speeds of the plurality of heat dissipation devices; The temperature change rate of the target component is determined based on a thermodynamic model, wherein the thermodynamic model is: dT / dt = a·(P heat - η·k·rpm^3) / (M·c p ) Wherein, dT / dt is the temperature change rate of the target component, a is the heat exchange coefficient of the target component in the previous control cycle, P heat is the current power of the target component, η is the average efficiency factor of the multiple heat dissipation devices in the previous control cycle, k is the startup constant of the heat dissipation device, rpm is the average speed of the multiple heat dissipation devices, M is the heat capacity of the radiator, c p is the specific heat capacity of air; Based on a temperature prediction model, a second temperature value of the target component in a plurality of future time steps is predicted, wherein the temperature prediction model is: in, is the second temperature value of the target component in the future i-th time step, is the first temperature value, is the time step.

3. The method according to claim 1, characterized in that The heat dissipation component includes a plurality of heat dissipation devices, and determining the target rotation speed of the heat dissipation component based on the second temperature value includes: With the goal of minimizing a calculation result of a cost function, based on the constraint conditions of the target rotation speeds of the multiple heat dissipating devices and the second temperature value, a target rotation speed prediction value for each of the multiple heat dissipating devices in multiple future time steps is determined, wherein the cost function is: in, is the calculation result of the cost function, N is the number of predicted time steps, and is the weight coefficient, is the second temperature value of the target component in the future i-th time step, is the reference temperature threshold of the target component, A predicted value of a target rotation speed of the j-th heat dissipation device among the multiple heat dissipation devices at the i-th time step in the future; The target rotation speed constraints of the multiple heat dissipation devices are: in, is the lower limit of the speed of the j-th heat dissipation device, is the upper limit of the speed of the j-th heat dissipation device; Based on the target speed prediction values ​​of each heat dissipation device in multiple future time steps, the target speed prediction value of each heat dissipation device in the first future time step is determined as the target speed of the heat dissipation device.

4. The method according to claim 1, wherein The current operating state information includes a current bearing vibration signal and a current rotational speed, the fault diagnosis information includes a bearing wear rate, the heat dissipation assembly includes a plurality of heat dissipation devices, and determining the fault diagnosis information of the heat dissipation assembly based on the current operating state information includes: For any heat dissipation device in the heat dissipation assembly, amplify, filter, analog-to-digital convert, and fast Fourier transform the current bearing vibration signal of the heat dissipation device to obtain a bearing frequency domain vibration signal in a target characteristic frequency band; Based on the first formula, the energy integral value of the bearing frequency domain vibration signal in the target characteristic frequency band is determined. The first formula is: Among them, E measured is the energy integral value of the bearing frequency domain vibration signal in the target characteristic frequency band, X(P) is the bearing frequency domain vibration signal at the Pth frequency point in the target characteristic frequency band, and f min is the lower limit of the target characteristic frequency band, f max is the upper limit of the target characteristic frequency band; Based on the second formula, the warning energy threshold of the bearing frequency domain vibration signal in the target characteristic frequency band is determined. The second formula is: E threshold =Baseline energy × [0.8 + 0.4 × (current speed of the heat sink / rated speed of the heat sink)] Among them, E threshold is the warning energy threshold of the bearing frequency domain vibration signal in the target characteristic frequency band, and the baseline energy is the reference energy value of the bearing frequency domain vibration signal in the target characteristic frequency band of the heat dissipation device in a healthy state; The bearing wear rate of the heat dissipation device is determined based on a third formula, which is: α = min(1,(E measured -E threshold ) / E range ) Among them, α is the bearing wear rate of the heat dissipation device, E range It is the effective wear energy range span of the heat dissipation device.

5. The method according to claim 1, wherein The current operating state information includes a current motor current signal and a current coil temperature value, the fault diagnosis information includes a coil aging rate, the heat dissipation assembly includes a plurality of heat dissipation devices, and determining the fault diagnosis information of the heat dissipation assembly based on the current operating state information includes: For any heat dissipation device in the heat dissipation assembly, amplify and perform analog-to-digital conversion on the current motor current signal of the heat dissipation device to obtain the motor current value to be corrected; The target motor current value is determined based on the temperature compensation model, which is: I comp = I meas × (1 + b·(T now - T cold )) Among them, I comp is the target motor current value, I meas is the motor current value to be corrected, b is the coil temperature coefficient, T now is the current coil temperature value, T cold is the coil reference temperature value; The coil aging rate of the heat dissipation device is determined based on the fourth formula, which is: β= max(0,(I cold - I comp ) / I cold ) Among them, β is the coil aging rate of the heat dissipation device, I cold is the motor reference current value.

6. The method according to claim 1, characterized in that The current operating state information includes a current vibration signal of a rotating plane, the fault diagnosis information includes a magnetic gap unbalance rate, the heat dissipation assembly includes a plurality of heat dissipation devices, and determining the fault diagnosis information of the heat dissipation assembly based on the current operating state information includes: For any heat dissipation device in the heat dissipation assembly, filtering, amplifying, and analog-to-digital conversion are performed on a current vibration signal of a rotation plane of the heat dissipation device to obtain a target vibration signal of the rotation plane; The peak-to-peak value of the X-axis vibration and the peak-to-peak value of the Y-axis vibration of the heat dissipation device are determined based on the fifth formula, which is: X pp = max(x(t)) - min(x(t)) Y pp = max(y(t)) - min(y(t)) Among them, X pp is the peak-to-peak value of the X-axis vibration, Y pp is the peak-to-peak value of the Y-axis vibration, x(t) is the target vibration signal of the X-axis, y(t) is the target vibration signal of the Y-axis, and the target vibration signal of the rotating plane includes the target vibration signal of the X-axis and the target vibration signal of the Y-axis; The magnetic gap unbalance rate of the heat dissipation device is determined based on the sixth formula, which is: γ = | X pp - AND pp | / (( X pp + And pp ) / 2) Where γ is the magnetic gap unbalance ratio of the heat dissipation device.

7. The method according to claim 1, characterized in that The heat dissipation assembly includes a plurality of heat dissipation devices, and adjusting the control model based on the fault diagnosis information includes: determining, based on the fault diagnosis information of the plurality of heat dissipation devices, an average efficiency factor of a current control period of the plurality of heat dissipation devices; updating a thermodynamic model based on average efficiency factors of the plurality of heat dissipation devices during a current control period; updating, based on the fault diagnosis information of the plurality of heat dissipation devices, constraints on the target rotational speeds of the plurality of heat dissipation devices and / or determining compensation values ​​for second temperature values ​​of the target component at a plurality of future time steps, so as to determine, in a next control cycle, the target rotational speeds of the plurality of heat dissipation devices based on the updated thermodynamic model, the updated constraints on the target rotational speeds of the plurality of heat dissipation devices and / or the compensation values ​​for the second temperature values ​​of the target component at a plurality of future time steps; The control model includes a thermodynamic model and constraint conditions of target rotation speeds of the plurality of heat dissipation devices.

8. The method according to claim 7, characterized in that The determining, based on the fault diagnosis information of the plurality of heat dissipation devices, an average efficiency factor of a current control period of the plurality of heat dissipation devices comprises: For any heat dissipation device among the plurality of heat dissipation devices, an efficiency factor of a current control cycle of the heat dissipation device is determined based on a seventh formula, where the seventh formula is: = η0 × [1 - q1×α - q2×β - q3×γ] in, 1 is the efficiency factor of the current control cycle of the heat dissipation device, η0 is the initial efficiency factor of the heat dissipation device, α is the bearing wear rate of the heat dissipation device, β is the coil aging rate of the heat dissipation device, γ is the magnetic gap imbalance rate of the heat dissipation device, q1, q2 and q3 are fault sensitivity coefficients; An average efficiency factor of the current control period of the plurality of heat dissipating devices is determined based on the efficiency factor of the current control period of each heat dissipating device in the plurality of heat dissipating devices.

9. The method according to claim 7, characterized in that The updating of the thermodynamic model based on the average efficiency factors of the current control periods of the plurality of heat dissipation devices includes: The heat exchange coefficient of the target component in the current control cycle is determined based on the eighth formula, which is: a new = a + R×(η new -or) Among them, a new is the heat exchange coefficient of the current control cycle of the target component, a is the heat exchange coefficient of the previous control cycle of the target component, R is the adjustment coefficient, η new is the average efficiency factor of the current control cycle of the plurality of heat dissipation devices, and η is the average efficiency factor of the previous control cycle of the plurality of heat dissipation devices; The thermodynamic model is updated based on the average efficiency factors of the plurality of heat dissipation devices in the current control period and the heat exchange coefficient of the target component in the current control period.

10. The method according to claim 7, characterized in that The fault diagnosis information includes a bearing wear rate. Updating the constraint conditions of the target rotational speeds of the plurality of heat dissipating devices and / or determining compensation values ​​of second temperature values ​​of the target component at a plurality of future time steps based on the fault diagnosis information of the plurality of heat dissipating devices includes: For any heat dissipation device in the heat dissipation assembly, if the bearing wear rate of the heat dissipation device is greater than the preset wear rate threshold, the upper speed limit of the heat dissipation device is updated based on the ninth formula, which is: max_rpm new =max_ rpm old × (1-0.8×the bearing wear rate of the heat dissipation device) Among them, max_ rpm new The upper limit of the speed of the cooling device after this update, max_ rpm old This is the upper limit of the speed of the cooling device before this update; determining an average bearing wear rate of the plurality of heat dissipation devices based on a bearing wear rate of each heat dissipation device in the plurality of heat dissipation devices; Based on the tenth formula, the compensation value of the second temperature value of the target component in multiple future time steps is determined. The tenth formula is: T offset = 1.5×average bearing wear rate of the multiple heat dissipation devices Among them, T offset The compensation value is a second temperature value of the target component at a future plurality of time steps.

11. The method according to claim 7, characterized in that The fault diagnosis information includes a coil aging rate. Updating the constraint conditions of the target rotational speeds of the plurality of heat dissipating devices and / or determining compensation values ​​of second temperature values ​​of the target component at a plurality of future time steps based on the fault diagnosis information of the plurality of heat dissipating devices includes: For any heat dissipation device in the heat dissipation assembly, if the coil aging rate of the heat dissipation device is greater than the preset aging rate threshold, the lower speed limit of the heat dissipation device is updated based on the eleventh formula, and the eleventh formula is: min_rpm new =min_rpm old × (1 + 0.5 × the aging rate of the coil of the heat sink) Among them, min_rpm new The lower limit of the speed of the cooling device after this update, min_rpm old This is the lower speed limit of the cooling device before this update.

12. The method according to claim 7, characterized in that The fault diagnosis information includes a magnetic gap unbalance rate, and updating the constraint conditions of the target rotation speeds of the plurality of heat dissipating devices and / or determining compensation values ​​of second temperature values ​​of the target component at a plurality of future time steps based on the fault diagnosis information of the plurality of heat dissipating devices includes: For any heat dissipation device in the heat dissipation assembly, if the magnetic gap imbalance rate of the heat dissipation device is greater than the preset imbalance rate threshold, the target rotational speed of the adjacent heat dissipation device of the heat dissipation device is updated based on the twelfth formula, and the twelfth formula is: in, is the updated target speed of the adjacent heat dissipation device, is the target speed of the adjacent heat dissipation device before updating, is the compensation coefficient, is the rated speed of the adjacent heat dissipation equipment.

13. A heat dissipation system, characterized in that: include: Target component, heat dissipation component, sensor component and heat dissipation component control equipment; The heat dissipation component is used to dissipate heat for the target component during operation of the target component; The sensing component is used to collect the current first temperature value of the target component and the current operating state information of the corresponding heat dissipation component in each control cycle, and send the current first temperature value of the target component and the current operating state information of the corresponding heat dissipation component to the heat dissipation component control device; The heat dissipation component control device is used to control the speed of the heat dissipation component using a control model based on the current first temperature value of the target component and the current operating status information corresponding to the heat dissipation component in each control cycle; and adjust the control model based on the current operating status information of the heat dissipation component.

14. The system according to claim 13, wherein: The input end of the sensing component is connected to the target component and the heat dissipation component; The output end of the sensor component is connected to the heat dissipation component control device; The air outlet of the heat dissipation component is arranged corresponding to the target component; The heat dissipation assembly includes a plurality of heat dissipation devices; The target component includes at least a central processing unit, a graphics processor and a memory module; The sensor assembly includes a temperature sensor, a rotation speed sensor, a vibration sensor and a current sensor.

15. An electronic device, characterized in that: include: The heat dissipation system according to any one of claims 13 to 14.

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