A control device for a motor cooling system based on multi-parameter linkage

Abstract

The present invention discloses a control device for a motor cooling system based on multi-parameter linkage, which relates to the technical field of data processing and includes: an acquisition module for acquiring the first ambient temperature and the first motor speed and acquiring the first parameter; a first processing and calculation module for acquiring the first interval time period, acquiring the second moment, acquiring the second motor speed, and acquiring the first prediction index; a first control and regulation module for acquiring the first water pump regulation signal, acquiring the first motor temperature and the second ambient temperature, and acquiring the second parameter; a second processing and calculation module for acquiring the second interval time period, acquiring the third moment, acquiring the second motor temperature, and acquiring the second prediction index; a second control and regulation module for correcting and generating the second water pump regulation signal and regulating the water pump output according to the second water pump regulation signal. The present invention has the advantages of predictability, dynamic regulation, and stability and reliability.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to a motor cooling system control device based on multi-parameter linkage. Background Art

[0002] With the continuous advancement of motor technology and the increasing expansion of its application fields, the heat dissipation problem of motors during operation has become increasingly prominent. The motor will generate a lot of heat when working. If the heat is not dissipated in time, it will seriously affect the working efficiency and service life of the motor, and may even cause damage to the motor or cause a safety accident. Therefore, the effective control of the motor cooling system has become a key issue that needs to be urgently solved in the field of motor technology. Traditional motor cooling systems mostly use fixed cooling strategies, such as fixed-speed water pumps or fans, and their output is usually adjusted according to the rated power of the motor or a preset temperature threshold. However, this fixed cooling strategy cannot adapt to changes in the actual working state and environmental conditions of the motor, resulting in poor cooling effect or energy waste.

[0003] In order to improve the shortcomings of traditional cooling systems, many intelligent cooling systems based on sensors and controllers have emerged in recent years. These systems can monitor key parameters such as motor temperature and speed in real time, and adjust the output of water pumps or fans according to these parameters to achieve more precise heat dissipation control. However, the existing intelligent cooling systems still have some limitations. On the one hand, most of the existing intelligent cooling systems only consider a single or a few parameters for adjustment, ignoring the comprehensive influence of multiple factors such as ambient temperature, motor speed, and water pump working efficiency on the heat dissipation effect. In fact, the heat dissipation effect of the motor is a complex process of multi-factor coupling, which requires comprehensive consideration of the changes and interactions of multiple parameters. On the other hand, the existing intelligent cooling system lacks dynamics and foresight in the adjustment process. Usually, it makes corresponding adjustments only after the motor temperature or speed changes, and cannot predict and adapt to these changes in advance, which leads to a delayed response of the cooling system and the inability to effectively control the temperature of the motor in a timely manner. Summary of the invention

[0004] In view of the defects in the prior art, the present invention provides a motor cooling system control device based on multi-parameter linkage.

[0005] A control device for a motor cooling system based on multi-parameter linkage, comprising: an acquisition module for acquiring a first ambient temperature and a first motor speed at a first moment, and acquiring a first parameter according to the first ambient temperature; a first processing and calculation module for acquiring a first interval period according to the first parameter, acquiring a second moment separated from the first moment by the first interval period, acquiring a second motor speed at the second moment, and acquiring a first prediction index based on a prediction model, the first motor speed, the second motor speed and the first parameter; a first control and adjustment module for acquiring a first water pump adjustment signal according to the first prediction index, adjusting the water pump output according to the first water pump adjustment signal, acquiring a first motor temperature and a second ambient temperature at the water pump output time point, and acquiring a second parameter according to the second ambient temperature; a second processing and calculation module for acquiring a second interval period according to the second parameter, acquiring a third moment separated from the water pump output time point by the second interval period, acquiring a second motor temperature at the third moment, and acquiring a second prediction index based on a feedback model, the first motor temperature, the second motor temperature and the second parameter; a second control and adjustment module for correcting the first water pump adjustment signal according to the second prediction index and generating a second water pump adjustment signal, and adjusting the water pump output according to the second water pump adjustment signal.

[0006] Optionally, the first processing and calculation module is further configured to: acquire a proportionality coefficient; acquire the first interval period according to the proportionality coefficient and the first parameter.

[0007] Optionally, the second processing and calculation module is further configured to: acquire a proportionality coefficient; acquire the second interval period according to the proportionality coefficient and the second parameter.

[0008] Optionally, the device further comprises a correction module, and the correction module is configured to: acquire a difference parameter according to the second prediction index and the first prediction index; correct the original proportionality coefficient according to the difference parameter and acquire a new proportionality coefficient, wherein the new proportionality coefficient is used to replace the original proportionality coefficient in the subsequent operations of the first processing and calculation module and the second processing and calculation module.

[0009] Optionally, acquiring the difference parameter according to the second prediction index and the first prediction index is expressed as: ; wherein, is the difference parameter, is the first prediction index, is the second prediction index.

[0010] Optionally, correcting the original proportionality coefficient according to the difference parameter and acquiring the new proportionality coefficient is expressed as: ; wherein, is the new proportionality coefficient, is the original proportionality coefficient.

[0011] Optionally, obtaining the first interval time period according to the proportionality coefficient and the first parameter is expressed as: ; where is the first interval time period, is the first parameter, is the proportionality coefficient.

[0012] Optionally, obtaining the first parameter according to the first ambient temperature is expressed as: ; where is the first parameter, is the first ambient temperature, is the preset temperature.

[0013] Optionally, the prediction model in the first prediction index obtained based on the prediction model, the first motor speed, the second motor speed, and the first parameter is expressed as: ; where is the first prediction index, is the first parameter, is the first motor speed, is the second motor speed, is the maximum motor speed, is the first influence coefficient, is the standard cooling index.

[0014] Optionally, the feedback model in the second prediction index obtained based on the feedback model, the first motor temperature, the second motor temperature, and the second parameter is expressed as: ; where is the second prediction index, is the second parameter, is the first motor temperature, is the second motor temperature, is the standard motor temperature, is the second influence coefficient, is the standard cooling index.

[0015] The beneficial effects of the present invention are reflected in:

[0016] In the entire control device of the motor cooling system based on multi-parameter linkage, first, the acquisition module captures the initial environmental data and motor status information during operation in real time, such as the first environmental temperature and the first motor speed, and obtains the first parameter according to the first environmental temperature. This first parameter, as a quantitative index of the influence of environmental temperature on the cooling efficiency, provides basic data support for subsequent calculations and predictions, making the adjustment of the cooling system more in line with the actual environmental conditions. Secondly, the first processing and calculation module calculates the first interval time period using the first parameter, obtains the second motor speed at the second moment, and calculates the first prediction index in combination with the prediction model. This index represents the trend of motor temperature change, provides an accurate adjustment signal for the first control and adjustment module, enables the output of the water pump to adapt to the change of motor temperature in advance, and enhances the predictability of the cooling system. Furthermore, the second processing and calculation module calculates the second interval time period according to the second parameter obtained by the first control and adjustment module. This second parameter reflects the possible influence of the environmental conditions on the cooling efficiency after the water pump is adjusted, obtains the second motor temperature at the third moment, and calculates the second prediction index in combination with the feedback model. This index provides a basis for the second control and adjustment module to correct the output of the water pump, making the adjustment of the cooling system more precise and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0018] Figure 1 It is a partial composition schematic diagram of the control device of the motor cooling system based on multi-parameter linkage of the present invention.

[0019] Figure 2 It is a composition schematic diagram of the control device of the motor cooling system based on multi-parameter linkage of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0021] Accordingly, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0022] It should be noted that like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not require further definition and explanation in subsequent drawings. In addition, the terms "first", "second", etc. are only used for descriptive distinction and should not be construed as indicating or implying relative importance.

[0023] As Figure 1 shown, a control device for a motor cooling system based on multi-parameter linkage is provided, including:

[0024] An acquisition module, configured to acquire a first ambient temperature and a first motor speed at a first moment, and acquire a first parameter according to the first ambient temperature;

[0025] A first processing and calculation module, configured to acquire a first interval period according to the first parameter, acquire a second moment separated from the first moment by the first interval period, acquire a second motor speed at the second moment, and acquire a first prediction index based on a prediction model, the first motor speed, the second motor speed, and the first parameter;

[0026] A first control and adjustment module, configured to acquire a first water pump adjustment signal according to the first prediction index, adjust the water pump output according to the first water pump adjustment signal, acquire a first motor temperature and a second ambient temperature at the water pump output time point, and acquire a second parameter according to the second ambient temperature;

[0027] A second processing and calculation module, configured to acquire a second interval period according to the second parameter, acquire a third moment separated from the water pump output time point by the second interval period, acquire a second motor temperature at the third moment, and acquire a second prediction index based on a feedback model, the first motor temperature, the second motor temperature, and the second parameter;

[0028] A second control and adjustment module, configured to correct the first water pump adjustment signal according to the second prediction index and generate a second water pump adjustment signal, and adjust the water pump output according to the second water pump adjustment signal.

[0029] In this embodiment, it should be noted that in the acquisition module, the initial environmental data and motor state information during operation are accurately captured. Specifically, at the first moment, the acquisition module accurately obtains the current environmental temperature through the built-in sensor or external data interface, which is called the first environmental temperature. At the same time, it also monitors the motor speed in real time and records the motor speed at this moment, which is called the first motor speed. The acquisition module not only satisfies collecting these raw data, but further obtains a first parameter associated with the environmental temperature according to the first environmental temperature through a preset algorithm or by looking up the corresponding parameter table. This first parameter may be a quantitative index of the impact of environmental temperature on cooling efficiency, or a reference value for subsequent calculation of time intervals, providing basic data support for dynamic adjustment.

[0030] For example, the acquisition module accurately measures the current environmental temperature through the environmental temperature sensor installed on the vehicle, which is called the first environmental temperature; at the same time, the acquisition module also uses the motor speed sensor to monitor the motor speed in real time and records the motor speed at this moment, that is, the first motor speed. In addition, the acquisition module also obtains a first parameter closely related to the current environmental temperature according to the first environmental temperature; this first parameter is a key factor for predicting the future heat dissipation requirements of the motor, and it can represent the cooling requirements of the motor or the time point of cooling intervention at the current environmental temperature.

[0031] In the first processing and calculation module, a series of complex calculations and predictions are carried out based on the initial data provided by the acquisition module, providing a decision-making basis for subsequent cooling adjustment. Specifically, the first processing and calculation module first receives the first parameter transmitted by the acquisition module. This parameter is obtained through a preset algorithm or parameter table based on the first environmental temperature, reflecting the possible impact of environmental temperature on cooling efficiency. Then, the first processing and calculation module uses this first parameter and combines it with the built-in proportionality coefficient to calculate the first interval time period. This time period determines when to obtain data such as motor speed again for the next prediction and adjustment. After the end of the first interval time period, the first processing and calculation module obtains the second motor speed at the second moment, and combines the first motor speed, the prediction model, and the first parameter to calculate the first prediction index. This first prediction index represents the trend of motor temperature change and directly determines the water pump output that needs to be adjusted for cooling, that is, providing an accurate adjustment signal for the first control and adjustment module.

[0032] Taking a new energy vehicle as an example, the working process of the first processing and calculation module can be described as follows: Suppose that during the vehicle's driving, the acquisition module has measured that the current ambient temperature is 30 degrees Celsius and the motor speed is 1500 revolutions per minute, and a first parameter related to the ambient temperature is obtained accordingly. After receiving this first parameter, the first processing and calculation module will calculate the first interval time period as 30 seconds according to the built-in proportionality coefficient (for example, for every 5-degree Celsius increase in ambient temperature, the interval time period is shortened by 10 seconds). After 30 seconds, that is, at the second moment, the first processing and calculation module acquires the motor speed again. Suppose the motor speed has increased at this time and is 1800 revolutions per minute. Then, the first processing and calculation module will use the prediction model, combine the first motor speed, the second motor speed, and the first parameter, and calculate a first prediction index. For example, if the first prediction index is relatively large, it means that it is predicted that the temperature may increase rapidly due to the increase in motor speed in the next period of time. This prediction index is then transmitted to the first control and adjustment module to adjust the output of the water pump to cope with the rising motor temperature in advance and ensure that the motor always operates within the optimal working temperature range.

[0033] In the first control and adjustment module, according to the prediction index provided by the first processing and calculation module, a corresponding water pump adjustment signal is generated and the output of the water pump is adjusted in real time to ensure that the motor temperature is effectively controlled. Specifically, after receiving the first prediction index transmitted by the first processing and calculation module, the first control and adjustment module will immediately interpret this index. The first prediction index represents the trend of motor temperature change, and in order to maintain the motor within the optimal working temperature range, based on this prediction index, the first control and adjustment module will generate an accurate first water pump adjustment signal, which contains the specific parameters that the water pump needs to adjust, such as speed, flow rate, etc., to meet the required output adjustment of the water pump. Subsequently, the first control and adjustment module will send this adjustment signal to the water pump controller, instructing the water pump to make adjustments according to the predetermined parameters. At the same time, after the water pump starts to operate according to the new adjustment signal, that is, at the water pump output time point, the first control and adjustment module will also obtain the first motor temperature and the second ambient temperature through the corresponding sensors. The acquisition of the second ambient temperature is to obtain a second parameter related to the ambient temperature according to the current environmental conditions through a preset algorithm or parameter table. This second parameter will be used for further calculations and predictions in the subsequent second processing and calculation module.

[0034] Taking a new energy vehicle as an example, assume that the first processing and calculation module has predicted that the motor temperature may rise rapidly in the next period of time based on parameters such as the ambient temperature and motor speed, and has calculated a relatively large first prediction index accordingly. After receiving this prediction index, the first control and regulation module will immediately generate a corresponding water pump regulation signal, such as increasing the water pump speed by 20%, to increase the flow rate of the cooling system and cope with the rise of the motor temperature in advance. Subsequently, the water pump controller adjusts the output of the water pump according to this regulation signal and starts to operate at a higher speed. When the water pump operates according to the new regulation signal, that is, at the water pump output time point, the first control and regulation module will obtain the first motor temperature and the second ambient temperature at this time through the temperature sensor installed on the vehicle. At this time, the first motor temperature is 35 degrees Celsius, and the second ambient temperature has also changed, rising from 30 degrees Celsius to 30.5 degrees Celsius. The first control and regulation module will obtain a second parameter associated with the current ambient temperature through a preset algorithm or parameter table according to this new ambient temperature, providing necessary data support for the subsequent second processing and calculation module to carry out further cooling system regulation and optimization.

[0035] In the second processing and calculation module, it is responsible for further calculation and prediction according to the actual feedback situation after the water pump is regulated to optimize the cooling control strategy. Specifically, the second processing and calculation module will first receive the second parameter obtained by the first control and regulation module. This second parameter reflects the possible impact of the current ambient condition on the cooling efficiency and is the basis for subsequent calculations. Then, the second processing and calculation module will use this second parameter and combine it with the built-in proportionality coefficient to calculate the second interval time period. This time period determines when to obtain data such as the motor temperature again for the next feedback and regulation. After the end of the second interval time period, the second processing and calculation module will obtain the second motor temperature at the third moment and calculate the second prediction index in combination with the first motor temperature, the feedback model, and the second parameter. This second prediction index reflects the actual change of the motor temperature after the water pump is regulated and whether it is necessary to further adjust the water pump output to maintain the motor within the optimal operating temperature range.

[0036] Taking a new energy vehicle as an example, assume that after the water pump operates for a period of time according to the adjustment signal generated by the first control adjustment module, that is, at the water pump output time point, the first control adjustment module has obtained the first motor temperature of 35 degrees Celsius and the second ambient temperature of 30.5 degrees Celsius at this time, and thus obtained a second parameter related to the ambient temperature. After receiving this second parameter, the second processing and calculation module will calculate the second interval time period of 25 seconds according to the built-in proportionality coefficient (for example, for every 0.5 degree Celsius increase in ambient temperature, the interval time period is shortened by 5 seconds). 25 seconds later, that is, at the third moment, the second processing and calculation module obtains the motor temperature again. Assume that the motor temperature has decreased at this time, to 33 degrees Celsius. Then, the second processing and calculation module will use the feedback model, combined with the first motor temperature, the second motor temperature, and the second parameter, to calculate the second prediction index. If the second prediction index indicates that the current water pump output is sufficient to meet the heat dissipation requirements of the motor and may even cause the motor temperature to be too low, then the second processing and calculation module will generate a corresponding signal for the subsequent second control adjustment module to adjust the water pump output to ensure that the motor always operates within the optimal working temperature range while avoiding energy waste.

[0037] In the second control adjustment module, according to the second prediction index provided by the second processing and calculation module, the output of the water pump is finely adjusted to ensure that the motor temperature is always maintained within the optimal working range. Specifically, the second control adjustment module will receive the second prediction index transmitted by the second processing and calculation module. This index is calculated through the feedback model based on the actual feedback situation after the water pump adjustment, reflecting the actual change in the motor temperature and the possible future trend. The second control adjustment module will conduct an in-depth analysis of this index to determine whether the current water pump output meets the heat dissipation requirements of the motor. If the second prediction index shows that the current water pump output is too high, which may cause the motor temperature to be too low and result in energy waste; or the water pump output is too low and cannot effectively control the increase in the motor temperature, then the second control adjustment module will generate a corresponding correction signal based on this index, that is, the second water pump adjustment signal. This second water pump adjustment signal will precisely adjust parameters such as the rotation speed and flow rate of the water pump based on the deviation between the second prediction index and the ideal heat dissipation state to meet the actual heat dissipation requirements of the motor. Subsequently, the second control adjustment module will send this corrected water pump adjustment signal to the water pump controller, instructing the water pump to make adjustments according to the new parameters, thereby achieving precise control of the motor temperature.

[0038] Taking a new energy vehicle as an example, assume that after a series of calculations and predictions are performed in the second processing and calculation module, a second prediction index is obtained, indicating that the output of the current water pump is too high, resulting in a downward trend in the motor temperature, which may be lower than the optimal operating temperature range. After receiving this prediction index, the second control and adjustment module will immediately generate a corresponding correction signal, such as reducing the water pump speed by 10% to reduce the cooling flow rate and prevent the motor temperature from being too low. Subsequently, the water pump controller adjusts the output of the water pump according to this corrected adjustment signal and starts to operate at a lower speed.

[0039] In summary, in the entire motor cooling system control device based on multi-parameter linkage, first, the acquisition module captures the initial environmental data and motor state information during the operation in real time, such as the first environmental temperature and the first motor speed, and obtains the first parameter according to the first environmental temperature. This first parameter, as a quantitative index of the influence of environmental temperature on cooling efficiency, provides basic data support for subsequent calculations and predictions, making the adjustment of the cooling system more in line with the actual environmental conditions. Secondly, the first processing and calculation module calculates the first time interval using the first parameter, obtains the second motor speed at the second moment, and calculates the first prediction index in combination with the prediction model. This index represents the trend of motor temperature change and provides an accurate adjustment signal for the first control and adjustment module, enabling the output of the water pump to adapt to the change of motor temperature in advance and enhancing the predictability of the cooling system. Furthermore, the second processing and calculation module calculates the second time interval according to the second parameter obtained by the first control and adjustment module. This second parameter reflects the possible influence of the environmental conditions on the cooling efficiency after the water pump adjustment, obtains the second motor temperature at the third moment, and calculates the second prediction index in combination with the feedback model. This index provides a basis for the second control and adjustment module to correct the water pump output, making the adjustment of the cooling system more refined and accurate.

[0040] In one embodiment, the first processing and calculation module is further configured to:

[0041] Obtain a proportionality coefficient;

[0042] Obtain the first time interval according to the proportionality coefficient and the first parameter.

[0043] In this embodiment, it should be noted that in the entire first processing and calculation module, a proportionality coefficient will be obtained first. This proportionality coefficient is a preset value, which is determined according to the design requirements of the entire motor system and the actual application scenario, and represents the linear relationship between the environmental temperature change and the data acquisition time interval. For example, based on historical data, the motor model, experimental data or experience, a proportionality coefficient can be selected so that when the environmental temperature rises by a certain value, the data acquisition time interval will be correspondingly shortened to monitor the motor state more frequently, so as to respond to possible temperature changes and cooling requirements more timely.

[0044] After obtaining the proportionality coefficient, the first processing and calculation module uses this coefficient and the first parameter transmitted from the acquisition module to jointly calculate the first interval time period. The first parameter is obtained through a preset algorithm or parameter table based on the first environmental temperature, and it reflects the potential impact of the current environmental temperature on the cooling efficiency or the change in the motor temperature. The first processing and calculation module combines the proportionality coefficient with the first parameter and, through certain mathematical operations, obtains the specific value of the first interval time period. This time period determines when the system will obtain data such as the motor speed again for the next prediction and adjustment.

[0045] For example, if the proportionality coefficient is set such that for every 5-degree Celsius increase in the environmental temperature, the interval time period is shortened by 10 seconds, and the first parameter indicates that the current environmental temperature is 10 degrees Celsius higher than the reference temperature, then the first processing and calculation module will, based on this proportionality coefficient and the first parameter, calculate that the first interval time period is shortened by 20 seconds compared to the default time, so as to respond more quickly to possible changes in the motor temperature and ensure that the cooling system can work in a timely and effective manner.

[0046] In one embodiment, the second processing and calculation module is further configured to:

[0047] Obtain the proportionality coefficient;

[0048] Obtain the second interval time period according to the proportionality coefficient and the second parameter.

[0049] In this embodiment, it should be noted that in the entire second processing and calculation module, the differences from the first processing and calculation module include that the second processing and calculation module performs calculations and predictions based on the actual feedback situation after the water pump is adjusted. Specifically, the second processing and calculation module first obtains a preset proportionality coefficient, which is the same as the proportionality coefficient in the first processing and calculation module and is also determined according to the design characteristics of the motor system and the actual application requirements. After obtaining the proportionality coefficient, the second processing and calculation module combines the second parameter transmitted from the first control and adjustment module to calculate the second interval time period. This second parameter is the second environmental temperature obtained based on the water pump output time point and is obtained through a preset algorithm or parameter table, and it reflects the new impact of the current environmental condition on the cooling efficiency after the water pump is adjusted. Different from the first processing and calculation module, the second interval time period obtained by the comprehensive operation of the proportionality coefficient and the second parameter by the second processing and calculation module is more in line with the actual heat dissipation requirements after the water pump is adjusted, enabling the system to obtain data such as the motor temperature again at a more appropriate time point for the next feedback and fine adjustment, so as to ensure that the motor temperature is always maintained within the optimal working range.

[0050] Such as Figure 2As shown, in one embodiment, the device further includes a correction module, and the correction module is configured to:

[0051] Obtain a difference parameter according to the second prediction index and the first prediction index;

[0052] Correct the original proportionality coefficient according to the difference parameter and obtain a new proportionality coefficient, where the new proportionality coefficient is used to replace the original proportionality coefficient in the subsequent operations of the first processing calculation module and the second processing calculation module.

[0053] In this embodiment, it should be noted that, first, the correction module accurately calculates the difference parameter by comparing the second prediction index and the first prediction index. In this process, the second prediction index reflects the actual change trend of the motor temperature after the water pump is adjusted, while the first prediction index represents the predicted change trend initially based on the ambient temperature and the motor speed change. By deeply analyzing the difference between these two prediction indexes, the correction module can quantify the deviation between the actual heat dissipation effect and the expected heat dissipation effect, that is, the difference parameter. This difference parameter is the basis for dynamically adjusting the proportionality coefficient, and it directly reflects the effectiveness and accuracy of the current cooling system control strategy.

[0054] Secondly, the correction module corrects the original proportionality coefficient according to the calculated difference parameter to obtain a new proportionality coefficient. This is significantly different from the way the proportionality coefficient is used in the first processing calculation module. In the first processing calculation module, the proportionality coefficient is a relatively fixed parameter used to adjust the time interval for data acquisition according to the ambient temperature change, and its setting is mainly based on historical data or experience. While the correction module dynamically adjusts the proportionality coefficient through a real-time feedback mechanism, enabling the cooling system to more flexibly adapt to the changing operating environment and motor state. The new proportionality coefficient takes into account the difference between the actual heat dissipation effect and the expectation. Therefore, in the subsequent operations of the first processing calculation module and the second processing calculation module, using this new proportionality coefficient can more accurately predict the change trend of the motor temperature and more timely adjust the water pump output, thereby significantly improving the control accuracy and response speed of the cooling system. This dynamic adjustment mechanism is the unique function of the correction module and is also the key to enhancing the intelligence and self-adaptability of the entire cooling system.

[0055] In one embodiment, obtaining the difference parameter according to the second prediction index and the first prediction index is expressed as:

[0056] ; where

[0057] is the difference parameter, is the first prediction index, is the second prediction index.

[0058] In this embodiment, it should be noted that if is close to zero, it indicates that the prediction model is accurate and the control strategy is effective, and the output adjustment of the water pump matches the change trend of the motor temperature. If is relatively large or small, it indicates that there are deviations in the prediction model or the control strategy, and adjustments are needed to better adapt to the actual operating conditions.

[0059] Meanwhile the positive or negative of directly reflects the direction of the difference between the prediction and the actual. When > 0, it means that the first prediction index is higher than the second prediction index, that is, the expected heat dissipation demand is overestimated; this may mean that the output adjustment of the water pump is too aggressive, resulting in too low motor temperature or energy waste; therefore, the output adjustment speed of the water pump can be slowed down by reducing the proportionality coefficient. When < 0, it means that the first prediction index is lower than the second prediction index, that is, the expected heat dissipation demand is underestimated; this may mean that the output adjustment of the water pump is insufficient to effectively control the increase in the motor temperature; therefore, the output adjustment speed of the water pump can be accelerated by increasing the proportionality coefficient.

[0060] In one embodiment, the original proportionality coefficient is corrected according to the difference parameter and the new proportionality coefficient is obtained, which is expressed as:

[0061] ; where

[0062] is the new proportionality coefficient, is the original proportionality coefficient.

[0063] In this embodiment, it should be noted that the original proportionality coefficient is set according to historical data, motor models or experience, and is used to adjust the time interval for data acquisition according to the change of the ambient temperature. The new proportionality coefficient is obtained by correcting the original proportionality coefficient according to the difference parameter . The correction formula is , that is, the new proportionality coefficient is equal to the original proportionality coefficient plus the difference parameter.

[0064] The positive or negative and magnitude of the difference parameter directly reflect the direction and degree of the difference between the prediction and the actual. When > 0, it means that the expected heat dissipation demand is overestimated and the output adjustment of the water pump is too aggressive; by reducing the proportionality coefficient (that is, < ), the output adjustment speed of the water pump can be slowed down to avoid too low motor temperature or energy waste. When < 0, it means that the expected heat dissipation demand is underestimated and the output adjustment of the water pump is insufficient; by increasing the proportionality coefficient (that is, > ), it can accelerate the output adjustment speed of the water pump and effectively control the increase in motor temperature. This way of dynamically adjusting the proportionality coefficient according to the difference parameter can optimize the control strategy and make the cooling system work more efficiently.

[0065] In one embodiment, obtaining the first interval time period according to the proportionality coefficient and the first parameter is expressed as:

[0066] ; where

[0067] is the first interval time period, is the first parameter, is the proportionality coefficient.

[0068] In this embodiment, it should be noted that multiplying the proportionality coefficient by the first parameter to obtain the first interval time period . This setting of the multiplication operation makes the first interval time period take into account both the influence of environmental temperature changes (through the proportionality coefficient ) and the specific influence of the current environmental temperature on the cooling efficiency (through the first parameter ).

[0069] By dynamically adjusting the time interval for data acquisition according to the environmental temperature and the motor state, the system can more timely monitor the changing trend of the motor temperature. This enables the system to obtain the necessary data before the motor temperature shows a significant change, so as to make predictions and adjustments in advance, enhancing the predictability of the cooling system.

[0070] Similarly, obtaining the second interval time period according to the proportionality coefficient and the second parameter is expressed as: ; where is the first interval time period, is the first parameter, is the proportionality coefficient.

[0071] In one embodiment, obtaining the first parameter according to the first environmental temperature is expressed as:

[0072] ; where

[0073] is the first parameter, is the first environmental temperature, is the preset temperature.

[0074] In this embodiment, it should be noted that (*) is an exponential function, and its value increases rapidly as the variable increases. This characteristic is suitable for describing the non-linear effect of ambient temperature on the cooling efficiency. In the motor cooling system, the cooling efficiency may decrease significantly in a high-temperature environment, and it is necessary to adjust the water pump output more frequently. (*) can capture this non-linear relationship well. By subtracting the first ambient temperature from the preset temperature and then dividing by the preset temperature , a normalized temperature value is obtained; this normalized value makes the calculations under different ambient temperatures comparable. Regardless of the actual ambient temperature, through normalization, a relative value can be obtained for subsequent calculations; where is the maximum temperature that the external environment where the motor is located can reach, and it can be obtained from existing data such as meteorological information. directly affects the time interval in subsequent calculations (such as the first interval period ); when the measured first ambient temperature is high, that is, approaching , is smaller, so is also smaller, which means that the ambient temperature is close to the maximum value and the cooling demand may be high. Therefore, the system will obtain data more frequently (because is short), so as to monitor and adjust the motor temperature more timely; on the contrary, when the ambient temperature is low, is larger, so is also larger, and the frequency of the system obtaining data will decrease (because is large) to save energy and reduce unnecessary adjustments.

[0075] In one embodiment, the prediction model in the first prediction index obtained based on the prediction model, the first motor speed, the second motor speed, and the first parameter is expressed as:

[0076] ; where,

[0077] is the first prediction index, is the first parameter, is the first motor speed, is the second motor speed, is the maximum motor speed, is the first influence coefficient, is the standard cooling index.

[0078] In this embodiment, it should be noted that the purpose is to capture the non-linear effect of the motor speed change. Among them, first calculate the speed difference , which represents the change in motor speed at two different times; then, normalization is performed by dividing the speed difference by the maximum speed , to obtain a normalized speed change rate, which ensures consistency in comparison between different motors (with different maximum speeds); finally, an exponential operation is performed on the normalized speed change rate. The exponential function can amplify small changes, making the change in the prediction index more sensitive when the speed change rate is small, and more significant when the speed change rate is large. This setting can better reflect the non-linear impact of motor speed changes on heat dissipation requirements, thereby improving the accuracy of prediction.

[0079] Furthermore, the linear transformation part aims to adjust the output range of the exponential function to make it more suitable for subsequent prediction index calculations. Subtracting 1 from the output of the exponential function is to adjust the output range of the exponential function from [1, +∞) to [0, +∞), so that when there is no change in speed (i.e., = N2), the output of this part is 0. Among them, dividing by the first influence coefficient is used to adjust the sensitivity of this part. It can be adjusted according to the actual application scenario. Generally, is the same as the standard cooling index to control the influence degree of speed change on the prediction index. Through the linear transformation part, the prediction model can be made more flexible to adapt to the needs of different motors and application scenarios. By adjusting , the prediction performance of the model can be optimized to more accurately reflect the impact of motor speed changes on heat dissipation requirements.

[0080] Furthermore, adding the standard cooling index aims to provide a benchmark cooling index, representing the cooling requirement under normal conditions (i.e., when there is no change in speed). The operation process: directly add to the output of the linear transformation. The introduction of makes the prediction model able to provide a reasonable cooling index even when there is no speed change, which helps to ensure that the cooling system can also maintain an appropriate cooling output during the stable operation of the motor, avoiding over-cooling or under-cooling.

[0081] Furthermore, multiplying by the first parameter is used to consider the impact of ambient temperature on cooling efficiency, reflecting the impact of ambient temperature on cooling efficiency, enabling the prediction model to dynamically adjust the prediction index to better meet the cooling requirements under the current environmental conditions. This setting enhances the self-adaptability of the cooling system, enabling it to more effectively control the motor temperature at different ambient temperatures.

[0082] In one embodiment, the feedback model for obtaining the second prediction index based on the feedback model, the first motor temperature, the second motor temperature, and the second parameter is expressed as:

[0083] ; where

[0084] is the second prediction index, is the second parameter, is the first motor temperature, is the second motor temperature, is the motor standard temperature, is the second influence coefficient, is the standard cooling index.

[0085] In this embodiment, it should be noted that the purpose is to capture the non-linear effect of the motor temperature change. First, calculate , which represents the change in the motor temperature at two different times; then, perform normalization processing by dividing the temperature difference by the motor standard temperature to obtain the normalized temperature change rate, which can ensure the consistency of comparison between different motors (with different standard temperatures); finally, perform an exponential operation on the normalized temperature change rate, which is similar to the exponential operation in the prediction model. The exponential function can amplify the small temperature changes, so that when the temperature change rate is small, the change in the prediction index is also more sensitive; and when the temperature change rate is large, the change in the prediction index will be more significant, thereby improving the accuracy of the feedback model.

[0086] Furthermore, the purpose of the linear transformation part is to adjust the output range of the exponential function to make it more suitable for the subsequent calculation of the prediction index; first, adjust the output range of the exponential function from [1, +∞) to [0, +∞), so that when the temperature does not change (i.e., = ), the output of this part is 0. Dividing by the second influence coefficient is used to adjust the sensitivity of the linear transformation part. can be adjusted according to the actual application scenario to control the influence degree of the temperature change on the prediction index. Similarly, in general, is the same as the standard cooling index to control the influence degree of the rotational speed change on the prediction index. Through the linear transformation part, the feedback model can be made more flexible to meet the requirements of different motors and application scenarios. By adjusting , the prediction performance of the model can be optimized to more accurately reflect the influence of the motor temperature change on the heat dissipation demand.

[0087] Further, add the standard cooling index The purpose is to provide a benchmark cooling index, which represents the cooling demand under normal conditions (i.e., when the temperature does not change). This enables the feedback model to provide a reasonable cooling index even when there is no temperature change, which helps to ensure that the cooling system can maintain an appropriate cooling output during the stable operation of the motor, avoiding over-cooling or under-cooling.

[0088] Further, multiply by the second parameter , and the purpose is to consider the influence of the environmental conditions on the cooling efficiency after the water pump is adjusted. is the second ambient temperature obtained based on the water pump output time point, and is obtained through a preset algorithm or parameter table. It reflects the influence of the current environmental conditions on the cooling efficiency after the water pump is adjusted. By multiplying by , the feedback model can dynamically adjust the prediction index to make it more in line with the actual heat dissipation requirements after the water pump is adjusted. This setting enhances the self-adaptability of the cooling system, enabling it to effectively control the motor temperature under different environmental conditions.

[0089] The preferred embodiments of the present disclosure have been described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0090] In addition, it should be noted that, among the various specific technical features described in the above specific embodiments, they can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combination methods.

[0091] Furthermore, any combination can be made between various different embodiments of the present disclosure, as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

[0092] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A control device for a motor cooling system based on multi-parameter linkage, characterized in that, Including: An acquisition module, configured to acquire a first ambient temperature and a first motor speed at a first moment, and acquire a first parameter according to the first ambient temperature; The obtaining of the first parameter according to the first ambient temperature is expressed as: where α1 is the first parameter, T1 is the first ambient temperature, and T m is the preset temperature; A first processing and calculation module, configured to acquire a first interval period according to the first parameter, acquire a second moment separated from the first moment by the first interval period, acquire a second motor speed at the second moment, and acquire a first prediction index based on a prediction model, the first motor speed, the second motor speed, and the first parameter; Among them, the prediction model is expressed as: Among them, P1 is the first prediction index, α1 is the first parameter, N1 is the rotational speed of the first motor, N2 is the rotational speed of the second motor, N max is the maximum rotational speed of the motor, ρ1 is the first influence coefficient, and β is the standard cooling index; A first control and adjustment module, configured to acquire a first water pump adjustment signal according to the first prediction index, adjust the water pump output according to the first water pump adjustment signal, acquire a first motor temperature and a second ambient temperature at the water pump output time point, and acquire a second parameter according to the second ambient temperature; A second processing and calculation module, configured to acquire a second interval period according to the second parameter, acquire a third moment separated from the water pump output time point by the second interval period, acquire a second motor temperature at the third moment, and acquire a second prediction index based on a feedback model, the first motor temperature, the second motor temperature, and the second parameter; Among them, the feedback model is expressed as: Among them, P2 is the second prediction index, α2 is the second parameter, T 1e is the temperature of the first motor, T 2e is the temperature of the second motor, T est is the standard temperature of the motor, ρ2 is the second influence coefficient, and β is the standard cooling index; A second control and adjustment module, configured to correct the first water pump adjustment signal according to the second prediction index and generate a second water pump adjustment signal, and adjust the water pump output according to the second water pump adjustment signal.

2. The control device for the motor cooling system based on multi-parameter linkage according to claim 1, wherein The first processing and calculation module is further configured to: Acquire a proportionality coefficient; Acquire the first interval period according to the proportionality coefficient and the first parameter.

3. The control device of the motor cooling system based on multi-parameter linkage according to claim 2, characterized in that, The second processing and calculation module is further configured to: Acquire a proportionality coefficient; Acquire the second interval period according to the proportionality coefficient and the second parameter.

4. The control device for the motor cooling system based on multi-parameter linkage according to claim 3, characterized in that It further includes a correction module, and the correction module is configured to: Acquire a differential parameter according to the second prediction index and the first prediction index; Correct the original proportionality coefficient according to the differential parameter and acquire a new proportionality coefficient, where the new proportionality coefficient is used to replace the original proportionality coefficient in the subsequent operations of the first processing and calculation module and the second processing and calculation module.

5. The control device of the motor cooling system based on multi-parameter linkage according to claim 4, characterized in that The acquiring the differential parameter according to the second prediction index and the first prediction index is expressed as: ΔP = P1 - P2; where, ΔP is the differential parameter, P1 is the first prediction index, and P2 is the second prediction index.

6. The control device for the motor cooling system based on multi-parameter linkage according to claim 5, wherein, The correcting the original proportionality coefficient according to the differential parameter and acquiring a new proportionality coefficient is expressed as: K n = K l + ΔP; where, K n is the new proportionality coefficient, K l is the original proportionality coefficient.

7. The control device for the motor cooling system based on multi-parameter linkage according to claim 3, characterized in that, The acquiring the first interval period according to the proportionality coefficient and the first parameter is expressed as: ΔT1 = α1·K; where, ΔT1 is the first interval period, α1 is the first parameter, and K is the proportionality coefficient.

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