A method and system for dynamic optimization of motor controller carrier frequency

Abstract

The present invention relates to the technical field of motor controller control, and more specifically to a method and system for dynamically optimizing the carrier frequency of a motor controller, comprising: obtaining a proportional coefficient between the carrier frequency and the energy consumption in the historical data based on the motor energy consumption and carrier frequency per second; obtaining the energy consumption availability per second based on the difference in the motor energy consumption between two adjacent seconds in the historical data; obtaining the motor carrier frequency adaptability at the current moment based on the carrier frequency and motor speed data at the current moment, the motor speed data per second in the historical data, the motor energy consumption and the energy consumption availability, and the proportional coefficient between the carrier frequency and the energy consumption in the historical data; and dynamically optimizing the carrier frequency of the motor controller based on the motor carrier frequency adaptability. The present invention enables the energy consumption of the motor speed and carrier frequency supply to develop in the direction of maintaining cubicity and reducing energy loss.

Description

Technical Field

[0001] The present invention relates to the technical field of control of motor controllers, and in particular to a method and system for dynamically optimizing the carrier frequency of a motor controller. Background Art

[0002] Fan motors are widely used in modern buildings and industrial facilities. Their main task is to change the motor speed according to environmental conditions and usage requirements to adjust parameters such as air flow, temperature, humidity and pressure. Ideally, the motor load remains constant, and a fixed carrier frequency can maintain the speed. However, in actual operation, the motor may be affected by factors such as airflow and wind speed variations, and system resistance, resulting in it not always being under the same load. Therefore, if the original speed needs to be maintained, a controller is required to dynamically optimize the carrier frequency. Generally, with maintaining the original motor speed as the optimization goal, dynamic carrier frequency optimization is achieved through a genetic algorithm. First, a complex mathematical model is established to determine the speed that a carrier frequency population can bring to the motor under the current load. The speed deviation from the previous moment is used to evaluate the fitness of each carrier frequency population. However, since the motor load conditions are diverse and difficult to predict due to factors such as airflow and wind speed variations, system resistance, etc., the mathematical model is difficult to establish, and determining the fitness of each carrier frequency population is also difficult. In general, a fixed mutation rate is set for the genetic algorithm. If the mutation rate is too small, it is difficult to escape the local optimal solution to cope with large load changes. If the mutation rate is too large, the algorithm will have difficulty converging and determining the carrier frequency that can maintain the original speed. Summary of the Invention

[0003] The present invention provides a method and system for dynamically optimizing the carrier frequency of a motor controller to solve existing problems: a genetic algorithm sets a fixed mutation rate. If the mutation rate is small, it is difficult to jump out of the local optimal solution to cope with large load changes; if the mutation rate is too large, it will make it difficult for the algorithm to converge and determine the carrier frequency that can maintain the original speed.

[0004] A motor controller carrier frequency dynamic optimization method and system of the present invention adopts the following technical solutions:

[0005] The present invention proposes a method for dynamically optimizing the carrier frequency of a motor controller, the method comprising the following steps:

[0006] Acquire historical data and current data of motor carrier frequency control; the historical data includes motor speed data, motor power data and carrier frequency for several seconds; the current data includes motor speed data, motor power data and carrier frequency at the current moment;

[0007] According to the fluctuation of motor power data per second in historical data, the optimal time granularity per second in historical data is obtained; according to the optimal time granularity per second, the motor energy consumption per second is obtained;

[0008] Based on the motor energy consumption and carrier frequency per second in the historical data, the proportional coefficient between the carrier frequency and the energy consumption in the historical data is obtained; based on the difference in the motor energy consumption between two adjacent seconds in the historical data, the energy consumption availability per second is obtained; based on the current carrier frequency and motor speed data, the motor speed data per second in the historical data, the motor energy consumption and the energy consumption availability, and the proportional coefficient between the carrier frequency and the energy consumption in the historical data, the motor carrier frequency adaptability at the current moment is obtained;

[0009] The motor controller is dynamically optimized for carrier frequency based on the motor carrier frequency adaptability.

[0010] Preferably, the specific method for obtaining the optimal time granularity per second in the historical data according to the fluctuation of the motor power data per second in the historical data is:

[0011] Preset several partitioning parameters, for any second in the historical data, use the The division parameter divides any one second into several intervals, which are all recorded as The time granularity interval under the partition parameters;

[0012] According to the fluctuation of motor power data per second in historical data, the optimization degree of each division parameter is obtained;

[0013] All partitioning parameters are screened based on the degree of preference to obtain the optimal time granularity of any one second.

[0014] Preferably, the specific method for obtaining the preference degree of each division parameter according to the fluctuation of the motor power data per second in the historical data is:

[0015] Among all the partition parameters, The normalized value of the partition parameter is recorded as The weight factor of the partition parameter; The first partition parameter The variance of the motor power data at all moments within the time granularity interval is recorded as The power fluctuation factor of the time granularity interval; calculate the The cumulative sum of the power fluctuation factors of all time granularity intervals under the partitioning parameters; The normalized value of the partition parameter is used as the numerator, and the hyperparameter is compared with the The sum of the power fluctuation factors of all time granularity intervals under the partitioning parameters is used as the denominator, and the ratio of the numerator and denominator is used as the first The preference of the partitioning parameters.

[0016] Preferably, the specific method of screening all the partitioning parameters based on the degree of preference to obtain the optimal time granularity of any one second is:

[0017] Among all the division parameters, the division parameter with the greatest preference is used as the optimal time granularity of any one second.

[0018] Preferably, the specific method for obtaining the motor energy consumption per second according to the optimal time granularity per second is:

[0019] The first The product of the mean value of the motor power data at all moments in the optimal time granularity interval and the inverse of the optimal time granularity of any one second is recorded as the The energy factor of each optimal time granularity interval is calculated; and the accumulated sum of the energy factors of all the optimal time granularity intervals in any one second is used as the motor energy consumption in any one second.

[0020] Preferably, the specific method for obtaining the proportional coefficient between the carrier frequency and the energy consumption in the historical data based on the motor energy consumption and carrier frequency per second in the historical data is:

[0021] The historical data The ratio of the second to the cumulative sum of all seconds in the historical data is recorded as The time proportion weight of the second Seconds of motor energy consumption and The ratio of the carrier frequency to the second is recorded as The ratio of carrier frequency energy within one second; The ratio of the carrier frequency energy in one second to the The product of the weights of the time proportion of seconds is recorded as The proportional factor between the carrier frequency and the consumed energy within a second; the cumulative sum of the proportional factors between the carrier frequency and the consumed energy within all seconds in the historical data is used as the proportional coefficient between the carrier frequency and the consumed energy in the historical data.

[0022] Preferably, the specific method for obtaining the energy consumption availability per second based on the difference in motor energy consumption between two adjacent seconds in the historical data is:

[0023] The historical data The motor energy consumption in seconds is consistent with the historical data. The normalized value of the reciprocal of the absolute value of the difference between the motor energy consumption in seconds is taken as the Seconds of consumed energy availability.

[0024] Preferably, the specific method for obtaining the motor carrier frequency adaptability at the current moment based on the carrier frequency and motor speed data at the current moment, the motor speed data per second in the historical data, the motor energy consumption and the consumed energy availability, and the proportional coefficient between the carrier frequency and the consumed energy in the historical data is:

[0025] Obtain the motor energy consumption set and the motor speed set;

[0026] The first The absolute value of the difference between the first element and the mean of all elements in the motor energy consumption set is recorded as the first absolute value of the difference; the ratio of the first absolute value of the difference to the standard deviation of all elements in the motor energy consumption set is recorded as the first absolute value of the motor energy consumption set. The first ratio of the elements in the motor speed set; The absolute value of the difference between the first element and the mean of all elements in the motor speed set is recorded as the second absolute value of the difference; the ratio of the second absolute value of the difference to the standard deviation of all elements in the motor speed set is recorded as the first absolute value of the motor speed set. The second ratio of the elements in the motor energy consumption set; The first ratio of the element to the motor speed set The product of the second ratios of the elements is recorded as The relevant weighting factor of the element; The correlation weighting factor of the element is The product of the consumed energy availability in seconds is recorded as The motor carrier frequency adaptation factor of each element is calculated; the average of the motor carrier frequency adaptation factors of all elements is taken as the motor carrier frequency adaptability at the current moment.

[0027] Preferably, the specific method for obtaining the motor energy consumption set and the motor speed set is:

[0028] The set consisting of the motor energy consumption of all seconds in the historical data and the product of the proportional coefficient between the carrier frequency and the energy consumption in the historical data and the carrier frequency at the current moment is recorded as the motor energy consumption set; the set consisting of the cube value of the motor speed data of all seconds in the historical data and the motor speed data at the current moment is recorded as the motor speed set.

[0029] The present invention also proposes a motor controller carrier frequency dynamic optimization system, comprising a memory and a processor, wherein the processor executes a computer program stored in the memory to implement the steps of the above-mentioned motor controller carrier frequency dynamic optimization method.

[0030] The beneficial effects of the technical solution of the present invention are as follows: the present invention obtains the proportional coefficient between the carrier frequency and the consumed energy in the historical data based on the motor energy consumption and carrier frequency per second in the historical data; obtains the consumed energy availability per second based on the difference in the motor energy consumption between two adjacent seconds in the historical data; obtains the motor carrier frequency adaptability at the current moment based on the carrier frequency and motor speed data at the current moment, the motor speed data per second in the historical data, the motor energy consumption and the consumed energy availability, and the proportional coefficient between the carrier frequency and the consumed energy in the historical data; dynamically optimizes the carrier frequency of the motor controller based on the motor carrier frequency adaptability; thereby, the energy consumption of the motor speed and carrier frequency supply develops in the direction of maintaining cubicity and reducing energy loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 A flowchart of a method for dynamically optimizing the carrier frequency of a motor controller according to the present invention;

[0033] Figure 2 This is a characteristic relationship flow chart of a method for dynamically optimizing the carrier frequency of a motor controller according to the present invention. DETAILED DESCRIPTION

[0034] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a method and system for dynamically optimizing the carrier frequency of a motor controller according to the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0035] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0036] The specific scheme of the motor controller carrier frequency dynamic optimization method and system provided by the present invention is described in detail below with reference to the accompanying drawings.

[0037] See also Figure 1 , which shows a flowchart of a method for dynamically optimizing the carrier frequency of a motor controller provided by one embodiment of the present invention, the method comprising the following steps:

[0038] Step S001: Acquire historical data and current data of motor carrier frequency control; the historical data includes motor speed data, motor power data and carrier frequency for several seconds; the current data includes motor speed data, motor power data and carrier frequency at the current moment.

[0039] In a specific implementation of the embodiment of the present invention, a specific method for obtaining historical data and current data of motor carrier frequency control is as follows:

[0040] The required motor speed is manually input, and the carrier frequency required for the motor speed is determined based on prior knowledge to start the motor. The motor speed data, motor power data, and carrier frequency are collected every 1 second for a total of 61 seconds. The motor speed data, motor power data, and carrier frequency for the first 60 seconds are used as historical data for motor carrier frequency control. The motor speed data, motor power data, and carrier frequency at the 61st second are used as current data for motor carrier frequency control.

[0041] So far, the historical data of the motor carrier frequency control and the current data of the motor carrier frequency control are obtained through the above method.

[0042] Step S002: according to the fluctuation of the motor power data per second in the historical data, the optimal time granularity per second in the historical data is obtained; according to the optimal time granularity per second, the motor energy consumption per second is obtained.

[0043] It should be noted that the energy consumed by the motor per second in the historical data can be regarded as the work it does in that second. This process is achieved through limit approximation in practical applications. Specifically, each second is divided into multiple time granularity intervals, the small area corresponding to each time granularity interval is calculated, and the overall integral is approximated by summing up. Therefore, the integral of the power can be regarded as the accumulation of the areas of these time granularity intervals. When the time granularity interval is too small, the data to be calculated is large and difficult. When the time granularity interval is too large, the motor often has periodic torque fluctuations, which makes the torque output of the motor at different positions not completely uniform. Therefore, these subtle torque fluctuations cannot be captured and the fluctuations are averaged, resulting in inaccurate estimates. Therefore, it is necessary to determine the optimal time granularity per second in the historical data, so that the power fluctuations that can be collected in each time granularity interval are as small as possible, so that the energy consumption per second obtained is sufficiently accurate.

[0044] Preferably, in some implementations of the embodiments of the present invention, the optimal time granularity per second in the historical data is obtained according to the fluctuation of the motor power data per second in the historical data;

[0045] Preset several partitioning parameters , , , , wherein this embodiment is based on , , , This example is described as an example, and this embodiment is not specifically limited. , , , Depends on the specific implementation situation;

[0046] For any second in the historical data, use The division parameter divides any one second into several intervals, which are all recorded as The time granularity interval under the partition parameters;

[0047] Among all the partition parameters, The normalized value of the partition parameter is recorded as The weight factor of the partition parameter; The first partition parameter The variance of the motor power data at all moments within the time granularity interval is recorded as The power fluctuation factor of the time granularity interval; calculate the The cumulative sum of the power fluctuation factors of all time granularity intervals under the partitioning parameters; The normalized value of the partition parameter is used as the numerator, and the hyperparameter is compared with the The sum of the power fluctuation factors of all time granularity intervals under the partitioning parameters is used as the denominator, and the ratio of the numerator and denominator is used as the first The preference degree of each partition parameter; the partition parameter with the greatest preference degree is used as the optimal time granularity of any one second;

[0048] Get the The specific formula for the optimization degree of a partition parameter is:

[0049]

[0050] Where, Indicates the The degree of preference of the partitioning parameters; Indicates the partition parameters; Indicates the The first partition parameter The variance of the power at all moments within a time granularity interval; represents the linear normalized value; Represents the preset hyperparameters. This implementation presets , used to prevent the denominator from being 0.

[0051] Preferably, in some implementations of the embodiments of the present invention, the specific method for obtaining the motor energy consumption per second according to the optimal time granularity per second is:

[0052] For any second in the historical data, the optimal time granularity of the any second is used to divide the any second into several intervals, and each interval is recorded as the optimal time granularity interval of the any second;

[0053] The first The product of the mean value of the motor power data at all moments in the optimal time granularity interval and the inverse of the optimal time granularity of any one second is recorded as the The energy factor of the optimal time granularity interval is calculated; the cumulative sum of the energy factors of all the optimal time granularity intervals in any one second is used as the energy consumption of the motor in any one second;

[0054] The specific formula is:

[0055]

[0056] Where, Indicates the energy consumed by the motor in any one second; Indicates the optimal time granularity of any one second; Indicates the first The mean value of the motor power data at all moments in the optimal time granularity interval; Indicates the optimal time granularity of any one second.

[0057] So far, the motor energy consumption per second in the historical data has been obtained through the above method.

[0058] Step S003: Based on the motor energy consumption and carrier frequency per second in the historical data, obtain the proportional coefficient between the carrier frequency and the energy consumption in the historical data; based on the difference in the motor energy consumption between two adjacent seconds in the historical data, obtain the energy consumption availability per second; based on the carrier frequency and motor speed data at the current moment, the motor speed data per second in the historical data, the motor energy consumption and the energy consumption availability, and the proportional coefficient between the carrier frequency and the energy consumption in the historical data, obtain the motor carrier frequency adaptability at the current moment.

[0059] It should be noted that, under no-load conditions, the internal loss of the motor is relatively small, and it can more effectively convert electrical energy into mechanical energy. This means that when the carrier frequency increases, the motor speed will increase accordingly, resulting in an increase in current and power. Because under a certain voltage, the increase in current will increase the power, and the power directly determines the energy consumed per second, thus forming a proportional relationship between the carrier frequency and the energy consumed per second, and then obtaining the proportional coefficient between the carrier frequency and the energy consumed in the historical data; according to the principles of fluid dynamics, the shaft power is proportional to the cube of the speed, which means that when the speed of the motor increases, its consumption Energy increases at the cube of the rotational speed, which means that the energy that needs to be supplied can maintain the current rotational speed as much as possible and maintain a cubic correlation with the previous moment. Under dynamic conditions, the acceleration and deceleration processes of the motor will affect energy consumption. When the motor is accelerating, additional energy is required to overcome inertia and increase the rotational speed. During deceleration, energy consumption may be reduced, and some energy can even be recovered through regenerative braking. Therefore, when determining the cubic correlation, the smaller the difference between the motor energy consumption per second in the historical data and the motor energy consumption in the previous second, the better the availability of the energy consumption per second in the historical data.

[0060] Preferably, in some implementations of the embodiments of the present invention, since the motor consumes a large amount of energy during the startup phase to overcome mechanical inertia so that the motor can achieve normal operation, and the influence of the inertia effect on energy consumption decreases over time, the later the proportional coefficient is determined in the historical data, the more accurate it is; based on the motor energy consumption and carrier frequency per second in the historical data, the specific method for obtaining the proportional coefficient between the carrier frequency and the consumed energy in the historical data is as follows:

[0061] The historical data The ratio of the second to the cumulative sum of all seconds in the historical data is recorded as The time proportion weight of the second Seconds of motor energy consumption and The ratio of the carrier frequency to the second is recorded as The ratio of carrier frequency energy within one second; The ratio of the carrier frequency energy in one second to the The product of the weights of the time proportion of seconds is recorded as The proportional factor between the carrier frequency and the consumed energy within a second; the cumulative sum of the proportional factors between the carrier frequency and the consumed energy within all seconds in the historical data is used as the proportional coefficient between the carrier frequency and the consumed energy in the historical data;

[0062] The specific formula is:

[0063]

[0064] Where, Indicates the proportional coefficient between carrier frequency and consumed energy in historical data; Indicates the number of all seconds in the historical data; Indicates the historical data seconds; Indicates the historical data Seconds of motor energy consumption; Indicates the historical data Seconds carrier frequency.

[0065] Preferably, in some implementations of the embodiments of the present invention, the specific method for obtaining the energy consumption availability per second based on the difference in motor energy consumption between two adjacent seconds in historical data is:

[0066] The historical data The motor energy consumption in seconds is consistent with the historical data. The normalized value of the reciprocal of the absolute value of the difference between the motor energy consumption in seconds is taken as the Seconds of consumed energy availability;

[0067] The specific formula is:

[0068]

[0069] Where, Indicates the Seconds of consumed energy availability; Indicates the Seconds of motor energy consumption; Indicates the Seconds of motor energy consumption; represents the linear normalized value; Represents the preset hyperparameters. This implementation presets , used to prevent the denominator from being 0.

[0070] Preferably, in some implementations of the embodiments of the present invention, since a cubic correlation needs to be maintained between the speed and the energy, a specific method for obtaining the motor carrier frequency adaptability at the current moment is as follows based on the current carrier frequency and motor speed data, the motor speed data per second in the historical data, the motor energy consumption and the consumed energy availability, and the proportional coefficient between the carrier frequency and the consumed energy in the historical data:

[0071] The motor energy consumption set is composed of the motor energy consumption of all seconds in the historical data and the product of the proportional coefficient between the carrier frequency and the energy consumption in the historical data and the carrier frequency at the current moment; the motor speed set is composed of the cube of the motor speed data of all seconds in the historical data and the motor speed data at the current moment;

[0072] The first The absolute value of the difference between the first element and the mean of all elements in the motor energy consumption set is recorded as the first absolute value of the difference; the ratio of the first absolute value of the difference to the standard deviation of all elements in the motor energy consumption set is recorded as the first absolute value of the motor energy consumption set. The first ratio of the elements in the motor speed set; The absolute value of the difference between the first element and the mean of all elements in the motor speed set is recorded as the second absolute value of the difference; the ratio of the second absolute value of the difference to the standard deviation of all elements in the motor speed set is recorded as the first absolute value of the motor speed set. The second ratio of the elements in the motor energy consumption set; The first ratio of the element to the motor speed set The product of the second ratios of the elements is recorded as The relevant weighting factor of the element; The correlation weighting factor of the element is The product of the consumed energy availability in seconds is recorded as The motor carrier frequency adaptation factor of each element; the average of the motor carrier frequency adaptation factors of all elements is used as the motor carrier frequency adaptability at the current moment;

[0073] The specific formula is:

[0074]

[0075] Where, Indicates the current motor carrier frequency adaptability; Indicates the number of all seconds in the historical data; Indicates the Seconds of consumed energy availability; Indicates the number of motor energy consumption sets elements; Represents the mean value of all elements in the motor energy consumption set; Represents the standard deviation of all elements in the motor energy consumption set; Indicates the number of motor speeds in the set elements; Represents the mean of all elements in the motor speed set; Represents the standard deviation of all elements in the motor speed set; Indicates taking the absolute value.

[0076] At this point, the motor carrier frequency adaptability at the current moment is obtained through the above method.

[0077] Step S004: dynamically optimizing the carrier frequency of the motor controller based on the motor carrier frequency adaptability.

[0078] Preferably, in some implementations of the embodiments of the present invention, the specific method for dynamically optimizing the carrier frequency of the motor controller based on the motor carrier frequency adaptability at the current moment is:

[0079] Preset a selection parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation;

[0080] Random selection carrier frequencies, and use the genetic algorithm to update the carrier frequency population. The motor carrier frequency fitness corresponding to each carrier frequency is obtained through the above-mentioned method for obtaining the motor carrier frequency fitness at the current moment, and the carrier frequency with the largest motor carrier frequency fitness is used as the carrier frequency at the next moment; the carrier frequency at the next moment is input into the motor controller to adjust the motor carrier frequency; then, the above operation is repeated every second, so that the motor can maintain the speed when the load changes due to airflow changes, wind speed changes, system resistance, etc.

[0081] Among them, the genetic algorithm is an existing technology and will not be described in detail in this embodiment.

[0082] See also Figure 2 , which shows a characteristic relationship flow chart of a method for dynamic optimization of the carrier frequency of a motor controller;

[0083] Through the above steps, a method for dynamic optimization of the carrier frequency of a motor controller is completed.

[0084] Another embodiment of the present invention provides a motor controller carrier frequency dynamic optimization system, the system comprising a memory and a processor, and when the processor executes a computer program stored in the memory, the processor performs steps S001 to S004 of the above method.

[0085] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for dynamic optimization of the carrier frequency of a motor controller, characterized in that: The method comprises the following steps: Acquire historical data and current data of motor carrier frequency control; the historical data includes motor speed data, motor power data and carrier frequency for several seconds; the current data includes motor speed data, motor power data and carrier frequency at the current moment; According to the fluctuation of the motor power data per second in the historical data, the optimal time granularity of the motor power data per second in the historical data is obtained; according to the optimal time granularity per second, the motor energy consumption per second is obtained; Based on the motor energy consumption and carrier frequency per second in the historical data, the proportional coefficient between the carrier frequency and the energy consumption in the historical data is obtained; based on the difference in the motor energy consumption between two adjacent seconds in the historical data, the energy consumption availability per second is obtained; based on the current carrier frequency and motor speed data, the motor speed data per second in the historical data, the motor energy consumption and the energy consumption availability, and the proportional coefficient between the carrier frequency and the energy consumption in the historical data, the motor carrier frequency adaptability at the current moment is obtained; The motor controller is dynamically optimized for carrier frequency based on the motor carrier frequency adaptability.

2. A method for dynamic optimization of motor controller carrier frequency according to claim 1, characterized in that: The specific method for obtaining the optimal time granularity of the motor power data per second in the historical data according to the fluctuation of the motor power data per second in the historical data is: Preset several partitioning parameters, for any second in the historical data, use the The division parameter divides any one second into several intervals, which are all recorded as The time granularity interval under the partition parameters; According to the fluctuation of motor power data per second in historical data, the optimization degree of each division parameter is obtained; All partitioning parameters are screened based on the degree of preference to obtain the optimal time granularity of any one second.

3. A method for dynamic optimization of motor controller carrier frequency according to claim 2, characterized in that: The specific method for obtaining the preference of each partition parameter based on the fluctuation of the motor power data per second in the historical data is as follows: Among all the partition parameters, The normalized value of the partition parameter is recorded as The weight factor of the partition parameter; The first partition parameter The variance of the motor power data at all moments within the time granularity interval is recorded as The power fluctuation factor of the time granularity interval; calculate the The cumulative sum of the power fluctuation factors of all time granularity intervals under the partitioning parameters; The normalized value of the partition parameter is used as the numerator, and the hyperparameter is compared with the The sum of the power fluctuation factors of all time granularity intervals under the partitioning parameters is used as the denominator, and the ratio of the numerator and denominator is used as the first The preference of the partitioning parameters.

4. A method for dynamic optimization of motor controller carrier frequency according to claim 2, characterized in that: The specific method of screening all the partitioning parameters based on the degree of preference to obtain the optimal time granularity of any one second is as follows: Among all the division parameters, the division parameter with the greatest preference is used as the optimal time granularity of any one second.

5. The method for dynamic optimization of motor controller carrier frequency according to claim 2, characterized in that: The specific method for obtaining the motor energy consumption per second based on the optimal time granularity per second is: The first The product of the mean value of the motor power data at all moments in the optimal time granularity interval and the inverse of the optimal time granularity of any one second is recorded as the The energy factor of each optimal time granularity interval is calculated; and the accumulated sum of the energy factors of all the optimal time granularity intervals in any one second is used as the motor energy consumption in any one second.

6. A method for dynamic optimization of motor controller carrier frequency according to claim 1, characterized in that: The specific method for obtaining the proportional coefficient between the carrier frequency and the energy consumption in the historical data based on the motor energy consumption and carrier frequency per second is: The historical data The ratio of the second to the cumulative sum of all seconds in the historical data is recorded as The time proportion weight of seconds; The first The motor energy consumption in seconds is equal to that in the first The ratio of the carrier frequency to the second is recorded as The ratio of carrier frequency energy within one second; The ratio of the carrier frequency energy in one second to the The product of the weights of the time proportion of seconds is recorded as The proportional factor between the carrier frequency and the consumed energy within a second; the cumulative sum of the proportional factors between the carrier frequency and the consumed energy within all seconds in the historical data is used as the proportional coefficient between the carrier frequency and the consumed energy in the historical data.

7. A method for dynamic optimization of motor controller carrier frequency according to claim 1, characterized in that: The specific method for obtaining the energy consumption availability per second based on the difference in motor energy consumption between two consecutive seconds in the historical data is as follows: The historical data The motor energy consumption in seconds is consistent with the historical data. The normalized value of the reciprocal of the absolute value of the difference between the motor energy consumption in seconds is taken as the Seconds of consumed energy availability.

8. The method for dynamic optimization of motor controller carrier frequency according to claim 1, characterized in that: The specific method for obtaining the motor carrier frequency adaptability at the current moment based on the carrier frequency and motor speed data at the current moment, the motor speed data per second in the historical data, the motor energy consumption and the energy availability, and the proportional coefficient between the carrier frequency and the energy consumption in the historical data is as follows: Obtain the motor energy consumption set and the motor speed set; The first The absolute value of the difference between the first element and the mean of all elements in the motor energy consumption set is recorded as the first absolute value of the difference; the ratio of the first absolute value of the difference to the standard deviation of all elements in the motor energy consumption set is recorded as the first absolute value of the motor energy consumption set. The first ratio of the elements in the motor speed set; The absolute value of the difference between the first element and the mean of all elements in the motor speed set is recorded as the second absolute value of the difference; the ratio of the second absolute value of the difference to the standard deviation of all elements in the motor speed set is recorded as the first absolute value of the motor speed set. The second ratio of the elements; The first The first ratio of the element to the motor speed set The product of the second ratios of the elements is recorded as The relevant weighting factor of each element; The first The correlation weighting factor of the element is The product of the consumed energy availability in seconds is recorded as The motor carrier frequency adaptation factor of each element is calculated; the average of the motor carrier frequency adaptation factors of all elements is taken as the motor carrier frequency adaptability at the current moment.

9. A method for dynamic optimization of motor controller carrier frequency according to claim 8, characterized in that: The specific method for obtaining the motor energy consumption set and the motor speed set is: The set consisting of the motor energy consumption of all seconds in the historical data and the product of the proportional coefficient between the carrier frequency and the energy consumption in the historical data and the carrier frequency at the current moment is recorded as the motor energy consumption set; the set consisting of the cube value of the motor speed data of all seconds in the historical data and the motor speed data at the current moment is recorded as the motor speed set.

10. A motor controller carrier frequency dynamic optimization system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of a method for dynamically optimizing the carrier frequency of a motor controller as described in any one of claims 1 to 9 are implemented.

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