Methods, apparatus, electronic equipment and storage medium for calculating compressor outlet refrigerant temperature

Abstract

This application provides a method, apparatus, electronic device, and storage medium for calculating the refrigerant temperature at the compressor outlet. The method includes: calculating a Kalman filter coefficient based on the relative proportion of the current temperature measurement error coefficient of the temperature sensor to the previous estimated error coefficient of the temperature sensor; and calculating the current estimated temperature of the refrigerant at the compressor outlet based on the previous estimated temperature, the current sampled value of the temperature sensor, and the Kalman filter coefficient. This application can calculate the refrigerant temperature at the compressor outlet and, while preserving the original input signal waveform and avoiding distortion, filter out glitches.

Description

Technical Field

[0001] This application relates to the field of temperature detection, and more specifically, to a method, apparatus, electronic device, and storage medium for calculating the refrigerant temperature at the compressor outlet. Background Technology

[0002] Currently, vehicle thermal management systems require the signal waveform of the compressor outlet refrigerant temperature to implement corresponding thermal management measures. For example, when the compressor outlet refrigerant temperature is too high, the compressor speed is reduced for protection. Furthermore, glitches in the compressor outlet refrigerant temperature signal waveform can affect the vehicle's thermal management system; for instance, the system may output incorrect thermal management commands based on glitches. Conversely, distortion in the compressor outlet refrigerant temperature signal waveform also affects the system; if the waveform is distorted, the system may issue incorrect commands. Therefore, to minimize the adverse effects of the compressor outlet refrigerant temperature signal waveform on the vehicle's thermal management system, distortion and glitches in the signal waveform should be avoided as much as possible.

[0003] Furthermore, the existing technology typically employs the following method to output the signal waveform of the compressor outlet refrigerant temperature: first, acquire the sampled values ​​of the temperature sensor; then, process the sampled values ​​of the temperature sensor based on a specific processing algorithm to obtain an estimated value representing the compressor outlet refrigerant temperature. Thus, the estimated values ​​of the compressor outlet refrigerant temperature at multiple moments constitute the signal waveform of the compressor outlet refrigerant temperature. The specific processing algorithm used in the existing technology refers to a filtering algorithm, which specifically updates the output estimated value by limiting the fluctuation rate of the sampled values.

[0004] Furthermore, existing filtering algorithms limit the fluctuation rate of sampled values ​​to update the output estimate, which can cause distortion in the signal waveform of the compressor outlet refrigerant temperature. For example, if the fluctuation rate is limited to a large value, it may cause signal glitches to be output along with the signal, resulting in poor filtering effect. If the fluctuation rate is limited to a small value, it may cause the filtered signal to be distorted, resulting in poor filtering effect as well.

[0005] Therefore, due to the existing filtering algorithms, the calculation process for the compressor outlet refrigerant temperature has the disadvantages of signal distortion and inability to filter out glitches. Summary of the Invention

[0006] The purpose of this application is to provide a method, apparatus, electronic device, and storage medium for calculating the refrigerant temperature at the compressor outlet, thereby synchronizing the signal waveform of the refrigerant temperature at the compressor outlet with the sampled value waveform. Furthermore, it is used to filter out glitch-prone sampled values.

[0007] In a first aspect, the present invention provides a method for calculating the refrigerant temperature at the outlet of a compressor, the method comprising:

[0008] The Kalman filter coefficient is calculated based on the temperature measurement error coefficient of the temperature sensor at the current moment and the estimated error coefficient of the temperature sensor at the previous moment. The Kalman filter coefficient is greater than 0 and less than 1. The larger the temperature measurement error coefficient of the temperature sensor at the current moment, the smaller the Kalman filter coefficient.

[0009] The estimated temperature of the refrigerant at the compressor outlet at the current moment is calculated based on the previous estimated temperature value of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. The smaller the Kalman filter coefficient, the smaller the proportion of the current sampled value of the temperature sensor in the calculation, and the larger the proportion of the previous estimated temperature value of the refrigerant at the compressor outlet in the calculation.

[0010] In the first aspect of this application, during the calculation of the current estimated temperature of the refrigerant at the compressor outlet based on the previous estimated temperature of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficients, there is no limitation on the fluctuation rate of the current sampled value of the temperature sensor. Instead, the Kalman filter coefficients are used to ensure that the current estimated temperature of the refrigerant at the compressor outlet is always calculated based on the current sampled value of the temperature sensor, while keeping the measurement error of the current sampled value of the temperature sensor small. This keeps the estimated temperature of the refrigerant at the compressor outlet synchronized with the current sampled value of the temperature sensor. That is, when the current sampled value of the temperature sensor is updated, the current estimated temperature of the refrigerant at the compressor outlet is also updated, thereby avoiding distortion of the current estimated temperature of the refrigerant at the compressor outlet. On the other hand, by using the Kalman filter coefficients, when the temperature measurement error coefficient of the temperature sensor at the current moment is large, the calculation proportion of the current sampling value of the temperature sensor is smaller, and the calculation proportion of the previous estimated temperature value of the refrigerant at the compressor outlet is larger. In particular, when the temperature measurement error coefficient of the temperature sensor at the current moment is very large, such that the current sampling value of the temperature sensor is a glitch, the Kalman filter coefficient is close to 0, and thus the calculation proportion of the current sampling value of the temperature sensor is close to 0. This ensures that the current estimated temperature value of the refrigerant at the compressor outlet is calculated only based on the previous estimated temperature value of the refrigerant at the compressor outlet, and is unrelated to the current sampling value of the temperature sensor. Ultimately, this avoids the current estimated temperature value of the refrigerant at the compressor outlet becoming a glitch as the current sampling value of the temperature sensor is updated. In other words, during the process of updating the current estimated temperature value of the refrigerant at the compressor outlet as the current sampling value of the temperature sensor is updated, the situation where the current estimated temperature value of the refrigerant at the compressor outlet is a glitch is filtered out, thereby reducing the adverse impact of the temperature sampling value on the thermal management system.

[0011] In an optional implementation, the formula for calculating the Kalman filter coefficients based on the relative proportion of the temperature measurement error coefficient at the current moment and the estimated error coefficient at the previous moment, according to the temperature sensor, is as follows:

[0012]

[0013] Among them, K k e1 represents the Kalman filter coefficients. k e2 represents the temperature measurement error coefficient of the temperature sensor at the current moment. k-1 This represents the estimation error coefficient of the temperature sensor at the previous moment.

[0014] This optional implementation can calculate the Kalman filter coefficients based on the above formula.

[0015] In an optional implementation, the formula for calculating the current temperature estimate of the compressor outlet refrigerant based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficients is as follows:

[0016] T k =T k-1 +K k *(Z k -T k-1 );

[0017] Among them, T k T represents the estimated current temperature of the refrigerant at the compressor outlet. k-1 Z represents the estimated temperature of the refrigerant at the compressor outlet at the previous moment. k This represents the current sampled value of the temperature sensor.

[0018] This optional implementation can calculate the estimated current temperature of the refrigerant at the compressor outlet using the above calculation formula. By combining the Kalman filter coefficient, when the temperature measurement error coefficient of the temperature sensor at the current moment is small, the estimated current temperature of the refrigerant at the compressor outlet is the current sampled value of the temperature sensor. When the estimation error coefficient of the temperature sensor at the previous moment is small, the estimated current temperature of the refrigerant at the compressor outlet is the estimated temperature of the refrigerant at the previous moment.

[0019] In an optional implementation, the method further includes:

[0020] The previous time-time estimation error coefficient of the temperature sensor is updated based on the Kalman filter coefficients to obtain the current time-time estimation error coefficient of the temperature sensor.

[0021] This optional implementation can update the previous time-estimation error coefficient of the temperature sensor based on the Kalman filter coefficients to obtain the current time-estimation error coefficient of the temperature sensor.

[0022] In an optional implementation, the calculation formula for updating the previous time-to-date estimation error coefficient of the temperature sensor based on the Kalman filter coefficients to obtain the current time-to-date estimation error coefficient of the temperature sensor is as follows:

[0023] e2 k = (1-K) k )*e2 k-1 ;

[0024] Among them, e2 k e2 represents the current time estimation error coefficient of the temperature sensor. k-1K represents the estimation error coefficient of the temperature sensor at the previous moment. k The Kalman filter coefficients are represented.

[0025] This optional implementation method can calculate the current time of the temperature sensor and estimate the error coefficient using the above calculation formula.

[0026] In an optional implementation, the method further includes:

[0027] Determine the RT meter of the temperature sensor;

[0028] The temperature measurement error coefficient of the temperature sensor at the current moment is retrieved from the RT table of the temperature sensor.

[0029] This optional implementation determines the RT table of the temperature sensor, and then queries the temperature measurement error coefficient of the temperature sensor at the current time based on the RT table of the temperature sensor.

[0030] In an optional implementation, determining the RT meter of the temperature sensor includes:

[0031] The RT table of the temperature sensor is determined based on the type of the temperature sensor.

[0032] This optional implementation can determine the RT table of the temperature sensor based on the type of the temperature sensor, thereby determining the temperature measurement error coefficient of the temperature sensor at the current moment.

[0033] In a second aspect, the present invention provides a compressor outlet refrigerant temperature calculation device, the device comprising:

[0034] The first calculation module is used to calculate the Kalman filter coefficient based on the temperature measurement error coefficient of the temperature sensor at the current moment and the estimated error coefficient of the temperature sensor at the previous moment. The Kalman filter coefficient is greater than 0 and less than 1. The larger the temperature measurement error coefficient of the temperature sensor at the current moment, the smaller the Kalman filter coefficient.

[0035] The second calculation module is used to calculate the current temperature estimate of the refrigerant at the compressor outlet based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. The smaller the Kalman filter coefficient, the smaller the proportion of the calculation of the current sampled value of the temperature sensor, and the larger the proportion of the calculation of the previous temperature estimate of the refrigerant at the compressor outlet.

[0036] In the second aspect of this application, during the calculation of the current temperature estimate of the refrigerant at the compressor outlet based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient, there is no limitation on the fluctuation rate of the current sampled value of the temperature sensor. Instead, the Kalman filter coefficient is used to ensure that the current temperature estimate of the refrigerant at the compressor outlet is always calculated based on the current sampled value of the temperature sensor, provided that the measurement error of the current sampled value of the temperature sensor is small. This keeps the estimate synchronized with the current sampled value of the temperature sensor. That is, when the current sampled value of the temperature sensor is updated, the current temperature estimate of the refrigerant at the compressor outlet is also updated, thereby avoiding distortion of the current temperature estimate of the refrigerant at the compressor outlet. On the other hand, by using the Kalman filter coefficients, when the temperature measurement error coefficient of the temperature sensor at the current moment is large, the calculation proportion of the current sampling value of the temperature sensor is smaller, and the calculation proportion of the previous estimated temperature value of the refrigerant at the compressor outlet is larger. In particular, when the temperature measurement error coefficient of the temperature sensor at the current moment is very large, such that the current sampling value of the temperature sensor is a glitch, the Kalman filter coefficient is close to 0, and thus the calculation proportion of the current sampling value of the temperature sensor is close to 0. This ensures that the current estimated temperature value of the refrigerant at the compressor outlet is calculated only based on the previous estimated temperature value of the refrigerant at the compressor outlet, and is unrelated to the current sampling value of the temperature sensor. Ultimately, this avoids the current estimated temperature value of the refrigerant at the compressor outlet becoming a glitch as the current sampling value of the temperature sensor is updated. In other words, during the process of updating the current estimated temperature value of the refrigerant at the compressor outlet as the current sampling value of the temperature sensor is updated, the situation where the current estimated temperature value of the refrigerant at the compressor outlet is a glitch is filtered out, thereby reducing the adverse impact of the temperature sampling value on the thermal management system.

[0037] Thirdly, the present invention provides an electronic device, comprising:

[0038] Processor; and

[0039] The memory is configured to store machine-readable instructions that, when executed by the processor, perform the compressor outlet refrigerant temperature calculation method as described in any of the foregoing embodiments.

[0040] The electronic device of the third aspect of this application, by executing the compressor outlet refrigerant temperature calculation method, can avoid glitches in the waveform of the temperature estimate while keeping the waveform of the temperature estimate synchronized with the temperature sample value without distortion under normal temperature sample value conditions, thereby reducing the adverse effects of the temperature sample value on the thermal management system.

[0041] Fourthly, the present invention provides a storage medium storing a computer program, the computer program being executed by a processor using the compressor outlet refrigerant temperature calculation method as described in any of the foregoing embodiments.

[0042] The storage medium of the fourth aspect of this application, by executing the compressor outlet refrigerant temperature calculation method, can avoid glitches in the waveform of the temperature estimate while keeping the waveform of the temperature estimate synchronized with the temperature sample value without distortion under normal temperature sample value conditions, thereby reducing the adverse effects of the temperature sample value on the thermal management system. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating a method for calculating the refrigerant temperature at the compressor outlet, as disclosed in an embodiment of this application.

[0045] Figure 2 This is a schematic diagram of the structure of a compressor outlet refrigerant temperature calculation device disclosed in an embodiment of this application;

[0046] Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. Detailed Implementation

[0047] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0048] Example 1

[0049] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for calculating the refrigerant temperature at the compressor outlet, as disclosed in an embodiment of this application. Figure 1 As shown, the method in this application embodiment includes the following steps:

[0050] 101. Calculate the Kalman filter coefficient based on the temperature measurement error coefficient of the temperature sensor at the current moment and the estimated error coefficient of the temperature sensor at the previous moment. The Kalman filter coefficient is greater than 0 and less than 1. The larger the temperature measurement error coefficient of the temperature sensor at the current moment, the smaller the Kalman filter coefficient.

[0051] 102. Calculate the current temperature estimate of the refrigerant at the compressor outlet based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. The smaller the Kalman filter coefficient, the smaller the proportion of the current sampled value of the temperature sensor in the calculation, and the larger the proportion of the previous temperature estimate of the refrigerant at the compressor outlet in the calculation.

[0052] In this embodiment, during the calculation of the current temperature estimate of the refrigerant at the compressor outlet based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient, there is no limitation on the fluctuation rate of the current sampled value of the temperature sensor. Instead, the Kalman filter coefficient is used to ensure that the current temperature estimate of the refrigerant at the compressor outlet is always calculated based on the current sampled value of the temperature sensor, while keeping the measurement error of the current sampled value of the temperature sensor small. This keeps the estimate synchronized with the current sampled value of the temperature sensor; that is, once the current sampled value of the temperature sensor is updated, the current temperature estimate of the refrigerant at the compressor outlet is also updated, thus avoiding distortion of the current temperature estimate of the refrigerant at the compressor outlet. On the other hand, by using the Kalman filter coefficients, when the temperature measurement error coefficient of the temperature sensor at the current moment is large, the calculation proportion of the current sampling value of the temperature sensor is smaller, and the calculation proportion of the previous moment's estimated temperature of the refrigerant at the compressor outlet is larger. In particular, when the temperature measurement error coefficient of the temperature sensor at the current moment is very large, that is, when the current sampling value of the temperature sensor is a glitch, the Kalman filter coefficient is close to 0, and thus the calculation proportion of the current sampling value of the temperature sensor is close to 0. This ensures that the current moment's estimated temperature of the refrigerant at the compressor outlet is calculated only based on the previous moment's estimated temperature of the refrigerant at the compressor outlet, and is unrelated to the current moment's sampling value of the temperature sensor. Ultimately, this avoids the current moment's estimated temperature of the refrigerant at the compressor outlet becoming a glitch as the current moment's sampling value of the temperature sensor is updated. In other words, during the process of updating the current moment's estimated temperature of the refrigerant at the compressor outlet as the current moment's sampling value of the temperature sensor is updated, the situation where the current moment's estimated temperature of the refrigerant at the compressor outlet is a glitch is filtered out, thereby reducing the adverse impact of the temperature sampling value on the thermal management system.

[0053] In this embodiment of the application, the temperature sensor can be a thermal resistance temperature sensor, wherein the resistance value of the thermal resistance temperature sensor has a corresponding relationship with the temperature of the object being detected. This correspondence is the RT characteristic of the thermal resistance temperature sensor. Based on the RT characteristic of the thermal resistance temperature sensor, after calculating the resistance value of the thermal resistance temperature sensor, a value can be obtained by looking up the resistance value in the RT characteristic table, and the obtained value can be used as the temperature sampling value.

[0054] Furthermore, the resistance value of the thermal resistance temperature sensor is calculated based on the voltage of the thermal resistance temperature sensor.

[0055] Furthermore, the error of the temperature sampling value of the temperature sensor is represented by the temperature measurement error coefficient, which is also recorded in the RT characteristic table to illustrate the degree of error of the temperature sampling value.

[0056] Furthermore, the magnitude of the temperature measurement error coefficient is related to the accuracy of the temperature sensor. Under specific conditions, the higher the accuracy of the temperature sensor, the stronger its ability to detect signal sources. Therefore, in addition to detecting the original temperature signal source, it can also detect noise signals. Consequently, the temperature sample value includes both the numerical part determined based on the original temperature sample signal and the numerical part determined based on the noise signal. Moreover, the higher the accuracy of the temperature sensor, the greater the influence of the noise signal, and the larger the proportion of the numerical part determined based on the noise signal in the temperature sample value, thus resulting in a larger temperature measurement error coefficient.

[0057] Furthermore, the larger the temperature measurement error coefficient corresponding to a temperature sample value, the sharper the temperature sample value will be in the sample value waveform, that is, the temperature sample value will appear as a spike in the sample value waveform.

[0058] Furthermore, after obtaining the temperature sampling value, it is also necessary to output a temperature estimate based on the temperature sampling value to estimate the true temperature of the object being detected. In this regard, for the existing technology, the larger the temperature measurement error coefficient of the temperature sampling value, the sharper the temperature estimate calculated based on the temperature sampling value will be in the estimated value waveform, that is, the temperature estimate will appear as a spike in the estimated value waveform.

[0059] Furthermore, the filtering out of burrs emphasized in the embodiments of this application refers to the smoothing of burrs in the estimated waveform. When the temperature measurement error coefficient is large, the temperature sampling value manifested as burrs has virtually no impact on the temperature estimated value. Therefore, the temperature estimated value will not be updated with the temperature sampling value manifested as burrs.

[0060] In an optional implementation, the formula for calculating the Kalman filter coefficients based on the current temperature measurement error coefficient and the previous estimation error coefficient of the temperature sensor is as follows:

[0061]

[0062] Among them, K k e1 represents the Kalman filter coefficients. k e2 represents the temperature measurement error coefficient of the temperature sensor at the current moment. k-1 This represents the estimation error coefficient of the temperature sensor at the previous moment.

[0063] This optional implementation can calculate the Kalman filter coefficients based on the above formula.

[0064] In an optional implementation, the formula for calculating the current estimated temperature of the refrigerant at the compressor outlet, based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient, is as follows:

[0065] T k =T k-1 +K k *(Z k -T k-1 );

[0066] Among them, T k T represents the estimated current temperature of the refrigerant at the compressor outlet. k-1 Z represents the estimated temperature of the refrigerant at the compressor outlet at the previous moment. k This represents the current sample value from the temperature sensor.

[0067] This optional implementation can calculate the estimated temperature of the refrigerant at the compressor outlet using the above calculation formula. Then, by combining the Kalman filter coefficient, it can achieve the following: when the temperature measurement error coefficient of the temperature sensor at the current moment is small, the estimated temperature of the refrigerant at the compressor outlet is the sampled value of the temperature sensor at the current moment; and when the estimation error coefficient of the temperature sensor at the previous moment is small, the estimated temperature of the refrigerant at the compressor outlet is the estimated temperature of the refrigerant at the previous moment.

[0068] In an optional implementation, the method of this application embodiment further includes the following steps:

[0069] The previous time-time estimation error coefficient of the temperature sensor is updated based on the Kalman filter coefficients to obtain the current time-time estimation error coefficient of the temperature sensor.

[0070] This optional implementation can update the previous time-estimation error coefficient of the temperature sensor based on the Kalman filter coefficients to obtain the current time-estimation error coefficient of the temperature sensor.

[0071] In an optional implementation, the previous time-time estimation error coefficient of the temperature sensor is updated based on the Kalman filter coefficients to obtain the calculation formula corresponding to the current time-time estimation error coefficient of the temperature sensor:

[0072] e2 k = (1-K) k )*e2 k-1 ;

[0073] Among them, e2 k e2 represents the current time estimation error coefficient of the temperature sensor.k-1 K represents the estimation error coefficient of the temperature sensor at the previous moment. k This represents the Kalman filter coefficients.

[0074] This optional implementation method can calculate the current time of the temperature sensor and estimate the error coefficient using the above calculation formula.

[0075] In an optional implementation, the method of this application embodiment further includes the following steps:

[0076] Determine the RT meter of the temperature sensor;

[0077] The RT table based on the temperature sensor is used to query the temperature measurement error coefficient of the temperature sensor at the current moment.

[0078] This optional implementation determines the RT table of the temperature sensor, and then can query the temperature measurement error coefficient of the temperature sensor at the current time based on the RT table of the temperature sensor.

[0079] In an optional implementation, determining the RT meter of the temperature sensor includes the following sub-steps:

[0080] The RT table of the temperature sensor is determined based on the type of temperature sensor.

[0081] This optional implementation can determine the RT table of the temperature sensor based on the type of temperature sensor, thereby determining the temperature measurement error coefficient of the temperature sensor at the current moment.

[0082] Example 2

[0083] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a compressor outlet refrigerant temperature calculation device disclosed in an embodiment of this application, as shown below. Figure 2 As shown, the apparatus in this embodiment includes the following functional modules:

[0084] The first calculation module 201 is used to calculate the Kalman filter coefficients based on the temperature measurement error coefficient of the temperature sensor at the current moment and the estimated error coefficient of the temperature sensor at the previous moment.

[0085] The second calculation module 202 is used to calculate the current temperature estimate of the refrigerant at the compressor outlet based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. The Kalman filter coefficient is used to make the current temperature estimate of the refrigerant at the compressor outlet the current sampled value of the temperature sensor when the current temperature measurement error coefficient of the temperature sensor is small, and to make the current temperature estimate of the refrigerant at the compressor outlet the previous temperature estimate when the previous estimation error coefficient of the temperature sensor is small.

[0086] This application embodiment can calculate the Kalman filter coefficient based on the current temperature measurement error coefficient and the previous estimation error coefficient of the temperature sensor, and calculate the current temperature estimate of the refrigerant at the compressor outlet based on the previous estimated temperature value of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. In this way, when the current temperature measurement error coefficient of the temperature sensor is small, the current estimated temperature of the refrigerant at the compressor outlet is the current sampled value of the temperature sensor, and when the previous estimation error coefficient of the temperature sensor is small, the current estimated temperature of the refrigerant at the compressor outlet is the previous estimated temperature value of the refrigerant at the compressor outlet. This can achieve the filtering out of glitches while maintaining the original input signal waveform, and prevent sudden changes in the temperature sensor sampling signal from affecting the thermal management system.

[0087] Example 3

[0088] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application, such as... Figure 3 As shown, the electronic device in this application embodiment includes:

[0089] Processor 301; and

[0090] The memory 302 is configured to store machine-readable instructions that, when executed by a processor, perform a compressor outlet refrigerant temperature calculation method as described in any of the foregoing embodiments.

[0091] The electronic device in this application embodiment, by executing the compressor outlet refrigerant temperature calculation method, can calculate the Kalman filter coefficient based on the current temperature measurement error coefficient and the previous estimation error coefficient of the temperature sensor, and calculate the current temperature estimate of the compressor outlet refrigerant based on the previous temperature estimate, the current sampled value of the temperature sensor, and the Kalman filter coefficient. In this way, when the current temperature measurement error coefficient of the temperature sensor is small, the current temperature estimate of the compressor outlet refrigerant is the current sampled value of the temperature sensor; and when the previous estimation error coefficient of the temperature sensor is small, the current temperature estimate of the compressor outlet refrigerant is the previous temperature estimate. This enables the filtering out of glitches while preserving the original input signal waveform, preventing sudden changes in the temperature sensor sampling signal from affecting the thermal management system.

[0092] Example 4

[0093] Fourthly, the present invention provides a storage medium storing a computer program, which is executed by a processor as described in any of the foregoing embodiments, a method for calculating the refrigerant temperature at the compressor outlet.

[0094] The storage medium in this embodiment of the application executes a method for calculating the refrigerant temperature at the compressor outlet. This method calculates Kalman filter coefficients based on the current temperature measurement error coefficient and the previous estimation error coefficient of the temperature sensor. It also calculates the current estimated temperature of the refrigerant at the compressor outlet based on the previous estimated temperature, the current sampled value of the temperature sensor, and the Kalman filter coefficients. Thus, when the current temperature measurement error coefficient of the temperature sensor is small, the current estimated temperature of the refrigerant at the compressor outlet is the current sampled value of the temperature sensor. Conversely, when the previous estimation error coefficient of the temperature sensor is small, the current estimated temperature of the refrigerant at the compressor outlet is the previous estimated temperature. This allows for the filtering out of glitches while preserving the original input signal waveform, preventing sudden changes in the temperature sensor sampling signal from affecting the thermal management system.

[0095] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0096] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0098] It should be noted that if a function is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0099] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0100] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method of calculating a refrigerant temperature at a compressor outlet, characterized by, The method includes: The Kalman filter coefficient is calculated based on the temperature measurement error coefficient of the temperature sensor at the current moment and the estimated error coefficient of the temperature sensor at the previous moment. The Kalman filter coefficient is greater than 0 and less than 1. The larger the temperature measurement error coefficient of the temperature sensor at the current moment, the smaller the Kalman filter coefficient. The estimated temperature of the refrigerant at the compressor outlet at the current moment is calculated based on the previous estimated temperature value of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. The smaller the Kalman filter coefficient, the smaller the proportion of the calculation based on the current sampled value of the temperature sensor, and the larger the proportion of the calculation based on the previous estimated temperature value of the refrigerant at the compressor outlet. Specifically, when the measurement error of the current sampled value of the temperature sensor is small, the estimated temperature of the refrigerant at the current moment is always calculated based on the current sampled value of the temperature sensor. Conversely, when the measurement error coefficient of the current temperature sensor is large, the proportion of the calculation based on the current sampled value of the temperature sensor is smaller, and the proportion of the calculation based on the previous estimated temperature value of the refrigerant at the compressor outlet is larger, ensuring that the estimated temperature of the refrigerant at the current moment is calculated solely based on the previous estimated temperature value of the refrigerant at the compressor outlet, and is independent of the current sampled value of the temperature sensor. Furthermore, the formula for calculating the Kalman filter coefficients based on the relative proportion of the current temperature measurement error coefficient and the previous estimated error coefficient of the temperature sensor is as follows: ； wherein, represents the Kalman filter coefficient, represents the current time temperature measurement error coefficient of the temperature sensor, represents the previous time estimation error coefficient of the temperature sensor; Furthermore, the formula for calculating the current temperature estimate of the compressor outlet refrigerant based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficients is as follows: ； in, This represents the estimated current temperature of the refrigerant at the compressor outlet. This represents the estimated temperature of the refrigerant at the compressor outlet at the previous moment. This represents the current sample value of the temperature sensor.

2. The method as described in claim 1, characterized in that, The method further includes: The previous time-time estimation error coefficient of the temperature sensor is updated based on the Kalman filter coefficients to obtain the current time-time estimation error coefficient of the temperature sensor.

3. The method as described in claim 2, characterized in that, The formula for updating the previous time-based estimation error coefficient of the temperature sensor based on the Kalman filter coefficients to obtain the current time-based estimation error coefficient of the temperature sensor is as follows: ； in, This indicates the current estimated error coefficient of the temperature sensor. This represents the estimation error coefficient of the temperature sensor at the previous moment. The Kalman filter coefficients are represented.

4. The method as described in claim 1, characterized in that, The method further includes: Determine the RT meter of the temperature sensor; The temperature measurement error coefficient of the temperature sensor at the current moment is retrieved from the RT table of the temperature sensor.

5. The method as described in claim 4, characterized in that, The determination of the RT table of the temperature sensor includes: The RT table of the temperature sensor is determined based on the type of the temperature sensor.

6. A compressor outlet refrigerant temperature calculation device, characterized in that, The device includes: The first calculation module is used to calculate the Kalman filter coefficient based on the temperature measurement error coefficient of the temperature sensor at the current moment and the estimated error coefficient of the temperature sensor at the previous moment. The Kalman filter coefficient is greater than 0 and less than 1. The larger the temperature measurement error coefficient of the temperature sensor at the current moment, the smaller the Kalman filter coefficient. The second calculation module is used to calculate the estimated temperature of the refrigerant at the compressor outlet at the current moment based on the previous estimated temperature value of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficient. The smaller the Kalman filter coefficient, the smaller the proportion of the calculation based on the current sampled value of the temperature sensor, and the larger the proportion of the calculation based on the previous estimated temperature value of the refrigerant at the compressor outlet. Specifically, when the measurement error of the current sampled value of the temperature sensor is small, the estimated temperature of the refrigerant at the current moment is always calculated based on the current sampled value of the temperature sensor. Conversely, when the measurement error coefficient of the current temperature sensor is large, the proportion of the calculation based on the current sampled value of the temperature sensor is smaller, and the proportion of the calculation based on the previous estimated temperature value of the refrigerant at the compressor outlet is larger, so that the estimated temperature of the refrigerant at the current moment is calculated solely based on the previous estimated temperature value of the refrigerant at the compressor outlet, and is independent of the current sampled value of the temperature sensor. Furthermore, the formula for calculating the Kalman filter coefficients based on the relative proportion of the current temperature measurement error coefficient and the previous estimated error coefficient of the temperature sensor is as follows: ； in, Represents the Kalman filter coefficients, This represents the temperature measurement error coefficient of the temperature sensor at the current moment. This represents the estimation error coefficient of the temperature sensor at the previous moment; Furthermore, the formula for calculating the current temperature estimate of the compressor outlet refrigerant based on the previous temperature estimate of the refrigerant at the compressor outlet, the current sampled value of the temperature sensor, and the Kalman filter coefficients is as follows: ； in, This represents the estimated current temperature of the refrigerant at the compressor outlet. This represents the estimated temperature of the refrigerant at the compressor outlet at the previous moment. This represents the current sample value of the temperature sensor.

7. An electronic device, characterized in that, include: processor; as well as The memory is configured to store machine-readable instructions that, when executed by the processor, perform the compressor outlet refrigerant temperature calculation method as described in any one of claims 1-5.

8. A storage medium, characterized in that, The storage medium stores a computer program, which is executed by a processor according to the compressor outlet refrigerant temperature calculation method as described in any one of claims 1-5.

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