MTPV curve calibration method and system

Abstract

The application provides an MTPV curve calibration method and system, and the MTPV curve calibration method comprises the following steps: based on the torque data obtained by testing the motor on a test bench, current-flux data group and current-torque data group are calculated; the first current corresponding to the maximum torque in the MTPA curve is input to the current-flux data group to obtain the first flux value corresponding to the first current, the turning speed under the condition that the voltage utilization rate is 1 at the first flux value, and the target flux value under the turning speed is calculated; the current-flux points with a flux value difference less than a threshold value from the target flux value are found in the current-flux data group, and the torque maximum point in all current-flux points is extracted as the MTPV point. After the above technical scheme is adopted, the MTPV curve obtained is smooth without fluctuation, and the feedback current in the MTPV region is basically consistent with the prediction.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of electric vehicle control, in particular to a MTPV curve calibration method and system. BACKGROUND

[0002] MTPV control mode, namely Maximum Torque-per-Voltage (MTPV), means that the torque generated by the stator voltage with a certain amplitude is maximum under the control mode, which is equivalent to the corresponding same electromagnetic torque, and the required stator voltage is minimum under the mode, and the corresponding motor iron loss is also minimum. In addition to the characteristic of minimum voltage, the amplitude of the stator flux of the working point corresponding to MTPV is also minimum. MTPV control can improve the torque output capability of the motor under unit stator voltage, so it is particularly important to define the MTPV curve.

[0003] Traditionally, MTPV curve needs to be finely calibrated on a test bench, and there are the following several calibration methods:

[0004] 1. Manually input current Id and Iq to the motor, and record the torque value by visual observation, under this calibration method, the recording accuracy is not high, the operation of manual calibration method is frequent, occupies a long time, and some human operation errors may occur;

[0005] 2. Through an automatic calibration platform, iteratively input current Iq and Id at different speeds, and find the MTPV curve based on the iterative data, under this calibration method, a long time is still occupied.

[0006] Therefore, a new MTPV curve calibration method is needed, which can greatly reduce the calibration time and avoid human operation errors. SUMMARY

[0007] In order to overcome the above technical defects, the purpose of the present application is to provide a MTPV curve calibration method and system, which obtains a smooth and undulating MTPV curve, and the feedback current in the MTPV region is basically consistent with the prediction.

[0008] The present application discloses a MTPV curve calibration method, comprising the following steps:

[0009] Based on the torque data obtained by testing the motor on the test bench, the current-flux data set and the current-torque data set are calculated;

[0010] The first current corresponding to the maximum torque in the MTPA curve is input to the current-flux data set to obtain the first flux value corresponding to the first current, and the turning speed when the voltage utilization rate is 1 under the first flux value, and the target flux value under the turning speed is calculated;

[0011] traverse the current-flux data set to find a current-flux point with a difference from the target flux value less than a threshold value, and extract a torque maximum point among all current-flux points as the MTPV point.

[0012] Preferably, the step of calculating the current-flux data set and the current-torque data set based on the torque data obtained by testing the motor on the test bench comprises:

[0013] obtaining torque data obtained by testing the motor on the test bench at different test speeds;

[0014] extracting d-axis voltage Ud, q-axis voltage Uq, d-axis current Id, and q-axis current Iq corresponding to each torque in the torque data;

[0015] for each torque, calculating the square sum of d-axis voltage Ud and q-axis voltage Uq, and dividing the square sum by the test speed corresponding to the torque to form the current-flux data set;

[0016] for each torque, arranging d-axis current Id and q-axis current Iq in ascending order to form the current-torque data set;

[0017] linearly interpolating the current-flux data set and the current-torque data set with 1A as the unit current.

[0018] Preferably, the step of inputting the first current corresponding to the maximum torque in the MTPA curve into the current-flux data set to obtain the first flux value corresponding to the first current, and the turning speed at which the voltage utilization rate is 1 at the first flux value, and calculating the target flux value at the turning speed comprises:

[0019] extracting calibrated data in the MTPA curve, wherein the calibrated data includes maximum torques at different test speeds and first currents corresponding to the maximum torques;

[0020] inputting the first current into the current-flux data set, and obtaining the first flux value corresponding to the first current by linear interpolation;

[0021] based on the motor controller controlling the motor to operate at a rated voltage, recording the speed value at which the voltage utilization rate is 1 as the turning speed;

[0022] based on a preset speed step, dividing the rated voltage by each test speed to calculate the target flux value corresponding to each test speed from the turning speed to the peak speed of the motor.

[0023] Preferably, the step of traversing the current-flux data set to find a current-flux point with a difference from the target flux value less than a threshold value, and extracting a torque maximum point among all current-flux points as the MTPV point comprises:

[0024] traversing the current-flux linkage data set to find current-flux linkage points with a difference from the target flux linkage value less than a threshold value and storing as an extraction array, wherein the extraction array includes d-axis current Id, q-axis current Iq and corresponding torque;

[0025] comparing all data in the extraction array and recording a point with a maximum torque value as the MTPV point.

[0026] Preferably, the step of traversing the current-flux linkage data set to find current-flux linkage points with a difference from the target flux linkage value less than a threshold value and extracting a maximum torque point in all current-flux linkage points as the MTPV point further comprises:

[0027] recording a point with a maximum d-axis current Id in all MTPV points as a starting point;

[0028] judging whether a d-axis current Id of a next MTPV point adjacent to a previous MTPV point from the starting point is less than the d-axis current Id of the previous MTPV point;

[0029] when the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, connecting adjacent MTPV points to fit a MTPV curve;

[0030] when the d-axis current Id of any or arbitrary next MTPV point is greater than or equal to the d-axis current Id of the previous MTPV point, subtracting a preset difference value from a maximum torque value to obtain a second maximum torque value, finding MTPV points between the second maximum torque value and the maximum torque value, and extracting a point closest to a point with a maximum d-axis current Id from the found MTPV points as an updated starting point,

[0031] replacing the updated starting point with the starting point and again judging whether a d-axis current Id of a next MTPV point adjacent to a previous MTPV point from the updated starting point is less than the d-axis current Id of the previous MTPV point until the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, and connecting adjacent MTPV points to fit a MTPV curve.

[0032] Preferably, the MTPV curve calibration method further comprises the following steps:

[0033] based on the MTPV curve, calculating motor external characteristic data at each operating voltage of the motor according to the flux linkage principle.

[0034] The application also discloses a MTPV curve calibration system, comprising a test bench and a processing module,

[0035] based on torque data obtained by testing the motor by the test bench, the processing module calculates a current-flux linkage data set and a current-torque data set;

[0036] The processing module inputs the first current corresponding to the maximum torque in the MTPA curve into the current-flux linkage data set to obtain a first flux linkage value corresponding to the first current, a turning speed at which the voltage utilization is 1 under the first flux linkage value, and a target flux linkage value at the turning speed;

[0037] The processing module traverses the current-flux linkage data set to find current-flux linkage points with a difference from the target flux linkage value less than a threshold value, and extracts a torque maximum point in all current-flux linkage points as an MTPV point.

[0038] Preferably, the processing module obtains torque data obtained by testing the motor at different test speeds on a test bench;

[0039] The processing module extracts a d-axis voltage Ud, a q-axis voltage Uq, a d-axis current Id, and a q-axis current Iq corresponding to each torque in the torque data;

[0040] For each torque, the processing module calculates the square sum of the d-axis voltage Ud and the q-axis voltage Uq, and divides the square sum by a test speed corresponding to the torque to form a current-flux linkage data set;

[0041] For each torque, the processing module arranges the d-axis current Id and the q-axis current Iq in ascending order to form a current-torque data set;

[0042] The processing module linearly interpolates the current-flux linkage data set and the current-torque data set by 1A as a unit current.

[0043] Preferably, the processing module extracts calibrated data in the MTPA curve, wherein the calibrated data includes maximum torques at different test speeds and corresponding first currents;

[0044] The processing module inputs the first current into the current-flux linkage data set, and obtains a first flux linkage value corresponding to the first current by linear interpolation;

[0045] Based on the motor controller processing module, the motor is controlled to operate at a rated voltage, and a speed value at which the voltage utilization is 1 is recorded as a turning speed;

[0046] Based on a preset speed step, the processing module divides the rated voltage by each test speed to calculate a target flux linkage value corresponding to each test speed from the turning speed to a peak speed of the motor.

[0047] Preferably, the processing module traverses the current-flux linkage data set to find current-flux linkage points with a difference from the target flux linkage value less than a threshold value, and stores the current-flux linkage points as an extraction array, wherein the extraction array includes a d-axis current Id, a q-axis current Iq, and a corresponding torque;

[0048] The processing module compares all data in the extraction array, and records a point corresponding to the d-axis current Id and the q-axis current Iq at which the maximum torque value is located as an MTPV point;

[0049] The processing module records a point with the maximum d-axis current Id among all MTPV points as a starting point;

[0050] The processing module judges whether the d-axis current Id of a next MTPV point adjacent to a previous MTPV point is less than the d-axis current Id of the previous MTPV point from the starting point;

[0051] When the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, the processing module connects adjacent MTPV points to fit an MTPV curve;

[0052] When the d-axis current Id of any or arbitrary next MTPV point is greater than or equal to the d-axis current Id of the previous MTPV point, the processing module subtracts a preset difference value from the maximum torque value to obtain a maximum torque value, finds MTPV points between the maximum torque value and the maximum torque value, and extracts a point closest to the point with the maximum d-axis current Id from the found MTPV points as an updated starting point,

[0053] The processing module replaces the starting point with the updated starting point, and again judges whether the d-axis current Id of a next MTPV point adjacent to a previous MTPV point is less than the d-axis current Id of the previous MTPV point from the updated starting point, until the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, and adjacent MTPV points are connected to fit an MTPV curve.

[0054] After the above technical solution is adopted, compared with the prior art, the following beneficial effects are obtained:

[0055] 1. No additional calibration work, which can save calibration time and avoid introducing human calibration errors;

[0056] 2. The obtained MTPV curve is smooth and without fluctuation, and a high-precision external characteristic curve can be directly generated. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 To meet the flowchart of the MTPV curve calibration method in a preferred embodiment of the application;

[0058] Figure 2 To meet the MTPV curve fluctuation and optimization in the MTPV curve calibration method in a preferred embodiment of the application;

[0059] Figure 3 To meet the external characteristic data diagram of the motor based on the MTPV curve in a preferred embodiment of the application. DETAILED DESCRIPTION

[0060] The advantages of the present application are further set forth in the description that follows, and will be appreciated by persons skilled in the art upon reading and understanding the following detailed description.

[0061] Exemplary embodiments are described herein with reference to the accompanying drawings, of which examples are shown. The following detailed description, which discloses exemplary embodiments, is intended to be read in connection with the accompanying drawings, which are described below, and wherein like numerals refer to like components, unless otherwise described. The following description is intended to be read in connection with the drawings and the description of the embodiments disclosed herein, which are intended to be illustrative only and are not intended to be limiting of the disclosure. Rather, the following description is intended to describe illustrative embodiments leading to a full understanding of the various inventive features and advantages thereof.

[0062] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or", as used herein, refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0063] It will be understood that, although the terms first, second, third, etc. can be used herein to describe various information, these terms are not intended to denote a particular order or hierarchy among the information. Rather, these terms are used only to distinguish one from another. For example, a first information can be termed a second information, and, similarly, a second information can be termed a first information, without departing from the scope of the present disclosure. As used herein, the term "if' can be interpreted to mean "when" or "upon" or "in response to determining" depending on the context.

[0064] In the description of the present application, it is to be understood that the orientations or positional relationships indicated by the terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like are based on the orientations or positional relationships shown in the drawings, and are for the purpose of facilitating the description of the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore should not be construed as limiting the present application.

[0065] In the description of the present application, unless otherwise specified and limited, it should be explained that the terms "mounting", "connection", "connecting" should be understood broadly, for example, it can be a mechanical connection or an electrical connection, or a communication between two elements, or a direct connection, or an indirect connection through an intermediate medium, and the specific meaning of the above terms can be understood by those skilled in the art according to the specific circumstances.

[0066] In the following description, the suffixes such as "module", "part", or "unit" used for an element are merely intended for facilitating explanation of the present application, and have no special meaning by themselves. Thus, "module" and "part" can be used interchangeably.

[0067] Referring to Figure 1 , in order to meet the flowchart of the MTPV curve calibration method in a preferred embodiment of the present application, in the embodiment, the MTPV curve calibration method comprises the following steps:

[0068] S100: based on the torque data obtained by testing the motor on the test bench, the current-flux data set and the current-torque data set are calculated;

[0069] When the test bench tests the motor (not the separate calibration result of the test bench, but the comprehensive test result), the torque calibration data of the motor is obtained, that is, the source of the original data in the present application can come from the existing data. The torque calibration data is recorded as torque data, and the corresponding current-flux data set and current-torque data set under different torques are extracted from the existing data. "Flux linkage" is the magnetic flux linked by a conducting coil or a current loop. The flux linkage is equal to the product of the number of turns N of the conducting coil and the average magnetic flux φ passing through each turn of the coil, so it is also called magnetic flux turn. The flux linkage is related to the current that establishes the magnetic flux, so the current-flux data set and the current-torque data set respectively reflect the relationship between the current and the flux and the current and the torque.

[0070] S200: input the first current corresponding to the maximum torque in the MTPA curve to the current-flux data set to obtain the first flux value corresponding to the first current, and the turning speed when the voltage utilization rate is 1 under the first flux value, and calculate the target flux value under the turning speed;

[0071] Based on the calibrated MTPA (maximum torque current ratio) curve, the first current corresponding to the maximum torque is input to the current-flux data set, the first flux value corresponding to the first current is obtained, and the turning speed when the voltage utilization rate is 1 under the first flux value is obtained. The voltage utilization rate refers to the ratio of the fundamental wave amplitude of the motor inverter output line voltage to the DC bus voltage. For the motor, since the size and phase of the stator current are certain, the size of the stator magnetic field and the relative position with the rotor are certain, so the size of the air gap synthesis magnetic field is certain. With the increase of the air gap synthesis magnetic field speed, the speed of cutting the stator winding also increases, and the terminal voltage of the motor also increases, until the terminal voltage of the motor reaches the voltage limit of the frequency converter output, and the torque cannot be kept constant and the speed cannot be increased. This highest speed point that keeps the torque constant is called turning speed. At this turning speed, the flux value corresponding to the first current is recorded as the target flux value.

[0072] S300: searching for a current-flux point in the current-flux data set that has a difference with the target flux value less than a threshold value, and extracting a point with maximum torque among all current-flux points as the MTPV point

[0073] Due to the size of the target flux value, it can not be recorded in the current-flux data set, but the MTPV point should be near the current corresponding to the target flux value, therefore, a current-flux point with a difference with the target flux value less than a threshold value (for example, 0.0001) is searched, and all points in the range are stored. Then, a point with maximum torque among all obtained current-flux points is extracted as the MTPV point, that is, it satisfies the maximum torque voltage ratio control mode.

[0074] Through the above configuration, manual calibration or configuration is not required throughout the process, and only the existing data can be used to complete the marking of the MTPV point and the fitting of the MTPV curve (the connection of multiple MTPV points is the MTPV curve).

[0075] In a preferred embodiment, step S100 comprises:

[0076] S110: obtaining torque data obtained by testing the motor at different test speeds of the test bench;

[0077] At different test speeds of the test bench, different torque data under the external characteristics of the motor can be obtained, that is, one test speed can correspond to multiple torque data.

[0078] S120: extracting d-axis voltage Ud, q-axis voltage Uq, d-axis current Id, and q-axis current Iq corresponding to each torque in the torque data;

[0079] In all torque data, d-axis voltage Ud, q-axis voltage Uq, d-axis current Id, and q-axis current Iq corresponding to each torque are obtained. It can be understood that when the torque is represented, the corresponding voltage and current values at that time are also recorded, therefore, d-axis voltage Ud, q-axis voltage Uq, d-axis current Id, and q-axis current Iq can be directly obtained in the torque data.

[0080] S130: for each torque, calculating the square sum of d-axis voltage Ud and q-axis voltage Uq, and then taking the square root and dividing by the test speed corresponding to the torque to form a current-flux data set;

[0081] In order to calculate the flux value corresponding to each current, the square sum of d-axis voltage Ud and q-axis voltage Uq is calculated, and then the square root is taken and divided by the test speed corresponding to the torque.

[0082] S140: for each torque, arranging d-axis current Id and q-axis current Iq in ascending order to form a current-torque data set;

[0083] S150: Linearly interpolating the current-flux data set and the current-torque data set with 1A as a unit current.

[0084] Since the current-flux data set and the current-torque data set rely on the torque calibration data, and the amount of data of the torque calibration data is limited, in step S140 and step S150, the current-flux data set and the current-torque data set are interpolated in a software manner. First, all the data need to be arranged in ascending order according to the d-axis current Id and the q-axis current Iq, and then the existing adjacent current-flux data and current-torque data are linearly interpolated with a small current step (such as 1A as a unit current) to enrich the data of the current-flux data set and the current-torque data set, that is, to simulate the linear change of the data that does not originally have, and when there is a large amount of data, the prediction error can be reduced.

[0085] In another preferred embodiment, step S200 comprises:

[0086] S210: Extracting the calibrated data in the MTPA curve, wherein the calibrated data comprises the maximum torque at different test speeds and the corresponding first current;

[0087] S220: Inputting the first current into the current-flux data set, and obtaining the first flux value corresponding to the first current through linear interpolation;

[0088] It can also be understood that the first current may not have in the original current-flux data set, and therefore the first flux value corresponding to the first current can be calculated through linear interpolation, and the first flux value is also the flux value at the intersection of the MTPA and the current circle.

[0089] S230: Controlling the motor to operate at a rated voltage based on the motor controller, and recording the speed value when the voltage utilization rate is 1 as the turning speed;

[0090] That is, the speed when the voltage utilization rate is 1 under the control of the rated voltage is the turning speed described above.

[0091] S240: Dividing the rated voltage by each test speed based on a preset speed step to calculate the target flux value corresponding to each test speed from the turning speed to the peak speed of the motor.

[0092] The preset speed step can be small, and by dividing the rated voltage by each test speed, a plurality of target flux values are obtained, each target flux value corresponding to each test speed between the turning speed and the peak speed of the motor (a known value of the motor property), to be used as a reference for subsequent searching for the equal flux circle.

[0093] Further, step S300 comprises:

[0094] S310: searching for the current-flux point with the difference value less than a threshold value from the target flux value in the current-flux data set, and storing as an extraction array, wherein the extraction array includes the d-axis current Id, the q-axis current Iq and the corresponding torque;

[0095] Based on the target flux value, all points near the target flux value (the threshold value can be 0.0001) in the current-flux data set are searched and stored as an extraction array.

[0096] S320: comparing all data in the extraction array, and recording the point with the maximum torque as the MTPV point corresponding to the d-axis current Id and the q-axis current Iq.

[0097] To determine whether the fitted MTPV point will cause the MTPV curve to fluctuate, i.e., the curve to fold back, step S300 further includes:

[0098] S330: recording the point with the maximum d-axis current Id in all MTPV points as the starting point, i.e., selecting the point closest to the Iq as the vertical axis in the Id and Iq coordinate axes in all MTPV points as the starting point. It can be understood that the starting point of the MTPV curve is the MTPV point corresponding to the turning speed, which is different from the above-mentioned starting point.

[0099] S340: determining whether the d-axis current Id of the next MTPV point adjacent to the previous MTPV point from the starting point is less than the d-axis current Id of the previous MTPV point.

[0100] That is, determining whether the d-axis current Id of the next MTPV point is less than the d-axis current Id of the previous MTPV point, if so, it indicates that the next MTPV point should be located on the right side of the previous MTPV point in the Id and Iq coordinate axes.

[0101] S350: when the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, it indicates that all next MTPV points are located on the right side of the previous MTPV point, and there is no MTPV point fluctuation, and the adjacent MTPV points are connected to fit a MTPV curve.

[0102] S350': when the d-axis current Id of any one or any subsequent MTPV point is greater than or equal to the d-axis current Id of the previous MTPV point, it indicates that the subsequent MTPV point is located on the left side of the previous MTPV point, which means that the selected MTPV point does not conform to the actual value, then the maximum torque is reduced by a preset difference (for example, it can be 1) to obtain a maximum torque (i.e. a torque value that is only less than the maximum torque as a comparison standard), find the MTPV point between the maximum torque and the maximum torque, and extract the point closest to the point with the maximum d-axis current Id from the found MTPV point as the updated starting point, i.e. repeat the previous step to find the point with the maximum d-axis current Id in all data within a certain range under the maximum torque, and record the point as the MTPV point of this time.

[0103] S360: replace the starting point with the updated starting point, and again determine whether the d-axis current Id of the subsequent MTPV point adjacent to the previous MTPV point from the updated starting point is less than the d-axis current Id of the previous MTPV point, until the d-axis current Id of all subsequent MTPV points is less than the d-axis current Id of the previous MTPV point, then connect the adjacent MTPV points to fit a MTPV curve, refer to Figure 2 , and finally obtain a MTPV curve with basically unchanged output torque and smooth shape.

[0104] Further, in a preferred embodiment, the MTPV curve calibration method further comprises the following steps:

[0105] S400: refer to Figure 3 , based on the MTPV curve, the motor external characteristic data at each operating voltage of the motor in its operating voltage range is calculated according to the equal magnetic flux principle, including the torque, speed and output power of the motor.

[0106] After the above configuration, it is tested that the actual feedback current in the area of the MTPV curve is basically consistent with the prediction, the actual output torque is basically consistent with the prediction, and the error is within 3%.

[0107] The application also discloses a MTPV curve calibration system, comprising a test bench and a processing module, based on the torque data obtained by testing the motor on the test bench, the processing module calculates the current-magnetic flux data set and the current-torque data set; the processing module inputs the first current corresponding to the maximum torque in the MTPA curve to the current-magnetic flux data set to obtain the first magnetic flux value corresponding to the first current, and the turning speed when the voltage utilization rate is 1 under the first magnetic flux value, and calculates the target magnetic flux value under the turning speed; the processing module traverses the current-magnetic flux data set to find the current-magnetic flux point with a difference from the target magnetic flux value less than a threshold value, and extracts the maximum torque point in all current-magnetic flux points as the MTPV point.

[0108] Preferably, the processing module obtains torque data of the motor tested by the test bench at different test speeds; the processing module extracts d-axis voltage Ud, q-axis voltage Uq and d-axis current Id, q-axis current Iq corresponding to each torque in the torque data; for each torque, the processing module calculates the square sum of the d-axis voltage Ud and the q-axis voltage Uq, and divides the square sum by the test speed corresponding to the torque to form a current-flux data set; for each torque, the processing module arranges the d-axis current Id and the q-axis current Iq in ascending order to form a current-torque data set; and the processing module linearly interpolates the current-flux data set and the current-torque data set with 1A as a unit current.

[0109] Preferably, the processing module extracts calibrated data in the MTPA curve, wherein the calibrated data includes maximum torques at different test speeds and corresponding first currents; the processing module inputs the first currents into the current-flux data set and obtains first flux values corresponding to the first currents by linear interpolation; the processing module controls the motor to operate at a rated voltage based on the motor controller, and records a speed value when the voltage utilization is 1 as a turning speed; and the processing module divides the rated voltage by each test speed to calculate target flux values corresponding to each test speed from the turning speed to a peak speed of the motor based on a preset speed step.

[0110] Preferably, the processing module traverses the current-flux linkage data set to find a current-flux linkage point with a difference from the target flux linkage value less than a threshold value, and stores it as an extraction array, wherein the extraction array includes a d-axis current Id, a q-axis current Iq, and a corresponding torque; the processing module compares all data in the extraction array, and records a point corresponding to a maximum torque value as an MTPV point; the processing module records a point with a maximum d-axis current Id among all MTPV points as a starting point; the processing module determines whether a d-axis current Id of a next MTPV point adjacent to a previous MTPV point is less than the d-axis current Id of the previous MTPV point from the starting point; when the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, the processing module connects adjacent MTPV points to fit an MTPV curve; when the d-axis current Id of any or arbitrary next MTPV point is greater than or equal to the d-axis current Id of the previous MTPV point, the processing module subtracts a preset difference from the maximum torque value to obtain a second maximum torque value, finds an MTPV point between the second maximum torque value and the maximum torque value, and extracts a point closest to the point with the maximum d-axis current Id from the found MTPV point as an updated starting point; the processing module replaces the starting point with the updated starting point, and again determines whether a d-axis current Id of a next MTPV point adjacent to a previous MTPV point is less than the d-axis current Id of the previous MTPV point from the updated starting point, until the d-axis current Id of all next MTPV points is less than the d-axis current Id of the previous MTPV point, and adjacent MTPV points are connected to fit an MTPV curve.

[0111] It should be noted that the embodiments of the present application have better implementation, and do not limit the present application in any form, any skilled person in the art can change or modify the above disclosed technical content into equivalent effective embodiments, as long as it does not deviate from the technical solution of the present application, and any modification or equivalent change and modification of the above embodiments according to the technical essence of the present application, still belongs to the scope of the technical solution of the present application.

Claims

1. A method for calibrating MTPV curves, characterized in that, Includes the following steps: Based on the torque data obtained from testing the motor on the test bench, the current-magnetic flux data set and the current-torque data set are calculated. The first current corresponding to the maximum torque in the MTPA curve is input to the current-magnetic flux data group to obtain the first magnetic flux value corresponding to the first current, the turning speed when the voltage utilization rate is 1 under the first magnetic flux value, and the target magnetic flux value under the turning speed. The current-magnetic flux linkage data group is traversed to find current-magnetic flux linkage points whose difference from the target magnetic flux linkage value is less than a threshold value, and the point with the maximum torque among all current-magnetic flux linkage points is extracted as the MTPV point.

2. The MTPV curve calibration method as described in claim 1, characterized in that, The steps for calculating the current-flux flux data set and the current-torque data set based on the torque data obtained from testing the motor on the test bench include: Obtain torque data from testing the motor on the test bench at different test speeds; Extract the d-axis voltage Ud, q-axis voltage Uq, d-axis current Id, and q-axis current Iq corresponding to each torque in the torque data; For each torque, the square root of the sum of the squares of the d-axis voltage Ud and the q-axis voltage Uq is calculated and divided by the test speed corresponding to the torque to form a current-magnetic flux linkage data set. For each torque, the d-axis current Id and q-axis current Iq are arranged in ascending order to form a current-torque data set; Using 1A as the unit current, linear interpolation is performed on the current-magnetic flux linkage data set and the current-torque data set.

3. The MTPV curve calibration method as described in claim 1, characterized in that, The steps of inputting the first current corresponding to the maximum torque in the MTPA curve into the current-flux linkage data set to obtain the first flux linkage value corresponding to the first current, the turning speed at which the voltage utilization rate is 1 under the first flux linkage value, and calculating the target flux linkage value at the turning speed include: Extract the calibrated data from the MTPA curve, wherein the calibrated data includes the maximum torque at different test speeds and its corresponding first current; The first current is input to the current-magnetic flux data set, and the first magnetic flux value corresponding to the first current is obtained by linear interpolation. The motor is controlled by the motor controller to operate under rated voltage, and the rotational speed when the voltage utilization rate is 1 is recorded as the turning speed. Based on a preset speed step, the rated voltage is divided by each test speed to calculate the target flux linkage value corresponding to each test speed from the turning speed to the peak speed of the motor.

4. The MTPV curve calibration method as described in claim 3, characterized in that, The steps of traversing the current-magnetic flux linkage data set to find current-magnetic flux linkage points whose difference from the target magnetic flux linkage value is less than a threshold, and extracting the point with the maximum torque among all current-magnetic flux linkage points as the MTPV point, include: The current-magnetic flux linkage data group is traversed to find current-magnetic flux linkage points whose difference from the target magnetic flux linkage value is less than a threshold value, and stored as an extraction array, wherein the extraction array includes d-axis current Id, q-axis current Iq and corresponding torque; Compare all the data in the extracted array and record the points where the d-axis current Id and q-axis current Iq corresponding to the maximum torque as the MTPV point.

5. The MTPV curve calibration method as described in claim 4, characterized in that, The step of traversing the current-magnetic flux linkage data set to find current-magnetic flux linkage points whose difference from the target magnetic flux linkage value is less than a threshold, and extracting the point with the maximum torque among all current-magnetic flux linkage points as the MTPV point, further includes: Record the point with the largest d-axis current Id among all MTPV points as the starting point; Determine whether the d-axis current Id of the next MTPV point adjacent to the previous MTPV point is less than the d-axis current Id of the previous MTPV point, starting from the aforementioned starting point. When the d-axis current Id of all subsequent MTPV points is less than the d-axis current Id of the previous MTPV point, connect adjacent MTPV points to fit an MTPV curve. When the d-axis current Id at any or any subsequent MTPV point is greater than or equal to the d-axis current Id at the previous MTPV point, the maximum torque value is subtracted by a preset difference to obtain the second largest torque value. MTPV points between the second largest torque value and the maximum torque value are then searched, and the point closest to the point with the largest d-axis current Id is extracted from the found MTPV points as the update starting point. Replace the starting point with the update starting point, and then determine again whether the d-axis current Id of the next MTPV point adjacent to the previous MTPV point is less than the d-axis current Id of the previous MTPV point, until the d-axis current Id of all the next MTPV points is less than the d-axis current Id of the previous MTPV point, then connect the adjacent MTPV points to fit an MTPV curve.

6. The MTPV curve calibration method as described in claim 1, characterized in that, The MTPV curve calibration method further includes the following steps: Based on the MTPV curve, the external characteristic data of the motor under each operating voltage are calculated according to the principle of equal flux linkage.

7. An MTPV curve calibration system, characterized in that, Includes test bench and processing module, Based on the torque data obtained from testing the motor on the test bench, the processing module calculates the current-magnetic flux data set and the current-torque data set. The processing module inputs the first current corresponding to the maximum torque in the MTPA curve to the current-magnetic flux data group to obtain the first magnetic flux value corresponding to the first current, the turning speed when the voltage utilization rate is 1 under the first magnetic flux value, and calculates the target magnetic flux value under the turning speed. The processing module iterates through the current-magnetic flux linkage data group to find current-magnetic flux linkage points whose difference from the target magnetic flux linkage value is less than a threshold, and extracts the point with the maximum torque among all current-magnetic flux linkage points as the MTPV point.

8. The MTPV curve calibration system as described in claim 7, characterized in that, The processing module acquires torque data obtained from testing the motor on the test bench at different test speeds; The processing module extracts the d-axis voltage Ud, q-axis voltage Uq, d-axis current Id, and q-axis current Iq corresponding to each torque in the torque data. For each torque, the processing module calculates the square root of the sum of the squares of the d-axis voltage Ud and the q-axis voltage Uq, and divides it by the test speed corresponding to the torque to form a current-magnetic flux linkage data set. For each torque, the processing module arranges the d-axis current Id and q-axis current Iq in ascending order to form a current-torque data set; The processing module linearly interpolates the current-magnetic flux linkage data set and the current-torque data set using 1A as the unit current.

9. The MTPV curve calibration system as described in claim 7, characterized in that, The processing module extracts the calibrated data from the MTPA curve, wherein the calibrated data includes the maximum torque at different test speeds and its corresponding first current; The processing module inputs the first current into the current-magnetic flux data group and obtains the first magnetic flux value corresponding to the first current through linear interpolation. The processing module of the motor controller controls the motor to operate under rated voltage and records the rotational speed when the voltage utilization rate is 1 as the turning speed. Based on a preset speed step, the processing module divides the rated voltage by each test speed to calculate the target flux linkage value corresponding to each test speed from the turning speed to the peak speed of the motor.

10. The MTPV curve calibration system as described in claim 9, characterized in that, The processing module traverses the current-magnetic flux linkage data group to find current-magnetic flux linkage points whose difference from the target magnetic flux linkage value is less than a threshold, and stores them as an extraction array, wherein the extraction array includes d-axis current Id, q-axis current Iq and corresponding torque; The processing module compares all the data in the extracted array and records the points where the d-axis current Id and q-axis current Iq corresponding to the maximum torque value are located as MTPV points; The processing module records the point with the largest d-axis current Id among all MTPV points as the starting point; the processing module determines whether the d-axis current Id of the next MTPV point adjacent to the previous MTPV point is less than the d-axis current Id of the previous MTPV point from the starting point. When the d-axis current Id of all subsequent MTPV points is less than the d-axis current Id of the previous MTPV point, the processing module connects adjacent MTPV points to fit an MTPV curve. When the d-axis current Id at any or any subsequent MTPV point is greater than or equal to the d-axis current Id at the previous MTPV point, the processing module subtracts a preset difference from the maximum torque value to obtain the second largest torque value, searches for MTPV points between the second largest torque value and the maximum torque value, and extracts the point closest to the point with the largest d-axis current Id from the found MTPV points as the update starting point. The processing module replaces the starting point with the update starting point and then determines again whether the d-axis current Id of the next MTPV point adjacent to the previous MTPV point is less than the d-axis current Id of the previous MTPV point, until the d-axis current Id of all the next MTPV points is less than the d-axis current Id of the previous MTPV point, and then connects the adjacent MTPV points to fit an MTPV curve.

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