A variable switching frequency calibration method and device integrating efficiency and electric drive noise

Abstract

The application relates to a variable-switching-frequency calibration method and device combining efficiency and electric drive noise, which comprises the following steps: obtaining the rotation speed data and torque data of a motor corresponding to the switching of a motor under multiple working conditions; calculating the weight of the multiple working conditions of the motor discretely in a preset frequency interval according to the rotation speed data and torque data; determining the calibration boundary of the frequency of the switching of the motor to be calibrated, wherein the calibration boundary comprises a fundamental frequency boundary, a maximum value, an upper limit boundary and a current loop bandwidth; collecting the electric drive noise data and electric drive efficiency value of the motor in real time based on the calibration boundary of the frequency of the switching of the motor to be calibrated and the weight of the multiple working conditions discretely in the preset frequency interval; and determining at least one switching frequency value which is optimal in terms of electric drive efficiency and noise according to the electric drive noise data and electric drive efficiency value of the motor. The application combines actual working conditions, performs efficiency-noise comprehensive optimization, and finally achieves the dynamic balance of the two, thereby improving the calibration efficiency.

Description

Technical Field

[0001] This invention belongs to the field of electric vehicle control technology, specifically relating to a method and device for calibrating the switching frequency of the vehicle with respect to overall efficiency and electric drive noise. Background Technology

[0002] As the market demands increasingly higher driving range and NVH (Noise, Vibration, and Harshness) levels for electric vehicles, design engineers of related components are paying more and more attention to the analysis and optimization of these issues. For electric drives, increasing driving range means improving overall system efficiency, while improving NVH involves the hardware and software design of the electronic control, motor, and reducer.

[0003] Optimization of efficiency and NVH (Noise, Vibration, and Harshness) can be achieved through electronic control software. Extensive research has been conducted on related software algorithms for efficiency improvement. One approach involves modifying the IGBT's switching frequency (also known as carrier frequency) by identifying different vehicle operating parameters (such as engine speed, torque, and three-phase current). Excessively high switching frequencies often lead to high losses and reduced assembly efficiency; conversely, excessively low switching frequencies introduce large current harmonics, worsening NVH performance.

[0004] Existing technology relates to a method for controlling the carrier frequency of an IGBT, which, based on conventional speed-varying switching frequency, adds monitoring of the current value and adjusts the switching frequency accordingly. While it optimizes NVH (noise, vibration, and harshness), the patent does not explain the method for achieving a balance between efficiency and NVH.

[0005] On the other hand, high-frequency noise is suppressed by controlling the IGBT switching frequency based on motor speed and torque signals. Simultaneously, a random switching frequency method is used in the high torque range to avoid concentrating interference energy at specific frequencies, thereby reducing the peak value of the noise spectrum and lowering high-frequency noise. Using speed and torque determination combined with a random switching frequency for NVH optimization can effectively reduce high-frequency noise; however, the patent does not clarify the impact of NVH optimization on efficiency or how to achieve a balance.

[0006] In addition, it incorporates bench noise and efficiency tests, which effectively ensures that the highest efficiency switching frequency is obtained while meeting the specified noise requirements. However, it has the following drawbacks:

[0007] ① The same screening rules were applied across the entire speed range without taking into account the actual operating conditions for comprehensive optimization. The balance between efficiency and noise can be further optimized.

[0008] ② A fixed switching frequency was used for processing throughout the entire speed range, and there is still room for further optimization of electric drive noise.

[0009] ③ The switching frequency was optimized using only two dimensions, noise and efficiency, across the entire vehicle speed range, without considering other constraints during motor operation. This may lead to a deterioration in motor control performance during actual application. Summary of the Invention

[0010] To balance switching efficiency and noise in electric vehicles, and to optimize the switching frequency calibration, the first aspect of this invention provides a variable switching frequency calibration method that integrates efficiency and electric drive noise. The method includes: acquiring the motor speed and torque data of the motor under various operating conditions; calculating the weights of the various operating conditions of the motor within a preset frequency range based on the speed and torque data; determining the calibration boundaries of the switching frequency of the motor under the calibrated motor, the calibration boundaries including a fundamental frequency boundary, a maximum value, an upper limit boundary, and a current loop bandwidth; based on the calibration boundaries of the switching frequency of the motor under the calibrated motor and the weights of the various operating conditions within the preset frequency range, real-time acquisition of electric drive noise data and electric drive efficiency values ​​of the motor; and determining at least one optimal switching frequency value that balances electric drive efficiency and noise based on the electric drive noise data and electric drive efficiency values ​​of the motor.

[0011] In some embodiments of the present invention, the step of calculating the weights of the various operating conditions of the motor discretely within a preset frequency range based on the speed data and torque data includes: dividing the preset frequency range of the switch of the motor to be calibrated into multiple sub-frequency ranges based on the speed data and torque data of the motor; mapping the speed data and torque data of the motor in each sub-frequency range onto a scatter plot of the vehicle operating conditions, and calculating the efficiency weight coefficient of each sub-range.

[0012] In some embodiments of the present invention, the real-time acquisition of motor drive noise data based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discretely within a preset frequency range includes: constructing a two-dimensional relationship table between rotational speed and switching frequency according to the calibration boundary of the switching frequency; dividing the preset switching frequency range into multiple intervals based on the two-dimensional relationship table between rotational speed and switching frequency, sequentially optimizing the switching frequency and recording the drive noise data of each interval.

[0013] In some embodiments of the present invention, determining at least one switching frequency value that balances optimal electric drive efficiency and noise based on the electric drive noise data and electric drive efficiency value of the motor includes: normalizing the electric drive noise data and electric drive efficiency value of the motor; and determining a switching frequency value that balances optimal electric drive efficiency and noise based on the normalized electric drive noise data and electric drive efficiency value, and the weights of the various operating conditions discretely distributed in a preset frequency range.

[0014] Furthermore, determining at least one optimal switching frequency value that balances electric drive efficiency and noise includes: if the electric drive efficiency values ​​are distributed within the frequency range, then the optimal switching frequency value is determined jointly based on the electric drive efficiency values ​​and noise data; otherwise, the optimal switching frequency value is determined according to the order of electric drive efficiency values ​​from largest to smallest.

[0015] In the above embodiments, the method further includes: performing vehicle-wide verification on at least one switching frequency value that balances electric drive efficiency and noise optimization; and optimizing each switching frequency value that balances electric drive efficiency and noise optimization based on the vehicle verification results and a random algorithm.

[0016] A second aspect of the present invention provides a variable switching frequency calibration device that integrates efficiency and electric drive noise, comprising: an acquisition module for acquiring speed data and torque data of a motor to be calibrated under various operating conditions; calculating the weights of the various operating conditions of the motor discretely distributed within a preset frequency range based on the speed data and torque data; a first determination module for determining the calibration boundary of the switching frequency of the motor to be calibrated, the calibration boundary including a fundamental frequency boundary, a maximum value, an upper limit boundary, and a current loop bandwidth; an acquisition module for acquiring electric drive noise data and electric drive efficiency values ​​of the motor in real time based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discretely distributed within the preset frequency range; and a second determination module for determining at least one switching frequency value that balances electric drive efficiency and noise optimality based on the electric drive noise data and electric drive efficiency values ​​of the motor.

[0017] Furthermore, the acquisition module includes: a division unit, used to divide the preset frequency range of the switch of the motor to be calibrated into multiple sub-frequency ranges according to the motor speed data and torque data; and a calculation unit, used to map the motor speed data and torque data of each sub-frequency range onto a vehicle operating condition scatter plot, and calculate the efficiency weighting coefficient of each sub-range.

[0018] A third aspect of the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the variable switching frequency calibration method for overall efficiency and electric drive noise provided in the first aspect of the present invention.

[0019] In a fourth aspect, the present invention provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the variable switching frequency calibration method for overall efficiency and electric drive noise provided in the first aspect of the present invention.

[0020] The beneficial effects of this invention are:

[0021] This invention relates to a method and apparatus for calibrating a variable switching frequency that integrates efficiency and electric drive noise. The method includes: acquiring the speed and torque data of the motor under various operating conditions; calculating the weights of the various operating conditions of the motor within a preset frequency range based on the speed and torque data; determining the calibration boundaries of the switching frequency of the motor under calibration, including a fundamental frequency boundary, a maximum value, an upper limit boundary, and a current loop bandwidth; real-time acquisition of electric drive noise data and electric drive efficiency values ​​of the motor based on the calibration boundaries of the switching frequency and the weights of the various operating conditions within the preset frequency range; and determining at least one optimal switching frequency value that balances both electric drive efficiency and noise based on the electric drive noise data and electric drive efficiency values. As can be seen, this invention combines actual operating conditions for comprehensive efficiency-noise optimization, ultimately achieving a balance between the two; a random frequency strategy is used to handle noise exceeding the standard range, ensuring efficiency optimization. When optimizing the switching frequency, three design boundaries of the motor controller are considered to constrain the test switching frequency, which can greatly reduce the ineffective workload of the bench calibration system. Attached Figure Description

[0022] Figure 1 This is a basic flowchart illustrating the variable switching frequency calibration method for overall efficiency and electric drive noise in some embodiments of the present invention.

[0023] Figure 2 This is a schematic diagram illustrating the speed change trend of a vehicle under CLTC operating conditions.

[0024] Figure 3 This is a scatter plot of the motor speed and torque of a vehicle under CLTC operating conditions.

[0025] Figure 4 This is a schematic diagram illustrating the principle of the variable switching frequency calibration method for overall efficiency and electric drive noise in some embodiments of the present invention.

[0026] Figure 5 This is a schematic diagram of the structure of a variable switching frequency calibration device for overall efficiency and electric drive noise in some embodiments of the present invention.

[0027] Figure 6 This is a schematic diagram of the structure of an electronic device in some embodiments of the present invention. Detailed Implementation

[0028] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0029] refer to Figure 1 and Figure 4In a first aspect of the present invention, a method for calibrating a variable switching frequency that integrates efficiency and electric drive noise is provided, comprising: S100. acquiring the rotational speed data and torque data of the motor to be calibrated under various operating conditions; calculating the weights of the various operating conditions of the motor discretely distributed within a preset frequency range based on the rotational speed data and torque data; S200. determining the calibration boundary of the switching frequency of the motor to be calibrated, the calibration boundary including a fundamental frequency boundary, a maximum value, an upper limit boundary, and a current loop bandwidth; S300. acquiring electric drive noise data and electric drive efficiency values ​​of the motor in real time based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discretely distributed within the preset frequency range; S400. determining at least one switching frequency value that balances electric drive efficiency and noise optimality based on the electric drive noise data and electric drive efficiency values ​​of the motor.

[0030] refer to Figure 2 and Figure 3 It should be noted that there are currently three mainstream operating cycles for calculating the driving range of new energy vehicles: NEDC, WLTP, and CLTC. Among them, CLTC is the most widely used cyclic testing method. The full name of the CLTC driving range standard is China Light-Duty Vehicle Test Cycle-Passenger, which has been implemented since October 1, 2021, and many models now use CLTC as their testing standard. Its biggest advantage is that it conforms to the actual driving environment in my country. The testing standard is based on the traffic conditions of 41 cities nationwide, including urban, suburban, and highway driving conditions. Therefore, although this disclosure uses the CLTC operating cycle as a reference, it does not affect its application in other operating conditions for comprehensive optimization calculations.

[0031] It is understood that by constructing an electric drive switch frequency calibration system, one or more steps of the disclosed variable switch frequency calibration method for overall efficiency and electric drive noise can be implemented; the calibration system includes:

[0032] ① Dynamometer: measures the actual output torque and speed of the motor under test and sends the values ​​to the host computer.

[0033] ② Host computer: 1) Receive the torque and speed measured by the dynamometer, calculate the mechanical power output of the electric drive, P = T * n / 9550; 2) Send the speed command to the dynamometer to maintain the motor speed; 3) Send the torque command to the motor controller.

[0034] ③ Motor controller: Receives torque commands from the host computer and drives the IGBT to generate three-phase current according to different switching frequencies, so that the motor rotates.

[0035] ④ Motor under test: Coaxially connected to the dynamometer, operating according to the three-phase current of the motor controller.

[0036] ⑤ Noise testing equipment: One microphone is placed 1m above, to the left, to the right, in front, and behind the electric drive envelope. In addition, one microphone is placed 0.1m above the reducer, the motor, and the rear near field.

[0037] ⑥ Power Analyzer: Connected to the high-voltage power supply, it collects the voltage U and current I of the high-voltage bus in real time. The input power of the high-voltage power supply is Pn, which can be calculated using the formula Pn = U * I.

[0038] ⑦ High-voltage power supply: Connected to the motor controller, it realizes the conversion of DC to AC to drive the motor through rectification or inversion by the motor controller, and the conversion of AC to DC to recover energy.

[0039] In step S100 of some embodiments of the present invention, the step of calculating the weights of the various operating conditions of the motor discretely in a preset frequency range based on the speed data and torque data includes: dividing the preset frequency range of the switch of the motor to be calibrated into multiple sub-frequency ranges based on the speed data and torque data of the motor; mapping the speed data and torque data of the motor in each sub-frequency range onto a scatter plot of the vehicle operating conditions, and calculating the efficiency weight coefficient of each sub-range.

[0040] Specifically, ① Switching frequency table dimension selection: The switching frequency range is divided according to two dimensions: motor speed and torque. Where Nn is the maximum motor speed and Tn is the maximum motor torque.

[0041] N1 N2 N3 N4 ...... Nn T1 K11 K12 K13 K14 ...... K1n T2 K21 K22 K23 K24 ...... K2n T3 K31 K31 K31 K31 ...... K3n T4 K41 K41 K41 K41 ...... K4n ...... ...... ...... ...... ...... ...... Tn Kn1 Kn2 Kn3 Kn4 Knn

[0042] ② Switching frequency table step size division: Motor speed and torque can be divided into equal step sizes, i.e., N3-N2=N2-N1, T3-T2=T2-T1. Alternatively, depending on the frequency of this operating condition during actual vehicle operation, it can be divided into variable step sizes, i.e., Nn-Nn-1≥N2-N1, Tn-Tn-1≥T2-T1;

[0043] ③ Efficiency Weighting Coefficient Calculation: Mapping the switching frequency table onto the CLTC operating condition scatter plot yields a switching frequency-scatter plot. Each switching frequency interval is assigned 1800 operating condition scatter points, representing the frequency of use of that frequency interval in the operating conditions. For a constant-step switching frequency table, the number of operating condition scatter points measures the weight of that frequency interval; however, for a variable-step switching frequency table, smaller switching frequency intervals may receive fewer operating condition scatter points, but this does not necessarily mean they are infrequently used. Therefore, an efficiency weighting coefficient is used to uniformly measure the importance of that switching frequency interval to efficiency. Let the intermediate efficiency weighting coefficient be η, then:

[0044] η xy =Sxy / [(N x -N x-1 )*(T y -T y-1 )],

[0045] in:

[0046] S xy —Falling on [(N x -N x-1 )*(T y -T y-1 The number of CLTC condition scatter points within the interval;

[0047] η xy —Interval [(N x -N x-1 )*(T y -T y-1 The efficiency weighting intermediate coefficients; x and y represent the x and y axes on the scatter plot, respectively;

[0048] After the calculation is completed, the distribution of the intermediate coefficients of efficiency weights on the switching frequency table can be obtained:

[0049] N1 N2 N3 N4 ...... Nn T1 h11 h12 h13 h14 ...... n1n T2 h21 h22 h23 h24 ...... n2n T3 h31 h32 h33 h34 ...... n3n T4 h41 n42 h43 h44...... n4n ...... ...... ...... ...... ...... ...... ...... Tn n1 n2 n3 n4 ...... nn

[0050] Due to S xy The magnitude is too small relative to the switching frequency range, and the resulting intermediate coefficients for efficiency weights are also very small, which is not conducive to subsequent calculations. Therefore, a maximum-minimum normalization process is applied: Let η min η max Let η be the minimum and maximum values ​​in the efficiency weight intermediate coefficient table, respectively. Then the original value η can be... xy The efficiency weighting coefficient η is mapped to the interval [0, 1] through max-min normalization. xy The normalization formula is as follows:

[0051] η xy '=(η xy -η min / (η max -η min ),

[0052] After normalization, the distribution of the intermediate coefficient η' of the efficiency weights on the switching frequency table can be obtained:

[0053] N1 N2 N3 N4...... Nn T1 η11′ η12′ η13′ the14′...... η1n′ T2 η21′ η22′ η23′ η24′ ...... η2n′ T3 η31′ η32′ η33′ η34′ ...... η3n′ T4 η41′ η42′ η43′ h44′...... η4n′ ...... ............ ...... ...... ...... ...... Tn n1′ ηn2′ ηn3′ n4′...... ηnn′

[0054] In step S300 of some embodiments of the present invention, the real-time acquisition of motor drive noise data based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discrete in the preset frequency range includes: constructing a two-dimensional relationship table between rotational speed and switching frequency according to the calibration boundary of the switching frequency; dividing the preset switching frequency range into multiple intervals based on the two-dimensional relationship table between rotational speed and switching frequency, performing switching frequency optimization in sequence, and recording the drive noise data of each interval.

[0055] Specifically, the switching frequency boundary is calculated as follows: Based on the fundamental frequency and current loop bandwidth limitations at different speeds described in the above embodiments, a table of speed and minimum switching frequency boundaries is determined:

[0056] N1 N2 N3 N4 ...... Nn T1 K11min K12min K13min K14min ...... K1nmin ...... ...... ...... ...... ...... ...... ...... Tn Kn1min Kn2min Kn3min Kn4min ...... Knnmin

[0057] Based on the hardware capabilities, software load rate, and current loop bandwidth limitations at different speeds described in the above embodiments, a speed-maximum switching frequency boundary table is determined:

[0058] N1 N2 N3 N4 ...... Nn T1 K11max K12max K13max K14max ...... K1nmax ...... ...... ...... ...... ...... ...... ...... Tn Kn1max Kn2max Kn3max Kn4max Knnmax

[0059] By merging the minimum and maximum switching frequency boundaries, a speed-switching frequency boundary table can be obtained, which can be used for the next step of bench calibration system switching frequency optimization, and can significantly reduce the workload of the calibration system.

[0060] In step S400 of some embodiments of the present invention, determining at least one switching frequency value that balances optimal electric drive efficiency and noise based on the electric drive noise data and electric drive efficiency value of the motor includes: S401. Normalizing the electric drive noise data and electric drive efficiency value of the motor;

[0061] Specifically, the switching frequency is optimized sequentially according to the intervals defined by the switching frequency. Taking the switching frequency range K22 as an example, the test bench first stabilizes the motor speed at (N2-N1) / 2, while the host computer inputs torque commands (T2-T1) / 2 at different switching frequencies to the motor controller. The switching frequency starts at K22max and is then gradually decreased in steps according to a set increment until it reaches K22min. During this process, the noise monitoring equipment continuously records the peak decibel value αN of the electric drive noise, while the host computer continuously calculates the overall electric drive efficiency βn corresponding to the corresponding switching frequency.

[0062] In the optimization calculation, the goal is to achieve a peak noise level at the switching frequency that approaches or meets the national or enterprise standard decibel level, while maximizing the overall efficiency of the electric drive. Therefore, the difference between the standard decibel value and the peak electric drive noise value is first calculated (αN' = αstandard - αN, where αstandard is the standard value of the electric drive noise within that speed range). A larger αN' value indicates lower noise. Normalization is then performed, and the range is transformed from [-0.5, 0.5] to [0, 1].

[0063] αn'=[(αN'-αN'min) / (αN'max-αN'min)]+0.5

[0064] Then, βn is subjected to max-min normalization:

[0065] βn'=(βn-βmin) / (βmax-βmin);

[0066] After normalization, optimization calculations can be performed by combining efficiency weighting coefficients:

[0067] 1) η22'≠0, then: γn=(1-η22')*αn'+η22'*βn';

[0068] 2) If η22'=0, then take the values ​​of αN'>0, and γn corresponding to βn' from largest to smallest.

[0069] Wherein, γn is the combined efficiency-noise value. As the above analysis shows, the larger γn is, the better the efficiency-noise balance, meaning a better overall performance in terms of noise level and electric drive efficiency.

[0070] S402. Based on the normalized electric drive noise data and electric drive efficiency value, as well as the weights of the various operating conditions discrete in the preset frequency range, determine a switching frequency value that takes into account both the electric drive efficiency value and the optimal noise.

[0071] Furthermore, determining at least one optimal switching frequency value that balances electric drive efficiency and noise includes: if the electric drive efficiency values ​​are distributed within the frequency range, then the optimal switching frequency value is determined jointly based on the electric drive efficiency values ​​and noise data; otherwise, the optimal switching frequency value is determined according to the order of electric drive efficiency values ​​from largest to smallest.

[0072] Specifically, within the switching frequency range K22, the efficiency-noise combined values ​​γn at different switching frequencies have been obtained through the above calculations and are arranged from highest to lowest value. The switching frequency corresponding to the highest combined value is defined as the first preset switching frequency K221, the switching frequency corresponding to the second lowest combined value is defined as the second preset switching frequency K222, and so on. After completing the optimization calculation for the K22 range, the same operation is performed on the remaining ranges in sequence. After determining the first preset switching frequency for each range, it is filled into the corresponding table to finally obtain the optimized switching frequency table:

[0073] N1 N2 N3 N4 ...... Nn T1 K111 K121 K131 K141...... K1n1 T2 K211 K221 K231 K241 ...... K2n1 T3 K311 K311 K311 K311 ...... K3n1 T4 K411 K411 K411 K411 ...... K4n1 ...... ...... ...... ...... ...... ...... K5n1 Tn Kn11 Kn21 Kn31 Kn41 ...... K6n1

[0074] It should be understood that due to the efficiency-noise integrated optimization strategy, noise may exceed the standard value in areas with high efficiency weighting coefficients. Therefore, the final switching frequency freeze of this solution needs to be confirmed in conjunction with the overall vehicle effect.

[0075] Therefore, in the above embodiments, step S500 is also included: performing vehicle-wide verification on at least one switching frequency value that balances electric drive efficiency and noise optimization; and optimizing each switching frequency value that balances electric drive efficiency and noise optimization based on the vehicle verification results and a random algorithm.

[0076] Specifically, a random number θ between [-1, 1] is obtained through a random algorithm. The switching frequency fluctuation range ΔKc is multiplied by the random number θ, and then the center switching frequency KC is added to obtain the randomized frequency modulation switching frequency: K = Kc + θ * ΔKc, where: Kc is the preset switching frequency Kxy where noise exceeds the standard, ΔKc is 1 / 2 of the difference between the preset switching frequencies of two adjacent speed ranges [i.e., ΔKc = 1 / 2 * (Kx + 1y - Kx - 1y)], and K is the optimized random switching frequency. Vehicle testing continues. If the vehicle standard value is met, this random switching frequency is frozen. Vehicle testing is then performed sequentially according to the second preset switching frequency Kxy2, the third preset switching frequency Kxy3, and so on, for the exceeding range, until the standard value is met, at which point this switching frequency is frozen.

[0077] After completing the above steps, all switching frequency values ​​will be determined, and the final optimal switching frequency table will be frozen. At this point, the optimization of the variable switching frequency for overall efficiency and electric drive noise is complete.

[0078] Example 2

[0079] refer to Figure 5In a second aspect, the present invention provides a variable switching frequency calibration device 1 that integrates efficiency and electric drive noise, comprising: an acquisition module 11, configured to acquire the speed data and torque data of the motor to be calibrated under various operating conditions; and to calculate the weights of the various operating conditions of the motor discretely distributed within a preset frequency range based on the speed data and torque data; a first determination module 12, configured to determine the calibration boundary of the switching frequency of the motor to be calibrated, the calibration boundary including the fundamental frequency boundary, the maximum value, the upper limit boundary, and the current loop bandwidth; an acquisition module 13, configured to acquire the electric drive noise data and electric drive efficiency value of the motor in real time based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discretely distributed within the preset frequency range; and a second determination module 14, configured to determine at least one switching frequency value that balances electric drive efficiency and noise optimality based on the electric drive noise data and electric drive efficiency value of the motor.

[0080] Furthermore, the acquisition module 11 includes: a division unit, used to divide the preset frequency range of the switch of the motor to be calibrated into multiple sub-frequency ranges according to the motor speed data and torque data; and a calculation unit, used to map the motor speed data and torque data of each sub-frequency range onto a vehicle operating condition scatter plot, and calculate the efficiency weighting coefficient of each sub-range.

[0081] Example 3

[0082] refer to Figure 6 A third aspect of the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of the first aspect of the present invention.

[0083] Electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0084] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, hard disks; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 6 Each box shown can represent a device or multiple devices as needed.

[0085] Specifically, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by a processing device 501, it performs the functions defined in the methods of embodiments of this disclosure. It should be noted that the computer-readable medium described in embodiments of this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0086] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more computer programs, which, when executed by the electronic device, cause the electronic device to:

[0087] Computer program code for performing the operations of embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, C++, and Python—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0088] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0089] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for calibrating a variable switching frequency that integrates efficiency and electric drive noise, characterized in that, include: Obtain the speed and torque data of the motor to be calibrated under various operating conditions; Based on the speed and torque data, the weights of various operating conditions of the motor discretely distributed within a preset frequency range are calculated: Based on the motor's speed and torque data, the preset frequency range of the motor's switch to be calibrated is divided into multiple sub-frequency ranges; the motor's speed and torque data in each sub-frequency range are mapped onto a scatter plot of the vehicle's operating conditions, and the efficiency weight coefficient for each sub-range is calculated; let the intermediate efficiency weight coefficient be η, then: η xy =S xy / [(N x -N x-1 )*(T y -T y-1 )], where: S xy It means falling on [(N x -N x-1 )*(T y -T y-1 The number of CLTC condition scatter points within the interval; η xyy Represents the interval [(N x -N x-1 )*(T y -T y-1 The efficiency weighting intermediate coefficients; x and y represent the x and y axes on the scatter plot, respectively; the original value η xy The efficiency weighting coefficient η is mapped to the interval [0,1] through max-min normalization. xy The normalization formula is as follows: η xy '=(η xy -η min / (η max -η min ); Determine the calibration boundaries of the switching frequency of the motor to be calibrated, including the fundamental frequency boundary, maximum value, upper limit boundary, and current loop bandwidth; Based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discrete in the preset frequency range, the electric drive noise data and electric drive efficiency value of the motor are collected in real time. Based on the electric drive noise data and electric drive efficiency value of the motor, at least one switching frequency value that balances electric drive efficiency and noise optimization is determined.

2. The method for calibrating the overall efficiency and electric drive noise of a variable switching frequency according to claim 1, characterized in that, The calibration boundary based on the frequency of the switch of the motor to be calibrated and the weights of the various operating conditions discrete within a preset frequency range, and the real-time acquisition of motor drive noise data include: Based on the calibration boundary of the switching frequency, a two-dimensional relationship table between rotational speed and switching frequency is constructed; Based on the two-dimensional relationship table between the rotational speed and the switching frequency, the preset switching frequency range is divided into multiple intervals, and the switching frequency is optimized in sequence while recording the electric drive noise data for each interval.

3. The method for calibrating the overall efficiency and electric drive noise of a variable switching frequency according to claim 1, characterized in that, The step of determining at least one switching frequency value that balances optimal electric drive efficiency and noise based on the electric drive noise data and electric drive efficiency value of the motor includes: The electric drive noise data and electric drive efficiency value of the motor are normalized; Based on the normalized electric drive noise data and electric drive efficiency value, as well as the weights of the various operating conditions discrete in the preset frequency range, at least one switching frequency value that balances electric drive efficiency and noise optimization is determined.

4. The method for calibrating the overall efficiency and electric drive noise of a variable switching frequency according to claim 3, characterized in that, Determining at least one optimal switching frequency value that balances electric drive efficiency and noise includes: If the electric drive efficiency values ​​are distributed within the frequency range, the optimal switching frequency value is determined jointly based on the electric drive efficiency values ​​and noise data. Otherwise, determine the optimal switching frequency value based on the order of electric drive efficiency values ​​from largest to smallest.

5. The method for calibrating the overall efficiency and electric drive noise of a variable switching frequency according to any one of claims 1 to 4, characterized in that, Also includes: At least one switching frequency value that balances electric drive efficiency and noise optimization should be verified on a whole vehicle. Based on the vehicle verification results and random algorithm, each switching frequency value that balances electric drive efficiency and noise optimization is optimized.

6. A variable switching frequency calibration device that integrates efficiency and electric drive noise, characterized in that, include: The acquisition module is used to acquire the speed and torque data of the motor to be calibrated under various operating conditions. Based on the speed and torque data, the weights of various operating conditions of the motor discretely distributed within a preset frequency range are calculated: Based on the motor's speed and torque data, the preset frequency range of the motor's switch to be calibrated is divided into multiple sub-frequency ranges; the motor's speed and torque data in each sub-frequency range are mapped onto a scatter plot of the vehicle's operating conditions, and the efficiency weight coefficient for each sub-range is calculated; let the intermediate efficiency weight coefficient be η, then: η xy =S xy / [(N x -N x-1 )*(T y -T y-1 )], where: S xy It means falling on [(N x -N x-1 )*(T y -T y-1 The number of CLTC condition scatter points within the interval; η xyy Represents the interval [(N x -N x-1 )*(T y -T y-1 The efficiency weighting intermediate coefficients; x and y represent the x and y axes on the scatter plot, respectively; the original value η xy The efficiency weighting coefficient η is mapped to the interval [0,1] through max-min normalization. xy The normalization formula is as follows: η xy '=(η xy -η min / (η max -η min ); The first determining module is used to determine the calibration boundaries of the switching frequency of the motor to be calibrated. The calibration boundaries include the fundamental frequency boundary, the maximum value, the upper limit boundary, and the current loop bandwidth. The acquisition module is used to acquire the electric drive noise data and electric drive efficiency value of the motor in real time based on the calibration boundary of the switching frequency of the motor to be calibrated and the weights of the various operating conditions discrete in the preset frequency range. The second determining module is used to determine at least one switching frequency value that balances the optimal electric drive efficiency and noise based on the electric drive noise data and electric drive efficiency value of the motor.

7. An electronic device, comprising: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the variable switching frequency calibration method for overall efficiency and electric drive noise as described in any one of claims 1 to 5.

8. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by the processor, it implements the variable switching frequency calibration method for overall efficiency and electric drive noise as described in any one of claims 1 to 5.

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