Insulation resistance calculation method based on statistical curve fitting prediction, medium and system

Abstract

The invention discloses an insulation resistance calculation method based on statistical curve fitting prediction, a medium and a system, and the method comprises the following steps: S1, recognizing a to-be-detected voltage signal in an insulation detection circuit as a step response of an RC circuit, and building a correction index model; s2, acquiring voltage sampling time sequence data, and based on the voltage sampling time sequence data, solving correction index model parameters by adopting a three-sum method; and S3, substituting the correction index model parameters into the correction index model, outputting a steady-state voltage prediction value, and inputting the steady-state voltage prediction value into an insulation resistance calculation formula to obtain the insulation resistance. According to the invention, the steady-state voltage can be calculated in the dynamic change process of the signal without waiting for the signal to be stable, so that the insulation resistance calculation time is shortened; according to the method, the steady-state voltage is calculated based on a statistical curve fitting prediction technology, the measured steady-state voltage can be calculated only by performing curve fitting and prediction according to a correction index model by using a three-sum method, and the precision is high.

Description

Technical Field

[0001] This invention mainly relates to the field of electric vehicle technology, specifically to a method, medium, and system for calculating insulation resistance based on statistical curve fitting prediction. Background Technology

[0002] Electric vehicles, as a type of new energy vehicle, are increasingly favored by consumers due to their advantages such as low energy consumption, low pollution, and economic and environmental benefits, resulting in a growing market share. With the increasing popularity of electric vehicles, their safety issues are becoming more prominent, and high-voltage insulation is one of the important indicators for measuring the safety of electric vehicles. Currently, there are clear requirements for the insulation resistance performance and insulation resistance testing functions of electric vehicles; therefore, accurate and rapid testing of the overall vehicle insulation resistance is crucial.

[0003] Currently available on-board or other online insulation resistance testing methods typically employ the unbalanced bridge method or the low-frequency signal injection method. Both methods calculate the insulation resistance value by measuring relevant voltage signals and detecting changes in the detection state. The detection speed mainly depends on the signal settling time. Electrical equipment is usually equipped with Y capacitors (common-mode capacitors) to eliminate common-mode interference. Due to the presence of Y capacitors, a steady-state voltage can only be acquired after the signal stabilizes, and the signal stabilization time is typically on the order of 1 second or 10 seconds, resulting in a long insulation resistance detection time. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides a method, medium, and system for calculating insulation resistance based on statistical curve fitting prediction, which improves detection speed and accuracy.

[0005] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows: A method for calculating insulation resistance based on statistical curve fitting prediction includes the following steps: S1. Identify the voltage signal to be measured in the insulation detection circuit as the step response of the RC circuit and establish a corrected exponential model; S2. Obtain voltage sampling time series data, and use the three-sum method to solve for the parameters of the corrected exponential model based on the voltage sampling time series data; S3. Substitute the parameters of the modified exponential model into the modified exponential model, output the steady-state voltage prediction value, and then input it into the insulation resistance calculation formula to obtain the insulation resistance.

[0006] Preferably, the specific process of step S2 is as follows: S201. Acquire voltage sampling time series data, and divide the voltage sampling time series into three equal and continuous parts, each part including n data points; S202. Calculate the observed values ​​for each part. S1, S2, S3; S203. Calculate trend value The sum of the three local values ;

[0007]

[0008]

[0009] k, a, and b are the parameters to be solved; S204. Based on trend values The sum of the three local values ​​is equal to the observed value. Using the idea of ​​summing three local values, we obtain three equations:

[0010] S205. Solving the three equations simultaneously yields estimation formulas for the three unknowns k, a, and b: .

[0011] Preferably, in step S205, the estimation formula for k is further calculated to eliminate the parameter b, resulting in:

[0012]

[0013] in The average of the three local values:

[0014] The calculated value of k is The final approximate value of the curve; if only the final trend needs to be predicted, then only the value of k needs to be calculated; if curve fitting is to be performed, then the values ​​of a and b also need to be calculated at the same time.

[0015] Preferably, in step S1, the data length of each part of the voltage sampling timing data is greater than an integer multiple of the circuit disturbance period.

[0016] Preferably, the specific process of step S1 is as follows: The voltage signal to be detected is essentially a step response of an RC circuit, and its time-domain dynamic response equation is:

[0017] Written in general form:

[0018] in: Let be the predicted voltage value at time t. ; k is the steady-state voltage approach value, ; a and b are fitting parameters to be determined, .

[0019] Preferably, in step S3, the insulation resistance calculation is applicable to the unbalanced bridge method, which specifically includes: Disconnect switches K1 and K2 to calculate the first set of voltages; Switch the switch states according to the voltage magnitude relationship to obtain the second set of voltages; Obtain the insulation resistance value based on the first set of voltages and the second set of voltages.

[0020] Preferably, the first set of voltages includes voltages U1 = u1 and U2 = u2;

[0021] The second set of voltages are respectively: If U1 < U2, disconnect K1 and close K2 to calculate voltages U1 = u'1 and U2 = u'2;

[0022] If U1 > U2, close K1 and disconnect K2 to calculate U1 = u''1 and U2 = u''2;

[0023] where R P , R N are respectively the insulation resistances of the positive and negative lines of the high-voltage circuit to the ground, R0 is a bias resistor with a known resistance value, and R1 and R2 are measurement voltage-dividing resistors.

[0024] The present invention also discloses a computer program product, including a computer program, and when the computer program is run by a processor, it executes the steps of the above-mentioned method.

[0025] The present invention further discloses a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, it executes the steps of the above-mentioned method.

[0026] The present invention also discloses an insulation resistance calculation system based on statistical curve fitting prediction, including a memory and a processor connected to each other, and a computer program is stored on the memory, and when the computer program is run by the processor, it executes the steps of the above-mentioned method.

[0027] Compared with the prior art, the advantages of the present invention are: The signal calculation and processing method of the present invention can calculate the steady-state voltage during the dynamic change of the signal without waiting for the signal to stabilize, and is not limited by the signal stabilization time. It reduces the insulation resistance calculation time and improves the detection speed by at least 1 to 2 orders of magnitude. The present invention calculates the steady-state voltage based on statistical curve fitting and prediction technology. It only needs to use the "three-sum method" to perform curve fitting and prediction according to the modified exponential model to calculate the measured steady-state voltage with high accuracy.

[0028] The signal calculation and processing method of the present invention can be used to detect insulation resistance by the unbalanced bridge method or the low-frequency signal injection method, but is not limited to the above two insulation resistance detection methods, and is applicable to a variety of insulation detection methods.

[0029] The signal calculation and processing method of the present invention does not depend on the parameters of the circuit being tested and is not affected by the parameters of the circuit being tested; the time for detecting insulation resistance using this signal calculation and processing method is only limited by the stabilization time of the detection circuit switch or the stabilization time of the excitation power supply and the sampling calculation period, and is not limited by the signal stabilization time; using this signal calculation and processing method to detect insulation resistance can significantly improve the insulation resistance detection speed and improve the insulation resistance detection accuracy. Attached Figure Description

[0030] Figure 1 This is a schematic diagram illustrating the principle of the "three-in-one method" in this invention.

[0031] Figure 2 This is a circuit diagram of the unbalanced bridge insulation detection method in this invention.

[0032] Figure 3 This is a flowchart of an embodiment of the insulation resistance calculation method of the present invention. Detailed Implementation

[0033] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0034] like Figure 3 As shown, the insulation resistance calculation method based on statistical curve fitting prediction provided in this embodiment of the invention includes the following steps: S1. Dynamic Signal Modeling: The voltage signal to be detected is essentially a step response of an RC circuit, and its time-domain dynamic response equation is:

[0035] Written in general form:

[0036] in: Let be the predicted voltage value at time t. k is the steady-state voltage approach value. a and b are the parameters to be fitted. ; It is clearly a standard modified exponential model, and the trend value k is unknown. Curve fitting and prediction can be performed according to the modified exponential model.

[0037] S2. Obtain voltage sampling time series data, and use the three-sum method to solve for the parameters of the corrected exponential model based on the voltage sampling time series data; For modified exponential models where the trend value k is unknown, the "three-sum method" is commonly used to estimate the parameters. The basic idea of ​​the "three-sum method" is: trend value k... The sum of the three local values ​​is equal to the original resource (observation value). The sum of three local values, such as Figure 1 As shown.

[0038] The basic steps for estimating model parameters using the three-sum method are as follows: S201. Acquire voltage sampling time series data, and divide the voltage sampling time series into three equal and continuous parts, each part including n data points; S202. Calculate the observed values ​​for each part. The sum of S1, S2, and S3 is as follows: ; S203. Calculate trend value The sum of the three local values (Including 3 unknowns k, a, b); Discrete summation formula for exponential functions:

[0039] From the above formula, we can obtain:

[0040]

[0041]

[0042] but:

[0043]

[0044]

[0045] S204. Based on trend values The sum of the three local values ​​is equal to the original resource (observation value). Using the idea of ​​summing three local values, we obtain three equations:

[0046] S205. Solving the three equations simultaneously yields estimation formulas for the three unknowns k, a, and b:

[0047] The third equation above can be further calculated to eliminate the parameter b, resulting in:

[0048]

[0049] in The average of the three local values:

[0050] The calculated value of k is The final approximate value of the curve. If only the final trend needs to be predicted, then only the value of k needs to be calculated; if curve fitting is required, then the values ​​of a and b also need to be calculated. S3. After finding the values ​​of k, a, and b, according to... Calculate That is, fitting the steady-state voltage value U (t) , will U (t) Substitute the values ​​into the insulation resistance calculation formula to calculate the insulation resistance value.

[0051] The formula for calculating k is identical in form to the expression for calculating the transfer function of an RC circuit using a bilinear transformation, except that the latter uses the average of three equally spaced samples.

[0052] Since the actual measured values ​​contain certain disturbances or interferences, the average value is obtained by calculating a certain number of measurement samples to filter out the interference. The final approximate value k of the modified exponential model is obtained by using the formula for calculating k, which can yield more accurate results.

[0053] The above derivation process uses t=1 as the initial value. The equation still holds true when t is any initial value m. That is:

[0054] Solving the equation now, we get:

[0055] It is evident that m only affects the calculation of parameter a, and has no effect on the calculation of parameters b and k. That is, the position of the data segment only affects the trend value. The initial value of t is (k+a) (the value at t=0). In reality, the starting time for calculating t is artificially defined; after obtaining the parameters of the fitted curve, it can be restored according to the defined t. The true time t0 is often unpredictable, and its value cannot be deliberately sought.

[0056] Due to the existence of the inverter, the signal perturbation is periodic, and the selection of the data segment needs to consider the period of the perturbation. When the length of each selected data segment is an integer multiple of the perturbation period, the perturbation can be completely eliminated. Since the actual perturbation period is unpredictable, the length of each selected data segment should be much larger than the perturbation period to obtain more accurate results.

[0057] The signal calculation and processing method of the present invention can calculate the steady-state voltage during the dynamic change process of the signal, without waiting for the signal to stabilize, is not limited by the signal stabilization time, reduces the insulation resistance calculation time, and realizes at least a 1-2 order of magnitude improvement in the detection speed; the present invention calculates the steady-state voltage based on the statistical curve fitting prediction technology, and only needs to perform curve fitting and prediction according to the modified exponential model by the "three-sum method" to calculate the measured steady-state voltage, with high accuracy.

[0058] The signal calculation and processing method of the present invention can be used for detecting insulation resistance by the unbalanced bridge method or the low-frequency signal injection method, but is not limited to the above two insulation resistance detection methods, and is applicable to various insulation detection methods.

[0059] The signal calculation and processing method of the present invention does not depend on the parameters of the detected circuit and is not affected by the parameters of the detected circuit; the time for detecting insulation resistance using this signal calculation and processing method is only limited by the stability time of the detection circuit switch or the excitation power supply stability time, and the sampling calculation period, and is not limited by the signal stability time; using this signal calculation and processing method to detect insulation resistance can greatly improve the insulation resistance detection speed, and at the same time can improve the insulation resistance detection accuracy.

[0060] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0061] Among them, insulation detection: measure the insulation resistance between the high-voltage side and the low-voltage housing side.

[0062] As Figure 2 shown, the insulation resistance calculation formula of the unbalanced bridge method insulation detection circuit is: Substitute the steady-state voltage into the insulation detection formula to calculate the insulation resistance value, and the calculation formula is as follows: Disconnect the K1 and K2 switches, and calculate the voltages U1 = u1 and U2 = u2; (1) If U1 < U2, disconnect K1 and close K2, and calculate the voltages U1 = u'1 and U2 = u'2; (2) If U1 > U2, close K1 and disconnect K2, and calculate U1 = u''1 and U2 = u''2; (3) Where R P R N R1 and R2 are the insulation resistances of the positive and negative lines of the high-voltage circuit to ground (vehicle body), respectively. R0 is a bias resistor with a known resistance value, and R1 and R2 are the voltage divider resistors for measurement.

[0063] The voltages in equations (1), (2), and (3) can all be obtained through formulas. Calculated, and the formula The same applies to low-frequency signal injection circuits, but is not limited to the two circuits mentioned above.

[0064] This invention also discloses a computer program product, comprising a computer program that, when run by a processor, performs the steps of the method described above. This invention further discloses a computer-readable storage medium storing a computer program that, when run by a processor, performs the steps of the method described above. This invention also discloses an insulation resistance calculation system based on statistical curve fitting prediction, comprising an interconnected memory and a processor, wherein the memory stores a computer program that, when run by a processor, performs the steps of the method described above. The products, media, and systems of this invention, corresponding to the methods described above, also possess the advantages described above.

[0065] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium includes: any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. The memory is used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0066] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for calculating insulation resistance based on statistical curve fitting prediction, characterized in that, It includes the following steps: S1. Identify the voltage signal to be measured in the insulation detection circuit as the step response of an RC circuit, and establish a modified exponential model; S2. Obtain the voltage sampling timing data. Based on the voltage sampling timing data, use the three-point method to solve the parameters of the modified exponential model; S3. Substitute the parameters of the modified exponential model into the modified exponential model, output the predicted value of the steady-state voltage, and then input it into the insulation resistance calculation formula to obtain the insulation resistance.

2. The insulation resistance calculation method based on statistical curve fitting prediction according to claim 1, characterized in that, The specific process of step S2 is as follows: S201. Obtain the voltage sampling timing data, divide the voltage sampling time series into three equal and continuous parts, and each part includes n data; S202. Calculate the observed values ​​for each part. S1, S2, S3; S203. Calculate trend value The sum of the three local values ; k, a, and b are parameters to be solved; S204. Based on trend values The sum of the three local values ​​is equal to the observed value. Using the idea of ​​summing three local values, we obtain three equations: S205. Solve the three equations simultaneously to obtain the estimation formulas for the three unknowns k, a, and b: 。 3. The insulation resistance calculation method based on statistical curve fitting prediction according to claim 2, characterized in that, In step S205, further operations on the estimation formula of k to eliminate the parameter b can obtain: in The average of the three local values: The calculated value of k is The curve eventually approaches the value; If only the final trend needs to be predicted, only the value of k needs to be calculated; if curve fitting is to be performed, the values of a and b also need to be calculated simultaneously.

4. The method for calculating insulation resistance based on statistical curve fitting prediction according to claim 2 or 3, characterized in that, In step S1, the data length of each part of the voltage sampling timing data is greater than an integer multiple of the circuit disturbance period.

5. The method for calculating insulation resistance based on statistical curve fitting prediction according to claim 1, 2, or 3, characterized in that, The specific process of step S1 is as follows: The voltage signal to be detected is essentially the step response of an RC circuit, and its time-domain dynamic response equation is: Written in a general form: in: Let be the predicted voltage value at time t. k is the steady-state voltage approach value. a and b are the parameters to be fitted. .

6. The method for calculating insulation resistance based on statistical curve fitting prediction according to claim 1, 2, or 3, characterized in that, In step S3, the insulation resistance calculation is applicable to the unbalanced bridge method, specifically including: Disconnect switches K1 and K2, and calculate the first set of voltages; Switch the switch state according to the voltage magnitude relationship to obtain the second set of voltages; Obtain the insulation resistance value based on the first set of voltages and the second set of voltages.

7. The insulation resistance calculation method based on statistical curve fitting prediction according to claim 6, characterized in that, The first set of voltages includes voltages U1 = u1 and U2 = u2; The second set of voltages are respectively: If U1 < U2, disconnect K1 and close K2, and calculate voltages U1 = u'1 and U2 = u'2; If U1 > U2, close K1 and disconnect K2, and calculate U1 = u''1 and U2 = u''2; Where R P R N R1 and R2 are the insulation resistances of the positive and negative lines of the high-voltage circuit to ground, respectively. R0 is a bias resistor with a known resistance value, and R1 and R2 are the voltage divider resistors for measurement.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is run by a processor, it executes the steps of the method described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by a processor, it executes the steps of the method described in any one of claims 1-7.

10. An insulation resistance calculation system based on statistical curve fitting prediction, comprising an interconnected memory and a processor, wherein the memory stores a computer program, characterized in that, When the computer program is run by a processor, it executes the steps of the method described in any one of claims 1-7.

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