Controller fault automatic detection method

Abstract

The invention discloses a controller fault automatic detection method, which comprises the following steps: acquiring real-time sine waves generated by a sine wave generator in an electric vehicle controller, and calculating the similarity between the real-time sine waves and standard sine waves; if the similarity is smaller than a preset similarity threshold value, it is judged that the sine wave generator breaks down; a real-time pulse width modulation signal waveform generated by a modulator in the electric vehicle controller is obtained, and the deviation degree between time domain information of the real-time pulse width modulation signal waveform and time domain information of the standard pulse width modulation signal waveform is calculated; if the deviation degree is larger than a preset deviation degree threshold value, modulator faults are judged, and error codes corresponding to the modulator faults are generated. The method for conducting automatic fault detection on the electric tricycle controller solves the problem that an existing manual troubleshooting mode is low in efficiency, and the method is simple and convenient to use. The device is suitable for overhauling equipment such as the electro-tricycle which is simple in structure and low in manufacturing cost.

Description

Technical Field

[0001] The invention relates to the field of electric vehicle controllers, and in particular to a method for automatically detecting controller faults. Background Art

[0002] With the development of society, electric tricycles are becoming more and more commonly used in transportation, express delivery, agriculture and household fields due to their convenience, energy saving, flexibility and economy. Like other motor equipment or vehicles, electric tricycles have controllers to control the driving power of electric vehicles. Due to various internal or external factors, the controller of the electric vehicle is one of the components with a higher frequency of damage. Therefore, automatic fault detection of the electric tricycle controller when the electric tricycle is being repaired can improve the maintenance efficiency.

[0003] However, the maintenance method of electric tricycles still uses manual troubleshooting to detect controller faults, and there is a lack of methods and equipment for automatic fault detection of electric tricycle controllers. In addition, electric tricycles are not suitable for complex and large-scale fault detection models due to their inherent characteristics of simple structure and low cost. Summary of the invention

[0004] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide a method for automatic detection of controller faults, aiming to solve the problem that the existing maintenance method of electric tricycles still uses manual troubleshooting to detect controller faults, lacks methods and equipment for automatic fault detection of electric tricycle controllers, and electric tricycles have a simple structure and low cost, and are not suitable for complex and large fault detection models.

[0005] In view of the above problems, the present application provides a method for automatically detecting controller faults.

[0006] In a first aspect disclosed in the present application, a method for automatically detecting a controller fault is provided, the method comprising the following steps: Step 1: Obtain the real-time sine wave generated by the sine wave generator in the electric vehicle controller, and calculate the similarity between the real-time sine wave and the standard sine wave; Step 2: If the similarity between the real-time sine wave and the standard sine wave is less than a preset similarity threshold, it is determined that the sine wave generator is faulty, and an error code corresponding to the sine wave generator fault is generated; Step 3: Obtain the real-time pulse width modulation signal waveform generated by the modulator in the electric vehicle controller, determine the time domain information of the real-time pulse width modulation signal waveform, and calculate the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform; Step 4: If the deviation between the time domain information of the real-time PWM signal waveform and the time domain information of the standard PWM signal waveform is greater than a preset deviation threshold, it is determined to be a modulator failure, and an error code corresponding to the modulator failure is generated.

[0007] Preferably, the step 1 specifically includes the following steps: Step 1.1: Obtain a real-time sine wave generated by a sine wave generator in an electric vehicle controller, sample a waveform of one cycle in the real-time sine wave, generate a waveform to be detected, sample a waveform of one cycle in a standard sine wave, generate a comparison waveform, wherein the standard sine wave is a sine wave waveform in a pre-stored normal situation; Step 1.2: Calculate the average value of the waveform to be detected and the average value of the comparison waveform using formula (1), where: and They are used to represent the waveform to be detected and the comparison waveform respectively. Used to represent the period of real-time sine wave and standard sine wave. Used to represent the number of milliseconds in the waveform time axis. and They are used to represent the average value of the waveform to be detected and the average value of the comparison waveform respectively: Formula (1); Step 1.3: According to the average value of the waveform to be detected and the average value of the comparison waveform, the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform are calculated using formula (2), where: and They are used to represent the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform respectively: Formula (2); Step 1.4: According to the average value of the waveform to be detected and the average value of the comparison waveform, the covariance between the waveform to be detected and the comparison waveform is calculated using formula (3), where: Used to represent the covariance between the waveform to be detected and the comparison waveform: Formula (3); Step 1.5: According to the covariance between the waveform to be detected and the comparison waveform, the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform, the Pearson correlation coefficient between the waveform to be detected and the comparison waveform is calculated using formula (4), where: Used to represent the Pearson correlation coefficient between the waveform to be detected and the comparison waveform: Formula (4); Step 1.6: The Pearson correlation coefficient between the waveform to be detected and the comparison waveform is taken as the similarity between the real-time sine wave and the standard sine wave.

[0008] Preferably, the step 2 specifically includes the following steps: Step 2.1: If the similarity between the real-time sine wave and the standard sine wave is less than a preset similarity threshold and greater than or equal to 97% of the preset similarity threshold, it is determined that the sine wave generator is interfered with, and an error code corresponding to the interference of the sine wave generator is generated; Step 2.2: If the similarity between the real-time sine wave and the standard sine wave is less than 97% of the preset similarity threshold, it is determined that the sine wave generator is faulty, and an error code corresponding to the sine wave generator fault is generated.

[0009] Preferably, the step 3 specifically includes the following steps: Step 3.1: Obtain the real-time pulse width modulation signal waveform generated by the modulator in the electric vehicle controller under three simulated loads, and respectively measure the period, frequency and duty cycle of the real-time pulse width modulation signal waveform generated under the three simulated loads, wherein the three simulated loads are loads of 25%, 50% and 75% of the maximum power of the simulated electric vehicle; Step 3.2: Obtain the period, frequency and duty cycle of the standard pulse width modulation signal waveform under three simulated loads, wherein the standard pulse width modulation signal waveform is the pulse width modulation signal waveform under each simulated load in the normal condition stored in advance; Step 3.3: Calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 25% of the maximum power of the simulated electric vehicle, and generate a first deviation; calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 50% of the maximum power of the simulated electric vehicle, and generate a second deviation; calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 75% of the maximum power of the simulated electric vehicle, and generate a third deviation; Step 3.4: Obtain the maximum value among the first deviation, the second deviation and the third deviation, and generate the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform.

[0010] Preferably, the step 4 specifically includes the following steps: Step 4.1: If the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform is greater than a preset deviation threshold and is less than or equal to 125% of the preset deviation threshold, it is determined that the modulator is interfered with or the component performance is unstable, and an error code corresponding to the modulator being interfered with or the component performance being unstable is generated; Step 4.2: If the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform is greater than 125% of the preset deviation threshold, it is determined to be a modulator integrity failure, and an error code corresponding to the modulator integrity failure is generated.

[0011] A second aspect disclosed in the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method for automatic detection of controller faults when executing the computer program.

[0012] According to a third aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for automatic detection of controller faults are implemented.

[0013] The fourth aspect disclosed in the present application provides a computer program product, including a computer program or instructions, which implement the steps of the above-mentioned method for automatic detection of controller faults when executed by a processor.

[0014] The beneficial effects of the present invention are: (1) A controller fault automatic detection method is provided to automatically detect faults of the electric tricycle controller, solving the problem of low efficiency of the existing manual troubleshooting method.

[0015] (2) Each device of the electric tricycle controller is tested separately and specifically, and the method is simple and suitable for the maintenance of electric tricycles, which are simple in structure and low in cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 The figure is an overall flow chart of a controller fault automatic detection method. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, an embodiment of the present application provides a method for automatically detecting a controller fault, the method comprising the following steps: Step 1: Obtain the real-time sine wave generated by the sine wave generator in the electric vehicle controller, and calculate the similarity between the real-time sine wave and the standard sine wave; Step 2: If the similarity between the real-time sine wave and the standard sine wave is less than a preset similarity threshold, it is determined that the sine wave generator is faulty, and an error code corresponding to the sine wave generator fault is generated; Step 3: Obtain the real-time pulse width modulation signal waveform generated by the modulator in the electric vehicle controller, determine the time domain information of the real-time pulse width modulation signal waveform, and calculate the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform; Step 4: If the deviation between the time domain information of the real-time PWM signal waveform and the time domain information of the standard PWM signal waveform is greater than a preset deviation threshold, it is determined to be a modulator failure, and an error code corresponding to the modulator failure is generated.

[0020] Furthermore, the step 1 specifically includes the following steps: Step 1.1: Obtain a real-time sine wave generated by a sine wave generator in an electric vehicle controller, sample a waveform of one cycle in the real-time sine wave, generate a waveform to be detected, sample a waveform of one cycle in a standard sine wave, generate a comparison waveform, wherein the standard sine wave is a sine wave waveform in a pre-stored normal situation; Step 1.2: Calculate the average value of the waveform to be detected and the average value of the comparison waveform using formula (1), where: and They are used to represent the waveform to be detected and the comparison waveform respectively. Used to represent the period of real-time sine wave and standard sine wave. Used to represent the number of milliseconds in the waveform time axis. and They are used to represent the average value of the waveform to be detected and the average value of the comparison waveform respectively: Formula (1); Step 1.3: According to the average value of the waveform to be detected and the average value of the comparison waveform, the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform are calculated using formula (2), where: and They are used to represent the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform respectively: Formula (2); Step 1.4: According to the average value of the waveform to be detected and the average value of the comparison waveform, the covariance between the waveform to be detected and the comparison waveform is calculated using formula (3), where: Used to represent the covariance between the waveform to be detected and the comparison waveform: Formula (3); Step 1.5: According to the covariance between the waveform to be detected and the comparison waveform, the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform, the Pearson correlation coefficient between the waveform to be detected and the comparison waveform is calculated using formula (4), where: Used to represent the Pearson correlation coefficient between the waveform to be detected and the comparison waveform: Formula (4); Step 1.6: The Pearson correlation coefficient between the waveform to be detected and the comparison waveform is taken as the similarity between the real-time sine wave and the standard sine wave.

[0021] Furthermore, the step 2 specifically includes the following steps: Step 2.1: If the similarity between the real-time sine wave and the standard sine wave is less than a preset similarity threshold and greater than or equal to 97% of the preset similarity threshold, it is determined that the sine wave generator is interfered with, and an error code corresponding to the interference of the sine wave generator is generated; Step 2.2: If the similarity between the real-time sine wave and the standard sine wave is less than 97% of the preset similarity threshold, it is determined that the sine wave generator is faulty, and an error code corresponding to the sine wave generator fault is generated.

[0022] Furthermore, the step 3 specifically includes the following steps: Step 3.1: Obtain the real-time pulse width modulation signal waveform generated by the modulator in the electric vehicle controller under three simulated loads, and respectively measure the period, frequency and duty cycle of the real-time pulse width modulation signal waveform generated under the three simulated loads, wherein the three simulated loads are loads of 25%, 50% and 75% of the maximum power of the simulated electric vehicle; Step 3.2: Obtain the period, frequency and duty cycle of the standard pulse width modulation signal waveform under three simulated loads, wherein the standard pulse width modulation signal waveform is the pulse width modulation signal waveform under each simulated load in the normal condition stored in advance; Step 3.3: Calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 25% of the maximum power of the simulated electric vehicle, and generate a first deviation; calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 50% of the maximum power of the simulated electric vehicle, and generate a second deviation; calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 75% of the maximum power of the simulated electric vehicle, and generate a third deviation; Step 3.4: Obtain the maximum value among the first deviation, the second deviation and the third deviation, and generate the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform.

[0023] Furthermore, the step 4 specifically includes the following steps: Step 4.1: If the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform is greater than a preset deviation threshold and is less than or equal to 125% of the preset deviation threshold, it is determined that the modulator is interfered with or the component performance is unstable, and an error code corresponding to the modulator being interfered with or the component performance being unstable is generated; Step 4.2: If the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform is greater than 125% of the preset deviation threshold, it is determined to be a modulator integrity failure, and an error code corresponding to the modulator integrity failure is generated.

[0024] In summary, the controller fault automatic detection method provided by the embodiment of the present application has the following technical effects: (1) A controller fault automatic detection method is provided to automatically detect faults of the electric tricycle controller, solving the problem of low efficiency of the existing manual troubleshooting method.

[0025] (2) Each device of the electric tricycle controller is tested separately and specifically, and the method is simple and suitable for the maintenance of electric tricycles, which are simple in structure and low in cost.

[0026] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of the above-mentioned controller fault automatic detection method when executing the computer program.

[0027] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned controller fault automatic detection method are implemented.

[0028] In one embodiment, a computer program product is provided, including a computer program or instructions, which implement the steps of the above-mentioned controller fault automatic detection method when executed by a processor.

[0029] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0030] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A controller fault automatic detection method, characterized in that: The method comprises the following steps: Step 1: Obtain the real-time sine wave generated by the sine wave generator in the electric vehicle controller, and calculate the similarity between the real-time sine wave and the standard sine wave; Step 2: If the similarity between the real-time sine wave and the standard sine wave is less than a preset similarity threshold, it is determined that the sine wave generator is faulty, and an error code corresponding to the sine wave generator fault is generated; Step 3: Obtain the real-time pulse width modulation signal waveform generated by the modulator in the electric vehicle controller, determine the time domain information of the real-time pulse width modulation signal waveform, and calculate the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform; Step 4: If the deviation between the time domain information of the real-time PWM signal waveform and the time domain information of the standard PWM signal waveform is greater than a preset deviation threshold, it is determined to be a modulator failure, and an error code corresponding to the modulator failure is generated.

2. A controller fault automatic detection method as claimed in claim 1, characterized in that: The step 1 specifically comprises the following steps: Step 1.1: Obtain a real-time sine wave generated by a sine wave generator in an electric vehicle controller, sample a waveform of one cycle in the real-time sine wave, generate a waveform to be detected, sample a waveform of one cycle in a standard sine wave, generate a comparison waveform, wherein the standard sine wave is a sine wave waveform in a pre-stored normal situation; Step 1.2: Calculate the average value of the waveform to be detected and the average value of the comparison waveform using formula (1), where: and They are used to represent the waveform to be detected and the comparison waveform respectively. Used to represent the period of real-time sine wave and standard sine wave. Used to represent the number of milliseconds in the waveform time axis. and They are used to represent the average value of the waveform to be detected and the average value of the comparison waveform respectively: Formula (1); Step 1.3: According to the average value of the waveform to be detected and the average value of the comparison waveform, the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform are calculated using formula (2), where: and They are used to represent the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform respectively: Formula (2); Step 1.4: According to the average value of the waveform to be detected and the average value of the comparison waveform, the covariance between the waveform to be detected and the comparison waveform is calculated using formula (3), where: Used to represent the covariance between the waveform to be detected and the comparison waveform: Formula (3); Step 1.5: According to the covariance between the waveform to be detected and the comparison waveform, the standard deviation of the waveform to be detected and the standard deviation of the comparison waveform, the Pearson correlation coefficient between the waveform to be detected and the comparison waveform is calculated using formula (4), where: Used to represent the Pearson correlation coefficient between the waveform to be detected and the comparison waveform: Formula (4); Step 1.6: The Pearson correlation coefficient between the waveform to be detected and the comparison waveform is taken as the similarity between the real-time sine wave and the standard sine wave.

3. A controller fault automatic detection method as claimed in claim 2, characterized in that: The step 2 specifically includes the following steps: Step 2.1: If the similarity between the real-time sine wave and the standard sine wave is less than a preset similarity threshold and greater than or equal to 97% of the preset similarity threshold, it is determined that the sine wave generator is interfered with, and an error code corresponding to the interference of the sine wave generator is generated; Step 2.2: If the similarity between the real-time sine wave and the standard sine wave is less than 97% of the preset similarity threshold, it is determined that the sine wave generator is faulty, and an error code corresponding to the sine wave generator fault is generated.

4. A controller fault automatic detection method as claimed in claim 3, characterized in that: The step 3 specifically comprises the following steps: Step 3.1: Obtain the real-time pulse width modulation signal waveform generated by the modulator in the electric vehicle controller under three simulated loads, and respectively measure the period, frequency and duty cycle of the real-time pulse width modulation signal waveform generated under the three simulated loads, wherein the three simulated loads are loads of 25%, 50% and 75% of the maximum power of the simulated electric vehicle; Step 3.2: Obtain the period, frequency and duty cycle of the standard pulse width modulation signal waveform under three simulated loads, wherein the standard pulse width modulation signal waveform is the pulse width modulation signal waveform under each simulated load in the normal condition stored in advance; Step 3.3: Calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 25% of the maximum power of the simulated electric vehicle, and generate a first deviation; calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 50% of the maximum power of the simulated electric vehicle, and generate a second deviation; calculate the average value of the absolute value of the deviation of the period, frequency and duty cycle between the real-time pulse width modulation signal waveform and the standard pulse width modulation signal waveform under a load of 75% of the maximum power of the simulated electric vehicle, and generate a third deviation; Step 3.4: Obtain the maximum value among the first deviation, the second deviation and the third deviation, and generate the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform.

5. A controller fault automatic detection method as claimed in claim 4, characterized in that: The step 4 specifically comprises the following steps: Step 4.1: If the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform is greater than a preset deviation threshold and is less than or equal to 125% of the preset deviation threshold, it is determined that the modulator is interfered with or the component performance is unstable, and an error code corresponding to the modulator being interfered with or the component performance being unstable is generated; Step 4.2: If the deviation between the time domain information of the real-time pulse width modulation signal waveform and the time domain information of the standard pulse width modulation signal waveform is greater than 125% of the preset deviation threshold, it is determined to be a modulator integrity failure, and an error code corresponding to the modulator integrity failure is generated.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of a controller fault automatic detection method described in any one of claims 1 to 5 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a controller fault automatic detection method according to any one of claims 1 to 5 are implemented.

8. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of a controller fault automatic detection method described in any one of claims 1 to 5 are implemented.

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