Electric bicycle charging circuit fault arc grading early warning method

Abstract

The invention discloses an electric bicycle charging circuit fault arc grading early warning method, and belongs to the technical field of electric bicycle charging circuit fault arc diagnosis. According to the method, the disaster-causing possibility of the fault arc is distinguished by estimating the incandescent energy of the fault arc, and the disaster-causing possibility is used as a basis for reducing the false alarm rate and the leakage protection rate of a traditional fault arc detection method, so that the method is more scientific and applicable, the electric bicycle charging pile can be better assisted to complete the decision of charging fault protection, and the fault protection efficiency is improved. On the premise of ensuring the charging safety of the electric bicycle as much as possible, the electric fire caused by the fault arc is effectively restrained.

Description

Technical Field

[0001] The invention relates to the technical field of electric bicycle charging line fault arc diagnosis, and in particular to an electric bicycle charging line fault arc graded early warning method. Background Art

[0002] Research and analysis show that the main causes of electrical fires during the charging process of electric bicycles include faults in the electric bicycle battery, the charger itself and the mismatch between the two, aging lines, private wiring, poor contact and other factors. Among them, battery failure and fault arcs caused by aging lines and poor contact are the main hidden dangers of disasters (the fault arc itself can also damage the electric bicycle battery and its charger).

[0003] In order to deal with possible fire accidents during the charging process of electric bicycles, the industry has developed a large number of fault arc detection devices that can be used for electric bicycle charging piles. However, due to the uneven quality of chargers during the charging process of electric bicycles, the charging circuit contains a large number of high-frequency harmonics, which makes the existing fault arc detection devices have a large number of false operations. In addition, even if there is a fault arc in the charging line of an electric bicycle, due to the sporadic nature of the fault arc and the different burning degrees, not all fault arcs have the potential to cause disasters. For such fault arcs, the circuit breaking treatment seriously interferes with the normal charging behavior of the electric bicycle. To this end, a graded warning method for fault arcs in the charging line of an electric bicycle is proposed. Summary of the invention

[0004] The technical problem to be solved by the present invention is: how to solve the technical difficulties that the existing fault arc detection device has low accuracy in identifying fault arcs and cannot evaluate the possibility of disasters caused by fault arcs, and provides a graded early warning method for fault arcs in electric bicycle charging lines.

[0005] like Figure 1 As shown, the present invention solves the above technical problems through the following technical solutions, and the present invention comprises the following steps:

[0006] S1: Collecting the charging current signal of the electric bicycle, and obtaining the arc burning voltage signal of the electric bicycle charging line fault arc based on the collected charging current signal of the electric bicycle, the basic transformation relationship of the circuit equation and the fault arc equivalent model;

[0007] S2: Calculate the arc fault characteristics of the collected electric bicycle charging current signal, and determine the burning time of the fault arc of the electric bicycle charging line based on the change law of the arc fault characteristics of the electric bicycle charging current;

[0008] S3: based on the collected charging current signal of the electric bicycle, the obtained arcing voltage signal of the fault arc, and the determined burning time of the fault arc, the burning energy of the fault arc is obtained;

[0009] S4: A graded warning of the fault arc in the electric bicycle charging line is realized based on the burning energy of the fault arc.

[0010] Furthermore, in step S1, the process of collecting the charging current signal of the electric bicycle is as follows:

[0011] S11: Connecting a manganese copper resistor with a set resistance in series to a charging circuit of the electric bicycle;

[0012] S12: collecting voltage signals at both ends of the manganese copper resistor;

[0013] S13: The voltage signal is inverted at a set ratio to obtain a charging current signal of the electric bicycle.

[0014] Furthermore, in step S1, the fault arc equivalent model is the Cassie arc model, and the basic transformation relationship of the circuit equation is the inverse relationship between conductance and current, thereby obtaining the arc voltage signal of the electric bicycle charging line fault arc as follows:

[0015] ;

[0016] in, is the voltage constant of the Cassie arc model; is the time constant of the Cassie arc model; is the time derivative of the electric bicycle charging current signal sequence, Charging current signal for electric bicycles.

[0017] Furthermore, in step S2, the specific process is as follows:

[0018] S21: Divide the charging current signal of the electric bicycle into M parts, so that each current signal has a length of a current half-wave cycle, and perform differential transformation on the charging current signal of the electric bicycle in each current half-wave cycle to obtain a differential charging current signal of the electric bicycle. , M is a positive integer;

[0019] S22: Calculate the differential charging current signal Arc fault characteristics :

[0020] ;

[0021] Wherein, N is the length of a current half-wave cycle of the electric bicycle charging current signal and its differential charging current signal; is the discrete sequence of the electric bicycle charging current signal, For The current signal sequence after differential processing, for The mean of

[0022] S23: Arc fault characteristics of M current signals calculated every second Combined into the fault feature vector of the electric bicycle charging current signal ;

[0023] S24: The fault feature vector of the electric bicycle charging current signal Input to the fault arc detection algorithm to determine whether the electric bicycle charging current signal carries fault arc information, and then detect the fault arc according to the arc fault characteristics. The changing rules in different current half-wave cycles determine the burning time of the line fault arc within an observation window .

[0024] Furthermore, in step S24, the arc fault characteristics exceeding the preset arc fault characteristic threshold value within each second are recorded. The number of half-wave current durations determines the burning time of the line fault arc within an observation window. .

[0025] Furthermore, in step S3, the burning energy of the fault arc The calculation formula is as follows:

[0026]

[0027] in, It is the arcing voltage signal sequence of the fault arc.

[0028] Furthermore, in step S4, the specific processing process is as follows:

[0029] S41: The burning energy of the fault arc based on The maximum value that can appear is normalized to obtain the arc burning energy factor :

[0030] ;

[0031] S42: Real-time calculation of arc burning energy factor of electric bicycle charging current signal ,according to The value divides the electric bicycle charging line fault arc into three levels for alarm.

[0032] Furthermore, in step S42, It means that the charging circuit of the electric bicycle is in good condition. It indicates that there is a weak fault arc in the electric bicycle line. It indicates that there is a severe fault arc in the electric bicycle line that may cause a disaster.

[0033] Compared with the prior art, the present invention has the following advantages: the electric bicycle charging line fault arc graded warning method, through the reverse voltage transformation of the electric bicycle charging current signal to be processed and the arc fault feature detection processing, completes the calculation of the arc voltage and arc time of the potential fault arc carried in the electric bicycle charging current signal to be processed, and then performs an integral operation on the product of the arc voltage and the arc current of the fault arc within the arcing cycle to obtain the energy integral of the electric bicycle charging line fault arc, and completes the graded warning of the electric bicycle charging line fault arc based on the fault arc burning energy. Compared with the traditional fault arc detection algorithm method, the present invention has the following beneficial technical effects: the method distinguishes the disaster-causing possibility of the fault arc by estimating the fault arc burning energy, and uses this as the basis for reducing the false alarm rate and leakage rate of the traditional fault arc detection method, which is more scientific and applicable, and can better assist the electric bicycle charging pile to complete the decision-making of charging fault protection, and realize the effective containment of electrical fires caused by fault arcs on the premise of ensuring the charging safety of electric bicycles as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flow chart of the arc classification early warning method for fault in the charging circuit of an electric bicycle according to the present invention. DETAILED DESCRIPTION

[0035] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0036] This embodiment provides a technical solution: a method for hierarchical early warning of arc faults in an electric bicycle charging line, comprising the following steps:

[0037] Step 1: Use the GD32F103 chip to collect the voltage signal at both ends of the manganese copper resistor, and invert the voltage signal by a certain proportion to obtain the charging current of the electric bicycle, and generate the charging current signal sequence of the electric bicycle to be processed ;

[0038] In this embodiment, the resistance of the manganese copper resistor is 10 , which is connected in series with the electric bicycle charging line. In addition, the fault arc classification warning method for the electric bicycle charging line generally performs fault arc diagnosis in seconds, and due to the cost and performance limitations of embedded software and hardware, the main current signal sequence In this embodiment, it refers to the current signal sequence of a certain second, and according to the response characteristics of the electric bicycle charger and battery to the circuit voltage, the current signal sampling frequency used in this embodiment is 40 kHz, that is, the main current signal sequence The length is 40k.

[0039] Step 2: Use the basic transformation relationship of the circuit equation and the fault arc equivalent model to inversely transform the electric bicycle charging current signal to obtain the arc voltage signal of the electric bicycle charging line fault arc .

[0040] In this embodiment, the fault arc equivalent model is the Cassie arc model, and the specific expression is: , the basic transformation relationship of the circuit equation is the inverse relationship between conductance and current. The above relationship can be used to obtain the equivalent transformation of the Cassie arc model, that is, the arc voltage signal of the electric bicycle charging line fault arc:

[0041] ;

[0042] in, is the voltage constant of the Cassie arc model, which can be specifically expressed as the arc fault characteristics of the electric bicycle charging current signal Characterization; is the time constant of the Cassie arc model; Take the time derivative of the electric bicycle charging current signal sequence.

[0043] Step 3: Calculate the arc fault characteristics of the electric bicycle charging current signal , the specific steps are:

[0044] According to the requirements of GB14287.4 for arc fault detection, the charging current signal of the electric bicycle is divided into 100 parts so that each current signal is just the length of a half cycle. The charging current signal of the electric bicycle is differentially transformed for each half-wave cycle of the current to obtain the differential charging current signal of the electric bicycle. ;

[0045] Obtaining the differential charging current signal Arc fault characteristics , specifically, its expression is:

[0046] ;

[0047] Among them, N is the length of the electric bicycle charging current signal and its differential charging current signal in one current half-wave cycle. It should be pointed out that according to the preset current signal sampling rate of 40 kHz in this embodiment, the value of N here is 400, that is, the length of the electric bicycle charging current signal in one current half-wave cycle is 400.

[0048] It should be noted that the arc fault characteristics It is an intermediate feature constructed by the above mathematical transformation in the method of the present invention, and has better performance in the subsequent processing of the method of the present invention.

[0049] Step 4: Compute the arc fault characteristics of 100 current signals calculated every second Combined into the fault feature vector of the electric bicycle charging current signal .

[0050] Step 5: Convert the fault feature vector of the electric bicycle charging current signal Input to the fault arc detection algorithm to determine a priori whether the electric bicycle charging current signal carries fault arc information, and The changing rules in different current half-wave cycles determine the burning time of the line fault arc within an observation window .

[0051] It should be noted that the burning time of the fault arc in this embodiment is It is the actual duration of the fault arc.

[0052] In this embodiment, the arc fault detection algorithm determines whether the arc fault information is carried in the current signal based on the degree of distortion of the current signal.

[0053] Step 6: Calculate the energy integral of the fault arc in the electric bicycle charging line during the arcing period to obtain the burning energy of the fault arc , its specific expression is:

[0054] .

[0055] In this embodiment, the burning energy of the fault arc is the energy released by the fault arc calculated based on the equivalent circuit model, that is, the time integral of the voltage and current.

[0056] Step 7: Convert the ignition energy of the fault arc based on The maximum value that can appear is normalized to obtain the arc burning energy factor :

[0057] .

[0058] Step 8: Calculate the arc burning energy factor of the electric bicycle charging current signal in real time according to The value divides the electric bicycle charging line fault arc into three levels for alarm.

[0059] In this embodiment, It means that the charging circuit of the electric bicycle is in good condition. It indicates that there is a weak fault arc in the electric bicycle line. It indicates that there is a severe fault arc in the electric bicycle line that may cause a disaster.

[0060] It should be noted that, in this embodiment, the energy integration of the current signal and the arc voltage signal within the burning time of the fault arc is added. By calculating the correlation between the arc voltage and the arc current, the interference of external harmonics can be better filtered out, and the possibility of false alarm of the original fault arc detection algorithm can be better reduced without interfering with the sensitivity of the original fault arc detection algorithm, thereby ensuring the reliability and anti-interference ability of the electric bicycle charging line fault arc detection graded warning method proposed in the present invention for the electric bicycle charging line.

[0061] To sum up, the electric bicycle charging line fault arc graded warning method in the above-mentioned embodiment only needs to perform reverse voltage conversion and energy integration on the electric bicycle charging current signal to realize the monitoring and evaluation of potential fault arcs in the electric bicycle charging line. It can effectively solve the industry problem that the existing fault arc detection technology is difficult or even impossible to complete the evaluation of the possibility of disasters caused by fault arcs in electric bicycle charging lines, and then cannot accurately screen occasional arcs or catastrophic arcs. In addition, the implementation of the overall solution has low requirements on hardware circuits, which is convenient for promotion and application.

[0062] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A classification warning method for arc fault in an electric bicycle charging line, characterized in that: The following steps are involved: S1: Collecting the charging current signal of the electric bicycle, and obtaining the arc burning voltage signal of the electric bicycle charging line fault arc based on the collected charging current signal of the electric bicycle, the basic transformation relationship of the circuit equation and the fault arc equivalent model; S2: Calculate the arc fault characteristics of the collected electric bicycle charging current signal, and determine the burning time of the fault arc of the electric bicycle charging line based on the change law of the arc fault characteristics of the electric bicycle charging current; S3: based on the collected charging current signal of the electric bicycle, the obtained arcing voltage signal of the fault arc, and the determined burning time of the fault arc, the burning energy of the fault arc is obtained; S4: A graded warning of the fault arc in the electric bicycle charging line is realized based on the burning energy of the fault arc.

2. The electric bicycle charging line fault arc classification warning method according to claim 1 is characterized in that: In step S1, the process of collecting the charging current signal of the electric bicycle is as follows: S11: Connecting a manganese copper resistor with a set resistance in series to a charging circuit of the electric bicycle; S12: collecting voltage signals at both ends of the manganese copper resistor; S13: The voltage signal is inverted at a set ratio to obtain a charging current signal of the electric bicycle.

3. The electric bicycle charging line fault arc classification warning method according to claim 2 is characterized in that: In step S1, the fault arc equivalent model is the Cassie arc model, and the basic transformation relationship of the circuit equation is the inverse relationship between conductance and current, thereby obtaining the arc voltage signal of the electric bicycle charging line fault arc as follows: ； in, is the voltage constant of the Cassie arc model; is the time constant of the Cassie arc model; is the time derivative of the electric bicycle charging current signal sequence, Charging current signal for electric bicycles.

4. The electric bicycle charging line fault arc classification warning method according to claim 3 is characterized in that: In step S2, the specific process is as follows: S21: Divide the charging current signal of the electric bicycle into M parts, so that each current signal has a length of a current half-wave cycle, and perform differential transformation on the charging current signal of the electric bicycle in each current half-wave cycle to obtain a differential charging current signal of the electric bicycle. , M is a positive integer; S22: Calculate the differential charging current signal Arc fault characteristics : ； Wherein, N is the length of a current half-wave cycle of the electric bicycle charging current signal and its differential charging current signal; is the discrete sequence of the electric bicycle charging current signal, For The current signal sequence after differential processing, for The mean of S23: Arc fault characteristics of M current signals calculated every second Combined into the fault feature vector of the electric bicycle charging current signal ; S24: The fault feature vector of the electric bicycle charging current signal Input to the fault arc detection algorithm to determine whether the electric bicycle charging current signal carries fault arc information, and then detect the fault arc according to the arc fault characteristics. The changing rules in different current half-wave cycles determine the burning time of the line fault arc within an observation window .

5. The electric bicycle charging line fault arc classification warning method according to claim 4 is characterized in that: In step S24, the arc fault characteristics exceeding the preset arc fault characteristic threshold value are recorded every second. The number of half-wave current durations determines the burning time of the line fault arc within an observation window. .

6. The electric bicycle charging line fault arc classification warning method according to claim 4 is characterized in that: In step S3, the burning energy of the fault arc The calculation formula is as follows: in, It is the arcing voltage signal sequence of the fault arc.

7. The electric bicycle charging line fault arc classification warning method according to claim 1 or 6, characterized in that: In step S4, the specific processing process is as follows: S41: The burning energy of the fault arc based on The maximum value that can appear is normalized to obtain the arc burning energy factor : ； S42: Real-time calculation of arc burning energy factor of electric bicycle charging current signal ,according to The value divides the electric bicycle charging line fault arc into three levels for alarm.

8. The electric bicycle charging line fault arc classification warning method according to claim 7 is characterized in that: In step S42, It indicates that the charging circuit of the electric bicycle is in good condition. It indicates that there is a weak fault arc in the electric bicycle line. It indicates that there is a severe fault arc in the electric bicycle line that may cause a disaster.

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