Operation self-checking method and system for intelligent shared charging pile, and medium

Abstract

The invention provides an operation self-checking method and system for an intelligent shared charging pile, and a medium, and belongs to the field of charging pile management. The problem of low self-checking efficiency of the charging pile is solved; the method specifically comprises the following steps: S1, acquiring charging pile data; s2, acquiring historical charging data of the charging pile, and constructing a pre-estimation equation A and a pre-estimation equation B; s3, a charging request of the electric vehicle is obtained, the maximum output voltage and the maximum output current of the charging pile are estimated in combination with the estimation equation A and the estimation equation B, the maximum output voltage and the maximum output current are compared with the actual output voltage and the actual output current of the charging pile, and whether the charging pile is normal or not is judged; if normal, not processing; if not, marking the charging pile with the fault; s4, continuously monitoring the charging piles, summarizing the charging piles with faults, and feeding back the summarized charging piles; according to the invention, the related data of the charging pile is acquired, analyzed and processed, the electrical parameter change of the charging pile in the charging process is analyzed, and the self-checking efficiency of the operation of the charging pile is improved.

Description

Technical Field

[0001] A method, system and medium for self-checking the operation of an intelligent shared charging pile according to the present invention relate to the field of charging pile management. Background Art

[0002] The existing methods or systems for self-checking the operation of shared charging piles have the following deficiencies:

[0003] High maintenance cost: The existing self-checking systems integrate various technologies such as network communication, data processing, and remote monitoring, resulting in relatively high manufacturing costs; in order to ensure the stability and reliability of the system, high-quality hardware devices and advanced software algorithms need to be used, further increasing the cost.

[0004] Dependence on network stability: The normal operation of the self-checking system for operation depends on a stable network infrastructure; if the network signal is unstable or interrupted, it will cause data transmission delay or failure, affecting the real-time monitoring and fault diagnosis functions of the system.

[0005] Accuracy problem: Most of the existing self-checking algorithms are based on the threshold comparison of the rated working data of the charging pile and do not have the ability to analyze data, which will lead to the situation of "the charging pile works normally but the electric vehicle charges abnormally (that is, the output power of the charging pile does not match the charging power of the electric vehicle)", posing a safety hazard. Summary of the Invention

[0006] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a method, system and medium for self-checking the operation of an intelligent shared charging pile, aiming to solve the problem of low self-checking efficiency of the charging pile.

[0007] In order to achieve the above purpose, the present invention is realized by the following technical solutions: A method for self-checking the operation of an intelligent shared charging pile, the method includes:

[0008] Step S1: Obtain the number of charging piles, obtain the maximum rated power, maximum rated current and maximum rated voltage of the charging piles to obtain charging pile data;

[0009] Step S2: Obtain the historical charging data of the charging piles; perform a first mathematical modeling on the historical charging data, analyze the change in the charging time of the charging pile when the battery overheat protection occurs and does not occur during the charging process of the electric vehicle, and construct a prediction equation A; perform a second mathematical modeling on the historical charging data, analyze the change in the output voltage and charging current of the charging pile with the charging power and charging time, and construct a prediction equation B;

[0010] Step S3: Obtain the charging request of the tram, detect whether battery overheat protection occurs during the charging process of the tram, and combine Estimation Equation A and Estimation Equation B to estimate the maximum output voltage and maximum output current of the charging pile during charging; obtain the actual output voltage and actual output current of the charging pile, and compare them with the maximum output voltage and maximum output current to determine whether the charging process of the charging pile is normal; if it is normal, do not process; if it is not normal, mark the charging pile with a fault.

[0011] Step S4: Continuously monitor the charging process of the charging pile, summarize the charging piles with faults, and give feedback.

[0012] Further, the specific steps of Step S2 are as follows:

[0013] Step S21: Obtain the number of charging piles ch; obtain the number of charging times ne of all charging piles (1) ~ne( ch) ;

[0014] Step S22: Count the number of times ro that the first charging pile has battery overheat protection, the number of times ur that it has no battery overheat protection, and the critical power le at which battery overheat protection occurs (1) , the number of times ur without battery overheat protection (1) , and the critical power le at which battery overheat protection occurs (1) ;

[0015] Step S221: Take ne (1) as nel, and obtain the charging time te of the first charging pile for the 1st to the nelth charging operations (1) ~te (nel) ;

[0016] Step S222: Determine whether the first charging pile has battery overheat protection during the first charging operation;

[0017] Take te (1) as tel, and obtain the charging power pi of the tram from the 1st to the telth second during the first charging operation (1) ~pi (tel) ;

[0018] Step S223: According to pi (1) ~pi (tel) , determine whether the battery has overheat protection;

[0019] If it occurs, then ro (1) is incremented by 1; calculate the value of le (1，1) :

[0020] If it does not occur, then ur (1) is incremented by 1, and the value of le (1，1) is 0;

[0021] Step S224: Determine whether battery overheat protection occurs during the 2nd to the nel-th charging operations, and calculate the critical charge amounts le of the 2nd to the nel-th charging operations (1，2) ~le (1，nel) ;

[0022] Calculate le (1，1) ~le (1，nel) and calculate the sum ale of le, and calculate the critical charge amount le of the first charging pile (1) .

[0023] Furthermore, the step S2 further includes:

[0024] Step S23: Count the number of times ro that battery overheat protection occurs in the 2nd to the ch-th charging piles (2) ~ro (ch) , the number of times ur that battery overheat protection does not occur (2) ~ur (ch) , the critical charge amount le when battery overheat protection occurs (2) ~le (ch) , and calculate the probability P that battery overheat protection occurs in the charging pile (ro) , the probability P that battery overheat protection does not occur (ur) ;

[0025] Calculate the average value ale of le (2) ~le (ch) ; Extract the maximum value le (2) ~le (ch) in le, the minimum value le (max) , and calculate the quasi-charge amount Epr: (min)

[0026] Step S24: Construct the prediction equation A for the 1st to the ch-th charging stations (1) ~A (ch) ; Fit the equation A (1) ~A (ch) to obtain the prediction equation A;

[0027] Step S25: Analyze the changes of the output power, output voltage and output current with time during the charging process of the 1st to the ch-th charging stations, construct the prediction equation B for the charging stations, and enter step S3

[0028] Furthermore, the specific steps of the step S24 are as follows:

[0029] Step S241: Construct the prediction equation A (1) ; Take ur (1) as url, and obtain the charging time tl of the 1st to the url-th charging in the target data (1) ~tl (url) ​, battery power percentage ec (1) ~ec (url) , battery capacity ba (1) ~ba (url) , charging power pii (1) ~pii (url) ;

[0030] Step S242: Calculate the total charging amount re for the first charging (1) ; the total charging amount re for the url-th charging (url) ;

[0031] Construct matrix X and matrix Y;

[0032] Step S243: Let the charging time for the h-th charging be tl (h) , the charging power of the tram be pii (h) , the battery power percentage of the tram be ec (h) , the battery capacity be ba (h) , the total charging amount be re (h) ;

[0033] Define the relationship coefficient β of equation A (1) ~β (0) ~β (5) , and construct the initial equation of equation A (1) ;

[0034] Step S244: Construct the relationship coefficient matrix B; Denote the regularization parameter as λ, and calculate the residual matrix Zz;

[0035] Step S245: Define the sum of squared residuals RSS of matrix B, construct the judgment formula of RSS, and iterate the judgment formula until the value of RSS is the smallest to obtain matrix Bb;

[0036] Substitute the parameters in matrix Bb into the initial equation to obtain equation A (1) ;

[0037] Step S245: Construct the prediction equations A for the 2nd to the ch-th charging stations (2) ~A (ch) .

[0038] Furthermore, the specific steps of step S25 are as follows:

[0039] Step S251: Construct the voltage and current prediction equation B for the 1st charging station (1) ;

[0040] Take ur (1) as url, and obtain the charging times tl for the 1st to the url-th charging operations in the target data (1) ~tl (url) ;

[0041] Step S252: Take tl (1) as tll, and obtain the output power Po (1) ~Po (tll) , output voltage Uo (1) ~Uo (tll) , output current Io (1) ~Io(tll);

[0042] Calculate the autoregressive coefficient Pφ of the output power (1,1) and the moving average coefficient Pθ (1,1) ;

[0043] Step S253: Calculate the autoregressive coefficient Pφ of the output power during the 2nd to the url-th charging operation at the 1st charging station (1,2) ~Pθ (1,url) , moving average coefficient Pθ (1,2) ~Pθ (1,url) ;

[0044] Calculate the average value of Pφ (1,1) ~Pθ (1,url) as the autoregressive coefficient Pφ of the output power of the 1st charging station (1) ; Calculate the average value of Pθ (1,1) ~Pθ (1,url) as the moving average coefficient Pθ of the output power of the 1st charging station (1) .

[0045] Furthermore, the specific steps of the said Step S252 are as follows:

[0046] Step S2521: Calculate the average value aPo of Po (1) ~Po (tll) ;

[0047] Calculate the white noise ψ of the output power from the 1st to the tll-th second (1) ~ψ (tll) ; Calculate the variance va of ψ (1) ~ψ (tll) ;

[0048] Step S2522: Construct a function based on ψ (1) ~ψ (tll) and va, and logarithmize the function to obtain a logarithmized function;

[0049] Step S2523: Define the iterative relationship between Pφ (1,1) and Pθ (1,1) :

[0050] Let the deviation value at the k-th second be de (k), constructor S(Pφ (1,1) , Pθ (1,1) ), and calculate the partial derivatives of the autoregressive coefficients Ss(Pφ (1,1) ) and the partial derivatives of the moving average coefficients Ss(Pθ (1,1) );

[0051] Furthermore, the subsequent steps of step S2523 are as follows:

[0052] Step S2524: Denote the autoregressive coefficients after the m-th iteration as (Pφ (m) (1,1) ), the moving average coefficients as (Pθ (m) (1,1) ), the partial derivatives of the autoregressive coefficients as Ss (m) (Pφ (1,1) ), and the partial derivatives of the moving average coefficients as Ss (m) (Pθ (1,1) );

[0053] The autoregressive coefficients after the (m + 1)-th iteration are denoted as (Pφ (m+1) (1,1) ), the moving average coefficients as (Pθ (m+1) (1,1) ), and define the iterative relationship;

[0054] Step S2525: Take the deviation values de (1) ~de (tll) from the 1st to the tll-th second as white noise and substitute them back into the logarithmic function in reverse; perform iteration on Pφ (1,1) and Pθ (1,1) according to the iterative relationship until the logarithmic function converges to obtain the autoregressive coefficients Pφ (1,1) and the moving average coefficients Pθ (1,1) .

[0055] Furthermore, the specific steps of step S3 are as follows:

[0056] Step S31: Obtain the quasi-charge amount Epr, the probability P (ro) of battery overheat protection occurring, and the probability P (ur) of battery overheat protection not occurring;

[0057] Obtain the current battery charge percentage en, the battery capacity at, the charging power Pe, and the charging power Ppe when the battery overheats;

[0058] Obtain the actual output power nPP, the actual output voltage nUU, and the actual output current nII of the charging pile;

[0059] Step S32: Substitute en, at, and Pe into the estimation equation A to calculate the ideal charging time gt;

[0060] Substitute Epr and Pe into the estimation equation A to calculate the charging time ti (1) ; Substitute

[0061] en, at, Epr, and Ppe into the estimation equation A again to calculate the charging time ti (2) , and obtain the expected charging duration qt;

[0062] Step S33: According to the estimation equation B, calculate and extract the maximum output power P of the charging pile from the 1st to the qt-th second (max) , the maximum output voltage U (max) , and the maximum output current I (max) ;

[0063] Step S34: Denote the maximum rated power of the charging pile as Pw (max) , the maximum rated current as Uw (max) , and the maximum rated voltage as Iw (max) ; Judge the charging process of the charging pile.

[0064] Furthermore, judge the charging process of the charging pile as follows:

[0065] Let the real-time output voltage during the charging process of the charging station be Ut, and the real-time output current be It;

[0066] Judge whether it holds;

[0067] If it holds, the charging pile is charging normally;

[0068] If it does not hold, then judge whether it holds;

[0069] If it holds, the charging pile is abnormal;

[0070] If it does not hold, then analyze the real-time output power of the charging pile;

[0071] Step S35: Calculate the real-time output power Pt;

[0072] Judge whether Pt > Pw (max) holds;

[0073] If it holds, the charging pile is abnormal;

[0074] If it does not hold, then judge whether the change rates of P (max) , U (max) and I (max) are the same;

[0075] If they are the same, the charging pile is normal;

[0076] If they are different, the charging pile is abnormal.

[0077] An operation self-checking system for intelligent shared charging piles, the system comprising:

[0078] A data acquisition module: used to acquire the number of charging piles, acquire the maximum rated power, maximum rated current and maximum rated voltage of the charging piles, and obtain charging pile data;

[0079] A data analysis module: used to acquire the historical charging data of the charging piles; conduct a first mathematical modeling on the historical charging data, analyze the change in the charging time of the charging pile when the electric vehicle has battery overheat protection and when it does not have battery overheat protection during the charging process, and construct a prediction equation A; conduct a second mathematical modeling on the historical charging data, analyze the output voltage and charging current of the charging pile with the change of charging power and charging time, and construct a prediction equation B;

[0080] A fault monitoring module: used to acquire the charging request of the electric vehicle, detect whether the electric vehicle has battery overheat protection during the charging process, and combine the prediction equation A and the prediction equation B to estimate the maximum output voltage and maximum output current of the charging pile during charging; acquire the actual output voltage and actual output current of the charging pile, and compare them with the maximum output voltage and maximum output current to determine whether the charging process of the charging pile is normal; if it is normal, do not process; if it is not normal, mark the charging pile with a fault;

[0081] A continuous monitoring module: used to continuously monitor the charging process of the charging pile, summarize the charging piles with faults, and give feedback.

[0082] A storage medium for operation self-checking of intelligent shared charging piles, on which a computer program is stored, and when the computer program is executed by a processor, it runs the method for operation self-checking of intelligent shared charging piles described in any one of the above.

[0083] Compared with the prior art, the beneficial effects of the present invention are:

[0084] Real-time monitoring and fault diagnosis: The present invention can collect various electrical data of the charging pile during the charging process in real time, and use the technologies of data analysis and mathematical modeling analysis to deeply analyze the collected electrical data; by comparing with preset standard parameters and historical data, the system can quickly and accurately judge whether the charging pile has a fault, and the self-checking accuracy is high.

[0085] Improve charging safety: By analyzing historical charging data through data analysis and mathematical modeling, this invention analyzes the charging power and charging volume of different electric vehicles, and the changes in charging time, output voltage, and current of charging piles, to predict the charging process of different electric vehicles in advance, avoiding the occurrence of the phenomenon of "mismatch between the output power of the charging pile and the charging power of the electric vehicle", and ensuring the safety and reliability of the electric vehicle during the charging process.

[0086] Reduce operation and maintenance costs: This invention can automatically detect charging piles regularly, mark and summarize faulty charging piles; this processing method not only helps managers understand the operating status of charging piles in a timely manner, but also provides data support for the maintenance and upgrade of charging stations. Brief Description of the Drawings

[0087] By reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings, other features, objectives, and advantages of the present invention will become more apparent:

[0088] Figure 1 It is a schematic diagram of the method of the present invention;

[0089] Figure 2 It is a schematic diagram of the charging pile of the present invention;

[0090] Figure 3 It is a schematic diagram of the system of the present invention. Detailed Embodiments

[0091] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0092] Embodiment 1

[0093] Please refer to Figure 1 and Figure 2 , a method for self-checking the operation of an intelligent shared charging pile includes:

[0094] Step S1: Obtain the number of charging piles in the (target area), and obtain the maximum rated power, maximum rated current, and maximum rated voltage of the charging piles during the charging process to obtain charging pile data;

[0095] It should be noted that the "target area" in the present invention refers to: the municipal area where the operation self-check of the charging pile is carried out by applying the present invention (a method, system, and medium for self-checking the operation of an intelligent shared charging pile);

[0096] Step S2: Obtain the historical charging data of the charging pile; conduct a first mathematical modeling on the historical charging data to analyze the change in the charging time of the charging pile when the electric vehicle has battery overheat protection and when it does not have battery overheat protection during the charging process, and construct an estimated equation A for (charging time); conduct a second mathematical modeling on the historical charging data to analyze the output voltage and charging current of the charging pile changing with the charging power and charging time, and construct an estimated equation B for (voltage and current).

[0097] The specific content of step S2 is as follows:

[0098] Step S21: Obtain the number of charging piles in (the target area), denoted as ch;

[0099] Obtain the number of charging times of the 1st to the pi-th charging piles in (the target area) in the past month, denoted as ne (1) ~ne (ch) ;

[0100] (Obtain the charging time, the percentage of the battery power before charging, the battery capacity, and the charging power of each charging pile during the charging operation, as well as the real-time output power, output voltage, and output current of the charging pile during the charging process as the historical charging data)

[0101] Step S22: Count the number of times ro that the 1st charging pile has battery overheat protection during the charging operation (1) , the number of times ur without battery overheat protection (1) , and the critical power le when the battery overheat protection occurs (1) ; (The initial values of ro (1) , ur (1) and le (1) are all 0)

[0102] Step S221: Take ne (1) as nel, and obtain the charging time of the 1st to the nel-th charging operations of the 1st charging pile (in the past month), denoted as te (1) ~te (nel) ; (Unit: second)

[0103] Step S222: Determine whether the 1st charging pile has battery overheat protection during the 1st charging operation (in the past month);

[0104] Take te (1) as tel, and obtain the charging power of the electric vehicle from the 1st to the tel-th second (when the 1st charging pile conducts the 1st charging operation in the past month), denoted as pi (1) ~pi (tel) ;

[0105] Define relationship A-1:

[0106] wherein, pi (1) represents the charging power of the tram at the z-th second; the value range of z is: 2 to tel; ε represents the error value (the value of ε is 0.1; users or relevant technicians can adjust the value of ε according to actual needs);

[0107] Step S223: Denote the critical power of the first charging operation as le (1，1) ; (substitute pi (2) to pi (tel) into the relational expression A-1) to determine whether the relational expression A-1 holds;

[0108] If it holds, then the first charging operation (performed by the first charging pile in the past month) has a battery overheat protection, and the value of ro (1) is incremented by 1; calculate le (1，1) :

[0109] wherein, pi (V) represents the charging power of the tram at the V-th second; the value range of v is: 1 to z;

[0110] If it does not hold, then the first charging operation (performed by the first charging pile in the past month) does not have a battery overheat protection, and the value of ur (1) is incremented by 1, and the value of le (1，1) is 0;

[0111] Step S224: Repeat the same steps for determining whether the first charging operation has a battery overheat protection (i.e., Step S222 to Step S223) to determine whether the 2nd to the nel-th charging operations (performed by the first charging pile in the past month) have a battery overheat protection, and calculate the critical power le (1，2) to le (1，nel) ;

[0112] Calculate the sum ale of le (1，1) to le (1，nel) , and calculate the critical power le (1) of the first charging pile: le (1) = ale / ro (1) ;

[0113] Step S23: Repeat the statistical and calculation processes of ro (1) , ur (1) and le (1) to statistically count the number of times ro (2) to ro (ch) of battery overheat protection occurred when the 2nd to the ch-th charging piles performed charging operations, and the number of times ur (2)~ur (ch) The critical power le at which battery overheat protection occurs (2) ~le (ch) ;

[0114] Calculate ne (1) ~ne (ch) The sum ane, ro (1) ~ro (ch) The sum aro, ur (1) ~ur (ch) The sum aur;

[0115] Calculate the probability P that the battery overheat protection occurs when the charging pile is performing the charging operation (ro) , P (ro) =aro / ane; The probability P that the battery overheat protection does not occur (ur) , P (ur) =aur / ane

[0116] Calculate le (2) ~le (ch) The average value ale; Extract the maximum value le (2) ~le (ch) from among le (max) , the minimum value le (min) , calculate the quasi-charging power Epr at which the battery overheat protection occurs for the charging pile:

[0117] Among them, le (s) represents the critical power at which the battery overheat protection occurs for the s-th charging pile; the value range of s is: 1 to ch;

[0118] Step S24: Construct the estimation equation A for the charging time of the 1st to ch-th charging stations (1) ~A (ch) ; (Using MATLAB software) Fit the equation A (1) ~A (ch) to obtain the estimation equation A for the charging time;

[0119] Step S241: Construct the estimation equation A for the charging time of the 1st charging station (1) ;

[0120] Take ur (1) as url, obtain the historical charging data of the 1st charging station without battery overheat protection as the target data;

[0121] Record the charging times of the 1st to url-th charging operations in the target data as tl (1) ~tl (url) ;

[0122] The percentage of battery power (before tram charging), denoted as ec (1) ~ec (url) ; The battery capacity, denoted as ba (1) ~ba (url) ; The charging power, denoted as pii (1) ~pii (url) ;

[0123] Step S242: Calculate the total charging amount re of the first charging operation (1) , re (1) = (1 - ec (1) ) × ba (1) ;

[0124] The total charging amount re of the second charging operation (2) , re (2) = (1 - ec (2) ) × ba (2) ;

[0125] And so on, the total charging amount re of the url-th charging operation (url) , re (url) = (1 - ec (url) ) × ba (url) ;

[0126] Using the charging power (i.e., pii (1) ~pii (url) ) and the total charging amount (i.e., re (1) ~re (url) ) as independent variables (i.e., 2 independent variables), and the charging time as the dependent variable (i.e., tl (1) ~tl (url) ), construct the independent variable matrix X and the dependent variable matrix Y;

[0127] Matrix X:

[0128]

[0129] Matrix Y:

[0130]

[0131] Step S243: Let the charging time of the h-th charging operation be tl (h) (dependent variable), the charging power of the tram be pii (h) , the percentage of battery power before tram charging be ec (h) , the battery capacity be ba (h) , and the total charging amount be re (h) ;

[0132] Denote the correlation coefficient of equation A (1) as β(0) ~β (5) ; β (0) ~β (5) The initial value of is 1;

[0133] Construct formula A-2-1 as the initial equation of equation A (1) :

[0134]

[0135] Step S244: Construct a (6×1) relationship coefficient matrix, denoted as matrix B: (That is )

[0136] Denote the regularization parameter as λ; (the value of λ is 0.01; users or relevant technical personnel can adjust the value of λ according to actual needs) Define the relational expression A-2-2 for iterating matrix B:

[0137] where Zz represents the residual matrix, * represents matrix multiplication, T represents the transpose of the matrix, and -1 represents the inverse of the matrix; I (6) represents a (6×6) all-ones matrix;

[0138] Step S245: Define the judgment formula A-2-3 for matrix B:

[0139] RSS = (Zz - X * B) T * (Zz - X * B); where RSS represents the residual sum of squares of matrix B;

[0140] (According to judgment formula A-2-3 and relational expression A-2-2) Iterate matrix B until the value of RSS is minimized to obtain matrix Bb;

[0141] Substitute the parameters in matrix Bb into formula A-2-1 to obtain equation A (1) ;

[0142] Step S245: Repeat the construction process of equation A (1) to construct the (charging time) prediction equations A (2) ~A (ch) ;

[0143] Step S25: Analyze the changes in the output power, output voltage, and output current of the (charging pile) over time during the charging process of the 1st to chth charging stations, and construct the (voltage and current) prediction equation B of the charging station;

[0144] Step S251: Construct the voltage and current prediction equation B of the 1st charging station (1) ;

[0145] Let ur(1) As the URL, obtain the historical charging data of the first charging station without overheating protection of the battery as the target data;

[0146] Obtain the charging time tl of the first to the URL-th charging operations in the target data (1) ~tl (url) ;

[0147] Step S252: Take tl (1) as tll, and obtain the output power Po (1) ~Po (tll) of the first to the tll-th seconds in the first charging operation of (the target data) (charging station), the output voltage Uo (1) ~Uo (tll) and the output current Io (1) ~Io (tll) ;

[0148] Calculate the autoregressive coefficient Pφ (1,1) and the moving average coefficient Pθ (1,1) of the output power during the first charging operation of the charging station;

[0149] Step S2521: Calculate the average value aPo of Po (1) ~Po (tll) ;

[0150] Calculate the white noise ψ of the output power at the first second (1) , ψ (1) = Po (1) − aPo;

[0151] The white noise ψ of the output power at the second second (2) , ψ (2) = Po (2) − aPo; Po (2) represents the output power of the charging station at the second second during the first charging operation;

[0152] And so on, the white noise ψ of the output power at the tll-th second (tll) , ψ (tll) = Po (tll) − aPo;

[0153] Calculate the variance of ψ (1) ~ψ (tll) and denote it as va;

[0154] Step S2522: Construct the likelihood function L(φ,θ,va) of the white noise as function A-3-1:

[0155] where ψ (k)White noise representing the output power of the charging station at the k-th second during the first charging operation, where the value range of k is: 1 to tll;

[0156] Logarithmize the function A-3-1 to obtain the function A-3-2:

[0157]

[0158] Step S2523: Define Pφ (1,1) and Pθ (1,1) 's iterative relationship:

[0159] Let the deviation value at the k-th second be de (k) :

[0160]

[0161] Define Pφ (1,1) and Pθ (1,1) 's function S(Pφ (1,1) , Pθ (1,1) ):

[0162]

[0163] According to the function S(Pφ (1,1) , Pθ (1,1) ), calculate the autoregressive coefficient (i.e., the partial derivative of the function S(Pφ (1,1) , Pθ (1,1) ) with respect to Pφ (1,1) ) as Ss(Pφ (1,1) );

[0164] Calculate the moving average coefficient (i.e., the partial derivative of the function S(Pφ (1,1) , Pθ (1,1) ) with respect to Pθ (1,1) ) as Ss(Pθ (1,1) );

[0165] Step S2524: Let the initial values of the autoregressive coefficient Pφ (1,1) and the moving average coefficient Pθ (1,1) be 1; Denote the autoregressive coefficient after the m-th iteration as (Pφ (m) (1,1) ), the moving average coefficient as (Pθ (m) (1,1) ), the partial derivative of the autoregressive coefficient as Ss (m) (Pφ (1,1) ), and the partial derivative of the moving average coefficient as Ss (m) (Pθ (1,1) );

[0166] Denote the autoregressive coefficient after the (m + 1)-th iteration as (Pφ(m+1) (1,1) ), and the moving average coefficient is denoted as (Pθ (m+1) (1,1) );

[0167] The defined iterative relation formula A-3-3:

[0168] where η represents the learning rate; the value of η is 0.01; users or relevant technicians can adjust the value of η according to actual needs

[0169] Step S2525: Take the deviation values de (1) ~de (tll) from the 1st to the tllth second as white noise and substitute them backward into function A-3-2; perform iteration on Pφ (1,1) and Pθ (1,1) according to relation formula A-3-3 (using the Newton-Raphson method) until function A-3-2 converges to obtain the autoregressive coefficient Pφ (1,1) and the moving average coefficient Pθ (1,1) ;

[0170] Step S253: Repeat the same steps of calculating Pφ (1,1) and Pθ (1,1) to calculate the autoregressive coefficients Pφ (1,2) ~Pθ (1,url) of the output power of the 1st charging station during the 2nd to the urlth charging operations, and the moving average coefficients Pθ (1,2) ~Pθ (1,url) ;

[0171] Calculate the average value of Pφ (1,1) ~Pθ (1,url) as the autoregressive coefficient Pφ (1) of the output power of the 1st charging station;

[0172] Calculate the average value of Pθ (1,1) ~Pθ (1,url) as the moving average coefficient Pθ (1) of the output power of the 1st charging station;

[0173] Step S254: Repeat the same steps of calculating Pφ (1) and Pφ (1) to calculate the autoregressive coefficients Uφ (1) and Iφ (1) of the output voltage and output current of the 1st charging station, and the moving average coefficients Uθ (1) and Iθ (1) ;

[0174] Let the time be t, and let the real-time output power of the charging station at the tth second be Pn(t) The real-time output voltage is Un (t) The real-time output current is In (t) ; The real-time output power at (t - 1) seconds is Pn (t-1) The real-time output voltage is Un (t-1) The real-time output current is In (t-1) ;

[0175] The expected output power at the (t + 1)-th second is Pq (t+1) The expected output voltage is Uq (t+1) The expected output current is Iq (t+1) ;

[0176] Construct equation BP (1) :

[0177] where dP (t) represents the deviation of the output power of the charging station at t seconds, and Pq (t) represents the expected output power of the charging pile at the t-th second;

[0178] Construct equation BU (1) :

[0179] where dU (t) represents the deviation of the output voltage of the charging station at t seconds, and Uq (t) represents the expected output voltage of the charging pile at the t-th second;

[0180] Construct equation BI (1) :

[0181] where dI (t) represents the deviation of the output current of the charging station at t seconds, and Iq (t) represents the expected output current of the charging pile at the t-th second;

[0182] Take equation BP (1) , equation BU (1) and equation BI (1) , as equation B (1) ;

[0183] Step S255: Repeat the same steps of constructing equation B (1) to construct the voltage and current prediction equations B (2) ~B (ch) for the 2nd to the ch-th charging stations; (Use MATLAB software) Fit equations B (1) ~B (ch) to obtain the (voltage and current) prediction equation B;

[0184] Step S3: Obtain the charging request of the electric vehicle (connected to the charging pile), detect whether battery overheat protection occurs during the charging process of the electric vehicle, and estimate the maximum output voltage and maximum output current of the charging pile during charging by combining the (charging time) estimation equation A and the (voltage and current) estimation equation B; obtain the actual output voltage and actual output current of the charging pile, and compare them with the maximum output voltage and maximum output current to determine whether the charging process of the charging pile is normal; if it is normal, do not process; if it is not normal, mark the faulty charging pile (and disconnect the charging connection between the charging pile and the electric vehicle);

[0185] The specific steps of Step S3 are as follows:

[0186] Step S31: Obtain the quasi-charging amount Epr when the charging pile has battery overheat protection, the probability P of battery overheat protection (ro) and the probability P of no battery overheat protection (ur) ;

[0187] Obtain the charging request of the electric vehicle (connected to the charging pile);

[0188] The charging request includes: the current battery power percentage en of the electric vehicle, the battery capacity at, the charging power Pe, and the charging power Ppe when the battery has overheat protection;

[0189] Obtain the actual output power nPP, the actual output voltage nUU, and the actual output current nII of the charging pile (during the charging process);

[0190] Step S32: Denote the expected charging duration of the electric vehicle as qt;

[0191] Substitute en, at, and Pe into the (charging time) estimation equation A to calculate the ideal charging time gt of the electric vehicle;

[0192] Judge whether [(1 - en) × at] ≥ Epr holds to determine the value of qt;

[0193] If it does not hold, the value of qt is gt;

[0194] If it holds, substitute Epr and Pe (once) into the (charging time) estimation equation A to calculate the (normal) charging time ti of the electric vehicle (1) ; substitute [((1 - en) × at) - Epr] and Ppe (twice) into the (charging time) estimation equation A to calculate the (charging time of the battery overheat protection) ti of the electric vehicle (2) ;

[0195] Calculate the value of qt:

[0196] Among them, "[((1 - en) × at) - Epr]" represents the additional charging amount when the tram exceeds the "quasi-charging amount Epr".

[0197] Step S33: Take nPP, nUU, and nII as the initial values of the real-time output power, real-time output voltage, and real-time output current of the charging station in the (voltage-current) prediction equation B, and calculate and extract the maximum output power P of the charging pile from the 1st to the qt-th second (max) , the maximum output voltage U (max) , and the maximum output current I (max) ;

[0198] Step S34: Denote the maximum rated power of the charging pile as Pw (max) , the maximum rated current as Uw (max) , and the maximum rated voltage as Iw (max) ;

[0199] Assume that the real-time output voltage of the charging station during charging (at a certain second) is Ut, and the real-time output current is It;

[0200] Judge whether Ut ≤ U (max) and It ≤ I (max) hold simultaneously;

[0201] If both hold, the charging of the charging pile is normal;

[0202] If they do not hold simultaneously, then judge whether [(Ut > Uw (max) ) ∪ (It > Iw (max) )] (that is, Ut > Uw (max) or It > Iw (max) , and one of them holds) holds;

[0203] If it holds, (immediately cut off the power and mark the charging pile) the charging of the charging pile is abnormal;

[0204] If it does not hold, then analyze the real-time output power of the charging pile;

[0205] Step S35: Calculate the real-time output power Pt of the charging pile, Pt = Ut × It;

[0206] Judge whether Pt > Pw (max) holds;

[0207] If it holds, (immediately cut off the power and mark the charging pile) the charging of the charging pile is abnormal;

[0208] If it does not hold, then define the relational expression B:

[0209]

[0210] Judge whether the relational expression B holds;

[0211] If it holds, the charging pile charges normally;

[0212] If it does not hold, then (immediately cut off the power and mark the charging pile) the charging pile has abnormal charging;

[0213] Step S4: Continuously monitor the charging process of the charging pile, summarize the charging piles with faults, and give feedback.

[0214] Embodiment 2

[0215] Please refer to Figure 3 , an operation self-checking system for intelligent shared charging piles includes:

[0216] Data acquisition module: used to acquire the number of charging piles in (the target area), acquire the maximum rated power, maximum rated current, and maximum rated voltage of the charging pile during the charging process, and obtain charging pile data;

[0217] Data analysis module: used to acquire the historical charging data of the charging pile; perform a first mathematical modeling on the historical charging data, analyze the change in the charging time of the charging pile when the electric vehicle has battery overheat protection and when it does not have battery overheat protection during the charging process, and construct an (charging time) prediction equation A; perform a second mathematical modeling on the historical charging data, analyze the output voltage and charging current of the charging pile with the change of charging power and charging time, and construct a (voltage and current) prediction equation B;

[0218] Fault monitoring module: used to acquire the charging request of the electric vehicle connected to the charging pile, detect whether the electric vehicle has battery overheat protection during the charging process, and combine the (charging time) prediction equation A and the (voltage and current) prediction equation B to estimate the maximum output voltage and maximum output current of the charging pile during charging; acquire the actual output voltage and actual output current of the charging pile, and compare them with the maximum output voltage and maximum output current to determine whether the charging process of the charging pile is normal; if it is normal, do not process; if it is not normal, mark the faulty charging pile (and disconnect the charging connection between the charging pile and the electric vehicle);

[0219] Continuous monitoring module: used to continuously monitor the charging process of the charging pile, summarize the charging piles with faults, and give feedback.

[0220] Embodiment 3

[0221] A storage medium for operation self-checking of intelligent shared charging piles, on which a computer program is stored. When the computer program is executed by a processor, it runs the steps in any one of the above-mentioned operation self-checking methods for intelligent shared charging piles. Through the above technical solutions, when the computer program is executed by the processor, it executes the methods in any optional implementation manner of the above embodiments to achieve the following functions:

[0222] Obtain, extract and process the historical charging data of charging piles, analyze the influence of the charging power and charging electricity of different electric vehicles on the charging time, as well as the changes of the output power, output voltage and output current of the charging station with the charging duration, and calculate the maximum output power, maximum output voltage and maximum output current of the electric vehicle during the process in combination with the actual charging power and charging electricity of the electric vehicle, and then combine the charging pile data to conduct self-inspection on the charging process of the charging pile;

[0223] The above formulas are all calculated by taking the numerical values after dimensionless, and the formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. For example, there are weight coefficients and proportionality coefficients, and the sizes of their settings are for quantifying each parameter to obtain a specific numerical value for subsequent comparison. Regarding the sizes of the weight coefficients and proportionality coefficients, as long as they do not affect the proportional relationship between the parameters and the quantified numerical values, it is fine.

[0224] Finally, it should be noted that: the above-mentioned embodiments are only specific implementation manners of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An operation self-checking method for an intelligent shared charging pile, characterized in that, The method includes: Step S1: Obtain the number of charging piles, the maximum rated power, the maximum rated current, and the maximum rated voltage of the charging piles to obtain charging pile data; Step S2: Obtain the historical charging data of the charging piles; perform a first mathematical modeling on the historical charging data to analyze the change in the charging time of the charging piles when the electric vehicle has battery overheat protection and when it does not have battery overheat protection during the charging process, and construct prediction equation A; perform a second mathematical modeling on the historical charging data to analyze the change in the output voltage and charging current of the charging piles with the charging power and charging time, and construct prediction equation B; Step S3: Obtain the charging request of the electric vehicle, detect whether the electric vehicle has battery overheat protection during the charging process, and combine prediction equation A and prediction equation B to estimate the maximum output voltage and maximum output current of the charging pile during charging; obtain the actual output voltage and actual output current of the charging pile, and compare them with the maximum output voltage and maximum output current to determine whether the charging process of the charging pile is normal; if it is normal, do not process; if it is not normal, mark the faulty charging pile; Step S4: Continuously monitor the charging process of the charging pile, summarize the faulty charging piles, and give feedback.

2. The operation self-checking method for an intelligent shared charging pile according to claim 1, wherein The specific steps of step S2 are as follows: Step S21: Obtain the number of charging piles ch; obtain the number of charging times ne of all charging piles (1) ~ne( ch) ; Step S22: Count the number of times ro that the first charging pile has experienced battery overheat protection (1) , the number of times ur that the battery overheat protection has not occurred (1) , and the critical power le at which the battery overheat protection occurs (1) ; Step S221: Take ne (1) As nel, obtain the charging time te for the first charging pile to perform the first to nelth charging operations (1) ~te (nel) ; Step S222: Determine whether the first charging pile has battery overheat protection during the first charging operation; Take te (1) As tel, obtain the charging power pi of the tram from the 1st to the telth second during the first charging operation (1) ~pi (tel) ; Step S223: According to pi (1) ~ pi (tel) , determine whether the battery has overheat protection; If it appears, then ro (1) Increment by 1; calculate le (1，1) Value of: If not present, then ur (1) is incremented by 1, le (1，1) has a value of 0; Step S224: Determine whether battery overheat protection occurs in the 2nd to the nel-th charging operations, and calculate the critical battery levels le (1，2) ~ le (1，nel) ; Calculate le (1，1) ~le (1，nel) The sum ale, calculate the critical power le of the first charging pile (1) .

3. A self-check method for the operation of an intelligent shared charging pile according to claim 2, characterized in that, Step S2 further includes: Step S23: Count the number of times ro that the 2nd to the chth charging piles have battery overheat protection (2) ~ro (ch) , the number of times ur that there is no battery overheat protection (2) ~ur (ch) , the critical power le at which the battery overheat protection occurs (2) ~le (ch) , and calculate the probability P that the charging pile has battery overheat protection (ro) , the probability P that there is no battery overheat protection (ur) ; Calculate le (2) ~le (ch) to obtain the average value ale; extract the maximum value le (2) ~le (ch) and the minimum value le (max) in it, and calculate the quasi-charge amount Epr: (min) ​ Step S24: Construct the estimation equations A for the 1st to the ch-th charging stations (1) ~A (ch) ; For the equations A (1) ~A (ch) perform fitting to obtain the estimation equations A; Step S25: Analyze the change in output power, output voltage, and output current over time during the charging process of the first to the chth charging stations, construct the prediction equation B for the charging stations, and proceed to step S3.

4. A self-checking method for the operation of an intelligent shared charging pile according to claim 3, characterized in that, The specific steps of step S24 are as follows: Step S241: Construct the prediction equation A (1) ; Take ur (1) as the url, and obtain the charging times tl (1) ~tl (url) for the 1st to the url-th charging in the target data, the battery charge percentages ec (1) ~ec (url) , the battery capacities ba (1) ~ba (url) , and the charging powers pii (1) ~pii (url) ; Step S242: Calculate the total charge amount re for the first charge (1) ; the total charge amount re for the url-th charge (url) ; Construct matrix X and matrix Y; Step S243: Set the charging time of the h-th charge as tl (h) , the charging power of the tram is pii (h) , the battery charge percentage of the tram is ec (h) , the battery capacity is ba (h) , the total charge amount is re (h) ; Define equation A (1) The correlation coefficient β (0) ~β (5) , construct the initial equation of equation A (1) ; Step S244: Construct the relationship coefficient matrix B; denote the regularization parameter as λ, and calculate the residual matrix Zz; Step S245: Define the residual sum of squares RSS of matrix B, construct the judgment formula of RSS, and perform iteration on the judgment formula until the value of RSS is the smallest to obtain matrix Bb; Substitute the parameters in matrix Bb into the initial equation to obtain equation A (1) ; Step S245: Construct the estimation equations A for the 2nd to the ch-th charging stations (2) ~A (ch) .

5. The operation self-check method for an intelligent shared charging pile according to claim 3, characterized in that The specific steps of step S25 are as follows: Step S251: Construct the voltage and current prediction equation B for the first charging station (1) ; Take ur (1) as the url, and obtain the charging time tl of the 1st to the url-th charging operations in the target data (1) ~tl (url) ; Step S252: Set tl (1) as tll, and obtain the output power Po from the 1st second to the tllth second during the first charge (1) ~Po (tll) , the output voltage Uo (1) ~Uo (tll) , and the output current Io (1) ~Io( t ll); Autoregressive coefficient Pφ for calculating the output power (1,1) and moving average coefficient Pθ (1,1) ; Step S253: Calculate the autoregressive coefficients \(P_{\varphi}\) to \(P_{\theta}\) of the output power of the first charging station during the 2nd to the \(url\)th charging operations (1,2) ~ \(P_{\theta}\) (1,url) , and the moving average coefficients \(P_{\theta}\) (1,2) ~ \(P_{\theta}\) (1,url) ; Calculate Pφ (1,1) ~Pθ (1,url) 's average value as the autoregressive coefficient Pφ of the output power of the first charging station (1) ; Calculate Pθ (1,1) ~Pθ (1,url) 's average value as the moving average coefficient Pθ of the output power of the first charging station (1) .

6. A self - checking method for the operation of an intelligent shared charging pile according to claim 5, characterized in that, The specific steps of step S252 are as follows: Step S2521: Calculate Po (1) ~Po (tll) The average value aPo of; Calculate the white noise ψ from the 1st to the tll-th second of the output power (1) ~ψ (tll) ; Calculate ψ (1) ~ψ (tll) variance va; Step S2522: According to ψ (1) ~ψ (tll) and the va constructor, logarithmize the function to obtain the logarithmized function; Step S2523: Define the iterative relationship of Pφ (1,1) and Pθ (1,1) : Let the deviation value at the k-th second be de (k) , construct the function S(Pφ (1,1) , Pθ (1,1) ), and calculate the partial derivatives Ss(Pφ (1,1) ) of the autoregressive coefficient and the partial derivatives Ss(Pθ (1,1) ).

7. A self-check method for the operation of an intelligent shared charging pile according to claim 6, characterized in that, The subsequent steps of step S2523 are as follows: Step S2524: Denote the autoregressive coefficients after the m-th iteration as (Pφ (m) (1,1) ), the moving average coefficients as (Pθ (m) (1,1) ), the partial derivative of the autoregressive coefficients as Ss (m) (Pφ (1,1) ), and the partial derivative of the moving average coefficients as Ss (m) (Pθ (1,1) ); The autoregressive coefficients after the (m + 1)-th iteration are denoted as (Pφ (m+1) (1,1) ), and the moving average coefficients are denoted as (Pθ (m+1) (1,1) ). Define the iterative relationship; Step S2525: Use the deviation values de from the 1st to the tll-th second (1) ~de (tll) as white noise and substitute them backward into the logarithmic function; perform iteration on Pφ (1,1) and Pθ (1,1) according to the iterative relationship until the logarithmic function converges, and obtain the autoregressive coefficient Pφ (1,1) and the moving average coefficient Pθ (1,1) .

8. A self-checking method for the operation of an intelligent shared charging pile according to claim 3, characterized in that, The specific steps of step S3 are as follows: Step S31: Obtain the quasi-charging amount Epr, the probability P of the occurrence of battery overheat protection (ro) and the probability P of the non-occurrence of battery overheat protection (ur) ; Obtain the current battery power percentage en, the battery capacity at, the charging power Pe, and the charging power Ppe when the battery has overheat protection of the electric vehicle; Obtain the actual output power nPP, the actual output voltage nUU, and the actual output current nII of the charging pile; Step S32: Substitute en, at, and Pe into prediction equation A to calculate the ideal charging time gt; Substitute Epr and Pe into the estimation equation A to calculate the charging time ti (1) ; Substitute Substitute en, at, Epr, and Ppe into the secondary substitution prediction equation A to calculate the charging time ti (2) , and obtain the expected charging duration qt; Step S33: Calculate and extract the maximum output power P of the charging pile in the 1st to qt-th seconds according to the estimation equation B (max) , the maximum output voltage U (max) , the maximum output current I (max) ; Step S34: Denote the maximum rated power of the charging pile as Pw (max) , denote the maximum rated current as Uw (max) , denote the maximum rated voltage as Iw (max) ; Judge the charging process of the charging pile.

9. The operation self-checking method for an intelligent shared charging pile according to claim 8, characterized in that, Judge the charging process of the charging pile as follows: Assume that the real-time output voltage during the charging process of the charging station is Ut and the real-time output current is It; Determine whether it holds; If it holds, the charging of the charging pile is normal; If it does not hold, then judge whether it holds; If it holds, the charging pile is abnormal; If it does not hold, analyze the real-time output power of the charging pile; Step S35: Calculate the real-time output power Pt; Determine whether Pt > Pw (max) holds; If it holds, the charging pile is abnormal; If not, then determine P (max) , U (max) and I (max) to see if their rates of change are the same; If they are the same, the charging pile is normal; If they are different, the charging pile is abnormal.

10. An operation self-checking system for an intelligent shared charging pile, applicable to an operation self-checking method for an intelligent shared charging pile according to any one of claims 1-9, characterized in that, The system includes: Data acquisition module: used to obtain the number of charging piles, obtain the maximum rated power, maximum rated current, and maximum rated voltage of the charging piles, and obtain charging pile data; Data analysis module: used to obtain the historical charging data of the charging piles; conduct a first mathematical modeling on the historical charging data, analyze the change in the charging time of the charging piles when the electric vehicle has battery overheat protection and when it does not have battery overheat protection during the charging process, and construct prediction equation A; conduct a second mathematical modeling on the historical charging data, analyze the output voltage and charging current of the charging piles with the change of charging power and charging time, and construct prediction equation B; Fault monitoring module: used to obtain the charging request of the electric vehicle, detect whether the electric vehicle has battery overheat protection during the charging process, and combine prediction equation A and prediction equation B to estimate the maximum output voltage and maximum output current of the charging pile during charging; obtain the actual output voltage and actual output current of the charging pile, and compare them with the maximum output voltage and maximum output current to determine whether the charging process of the charging pile is normal; if it is normal, do not process; if it is not normal, mark the charging pile with a fault; Continuous monitoring module: used to continuously monitor the charging process of the charging piles, summarize the charging piles with faults, and give feedback.

11. A storage medium for self-checking the operation of an intelligent shared charging pile, on which a computer program is stored, characterized in that, When the computer program is executed by a processor, it runs the steps in the method according to any one of claims 1-9.

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