Large-scale electric vehicle charging pile overhaul and maintenance optimization method and system

Abstract

The invention provides a large-scale electric vehicle charging pile overhaul and maintenance optimization method and system. The method comprises the following steps: constructing a charging pile operation health state evaluation index system; obtaining an index value and performing objective index weighting by adopting a CRITIC method to obtain an operation health state value; the charging stations needing to be overhauled and maintained and the maintenance sequence of the charging piles of the charging stations are determined, and the maintenance duration of the charging piles is optimized with the purpose of minimizing the sum of the maintenance loss value and the maintenance resource consumption cost of the charging piles of the charging stations needing to be overhauled and maintained; after the current charging station is overhauled and maintained, the operation health states of the charging piles of the remaining charging stations are evaluated in real time, and the maintenance duration of the charging pile of the next charging station is optimized based on the operation health states; the maintenance time of the charging facility, the maintenance loss value cost of the charging pile and the maintenance resource consumption cost can be remarkably reduced, and the overall operation and maintenance benefits of the charging facility are improved while the reliability of the charging pile is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of operation and maintenance technology for electric vehicle charging piles, and specifically to a method and system for optimizing the inspection and maintenance of large-scale electric vehicle charging piles. Background Technology

[0002] Due to their complex structure, high operating power, and long-term outdoor location, charging piles are susceptible to numerous factors that can cause malfunctions, resulting in a high failure rate. When a charging pile malfunctions or is damaged, it cannot provide service to charging users. This not only causes economic losses for charging operators but also affects the service experience for users and may even lead to accidents such as fires. Therefore, the subsequent operation, maintenance, and repair of charging piles and related strategies have gradually become a focus of attention for charging operation companies.

[0003] Currently, the operation and maintenance (O&M) of charging piles in my country is still in its early stages of development. Existing research mainly focuses on online monitoring and O&M operation and maintenance methods for charging piles within stations. Charging pile O&M work is divided into two parts: emergency repair and inspection. Emergency repair refers to the restoration of normal operation of the equipment by maintenance personnel after a charging pile malfunctions. Inspection refers to regular checks and preventative maintenance of charging piles when no malfunctions occur, to ensure their normal operation and extend their service life. Traditional inspection methods mainly rely on regular manual inspections. However, with the increasing number of charging piles and the continuous improvement of charging pile technology, this method has many drawbacks: inspection personnel need to routinely conduct the same level of inspection and maintenance on every charging pile. This indiscriminate inspection method not only incurs significant manpower and material costs but also makes it difficult to maintain charging piles in poor condition in a timely manner. Often, emergency repairs can only be carried out after a malfunction occurs, affecting the user experience and causing economic losses to charging operation companies. Summary of the Invention

[0004] In view of this, the problem to be solved by the present invention is to provide a method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles. This method can significantly reduce maintenance time, charging pile maintenance loss value cost and maintenance resource consumption cost, and improve the overall operation and maintenance efficiency while ensuring the reliability of charging piles.

[0005] This invention solves the above-mentioned technical problems through the following technical means: This invention provides a method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles, including the following steps:

[0006] Conduct an operational health status assessment of the charging piles at the charging station and construct an indicator system for assessing the operational health status of the charging piles.

[0007] Obtain indicator values ​​and use the CRITIC method to objectively assign weights to the indicators to obtain operational health status values;

[0008] Based on the operational health status value, the charging stations that need maintenance and the maintenance sequence of the charging piles at those stations are determined. Based on the time sequence of the arrival rate of charging vehicles, the maintenance time of the charging piles is optimized with the goal of minimizing the sum of the maintenance loss value and the maintenance resource consumption cost of the charging piles at the charging stations that need maintenance.

[0009] After the maintenance of the current charging station is completed, the operational health status of the charging piles in the remaining charging stations is assessed in real time, and the maintenance time of the charging piles in the next charging station is optimized based on the operational health status.

[0010] Repeat the above steps to optimize the maintenance time of charging piles at all charging stations.

[0011] Furthermore, the constructed charging pile operation health status assessment index system includes a target layer, a criterion layer, and an index layer; the target layer is the charging pile operation health status value; the criterion layer includes electrical and control status, communication status, and safety performance status; the index layer of electrical and control status includes voltage error rate, current error rate, contact current, inrush current, grounding resistance, insulation resistance, short circuit protection, temperature rise, and emergency stop button indicators; the index layer of communication status includes electronic lock anti-counterfeiting module, communication baud rate, and external CAN indicators; and the safety performance status includes access control, fire protection, and charging failure rate indicators.

[0012] Furthermore, it also includes identifying the charging station with the lowest average health status value of the charging piles as the charging station that needs maintenance, sorting the health status values ​​of the charging piles in the charging station that needs maintenance in order of magnitude, with the smaller the health status value, the higher the maintenance order, and when the health status value is greater than the preset health value of the charging pile, maintenance is not performed.

[0013] Furthermore, the objective of minimizing the sum of the maintenance loss value and maintenance resource consumption cost of the charging piles requiring repair and maintenance at the charging station also includes the following: the objective function is:

[0014]

[0015] Where c1 and c2 are the weight coefficients of the two sub-objectives: maintenance loss value and maintenance resource consumption cost. These weight coefficients are normalized according to the importance of each sub-objective; f maint,k M represents the maintenance resource consumption cost for charging pile k at the charging station that requires inspection and maintenance. k Let t be the unit time maintenance resource consumption cost of charging pile k. k The maintenance time for charging pile k.

[0016] Furthermore, the maintenance loss value of the charging pile is:

[0017]

[0018] Among them, f loss,k Let t be the maintenance loss value of charging pile k, FL() be the floor function, and t be the value of the maintenance loss value of charging pile k. k t represents the maintenance time of charging pile k. e λ(H) is the duration of a set maintenance period. k H k The following are the failure rate and operational health status values ​​of charging pile k, in order. The time cost incurred due to the maintenance of charging pile k, l k b1 and b2 are the coefficients of the exponential model relating the failure rate and health status of charging piles. The failure rate and health status data of charging piles for more than two years are collected, and the values ​​of these coefficients are obtained by least squares fitting method. c3 is the economic cost coefficient per unit of lost time for charging users, in yuan / minute. Its value is the average charging cost per minute for charging users. For l k The difference in waiting time per unit vehicle between charging stations with and without charging pile maintenance, i.e., the loss of waiting time per unit vehicle caused by charging pile maintenance, expressed in minutes per vehicle. The time period for the maintenance of charging pile k k The vehicle arrival rate is expressed in vehicles per minute.

[0019] Furthermore, time-varying M is adopted. t / M t The / S / K queuing model yields the waiting time per unit vehicle.

[0020] in They are respectively l k Waiting time for vehicles at charging stations with S and S-1 charging piles, with and without charging pile maintenance, T (l) , The figures, in order, are the unit vehicle waiting time, average number of people in the queue, and effective arrival rate for each time period.

[0021] The average number of people in the queue is:

[0022] Where, λ l μ l ρ l S l These are, in order, the arrival rate, service rate, traffic intensity, and number of available charging stations for the time period, where K is the maximum capacity of the queuing system. The system idle probability is a time period / (time period).

[0023] The system idle probability for the time period / is

[0024] Where p is an intermediate variable, p = 0, 1, 2...S l -1;

[0025] Effective arrival rate

[0026] in The blocking probability is for a given time period.

[0027] Furthermore, it also includes assessing the operational health status of the remaining charging stations' charging piles after completing the identified charging station charging pile maintenance, determining the next charging station to be maintained and the maintenance sequence of the charging piles at that station, deciding on the optimal maintenance duration, and then carrying out the maintenance of the next charging station's charging piles according to the sequence.

[0028] The present invention also provides a large-scale electric vehicle charging pile inspection, maintenance and optimization system, comprising: at least one processor, at least one memory and a communication interface; wherein the processor, memory and communication interface communicate with each other; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute a large-scale electric vehicle charging pile inspection, maintenance and optimization method.

[0029] As can be seen from the above technical solution, the beneficial effects of the present invention are as follows: The present invention provides a method for optimizing the maintenance of large-scale electric vehicle charging piles, including the following steps: assessing the operational health status of charging piles in charging stations and constructing an operational health status assessment index system for charging piles; obtaining index values ​​and objectively weighting the indicators using the CRITIC method to obtain operational health status values; determining the charging stations requiring maintenance and the maintenance sequence of charging piles in those charging stations based on the operational health status values; optimizing the maintenance time of charging piles based on the time sequence of charging vehicle arrival rates, with the goal of minimizing the sum of maintenance loss value and maintenance resource consumption cost of charging piles in charging stations requiring maintenance; after the maintenance of the current charging station is completed, assessing the operational health status of the remaining charging piles in charging stations in real time, and optimizing the maintenance time of the next charging pile in charging station based on the operational health status; repeating the above steps to complete the optimization of the maintenance time of charging piles in all charging stations.

[0030] This invention employs the CRITIC method for objective weighting of indicators to obtain the operational health status value of charging piles. This value objectively reflects the operational health status of charging piles and is suitable for real-time assessment of their operational health status. This invention can significantly reduce the maintenance time, maintenance loss value, and maintenance resource consumption costs of charging facilities, thereby improving the overall operational efficiency of charging facilities while ensuring the reliability of charging piles. Attached Figure Description

[0031] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0032] Figure 1 A flowchart of a large-scale electric vehicle charging pile inspection and maintenance optimization method provided by the present invention;

[0033] Figure 2 This is a display diagram showing the inspection and maintenance time and time period of 10 charging stations under the method of the present invention;

[0034] Figure 3 This is a schematic diagram of the physical structure of the system provided by the present invention. Detailed Implementation

[0035] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0036] Please see Figures 1-3 A method for optimizing the inspection and maintenance of large-scale electric vehicle charging stations, characterized by the following steps:

[0037] S1. Conduct an operational health status assessment of the charging piles at the charging station and construct an operational health status assessment index system for the charging piles.

[0038] Specifically, a health status assessment index system for charging piles is constructed, including a target layer, a criterion layer, and an indicator layer. The target layer represents the health status value of the charging pile. The criterion layer represents the electrical and control status, communication status, and safety performance status. The indicator layer for electrical and control status includes voltage error rate, current error rate, contact current, inrush current, grounding resistance, insulation resistance, short circuit protection, temperature rise, and emergency stop button indicators. The indicator layer for communication status includes electronic lock anti-counterfeiting module, communication baud rate, and external CAN indicators. The indicator layer for safety performance status includes access control, fire protection, and charging failure rate indicators.

[0039] S2. Obtain indicator values ​​and use the CRITIC method to objectively assign weights to the indicators to obtain operational health status values;

[0040] Specifically, voltage error rate, current error rate, contact current, inrush current, grounding resistance, insulation resistance, temperature rise, and charging failure rate are measurable indicators with appropriate ranges. The measured values ​​of these indicators are obtained through monitoring, and then converted into values ​​between 0 and 10 using the range variation method. These values ​​are then averaged into positive indicators, with the optimal and worst values ​​being 10 and 0, respectively. Short-circuit protection, electronic lock anti-counterfeiting module, access control, emergency stop button, fire protection, communication baud rate, and external CAN indicators cannot be directly obtained from monitoring data. These indicators are determined by on-site inspection of the corresponding equipment's appearance and functionality by personnel. If the appearance is intact and the function is normal, the indicator value is 10; if the appearance is damaged but the function is normal, the indicator value is 5; and if the function fails, the indicator value is 0. The CRITIC method is then used to objectively weight the indicators, and the weighted sum of each indicator value yields the charging pile's health status value.

[0041] S3. Based on the operational health status values, determine the charging stations requiring maintenance and the maintenance sequence of their charging piles. Based on the time-sequential nature of vehicle arrival rates, optimize the maintenance duration of the charging piles to minimize the sum of maintenance loss value and maintenance resource consumption cost. Specifically,

[0042] S31. Based on the health status values ​​of the charging piles obtained from the assessment, the charging station with the smallest average health status value of the charging piles is identified as the charging station that needs to be inspected and maintained. Then, the maintenance order of the charging piles is determined according to the order of the health status values ​​of the charging piles of the charging station. The smaller the health status value, the earlier the maintenance order. When the health status value is greater than the set health value of the charging pile, no maintenance is performed.

[0043] S32. The purpose of charging pile maintenance is to reduce its failure rate. Setting a maintenance period for a specific charging pile will halve its failure rate. On the other hand, because the maintenance period occupies the charging pile, preventing users from charging, it will extend the completion time of the user's charging service. Therefore, the maintenance loss value is defined as:

[0044]

[0045] Where f loss,k Let t be the maintenance loss value of charging pile k, FL() be the floor function, and t be the value of the maintenance loss value of charging pile k. k Let t be the maintenance duration of charging pile k, which is the optimization variable for maintenance decisions. e λ(H) is the duration of a set maintenance period. k H k The following are the failure rate and operational health status values ​​of charging pile k, in order. The time cost incurred due to the maintenance of charging pile k, l kLet b1 and b2 be the time period during which charging pile k is maintained, and b1 and b2 be the coefficients of the exponential model relating the charging pile failure rate to its health status. Data on the failure rate and health status of charging piles for more than two years are collected, and the values ​​of these coefficients are obtained through the least squares fitting method.

[0046] Considering the temporal nature of vehicle arrival rates, and with the objective of minimizing the sum of the maintenance loss value and maintenance resource consumption cost of the determined charging stations requiring maintenance, the objective function can be:

[0047]

[0048] Where c1 and c2 are the weight coefficients of the two sub-objectives: maintenance loss value and maintenance resource consumption cost. These weight coefficients are normalized according to the importance of each sub-objective, f. maint,k M represents the maintenance resource consumption cost for charging pile k at the charging station that requires inspection and maintenance. k The unit time maintenance resource consumption cost of charging pile k is obtained from the cost of the resources consumed for maintenance;

[0049] The constraints include the maintenance duration and operation and maintenance sequence constraints for individual charging piles, for

[0050] t min ≤t k ≤t max ,l k+1 =l k +t k (3) Where, t min t max These are the minimum and maximum maintenance times for a single charging station, respectively. k+1 This refers to the time period during which the charging station (k+1) is being maintained;

[0051] In formula (1) The calculation is as follows

[0052]

[0053] Where c3 is the economic cost coefficient per unit of lost time for the charging user, expressed in yuan per minute. Its value can be set as the average charging cost per minute for the charging user. For l k The difference in waiting time per unit vehicle between charging stations with and without charging pile maintenance, i.e., the loss of waiting time per unit vehicle due to charging pile maintenance, expressed in minutes per vehicle. The time period for the maintenance of charging pile k k The vehicle arrival rate is measured in vehicles per minute and is obtained from data statistics on the operation of the charging station.

[0054] Using time-varying Mt / M t / S / K queuing model, The calculation of waiting time for vehicles per unit is as follows:

[0055]

[0056] in They are l k The waiting time for vehicles at a charging station containing charging piles S and S-1, with and without charging pile maintenance, is T. (l) , These represent the unit vehicle waiting time, average number of people in the queue, and effective arrival rate for each time period / time period.

[0057] The average number of people queuing reflects the average number of vehicles queuing in front of the charging station, and is calculated by equation (6):

[0058]

[0059] in λ represents the average number of people queuing during the time period. l μ l ρ l S l These represent the arrival rate, service rate, traffic intensity, and number of available charging stations for the time period, respectively, where K is the maximum capacity of the queuing system. The system idle probability is a time period / (time period).

[0060] The system idle probability reflects the likelihood that a charging station will be idle during a given time period, and is calculated using equation (7):

[0061]

[0062] Where p is an intermediate variable, p = 0, 1, 2...S l -1;

[0063] Considering the possibility of vehicle congestion due to queuing, the effective arrival rate is calculated using equation (8):

[0064]

[0065] in The blocking probability for the time period / ;

[0066] Solve the objective function (2) to obtain the maintenance time of the charging pile.

[0067] S4. After the maintenance of the current charging station is completed, the operational health status of the remaining charging piles in the charging station is evaluated in real time, and the maintenance time of the next charging pile is optimized based on the operational health status.

[0068] Specifically, after the maintenance of the charging piles at the designated charging stations is completed, the operational health status of the charging piles at the remaining charging stations is assessed to determine the next charging station to be maintained and the maintenance sequence of the charging piles at that station. An optimized maintenance duration is then determined, and the maintenance of the charging piles at the next charging station is carried out.

[0069] S5. Repeat the above steps to optimize the maintenance time of all charging piles at all charging stations.

[0070] Example 1: Taking the optimization of charging pile maintenance at 10 charging stations within a certain charging station operation and maintenance management area as an example. The charging stations are numbered 1 to 10, and the number of charging piles in each charging station is 8, 10, 11, 10, 12, 12, 11, 8, 10, and 8 respectively. The duration of a maintenance period is set to 20 minutes. The minimum and maximum values ​​of the maintenance duration t for a single charging pile are set. min t max The maintenance times were set to 20 minutes and 60 minutes respectively, with a charging pile health value of 9 (an empirical value) and a maintenance period from 8:00 to 18:00. Using the method proposed in this invention, the maintenance time for charging piles in 10 example charging stations was optimized. The weight coefficients c1 and c2 for the two sub-objectives, maintenance loss value and maintenance resource consumption cost, were both set to 0.5 (in multi-objective optimization, different sub-objective weight coefficients can be set according to actual needs, and the sum of all sub-objective weight coefficients is 1). The economic cost coefficient c3 for charging users losing time per unit time was set to 0.2 yuan / minute.

[0071] 1) Conduct the first health status assessment of the charging piles at the charging station. Construct a health status assessment index system for the charging piles. The target layer is the health status value of the charging piles, and the criterion layer includes electrical and control status, communication status, and safety performance status. Specifically, the index layer for electrical and control status includes voltage error rate, current error rate, contact current, inrush current, grounding resistance, insulation resistance, short-circuit protection, temperature rise, and emergency stop button indicators. The index layer for communication status includes electronic lock anti-counterfeiting module, communication baud rate, and external CAN indicators. The index layer for safety performance status includes access control, fire protection, and charging failure rate indicators. The index weights obtained using the CRITIC method are shown in Table 1. The values ​​of each indicator were obtained and weighted to obtain the average values ​​of the operational health status of charging stations numbered 1 to 10 in the first evaluation: 6.89, 7.02, 7.27, 5.59, 6.99, 5.34, 6.84, 5.89, 7.29, and 6.14, respectively. The operational health status values ​​of the 12 charging piles in charging station number 6 were 9.54, 5.21, 6.11, 3.41, 7.00, 3.10, 2.34, 7.17, 6.90, 7.80, 3.46, and 3.43, respectively.

[0072] Table 1 Weights of Charging Pile Operational Health Status Assessment Indicators

[0073]

[0074] 2) Based on the average operational health status of the 10 charging stations obtained from the charging pile operational health status assessment, charging station No. 6 was determined to require maintenance. Then, based on the operational health status values ​​of charging piles at charging station No. 6 obtained from the assessment, the maintenance order for charging piles at charging station No. 6 was determined to be 7, 6, 4, 12, 11, 2, 3, 9, 5, 8, 10. Since the operational health status value of charging pile No. 1 is 9.54, which is greater than the set charging pile health value, no maintenance is required.

[0075] 3) Considering the temporal nature of the arrival rate of charging vehicles, the maintenance time of the charging piles at charging station No. 6 is optimized to minimize the sum of the maintenance loss value cost and the maintenance resource consumption cost, as shown in Table 2.

[0076] Table 2 Maintenance time of charging piles at charging station No. 6

[0077] Maintenance order Charging station number Maintenance time / minute 1 7 20 2 6 32 3 4 33 4 12 34 5 11 41 6 2 42 7 3 49 8 9 51 9 5 53 10 8 54 11 10 60 / 1 0

[0078] 4) After the maintenance of charging station No. 6 is completed, the operational health status of the charging piles at the remaining charging stations is assessed in real time. A decision is made to proceed to the next charging station for maintenance, and the above steps are repeated. This yields the maintenance duration and time periods for the 10 charging stations under the method of this invention, as shown below. Figure 2 As shown.

[0079] 5) Under the condition that the routine maintenance time for each charging pile is set to two time periods, the comparison results between the method of the present invention and the conventional maintenance method are as follows: the maintenance time is 3432 minutes and 4000 minutes respectively; the maintenance loss value cost of charging piles is RMB 18222.9 and RMB 23781.9 respectively; and the maintenance resource consumption cost is RMB 34319.4 and RMB 40000 respectively. Compared with the conventional maintenance method, the method of the present invention reduces the maintenance time by 23.37%, reduces the maintenance resource consumption cost by 14.2%, and significantly reduces the maintenance loss value cost of charging piles. This method effectively improves the overall operation and maintenance efficiency of charging facilities while ensuring the reliability of charging piles.

[0080] The present invention also provides a large-scale electric vehicle charging pile inspection and maintenance optimization system, comprising: at least one processor, at least one memory and a communication interface; wherein the processor, memory and communication interface communicate with each other;

[0081] The memory stores program instructions that can be executed by the processor, which calls the program instructions to execute a large-scale electric vehicle charging pile inspection and maintenance optimization method.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for optimizing the inspection and maintenance of large-scale electric vehicle charging stations, characterized in that, Includes the following steps: Conduct an operational health status assessment of the charging piles at the charging station and construct an indicator system for assessing the operational health status of the charging piles. Obtain indicator values ​​and use the CRITIC method to objectively assign weights to the indicators to obtain operational health status values; Based on the operational health status value, the charging stations that need maintenance and the maintenance sequence of the charging piles at those stations are determined. Based on the time sequence of the arrival rate of charging vehicles, the maintenance time of the charging piles is optimized with the goal of minimizing the sum of the maintenance loss value and the maintenance resource consumption cost of the charging piles at the charging stations that need maintenance. After the maintenance of the current charging station is completed, the operational health status of the remaining charging piles is assessed in real time, and the maintenance time of the next charging pile is optimized based on the operational health status. Repeat the above steps to optimize the maintenance time of charging piles at all charging stations.

2. The method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles according to claim 1, characterized in that, The constructed charging pile operation health status assessment index system includes a target layer, a criterion layer, and an indicator layer. The target layer represents the charging pile's operation health status value. The criterion layer includes electrical and control status, communication status, and safety performance status. The indicator layer for electrical and control status includes voltage error rate, current error rate, contact current, inrush current, grounding resistance, insulation resistance, short circuit protection, temperature rise, and emergency stop button indicators. The indicator layer for communication status includes electronic lock anti-counterfeiting module, communication baud rate, and external CAN indicators. The safety performance status includes access control, fire protection, and charging failure rate indicators.

3. The method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles according to claim 1, characterized in that, It also includes identifying the charging station with the lowest average health status value of the charging piles as the charging station that needs maintenance, sorting the health status values ​​of the charging piles in the charging station that needs maintenance in order of size, with the smaller the health status value, the higher the maintenance order, and not performing maintenance when the health status value is greater than the preset health value of the charging pile.

4. The method for optimizing the inspection and maintenance of large-scale electric vehicle charging stations according to claim 1, characterized in that, The objective of minimizing the sum of maintenance loss value and maintenance resource consumption cost of charging piles requiring repair and maintenance at charging stations also includes the following: the objective function is: Where c1 and c2 are the weight coefficients of the two sub-objectives: maintenance loss value and maintenance resource consumption cost. These weight coefficients are normalized according to the importance of each sub-objective; f maint,k M represents the maintenance resource consumption cost of charging pile k at a charging station that requires repair and maintenance. k Let t be the unit time maintenance resource consumption cost of charging pile k. k The maintenance time for charging pile k.

5. The method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles according to claim 4, characterized in that, The maintenance loss value of the charging pile is: Among them, f loss,k Let t be the maintenance loss value of charging pile k, FL() be the floor function, and t be the value of the maintenance loss value of charging pile k. k t represents the maintenance time of charging pile k. e λ(H) is the duration of a set maintenance period. k H k The following are the failure rate and operational health status values ​​of charging pile k, in order. The time cost incurred due to the maintenance of charging pile k, l k b1 and b2 are the coefficients of the exponential model relating the failure rate and health status of charging piles. The failure rate and health status data of charging piles for more than two years are collected, and the values ​​of these coefficients are obtained by least squares fitting method. c3 is the economic cost coefficient per unit of lost time for charging users, in yuan / minute. Its value is the average charging cost per minute for charging users. For l k The difference between the waiting time of a unit vehicle at a charging station with charging pile maintenance and the waiting time of a unit vehicle without charging pile maintenance is the unit vehicle waiting time loss caused by charging pile maintenance, expressed in minutes per vehicle. The time period for the maintenance of charging pile k k The vehicle arrival rate is expressed in vehicles per minute.

6. The method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles according to claim 5, characterized in that, Using time-varying M t / M t The / S / K queuing model yields the waiting time per unit vehicle. in They are respectively l k The waiting time for vehicles at a charging station with charging piles (including S and S-1) with charging pile maintenance and the waiting time for vehicles without charging pile maintenance, T (l) , The figures, in order, are the unit vehicle waiting time, average number of people in the queue, and effective arrival rate for each time period. The average number of people in the queue is: Where, λ l μ l ρ l S l These are, in order, the arrival rate, service rate, traffic intensity, and number of available charging stations for the time period, where K is the maximum capacity of the queuing system. The system idle probability is a time period / (time period). The system idle probability for the time period / is Where p is an intermediate variable, p = 0, 1, 2...S l -1; Effective arrival rate in The blocking probability is for a given time period.

7. The method for optimizing the inspection and maintenance of large-scale electric vehicle charging piles according to claim 1, characterized in that, It also includes assessing the operational health status of the remaining charging stations' charging piles after completing the identified charging station charging pile inspection and maintenance, determining the next charging station to be inspected and maintained and the maintenance sequence of the charging piles at that charging station, deciding on the optimal maintenance duration, and then carrying out the next charging station's charging pile inspection and maintenance according to the sequence.

8. A large-scale electric vehicle charging pile inspection and maintenance optimization system, characterized in that, include: The system includes at least one processor, at least one memory, and a communication interface; wherein the processor, memory, and communication interface communicate with each other. The memory stores program instructions that can be executed by the processor, which invokes the program instructions to perform the method according to any one of claims 1-7.

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