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CN-121973657-A - Intelligent fault detection system and method for liquid cooling charging pile

CN121973657ACN 121973657 ACN121973657 ACN 121973657ACN-121973657-A

Abstract

The invention discloses a fault intelligent detection system and a fault intelligent detection method for a liquid cooling charging pile, which relate to the technical field of charging pile fault detection, and are used for collecting parameters such as a branch structure, cooling liquid characteristics, pressure pulse propagation speed and the like under normal working conditions, and constructing an associated reference model of an embedded branch volume library and a blockage judging logic by combining historical blockage case data; the method comprises the steps of synchronously collecting real-time key data before charging and at the initial stage of circulation, judging false fluid infusion abnormality through analyzing contradictory characteristics, locking a blocked suspected branch after non-blocking interference is eliminated, sending pressure pulse to the suspected branch, checking and diagnosing blocking faults based on reflection attenuation coefficient and propagation speed deviation, recording reflection time to calculate blocking point positions and quantify failure cooling liquid amount, calculating effective cooling liquid amount and effective heat dissipation power according to the failure cooling liquid amount, and dynamically adjusting charging power according to heating characteristics of a current SOC stage of a battery.

Inventors

  • Long Chengguo
  • LI YITUO
  • ZHENG YUJIE

Assignees

  • 深圳达德航空科技有限公司

Dates

Publication Date
20260505
Application Date
20260327

Claims (10)

  1. 1. The intelligent fault detection method for the liquid cooling charging pile is characterized by comprising the following steps of: Acquiring branch structure parameters, cooling liquid characteristic parameters and pressure pulse propagation speed under normal working conditions, and establishing an associated reference model of an embedded branch volume library and a blockage judging logic by combining historical blockage case data; Based on the collected real-time key data, judging false fluid infusion abnormality by analyzing contradictory characteristics, removing non-blockage interference according to the judging result of the false fluid infusion abnormality, and locking a blockage suspected branch; Sending a pressure pulse to the locked suspected blockage branch, combining the propagation speed of the pressure pulse in the associated reference model, obtaining a confirmed blockage branch through a reflection attenuation coefficient, and recording the reflection time; Calculating the position of a blocking point based on the reflection time and the propagation speed of the pressure pulse, and combining a branch sectional volume library of an associated reference model to quantify the invalid cooling liquid quantity of a blocked branch; based on the effective heat dissipation power, the charging power is dynamically adjusted in combination with the heating characteristic of the battery in the current SOC stage.
  2. 2. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the collecting of the branch structure parameter, the coolant characteristic parameter and the pressure pulse propagation speed under the normal working condition, in combination with the historical blockage case data, establishes an associated reference model of the embedded branch volume library and the blockage judging logic, and comprises the following steps: The method comprises the steps of obtaining the length and the inner diameter of each branch segment through actual measurement, calculating the volume of each branch segment, constructing a branch volume library, calibrating cooling liquid characteristic parameters and pressure pulse propagation speed under standard environment, wherein the cooling liquid characteristic parameters comprise cooling liquid specific heat capacity, cooling liquid density, cooling liquid viscosity reference value and cooling liquid circulation period, preprocessing historical blockage case data to obtain contradictory characteristic quantification standard of blockage judgment and pressure pulse reflection attenuation coefficient critical value, and integrating the branch structure parameters, the cooling liquid characteristic parameters, the pressure pulse propagation speed, the branch volume library and blockage judgment logic to form a multi-parameter coupling correlation reference model.
  3. 3. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the step of synchronously acquiring real-time key data before charging and at an initial cycle according to a parameter dimension of an associated reference model comprises the steps of: Setting a preset initial period after the circulating pump is started as a circulating initial period, synchronously collecting real-time key data comprising liquid level data, real-time flow data of each branch, real-time pressure data of each branch and real-time viscosity data of cooling liquid in preset initial time and the circulating initial period before charging according to parameter dimension of an associated reference model, wherein the liquid level data is used for matching with a liquid supplementing related judgment standard in the associated reference model, the real-time flow data of each branch and the real-time pressure data of each branch form comparison dimension with branch structure parameters of the reference model, and the real-time viscosity data of the cooling liquid corresponds to cooling liquid characteristic parameters in the reference model.
  4. 4. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the determining of the false fluid replacement abnormality based on the collected real-time critical data by analyzing contradictory features comprises: Extracting liquid level data, real-time flow data of each branch, real-time pressure data of each branch and real-time viscosity data of the cooling liquid from real-time key data, and judging that the liquid level of a liquid supplementing link reaches the standard when the liquid level data is larger than or equal to a preset liquid level standard threshold value in an associated reference model; When the liquid level reaches the standard, the real-time flow data of each branch, the real-time pressure data of each branch and the real-time viscosity data of the cooling liquid are respectively compared with the corresponding preset rated flow range, the preset rated pressure range and the preset normal viscosity range of the cooling liquid in the associated reference model, and when at least one contradictory feature appears, particularly at least one item exceeds the corresponding preset range, the false fluid replacement abnormality is judged.
  5. 5. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the step of removing non-blocking interference and locking a blocking suspected branch according to a determination result of a false fluid replacement abnormality comprises the steps of: When the false fluid infusion abnormality is judged to exist, combining the associated reference model and real-time key data, and carrying out non-blocking interference investigation in dimensions; comparing the real-time flow data of each branch and the real-time pressure data of each branch, which are acquired by the main sensor and the auxiliary sensor at the same monitoring point, judging that the sensors are in fault interference when the data deviation exceeds the preset sensor allowable deviation threshold, removing abnormal data and marking fault sensors; After the sensor fault type interference and the equipment working condition type interference are eliminated, specific branches are positioned by combining branch structure parameters in the associated reference model according to branches which still meet the requirement that the liquid level of the liquid supplementing link meets the standard and at least one of the real-time flow data of each branch, the real-time pressure data of each branch and the real-time viscosity data of the cooling liquid exceeds a corresponding preset range, and the corresponding branches are locked to be suspicious blocking branches.
  6. 6. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the sending a pressure pulse to a locked suspected branch of a blockage, combining with a propagation speed of the pressure pulse in an associated reference model, obtaining a diagnosed branch of the blockage by a reflection attenuation coefficient, and recording a reflection time, comprises: Transmitting low-amplitude high-frequency pressure pulses with preset parameters to a suspected blockage branch, collecting incident signals and reflected signals of the pressure pulses in real time through a pressure sensor at the inlet of the branch, extracting peak pressure P 1 of the incident signals and peak pressure P 2 of the reflected signals, and calculating a reflection attenuation coefficient alpha, wherein the formula is as follows: ; comparing the calculated reflection attenuation coefficient alpha with a preset pressure pulse reflection attenuation coefficient critical value alpha 0 in an associated reference model, simultaneously obtaining the real-time pressure pulse propagation speed v blocking a suspected branch, performing deviation check on the real-time pressure pulse propagation speed v 0 under the normal working condition calibrated in the associated reference model, and when alpha is more than or equal to alpha 0 and is equal to And when the deviation threshold value of the propagation speed of the pressure pulse is less than or equal to the preset value, confirming that the corresponding branch has a blockage fault, and recording the time difference of the pressure pulse from the sending time to the receiving time of the reflected signal as the reflecting time t.
  7. 7. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein calculating the position of the blocking point based on the reflection time and the propagation speed of the pressure pulse, and quantifying the amount of the failed cooling liquid blocking the branch by combining the branch sectional volume library of the associated reference model, comprises: based on the reflection time t and the pressure pulse propagation speed v 0 under the normal working condition calibrated in the relevant reference model, calculating the linear distance L of the blocking point from the branch inlet, wherein the formula is as follows: ; And combining the constructed branch sectional volume library, determining all sections from the blocking point to the branch inlet through L matching of the corresponding branch sections, and accumulating the sectional volumes of the branches to obtain the total volume of cooling liquid which can not participate in circulation in front of the blocking point, wherein the total volume of cooling liquid represents the ineffective cooling liquid volume V 0 of the blocked branch.
  8. 8. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the calculating the effective cooling liquid amount and the effective heat dissipation power according to the failure cooling liquid amount comprises: Based on the constructed branch volume library, accumulating the branch sectional volumes of all branches to obtain a total volume V all of cooling liquid, subtracting the ineffective cooling liquid volume V 0 from the total volume V all of cooling liquid to obtain the effective cooling liquid volume V which can participate in circulation at present, and calculating the effective heat dissipation power Q by combining the calibrated cooling liquid characteristic parameters in the relevant reference model and the allowable maximum temperature range delta T of the cooling liquid based on the heat dissipation requirement of equipment and the tolerance temperature of the cooling liquid, wherein the formula is as follows: ; where ρ is the coolant density, c is the coolant specific heat capacity, and Δt is the coolant circulation period.
  9. 9. The intelligent fault detection method for a liquid-cooled charging pile according to claim 1, wherein the dynamically adjusting the charging power based on the effective heat dissipation power in combination with the heating characteristic of the current SOC stage of the battery comprises: The method comprises the steps of obtaining a current SOC value of a battery of a charging vehicle, dividing the current SOC value into a low SOC stage, a medium SOC stage and a high SOC stage according to preset intervals, extracting preset maximum allowable heating power thresholds P i corresponding to each SOC stage according to heating characteristics of each SOC stage of the battery, wherein i is 1,2 and 3 respectively in the low SOC stage, the medium SOC stage and the high SOC stage, comparing the calculated effective heat dissipation power Q with a preset maximum allowable heating power threshold P i of the current SOC stage, when Q is more than or equal to P i , indicating that the current heat dissipation power meets the heating requirement of the battery of the corresponding stage, and executing charging according to the default maximum allowable charging power of the corresponding SOC stage, and when Q is less than P i , the charging power needs to be adjusted down, wherein an adjustment formula is as follows: ; Wherein, P l is the adjusted charging power value, P di is the default maximum allowable charging power corresponding to the SOC stage, Q is the effective heat dissipation power, and P i is the preset maximum allowable heating power threshold of the current SOC stage; And monitoring the change of the battery temperature, the real-time temperature of the cooling liquid and the effective heat dissipation power in the charging process in real time, and repeating the charging power adjustment process until the parameters are stable when the battery temperature exceeds a preset battery safety threshold or the effective heat dissipation power is further reduced.
  10. 10. A fault intelligent detection system for a liquid-cooled charging pile, using a fault intelligent detection method for a liquid-cooled charging pile according to any one of claims 1-9, comprising: The model construction and data acquisition module comprises a basic parameter acquisition unit, a branch volume library construction unit, an association reference modeling unit and a multidimensional data acquisition unit, wherein the basic parameter acquisition unit is used for actually measuring the branch sectional length and the internal diameter and calibrating the characteristic parameters of cooling liquid and the propagation speed of pressure pulse; The fault preliminary positioning module comprises a false fluid replacement abnormality determination unit, a non-blockage interference investigation unit and a blockage suspected branch positioning unit, wherein the false fluid replacement abnormality determination unit extracts real-time data and judges whether false fluid replacement abnormality exists through logic analysis; The blockage accurate diagnosis and parameter quantification module comprises a pressure pulse interaction unit, a blockage fault diagnosis unit, a blockage point positioning unit and a failure cooling liquid quantity quantification unit, wherein the pressure pulse interaction unit sends low-amplitude high-frequency pressure pulses to a suspected branch, acquires incident signals and reflected signals of the pressure pulses, and extracts peak pressure; The heat radiation performance evaluation module comprises an effective cooling liquid amount calculation unit and an effective heat radiation power evaluation unit, wherein the effective cooling liquid amount calculation unit accumulates all branch volumes to obtain total volume and calculates the effective cooling liquid amount capable of participating in circulation; The charging power regulation and control module comprises an SOC stage matching unit, a charging power adjustment calculation unit and a real-time closed loop optimization unit, wherein the SOC stage matching unit divides low, middle and high SOC stages of the battery, matches heating characteristics of each stage, extracts a corresponding preset maximum allowable heating power threshold value, compares effective heat dissipation power with the heating threshold value of the current SOC stage, calculates adjusted charging power, the real-time closed loop optimization unit monitors battery temperature, cooling liquid temperature and heat dissipation power, and repeats a power adjustment flow when parameters are abnormal.

Description

Intelligent fault detection system and method for liquid cooling charging pile Technical Field The invention relates to the technical field of fault detection of charging piles, in particular to an intelligent fault detection system and method for a liquid cooling charging pile. Background In the field of quick charging of new energy automobiles, liquid cooling charging piles become mainstream configuration due to excellent heat dissipation efficiency, but pipeline branch and lewis faults occur due to impurity deposition, cooling liquid aging and the like, so that charging safety and efficiency are seriously affected. The existing liquid cooling charging pile fault detection technology has a plurality of short plates, and is difficult to meet the accurate operation and maintenance requirements. In the prior art, the blockage is judged by monitoring single parameters, a contradictory characteristic analysis mechanism among the parameters is not established, non-blockage interferences such as sensor faults, abnormal circulating pump working conditions and the like are often misjudged as blockage, or false fluid infusion abnormality is regarded as real blockage, so that fault positioning deviation is large, and a suspected blockage branch cannot be accurately locked. Even if some technologies can detect the blockage initially, the existence of the blockage can be judged, the position of the blockage point is difficult to accurately position by an effective means, the quantitative evaluation of the ineffective cooling liquid amount in the blockage branch is further lacking, and the circulation effectiveness and the heat dissipation capacity loss degree of the cooling liquid can not be mastered. In addition, the existing charging power adjustment strategy is based on battery temperature or fixed threshold value, effective heat dissipation power is derived by the failure cooling liquid quantity caused by uncombined blockage, dynamic adaptation of heat dissipation capacity and charging power is difficult to realize, the problem that battery is overheated due to insufficient heat dissipation or charging efficiency is low due to heat dissipation redundancy is easy to occur, and the operation stability of the charging pile and the service life of the battery are seriously affected. Disclosure of Invention The invention aims to provide a fault intelligent detection system and method for a liquid cooling charging pile, which are used for solving the problems in the prior art. In order to achieve the above purpose, the present invention provides the following technical solutions: in a first aspect, the present invention provides a fault intelligent detection method for a liquid-cooled charging pile, including: Acquiring branch structure parameters, cooling liquid characteristic parameters and pressure pulse propagation speed under normal working conditions, and establishing an associated reference model of an embedded branch volume library and a blockage judging logic by combining historical blockage case data; Based on the collected real-time key data, judging false fluid infusion abnormality by analyzing contradictory characteristics, removing non-blockage interference according to the judging result of the false fluid infusion abnormality, and locking a blockage suspected branch; Sending a pressure pulse to the locked suspected blockage branch, combining the propagation speed of the pressure pulse in the associated reference model, obtaining a confirmed blockage branch through a reflection attenuation coefficient, and recording the reflection time; Calculating the position of a blocking point based on the reflection time and the propagation speed of the pressure pulse, and combining a branch sectional volume library of an associated reference model to quantify the invalid cooling liquid quantity of a blocked branch; based on the effective heat dissipation power, the charging power is dynamically adjusted in combination with the heating characteristic of the battery in the current SOC stage. With reference to the first aspect, in a first implementation manner of the first aspect of the present application, the collecting the branch structure parameter, the cooling liquid characteristic parameter and the pressure pulse propagation speed under the normal working condition, and combining the historical blockage case data, establishing an associated reference model of the embedded branch volume library and the blockage judging logic includes: The method comprises the steps of obtaining the length and the inner diameter of each branch segment through actual measurement, calculating the volume of each branch segment, constructing a branch volume library, calibrating cooling liquid characteristic parameters and pressure pulse propagation speed under standard environment, wherein the cooling liquid characteristic parameters comprise cooling liquid specific heat capacity, cooling liquid density, cooling liquid viscosity refere