A method and device for evaluating insulation degradation of a power battery pack

Abstract

The application discloses a kind of power battery pack insulation deterioration evaluation method and device, method includes: collection service scene dust constructs conductive dust working condition spectrum;Battery pack is placed in closed test cabin, completes dust deposition and weak interface directional enrichment;Apply wet heat cycle load and synchronously couple electric load, real-time monitoring insulation resistance, surface resistivity and partial discharge signal;Extract single cycle high temperature and high humidity minimum insulation resistance constitutes degradation sequence, adopts exponential model to fit attenuation curve and calculates safety margin;Based on dust resistivity mapping IEC pollution grade, check creepage distance and electrical clearance;Utilize Arrhenius-Peck acceleration model to predict insulation failure life.The application is realized dust deposition, wet heat cycle and electric load three stress synchronous coupling by constructing conductive dust working condition spectrum in closed test cabin, and truly reproduces the double failure mechanism that dust absorbs moisture to form conductive water film and fill creepage gap in high dust scene in mining area.

Description

Technical Field

[0001] This invention relates to the field of power battery safety testing technology, specifically a method and apparatus for evaluating the insulation degradation of a power battery pack. Background Technology

[0002] With the rapid development of the new energy vehicle industry, power battery packs have gradually expanded from passenger vehicles to industrial applications such as construction machinery and mining vehicles. In high-dust industrial environments such as coal mines, metal mines, cement plants, and steel mills, battery packs are exposed to a complex environment of conductive dust, alternating day and night temperature and humidity, and continuous self-heating from vehicle discharge. Conductive dust adheres to electrical weak points such as high-voltage connectors, busbars, and vent valves, repeatedly absorbing moisture under day and night dry-wet cycles to form a conductive water film. Leakage current accumulates continuously, gradually leading to leakage and arcing, and in severe cases, triggering thermal runaway, posing a significant threat to vehicle and personnel safety.

[0003] However, existing power battery insulation safety testing systems are mainly based on the clean environment of passenger vehicles, and have the following significant drawbacks:

[0004] First, the operational condition simulation is incomplete. Current national standards GB 38031-2020 / 2025 and GB / T 31467.3-2015, as well as international standards ISO 12405-3:2014 and IEC 60664-1:2020, do not establish a complete set of test methods for the coupling of conductive dust and damp heat cycling. Existing dustproof sealing tests (IP6X) only use non-conductive talc powder for testing, only determining the sealing performance of the casing, and cannot simulate the real failure condition of conductive dust absorbing moisture and forming a conductive water film after deposition; salt spray damp heat tests only simulate coastal corrosive environments, without the conductive dust deposition stage, targeting material corrosion rather than dust conductivity leading to insulation degradation; conventional damp heat insulation aging tests do not introduce dust deposition variables and cannot simulate the cumulative damage of dust conductive pathways. All of the above tests treat dust and damp heat as independent variables, failing to consider the coupling effect between the two in actual service environments.

[0005] Second, the evaluation methods are qualitative. Although IEC 60664-1:2020 classifies pollution levels into four levels, PD1 to PD4, it only provides a qualitative textual description and does not provide a quantitative standard for the correspondence between dust layer resistivity and pollution level, nor does it provide a corresponding battery pack testing procedure. Mining batteries are actually in a PD4 high-conductivity pollution environment, but the industry generally defaults to PD2 / PD3 in its designs, resulting in a serious mismatch between creepage distance and clearance design and actual operating conditions.

[0006] Third, the degradation pattern is not extracted reasonably. Conventional damp heat tests directly use the average value of insulation resistance as the evaluation basis, ignoring the sawtooth fluctuation characteristics of insulation resistance under dry and wet cycles, which is characterized by "sudden drop at high temperature and rebound at low temperature". This makes it impossible to extract the most stringent safety state of a single cycle, resulting in an overly optimistic evaluation result and potential safety risks.

[0007] Fourth, there is a lack of standardized degradation modeling and life prediction methods. Existing technologies lack degradation fitting models adapted to dust-coupled damp-heat conditions, lack the Arrhenius-Peck temperature and humidity accelerated equivalent conversion method, cannot quantitatively estimate the service life of battery insulation, and cannot correlate long-term degradation prediction values ​​with national standard insulation limits to quantitatively assess safety margins.

[0008] Fifth, there is a disconnect between testing and engineering design. Existing test results cannot provide feedback to optimize the insulation coordination of the creepage distance and clearance of the battery high-voltage terminals, resulting in a disconnect between testing and design.

[0009] In summary, existing technologies lack a complete set of quantitative evaluation methods for the insulation degradation of power battery packs under conductive dust-damp heat coupling conditions, and cannot support the insulation reliability verification of battery packs in high dust scenarios such as mining areas. Summary of the Invention

[0010] The purpose of this invention is to overcome or at least partially solve the above-mentioned problems by providing a method and apparatus for evaluating the insulation degradation of a power battery pack.

[0011] To achieve the above objectives, the present invention adopts the following technical solution: a method for evaluating the insulation degradation of a power battery pack, comprising the following steps:

[0012] Dust samples were collected from the service scenarios of the power battery pack under test, and a conductive dust operating condition spectrum was constructed.

[0013] The power battery pack to be tested was placed in a sealed test chamber, and dust deposition was completed according to the conductive dust working condition spectrum.

[0014] A damp heat cycle load is applied to the power battery pack to couple the deposited dust with the damp heat environment, and the insulation resistance of the power battery pack is monitored simultaneously.

[0015] Insulation degradation sequences are extracted from monitoring data, insulation attenuation curves are fitted, insulation safety margins are calculated, and the degree of insulation degradation of the power battery pack is evaluated.

[0016] Preferably, the construction of the conductive dust operating condition spectrum includes:

[0017] The volume resistivity of the dust sample was measured, and dust with a volume resistivity of less than 10³Ω·m was defined as conductive dust.

[0018] Based on the composition, particle size distribution, and on-site deposition characteristics of the dust samples, the dust deposition density was determined to be 0.5~5.0 mg / cm², and the uniform deposition was distinguished from the directional high-density deposition at high-voltage connectors, BMS interfaces, manifolds, and vent valves.

[0019] Preferably, the dust deposition includes:

[0020] An aerosol generator is used to disperse the dust, which is then deposited uniformly throughout the entire process.

[0021] By using a directional nozzle array to spray powder onto the electrical weak interfaces of the power battery pack, local dust accumulation is achieved.

[0022] Preferably, the single-cycle period of the damp heat cycling load is 8~16 hours, including:

[0023] High temperature and high humidity stage: temperature 55~65℃, relative humidity 85%~95% RH, for 6~8 hours, so that the deposited dust absorbs moisture and forms a conductive water film;

[0024] Low temperature and low humidity stage: temperature 5~15℃, relative humidity 30%~50% RH, for 6~8 hours to allow moisture to evaporate;

[0025] The heating and cooling rates are 1~3℃ / min.

[0026] Preferably, while applying the damp heat cycle load, an electrical load is applied to the power battery pack, continuously discharging at 30% to 70% of the rated current to simulate the battery's self-heating operation.

[0027] Preferably, the extraction of the insulation degradation sequence includes:

[0028] For each damp heat cycle, only the lowest insulation resistance during the high temperature and high humidity stage is extracted as the characteristic degradation value of that cycle, forming a monotonically decreasing degradation trend sequence.

[0029] Using an exponential model The degradation trend sequence is fitted, and the degradation rate constant is solved using the least squares method. ,in denoted as the initial insulation resistance, and n as the number of damp heat cycles.

[0030] Preferably, the calculation of the insulation safety margin includes:

[0031] According to national standard insulation limits Insulation resistance corresponding to the preset service life obtained by extrapolation from the exponential model Calculate the safety margin ;

[0032] When K > 1, the insulation safety margin is considered sufficient within the target life; when K ≤ 1, the insulation is considered to have a risk of failure within the target life.

[0033] As a preferred option, it also includes:

[0034] The surface resistivity of the dust layer at the key interface of the power battery pack is measured, and the pollution level is determined according to the preset quantitative mapping criteria.

[0035] The quantitative mapping criterion is: surface resistivity > 10. 10 Ω·cm corresponds to PD1, 10 8 ~10 10 Ω·cm corresponds to PD2, 10 4 ~10 8 Ω·cm corresponds to PD3, <10 4 Ω·cm corresponds to PD4;

[0036] Based on the determined pollution level, combined with the battery operating voltage and the CTI value of the insulation material, the creepage distance and electrical clearance of the high-voltage terminals of the power battery pack are checked to see if they meet the insulation coordination requirements.

[0037] As a preferred option, it also includes:

[0038] Based on the Arrhenius-Peck accelerated model, the number of laboratory damp heat cycles is equivalently converted into the actual service time to predict the insulation failure life of the power battery pack.

[0039] The combined acceleration factor of the Arrhenius-Peck acceleration model is:

[0040]

[0041] Among them activation energy =0.8eV, humidity index n=2.5, Boltzmann constant k=8.617×10 -5 eV / K.

[0042] The present invention also provides a power battery pack insulation degradation evaluation device, comprising:

[0043] A sealed test chamber is used to house the power battery pack under test;

[0044] The dust deposition system includes a dust storage bin, an aerosol generator, and a directional nozzle array, used to complete overall uniform deposition and local interface directional enrichment of dust spraying in the test chamber;

[0045] A temperature and humidity control system is used to execute a preset damp heat cycle curve within the test chamber.

[0046] An online insulation resistance monitoring system, including a high-voltage insulation resistance tester and a multi-channel scanning switch, is used to collect the insulation resistance of the power battery pack in real time.

[0047] An electrical load application system, including a high-power programmable DC electronic load, is used to synchronously simulate the self-heating conditions of battery operation;

[0048] The control and data processing system is used to coordinate the timing of various subsystems, store monitoring data, and execute the evaluation methods described above.

[0049] Compared with existing technologies, this invention fills the industry gap in quantitative evaluation of insulation degradation of power battery packs under coupled conditions of conductive dust and damp heat cycling. By constructing a conductive dust operating condition spectrum and simultaneously coupling the three stresses of dust deposition, damp heat cycling, and electrical load in a sealed test chamber, it realistically replicates the dual failure mechanism of dust absorbing moisture to form a conductive water film and filling creepage gaps in high-dust scenarios such as mining areas. This solves the evaluation distortion problem caused by the independent testing of dust and damp heat in existing standards. By extracting the degradation sequence of the lowest insulation resistance under high temperature and humidity in a single cycle and constructing a rule and exponential model for fitting, the sawtooth fluctuation interference is eliminated, and the insulation degradation law is accurately extracted. Based on safety margin criteria and the Arrhenius-Peck accelerated model, a quantitative conversion link from laboratory accelerated testing to actual service life prediction was established. At the same time, the quantitative mapping between dust layer surface resistivity and IEC pollution level filled the gap in the standard qualitative description, enabling test results to guide the insulation coordination verification of battery pack creepage distance and electrical clearance. Finally, an integrated closed-loop evaluation system was formed, from operating condition replication, accelerated testing, degradation modeling, pollution level determination, insulation verification to service life prediction. This significantly improved the accuracy, reproducibility, and engineering practicality of power battery insulation safety evaluation in high-dust industrial scenarios. Attached Figure Description

[0050] Figure 1 This is a flowchart of the power battery pack insulation degradation evaluation method of the present invention;

[0051] Figure 2 This is a schematic diagram of the overall structure of the power battery pack insulation degradation evaluation device of the present invention. Detailed Implementation

[0052] The present invention will be further described in detail below with reference to the accompanying drawings.

[0053] This specific embodiment is merely an explanation of the present invention and is not intended to limit the invention. After reading this description, those skilled in the art can make creative modifications to this embodiment as needed, but as long as they are within the scope of the claims of the present invention, they are protected by patent law.

[0054] This invention provides a method and apparatus for evaluating the insulation degradation of a power battery pack, which solves the technical problems in the prior art. The overall concept is as follows:

[0055] Example 1

[0056] Please see Figures 1-2 This embodiment provides a method for evaluating the insulation degradation of power battery packs, applicable to the evaluation of insulation degradation of power battery packs for new energy mining dump trucks in coal mine scenarios. The method specifically includes the following steps:

[0057] Step 1: Collect dust samples from the mining area and construct a conductive dust operating condition spectrum.

[0058] Dust samples were collected from the site according to coal mines, metallic mines, and non-metallic mines, and their composition, particle size distribution, and volume resistivity were analyzed. Dust with a volume resistivity less than 10³ Ω·m was defined as conductive dust. Based on the composition, particle size distribution, and on-site deposition characteristics of the dust samples, the dust deposition density was determined to be 0.5–5.0 mg / cm², corresponding to the natural deposition volume in the mining area over 3 months to 5 years. A distinction was made between uniform overall deposition and directional high-density deposition in electrically vulnerable areas such as high-voltage connectors, BMS interfaces, busbars, and vent valves, where the local deposition density was 2–3 times the overall deposition density.

[0059] Step 2: Simulate dust deposition inside the sealed test chamber

[0060] The complete power battery pack under test was placed in a sealed stainless steel test chamber. A compressed air aerosol generator was used to disperse the dust, and then uniform deposition was achieved according to the concentration and duration set by the operating condition spectrum. A directional nozzle array was activated to directionally spray dust onto the electrical weak points of the battery pack, achieving localized dust enrichment and replicating the true state of dust accumulation in the airflow of a mining area.

[0061] Step 3: Apply a damp heat cycle load and simultaneously couple an electrical load to simulate self-heating.

[0062] The power battery pack was subjected to a damp heat cycling load inside the test chamber, with a single cycle of 8-16 hours and a temperature rise / fall rate of 1-3 ℃ / min, and the operation was carried out alternately in two segments:

[0063] High temperature and high humidity stage: temperature 55~65 ℃, relative humidity 85%~95% RH, lasting 6~8 h. During this stage, the deposited dust absorbs moisture to form a continuous conductive water film, and the insulation resistance decreases significantly.

[0064] Low temperature and low humidity stage: temperature 5~15 ℃, relative humidity 30%~50% RH, lasting 6~8 hours. During this stage, moisture evaporates, and the insulation resistance rises slightly.

[0065] While applying a damp heat cycling load, an electrical load is applied to the power battery pack. An external DC electronic load is continuously discharged at 30% to 70% of the rated current to simulate the battery's Joule self-heating condition.

[0066] Step 4: Full-process multi-channel online real-time monitoring

[0067] Three types of data are collected simultaneously, and all data is uploaded to the control and data processing system.

[0068] Core monitoring: A high-voltage insulation resistance tester is used for multi-channel scanning to collect the insulation resistance between the positive electrode and the casing, and between the negative electrode and the casing in real time.

[0069] Auxiliary monitoring 1: The surface resistivity of the dust layer at each key interface is measured using a coaxial three-electrode module.

[0070] Auxiliary monitoring method 2: Leakage current is collected using a microammeter, and partial discharge signals are collected using a high-frequency current transformer as evidence of early signs of degradation.

[0071] Step 5: Extract the degradation sequence and fit the insulation attenuation curve using an exponential model.

[0072] Data selection rules: For each damp heat cycle, only the lowest insulation resistance during the high temperature and high humidity stage is extracted as the characteristic degradation value of that cycle to eliminate sawtooth fluctuation interference and form a monotonically decreasing degradation trend sequence. This lowest value represents the most dangerous insulation state in a single cycle, with a conservative evaluation and higher safety.

[0073] An exponential model is used to fit the degradation trend sequence:

[0074]

[0075] in, Let n be the initial insulation resistance and n be the number of damp heat cycles. Let λ be the degradation rate constant. λ is solved by fitting the sequence using the least squares method. Compared to linear and power function models, the exponential model has a goodness of fit R0. 2 The accuracy can reach 0.96, achieving optimal precision. The model parameters follow the following pattern: the stronger the dust conductivity, the greater the deposition density, the higher the electrical load, the larger the λ value, and the faster the insulation degradation rate.

[0076] Step Six: Calculate the insulation safety margin and output the basic safety evaluation conclusion.

[0077] According to national standard insulation limits Insulation resistance corresponding to the preset service life obtained by extrapolation from the exponential model Calculate the safety margin .

[0078] Among them, the national standard insulation limit Take 100 Ω / V × battery rated voltage (GB 38031-2020 personnel safety threshold). Convert the preset service life into equivalent cycle count, substitute it into the exponential model to predict the insulation resistance, and obtain... .

[0079] When K > 1, the insulation safety margin is considered sufficient within the target life; when K ≤ 1, the insulation is considered to have a risk of failure within the target life, and the margin is insufficient.

[0080] Step 7: Map dust resistivity to pollution level and verify insulation coordination.

[0081] Measure the surface resistivity of the dust layer at key interfaces of the power battery pack, and determine the pollution level according to the following quantitative mapping criteria: surface resistivity > 10. 10 Ω·cm corresponds to PD1, 10 8 ~10 10 Ω·cm corresponds to PD2, 10 4 ~10 8 Ω·cm corresponds to PD3, <10 4 Ω·cm corresponds to PD4.

[0082] Based on the determined pollution level, combined with the battery operating voltage and the CTI value of the insulation material, the mandatory requirements for minimum creepage distance and clearance are obtained from IEC 60664-1. By comparing the existing high-voltage terminal design dimensions of the battery, it is determined whether they meet the insulation coordination requirements for PD4 high-pollution environments, and an optimized insulation structure solution is proposed, such as adding insulating barriers, potting, or hydrophobic coatings.

[0083] Step 8: Predict insulation failure lifetime based on the Arrhenius-Peck accelerated model

[0084] The Arrhenius-Peck combined acceleration model was used to convert the number of laboratory damp-heat cycles into equivalent actual service time, predicting the insulation failure life of the power battery pack. The formula for the combined acceleration factor is:

[0085]

[0086] Among them activation energy =0.8eV, humidity index n=2.5, Boltzmann constant k=8.617×10 -5 eV / K.

[0087] The number of failure cycles corresponding to the insulation resistance falling to the limit is calculated by back-calculating the exponential degradation model. The laboratory cycle number is converted into the actual service time in the mining area by the acceleration factor, and the predicted years of insulation failure are output to formulate the operation and maintenance cycle.

[0088] The evaluation device described in this invention is an integrated, sealed device where the entire system shares the same test chamber, eliminating the need to transfer the battery pack. The device includes the following subsystems:

[0089] Sealed test chamber: Constructed of 304 stainless steel, with dimensions no less than 2000 mm × 1500 mm × 1200 mm, IP65 protection rating, equipped with observation window and cable through-wall terminals, capable of accommodating a complete commercial vehicle battery pack. Dust deposition, temperature and humidity regulation, electrical load application, and multi-parameter monitoring are all completed simultaneously inside the chamber.

[0090] Dust deposition system: includes a dust storage silo (capacity not less than 5 kg), a compressed air aerosol generator, and a directional nozzle array. The adjustable dust concentration is 0.5~10 mg / m³, enabling both uniform deposition and localized high-density directional dust spraying at interfaces.

[0091] Temperature and humidity control system: includes heater, refrigeration compressor, humidifier, and dehumidifier combination. Temperature control range is −20~80 ℃ (accuracy ±1 ℃), humidity control range is 20%~98% RH (accuracy ±3% RH), and it can automatically execute preset humidity and heat cycle curves.

[0092] Insulation resistance online monitoring system: includes a high-voltage insulation resistance tester (range 1 kΩ~10 GΩ, test voltage adjustable 100 / 500 / 1000 V) and a multi-channel scanning switch (no less than 8 channels), which automatically polls the insulation resistance between the positive and negative poles and the shell.

[0093] Surface resistivity measurement module: The chamber is equipped with multiple sets of coaxial three electrodes (compliant with IEC 61340-5-1 standard) and a programmable high voltage source, which are arranged in key positions such as connectors, busbars, and vent valves to collect the surface resistivity of the dust layer in real time.

[0094] Electrical load application system: includes a high-power programmable DC electronic load (maximum power not less than 200 kW), which is connected to the battery pack inside the compartment via a through-wall cable, supports constant current continuous discharge, and simulates 30%~70% rated current self-heating conditions.

[0095] Auxiliary monitoring and overall control system: including partial discharge detector (high frequency current transformer, frequency band 1~30 MHz, captures early discharge signals of insulation degradation) and control and data processing system (PLC coordinates the timing of each device, industrial computer stores and fits all monitoring data, automatically calculates degradation rate λ, safety margin K, equivalent service life, pollution level determination results, and outputs a complete evaluation report).

[0096] The verification data and evaluation results are as follows:

[0097] Operating condition calibration data shows that the volume resistivity of coal mine dust is 8.5 × 10² Ω·m, and the volume resistivity of metal ore dust is 3.2 × 10² Ω·m. -1 Ω·m. At the same depositional density, the degradation rate constant λ of metallic minerals is 47% higher than that of coal minerals; under 50% rated current load, λ increases by 27%.

[0098] The verification results of the examples are as follows: Under no-load conditions in coal mines, the equivalent 3-year insulation margin of the battery pack is insufficient, and insulation failure occurs in 4-5 years; in the environment of highly conductive dust in metal mines, the insulation resistance is lower than the national standard safety limit in just 2 years. The original battery pack is designed according to PD3 (creepage distance 12 mm), but the actual test was conducted in a PD4 environment, and it needs to be extended to more than 25 mm to meet the insulation requirements.

[0099] This invention fills the industry gap in quantitative evaluation of insulation degradation of power battery packs under coupled conditions of conductive dust and humid heat cycling. By constructing a conductive dust operating condition spectrum and simultaneously coupling the three stresses of dust deposition, humid heat cycling, and electrical load in a sealed test chamber, it realistically replicates the dual failure mechanism of dust absorbing moisture to form a conductive water film and filling creepage gaps in high-dust scenarios such as mining areas. By extracting the degradation sequence of the lowest insulation resistance under high temperature and humidity in a single cycle, rules and exponential models are constructed and fitted, eliminating sawtooth fluctuation interference and achieving accurate extraction of insulation degradation laws. Based on the safety margin criterion and the Arrhenius-Peck accelerated model, a quantitative conversion link from laboratory accelerated testing to actual service life prediction is established. At the same time, the quantitative mapping of dust layer surface resistivity to IEC pollution level fills the gap in standard qualitative description, enabling test results to guide the insulation matching verification of battery pack creepage distance and electrical clearance. Finally, an integrated closed-loop evaluation system is formed, from operating condition replication, accelerated testing, degradation modeling, pollution level determination, insulation verification to service life prediction.

[0100] The above description of the embodiments is provided to facilitate understanding and use of the present invention by those skilled in the art. It is obvious to those skilled in the art that various modifications can be made to the embodiments, and the general principles described herein can be applied to other embodiments without creative effort. Therefore, the present invention is not limited to the above embodiments. Improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the present invention should be within the protection scope of the present invention.

Claims

1. A method for evaluating insulation degradation of a power battery pack, characterized in that, Includes the following steps: Dust samples were collected from the service scenarios of the power battery pack under test, and a conductive dust operating condition spectrum was constructed. The power battery pack to be tested was placed in a sealed test chamber, and dust deposition was completed according to the conductive dust working condition spectrum. A damp heat cycle load is applied to the power battery pack to couple the deposited dust with the damp heat environment, and the insulation resistance of the power battery pack is monitored simultaneously. Insulation degradation sequences are extracted from monitoring data, insulation attenuation curves are fitted, insulation safety margins are calculated, and the degree of insulation degradation of the power battery pack is evaluated.

2. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: The construction of the conductive dust operating condition spectrum includes: The volume resistivity of the dust sample was measured, and dust with a volume resistivity of less than 10³Ω·m was defined as conductive dust. Based on the composition, particle size distribution, and on-site deposition characteristics of the dust samples, the dust deposition density was determined to be 0.5~5.0 mg / cm², and the uniform deposition was distinguished from the directional high-density deposition at high-voltage connectors, BMS interfaces, manifolds, and vent valves.

3. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: The dust deposition includes: An aerosol generator is used to disperse the dust, which is then deposited uniformly throughout the entire process. By using a directional nozzle array to spray powder onto the electrical weak interfaces of the power battery pack, local dust accumulation is achieved.

4. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: The single cycle period of the damp heat cycling load is 8~16 hours, including: High temperature and high humidity stage: temperature 55~65℃, relative humidity 85%~95% RH, for 6~8 hours, so that the deposited dust absorbs moisture and forms a conductive water film; Low temperature and low humidity stage: temperature 5~15℃, relative humidity 30%~50% RH, for 6~8 hours to allow moisture to evaporate; The heating and cooling rates are 1~3℃ / min.

5. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: While applying the damp heat cycle load, an electrical load is applied to the power battery pack, continuously discharging at 30% to 70% of the rated current to simulate the battery's self-heating operation.

6. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: The extracted insulation degradation sequence includes: For each damp heat cycle, only the lowest insulation resistance during the high temperature and high humidity stage is extracted as the characteristic degradation value of that cycle, forming a monotonically decreasing degradation trend sequence. Using an exponential model The degradation trend sequence is fitted, and the degradation rate constant is solved using the least squares method. ,in denoted as the initial insulation resistance, and n as the number of damp heat cycles.

7. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: The calculation of the insulation safety margin includes: According to national standard insulation limits Insulation resistance corresponding to the preset service life obtained by extrapolation from the exponential model Calculate the safety margin ; When K > 1, the insulation safety margin is considered sufficient within the target life; when K ≤ 1, the insulation is considered to have a risk of failure within the target life.

8. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: Also includes: The surface resistivity of the dust layer at the key interface of the power battery pack is measured, and the pollution level is determined according to the preset quantitative mapping criteria. The quantitative mapping criterion is: surface resistivity > 10. 10 Ω·cm corresponds to PD1, 10 8 ~10 10 Ω·cm corresponds to PD2, 10 4 ~10 8 Ω·cm corresponds to PD3, <10 4 Ω·cm corresponds to PD4; Based on the determined pollution level, combined with the battery operating voltage and the CTI value of the insulation material, the creepage distance and electrical clearance of the high-voltage terminals of the power battery pack are checked to see if they meet the insulation coordination requirements.

9. The method for evaluating insulation degradation of a power battery pack according to claim 1, characterized in that: Also includes: Based on the Arrhenius-Peck accelerated model, the number of laboratory damp heat cycles is equivalently converted into the actual service time to predict the insulation failure life of the power battery pack. The combined acceleration factor of the Arrhenius-Peck acceleration model is: ； Among them activation energy =0.8eV, humidity index n=2.5, Boltzmann constant k=8.617×10 -5 eV / K.

10. A device for evaluating the insulation degradation of a power battery pack, characterized in that: include: A sealed test chamber is used to house the power battery pack under test; The dust deposition system includes a dust storage bin, an aerosol generator, and a directional nozzle array, used to complete overall uniform deposition and local interface directional enrichment of dust spraying in the test chamber; A temperature and humidity control system is used to execute a preset damp heat cycle curve within the test chamber. An online insulation resistance monitoring system, including a high-voltage insulation resistance tester and a multi-channel scanning switch, is used to collect the insulation resistance of the power battery pack in real time. An electrical load application system, including a high-power programmable DC electronic load, is used to synchronously simulate the self-heating conditions of battery operation; A control and data processing system for coordinating the timing of various subsystems, storing monitoring data, and executing the evaluation method as described in any one of claims 1 to 9.

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