Waste power battery disassembly safety risk grading method based on expansion characteristics

Abstract

The invention discloses a waste power battery disassembly safety risk grading method based on expansion characteristics, and relates to the technical field of battery disassembly. Comprising the following steps: step 1, carrying out appearance inspection and voltage measurement on waste power batteries to be disassembled, removing batteries with obvious physical damage and abnormal voltage, sequentially putting the waste power batteries with qualified appearance inspection and voltage measurement into a closed safety bin, obtaining initial volumes of the batteries through a non-contact sensor, and calculating the initial volumes of the batteries according to the initial volumes of the batteries; an initial expansive force of the battery within the constraining frame is measured using a force sensor. According to the method, micro-perturbation excitation with specific multiplying power and duration is applied to the to-be-detected battery, the volume and expansive force change characteristic parameters of the battery are monitored and extracted in real time, a multi-dimensional risk assessment system is constructed in combination with a time domain response index, and then the weight ratio of each characteristic parameter is dynamically adjusted according to the type of a battery system, so that the risk assessment accuracy is improved. And accurate quantitative grading of the disassembling risks of the waste power batteries in different chemical systems is realized.

Description

Technical Field

[0001] This invention relates to the field of battery dismantling technology, specifically to a method for safety risk classification in the dismantling of spent power batteries based on their expansion characteristics. Background Technology

[0002] With the explosive growth of the new energy vehicle industry, the first batch of vehicle power batteries has entered the retirement period on a large scale. How to safely, efficiently and environmentally recycle and dispose of these used power batteries has become a major issue related to environmental protection, resource recycling and public safety. Among the many stages of battery recycling, physical dismantling is a key preliminary step that breaks down the battery pack into cells so that they can be finely recycled and reused in the future.

[0003] However, used power batteries, especially those whose performance has deteriorated due to internal short circuits, aging, or misuse, are highly susceptible to thermal runaway during dismantling due to mechanical stress, thermal shock, or short circuits. This can lead to fires, explosions, or even the release of toxic gases, posing a serious threat to personnel and equipment. Therefore, accurately assessing the safety risks of batteries before dismantling and implementing differentiated safety measures accordingly is a critical challenge that the industry urgently needs to address.

[0004] Currently, the industry's initial screening of used batteries mainly relies on two external electrical parameters: voltage and internal resistance. Batteries with excessively low voltage (severely depleted) or excessively high voltage (fully charged) are generally considered to be of higher risk. However, this method has significant limitations. For example, voltage and internal resistance are macroscopic, static indicators of battery condition and cannot sensitively reflect damage to the battery's internal microstructure, such as separator wear, lithium dendrite growth, and phase transitions in the positive and negative electrode materials. A battery with normal voltage may already be in a critical state of thermal runaway, but this cannot be detected in static measurements. Furthermore, the dismantling process is dynamic and involves external stimuli; static parameters cannot predict the battery's dynamic response and the likelihood of risk outbreaks when subjected to mechanical forces such as cutting or crushing. Summary of the Invention

[0005] The purpose of this invention is to provide a safety risk classification method for dismantling spent power batteries based on expansion characteristics, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for safety risk classification of dismantling spent power batteries based on expansion characteristics, comprising the following steps: Step 1: Conduct visual inspection and voltage measurement on the dismantled waste power batteries, and remove batteries with obvious physical damage or abnormal voltage. Place the waste power batteries that pass the visual inspection and voltage measurement in a sealed safety chamber in sequence. Obtain the initial volume of the battery through non-contact sensors and measure the initial expansion force of the battery within the constraint frame using force sensors. Step 2: Apply micro-perturbation excitation to the battery placed in the sealed safety chamber. During the application of micro-perturbation excitation and for 3-10 minutes after its end, continuously monitor and record the changes in battery volume and surface expansion force. Step 3: Based on the time-series data of battery volume change and surface expansion force change from Step 2, extract the change characteristic parameters; Step 4: Input the change feature parameters extracted in Step 3 into the preset risk assessment model. The risk assessment model performs threshold judgment and scoring on the change feature parameters. The risk assessment model integrates the scores of all change feature parameters and the known information of the battery to output a quantitative disassembly safety risk level. The risk level includes at least three levels: low-risk battery, medium-risk battery, and high-risk battery. Step 5: Based on the battery risk level determined in Step 4, assign differentiated disassembly solutions to the battery and output a risk mitigation plan report.

[0007] Furthermore, the micro-perturbation excitation is to apply a discharge pulse with a rate range of 0.05C to 0.5C to the battery under test, and the duration of the discharge pulse ranges from 10 seconds to 600 seconds.

[0008] Furthermore, the changing characteristic parameters include: Amplitude characteristic parameters, including maximum volume change rate and maximum expansion force change rate; The time-domain characteristic parameters include response time Tr and decay time Td. Response time is the time required from the start of the micro-perturbation until the volume change rate reaches 80-90% of the maximum volume change rate, and decay time is the time taken from the end of the micro-perturbation until the volume change rate decays from the peak to 10-20% of the peak.

[0009] Furthermore, the formula for calculating the maximum volume change rate is: ; Where max(ΔV(t)) is the maximum value of the volume change during the monitoring period t, and V0 is the initial volume of the battery under test; The formula for calculating the maximum rate of change of expansion force is: ; Where max(ΔF(t)) is the maximum value of the change in expansion force during the monitoring period t, and F0 is the initial expansion force of the battery under test.

[0010] Furthermore, the risk assessment model uses the following rules for threshold judgment and scoring of the maximum volume change rate and the maximum expansion force change rate: Vmax < 0.15%, judged as a low-risk volume change rate, assigned 2 points; If 0.15% ≤ Vmax < 0.25%, it is judged as a sub-medium risk volume change rate and assigned 5 points; If 0.25% ≤ Vmax < 0.4%, it is judged as a medium risk volume change rate and assigned 8 points; If Vmax ≥ 0.4%, it is judged as a high risk volume change rate and assigned 10 points; If Fmax < 1.5%, it is judged as a low risk volume change rate and assigned 2 points; If 1.5% ≤ Fmax < 3.0%, it is judged as a sub-medium risk volume change rate and assigned 5 points; If 3.0% ≤ Fmax < 5.0%, it is judged as a medium risk volume change rate and assigned 8 points; If Fmax ≥ 5.0%, it is judged as a high risk volume change rate and assigned 10 points.

[0011] Furthermore, the rules for the risk judgment model to perform threshold judgment and scoring on the response time and decay time are as follows: If Tr > 60S, it is judged as a low risk response time and assigned 2 points; If 40S < Tr ≤ 60S, it is judged as a sub-medium risk response time and assigned 6 points; If 20S < Tr ≤ 40S, it is judged as a medium risk response time and assigned 9 points; If Tr ≤ 20S, it is judged as a high risk response time and assigned 10 points; If Td ≤ 120S, it is judged as a low risk decay time and assigned 2 points; If 120 < Td ≤ 240S, it is judged as a sub-medium risk decay time and assigned 6 points; If 240S < Td ≤ 360S, it is judged as a medium risk decay time and assigned 9 points; If Td > 360S, it is judged as a high risk decay time and assigned​​​​​​​​​​​ S≧7 indicates a high-risk battery, meaning the battery is extremely unstable and has a very high risk of thermal runaway.

[0013] Furthermore, the risk assessment model integrates the scores of all changing characteristic parameters and the known information of the battery to output a quantitative disassembly safety risk level. For ternary lithium system batteries, the sum of the weights of the amplitude characteristic parameters is not less than 0.6, and for lithium iron phosphate system batteries, the sum of the weights of the time domain characteristic parameters is not less than 0.6.

[0014] Furthermore, the differentiated disassembly scheme specifically includes: For low-risk batteries, use high-speed cutting tools with a cutting speed r > 8000 rpm; For medium-risk batteries, a medium-speed cutting tool with a cutting speed r>3000rpm and r≤8000rpm is used, supplemented by local water cooling; For high-risk batteries, a low-speed cutting tool with a cutting speed r≤3000 rpm is used for cutting, and the cutting is carried out in a fully enclosed explosion-proof chamber filled with inert gas.

[0015] Furthermore, in step one, when the open-circuit voltage of the battery is less than or equal to 1.5V, it is directly determined to be a low-risk battery, and batteries with an open-circuit voltage greater than or equal to 4.2V are directly determined to be high-risk batteries.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This method for classifying the safety risks of dismantling spent power batteries based on their expansion characteristics involves applying micro-perturbation excitation at a specific rate and duration to the battery under test, monitoring and extracting characteristic parameters of the battery's volume and expansion force changes in real time, constructing a multi-dimensional risk assessment system by combining time-domain response indicators, and then dynamically adjusting the weight ratio of each characteristic parameter according to the battery system type. This achieves accurate quantitative classification of the dismantling risks of spent power batteries with different chemical systems.

[0017] Based on this, differentiated dismantling solutions are matched for batteries with low, medium and high risk levels, namely high-speed cutting, medium-speed cutting with water cooling and low-speed cutting with inert gas protection. At the same time, the open-circuit voltage preliminary screening mechanism can quickly identify batteries with extreme risks, effectively avoiding safety accidents caused by risk misjudgment in the traditional dismantling process. This significantly improves the safety and efficiency of the resource utilization of waste power batteries and provides the industry with a scientific, systematic and highly operable risk management solution. Attached Figure Description

[0018] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] like Figure 1 As shown, this invention provides a technical solution: a method for safety risk classification in the dismantling of spent power batteries based on expansion characteristics, comprising the following steps: Step 1: Conduct a visual inspection and voltage measurement on the used power batteries to be dismantled, and record the battery's chemical system, capacity, and production batch information to establish an initial battery file. Discard batteries with obvious physical damage or abnormal voltage. The discarded batteries are divided into two categories: hazardous batteries and safe batteries. In practical applications, when the open circuit voltage of the battery to be dismantled is greater than or equal to 4.2V, it is determined to be a hazardous battery, and when the open circuit voltage of the battery is less than or equal to 1.5V, it is determined to be a safe battery. Batteries with obvious physical damage are directly classified as hazardous batteries.

[0021] Used power batteries that passed visual inspection and voltage measurement were placed in a sealed safety chamber with constant temperature and humidity for 24 hours. The batteries were then placed on a platform with limit constraints. The platform had a built-in distributed force sensor, and the batteries were slightly tightened to prevent them from expanding freely, but without applying overpressure. The initial static expansion force generated by the batteries on the constraint frame after stabilization was recorded. The inner wall of the sealed safety chamber was equipped with an explosion-proof lining and temperature, smoke, and gas concentration sensors. During this period, the temperature and humidity inside the chamber were monitored in real time to ensure that the environmental parameters were stable within the range of 25±2℃ and relative humidity of 45±5%, eliminating the interference of external environmental factors on the battery state and providing stable initial conditions for subsequent expansion characteristic testing. The initial morphology of each surface of the battery was measured non-contactly using a high-precision displacement sensor array, and the initial volume of the battery was calculated. The high-precision displacement sensor array included one or more combinations of laser displacement sensors, white light interferometers, or structured light 3D scanners, with laser displacement sensors being preferred, as their measurement accuracy was better than 10 micrometers.

[0022] Step Two: Apply micro-perturbation excitation to the battery placed in the sealed safety chamber. During the application of micro-perturbation excitation and for 3-10 minutes after its end, continuously monitor and record the changes in battery volume and surface expansion force. The micro-perturbation excitation is one of the following methods: electrical perturbation, applying a discharge pulse with a rate range of 0.05C to 0.5C to the battery under test, with a discharge pulse duration ranging from 10 seconds to 600 seconds; mechanical perturbation, applying mechanical vibration with an acceleration range of 0.2g to 5g and a frequency range of 5Hz to 200Hz, with a duration not exceeding 120 seconds; thermal perturbation, through temperature... The heat source causes the battery surface to rise by 1°C to 15°C, with the rate of temperature rise controlled within 3°C per minute. In this scheme, electrical perturbation is preferred, that is, using a programmable power supply to apply a constant current charging pulse of 0.2C rate for 60 seconds to the battery. This operation will slightly polarize the battery and stimulate potential side reactions, but not to the extent of damage. Throughout the application of the perturbation and within 3 minutes after the perturbation ends, the laser displacement sensor array and force sensor continuously collect data at high frequency (e.g., 10Hz) to record the time-series curves of battery volume change and expansion force change in real time.

[0023] Step 3: Based on the time-series data of battery volume change and surface expansion force change from Step 2, extract the change characteristic parameters, which include: The amplitude characteristic parameters include the maximum volume change rate and the maximum expansion force change rate. The formula for calculating the maximum volume change rate is: ; Where max(ΔV(t)) is the maximum value of the volume change during the monitoring period t, and V0 is the initial volume of the battery under test.

[0024] The maximum volume change rate Vmax is calculated as the maximum value of (ΔV(t) / V0) over the entire monitoring period. This value directly reflects the intensity of the gas generation reaction inside the battery. The larger Vmax is, the higher the risk.

[0025] Specifically, in this scheme, the laser displacement sensor is activated to scan the surface of the battery cell and calculate its initial volume V0 = 1.245 liters. Within 10 seconds before the start of discharge, within 120 seconds of discharge, and within 180 seconds after the end of discharge, the system synchronously collects and records the volume change ΔV(t) at a frequency of 10Hz. After the monitoring is completed, the safety chamber automatically performs forced cooling to ensure that the battery cell temperature returns to the ambient temperature. During the monitoring period, the maximum value of ΔV(t) is 4.1 ml, and Vmax = (4.1 / 1245) × 100% = 0.33%.

[0026] The formula for calculating the maximum rate of change of expansion force is: ; Where max(ΔF(t)) is the maximum value of the change in expansion force during the monitoring period t, and F0 is the initial expansion force of the battery under test. The larger Fmax is, the higher the risk.

[0027] The initial expansion force F0 = 25.5 N was recorded by the force sensor. During the monitoring period, the maximum value of ΔF(t) was 1.2 N, and Fmax = (1.2 / 25.5) × 100% = 4.7%.

[0028] The time-domain characteristic parameters include response time Tr and decay time Td. Response time is the time required from the start of the micro-perturbation until the volume change rate reaches 80-90% of the maximum volume change rate. Decay time is the time taken from the end of the micro-perturbation until the volume change rate decays from the peak to 10-20% of the peak. In this scheme, response time is the time required from the start of the micro-perturbation until the volume change rate reaches 80% of the maximum volume change rate, and decay time is the time taken from the end of the micro-perturbation until the volume change rate decays from the peak to 20% of the peak.

[0029] In this scheme, the time from the start of discharge to the first time the volume change rate reaches 80% of 0.33% (i.e. 0.264%) is calculated to be 45 seconds for the response time Tr. The time from the end of discharge to the time when the volume change rate decays from 0.33% to 20% (i.e. 0.066%) is calculated to be 210 seconds for the decay time Td.

[0030] Step 4: Input the variation feature parameters extracted in Step 3 into the preset risk assessment model. The risk assessment model performs threshold judgment and scoring on the variation feature parameters. Combining all variation feature parameter scores and known battery information, the risk assessment model outputs a quantified disassembly safety risk level. The risk level includes at least three levels: low-risk battery, medium-risk battery, and high-risk battery. In this scheme, the rules for threshold judgment and scoring of the maximum volume change rate and the maximum expansion force change rate in the risk assessment model are as follows: Vmax < 0.15%, judged as a low-risk volume change rate, assigned 2 points; 0.15%≤Vmax<0.25%, judged as secondary risk volume change rate, assigned 5 points; 0.25%≤Vmax<0.4%, judged as medium-risk volume change rate, assigned a score of 8; Vmax≥0.4% is judged as a high-risk volume change rate and is assigned a score of 10. Fmax < 1.5%, judged as a low-risk volume change rate, assigned 2 points; 1.5%≤Fmax<3.0%, judged as medium-risk volume change rate, assigned 5 points; If 3.0% ≤ Fmax < 5.0%, it is judged as a medium-risk volume change rate and assigned 8 points. If Fmax ≥ 5.0%, it is judged as a high-risk volume change rate and assigned 10 points.

[0031] The rules for the risk determination model to perform threshold judgment and scoring on the response time and decay time are as follows: If Tr > 60S, it is judged as a low-risk response time and assigned 2 points. If 40S < Tr ≤ 60S, it is judged as a sub-medium-risk response time and assigned 6 points. If 20S < Tr ≤ 40S, it is judged as a medium-risk response time and assigned 9 points. If Tr ≤ 20S, it is judged as a high-risk response time and assigned 10 points. If Td ≤ 120S, it is judged as a low-risk decay time and assigned 2 points. If 120 < Td ≤ 240S, it is judged as a sub-medium-risk decay time and assigned 6 points. If 240S < Td ≤ 360S, it is judged as a medium-risk decay time and assigned 9 points. If Td > 360S, it is judged as a high-risk decay time and assigned 10 points.

[0032] Specifically in this solution, the measured value of Vmax is 0.33%, and the score is 8 points; the measured value of Fmax is 4.7%, and the score is 8 points; the measured value of Tr is 45s, and the score is 6 points; the measured value of Td is 210s, and the score is 6 points.

[0033] Step Five: According to the battery risk level determined in Step Four, assign a differentiated disassembly plan to the battery and output a risk disposal plan report. Among them, output a quantitative disassembly safety risk level, and its implementation includes the following steps: Set weight coefficients for each change characteristic parameter; Calculate the comprehensive risk score S = W1×Vmaxs + W2×Fmaxs + W3×Trs + W4×Tds, where W1, W2, W3, and W4 are the corresponding weight coefficients, and ΣW = 1. Vmaxs, Fmaxs, Trs, and Tds are the scores of the maximum volume change rate, the maximum expansion force change rate, the response time score, and the decay time score respectively. Set the values of W1, W2, W3, and W4 to 0.35, 0.36, 0.15, and 0.15.

[0034] Through calculation, the comprehensive risk score S of this battery is 7.4.

[0035] In this solution, if S < 3, it is a low-risk battery, indicating that the battery is internally stable and can be safely processed; 3≤S<7 indicates a medium-risk battery, suggesting that the battery has some instability and should be handled with caution. S≧7 indicates a high-risk battery, meaning the battery is extremely unstable and has a very high risk of thermal runaway. Since the battery's overall risk score is 7.4, it is classified as a "high-risk" level.

[0036] The risk assessment model integrates the scores of all variable characteristic parameters and the known information of the battery to output a quantitative disassembly safety risk level. For ternary lithium system batteries, the sum of the weights of the amplitude characteristic parameters is not less than 0.6, and for lithium iron phosphate system batteries, the sum of the weights of the time domain characteristic parameters is not less than 0.6.

[0037] The differentiated disassembly solutions specifically include: For low-risk batteries, use high-speed cutting tools with a cutting speed r > 8000 rpm; For medium-risk batteries, a medium-speed cutting tool with a cutting speed r>3000rpm and r≤8000rpm is used, supplemented by local water cooling; For high-risk batteries, a low-speed cutting tool with a cutting speed r≤3000 rpm is used for cutting, and the cutting is carried out in a fully enclosed explosion-proof chamber filled with inert gas.

[0038] In addition, in step one, safe batteries are directly classified as low-risk batteries, and dangerous batteries are directly classified as high-risk batteries.

[0039] The central processing system sends the "high-risk" assessment result and disposal instructions for the battery to the execution end. The battery is automatically conveyed into a fully enclosed explosion-proof inert gas dismantling chamber. Inside the chamber, a robot receives the instructions and uses a low-speed water jet cutting process (cutting head travel speed <5mm / s) to dismantle the battery cell under a continuous nitrogen atmosphere. Throughout the process, a thermal imager monitors the entire process, and no fire or explosion occurs. The system automatically generates and saves a risk disposal plan report, which includes: battery information, chemical system, initial voltage, measured values ​​and curves of various expansion characteristic parameters, weighted scoring process and final score.

[0040] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. A method for safety risk classification in the dismantling of spent power batteries based on expansion characteristics, characterized in that, Includes the following steps: Step 1: Conduct visual inspection and voltage measurement on the dismantled waste power batteries, and remove batteries with obvious physical damage or abnormal voltage. Place the waste power batteries that pass the visual inspection and voltage measurement in a sealed safety chamber in sequence. Obtain the initial volume of the battery through non-contact sensors and measure the initial expansion force of the battery within the constraint frame using force sensors. Step 2: Apply micro-perturbation excitation to the battery placed in the sealed safety chamber. During the application of micro-perturbation excitation and for 3-10 minutes after its end, continuously monitor and record the changes in battery volume and surface expansion force. Step 3: Based on the time-series data of battery volume change and surface expansion force change from Step 2, extract the change characteristic parameters; Step 4: Input the change feature parameters extracted in Step 3 into the preset risk assessment model. The risk assessment model performs threshold judgment and scoring on the change feature parameters. The risk assessment model integrates the scores of all change feature parameters and the known information of the battery to output a quantitative disassembly safety risk level. The risk level includes at least three levels: low-risk battery, medium-risk battery, and high-risk battery. Step 5: Based on the battery risk level determined in Step 4, assign differentiated disassembly solutions to the battery and output a risk mitigation plan report.

2. The method for safety risk classification of dismantling waste power batteries based on expansion characteristics according to claim 1, characterized in that, The micro-perturbation excitation is to apply a discharge pulse with a rate range of 0.05C to 0.5C to the battery under test, and the duration of the discharge pulse ranges from 10 seconds to 600 seconds.

3. The method for safety risk classification of dismantling waste power batteries based on expansion characteristics according to claim 1, characterized in that, The changing characteristic parameters include: Amplitude characteristic parameters, including maximum volume change rate and maximum expansion force change rate; The time-domain characteristic parameters include response time Tr and decay time Td. Response time is the time required from the start of the micro-perturbation until the volume change rate reaches 80-90% of the maximum volume change rate, and decay time is the time taken from the end of the micro-perturbation until the volume change rate decays from the peak to 10-20% of the peak.

4. The method for safety risk classification of dismantling waste power batteries based on expansion characteristics according to claim 3, characterized in that, The formula for calculating the maximum volume change rate is: ； Where max(ΔV(t)) is the maximum value of the volume change during the monitoring period t, and V0 is the initial volume of the battery under test; The formula for calculating the maximum rate of change of expansion force is: ; Where max(ΔF(t)) is the maximum value of the change in expansion force during the monitoring period t, and F0 is the initial expansion force of the battery under test.

5. The method for safety risk classification of dismantling waste power batteries based on expansion characteristics according to claim 4, characterized in that, The risk assessment model uses the following rules for threshold judgment and scoring of the maximum volume change rate and the maximum expansion force change rate: Vmax < 0.15%, judged as a low-risk volume change rate, assigned 2 points; 0.15%≤Vmax<0.25%, judged as secondary risk volume change rate, assigned 5 points; 0.25%≤Vmax<0.4%, judged as medium-risk volume change rate, assigned a score of 8; Vmax≥0.4% is judged as a high-risk volume change rate and is assigned a score of 10. Fmax < 1.5%, judged as a low-risk volume change rate, assigned 2 points; 1.5%≤Fmax<3.0%, judged as medium-risk volume change rate, assigned 5 points; 3.0%≤Fmax<5.0%, judged as medium-risk volume change rate, assigned a score of 8; If Fmax≥5.0%, it is judged as a high-risk volume change rate and assigned 10 points.

6. The method for safety risk classification of dismantling waste power batteries based on expansion characteristics according to claim 5, characterized in that, The rules for the risk judgment model to perform threshold judgment and scoring on the response time and decay time are as follows: If Tr>60S, it is judged as a low-risk response time and assigned 2 points; If 40S<Tr≤60S, it is judged as a sub-medium risk response time and assigned 6 points; If 20S<Tr≤40S, it is judged as a medium risk response time and assigned 9 points; If Tr≤20S, it is judged as a high-risk response time and assigned 10 points; If Td≤120S, it is judged as a low-risk decay time and assigned 2 points; If 120<Td≤240S, it is judged as a sub-medium risk decay time and assigned 6 points; If 240S<Td≤360S, it is judged as a medium risk decay time and assigned 9 points; If T d>360S, it is judged as a high-risk decay time and assigned 10 points.

7. The method for safety risk classification of dismantling spent power batteries based on expansion characteristics according to claim 6, characterized in that, Output a quantified disassembly safety risk level, and its implementation includes the following steps : Set weight coefficients for each of the change characteristic parameters; Calculate the comprehensive risk score S = W1×Vmaxs + W2×Fmaxs + W3×Trs + W4×Tds, where W1, W2, W3, and W4 are the corresponding weight coefficients, and ΣW = 1, and Vmaxs, Fmaxs, Trs, and Tds are the maximum volume change rate score, maximum expansion force change rate score, response time score, and decay time score respectively; If S<3, it is a low-risk battery, indicating that the battery is internally stable and can be safely processed; If 3≤S<7, it is a medium-risk battery, indicating that the battery has certain instability and needs to be treated with caution; If S≧7, it is a high-risk battery, indicating that the battery is extremely unstable and has a very high risk of thermal runaway.

8. The method for safety risk classification of dismantling waste power batteries based on expansion characteristics according to claim 7, characterized in that, In the risk judgment model that comprehensively scores all change characteristic parameters and the known information of the battery and outputs a quantified disassembly safety risk level, for ternary lithium system batteries, the sum of the weight coefficients of the amplitude characteristic parameters is not less than 0.6, and for lithium iron phosphate system batteries, the sum of the weight coefficients of the time domain characteristic parameters is not less than 0.

6.

9. The method for safety risk classification of dismantling spent power batteries based on expansion characteristics according to claim 1, characterized in that, The specific differential disassembly plan includes: For low-risk batteries, use a high-speed cutting tool with a cutting speed r>8000rpm; For medium-risk batteries, use a medium-speed cutting tool with a cutting speed r>3000rpm and r≤8000rpm, and supplement it with local water cooling; For high-risk batteries, use a low-speed cutting tool with a cutting speed r≤3000 rpm for cutting and perform it in a fully enclosed explosion-proof cabin filled with inert gas.

10. A method for safety risk classification of dismantling spent power batteries based on expansion characteristics, as described in claim 9, is characterized in that... In step one, when the open-circuit voltage of the battery is less than or equal to 1.5V, it is directly judged as a low-risk battery, and the battery with an open-circuit voltage greater than or equal to 4.2V is directly judged as a high-risk battery.

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