Method and system for automatically positioning reason for too fast attenuation of service life of battery

Abstract

The invention relates to a method and a system for automatically positioning a reason for too fast attenuation of battery life, and belongs to the field of battery detection. For the battery which is judged to be too fast in battery life attenuation, acquiring influence factor data of the battery which affects the battery life attenuation; according to the data of each influence factor, the specific reason for too fast attenuation of the service life of the battery is positioned. The specific reason for SOH outlier of the battery can be accurately and quickly judged through the method provided by the invention.

Description

Technical Field

[0001] The invention relates to a method and system for automatically locating the cause of rapid battery life decay, belonging to the field of battery detection. Background Art

[0002] In recent years, new energy vehicles have become more and more popular among the public, and their market share has increased significantly. Among them, the lifespan issue is one of the key performance issues that everyone is more concerned about. The decline in lifespan leads to a reduction in driving range, affecting the normal operation of customers. For new energy vehicle manufacturers, it is crucial to accurately identify the rapid decline in battery lifespan and the reasons for the decline, and to intervene in the batteries of vehicles in the market in advance and quickly to slow down the decline in lifespan. The battery system can be repaired and replaced before customers perceive the reduction in mileage, thereby improving customer satisfaction. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for automatically locating the cause of rapid battery life decay, so as to solve the problem that the cause of rapid battery life decay cannot be quickly and accurately located.

[0004] To achieve the above objectives, the method for automatically locating the cause of rapid battery life decay of the present invention includes: for a battery determined to have a rapidly decaying battery life, obtaining data on influencing factors that affect the battery life decay of the battery; and locating the specific cause of the rapid battery life decay based on the data on each influencing factor.

[0005] Furthermore, the influencing factors include one, two or more influencing factors such as battery cycle number, total vehicle operating mileage, vehicle operating years, battery historical operating temperature, battery system consistency, battery failure condition, battery daily charging times, battery daily operating mileage, battery charging rate, battery feedback rate, vehicle battery configuration information, and battery cell data.

[0006] Further factors that affect battery life degradation include the battery's historical average daily temperature, battery system configuration, and the vehicle's average daily mileage; If the battery's historical daily average temperature is abnormal, the battery system is configured for non-liquid cooling, and the vehicle's daily average mileage exceeds the limit, then the reason for the rapid attenuation of the battery life is determined to be excessive temperature caused by excessive operation; If the battery's historical daily average temperature is abnormal, the battery system is configured for non-liquid cooling, and the vehicle's daily average mileage is within the limit, then the reason for the rapid attenuation of the battery life is determined to be excessive temperature caused by poor battery heat dissipation; Among them, the normal historical average daily temperature of the battery means that the historical average daily temperature of the battery does not exceed the battery operating warranty temperature.

[0007] If the battery's historical daily average temperature is abnormal, the battery system is configured for liquid cooling, and the vehicle's daily average mileage is within the limit, then it is determined that the reason for the rapid attenuation of the battery life is excessive temperature caused by a liquid cooling system failure; Further factors affecting battery life degradation include the battery's historical daily average temperature and battery system consistency; If the historical average daily temperature of the battery is normal and there is no consistency difference between the batteries, it is determined that the reason for the rapid attenuation of the battery life is the quality problem of the battery cell; Among them, the normal historical average daily temperature of the battery means that the historical average daily temperature of the battery does not exceed the battery operating warranty temperature, and the non-existence of consistency difference in the battery means that the static soc difference of the battery is less than or equal to the set soc threshold.

[0008] Further factors that affect battery life degradation include the battery's historical daily average temperature, battery system consistency, and battery cell data; If the historical average daily temperature of the battery is normal, there is a consistency difference problem with the battery, and the battery cell data conforms to the battery self-discharge abnormal model, it is determined that the reason for the rapid attenuation of the battery life is a micro short circuit of the battery cell; If the historical average daily temperature of the battery is normal, there is a problem of battery consistency difference, and the battery cell data conforms to the model of high battery charging voltage and low discharge voltage, then it is determined that the reason for the rapid attenuation of battery life is that the battery is aged and has large internal resistance; If the historical average daily temperature of the battery is normal, the battery has consistency differences, and the cell data does not conform to the battery self-discharge abnormality model and the battery high charging voltage and low discharge voltage model, then it is determined that the reason for the rapid attenuation of the battery life is poor battery system consistency.

[0009] Among them, the normal historical average daily temperature of the battery means that the historical average daily temperature of the battery does not exceed the battery operating warranty temperature, and the consistency difference of the battery means that the static soc difference of the battery is greater than the set soc threshold.

[0010] A further method for determining whether the battery life is decaying too quickly includes: calculating the real SOH value of the battery; determining whether the real SOH value of the battery is within a preset normal SOH range; if not within the preset range, determining that the battery is decaying too quickly.

[0011] Furthermore, the preset normal SOH range is determined based on the theoretical SOH value and in combination with the actual SOH values ​​of batteries in the same batch.

[0012] Furthermore, the theoretical SOH is based on a battery physical model, using data from real laboratory tests on how the battery SOH changes with the number of cycles, and is calculated based on the number of battery attenuation cycles and age.

[0013] The charging data selected for further calculating the real SOH of the battery meets the following conditions: the vehicle where the battery is located is in a stationary state when charging starts, the initial charging data is data of the lithium iron phosphate battery in a non-voltage plateau period, and the battery data is battery full charge data.

[0014] A system for automatically locating the cause of a battery's life fading too quickly includes a processor, wherein the processor executes a computer program to implement the method for automatically locating the cause of a battery's life fading too quickly as described above.

[0015] The beneficial effects of the present invention are as follows: for a battery that is determined to have a battery life decay that is too fast, data on influencing factors that affect the battery life decay are obtained, and the specific reasons for the battery life decaying too fast are located based on the data of each influencing factor. The present invention can accurately and quickly determine the specific reasons for the battery SOH outlier. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a method for automatically locating the cause of rapid battery life decay based on a large model algorithm in method embodiment 1 of the present invention; Figure 2 is a flow chart of calculating the real SOH of a battery in method embodiment 1 of the present invention; Figure 3 is a violin plot of the outlier battery output in method embodiment 1 of the present invention; Figure 4 is a battery outlier display diagram in method embodiment 1 of the present invention; Figure 5 It is a schematic diagram of the fusion of the large model algorithm in method embodiment 1 of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail in a clear and complete manner in conjunction with the accompanying drawings and embodiments.

[0018] The idea of ​​the present invention is to obtain data of influencing factors affecting the battery life decay for a battery whose battery life decays too quickly; and locate the specific reason why the battery life decays too quickly based on the data of each influencing factor.

[0019] Method Example 1: like Figure 1 The figure shows a flow chart of a method for automatically locating the cause of rapid battery life degradation based on a large model algorithm. Figure 5 It is a schematic diagram of the fusion of the large model algorithm in the method embodiment 1 of the present invention. The specific implementation steps include: Step 1: Calculate and obtain the actual SOH of the battery. Figure 2This is a flowchart for calculating the true SOH of the battery. First, the charging data is obtained from the cloud data, and then the charging data is cleaned, that is, data screening. First, data that can calculate the static SOC is selected. Since the lithium iron phosphate battery has a voltage plateau period, the battery cell SOC cannot be calculated by voltage during this period, so it is necessary to select data with a non-plateau initial charge. Second, the battery must be fully charged to ensure that the battery system capacity is 100%. Third, the vehicle is stationary at the beginning of charging to ensure that the voltage is in a non-polarized state, and the true SOC of the battery cell is calculated. After the data cleaning is completed, the charged power is calculated by the ampere-hour integration method, and finally the true SOH of the battery is obtained by the SOH calculation formula. The formula for calculating the true SOH of the battery is: (charge power + starting power) / rated capacity.

[0020] Step 2: Calculate and obtain the factors affecting battery degradation. Specifically, the large model determines the factors that will affect battery degradation, and then calculates the influencing factors. The specific characteristic parameters include battery cycle number, total vehicle operating mileage, vehicle operating years, battery historical operating temperature, battery consistency, battery failure conditions, battery daily charging times, battery daily operating mileage, battery charging rate, battery feedback rate, vehicle battery configuration information, etc.

[0021] In order to improve query performance and simplify data management, an implementable method is to establish a large model data table based on the calculated historical operating condition characteristic parameters and combined with the basic information and real-time information of the vehicle, including: real-time table: SOH table, battery current consistency difference table, historical statistics table: daily operating mileage, daily battery cycle number, daily battery charging number, total mileage, total cycle number, operating years, daily battery temperature, daily charging rate, daily battery feedback rate, basic information table: vehicle battery configuration information, rated capacity, rated energy, static OCV-SOC curve table, etc.

[0022] Step 3: Calculate and obtain the theoretical SOH of the battery. Specifically, the large model provides a physical attenuation model, which uses the data of the battery SOH changing with the number of cycles tested in a real laboratory, and calculates the theoretical SOH of the battery based on the number of attenuation cycles and years of the actual vehicle.

[0023] Step 4: Use the data-driven outlier detection model to identify and output SOH outlier vehicles. Specifically, first determine whether the battery SOH is within the normal attenuation range based on the theoretical value, and then determine the problem vehicle based on the degree of outliers in the same batch of vehicles (violin plot). The annual attenuation is within a range. If it exceeds this range and is outliers in the same batch of vehicles at the same time, it is attenuated too fast. It is judged to be attenuated too fast, that is, the SOH of this vehicle is outliers. For vehicles whose actual battery SOH decays too fast, the program can accurately output, such as Figure 3 , Figure 4 .

[0024] Step 5: Determine the reason why the actual SOH of the battery decays too quickly. Based on step 2, the large model determines the importance of each influencing factor, that is, determines the main influencing factor, the secondary influencing factor, and then locates the specific reason that affects the rapid decay of the battery based on each influencing factor.

[0025] The following example explains the above process in detail: It is assumed that the factors affecting the attenuation of outlier batteries include battery temperature, battery system consistency, and battery cell quality.

[0026] First, the large model determines that the factors affecting battery attenuation include battery temperature, battery system consistency, and battery cell quality. After determining the influencing factors, the historical operating condition characteristic parameters of all influencing factors are calculated, that is, the historical operating condition characteristic parameters of battery temperature, battery system consistency, and battery cell quality are calculated. After the battery outliers are identified and output, the large model sorts the influencing factors based on the judgment. In this embodiment, the order of importance is battery temperature, battery system consistency, and battery cell quality. Based on the large model's determination that the main factor affecting battery SOH attenuation is battery temperature, first determine the size of the battery characteristic temperature and the battery warranty operating temperature. If the battery characteristic temperature is greater than the battery warranty operating temperature, then further analyze whether the operation exceeds the safety range based on the characteristic parameter safety range given by the large model. If it exceeds, it is determined that the specific cause of the rapid attenuation of the battery SOH is the operation exceeding the limit; if it does not exceed, it is determined that there are problems such as liquid cooling system failure.

[0027] If the characteristic temperature of the battery is lower than the battery warranty operating temperature, it indicates that the real SOH decay of the battery is not caused by the temperature exceeding the limit, and further analysis is needed to see if the consistency is poor. The consistency of the battery system is judged based on the static SOC of the battery. In the large model, there is an X1 which is the standard value of the static SOC of the battery, X1>5. If the static SOC difference of the battery is less than X1, the reason for the rapid decay of the SOH is located in the quality problem of the battery cell, and the battery cell needs to be replaced; if the static SOC difference of the battery is greater than X1, it is further judged whether the battery cell has abnormal self-discharge or is charged high and discharged low. If so, the reason for the rapid decay of the real SOH of the battery is located in the micro short circuit of the battery cell or the large internal resistance of the battery cell, and the battery cell needs to be replaced; if not, the reason for the rapid decay of the real SOH of the battery is located in the poor consistency of the battery system, and active or passive balancing is required.

[0028] Specifically, determine whether the battery temperature exceeds the limit based on the vehicle battery operating warranty temperature. If the battery's historical average daily temperature exceeds the warranty temperature, the battery is judged to be at high temperature. Determine whether the battery system has a consistency problem based on the battery's static soc difference. If the battery's static soc difference is greater than X1, X1>5, determine that the battery system has a consistency difference.

[0029] When SOH is outliers and the battery is at high temperature, it is a battery high temperature problem. To further determine the cause of the battery high temperature, if the battery system is configured for non-liquid cooling and the average daily mileage of the vehicle exceeds the limit, it is determined to be an operation over-limit. If it is not an operation over-limit, it is caused by poor battery heat dissipation. If the battery system is configured for liquid cooling, it is a liquid cooling system failure. When SOH is outliers and the battery is not at high temperature and there are consistency differences in the battery, if the battery cell data conforms to the abnormal self-discharge model, it is caused by a micro-short circuit of the battery. If the battery cell data conforms to the model of higher charging voltage and lower discharge voltage, it is caused by battery aging and large internal resistance. If the battery cell data does not conform to the above model, it is caused by inconsistent battery SOC power. When SOH is outliers and the battery is not at high temperature and the battery system consistency is good, it is a battery cell quality problem. The battery cell process is poor, resulting in a high battery cell attenuation rate.

[0030] Method Example 2: On the basis of Example 1, in order to realize daily data monitoring and analysis of users, as an implementable method, the real SOH attenuation outlier and cause location algorithm of the battery is deployed on the data visualization platform, and a wide table for the real SOH attenuation outlier and cause location analysis of the battery is established. After extracting the vehicle, the real SOH value of the current battery of the vehicle, the theoretical attenuation SOH value of the battery, whether it is attenuating too fast, the cause of excessive attenuation, the average daily temperature of the vehicle, the average daily operating mileage and other data can be displayed, so that users can analyze problems efficiently.

[0031] Method embodiment 3: On the basis of Example 1, in order to realize the rapid repair of vehicles with excessive SOH decay, as an implementable method, the real SOH outlier alarm of the battery triggered by the vehicle is automatically pushed to the after-sales service integrated platform. The after-sales service can quickly repair the vehicle according to the pushed repair suggestions, thereby realizing the automatic push repair function of SOH decay outlier.

[0032] System Example: A system for automatically locating the cause of battery life decaying too quickly includes a processor. The system for automatically locating the cause of battery life decaying too quickly in this embodiment executes the method for automatically locating the cause of battery life decaying too quickly as described in method embodiment 1, method embodiment 2, and method embodiment 3. The method for automatically locating the cause of battery life decaying too quickly has been described clearly enough in method embodiment 1, method embodiment 2, and method embodiment 3, and will not be repeated here.

[0033] Through the above steps, the present invention provides a method and system for automatically locating the cause of rapid battery life decay, and displays this function through a data visualization platform and pushes real-time alarms, so that users can more quickly query the real SOH value of the battery on the vehicle, whether the real SOH of the battery is decaying normally, and judge the decay cause, which can help after-sales to quickly repair the vehicle and improve work efficiency. In addition, it can identify and repair the battery in advance before it decays beyond the limit, saving maintenance costs and avoiding customer vehicles from breaking down, which has great application value in the field of new energy vehicles.

[0034] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that numerous changes, modifications, substitutions and variations may be made to the examples without departing from the principles and spirit of the invention, the scope of the invention being defined by the appended claims and their equivalents.

Claims

1. A method for automatically locating the cause of rapid battery life decay, characterized in that: The method includes: for a battery determined to have a battery life decay that is too fast, obtaining data of influencing factors that affect the battery life decay of the battery; and locating the specific cause of the battery life decaying too fast according to the data of each influencing factor.

2. The method for automatically locating the cause of rapid battery life decay according to claim 1, characterized in that: The influencing factors include one, two or more influencing factors such as battery cycle number, total vehicle operating mileage, vehicle operating years, battery historical operating temperature, battery system consistency, battery failure conditions, battery daily charging times, battery daily operating mileage, battery charging rate, battery feedback rate, vehicle battery configuration information, and battery cell data.

3. The method for automatically locating the cause of rapid battery life decay according to claim 1, characterized in that: Factors that affect battery life degradation include the battery's historical average daily temperature, battery system configuration, and the vehicle's average daily mileage; If the battery's historical daily average temperature is abnormal, the battery system is configured for non-liquid cooling, and the vehicle's daily average mileage exceeds the limit, then the reason for the rapid attenuation of the battery life is determined to be excessive temperature caused by excessive operation; If the battery's historical daily average temperature is abnormal, the battery system is configured for non-liquid cooling, and the vehicle's daily average mileage is within the limit, then the reason for the rapid attenuation of the battery life is determined to be excessive temperature caused by poor battery heat dissipation; If the battery's historical daily average temperature is abnormal, the battery system is configured for liquid cooling, and the vehicle's daily average mileage is within the limit, then it is determined that the reason for the rapid attenuation of the battery life is excessive temperature caused by a liquid cooling system failure; Among them, the normal historical average daily temperature of the battery means that the historical average daily temperature of the battery does not exceed the battery operating warranty temperature.

4. The method for automatically locating the cause of rapid battery life decay according to claim 1, characterized in that: Factors that affect battery life degradation include the battery's historical daily average temperature and battery system consistency; If the historical average daily temperature of the battery is normal and there is no consistency difference between the batteries, it is determined that the reason for the rapid attenuation of the battery life is the quality problem of the battery cell; Among them, the normal historical average daily temperature of the battery means that the historical average daily temperature of the battery does not exceed the battery operating warranty temperature, and the non-existence of consistency difference in the battery means that the static SOC difference of the battery is less than or equal to the set SOC threshold.

5. The method for automatically locating the cause of rapid battery life decay according to claim 1, characterized in that: Factors that affect battery life degradation include the battery's historical average daily temperature, battery system consistency, and battery cell data; If the historical average daily temperature of the battery is normal, there is a consistency difference problem with the battery, and the battery cell data conforms to the battery self-discharge abnormal model, it is determined that the reason for the rapid attenuation of the battery life is a micro short circuit of the battery cell; If the historical average daily temperature of the battery is normal, there is a problem of battery consistency difference, and the battery cell data conforms to the model of high battery charging voltage and low discharge voltage, then it is determined that the reason for the rapid attenuation of battery life is that the battery is aged and has large internal resistance; If the historical average daily temperature of the battery is normal, the battery has consistency differences, and the cell data does not conform to the battery self-discharge abnormality model and the battery high charging voltage and low discharge voltage model, then it is determined that the reason for the rapid attenuation of the battery life is poor battery system consistency; Among them, the normal historical average daily temperature of the battery means that the historical average daily temperature of the battery does not exceed the battery operating warranty temperature, and the consistency difference of the battery means that the static soc difference of the battery is greater than the set soc threshold.

6. The method for automatically locating the cause of rapid battery life decay according to claim 1, characterized in that: Methods for determining that the battery life is decaying too quickly include: calculating the real SOH value of the battery; determining whether the real SOH value of the battery is within a preset normal SOH range; if not within the preset range, determining that the battery is decaying too quickly.

7. The method for automatically locating the cause of rapid battery life decay according to claim 6, characterized in that: The preset normal SOH range is determined based on the theoretical SOH value and in combination with the actual SOH values ​​of batteries in the same batch.

8. The method for automatically locating the cause of rapid battery life decay according to claim 7, characterized in that: The theoretical SOH is based on a battery physical model, using data from real laboratory tests on how the battery SOH changes with the number of cycles, and is calculated based on the number of battery attenuation cycles and age.

9. The method for automatically locating the cause of rapid battery life decay according to claim 6, characterized in that: The charging data selected for calculating the real SOH of the battery meets the following conditions: the vehicle in which the battery is located is in a stationary state when charging starts, the initial charging data is data of the lithium iron phosphate battery in a non-voltage plateau period, and the battery data is battery full charge data.

10. A system for automatically locating the cause of rapid battery life decay, comprising a processor, characterized in that: The processor executes a computer program to implement the method for automatically locating the cause of rapid battery life decay as described in any one of claims 1-9.

Images