A method for detecting abnormality of battery in static state

Abstract

The present invention belongs to the technical field of battery management and relates to battery anomaly detection. A method for detecting battery anomalies in a stationary state comprises the following steps in sequence: collecting the voltage and current of each battery in a series-connected battery pack in real time; determining whether the battery is in a stationary state and timing the stationary state; obtaining the open-circuit voltage and SOC of each battery at the stationary state time t1; setting the SOC change rate n and calculating the OCV change rate α of each battery i ; obtaining the open-circuit voltage of each i-th battery when the #imgabs0# changes by n except for the k-th battery; making a judgment on whether the battery is abnormal. The advantages of this patent are that it solves the fault diagnosis of problems such as micro-short circuits in individual batteries in a series-connected battery pack, and the method is easy to implement and convenient for engineering applications.

Description

Technical Field

[0001] The invention belongs to the technical field of battery management, and relates to battery abnormality detection, and in particular to an abnormality detection method when a battery is in a static state. Background Art

[0002] Batteries are widely used in real life, such as backup power supplies for traditional power substations, communication base station rooms, etc., especially with the rapid development of new energy fields such as electric vehicles and energy storage power stations, a large number of electrochemical batteries such as lithium-ion power batteries or lead-acid batteries are used in electric vehicles, energy storage power stations and other environments. As a representative lithium battery, it has attracted more attention and has been applied in many fields. It has been applied on a large scale in the field of energy storage, providing an effective tool for frequency regulation and peak shaving of power grids, and improving the stability and reliability of power grids. With the rapid development of new energy vehicles, lithium batteries also have very good prospects in the field of transportation, and are currently used in a large number of backup power supplies.

[0003] Electric vehicles, energy storage power stations and other environments all require a large number of batteries to form high voltages. In order to adapt to the safe operation of the battery pack, it is essential to equip it with a corresponding battery management system. However, the main operating state of the battery is charging or discharging, and the battery management system performs related control management, such as charging over-limit, discharging over-limit, temperature over-limit, current over-limit, etc. When not in operation, that is, in a static (or open circuit) state, since there is no charging and discharging, the battery state is relatively stable. Generally, there will be no problems such as charging over-limit, discharging over-limit, current over-limit, etc. during the charging and discharging process. However, it is also exposed to the situation that failures occur in the static state, thus causing safety accidents, that is, it is necessary to detect abnormal battery conditions in the static state. Summary of the invention

[0004] The purpose of the present invention is to solve the above-mentioned deficiencies in battery abnormality detection and to provide a method for accurately detecting battery abnormality in a static state.

[0005] For the purpose of the present invention, the following technical solutions are adopted to achieve the goal:

[0006] A method for detecting abnormality of a battery in a static state comprises the following steps in sequence:

[0007] S1, real-time acquisition of the voltage and current of each battery in the series battery pack;

[0008] S2, determining whether the battery is in a static state, and timing the static state;

[0009] S3, obtain the open circuit voltage and SOC of each battery at the static state t1, and the SOC of the i-th battery at t1 is recorded as The open circuit voltage of the battery is recorded as OCV i t1 ,SOC is a percentage data not exceeding 100%;

[0010] S4, set the SOC change rate n, when the kth battery reaches At this time, the voltage of each battery is recorded as OCV i t1+t2 , calculate the OCV change rate α of each battery i ;

[0011] S5, obtain the values ​​of each i-th battery except the k-th battery The open circuit voltage of the battery when changing n is recorded as OCV i t1 +t2+t3

[0012] S6, determining whether the battery is abnormal.

[0013] Preferably, in S3, a curve of the relationship between the battery open circuit voltage and SOC is stored in the voltage analysis module; in S3, time t1 is the time of the battery open circuit voltage after being left to stabilize, which is generally 4 hours.

[0014] Preferably, in S4, the battery OCV change rate α i ,

[0015] Preferably, the SOC change rate n is 1%.

[0016] Preferably, in S6, the OCV of each i-th battery is calculated. i t1+t2 Change to OCV i t1+t2+t3 Time Statistics i Less than the number of batteries N at time t3, when N is less than or equal to m% of the number of batteries in the battery pack, it is considered abnormal; time t3 is 20% of time t2, and the minimum is 1 hour, and m is 50.

[0017] A battery abnormality detection system in a static state, comprising a battery detection module, a battery state judgment module, a battery state timing module, a voltage analysis module, a voltage change rate module and a battery abnormality judgment module;

[0018] The battery detection module is used to collect the voltage and current of each battery in the series battery pack in real time;

[0019] The battery status judgment module is used to judge whether the battery is in a static state; the battery status timing module is used to time the static state;

[0020] The voltage analysis module is used to obtain the open circuit voltage and SOC of each battery in the static state at time t1, and to obtain the voltage of each i-th battery except the k-th battery. The open circuit voltage of the battery when n changes;

[0021] The voltage change rate module is used to set the SOC change rate n and calculate the OCV change rate α of each battery i ;

[0022] The battery abnormality judgment module is used to judge whether the battery is abnormal.

[0023] In summary, the advantage of the present invention is that it solves the problems existing in the above-mentioned prior art and provides a method for detecting battery abnormalities in a static state. The method is based on the voltage distribution at different times and combines capacity analysis to solve the fault diagnosis of problems such as micro-short circuits in individual batteries in a series battery pack. The method is easy to implement and convenient for engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 : The battery abnormality detection process and the relationship between the modules involved. DETAILED DESCRIPTION

[0025] The specific implementation modes of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0026] Example 1

[0027] A method for detecting abnormality of a battery in a static state comprises the following steps in sequence:

[0028] S1, collects the voltage and current of each battery in the series battery pack in real time through the battery detection module;

[0029] S2, determining whether the battery is in a static state by means of a battery state determination module, and timing the static state by means of a battery state timing module;

[0030] Preferably, when the current is less than or equal to the current acquisition error, it is in the static state.

[0031] S3, through the voltage analysis module, obtain the open circuit voltage (OCV) and SOC of each battery at the static state t1. The SOC of the i-th battery at t1 is recorded as The open circuit voltage of the battery is recorded as OCV i t1 ,SOC is a percentage data not exceeding 100%;

[0032] Preferably, a relationship curve between the battery open circuit voltage and SOC is stored in the voltage analysis module.

[0033] Preferably, time t1 is the time for the open circuit voltage of the battery to stabilize after standing still, which is generally 4 hours.

[0034] Table 1: Relationship curve between battery open circuit voltage and SOC

[0035] SOC OCV SOC OCV 0％ 3.254 55％ 3.710 5％ 3.402 60％ 3.743 10％ 3.479 65％ 3.778 15％ 3.513 70％ 3.820 20％ 3.550 75％ 3.874 25％ 3.577 80％ 3.922 30％ 3.600 85％ 3.973 35％ 3.621 90％ 4.025 40％ 3.641 95％ 4.084 45％ 3.659 100％ 4.146 50％ 3.680

[0036] Example 1: If there are the following 5 batteries with open circuit voltage OCV at time t1, their SOC data can be obtained through Table 1, as shown in Table 2 below.

[0037] Table 2: Relationship between open circuit voltage and SOC of a battery with 5 cells at time t1

[0038] Battery ID 1 2 3 4 5 OCV 3.705 3.710 3.700 3.690 3.695 SOC 54.2 55.0 53.3 51.7 52.5

[0039] S4, through the voltage change rate module, set the SOC change rate n, when the kth battery reaches At this time, the voltage of each battery is recorded as OCV i t1+t2 , calculate the OCV change rate of each battery;

[0040]

[0041] Preferably, the SOC change rate n is 1%;

[0042] Example 2: After a period of time t2 (10 hours), the open circuit voltage of the second battery corresponds to 55% of the SOC First change to 54% The battery open circuit voltage is 3.710 Change to 3.704

[0043] Other battery changes are shown in Table 3, and α is calculated i

[0044] Table 3: Relationship between open circuit voltage and SOC of a battery at t1 and t2 for 5 cells

[0045]

[0046] S5, through the voltage analysis module, obtain the voltage of each i-th battery except the k-th battery The open circuit voltage of the battery when changing n is recorded as OCV i t1+t2+t3

[0047] Preferably, the SOC change rate n is 1%;

[0048] Example 3: After a period of time t3, when all batteries except the second battery After a 1% change, the OCV i t1+t2+t3 and See Table 4.

[0049] Table 4: Relationship between open circuit voltage and SOC of a battery at t1, t2, and t3 for 5 cells

[0050]

[0051] S6, through the battery abnormality judgment module, calculate the OCV of each i-th battery i t1+t2 Change to OCV i t1+t2+t3 Time

[0052] Statistics i The number of batteries N at time t3 is less than or equal to t3, and when N is less than or equal to m% of the number of batteries in the battery pack, it is considered abnormal.

[0053] Preferably, time t3 is 20% of time t2 and is at least 1 hour.

[0054] Preferably, m is 50.

[0055] Example 4: After a period of time t3, when all batteries except the second battery After a 1% change, T i The calculation is shown in Table 5. After statistical T i The number of batteries N at time t3 (20% of time t2, i.e. 2 hours) is 2. When N (i.e. 2) is less than or equal to m% (i.e. 40%) of the number of batteries in the battery pack (a total of 5 batteries) and is less than 50%, it is determined that the two batteries are abnormal.

[0056] Table 5: A 5-section T i Calculate data

[0057]

[0058] Example 2

[0059] A battery abnormality detection system in a static state comprises a battery detection module, a battery state judgment module, a battery state timing module, a voltage analysis module, a voltage change rate module and a battery abnormality judgment module.

[0060] The battery detection module is used to collect the voltage and current of each battery in the series battery pack in real time; the battery status judgment module is used to judge whether the battery is in a static state; the battery status timing module is used to time the static state; the voltage analysis module is used to obtain the open circuit voltage and SOC of each battery at the static state t1, and to obtain the SOC of each battery except the kth battery. The battery open circuit voltage when changing n; the voltage change rate module is used to set the SOC change rate n and calculate the OCV change rate α of each battery i The battery abnormality judgment module is used to judge whether the battery is abnormal.

Claims

1. A method for detecting abnormality of a battery in a static state, characterized in that: Follow these steps in order: S1, real-time acquisition of the voltage and current of each battery in the series battery pack; S2, determining whether the battery is in a static state, and timing the static state; S3, obtain the open circuit voltage and SOC of each battery at the static state t1, and the SOC of the i-th battery at t1 is recorded as SOC i t1 , the battery open circuit voltage is recorded as OCV i t1 , SOC is a percentage data not exceeding 100%; S4, set the SOC change rate n, when the kth battery reaches At this time, the voltage of each battery is recorded as OCV i t1+t2 , calculate the OCV change rate α of each battery i ; ； S5, obtain the SOC of each i-th battery except the k-th battery i t1 The open circuit voltage of the battery when changing n is recorded as OCV i t1 +t2+t3 ; S6, determine whether the battery is abnormal: calculate the OCV of each i-th battery i t1+t2 Change to OCV i t1+t2+t3 Time T i , ； Statistics i Less than the number of batteries N at time t3, when N is less than or equal to m% of the number of batteries in the battery pack, it is considered abnormal.

2. The method for detecting abnormality of a battery in a static state according to claim 1, characterized in that: In S2, the static state is that the current is less than or equal to the current acquisition error.

3. The method for detecting abnormality of a battery in a static state according to claim 1, characterized in that: In S3, a relationship curve between the battery open circuit voltage and the SOC is stored in the voltage analysis module.

4. The method for detecting abnormality of a battery in a static state according to claim 1, characterized in that: In S3, time t1 is the time when the open circuit voltage of the battery is stabilized after being left to stand.

5. The method for detecting abnormality of a battery in a static state according to claim 1, characterized in that: The SOC change rate n is 1%.

6. The method for detecting abnormality of a battery in a static state according to claim 5, characterized in that: The time t3 is 20% of the time t2 and the minimum is 1 hour.

7. The method for detecting abnormality of a battery in a static state according to claim 5, characterized in that: m is 50.

8. A detection system for abnormal battery in a static state, the detection system adopts the method according to any one of claims 1 to 7, characterized in that: It includes a battery detection module, a battery status judgment module, a battery status timing module, a voltage analysis module, a voltage change rate module and a battery abnormality judgment module; The battery detection module is used to collect the voltage and current of each battery in the series battery pack in real time; The battery status judgment module is used to judge whether the battery is in a static state; The battery status timing module is used to time the static state; The voltage analysis module is used to obtain the open circuit voltage and SOC of each battery in the static state at time t1, and to obtain the SOC of each i-th battery except the k-th battery. i t1 The open circuit voltage of the battery when n changes; The voltage change rate module is used to set the SOC change rate n and calculate the OCV change rate α of each battery i ; The battery abnormality judgment module is used to judge whether the battery is abnormal.

Images