Lithium ion battery micro short circuit detection method and system

Abstract

The invention discloses a lithium ion battery micro short circuit detection method and system. The method comprises the following steps: through a battery management system, collecting equalization start time and equalization end time of a to-be-tested battery and voltage of the to-be-tested battery in a first duration; through the battery remote monitoring system, according to the equalization starting time, the equalization ending time, the voltage, a preset equalization resistor resistance value, the capacity of the to-be-measured battery during equalization and a second duration, calculating a self-discharge rate coefficient of the to-be-measured battery after each equalization ending; generating a self-discharge evolution curve through the battery remote monitoring system according to the self-discharge rate coefficient and the second duration; and through a battery remote monitoring system, whether the to-be-detected battery has a micro-short circuit risk is identified according to the self-discharge evolution curve. According to the method, passive equalization data is used for micro short circuit risk detection, the nonlinear influence of battery parameters is eliminated, the linearity of the self-discharge rate coefficient is good, the result reliability is high, meanwhile, big data accumulation is achieved, and the accuracy of micro short circuit detection is continuously improved.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a method and system for detecting a lithium-ion battery micro-short circuit. Background Art

[0002] Lithium-ion batteries have the characteristics of high energy density and long cycle life, and are widely used in 3C consumer electronics, electric vehicles, and energy storage systems. However, since lithium-ion batteries use organic solvents, once the electrical energy stored in the battery is converted into heat out of control, it will cause the lithium-ion battery to catch fire or even explode, causing safety accidents. In recent years, stories of laptop fires, mobile phone fires, vehicle fires, and energy storage power station fires have been reported from time to time, attracting widespread attention and research. There is a gradual evolution process for some lithium-ion batteries to catch fire. During the manufacturing and use process, metal particles are mixed in, lithium precipitation, copper precipitation, etc., causing micro-puncture of the diaphragm, forming a micro-short circuit, allowing current to flow through the diaphragm for self-discharge. After the evolution of the micro-short circuit, the leakage current increases. If a vicious cycle of micro-short circuit, temperature rise, and short-circuit current increase is caused, thermal runaway will be formed. Thermal runaway is the main failure mode of lithium-ion battery fire and explosion. Identifying micro-short circuits and avoiding thermal runaway in advance are of great significance to ensure the safe operation of lithium-ion batteries and avoid safety accidents such as fire and explosion.

[0003] The existing detection method of lithium-ion battery micro-short circuit has a large error and a low recognition rate due to the nonlinearity of the battery, that is, the randomness of the performance of the same battery cell under the same conditions. Summary of the invention

[0004] The present invention provides a method and system for detecting a lithium ion battery micro-short circuit, so as to solve the problem of low recognition rate in the prior art.

[0005] According to one aspect of the present invention, a method for detecting a micro-short circuit of a lithium-ion battery is provided, which is used for a detection system for a micro-short circuit of a lithium-ion battery. The detection system for a micro-short circuit of a lithium-ion battery comprises a battery, a battery management system and a battery remote monitoring system, wherein the battery, the battery management system and the battery remote monitoring system are connected in sequence; the method for detecting a micro-short circuit of a lithium-ion battery comprises:

[0006] By means of the battery management system, collecting the equalization start time, the equalization end time and the voltage of the battery under test within a first time period of the battery under test, wherein the first time period is the time interval between the equalization start time and the equalization end time;

[0007] By means of the battery remote monitoring system, the self-discharge rate coefficient of the battery to be tested after each equalization is calculated according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second time length, wherein the second time length is the time length from the end of the nth equalization to the end of the n-1th equalization, where n is a positive integer greater than or equal to 2;

[0008] Generate a self-discharge evolution curve according to the self-discharge rate coefficient and the second time period through the battery remote monitoring system;

[0009] Through the battery remote monitoring system, it is identified whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve.

[0010] Optionally, the calculating, by the battery remote monitoring system, according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second duration, of the self-discharge rate coefficient of the battery to be tested after each equalization is completed includes:

[0011] By means of the battery remote monitoring system, the amount of electricity of each equalization of the battery to be tested is calculated according to the equalization start time, the equalization end time, the i-th preset time interval, the voltage of the battery to be tested at the i-th preset time interval, and the preset equalization resistance value, wherein the i-th preset time interval is included in the time interval from the equalization start time to the equalization end time, and i is a positive integer greater than or equal to 1;

[0012] The battery remote monitoring system calculates the self-discharge rate coefficient of the battery to be tested after each equalization according to the electric quantity of the nth equalization, the capacity of the battery to be tested during the nth equalization, and the second time period.

[0013] Optionally, the battery remote monitoring system calculates the amount of electricity of each equalization of the battery to be tested according to the equalization start time, the equalization end time, the i-th preset time interval, the voltage of the battery to be tested at each i-th preset time interval, and a preset equalization resistor value, including:

[0014] The following formula is used to calculate the amount of electricity that the battery to be tested balances each time:

[0015]

[0016] In the formula, Q is the amount of electricity that the battery to be tested is balanced each time, t 开始 is the equilibrium start time, t 停止 is the equilibrium end time, Δt iis the ith preset time interval, Vi is the voltage of the battery to be tested in the ith preset time interval, and R is the preset equalizing resistor value.

[0017] Optionally, the calculating, by the battery remote monitoring system, a self-discharge rate coefficient of the battery to be tested after each equalization according to the power of the nth equalization, the capacity of the battery to be tested during the nth equalization, and the second time period, includes:

[0018] The self-discharge rate coefficient of the battery under test after each equalization is calculated using the following formula:

[0019]

[0020] Where η n Q is the self-discharge rate coefficient of the battery under test after each equalization. n is the amount of electricity balanced for the nth time, C n is the capacity of the battery under test during the nth balancing, T n is the second duration, that is, the duration from the end of the nth equalization to the end of the n-1th equalization.

[0021] Optionally, generating a self-discharge evolution curve according to the self-discharge rate coefficient and the second time period through the battery remote monitoring system includes:

[0022] The self-discharge rate coefficient and the second time length calculated each time are stored through the battery remote monitoring system, and a self-discharge evolution curve is generated with the self-discharge rate coefficient as the vertical axis and the second time length as the horizontal axis.

[0023] Optionally, identifying, by the battery remote monitoring system, whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve includes:

[0024] When the self-discharge rate of the self-discharge evolution curve does not meet the preset self-discharge rate standard value, it is determined that the battery to be tested has a micro-short circuit risk;

[0025] Alternatively, when the self-discharge rate growth slope of the self-discharge evolution curve does not meet the preset slope standard value, it is determined that the battery to be tested has a micro-short circuit risk;

[0026] Alternatively, when the self-discharge evolution curve shows that the self-discharge rate approaches an upper limit of a preset self-discharge rate standard value, it is determined that the battery to be tested has a micro-short circuit risk.

[0027] Optionally, after identifying whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve through the battery remote monitoring system, the method further includes:

[0028] According to the preset warning time, when the self-discharge rate is greater than or equal to the upper limit of the preset self-discharge rate standard value for the first time, a micro-short circuit alarm is issued.

[0029] Optionally, the lithium-ion battery micro-short circuit detection system further includes a battery remote transmission system, and the battery remote transmission system is connected between the battery management system and the battery remote monitoring system;

[0030] Before calculating the self-discharge rate coefficient of the battery to be tested after each equalization is completed by the battery remote monitoring system according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second time period, the method further includes:

[0031] The balancing start time, the balancing end time, and the voltage are transmitted to the battery remote monitoring system through the battery remote transmission system.

[0032] According to another aspect of the present invention, there is provided a lithium-ion battery micro-short circuit detection system, comprising a battery, a battery management system and a battery remote monitoring system, wherein the battery, the battery management system and the battery remote monitoring system are connected in sequence;

[0033] The battery management system is used to collect the equalization start time, the equalization end time of the battery to be tested, and the voltage of the battery to be tested within a first time period, where the first time period is the time interval between the equalization start time and the equalization end time;

[0034] The battery remote monitoring system is used to calculate the self-discharge rate coefficient of the battery to be tested after each equalization according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and a second time length, wherein the second time length is the time length from the end of the nth equalization to the end of the n-1th equalization, where n is a positive integer greater than or equal to 2;

[0035] The battery remote monitoring system is further used to generate a self-discharge evolution curve according to the self-discharge rate coefficient and the second time length;

[0036] The battery remote monitoring system is also used to identify whether the battery to be tested has a micro-short circuit risk based on the self-discharge evolution curve.

[0037] Optionally, the lithium-ion battery micro-short circuit detection system further includes a battery remote transmission system, and the battery remote transmission system is connected between the battery management system and the battery remote monitoring system;

[0038] The battery remote transmission system is used to transmit the balancing start time, the balancing end time, and the voltage to the battery remote monitoring system.

[0039] The embodiment of the present invention provides a method and system for detecting micro-short circuits of lithium-ion batteries. The method includes: collecting the equalization start time, equalization end time and voltage of the battery to be tested within a first time period through a battery management system; calculating the self-discharge rate coefficient of the battery to be tested after each equalization according to the equalization start time, equalization end time, voltage, preset equalization resistance value, capacity of the battery to be tested during equalization and the second time period through a battery remote monitoring system; generating a self-discharge evolution curve according to the self-discharge rate coefficient and the second time period through a battery remote monitoring system; identifying whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve through a battery remote monitoring system. The technical solution provided by the embodiment of the present invention, the battery remote monitoring system includes a big data processing platform, which can store the equalization data of each battery for a long time, track the evolution of micro-short circuits of the battery cells in real time, reduce the occurrence rate of safety accidents, and has strong storage capacity and computing power, uses passive equalization data for micro-short circuit risk detection, eliminates the influence of nonlinear battery parameters, makes the self-discharge rate coefficient linear, and has high credibility, while realizing big data accumulation, continuously improving the reliability and recognition rate of micro-short circuit detection.

[0040] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 A flow chart of a method for detecting a micro-short circuit of a lithium-ion battery provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of the structure of a lithium-ion battery micro-short circuit detection system provided by an embodiment of the present invention;

[0044] Figure 3 A schematic structural diagram of another lithium-ion battery micro-short circuit detection system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0046] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0047] Figure 1 A flow chart of a method for detecting a micro-short circuit of a lithium-ion battery provided in an embodiment of the present invention. This embodiment can be applied to the micro-short circuit detection of a lithium-ion battery. The method for detecting a micro-short circuit of a lithium-ion battery can be executed by a detection system for a micro-short circuit of a lithium-ion battery. Figure 2 A schematic diagram of a lithium-ion battery micro-short circuit detection system provided by an embodiment of the present invention, see Figure 2 The lithium-ion battery micro-short circuit detection system includes a battery 210, a battery management system 220 and a battery remote monitoring system 230, and the battery 210, the battery management system 220 and the battery remote monitoring system 230 are connected in sequence; see Figure 1 , the lithium-ion battery micro-short circuit detection method includes:

[0048] S110 , collecting, through a battery management system, a balancing start time, a balancing end time, and a voltage of the battery to be tested within a first time period of the battery to be tested.

[0049] The first duration is the time interval between the start time of the balance and the end time of the balance. Figure 2 The battery 210 may be a battery cell, or may be a plurality of battery cells connected in parallel and then in series. The embodiment of the present invention is illustrated by taking a plurality of battery cells connected in parallel and then in series as an example; the battery management system 220 includes a passive balancing system, and the passive balancing system includes Figure 2Each battery cell is provided with a balancing resistor and a balancing switch, and may also include Figure 3 Any of the controllable balancing resistors plus balancing switches shown, Figure 3 A structural schematic diagram of another lithium-ion battery micro-short circuit detection system provided in an embodiment of the present invention. When the full-charge voltage difference of the battery to be tested is greater than the first voltage difference threshold, the balancing switch is closed and the battery to be tested starts balancing. When the full-charge voltage difference of the battery to be tested is less than the second voltage difference threshold, the balancing switch is disconnected and the battery to be tested stops balancing. Then, the balancing start time and the balancing end time of the battery to be tested are respectively the time when the full-charge voltage difference of the battery to be tested is greater than the first voltage difference threshold, and the time when the full-charge voltage difference of the battery to be tested is less than the second voltage difference threshold. The first voltage difference threshold is greater than the second voltage difference threshold. Exemplarily, the embodiment of the present invention is described by taking the first voltage difference threshold of 80mv and the second voltage difference threshold of 30mv as an example. When the full-charge voltage difference of the battery to be tested is greater than 80mv, the balancing switch is closed and the battery to be tested starts to be balanced. When the full-charge voltage difference of the battery to be tested is less than 30mv, the balancing switch is opened and the battery to be tested stops balancing. Then the balancing start time and balancing end time of the battery to be tested are respectively the time when the full-charge voltage difference of the battery to be tested is greater than 80mv and the time when the full-charge voltage difference of the battery to be tested is less than 30mv.

[0050] Specifically, the battery management system is used to collect the equalization start time and the equalization end time of the battery to be tested, and the battery management system is used to collect the voltage of the battery to be tested within a first time period based on a preset time interval; when the battery to be tested is in a stationary state, the preset time interval can be set to 10 minutes; when the battery to be tested is in a charging state, the preset time interval can be set to 5s; when the battery to be tested is in a fault state, the preset time interval can be set to 0.1s, and the present invention does not limit this.

[0051] S120, calculating the self-discharge rate coefficient of the battery to be tested after each equalization is completed through the battery remote monitoring system according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second time period.

[0052] The second duration is the duration from the end of the nth balancing to the end of the n-1th balancing, and n is a positive integer greater than or equal to 2. The battery remote monitoring system includes a big data processing platform and an artificial intelligence model.

[0053] Specifically, the self-discharge rate coefficient is an important parameter that reflects the self-discharge characteristics of the battery. Self-discharge refers to the phenomenon that when the battery is not in use, it will consume electrical energy due to internal chemical reactions and other reasons, resulting in a gradual decrease in battery power. The self-discharge rate coefficient of the battery to be tested is calculated after each equalization by the equalization start time, equalization end time, voltage, preset equalization resistance value, and capacity of the battery to be tested during equalization, as well as the second duration. This coefficient can help us understand the speed of battery self-discharge, and provide an important basis for battery performance evaluation, life prediction, and subsequent maintenance and use. For example, if the self-discharge rate coefficient is high, it means that the battery self-discharges quickly and may require more frequent charging or other maintenance measures. On the contrary, it indicates that the battery has good self-discharge performance and can maintain a high level of power storage for a certain period of time.

[0054] S130. Generate a self-discharge evolution curve according to the self-discharge rate coefficient and the second time period through the battery remote monitoring system.

[0055] Specifically, based on the self-discharge rate coefficient and the second duration, the data integration and analysis function of the battery remote monitoring system is used to sort out the self-discharge rate coefficients corresponding to different times in chronological order. With time (second duration) as the horizontal axis and the self-discharge rate coefficient as the vertical axis, the data of each time point and its corresponding self-discharge rate coefficient are marked on the coordinate plane, and then a curve that can intuitively reflect the trend of battery self-discharge over time is formed by connecting lines, etc., that is, the self-discharge evolution curve. This curve can clearly show how the degree of battery self-discharge changes over time. For example, the rise of the curve indicates that the self-discharge is getting more and more serious, and the stability of the curve means that the self-discharge is relatively stable. With the help of such a curve, relevant personnel can better grasp the self-discharge law of the battery, and then evaluate the performance and status of the battery, and can also provide an intuitive and powerful reference for subsequent battery use, maintenance and life prediction.

[0056] S140. Using the battery remote monitoring system, identify whether the battery to be tested has a micro-short circuit risk based on the self-discharge evolution curve.

[0057] Specifically, according to the self-discharge evolution curve, it is possible to identify abnormal fluctuations in the self-discharge rate coefficient, that is, the self-discharge evolution curve is not smooth enough, and the self-discharge rate coefficient suddenly becomes large or small, indicating that the micro-short circuit evolution intensity is large and the risk is high; according to the self-discharge evolution curve, it is also possible to identify that the self-discharge rate coefficient has a high growth slope, that is, the growth slope of the self-discharge rate coefficient exceeds the standard slope, causing the self-discharge evolution curve to deviate from the standard self-discharge evolution curve, indicating that the internal short circuit is expanding rapidly; according to the self-discharge evolution curve, it is also possible to identify that the self-discharge rate coefficient is close to the qualified maximum value, indicating that the micro-short circuit density is high. The above three categories are all situations where there is a risk of micro-short circuit.

[0058] The technical solution provided by the embodiment of the present invention is that the battery remote monitoring system includes a big data processing platform, which can store the balancing data of each battery for a long time, track the evolution of micro-short circuits of battery cells in real time, and reduce the occurrence rate of safety accidents. It has strong storage and computing capabilities, uses passive balancing data to perform micro-short circuit risk detection, eliminates the influence of nonlinear battery parameters, and makes the linearity of the self-discharge rate coefficient good, the result credibility is high, and at the same time realizes big data accumulation, and continuously improves the reliability and recognition rate of micro-short circuit detection.

[0059] Based on the above embodiment, optionally, S120 includes:

[0060] S121, calculating the amount of electricity of each equalization of the battery under test through the battery remote monitoring system according to the equalization start time, the equalization end time, the ith preset time interval, the voltage of the battery under test at the ith preset time interval, and the preset equalization resistor value.

[0061] The i-th preset time interval is included in the time interval from the equalization start time to the equalization end time, and i is a positive integer greater than or equal to 1.

[0062] Specifically, the following formula is used to calculate the amount of electricity that the battery to be tested balances each time:

[0063]

[0064] In the formula, Q is the amount of electricity that the battery to be tested is balanced each time, t 开始 is the equilibrium start time, t 停止 is the equilibrium end time, Δt i is the ith preset time interval, Vi is the voltage of the battery to be tested in the ith preset time interval, and R is the preset equalizing resistor value.

[0065] S122, calculating, by the battery remote monitoring system, a self-discharge rate coefficient of the battery to be tested after each equalization according to the power of the nth equalization, the capacity of the battery to be tested during the nth equalization, and the second time period.

[0066] Specifically, the following formula is used to calculate the self-discharge rate coefficient of the battery under test after each equalization:

[0067]

[0068] Where η n Q is the self-discharge rate coefficient of the battery under test after each equalization. n is the amount of electricity balanced for the nth time, C n is the capacity of the battery under test during the nth balancing, T n is the second duration, that is, the duration from the end of the nth equalization to the end of the n-1th equalization.

[0069] Based on the above embodiment, optionally, S130 includes:

[0070] S131. The self-discharge rate coefficient and the second time length calculated each time are stored through the battery remote monitoring system, and a self-discharge evolution curve is generated with the self-discharge rate coefficient as the vertical axis and the second time length as the horizontal axis.

[0071] Based on the above embodiment, optionally, S140 includes:

[0072] S141. When the self-discharge rate of the self-discharge evolution curve does not meet the preset self-discharge rate standard value, it is determined that the battery to be tested has a micro-short circuit risk.

[0073] Among them, the preset self-discharge rate standard value can be preset.

[0074] or,

[0075] S142. When the self-discharge rate growth slope of the self-discharge evolution curve does not meet the preset slope standard value, it is determined that the battery to be tested has a micro-short circuit risk.

[0076] Among them, the preset slope standard value can be preset.

[0077] or,

[0078] S143. When the self-discharge rate in the self-discharge evolution curve approaches the upper limit of the preset self-discharge rate standard value, it is determined that the battery to be tested has a micro-short circuit risk.

[0079] Based on the above embodiment, optionally, after S140, the method further includes:

[0080] S150. According to the preset warning time, when the self-discharge rate is greater than or equal to the upper limit of the preset self-discharge rate standard value for the first time, a micro-short circuit alarm is issued.

[0081] Among them, the preset warning time can be pre-set according to user needs, which can be 3 months or 1 year, and the present invention is not limited to this.

[0082] Based on the above embodiment, optionally, continue to refer to Figure 2 The lithium-ion battery micro-short circuit detection system further includes a battery remote transmission system 240, and the battery remote transmission system 240 is connected between the battery management system 220 and the battery remote monitoring system 230; before S120, it also includes:

[0083] S160, transmitting the balancing start time, balancing end time, and voltage to the battery remote monitoring system through the battery remote transmission system.

[0084] Specifically, the battery remote transmission system Tbox transmits the balancing start time, balancing end time, and voltage to the battery remote monitoring system according to the communication protocol.

[0085] Continue to see Figure 2 , an embodiment of the present invention provides a lithium-ion battery micro-short circuit detection system, including a battery 210, a battery management system 220 and a battery remote monitoring system 230, the battery 210, the battery management system 220 and the battery remote monitoring system 230 are connected in sequence;

[0086] The battery management system 220 is used to collect the equalization start time, the equalization end time and the voltage of the battery under test within a first time period. The first time period is the time interval between the equalization start time and the equalization end time. The specific collection process can be referred to step S110 in the above embodiment, which will not be repeated here.

[0087] The battery remote monitoring system 230 is used to calculate the self-discharge rate coefficient of the battery to be tested after each equalization according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second time length, wherein the second time length is the time length from the end of the nth equalization to the end of the n-1th equalization, and n is a positive integer greater than or equal to 2. Specifically refer to step S120 in the above real-time, step S120 specifically includes step S121 and step S122 in the above embodiment, which will not be repeated here.

[0088] The battery remote monitoring system 230 is also used to generate a self-discharge evolution curve according to the self-discharge rate coefficient and the second time length, see step S130 in the above embodiment for details. Step S130 specifically includes step S131 in the above embodiment, which will not be repeated here.

[0089] The battery remote monitoring system 230 is also used to identify whether the battery under test has a micro-short circuit risk according to the self-discharge evolution curve, see step S140 in the above embodiment for details. Step S140 includes step S141, step S142 and step S143 in the above embodiment. Optionally, the battery remote monitoring system 230 is also used for step S150.

[0090] Optional, continue to see Figure 2 The lithium-ion battery micro-short circuit detection system also includes a battery remote transmission system 240 , and the battery remote transmission system 240 is connected between the battery management system 220 and the battery remote monitoring system 230 .

[0091] The battery remote transmission system 240 is used to transmit the balancing start time, balancing end time, and voltage to the battery remote monitoring system. For details, please refer to step S160 in the above embodiment, which will not be described in detail here.

[0092] The lithium-ion battery micro-short circuit detection system provided in the embodiment of the present invention can execute the lithium-ion battery micro-short circuit detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0093] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0094] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for detecting a micro short circuit of a lithium-ion battery, characterized in that: A detection system for a lithium-ion battery micro-short circuit, the detection system for a lithium-ion battery micro-short circuit comprising a battery, a battery management system and a battery remote monitoring system, the battery, the battery management system and the battery remote monitoring system are connected in sequence; the detection method for a lithium-ion battery micro-short circuit comprises: By means of the battery management system, collecting the equalization start time, the equalization end time and the voltage of the battery under test within a first time period of the battery under test, wherein the first time period is the time interval between the equalization start time and the equalization end time; By means of the battery remote monitoring system, the self-discharge rate coefficient of the battery to be tested after each equalization is calculated according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second time length, wherein the second time length is the time length from the end of the nth equalization to the end of the n-1th equalization, where n is a positive integer greater than or equal to 2; Generate a self-discharge evolution curve according to the self-discharge rate coefficient and the second time period through the battery remote monitoring system; Through the battery remote monitoring system, it is identified whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve.

2. The detection method according to claim 1, characterized in that: The calculating, by the battery remote monitoring system, according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery under test during equalization, and the second duration, of the self-discharge rate coefficient of the battery under test after each equalization is completed includes: By means of the battery remote monitoring system, the amount of electricity of each equalization of the battery to be tested is calculated according to the equalization start time, the equalization end time, the i-th preset time interval, the voltage of the battery to be tested at the i-th preset time interval, and the preset equalization resistance value, wherein the i-th preset time interval is included in the time interval from the equalization start time to the equalization end time, and i is a positive integer greater than or equal to 1; The battery remote monitoring system calculates the self-discharge rate coefficient of the battery to be tested after each equalization according to the electric quantity of the nth equalization, the capacity of the battery to be tested during the nth equalization, and the second time period.

3. The detection method according to claim 2, characterized in that: The battery remote monitoring system calculates the amount of electricity of the battery to be tested for each equalization according to the equalization start time, the equalization end time, the i-th preset time interval, the voltage of the battery to be tested at each i-th preset time interval, and the preset equalization resistor value, including: The following formula is used to calculate the amount of electricity that the battery to be tested balances each time: In the formula, Q is the amount of electricity that the battery to be tested is balanced each time, t 开始 is the equilibrium start time, t 停止 is the equilibrium end time, Δt i is the ith preset time interval, Vi is the voltage of the battery to be tested in the ith preset time interval, and R is the preset equalizing resistor value.

4. The detection method according to claim 2, characterized in that: The method of calculating the self-discharge rate coefficient of the battery to be tested after each equalization is completed by the battery remote monitoring system according to the power of the nth equalization, the capacity of the battery to be tested during the nth equalization, and the second time period includes: The self-discharge rate coefficient of the battery under test after each equalization is calculated using the following formula: Where η n Q is the self-discharge rate coefficient of the battery under test after each equalization. n is the amount of electricity balanced for the nth time, C n is the capacity of the battery under test during the nth balancing, T n is the second duration, that is, the duration from the end of the nth equalization to the end of the n-1th equalization.

5. The detection method according to claim 1, characterized in that: The generating, by the battery remote monitoring system, a self-discharge evolution curve according to the self-discharge rate coefficient and the second duration comprises: The self-discharge rate coefficient and the second time length calculated each time are stored through the battery remote monitoring system, and a self-discharge evolution curve is generated with the self-discharge rate coefficient as the vertical axis and the second time length as the horizontal axis.

6. The detection method according to claim 1, characterized in that: The identifying, by the battery remote monitoring system, whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve comprises: When the self-discharge rate of the self-discharge evolution curve does not meet the preset self-discharge rate standard value, it is determined that the battery to be tested has a micro-short circuit risk; Alternatively, when the self-discharge rate growth slope of the self-discharge evolution curve does not meet the preset slope standard value, it is determined that the battery to be tested has a micro-short circuit risk; Alternatively, when the self-discharge evolution curve shows that the self-discharge rate approaches an upper limit of a preset self-discharge rate standard value, it is determined that the battery to be tested has a micro-short circuit risk.

7. The detection method according to claim 1, characterized in that: After identifying whether the battery to be tested has a micro-short circuit risk according to the self-discharge evolution curve through the battery remote monitoring system, the method further includes: According to the preset warning time, when the self-discharge rate is greater than or equal to the upper limit of the preset self-discharge rate standard value for the first time, a micro-short circuit alarm is issued.

8. The detection method according to claim 1, characterized in that: The lithium-ion battery micro-short circuit detection system further includes a battery remote transmission system, and the battery remote transmission system is connected between the battery management system and the battery remote monitoring system; Before calculating the self-discharge rate coefficient of the battery to be tested after each equalization is completed by the battery remote monitoring system according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and the second time period, the method further includes: The balancing start time, the balancing end time, and the voltage are transmitted to the battery remote monitoring system through the battery remote transmission system.

9. A lithium-ion battery micro-short circuit detection system, characterized in that: It includes a battery, a battery management system and a battery remote monitoring system, wherein the battery, the battery management system and the battery remote monitoring system are connected in sequence; The battery management system is used to collect the equalization start time, the equalization end time of the battery to be tested, and the voltage of the battery to be tested within a first time period, where the first time period is the time interval between the equalization start time and the equalization end time; The battery remote monitoring system is used to calculate the self-discharge rate coefficient of the battery to be tested after each equalization according to the equalization start time, the equalization end time, the voltage, the preset equalization resistance value, the capacity of the battery to be tested during equalization, and a second time length, wherein the second time length is the time length from the end of the nth equalization to the end of the n-1th equalization, where n is a positive integer greater than or equal to 2; The battery remote monitoring system is further used to generate a self-discharge evolution curve according to the self-discharge rate coefficient and the second time length; The battery remote monitoring system is also used to identify whether the battery to be tested has a micro-short circuit risk based on the self-discharge evolution curve.

10. The detection system according to claim 9, characterized in that: It also includes a battery remote transmission system, which is connected between the battery management system and the battery remote monitoring system; The battery remote transmission system is used to transmit the balancing start time, the balancing end time, and the voltage to the battery remote monitoring system.

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