CN110187225B - Method and system for detecting abnormal short-circuit voltage and current in lithium battery - Google Patents
Method and system for detecting abnormal short-circuit voltage and current in lithium battery Download PDFInfo
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- CN110187225B CN110187225B CN201910523515.2A CN201910523515A CN110187225B CN 110187225 B CN110187225 B CN 110187225B CN 201910523515 A CN201910523515 A CN 201910523515A CN 110187225 B CN110187225 B CN 110187225B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
Abstract
The invention provides a method and a system for detecting the abnormality of short-circuit voltage and current in a lithium battery, which comprises the following steps: s1: charging and discharging a lithium battery and determining that the lithium battery enters a charging and discharging state; s2: synchronously acquiring at least one of voltage data at two ends of the lithium battery and current data passing through the lithium battery in real time; s3: judging whether the voltage data and the current data are abnormal or not; and stopping the automatic production when the voltage and/or the current are abnormal. The thermal runaway in the formation and partial capacity process caused by short circuit in the lithium battery can be effectively avoided, and the safety of automatic production of the lithium battery is improved.
Description
Technical Field
The invention relates to the technical field of lithium batteries, in particular to a method and a system for detecting abnormal short-circuit voltage and current in a lithium battery.
Background
In the latter-stage automatic production process (formation, capacity grading, standing, DCIR detection, etc.) of lithium batteries, the main causes of lithium battery heating and even explosion can be classified into the following two categories: 1. the SEI of the solid electrolyte interface film of the lithium battery is decomposed, falls off and even reacts reversely due to overcharge or overdischarge, and thermal runaway is finally caused along with violent reactions such as heating, gas and the like. Due to the fact that the component capacitance and detection system has a protection strategy specially aiming at overcharge and overdischarge, thermal runaway caused by the reason can be avoided. 2. Thermal runaway of lithium batteries due to short circuits. The short circuit is divided into an external short circuit and an internal short circuit, and the double-voltage monitoring system in the charging and discharging system can effectively detect and prevent the external short circuit, so that effective early warning and control are mainly needed for the internal short circuit of the lithium battery at present, and a thermal runaway state caused by the internal short circuit is avoided.
Because the internal short circuit is difficult to directly monitor, a battery internal short circuit detection way is lacked in the prior art at present.
Disclosure of Invention
The invention provides a method and a system for detecting abnormal short-circuit voltage and current in a lithium battery, aiming at solving the existing problems.
In order to solve the above problems, the technical solution adopted by the present invention is as follows:
a method for detecting the abnormality of short-circuit voltage and current in a lithium battery comprises the following steps: s1: charging and discharging a lithium battery and determining that the lithium battery enters a charging and discharging state; s2: synchronously acquiring at least one of voltage data at two ends of the lithium battery and current data passing through the lithium battery in real time, and carrying out internal short circuit index monitoring; s3: judging whether an internal short circuit index of at least one of the voltage data and the current data is abnormal; and stopping charging and discharging the lithium battery when one of the voltage data and the current data is abnormal.
Preferably, the judging whether the voltage data is abnormal includes the steps of: filtering noise of the voltage data, selecting the voltage data with an undersampling rate reaching a set value in real time, and dynamically updating the maximum recorded voltage; the internal short circuit index monitoring comprises at least one of voltage rising abnormity detection, voltage abnormity falling detection and voltage falling trend abnormity detection.
Preferably, the voltage rise abnormality detection includes: calculating real-time voltage data VnAnd a charge starting voltage VstartDifference value V ofras＝Vn-Vstart(ii) a And judging whether the difference value is smaller than a preset voltage rising threshold value or not, and if the difference value is smaller than the preset voltage rising threshold value, judging that the voltage rises abnormally.
Preferably, the voltage abnormal drop detection includes: calculating the maximum recording voltage VmaxWith real-time voltage data VnIs equal to Vmax-Vn(ii) a And judging whether the difference value exceeds a preset voltage drop threshold value or not, and if the difference value exceeds the preset voltage drop threshold value, judging that the voltage drop is abnormal.
Preferably, the voltage-falling-tendency abnormality detection includes: calculating the difference of the voltage data of the two ends of the lithium battery collected in real time: dn ═ Vn-Vn-1And obtaining the sign d of the sign of dnsng-n(ii) a Calculating whether the sum of the symbols exceeds a preset voltage descending trend threshold value or not, and recording a voltage descending trend starting point voltage V if the sum of the symbols is smaller than the preset voltage descending trend threshold valueref(ii) a Calculating the voltage drop slope: s ═ Vref-Vn) N, wherein N is the voltage undersampling rate; and judging whether the voltage falling slope exceeds a preset falling slope threshold value or not, wherein if the voltage falling slope exceeds the preset falling slope threshold value, the voltage falling trend is abnormal.
Preferably, the lithium battery is in a constant current charging, constant voltage charging or constant current discharging state, and the corresponding current abnormality is: constant current charging is abnormal, constant voltage charging is abnormal or constant current discharging is abnormal.
Preferably, the judging whether the current data is abnormal includes the steps of: filtering noise of the current data and dynamically updating the cache data; determining the state of the lithium battery and calculating the change rate of current; and comparing the change rate of the current with a preset change rate threshold of the current, and if the change rate of the current is greater than the preset change rate threshold of the current, judging that the change of the current is abnormal.
Preferably, the rate of change of the current is calculated: d ═ Cn-Cn-N+1) N, wherein CnIs real-time current data, Cn-N+1Is current data prior to time N, which is a time interval, of the real-time; the preset current change rate threshold value is T when the lithium battery is in a constant current charging state1If d is>T1If the charging is abnormal, the constant current charging is abnormal; the preset current change rate threshold value is T when the lithium battery is in a constant-voltage charging state2If d is>T2If so, the constant voltage charging is abnormal; the preset current change rate threshold value is T when the lithium battery is in a constant current discharge state3If d is>T3The constant current discharge is abnormal.
The invention also provides a system for detecting the abnormal short-circuit voltage and current in the lithium battery, which comprises the following components: the charging and discharging unit is used for charging and discharging the lithium battery; the voltage acquisition unit is used for acquiring voltage data of two ends of the lithium battery in real time; the current acquisition unit is used for acquiring current data passing through the lithium battery in real time; the processing unit is used for judging whether the voltage data and the current data are abnormal or not; and when the voltage and/or the current are abnormal, stopping charging and discharging.
The invention further provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as set forth in any of the above.
The invention has the beneficial effects that: the method comprises the steps of collecting voltage and current data of a charged and discharged lithium battery and judging whether the voltage data and the current data are abnormal or not; when the voltage and/or the current are abnormal, charging and discharging are stopped, short circuit in the lithium battery caused by abnormal voltage and current is effectively avoided, and safety of the lithium battery is improved.
In some embodiments of the invention, aiming at the characteristics that the cause of the internal short circuit is complex, the external performance is not obvious, and the voltage circuit index is not easily perceived, various performance modes of the internal short circuit are summarized, characterization parameters in each mode are formulated, and the occurrence of the internal short circuit is monitored by monitoring the characterization parameters.
Drawings
Fig. 1 is a schematic diagram of a thermal runaway early warning protection system for a lithium battery in an embodiment of the invention.
Fig. 2 is a schematic diagram of a method for detecting abnormal short-circuit voltage and current in a lithium battery according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a method for determining whether the voltage data is abnormal according to an embodiment of the present invention.
FIG. 4 is a schematic diagram of a method for detecting abnormal voltage rise according to an embodiment of the present invention.
FIG. 5 is a schematic diagram of a method for detecting abnormal voltage drop according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a method for detecting an abnormal voltage-decreasing trend in an embodiment of the present invention.
Fig. 7 is a schematic diagram of a method for determining whether the current data is abnormal according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of a system for detecting an abnormal short-circuit voltage and current in a lithium battery according to an embodiment of the present invention.
Fig. 9 is a schematic diagram of the charging voltage in the embodiment of the invention.
Fig. 10 is a schematic diagram of voltage trend in an embodiment of the invention.
Fig. 11 is a schematic diagram of a charging current in an embodiment of the invention.
Fig. 12 is a schematic view of current trend in the embodiment of the present invention.
Fig. 13 is a schematic diagram of a method for calculating a cell surface temperature of a lithium battery in an embodiment of the present invention.
Fig. 14 is a schematic diagram of a method for calculating a correlation between a cell surface temperature of a lithium battery and a measured temperature of a temperature sensor in an embodiment of the present invention.
Fig. 15 is a schematic structural diagram of a temperature anomaly detection subsystem in an embodiment of the present invention.
Fig. 16 is an estimation error distribution diagram between the cell surface temperature estimated by the temperature abnormality detection subsystem and the actually measured temperature in the embodiment of the present invention.
The probe mounting device comprises a temperature sensor 1, a needle bed 2, a tray 3, an electric core 4, a smoke sensor 5, a probe mounting module 6 and a probe supporting module 7.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the embodiments of the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element. The connection may be for fixation or for circuit connection.
It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for convenience in describing the embodiments of the present invention and to simplify the description, and are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed in a particular orientation, and be in any way limiting of the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of the present invention, "a plurality" means two or more unless specifically limited otherwise.
Some of the following embodiments of the invention are based on the recognition that:
1. the cases causing the internal short circuit are classified into the following ones: membrane defects or age cracking; penetrating the diaphragm through lithium dendrite and simple substance iron ion reduction deposition; when the battery core is manufactured, the membrane is pierced due to the entrainment of foreign matters; and burrs are formed on the edge of the copper foil or the aluminum foil of the current collector.
2. According to the classification of the internal short circuit position, the internal short circuit form of the battery is divided into the following types: short-circuiting the negative electrode material and the aluminum current collector; short circuiting the copper current collector and the aluminum current collector; short circuit of copper current collector and anode material; the positive electrode material and the negative electrode material are short-circuited;
3. the various internal shorts behave differently: the short circuit between the aluminum current collector and the charged negative electrode material is easy to cause thermal side reaction due to rapid temperature rise of the short circuit part in a short time because of small contact resistance and large passing current, so that thermal runaway is generated; the short circuit of the aluminum current collector and the copper current collector is similar to the external short circuit, and the temperature can be uniformly transmitted to the whole battery; the short circuit of the anode material, the copper current collector and the anode and cathode materials has the minimum influence because the resistance of the anode material is large.
As a result, the causes of the internal short circuit are various, the locations are also varied, and the voltage expression are inevitably different from each other. Therefore, the invention analyzes the internal short circuit caused by various reasons and parts, summarizes typical modes, and finds out proper characteristic parameters of each mode, thereby realizing the monitoring of the internal short circuit through monitoring the parameters. For example, these modes include:
1. when an internal short circuit occurs in a lithium battery having no porous protective film structure, the battery voltage rapidly decreases, and thereafter the voltage does not recover.
2. When the ternary lithium ion power battery is subjected to internal short circuit, the voltage rapidly decreases to 0 within 2 seconds, and simultaneously, the temperature rises to about 200 ℃ in the vicinity of 5 seconds along with the rise of the temperature, and then the ternary lithium ion power battery is in a thermal runaway state.
3. When the internal short circuit of the lithium battery with the porous protective film occurs, the voltage drops in the initial stage of the internal short circuit, and then the voltage rises to some extent because the short circuit is prevented by the protective diaphragm from entering a micro-short circuit state, and the voltage drops gradually along with the gradual rise of the temperature.
4. When the lithium iron phosphate battery monomer is in an internal short circuit, the secondary battery using lithium iron phosphate (LiFeP04) as the anode material has low conductivity and extremely low lithium ion diffusion speed, the voltage is reduced from the initial 3.7V to 3.2V within 1 second after puncture (simulating internal short circuit), and then the voltage is not reduced after entering a stable state. The surface temperature of the shell gradually and rapidly rises along with the progress of the puncture, and the shell enters a thermal runaway state within 4-6 seconds.
According to experimental data of the lithium batteries of different types, the voltage change firstly occurs in 1-2 seconds of internal short circuit, the temperature rise of the shell can be obviously detected in the following 2-4 seconds, and most batteries can enter a thermal runaway state in the following 4-6 seconds. Therefore, an accurate and safe thermal runaway protection strategy should be protected step by step according to the strategies of voltage and current parameter monitoring, temperature monitoring and fog monitoring.
Based on this recognition, the present invention proposes the following specific examples:
example 1
In the automatic production of lithium batteries, the internal short circuit detection approach of lithium batteries comprises the following steps:
and (3) voltage abnormity detection: the internal short circuit of the lithium battery can cause the voltage to be reduced, and judgment and early warning can be made on the internal short circuit through monitoring the voltage reduction trend.
Thermal detection: whether short circuit occurs or not is judged in a mode of attaching a thermocouple to the side wall of the lithium battery to detect temperature change. In the prior art, because heat is conducted from inside to outside when a short circuit occurs, temperature display has certain lag, and therefore the short circuit condition cannot be fed back at the first time.
Capacity anomaly detection: because a part of electric energy is converted into heat energy to be dissipated when the internal short circuit occurs, the charging capacity in the charging process is higher than that when the internal short circuit does not occur, the internal short circuit fault is reported when the charging capacity is higher than the reference capacity, and the state of the lithium battery is normal when the charging capacity is lower than or equal to the reference capacity.
As shown in fig. 1, a thermal runaway early warning protection system for a lithium battery includes:
the voltage and current abnormity detection subsystem is used for acquiring voltage data at two ends of the lithium battery and current data passing through the lithium battery in real time in the charging and discharging processes of the lithium battery and judging whether the voltage data and the current data are abnormal or not; when the voltage and/or the current are abnormal, stopping charging and discharging;
the temperature anomaly detection subsystem is used for acquiring the temperature of the lithium battery in real time in the charging and discharging processes of the lithium battery, judging whether the temperature exceeds a preset temperature threshold value or not, and sending out a temperature anomaly alarm when the temperature exceeds the temperature threshold value;
and the smoke induction abnormity detection subsystem is used for detecting whether smoke exists in the lithium battery charging and discharging process in real time, and starting alarm and fire-fighting spraying when the smoke is detected.
Synthesize the experimental data of different grade type lithium cell and obtain, the change of at first taking place voltage in inside short circuit 1 ~ 2 seconds, can obviously detect the rising of casing problem in 2 ~ 4 seconds afterwards, and most lithium cells of time 4 ~ 6 seconds later can get into the thermal runaway state, and consequently, accurate and safe thermal runaway's protection strategy should be according to: piezoelectric flow abnormity → temperature abnormity → smoke induction abnormity is protected step by step.
It is understood that in one embodiment of the present invention, the voltage and current anomaly detection subsystem may capture the anomaly signal before the temperature anomaly detection subsystem and the smoke sensing anomaly detection subsystem; when the smoke induction abnormity detection subsystem sends out early warning and the voltage and current abnormity detection subsystem and the temperature abnormity detection subsystem do not capture abnormal signals, the smoke induction abnormity detection subsystem is judged to report by mistake. The voltage and current abnormity detection subsystem synchronously collects at least one of voltage data at two ends of the lithium battery and current data passing through the lithium battery in real time, carries out internal short circuit index monitoring, and judges whether the internal short circuit index of at least one of the voltage data and the current data is abnormal.
The three subsystems effectively prevent the thermal runaway of the lithium battery through abnormal monitoring of three aspects of comprehensive voltage, temperature and smoke induction, and adopt strategies of single-channel stopping, whole-disk stopping, starting fire observation, starting fire spraying, six-surface protection and the like to control and protect the thermal runaway step by step.
When short circuit occurs, the voltage and current abnormity monitoring subsystem captures abnormal signals before the temperature abnormity detection subsystem and the smoke induction abnormity detection subsystem to send early warning, and the single-channel charging and discharging operation is usually stopped when the voltage and current abnormity monitoring subsystem gives early warning to prevent the side reaction from being further aggravated; when the temperature anomaly detection subsystem detects that the temperature of the shell of the lithium battery is remarkably increased, the whole lithium battery can be stopped and fire-fighting observation can be started according to user configuration; when the smoke induction abnormity detection subsystem sends out early warning, the system gives an alarm and starts fire-fighting spraying. When the smoke induction abnormity detection subsystem sends out early warning and the other two subsystems do not send early warning, the system judges that the smoke induction abnormity detection subsystem misrereports according to the configuration.
The automatic needle bed storehouse position of the thermal runaway early warning protection system in the automatic production of the lithium battery is provided with 6 protective devices, so that the thermal runaway is prevented from expanding to an adjacent storehouse position. The system has independent process step protection and global protection, and eliminates potential factors causing thermal runaway caused by overcharge, overdischarge, poor crimping, voltage and current exceeding upper and lower limits and the like.
Example 2
The voltage and current abnormity detection subsystem is the core of a thermal runaway early warning protection system in automatic production of the lithium battery, and judges and early warns the short circuit of the internal battery by monitoring and tracking the change of voltage and current in real time and utilizing the rule of the change of voltage and current in the short circuit of the internal battery. The voltage and current abnormality detection subsystem can usually stop an abnormal channel within 1 second of occurrence of an internal short circuit, so that further aggravation of negative reaction of the internal short circuit is prevented, and the probability of occurrence of thermal runaway is greatly reduced. In the formation and partial capacitance process, judgment and early warning of internal short circuit are realized by monitoring abnormal trend of voltage during charging and discharging and monitoring abnormal reduction of current during discharging. Since the voltage and current anomalies of the internal short circuit are small instantaneous fluctuations, this places high demands on the accuracy and response speed of the detection device. The high-precision charging and discharging equipment has the following conditions:
(1) high precision: a voltage fluctuation of 2mv is resolvable with an accuracy setting of 0.02%;
(2) high sampling rate: the sampling rate of the lower computer is up to 5ms, a Cassel window digital finite impulse response filter is adopted, white noise and out-of-band interference are filtered out, and meanwhile, each point outputs, and long time delay of a moving average filter is avoided;
(3) the high-performance lower computer can realize a trend tracking algorithm on the lower computer, and the trend abnormity of the voltage and the current is tracked and processed in real time by combining high precision and high sampling rate. In the charging and static links, an anomaly tracking algorithm (internally called an electron microscope magnifier) tracks the following trends:
a. sudden rise or fall of voltage
b. The voltage is rapidly reduced to another platform and slowly and gradually reduced
c. The voltage is rapidly and greatly reduced and then gradually increased again, and then slowly and gradually reduced
In the discharging stage, the abnormity tracking algorithm tracks the abnormity descending trend of the current, namely the slope abnormity of delta I/delta t.
As shown in fig. 2, in an embodiment of the present invention, a method for detecting an abnormal short-circuit voltage and current in a lithium battery includes the following steps:
s1: charging and discharging a lithium battery and determining that the lithium battery enters a charging and discharging state;
s2: synchronously acquiring at least one of voltage data at two ends of the lithium battery and current data passing through the lithium battery in real time, and carrying out internal short circuit index monitoring;
s3: judging whether an internal short circuit index of at least one of the voltage data and the current data is abnormal; and stopping charging and discharging the lithium battery when one of the voltage data and the current data is abnormal.
As shown in fig. 3, determining whether the voltage data is abnormal includes the following steps:
filtering noise of the voltage data, selecting the voltage data with an undersampling rate reaching a set value in real time, and dynamically updating the maximum recorded voltage;
the internal short circuit index monitoring comprises at least one of voltage rising abnormity detection, voltage abnormity falling detection and voltage falling trend abnormity detection.
As shown in fig. 4, the voltage rise abnormality detection includes:
calculating real-time voltage data VnAnd a charge starting voltage VstartDifference value V ofras＝Vn-Vstart；
And judging whether the difference value is smaller than a preset voltage rising threshold value or not, and if the difference value is smaller than the preset voltage rising threshold value, judging that the voltage rises abnormally.
As shown in fig. 5, the voltage drop abnormality detection includes:
calculating the maximum recording voltage VmaxWith real-time voltage data VnIs equal to Vmax-Vn；
And judging whether the difference value exceeds a preset voltage drop threshold value or not, and if the difference value exceeds the preset voltage drop threshold value, judging that the voltage drop is abnormal.
As shown in fig. 6, the voltage-falling tendency abnormality detection includes:
calculating the difference of the voltage data of the two ends of the lithium battery collected in real time: dn ═ Vn-Vn-1And obtaining the sign d of the sign of dnsng-n，
Calculating whether the sum of the symbols exceeds a preset voltage descending trend threshold value or not, and recording a voltage descending trend starting point voltage V if the sum of the symbols is smaller than the preset voltage descending trend threshold valueref；
Calculating the voltage drop slope: s ═ Vref-Vn) N, wherein N is the voltage undersampling rate;
and judging whether the voltage falling slope exceeds a preset falling slope threshold value or not, wherein if the voltage falling slope exceeds the preset falling slope threshold value, the voltage falling trend is abnormal.
Specifically, the actual automatic production can be performed according to the following operations:
step 2: resetting all variables;
and step 3: judging whether the lithium battery enters a charging state, and if the lithium battery enters the charging state, entering a step 4;
and 4, step 4: device for collecting battery voltage data VnFiltering noise by a low-pass filter, and meanwhile, incrementing an under-sampling counter;
and 5: if the undersampling counter reaches the undersampling rate N, the voltage buffer is updated (the sampling point before the W moment in the voltage buffer is removed, and the current sampling data V is reducednStoring into a cache), otherwise, returning to the step 4; where W is the size of the observation window, typically set by default to 128, and N is adjusted according to the size of the sampling rate, typically set to 1 or 2.
Step 6: comparison VnAnd a maximum recording voltage VmaxIf V isnGreater than VmaxWill VnImpartation of VmaxAnd zero clearing counter n _ max is 0; otherwise, recording the relative offset n _ max of the Vmax and increasing by n _ max to n _ max + 1;
and 7: detecting abnormal voltage rise: and if the voltage rise abnormity detection switch is turned on, performing voltage rise abnormity detection, otherwise, skipping the step. Difference in voltage riseThe common detection algorithm is as follows: calculating the current sample data VnAnd a charge starting voltage VstartIs a difference v ofras＝Vn-VstarIf the rising difference value is smaller than the voltage rising trend abnormal threshold value after the Time limit (Time _ Rais _ Thres) for judging the voltage rising abnormality, namely vras<Vrais_ThresThe system sends out a voltage rise abnormity alarm and stops the channel to exit the current working state;
and 8: monitoring abnormal voltage drop: and if the voltage abnormal drop monitoring switch is turned on, performing voltage abnormal drop detection, and otherwise, skipping the step. The voltage abnormal drop detection algorithm is as follows: calculating the maximum recording voltage VmaxWith the current sample data VnIs equal to Vmax-v (n). If the voltage is judged to be abnormally reduced for a Time limit (Time _ Drop _ Thres): record the relative offset n _ max of Vmax<The Drop difference in Time _ Drop _ Thres is greater than a threshold, i.e., Δ V>ΔVdThe system sends out a voltage drop abnormal alarm and stops the channel from exiting the current working state;
and step 9: monitoring the voltage drop trend abnormity: and if the voltage falling trend abnormity monitoring switch is turned on, carrying out voltage falling trend abnormity detection, otherwise, skipping the step. The voltage drop trend anomaly detection algorithm is as follows:
(1) calculating the difference d (n) of voltage samples V (n) V (n-1) and obtaining the positive and negative d of dnsng(n)；
(2) Judging whether the descending trend occurs by calculating the sum of the signs: if and dsng(n) less than a threshold, i.e., ∑ dsng＜DtIf so, executing (3) if a descending trend appears;
(3) if the trend tracking is not started, namely the tracking mark trace _ flg is 0, starting the trend tracking, and recording the descending trend starting point voltage Vref v (n); if trend tracking has been enabled, the recording trend of the down trend counter, N _ trend, is incremented: n _ trend + 1;
(4) calculating a falling Slope [ Vref-v (N) ]/N _ trend;
(5) judging whether the Slope exceeds a falling Slope threshold Slope > Slope _ Thres, and if the Slope exceeds the falling Slope threshold, sending out an early warning of short circuit in the battery;
step 10: and repeating the steps 4 to 9 for each sampling point until the channel working step is completed or the abnormal exit is realized.
Example 3
In an embodiment of the present invention, in an internal short-circuit voltage and current abnormality detection method in automatic production of a lithium battery, the lithium battery is in a constant-current charging state, a constant-voltage charging state or a constant-current discharging state, and the corresponding current abnormality is: constant current charging is abnormal, constant voltage charging is abnormal or constant current discharging is abnormal.
As shown in fig. 7, determining whether the current data is abnormal includes the following steps:
filtering noise of the current data and dynamically updating the cache data;
determining the state of the lithium battery and calculating the change rate of current;
and comparing the change rate of the current with a preset change rate threshold of the current, and if the change rate of the current is greater than the preset change rate threshold of the current, judging that the change of the current is abnormal.
Calculating the rate of change of current: d ═ Cn-Cn-N+1) N, wherein CnIs real-time current data, Cn-N+1Is current data prior to time N, which is a time interval, of the real-time;
the preset current change rate threshold value is T when the lithium battery is in a constant current charging state1If d is>T1If the charging is abnormal, the constant current charging is abnormal;
the preset current change rate threshold value is T when the lithium battery is in a constant-voltage charging state2If d is>T2If so, the constant voltage charging is abnormal;
the preset current change rate threshold value is T when the lithium battery is in a constant current discharge state3If d is>T3The constant current discharge is abnormal.
Specifically, the actual automatic production can be performed according to the following operations:
step 2: resetting all variables;
and step 3: judging whether the lithium battery enters a charge-discharge state, and entering a step 4 if the lithium battery enters the charge-discharge state;
and 4, step 4: device acquisition current data CnAnd filtering noise through a low-pass filter, and updating a current observation buffer c _ buff buffer: removing the sampling point before the N time in the buffer and reducing the current sampling data CnStoring the data into a cache;
and 5: calculating the current change rate: d ═ Cn-Cn-N+1) N and compared with a threshold value, wherein CnIs real-time current data, Cn-N+1Is current data prior to time N, which is a time interval, of the real-time;
(1) setting a threshold value T: if the current state is in the constant-current charging state, the constant-current charging abnormal threshold value T is Tccc, if the current state is in the constant-voltage charging state, the constant-voltage charging abnormal threshold value T is Tcvc, and if the current state is in the constant-current discharging state, the constant-current discharging abnormal threshold value T is Tccd;
(2) and (3) comparison: if d is larger than T, judging that the current is abnormal, stopping the channel to exit the current working step, and otherwise, repeating the step 4.
Example 4
As shown in fig. 8, the present invention further provides a system for detecting an abnormality of a short-circuit voltage and current in a lithium battery, including:
the charging and discharging unit is used for charging and discharging the lithium battery;
the voltage acquisition unit is used for acquiring voltage data of two ends of the lithium battery in real time;
the current acquisition unit is used for acquiring current data passing through the lithium battery in real time;
the processing unit is used for judging whether the voltage data and the current data are abnormal or not; and when the voltage and/or the current are abnormal, stopping charging and discharging.
It will be appreciated that the above definitions of the various elements are merely functional and that virtually any system capable of implementing the present invention is possible. In another embodiment of the present invention, the processing unit may further determine whether the temperature is abnormal or the smoke is abnormal, and then take the corresponding operations as described above.
Example 5
All or part of the flow of the method of the embodiments may be implemented by a computer program, which may be stored in a computer readable storage medium and executed by a processor, to instruct related hardware to implement the steps of the embodiments of the methods. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Example 6
The system and the method are applied to actual production, and the proportion of 12 nickel-cobalt-manganese NCMs is 6: 2: 2, performing charge-discharge cycle test on the 53Ah ternary battery cell, wherein 3 of 12 battery cells are bad battery cells but are not marked, and the purpose of the experiment is to verify whether the system can detect the bad battery cells through the charge-discharge cycle test of the lithium battery.
Fig. 9 is a voltage curve of a battery cell during constant-current constant-voltage charging, fig. 10 is a voltage trend calculated in real time by the system of the present invention, fig. 11 is a current curve during constant-current constant-voltage charging, and fig. 12 is a current trend calculated in real time by the system of the present invention. As shown in fig. 10 and 12, in the constant voltage charging stage, voltage trends and current trends of three cells are shown in fig. 9 to 12, and abnormal jumps different from normal cells appear in a bad cell at the same time of the voltage trends and the current trends, so that the bad cell can be detected and marked.
In another embodiment of the invention, the system detects and judges 2.3 thousands of bad cells, 150 cells are judged by mistake through off-line test verification, and the judgment mistake rate is less than 0.01 per thousand.
Example 7
The temperature abnormality detection subsystem of the present embodiment includes: the lithium battery is characterized in that a temperature probe is crimped on a tab of the lithium battery; it can be understood that, because each lithium battery has a temperature probe pressed on the tab, the temperature of the lithium battery is monitored in real time in the charging and discharging process of the lithium battery, and when the temperature of the tab continuously exceeds a temperature threshold value, the temperature abnormity detection subsystem can send out temperature abnormity alarm.
Example 8
For laminate polymer battery, because laminate polymer battery aluminium plastic envelope heat conductivility is not good, consequently laminate polymer battery core body temperature and pole piece temperature difference are great. For such a situation, this embodiment 8 provides a method for calculating the cell surface temperature of the lithium battery through software. In this embodiment, a row of temperature sensor arrays are respectively installed on the front and back of the top of the needle bed of the lithium battery, and the temperature sensor arrays include L temperature sensors at equal intervals to form a 2 × L temperature sensor array. The temperature of each battery pack can be calculated from the 2 x L temperature sensor measurements. The following examples illustrate:
as shown in fig. 15, which is a specific example of the system and method applied in actual production for measuring the temperature of the surface of the battery cell according to the present invention, 4 temperature sensors are respectively installed in the front row and the back row of the top of the needle bed 2 of the partial volume of the thermal runaway early warning protection system for the lithium battery, 8 temperature sensors form a temperature sensor array, 32 soft package battery cells 4 are placed on one tray 3, and a temperature sensor 1 is installed on the surface of each battery cell 4 for measuring the temperature of the surface of the battery cell. Each lithium battery is pressed with a temperature probe at a tab, and a probe installation module 6 and a probe supporting module 7 are visible in the figure. The smoke sensor 5 is arranged between the temperature sensor 1 and the battery cell 4.
As shown in fig. 13, in an embodiment, the method for calculating the cell surface temperature of the lithium battery includes the following steps:
t1: calculating the correlation between the cell surface temperature of the lithium battery and the measurement temperature of the temperature sensor;
t2: and estimating the surface temperature of the battery core of the lithium battery in real time according to the correlation and the measured temperature of the temperature sensor array.
As shown in fig. 14, step T1 includes:
t11: calculating a cross-correlation matrix between the temperature sensors:
wherein r isn，IFor the measured temperature of the nth temperature sensor and the measured temperature of the first temperature sensor
The cross-correlation between the temperatures is such that,
for the measured temperature of the nth temperature sensor and the first temperature
The covariance between the measured temperatures of the degree sensors,
for measuring temperature of nth temperature sensor
The variance of the degree(s) is,
the variance of the measured temperature of the ith temperature sensor;
t12: calculating a cross-correlation matrix between each of the lithium batteries and the temperature sensor,
wherein, cm，lFor the cross-correlation between the mth cell surface temperature and the l-th temperature sensor measurement temperature,
is the covariance between the surface temperature of the mth temperature sensor and the measured temperature of the lth temperature sensor,
is the variance of the surface temperature of the mth cell,
the ith temperature sensor measures the variance of the temperature.
Step T2 includes: and setting the measurement temperature vector of the temperature sensor at the moment k as follows:
the cell surface temperature according to the 2D-MMSE criterion was:
generally, when the surface temperature of a battery tab or the surface temperature of a battery core exceeds 100 ℃, the temperature is judged to be abnormal, and an alarm is started.
Fig. 16 shows the estimated error distribution between the cell surface temperature estimated by the system and the actual measured temperature, and from the results, it can be seen that most of the error distribution is in the range of [ -0.1, 0.1], and the mean square error is 6 e-3. Therefore, the result is very reliable, and the requirement of thermal runaway early warning protection can be met.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several equivalent substitutions or obvious modifications can be made without departing from the spirit of the invention, and all the properties or uses are considered to be within the scope of the invention.
Claims (9)
1. A method for detecting the abnormal short-circuit voltage and current in a lithium battery is characterized by comprising the following steps:
s1: charging and discharging a lithium battery and determining that the lithium battery enters a charging and discharging state;
s2: synchronously acquiring at least one of voltage data at two ends of the lithium battery and current data passing through the lithium battery in real time, and carrying out internal short circuit index monitoring;
s3: judging whether an internal short circuit index of at least one of the voltage data and the current data is abnormal; judging whether the voltage data is abnormal or not comprises voltage falling trend abnormal detection, wherein the voltage falling trend abnormal detection comprises the following steps:
calculating the difference of the voltage data of the two ends of the lithium battery collected in real time: dn ═ Vn-Vn-1And obtaining the sign d of the sign of dnsng-n；
Calculating whether the sum of the symbols exceeds a preset voltage descending trend threshold value or not, and recording a voltage descending trend starting point voltage V if the sum of the symbols is smaller than the preset voltage descending trend threshold valueref；
Calculating the voltage drop slope: s ═ Vref-Vn) N, wherein N is the voltage undersampling rate;
judging whether the voltage falling slope exceeds a preset falling slope threshold value or not, and if the voltage falling slope exceeds the preset falling slope threshold value, judging that the voltage falling trend is abnormal;
and stopping charging and discharging the lithium battery when one of the voltage data and the current data is abnormal.
2. The method for detecting the abnormality of the short-circuit voltage and current in the lithium battery according to claim 1, wherein the step of determining whether the voltage data is abnormal includes the steps of:
filtering noise of the voltage data, selecting the voltage data with an undersampling rate reaching a set value in real time, and dynamically updating the maximum recorded voltage;
and monitoring the internal short circuit index, wherein the monitoring of the internal short circuit index comprises at least one of synchronous voltage rise abnormity detection, voltage abnormity drop detection and voltage drop trend abnormity detection.
3. The method for detecting a short-circuit voltage current abnormality in a lithium battery according to claim 2, wherein the voltage rise abnormality detection includes:
calculating real-time voltage data VnAnd a charge starting voltage VstartDifference value V ofras＝Vn-Vstart；
And judging whether the difference value is smaller than a preset voltage rising threshold value or not, and if the difference value is smaller than the preset voltage rising threshold value, judging that the voltage rises abnormally.
4. The method for detecting a short-circuit voltage current abnormality in a lithium battery according to claim 2, wherein the voltage abnormality drop detection includes:
calculating the maximum recording voltage VmaxWith real-time voltage data VnIs equal to Vmax-Vn；
And judging whether the difference value exceeds a preset voltage drop threshold value or not, and if the difference value exceeds the preset voltage drop threshold value, judging that the voltage drop is abnormal.
5. The method for detecting the current abnormality of the short-circuit voltage in the lithium battery according to claim 1, wherein the lithium battery is in a constant-current charging state, a constant-voltage charging state or a constant-current discharging state, and the corresponding current abnormality is: constant current charging is abnormal, constant voltage charging is abnormal or constant current discharging is abnormal.
6. The method for detecting the abnormality of the short-circuit voltage and current in the lithium battery according to claim 5, wherein the step of determining whether the current data is abnormal includes the steps of:
filtering noise of the current data and dynamically updating the cache data;
determining the state of the lithium battery and calculating the change rate of current;
and comparing the change rate of the current with a preset change rate threshold of the current, and if the change rate of the current is greater than the preset change rate threshold of the current, judging that the change of the current is abnormal.
7. The method for detecting a short-circuit voltage current abnormality in a lithium battery according to claim 6,
calculating the rate of change of current: d ═ Cn-Cn-N+1) N, wherein CnIs real-time current data, Cn-N+1Is current data prior to time N, which is a time interval, of the real-time;
the preset current change rate threshold value is T when the lithium battery is in a constant current charging state1If d is>T1If the charging is abnormal, the constant current charging is abnormal;
the preset current change rate threshold value is T when the lithium battery is in a constant-voltage charging state2If d is>T2If so, the constant voltage charging is abnormal;
the preset current change rate threshold value is T when the lithium battery is in a constant current discharge state3If d is>T3The constant current discharge is abnormal.
8. The utility model provides a short-circuit voltage current anomaly detection system in lithium cell which characterized in that includes:
the charging and discharging unit is used for charging and discharging the lithium battery;
the voltage acquisition unit is used for acquiring voltage data of two ends of the lithium battery in real time;
the current acquisition unit is used for acquiring current data passing through the lithium battery in real time;
the processing unit is used for judging whether the voltage data and the current data are abnormal or not; judging whether the voltage data is abnormal or not comprises voltage falling trend abnormal detection, wherein the voltage falling trend abnormal detection comprises the following steps:
calculating the difference of the voltage data of the two ends of the lithium battery collected in real time: dn ═ Vn-Vn-1And obtaining the sign d of the sign of dnsng-n；
Calculating whether the sum of the symbols exceeds a preset voltage descending trend threshold value or not, and recording a voltage descending trend starting point voltage V if the sum of the symbols is smaller than the preset voltage descending trend threshold valueref；
Calculating the voltage drop slope: s ═ Vref-Vn) N, wherein N is the voltage undersampling rate;
judging whether the voltage falling slope exceeds a preset falling slope threshold value or not, and if the voltage falling slope exceeds the preset falling slope threshold value, judging that the voltage falling trend is abnormal; and when the voltage and/or the current are abnormal, stopping charging and discharging.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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