Vehicle Power Battery Monitoring Method and Device

Abstract

The present invention discloses a method and device for monitoring a vehicle power battery, relating to the technical field of batteries. The power battery includes a plurality of battery cells. The method comprises the following steps: collecting calibration data of each battery cell; dividing the collected ambient temperature data into a plurality of temperature data sets, dividing the collected voltage data into a plurality of voltage data sets, and establishing a voltage-electric quantity curve and a temperature-pressure curve of the battery cell; establishing a calibration data packet; collecting measured data of each battery cell, comparing the measured data with the data in the calibration data packet, and when the deviation value of the comparison exceeds a preset range, determining that the power battery has a risk of thermal runaway. The advantages of the present invention are as follows: the electric quantity data of the battery cell that is consistent with the actual working condition of the battery cell can be obtained, and compared with the fixed calibration data set in the traditional factory setting, the judgment of battery thermal runaway is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of batteries, and in particular to a method and device for monitoring a vehicle power battery. Background Art

[0002] During the diagnosis of thermal runaway of a power battery, the battery management system (BMS) can be combined with sampling sensors to monitor signals such as the temperature, voltage of the battery cells in the battery module, and the air pressure in the battery pack, and determine whether the battery has thermal runaway by judging whether the change of the collected relevant monitoring data from the preset calibration data reaches the set threshold. However, the existing calibration data is usually a fixed value preset at the factory. As the battery is used, its performance will decrease, resulting in the existing calibration data no longer being applicable to the determination of thermal runaway, and thus causing misjudgment of battery thermal runaway. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the above background art and provide a method and device for monitoring a vehicle power battery.

[0004] In a first aspect, a method for monitoring a vehicle power battery is provided. The power battery includes a plurality of battery cells, and the method includes the following steps:

[0005] Collect the calibration data of each battery cell. The calibration data includes the voltage data, ambient temperature data, ambient pressure data, and battery cell power data of the battery cell;

[0006] Divide the collected ambient temperature data into multiple temperature data sets, and establish a voltage-electricity curve of the battery cell corresponding to each temperature data set;

[0007] Divide the collected voltage data into multiple voltage data sets, and establish a temperature-pressure curve of the battery cell corresponding to each voltage data set;

[0008] Establish a calibration data packet including multiple temperature data sets and their voltage-electricity curve data, and multiple temperature data sets and their temperature-pressure curve data;

[0009] Collect the measured data of each battery cell, compare the measured data with the voltage-electricity curve and / or temperature-pressure curve data in the calibration data packet, and when the deviation value of the comparison exceeds the preset range, determine that the power battery has a risk of thermal runaway.

[0010] Further, compare the measured data with the calibration data packet. When the deviation value of the comparison does not exceed the preset range, update the voltage-electricity curve and temperature-pressure curve of the calibration data packet based on the measured data.

[0011] The beneficial effects of the above further solution are as follows: By updating the calibration data of the calibration data packet to update the voltage-electricity curve and the temperature-pressure curve, more accurate electric core electricity data can be obtained, and the determination of whether there is a thermal runaway risk in the power battery is more accurate.

[0012] Further, the step of dividing the collected ambient temperature data into multiple temperature data sets includes:

[0013] Dividing the collected ambient temperature data into N temperature data sets starting from the lowest temperature tolerance of the electric core with each A °C as a temperature interval range; wherein, each temperature data set contains the voltage values and electricity values of all electric cores within the corresponding temperature interval range of the temperature data set.

[0014] Further, the step of establishing the voltage-electricity curve of the electric core corresponding to each temperature data set includes:

[0015] Starting from the lowest voltage of all electric cores in each of the temperature data sets, dividing them into M voltage data subsets with each B mv as an interval range, taking the median of multiple electricity values in each voltage data subset as the electricity value of the voltage data subset, and taking the lowest voltage in each voltage data subset as the voltage value of the voltage data subset;

[0016] Taking the electricity values of the M voltage data subsets as the abscissa and the voltage values of the M voltage data subsets as the ordinate, and using the Hermite interpolation method to interpolate the abscissa and the ordinate to generate the voltage-electricity curve.

[0017] Further, the step of dividing the collected voltage data into multiple voltage data sets includes:

[0018] Dividing the collected voltage data into M voltage data sets starting from the lowest voltage of the electric core with each B mv as a voltage interval range; wherein, each voltage data set contains the temperature values and pressure values of all electric cores within the corresponding voltage interval range of the voltage data set.

[0019] Further, the step of establishing the temperature-pressure curve of the electric core corresponding to each voltage data set includes:

[0020] Starting from the lowest temperature tolerance of the electric core, dividing the temperature values of all electric cores in each of the voltage data sets into N temperature data subsets with each A °C as a temperature interval range, taking the median of multiple pressure values in each temperature data subset as the pressure value of the temperature data subset, and taking the lowest temperature in each temperature data subset as the temperature value of the temperature data subset;

[0021] Taking the pressure values of the N temperature data subsets as the abscissa and the temperature values of the N temperature data subsets as the ordinate, use the Hermite interpolation method to interpolate the abscissa and ordinate to generate the temperature-pressure curve.

[0022] Further, the measured data includes voltage data, ambient temperature data, ambient pressure data, and battery cell power data of each battery cell collected in real time.

[0023] Further, the step of comparing the measured data with the voltage-power curve and / or temperature-pressure curve data in the calibration data packet includes:

[0024] Combining the voltage data collected in real time with the voltage-power curve in the calibration data packet to obtain optimized battery cell power data;

[0025] Combining the temperature data collected in real time with the temperature-pressure curve of the calibration data packet to obtain the pressure value corresponding to the temperature data collected in real time in the temperature-pressure curve, and comparing this pressure value with the ambient pressure data collected in real time.

[0026] In a second aspect, the present invention also proposes a vehicle power battery monitoring device, which is applied to the method to monitor the vehicle power battery, and the power battery includes a plurality of battery cells; the device includes: a data acquisition chip, a storage chip, a processing chip, and a signal transmission chip;

[0027] The data acquisition chip is used to collect calibration data and measured data of each battery cell, and both the calibration data and the measured data include voltage data, ambient temperature data, ambient pressure data, and battery cell power data of the battery cell;

[0028] The storage chip is used to store the calibration data and the measured data, and is data-connected to the processing chip and the signal transmission chip;

[0029] The processing chip is used to establish a calibration data packet, compare the measured data with the data in the calibration data packet, determine whether there is a risk of thermal runaway in the power battery according to the comparison result, and feedback the comparison result to the storage chip and the signal transmission chip;

[0030] The signal transmission chip is data-connected to the vehicle system and an external server through wireless communication, and is used to feedback the comparison result to the vehicle system and the external server.

[0031] Further, the data acquisition chip includes an all-in-one signal acquisition chip and a gas sensing chip; the all-in-one signal acquisition chip is used to acquire the voltage data, ambient temperature data, and cell power data of each cell; the gas sensing chip is used to acquire the ambient pressure data of each chip.

[0032] Compared with the prior art, the advantages of the present invention are as follows: By establishing a calibration data packet based on the acquired cell calibration data and comparing it with the measured data of the cell, the cell power data that matches the actual working condition of the cell can be obtained. Compared with the traditional fixed calibration data set at the factory, the judgment of battery thermal runaway is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a schematic flowchart of the vehicle power battery monitoring method of the present invention;

[0034] Figure 2 is a schematic structural diagram of the vehicle power battery monitoring device of the present invention.

[0035] In the figure: 100 - all-in-one signal acquisition chip; 200 - gas sensing chip; 300 - storage chip; 400 - processing chip; 500 - signal transmission chip. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] Now, specific embodiments of the present invention will be described in detail. Examples of the present invention are illustrated in the accompanying drawings. Although the present invention will be described in conjunction with specific embodiments, it will be understood that it is not intended to limit the present invention to the described embodiments. On the contrary, it is intended to cover modifications, variations, and equivalents included within the spirit and scope of the present invention as defined by the appended claims. It should be noted that the method steps described herein can all be implemented by any functional block or functional arrangement, and any functional block or functional arrangement can be implemented as a physical entity or a logical entity, or a combination of both.

[0037] In order to enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] Note: The example to be introduced next is only a specific example and does not limit that the embodiments of the present invention must be the following specific steps, numerical values, conditions, data, sequences, etc. Those skilled in the art can use the concept of the present invention described in this specification to construct more embodiments not mentioned in this specification.

[0039] As Figure 1 shown, the vehicle power battery monitoring method proposed in this embodiment, the power battery includes a plurality of cells, and the method includes the following steps:

[0040] Collect the calibration data of each battery cell, where the calibration data includes the voltage data, ambient temperature data, ambient pressure data, and battery cell power data of the battery cell;

[0041] Divide the collected ambient temperature data into multiple temperature data sets, and establish the voltage-power curve of the battery cell corresponding to each temperature data set;

[0042] Divide the collected voltage data into multiple voltage data sets, and establish the temperature-pressure curve of the battery cell corresponding to each voltage data set;

[0043] Establish a calibration data packet including multiple temperature data sets and their voltage-power curve data, as well as multiple temperature data sets and their temperature-pressure curve data;

[0044] Collect the measured data of each battery cell, compare the measured data with the voltage-power curve and / or temperature-pressure curve data in the calibration data packet, and when the deviation value of the comparison exceeds the preset range, determine that the power battery has a thermal runaway risk.

[0045] In this embodiment, when the measured data is compared with the calibration data packet and the deviation value of the comparison does not exceed the preset range, the voltage-power curve and temperature-pressure curve of the calibration data packet are updated based on the measured data. Therefore, the calibration data of the calibration data packet in this embodiment can actually be updated in real time.

[0046] In a further specific implementation manner of the method of the present invention, the step of dividing the collected ambient temperature data into multiple temperature data sets includes:

[0047] Divide the collected ambient temperature data into N temperature data sets starting from the lowest temperature tolerance of the battery cell with each A °C as a temperature interval range; where each temperature data set contains the voltage values and power values of all battery cells within the temperature interval range corresponding to the temperature data set.

[0048] The step of establishing the voltage-power curve of the battery cell corresponding to each temperature data set includes:

[0049] Divide the voltage values of all battery cells in each temperature data set from the lowest voltage, with each B mv as an interval range, into M voltage data subsets, take the median of the multiple power values in each voltage data subset as the power value of the voltage data subset, and take the lowest voltage in each voltage data subset as the voltage value of the voltage data subset.

[0050] In the above embodiment, A = 5 and B = 0.05 are taken as examples. Of course, in practice, both A and B can be other values. For example, A can be 4 or 3 or 6, and B can be 0.02, 0.03, 0.04, 0.05, etc.

[0051] Taking the charge values of the M voltage data subsets as the abscissa and the voltage values of the M voltage data subsets as the ordinate, use the piecewise cubic Hermite interpolation method in MATLAB to interpolate the abscissa and ordinate to generate the voltage-charge curve.

[0052] The MATLAB code is as follows:

[0053] U = [voltage values];

[0054] Soc = [corresponding SOC values];

[0055] Soc1 = 0:0.01:100;

[0056] U1 = interp1(Soc, U, Soc1, 'pchip')

[0057] plot(Soc1, U1);

[0058] Taking the temperature dataset at 25°C as an example, this temperature dataset contains the voltage values and charge values of all battery cells within the temperature range corresponding to this temperature dataset.

[0059] Starting from the lowest voltage of 3.280 mV for the voltage values of all battery cells in each temperature dataset, divide them into 21 voltage data subsets with an interval range of every 0.05 mV. Take the median of the multiple charge values in each voltage data subset as the charge value of this voltage data subset, and take the lowest voltage in each voltage data subset as the voltage value of this voltage data subset. For example, the voltage value of the first voltage data subset (corresponding to 3.280 mV) is 3.280 mV, and the charge value of this first voltage data subset is 0%. The voltage value of the second voltage data subset is 3.330 mV, and the charge value of this second voltage data subset is 1.12%.

[0060] After median selection, the corresponding table of the voltage value (OCV) and charge value (SOC) of a certain battery cell at 25°C is as follows:

[0061]

[0062]

[0063] At this time, substitute the data into MATLAB for calculation:

[0064] U = [3.280, 3.330, 3.380, 3.430, 3.480, 3.530, 3.580, 3.630, 3.680, 3.730, 3.780, 3.830, 3.880, 3.930, 3.980, 4.030, 4.080, 4.130, 4.180, 4.230, 4.309];

[0065] Soc = [0, 1.12, 2.36, 3.97, 7.67, 13.45, 20, 30.58, 43.72, 50.7, 54.53, 58.73, 62.96, 67.29, 71.61, 75.75, 79.92, 84.41, 90, 95.5, 100];

[0066] Soc1 = 0:0.1:100;

[0067] U1 = interp1(Soc, U, Soc1, 'pchip');

[0068] plot(Soc1, U1);

[0069] It can automatically generate the voltage - power curve of the battery cell at an ambient temperature of 25°C.

[0070] The step of dividing the collected voltage data into multiple voltage data sets includes:

[0071] The collected voltage data is divided into M voltage data sets starting from the lowest voltage of the battery cell, with each B mv as a voltage interval range; among them, each voltage data set contains all the temperature values and pressure values of the battery cell within the corresponding voltage interval range.

[0072] The step of establishing the temperature - pressure curve of the battery cell corresponding to each voltage data set includes:

[0073] The temperature values of all the battery cells in each of the voltage data sets are divided into N temperature data subsets starting from the lowest temperature resistance of the battery cell, with each A°C as a temperature interval range. The median of the multiple pressure values in each temperature data subset is taken as the pressure value of the temperature data subset, and the lowest temperature of each temperature data subset is taken as the temperature value of the temperature data subset;

[0074] Taking the pressure values of the N temperature data subsets as the abscissa and the temperature values of the N temperature data subsets as the ordinate, using the piecewise cubic Hermite interpolation method in MATLAB to interpolate the abscissa and ordinate to generate the temperature - pressure curve.

[0075] Similarly, taking the voltage dataset of 4 mV as an example, the temperature values and pressure values of all battery cells within the voltage range corresponding to this voltage dataset are included. Taking every 5 °C as a temperature range, it is divided into 6 temperature data subsets. The lowest temperature of each temperature data subset is taken as the temperature value of this temperature data subset, and the median of multiple pressure values in each temperature data subset is taken as the pressure value (or air pressure value) of this temperature data subset. For example, the temperature value of the first temperature data subset is 25 °C, and the pressure value of this first temperature data subset is 101.0 Kpa.

[0076] The MATLAB code is as follows:

[0077] T = [temperature values];

[0078] P = [corresponding air pressure values];

[0079] P1 = Pmin:0.01:Pmax;

[0080] T1 = interp1(P,T,P1,'pchip')

[0081] plot(P1,T1);

[0082] For example:

[0083] After median selection, the partial data correspondence table of the temperature values and air pressure values of the battery cells at a constant voltage of 4 mV is as follows:

[0084] Temperature (°C) Air pressure value (Kpa) 25 101.0 30 101.1 35 101.18 40 101.28 45 101.35 50 101.4

[0085] T = [25, 30, 35, 40, 45, 50];

[0086] P = [101, 101.1, 101.18, 101.28, 101.35, 101.4];

[0087] P1 = 101:0.01:101.4;

[0088] T1 = interp1(P,T,P1,'pchip')

[0089] plot(P1,T1);

[0090] The temperature-pressure curve of the battery cells at a voltage of 4 mV can be automatically generated.

[0091] The measured data includes voltage data, ambient temperature data, ambient pressure data, and battery cell power data of each battery cell collected in real time.

[0092] The step of comparing the measured data with the voltage-electricity curve and / or temperature-pressure curve data in the calibration data packet includes:

[0093] The real-time collected voltage data is combined with the voltage-capacity curve in the calibration data packet to obtain the optimized cell capacity data;

[0094] The real-time collected temperature data is combined with the temperature-pressure curve of the calibration data packet to obtain the pressure value corresponding to the real-time collected temperature data in the temperature-pressure curve, and the pressure value is compared with the real-time collected ambient pressure data.

[0095] When the deviation value of the comparison exceeds a preset range, the power battery is determined to be at risk of thermal runaway. For example, if the difference between the pressure value and the real-time collected ambient pressure data, i.e., the deviation value, exceeds 1% of the current real-time collected ambient pressure data (e.g., the measured pressure value), the power battery is determined to be at risk of thermal runaway.

[0096] Based on the same inventive concept, Figure 2 As shown, this embodiment also proposes a vehicle power battery monitoring device, which is applied to the method of the above embodiment to monitor the vehicle power battery. The device includes: a data acquisition chip, a storage chip, a processing chip, and a signal transmission chip;

[0097] The data acquisition chip is used to collect calibration data and measured data of each battery cell, and the calibration data and measured data both include the battery cell voltage data, ambient temperature data, ambient pressure data and battery cell power data; wherein, the data acquisition chip includes an all-in-one signal acquisition chip and a gas sensor chip; the all-in-one signal acquisition chip is used to collect voltage data, ambient temperature data and battery cell power data of each battery cell; the gas sensor chip is used to collect ambient pressure data of each chip.

[0098] The storage chip is used to store the calibration data and measured data, and is data-connected to the processing chip and the signal transmission chip;

[0099] The processing chip is used to create a calibration data packet, compare the measured data with the data in the calibration data packet, determine whether the power battery has a thermal runaway risk based on the comparison result, and feed back the comparison result to the storage chip and the signal transmission chip;

[0100] The signal transmission chip is connected to the entire vehicle system and the external server through wireless communication to provide data for feeding back the comparison results to the entire vehicle system and the external server.

[0101] It should be noted that there may be multiple devices in this embodiment, and each device can be used to monitor one or more battery cells.

[0102] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by terms such as "upper" and "lower" is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. Unless otherwise clearly specified and defined, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0103] It should be noted that in the present invention, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the said element.

[0104] The above is only the specific implementation manner of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A method for monitoring a vehicle power battery, characterized in that The power battery includes a plurality of battery cells, and the method includes the following steps: Collect the calibration data of each battery cell, where the calibration data includes the voltage data, ambient temperature data, ambient pressure data, and battery cell power data of the battery cell; Divide the collected ambient temperature data into a plurality of temperature data sets, and establish a voltage-power curve of the battery cell corresponding to each temperature data set; Divide the collected voltage data into a plurality of voltage data sets, and establish a temperature-pressure curve of the battery cell corresponding to each voltage data set; Establish a calibration data packet including a plurality of temperature data sets and their voltage-power curve data, and a plurality of temperature data sets and their temperature-pressure curve data; Collect the measured data of each battery cell, compare the measured data with the voltage-power curve and temperature-pressure curve data in the calibration data packet, and when the deviation value of the comparison exceeds the preset range, determine that the power battery has a thermal runaway risk; The step of dividing the collected voltage data into a plurality of voltage data sets includes: Divide the collected voltage data into M voltage data sets starting from the lowest voltage of the battery cell with each B mv as a voltage interval range; where each voltage data set contains the temperature values and pressure values of all battery cells within the voltage interval range corresponding to the voltage data set; The step of establishing a temperature-pressure curve of the battery cell corresponding to each voltage data set includes: Divide the temperature values of all battery cells in each voltage data set into N temperature data subsets starting from the lowest temperature resistance of the battery cell with each A °C as a temperature interval range, take the median of the plurality of pressure values in each temperature data subset as the pressure value of the temperature data subset, and take the lowest temperature of each temperature data subset as the temperature value of the temperature data subset; Take the pressure values of the N temperature data subsets as the abscissa, take the temperature values of the N temperature data subsets as the ordinate, and use Hermite interpolation to interpolate the abscissa and ordinate to generate the temperature-pressure curve.

2. The vehicle power battery monitoring method according to claim 1, wherein, Compare the measured data with the calibration data packet, and when the deviation value of the comparison does not exceed the preset range, update the voltage-power curve and temperature-pressure curve of the calibration data packet based on the measured data.

3. The vehicle power battery monitoring method according to claim 1, characterized in that, The step of dividing the collected ambient temperature data into a plurality of temperature data sets includes: Divide the collected ambient temperature data into N temperature data sets starting from the lowest temperature resistance of the battery cell with each A °C as a temperature interval range; where each temperature data set contains the voltage values and power values of all battery cells within the temperature interval range corresponding to the temperature data set.

4. The vehicle power battery monitoring method according to claim 3, wherein, The step of establishing a voltage-power curve of the battery cell corresponding to each temperature data set includes: Divide the voltage values of all battery cells in each temperature data set into M voltage data subsets starting from the lowest voltage with each B mv as an interval range, take the median of the plurality of power values in each voltage data subset as the power value of the voltage data subset, and take the lowest voltage of each voltage data subset as the voltage value of the voltage data subset; The power values of the M voltage data subsets are used as abscissas, the voltage values of the M voltage data subsets are used as ordinates, and the abscissas and ordinates are interpolated using the Hermite interpolation method to generate the voltage-power curve.

5. The vehicle power battery monitoring method according to claim 1, characterized in that, The measured data includes voltage data, ambient temperature data, ambient pressure data and battery cell power data of each battery cell collected in real time.

6. The vehicle power battery monitoring method according to claim 5, characterized in that, The step of comparing the measured data with the voltage-electricity curve and temperature-pressure curve data in the calibration data packet includes: The real-time collected voltage data is combined with the voltage-capacity curve in the calibration data packet to obtain the optimized cell capacity data; The real-time collected temperature data is combined with the temperature-pressure curve of the calibration data packet to obtain the pressure value corresponding to the real-time collected temperature data in the temperature-pressure curve, and the pressure value is compared with the real-time collected ambient pressure data.

7. A vehicle power battery monitoring device, characterized in that The device is applied to the method according to any one of claims 1 to 6 to monitor a vehicle power battery, wherein the power battery comprises a plurality of cells; the device comprises: a data acquisition chip, a storage chip, a processing chip, and a signal transmission chip; The data acquisition chip is used to collect calibration data and measured data of each battery cell, and the calibration data and measured data both include battery cell voltage data, ambient temperature data, ambient pressure data and battery cell power data; The storage chip is used to store the calibration data and measured data, and is data-connected to the processing chip and the signal transmission chip; The processing chip is used to create a calibration data packet, compare the measured data with the data in the calibration data packet, determine whether the power battery has a thermal runaway risk based on the comparison result, and feed back the comparison result to the storage chip and the signal transmission chip; The signal transmission chip is connected to the entire vehicle system and the external server through wireless communication to provide data for feeding back the comparison results to the entire vehicle system and the external server.

8. The vehicle power battery monitoring device according to claim 7, wherein, The data acquisition chip includes an all-in-one signal acquisition chip and a gas sensor chip; the all-in-one signal acquisition chip is used to collect voltage data, ambient temperature data and battery power data of each battery cell; the gas sensor chip is used to collect ambient pressure data of each chip.

Images