Battery pack, control method, device and system thereof, vehicle and storage medium

Abstract

The invention relates to a battery pack, a control method, device and system thereof, a vehicle and a storage medium. The battery pack control method comprises the steps that multi-dimensional sensing data of a vehicle battery pack are obtained through an optical fiber sensor, the multi-dimensional sensing data comprise at least one of electrical parameters and non-electrical parameters, the electrical parameters comprise at least one of current and voltage of the battery pack, and the non-electrical parameters comprise at least one of current and voltage of the battery pack; the non-electrical parameters comprise at least one of temperature and strain of the battery pack; according to the multi-dimensional sensing data, the working condition of the vehicle is determined; and performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle. Multi-dimensional data dynamic information of force, electricity, heat, gas and the like of the battery can be collected in real time, and high-safety and high-performance monitoring and application of the whole life cycle of the battery pack can be achieved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of new energy commercial vehicles, in particular to a battery pack, a control method, device and system thereof, a vehicle and a storage medium. BACKGROUND

[0002] The application scenarios of new energy commercial vehicles have rapidly increasing demands for high efficiency, long service life, safety and fast charging of battery systems. The metal sensors commonly used in current battery pack information collection and transmission technologies are prone to sensing distortion and perception failure under conditions such as high electromagnetic interference and high-frequency sampling in specific application scenarios and complex working conditions, and are difficult to meet the requirements of high-precision and real-time information collection and analysis. SUMMARY

[0003] In view of at least one of the above technical problems, the present disclosure provides a battery pack, a control method, device and system thereof, a vehicle and a storage medium, which can collect multi-dimensional data dynamic information of force, electricity, heat and gas of the battery in real time, and realize high safety and high performance monitoring and application of the battery pack throughout its life cycle.

[0004] According to an aspect of the present disclosure, a battery pack control method is provided, comprising: obtaining multi-dimensional sensing data of a vehicle battery pack by an optical fiber sensor, wherein the multi-dimensional sensing data includes at least one of electrical parameters and non-electrical parameters, the electrical parameters include at least one of current and voltage of the battery pack, and the non-electrical parameters include at least one of temperature and strain of the battery pack; determining a working condition of the vehicle according to the multi-dimensional sensing data; performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

[0005] In some embodiments of the present disclosure, the determining of the working condition of the vehicle according to the multi-dimensional sensing data comprises: determining multi-dimensional change data according to the multi-dimensional sensing data, wherein the multi-dimensional change data includes at least one of first direction change data, second direction change data and third direction change data, the first direction is a vertical direction, the second direction is a vehicle travel direction, and the third direction is perpendicular to the first direction and the second direction respectively; determining the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional change data.

[0006] In some embodiments of the present disclosure, the multi-dimensional sensing data includes battery cell surface strain data, and the determining of the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional change data comprises at least one of the following steps: determining a whole vehicle load state according to the first direction change data; determine whether the working condition of the vehicle is a rough road condition according to second direction change data and third direction change data of both sides of the vehicle; determine whether the working condition of the vehicle is any one of a high-low speed turning condition, a climbing condition, and a front-rear axle direction downhill condition according to second direction change data and third direction change data of one side of the vehicle; determine whether the working condition of the vehicle is a charging and discharging condition according to the surface strain data of the battery monomer.

[0007] In some embodiments of the present disclosure, the safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: controlling the working mode of the vehicle battery pack according to the working condition of the vehicle.

[0008] In some embodiments of the present disclosure, the controlling of the working mode of the vehicle battery pack according to the working condition of the vehicle comprises at least one of the following steps: controlling the vehicle battery pack to enter a high-power output mode when the vehicle is in at least one of a rough road condition, a high-speed turning condition, and a climbing condition; controlling the power of the vehicle battery pack to change from low to high according to the amount of cargo from small to large when the vehicle is in a cargo carrying state; controlling the vehicle battery pack to perform kinetic energy recovery when the vehicle is in a downhill condition.

[0009] In some embodiments of the present disclosure, the safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: obtaining a battery pack charging state and an external environment condition, wherein the battery pack charging state comprises change data of battery pack charging power and current, and the external environment condition is an ambient temperature; obtaining multi-dimensional change data of the battery pack, wherein the multi-dimensional change data comprises change data of at least one of battery voltage, charging and discharging current, and temperature; judging whether the battery is safe according to the battery pack charging state, the external environment condition, the multi-dimensional change data, and the multi-dimensional sensing data.

[0010] In some embodiments of the present disclosure, the judging whether the battery is safe according to the battery pack charging state, the external environment condition, the multi-dimensional change data, and the multi-dimensional sensing data comprises: judging whether the battery charging and discharging is abnormal according to at least one of the surface strain data of the battery monomer, the tab temperature change data, and the pressure difference change data under different charging and discharging currents.

[0011] In some embodiments of the present disclosure, the safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: determining multi-dimensional change data according to the multi-dimensional sensing data, wherein the multi-dimensional change data comprises change data of at least one of battery voltage, charging and discharging current and temperature; estimating the safe life of the battery pack according to the multi-dimensional sensing data and the multi-dimensional change data.

[0012] In some embodiments of the present disclosure, the multi-dimensional sensing data of the vehicle battery pack obtained by the optical fiber sensor comprises: obtaining multi-dimensional sensing data of a plurality of battery points of each battery monomer in the vehicle battery pack by the optical fiber sensor, wherein the optical fiber sensor is arranged in a groove on the inner side of the battery shell of each battery monomer in the vehicle battery pack, and the battery point comprises at least one of the battery tab and the battery shell.

[0013] In some embodiments of the present disclosure, the safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: monitoring the battery temperature change of all battery monomers, wherein the battery temperature change comprises the change of the heating state of the battery tab and the battery shell; According to the battery temperature change, the heat dissipation of the battery monomer whose battery temperature change is greater than the predetermined value is carried out by using heat management.

[0014] In some embodiments of the present disclosure, the multi-dimensional sensing data comprises battery monomer surface strain data, and the safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: monitoring the battery monomer surface strain data; determining whether the difference between the current predetermined time period battery monomer surface strain data and the previous predetermined time period battery monomer surface strain data is greater than a predetermined value; In the case where the difference is greater than the predetermined value, it is determined that the battery pack fails, and a warning is given.

[0015] In some embodiments of the present disclosure, the multi-dimensional sensing data comprises battery monomer surface strain data, and the safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: monitoring the battery monomer surface strain data; determining whether the current battery monomer surface strain data is greater than a first distance; In the case where the current battery monomer surface strain data is greater than the first distance, it is determined whether the current battery monomer surface strain data is recovered after a predetermined time interval; In a case where the current battery cell surface strain data is not recovered after a predetermined time interval, it is determined that the battery pack is faulty, and a warning is given.

[0016] In some embodiments of the present disclosure, the determining the working condition of the vehicle according to the multi-dimensional sensing data comprises: acquiring vehicle data, wherein the vehicle data comprises at least one of vehicle speed, vehicle vertical acceleration, vehicle lateral angular velocity and vehicle pitch angle; determining the working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

[0017] According to another aspect of the present disclosure, a battery pack control device is provided, comprising: a data acquisition module configured to acquire multi-dimensional sensing data of a vehicle battery pack by an optical fiber sensor, wherein the multi-dimensional sensing data comprises at least one of electrical parameters and non-electrical parameters, the electrical parameters comprising at least one of current and voltage of the battery pack, and the non-electrical parameters comprising at least one of temperature and strain of the battery pack; a working condition determination module configured to determine the working condition of the vehicle according to the multi-dimensional sensing data; a safety control module configured to perform safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

[0018] According to another aspect of the present disclosure, a battery pack control device is provided, comprising: a memory configured to store instructions; a processor coupled to the memory, the processor being configured to execute the battery pack control method according to any one of the above embodiments based on the instructions stored in the memory.

[0019] According to another aspect of the present disclosure, a battery pack is provided, comprising a plurality of battery cells, each battery cell comprising an optical fiber sensor disposed in a groove on the inside of the shell of the battery cell, wherein: the optical fiber sensor is configured to collect multi-dimensional sensing data of a plurality of battery points of each battery cell in the vehicle battery pack and send the multi-dimensional sensing data to a battery pack control device, wherein the multi-dimensional sensing data comprises at least one of electrical parameters and non-electrical parameters, the electrical parameters comprising at least one of current and voltage of the battery pack, and the non-electrical parameters comprising at least one of temperature and strain of the battery pack, the multi-dimensional sensing data being used by the battery pack control device to determine the working condition of the vehicle and to perform safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

[0020] According to another aspect of the present disclosure, a battery pack control system is provided, comprising the battery pack control device according to any one of the above embodiments.

[0021] In some embodiments of the present disclosure, the battery pack control system further comprises the battery pack as claimed in any one of the preceding embodiments.

[0022] According to another aspect of the present disclosure, a vehicle is provided, comprising the battery pack control system as claimed in any one of the preceding embodiments.

[0023] According to another aspect of the present disclosure, a computer readable storage medium is provided, wherein the computer readable storage medium stores computer instructions, and the instructions, when executed by a processor, implement the battery pack control method as claimed in any one of the preceding embodiments.

[0024] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program, and the computer program, when executed by a processor, implements the battery pack control method as claimed in any one of the preceding embodiments.

[0025] The present disclosure can collect multi-dimensional data dynamic information of force, electricity, heat, gas, etc. of the battery in real time, and can realize high safety and high performance monitoring and application of the battery pack in the whole life cycle. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0027] Figure 1 A schematic diagram of some embodiments of the battery pack control method of the present disclosure.

[0028] Figure 2 A connection diagram of the battery and the optical fiber of the battery pack of some embodiments of the present disclosure.

[0029] Figure 3 A schematic diagram of some embodiments of the battery pack control device of the present disclosure.

[0030] Figure 4 A structural schematic diagram of other embodiments of the battery pack control device of the present disclosure.

[0031] Figure 5 A structural schematic diagram of some embodiments of the battery pack control system of the present disclosure.

[0032] Figure 6 A structural schematic diagram of other embodiments of the battery pack control system of the present disclosure. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present disclosure will be described clearly and completely in the embodiments of the present disclosure in combination with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. The description of the at least one example embodiment is actually only illustrative, but not as any limitation on the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present disclosure.

[0034] Unless specifically stated, the relative arrangement of the components and steps, numerical expressions, and values shown in the embodiments are not meant to limit the scope of the present disclosure.

[0035] It should be understood that the size of each part shown in the drawings is not drawn in accordance with the actual proportion relationship for the convenience of description.

[0036] The technology, methods and devices known to those of ordinary skill in the relevant art can not be discussed in detail, but should be considered as part of the authorized description under appropriate circumstances.

[0037] In all examples shown and discussed herein, any specific value should be interpreted as merely exemplary and not as a limitation. Thus, other examples of example embodiments can have different values.

[0038] It should be noted that similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0039] Figure 1 The schematic diagram of some embodiments of the battery pack control method of the present disclosure. Preferably, Figure 1 The embodiments can be performed by the battery pack control device of the present disclosure or the battery pack control system of the present disclosure or the battery pack of the present disclosure or the vehicle of the present disclosure. As Figure 1 The method shown in Figure 1 may include at least one of steps 100 to 300.

[0040] In step 100, multi-dimensional sensing data of a vehicle battery pack is acquired by an optical fiber sensor, wherein the multi-dimensional sensing data includes at least one of electrical parameters and non-electrical parameters, the electrical parameters include at least one of current and voltage of the battery pack, and the non-electrical parameters include at least one of temperature and strain of the battery pack.

[0041] In some embodiments of the present disclosure, the electrical parameters can also include internal resistance, etc.

[0042] In some embodiments of the present disclosure, the non-electrical parameters can further include deformation, air pressure, gas species, etc.

[0043] In some embodiments of the present disclosure, the strain of the battery pack can be replaced by the expansion force of the battery, the battery expansion displacement, the battery surface deformation, or the battery surface strain.

[0044] In some embodiments of the present disclosure, step 100 can include obtaining multi-dimensional sensing data of a plurality of battery points of each battery monomer in the vehicle battery pack by an optical fiber sensor, wherein the optical fiber sensor is arranged in a groove on the inner side of the battery shell of each battery monomer in the vehicle battery pack, and the battery points include at least one of the battery tab and the battery shell.

[0045] Figure 2 The connection diagram of the battery and the optical fiber of the battery pack of some embodiments of the present disclosure is shown. As shown in Figure 2 The connection method of the battery and the optical fiber of the battery pack can include at least one of steps 1 to 4.

[0046] Step 1, the optical fiber sensor 1 is continuously bent in U shape according to the length direction from the battery tab to the shell, the optical fiber sensor 1 is embedded through the aluminum plate fixing support, forming an integrated optical fiber sensing unit, so as to ensure the effective layout of the optical fiber sensor 1 at the tab, the shell edge and the center position.

[0047] The optical fiber sensor of the present disclosure has the advantages of corrosion resistance and anti-electromagnetic interference, and can realize multi-point simultaneous monitoring by using distributed measurement.

[0048] Step 2, the battery monomer shell 2 is guided according to the direction of the integrated optical fiber sensing unit, a groove with a single side of 0.8mm depth and 2mm width is made, forming a compatible battery monomer, ensuring smooth surface, and the overall surface of the shell is free of concave and convex.

[0049] Step 3, the integrated optical fiber sensing unit is combined with the compatible battery monomer, so that the optical fiber sensing is in full contact with the surface of the battery monomer groove, and the optical fiber sensing connection point is on the tab side. According to this assembly process, a plurality of battery monomers 3 are assembled.

[0050] Step 4, the assembled 6 groups of batteries 4 are arranged horizontally, and fixing supports are added on both sides to ensure that each group of batteries 4 is not loose. The positive and negative tabs of each group of batteries 4 are fixed, all the optical fiber sensing points are connected in parallel, and finally connected to the controller port of the battery pack control device.

[0051] In some embodiments of the present disclosure, step 100 can include: using a fiber sensor to perform distributed multipoint monitoring, sensing and collecting electrical parameters such as current, voltage, internal resistance of the battery, and non-electrical parameters such as temperature, strain, deformation, air pressure, and gas species; monitoring the internal material aging caused by the embedding and de-embedding of lithium ions, the gas production and lithium precipitation caused by the side reaction, and other phenomena during long-term use of the battery; and providing a low-cost fiber sensing system that can simultaneously monitor multiple parameters of the battery through some special structural design.

[0052] In some embodiments of the present disclosure, the special structural design is a fiber U-shaped layout arranged away from the center along the edge of the battery, so that the fiber length can be effectively reduced while being closer to the tab.

[0053] In some embodiments of the present disclosure, step 100 can include: collecting real-time dynamic information of multi-dimensional data such as force, electricity, heat, and gas of the battery, for example, real-time data such as surface micron changes of the battery during charging and discharging, tab temperature rise change rate, and 0.01% full data.

[0054] In step 200, the working condition of the vehicle is determined according to the multi-dimensional sensing data.

[0055] In some embodiments of the present disclosure, step 200 can include: obtaining vehicle data, wherein the vehicle data includes at least one of vehicle speed, vehicle vertical acceleration, vehicle lateral angular velocity, and vehicle pitch angle; and determining the working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

[0056] In some embodiments of the present disclosure, step 200 can include at least one of steps 210 to 220.

[0057] In step 210, multi-dimensional change data is determined according to the multi-dimensional sensing data, wherein the multi-dimensional change data includes at least one of first direction (Z direction) change data, second direction (X direction) change data, and third direction (Y direction) change data, the first direction is a vertical direction, the second direction is a vehicle travel direction, and the third direction is perpendicular to the first direction and the second direction.

[0058] In step 220, the working condition of the vehicle is determined according to the multi-dimensional sensing data and the multi-dimensional change data.

[0059] In step 300, the battery pack is controlled according to the multi-dimensional sensing data and the working condition of the vehicle.

[0060] In some embodiments of the present disclosure, the multi-dimensional sensing data can include battery cell surface strain data. Step 300 can include at least one of steps 310 to 340.

[0061] In step 310, the whole vehicle load state is determined according to the first direction change data.

[0062] In some embodiments of the present disclosure, step 310 can include determining the whole vehicle load state according to the waveform in the Z direction change data.

[0063] In step 320, whether the working condition of the vehicle is a rough road is determined according to the second direction change data and the third direction change data of the two sides of the vehicle.

[0064] In some embodiments of the present disclosure, step 320 can include determining whether the working condition of the vehicle is a rough road according to the X and Y direction data of the two sides.

[0065] In step 330, whether the working condition of the vehicle is any one of a high-low speed turning condition, a climbing condition, and a downhill condition of the front and rear axle directions is determined according to the second direction change data and the third direction change data of one side of the vehicle.

[0066] In some embodiments of the present disclosure, step 330 can include determining whether the working condition of the vehicle is any one of a high-low speed turning condition, a climbing condition, and a downhill condition of the front and rear axle directions according to the X and Y direction data of one side.

[0067] In step 340, whether the working condition of the vehicle is a charging and discharging condition is determined according to the battery cell surface strain data.

[0068] In some embodiments of the present disclosure, step 340 can include determining whether the working condition of the vehicle is a charging and discharging condition according to the cell surface strain data.

[0069] In some embodiments of the present disclosure, step 300 can include controlling the working mode of the vehicle battery pack according to the working condition of the vehicle.

[0070] In some embodiments of the present disclosure, the step of controlling the working mode of the vehicle battery pack according to the working condition of the vehicle can include at least one of steps 301 to 303.

[0071] In step 301, the vehicle battery pack is controlled to enter a high-power output mode when the vehicle is in at least one of a rough road, a high-speed turning, and a climbing condition.

[0072] In some embodiments of the present disclosure, step 301 can include identifying that the vehicle is in at least one of a rough road, a high-speed turning, and a climbing condition by detecting the vehicle state and the battery shell physical change condition, and supporting the decision of the vehicle entering the high-power output mode.

[0073] In step 302, when the vehicle is in a cargo state, the vehicle battery pack power is controlled to change from low to high according to the cargo amount from small to large.

[0074] In step 303, when the vehicle is in a downhill working condition, the vehicle battery pack is controlled to perform kinetic energy recovery, and the battery instantaneously heats up.

[0075] In some embodiments of the present disclosure, the step of controlling the working mode of the vehicle battery pack according to the working condition of the vehicle can include: in the charging mode, controlling the maximum heat generation of the battery, and in the discharging mode, monitoring the high and low changes of the battery interval.

[0076] In some embodiments of the present disclosure, the multi-dimensional sensing data can include battery cell surface strain data. Step 300 can include at least one of steps 350 to 370.

[0077] In step 350, the battery pack charging state and external environmental conditions are obtained, wherein the battery pack charging state includes battery pack charging power and current change data, and the external environmental conditions are environmental temperature.

[0078] In step 360, multi-dimensional change data of the battery pack is obtained, wherein the multi-dimensional change data includes change data of at least one of battery voltage, charging and discharging current, and temperature.

[0079] In step 370, it is judged whether the battery is safe according to the battery pack charging state, the external environmental conditions, the multi-dimensional change data, and the multi-dimensional sensing data.

[0080] In some embodiments of the present disclosure, step 370 can include: under different charging and discharging currents, judging whether the battery charging and discharging is abnormal according to at least one of the battery cell surface strain data, the tab temperature change data, and the pressure difference change data.

[0081] In some embodiments of the present disclosure, step 300 can include: identifying whether the battery pack is in a high-power charging, long-time, extreme weather, or other state through the battery system charging state and external environmental conditions, and adopting a corresponding battery pack power mode and thermal management mode.

[0082] In some embodiments of the present disclosure, step 300 can include: determining different charging modes such as overcharging, high-power fast charging, and low-power fast charging by monitoring the charging power and current change of the battery. For example: different charging modes such as overcharging, high-power fast charging, and low-power fast charging correspond to different charging power and current changes, and different charging power and current changes will directly affect the change of the battery, so that it can be determined whether the current power change is normal charging.

[0083] In some embodiments of the present disclosure, the external environment refers to the air temperature, and the optical fiber can identify the external environment through waveform changes. Whether the change of the battery under extremely high or low environmental temperature affects the service life of the battery compared with the conventional data.

[0084] In some embodiments of the present disclosure, step 300 can include: in the case of high-power charging, adopting a full-load thermal management mode, and monitoring whether the battery is in a safe temperature range.

[0085] In some embodiments of the present disclosure, step 300 can include: in the case of long-time charging and discharging, adopting a multi-mode power and thermal management mode, corresponding to different modes under different driving conditions such as high-speed driving and climbing of the whole vehicle. The above embodiments of the present disclosure mainly depend on the deviation of the data under the change of the battery temperature and the database in the algorithm to determine the mode change and the safety of the battery.

[0086] In some embodiments of the present disclosure, step 300 can include: determining multi-dimensional change data according to the multi-dimensional sensing data, wherein the multi-dimensional change data includes change data of at least one of the battery voltage, the charging and discharging current, and the temperature; and estimating the safe service life of the battery pack according to the multi-dimensional sensing data and the multi-dimensional change data.

[0087] In some embodiments of the present disclosure, step 300 can include: monitoring the battery temperature change of all battery monomers, wherein the battery temperature change includes the change of the heating state of the battery tab and the battery shell; and adopting thermal management to dissipate heat for the battery monomer whose battery temperature change is greater than a predetermined value.

[0088] In some embodiments of the present disclosure, step 300 can include: determining the rate current according to the heating state of the battery tab and the shell, calculating the current of the battery charging and discharging through the heat change large model data, and determining the working mode of the thermal management.

[0089] In some embodiments of the present disclosure, step 300 can include: monitoring the temperature change of the tab by using the optical fiber sensor, or also using optical signal modulation to convert the electrical signal into an optical signal; and then estimating the change of the current through an algorithm.

[0090] In some embodiments of the present disclosure, the battery is usually charged and discharged at a rate of 2C-3C, and the peak value of the charging and discharging is the maximum battery maximum rate. Under the conventional condition, it is always kept working at the maximum rate.

[0091] In some embodiments of the present disclosure, step 300 can include: in order to make the battery work at the maximum rate, it is necessary to monitor the temperature change of the battery, accurately dissipate heat for the battery through thermal management, and realize the maximum working capacity of the battery.

[0092] In some embodiments of the present disclosure, the multi-dimensional sensing data can include battery cell surface strain data, and step 300 can include at least one of steps 304 to 306.

[0093] In step 304, battery cell surface strain data is monitored.

[0094] In step 305, it is determined whether a difference between the battery cell surface strain data of a current predetermined time period and the battery cell surface strain data of a previous predetermined time period is greater than a predetermined value.

[0095] In step 306, in the case where the difference is greater than the predetermined value, it is determined that the battery pack is faulty, and a warning is given.

[0096] In some embodiments of the present disclosure, the multi-dimensional sensing data can include battery cell surface strain data, and step 300 can include at least one of steps 311 to 314.

[0097] In step 311, battery cell surface strain data is monitored.

[0098] In step 312, it is determined whether the current battery cell surface strain data is greater than a first distance.

[0099] In step 313, in the case where the current battery cell surface strain data is greater than the first distance, it is determined whether the current battery cell surface strain data recovers after a predetermined time interval.

[0100] In step 314, in the case where the current battery cell surface strain data does not recover after the predetermined time interval, it is determined that the battery pack is faulty, and a warning is given.

[0101] In some embodiments of the present disclosure, step 300 can include monitoring real-time information such as battery discharge heat, current, battery pack gas pressure, and the like, analyzing battery safety performance curves, and adjusting a warning mode according to changes in vehicle light, medium, and heavy load modes.

[0102] In some embodiments of the present disclosure, in the case of heavy load, the change in the battery heat generation interval is greater, and the power of discharge and recovered kinetic energy is increased, such as continuous expansion of the battery surface, which is greater than the change in previous data. Through comparison by algorithm, a basis for directly affecting the battery life is given, and a warning can be given at the same time.

[0103] In some other embodiments of the present disclosure, the change interval of the battery in the case of light and medium load is smaller than that in the case of heavy load, and the warning principle is the same.

[0104] The above-mentioned embodiments of the present disclosure solve the limitation that the battery management system of a new energy commercial vehicle can only monitor the current, voltage and external temperature of some points of the battery, and cannot fully control the battery accurately and efficiently by using an optical fiber sensor and a large computing power control system. The above-mentioned embodiments of the present disclosure integrate a multi-parameter sensor that can monitor the temperature, stress, deformation, gas and other parameters of the internal chemical and physical reactions of the battery, analyze and identify the whole vehicle load state, rough road, high and low speed turning, climbing, descending state, charging and discharging and other working conditions, and can diagnose, manage safety and optimize performance in real time, thereby improving the safety and energy saving of the whole vehicle battery system throughout its life cycle.

[0105] Figure 3 A schematic diagram of some embodiments of the battery pack control device of the present disclosure. As shown in Figure 3 The battery pack control device of the present disclosure can include a data acquisition module 31, a working condition determination module 32 and a safety control module 33.

[0106] The data acquisition module 31 is configured to acquire multi-dimensional sensing data of a vehicle battery pack by an optical fiber sensor, wherein the multi-dimensional sensing data includes at least one of an electrical parameter and a non-electrical parameter, the electrical parameter includes at least one of a current and a voltage of the battery pack, and the non-electrical parameter includes at least one of a temperature and a strain of the battery pack.

[0107] In some embodiments of the present disclosure, the data acquisition module 31 can be configured to acquire multi-dimensional sensing data of a plurality of battery points of each battery monomer in the vehicle battery pack by an optical fiber sensor, wherein the optical fiber sensor is arranged in a groove on the inner side of the battery shell of each battery monomer in the vehicle battery pack, and the battery points include at least one of a battery tab and a battery shell.

[0108] The working condition determination module 32 is configured to determine the working condition of the vehicle according to the multi-dimensional sensing data.

[0109] In some embodiments of the present disclosure, the working condition determination module 32 can be configured to acquire vehicle data, wherein the vehicle data includes at least one of a vehicle speed, a vehicle vertical acceleration, a vehicle lateral angular velocity and a vehicle pitch angle; and determine the working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

[0110] In some embodiments of the present disclosure, the working condition determination module 32 can be configured to determine multi-dimensional change data according to the multi-dimensional sensing data, wherein the multi-dimensional change data includes at least one of first direction change data, second direction change data and third direction change data, the first direction is a vertical direction, the second direction is a vehicle travel direction, and the third direction is perpendicular to the first direction and the second direction; and determine the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional change data.

[0111] In some embodiments of the present disclosure, the multi-dimensional sensing data can include battery cell surface strain data, and the working condition determining module 32, in determining the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional change data, can be configured to perform at least one of the following operations: determining the whole vehicle load state according to the first direction change data; determining whether the working condition of the vehicle is a rough road condition according to the second direction change data and the third direction change data of the two sides of the vehicle; determining whether the working condition of the vehicle is any one of a high-low speed turning condition, a climbing condition, and a front-rear axle direction downhill condition according to the second direction change data and the third direction change data of one side of the vehicle; and determining whether the working condition of the vehicle is a charging and discharging condition according to the battery cell surface strain data.

[0112] The safety control module 33 is configured to perform safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

[0113] In some embodiments of the present disclosure, the safety control module 33 can be configured to control the working mode of the vehicle battery pack according to the working condition of the vehicle.

[0114] In some embodiments of the present disclosure, the safety control module 33, in controlling the working mode of the vehicle battery pack according to the working condition of the vehicle, can be configured to perform at least one of the following operations: controlling the vehicle battery pack to enter a high-power output mode when the vehicle is in at least one of a rough road condition, a high-speed turning condition, and a climbing condition; controlling the vehicle battery pack power to change from low to high according to the load amount from small to large when the vehicle is in a load state; and controlling the vehicle battery pack to perform kinetic energy recovery when the vehicle is in a downhill condition.

[0115] In some embodiments of the present disclosure, the safety control module 33 can be configured to obtain battery pack charging state and external environmental conditions, wherein the battery pack charging state includes change data of battery pack charging power and current, and the external environmental conditions are environmental temperature; obtain multi-dimensional change data of the battery pack, wherein the multi-dimensional change data includes change data of at least one of battery voltage, charging and discharging current, and temperature; and determine whether the battery is safe according to the battery pack charging state, the external environmental conditions, the multi-dimensional change data, and the multi-dimensional sensing data.

[0116] In some embodiments of the present disclosure, the safety control module 33, in determining whether the battery is safe according to the battery pack charging state, the external environmental conditions, the multi-dimensional change data, and the multi-dimensional sensing data, can be configured to determine whether the battery charging and discharging is abnormal according to at least one of the battery cell surface strain data, the tab temperature change data, and the differential pressure change data under different charging and discharging currents.

[0117] In some embodiments of this disclosure, the safety control module 33 may be configured to determine multidimensional change data based on the multidimensional sensing data, wherein the multidimensional change data includes change data of at least one of battery voltage, charging and discharging current and temperature; and to estimate the safe life of the battery pack based on the multidimensional sensing data and the multidimensional change data.

[0118] In some embodiments of this disclosure, the safety control module 33 can be configured to monitor the battery temperature changes of all battery cells, wherein the battery temperature changes include the changes in the heating state of the battery tabs and the battery casing; and based on the battery temperature changes, thermal management is used to dissipate heat from battery cells whose battery temperature changes exceed a predetermined value.

[0119] In some embodiments of this disclosure, the multidimensional sensing data may include battery cell surface strain data. The safety control module 33 may be configured to monitor the battery cell surface strain data; determine whether the difference between the battery cell surface strain data in the current predetermined time period and the battery cell surface strain data in the previous predetermined time period is greater than a predetermined value; and if the difference is greater than the predetermined value, determine that the battery pack is faulty and issue an early warning.

[0120] In some embodiments of this disclosure, the multidimensional sensing data includes battery cell surface strain data. The safety control module 33 can be configured to monitor the battery cell surface strain data; determine whether the current battery cell surface strain data is greater than a first distance; if the current battery cell surface strain data is greater than the first distance, determine whether the current battery cell surface strain data recovers after a predetermined time interval; if the current battery cell surface strain data does not recover after the predetermined time interval, determine that the battery pack is faulty and issue an early warning.

[0121] In some embodiments of this disclosure, the battery pack control device may also be configured to perform the battery pack control method described in any of the above embodiments of this disclosure.

[0122] Figure 4 This is a schematic diagram of the structure of some other embodiments of the battery pack control device of this disclosure. For example... Figure 4 As shown, the battery pack control device includes a memory 41 and a processor 42.

[0123] The memory 41 is used to store instructions, and the processor 42 is coupled to the memory 41. The processor 42 is configured to implement the battery pack control method described in any of the above embodiments of this disclosure based on the execution of instructions stored in the memory.

[0124] like Figure 4As shown, the battery pack control device further comprises a communication interface 43 for information interaction with other devices. Meanwhile, the battery pack control device further comprises a bus 44, and the processor 42, the communication interface 43 and the memory 41 complete communication with each other through the bus 44.

[0125] The memory 41 can contain a high-speed RAM memory, and can also include a non-volatile memory, such as at least one disk memory. The memory 41 can also be a memory array. The memory 41 can also be divided into blocks, and the blocks can be combined into a virtual volume according to certain rules.

[0126] In addition, the processor 42 can be a central processing unit CPU, or can be an application specific integrated circuit ASIC, or one or more integrated circuits configured to implement embodiments of the present disclosure.

[0127] Figure 2 A schematic diagram of a battery pack of some embodiments of the present disclosure is also given. As shown, Figure 2 As shown, the battery pack of the present disclosure can include 6 groups of batteries 4, each group of batteries 4 including a plurality of battery monomers 3, and each battery monomer 3 including a battery shell 2 and an optical fiber sensor 1.

[0128] The optical fiber sensor 1 is arranged in a groove on the inner side of the shell 2 of the battery monomer 3.

[0129] The optical fiber sensor 1 is configured to collect multi-dimensional sensing data of a plurality of battery points of each battery monomer 3 in the vehicle battery pack, and send the multi-dimensional sensing data to the battery pack control device, wherein the multi-dimensional sensing data includes at least one of an electrical parameter and a non-electrical parameter, the electrical parameter includes at least one of a current and a voltage of the battery pack, and the non-electrical parameter includes at least one of a temperature and a strain of the battery pack, the multi-dimensional sensing data is used for the battery pack control device to determine the working condition of the vehicle, and the battery pack is controlled according to the multi-dimensional sensing data and the working condition of the vehicle.

[0130] Figure 5 A structural schematic diagram of some embodiments of the battery pack control system of the present disclosure is given. As shown, Figure 5 As shown, the battery pack control system includes a battery pack control device 51 and an optical fiber sensor 52.

[0131] The battery pack control device 51 can be implemented as the battery pack control device described in any of the above embodiments.

[0132] The optical fiber sensor 52 is arranged in a groove on the inner side of the battery shell of each battery monomer in the vehicle battery pack, and is configured to collect multi-dimensional sensing data of a plurality of battery points of each battery monomer in the vehicle battery pack, and send the multi-dimensional sensing data to the battery pack control device 51.

[0133] Figure 6 Structure diagram of another embodiment of the battery pack control system of the present disclosure. As shown in Figure 6 , the battery pack control system comprises a battery management system (BMS) 61, an optical fiber sensor 62, a vehicle control unit (VCU) 63, a cloud server 64, a demodulator 65 and a battery pack 66.

[0134] Figure 6 The battery pack 66 of the embodiment can be the battery pack of any of the above embodiments of the present disclosure, for example, the battery pack 4 of the embodiment of the present disclosure. Figure 2 The battery pack 4 of the embodiment of the present disclosure.

[0135] Figure 6 The optical fiber sensor 62 of the embodiment of the present disclosure can be the optical fiber sensor of any of the above embodiments of the present disclosure, for example, the optical fiber sensor 1 of the embodiment of the present disclosure. Figure 2 The optical fiber sensor 1 of the embodiment of the present disclosure. Figure 5 The optical fiber sensor 52 of the embodiment of the present disclosure.

[0136] In some embodiments of the present disclosure, as shown in Figure 6 , the optical fiber sensor 62 can comprise a grating, a cladding and a core, the grating is used for reflecting and transmitting incident light to produce reflected light and transmitted light, and grating conduction is realized.

[0137] The functions of the battery pack control device of the present disclosure can be realized as the functions of the battery management system (BMS) 61, the vehicle control unit (VCU) 63 and the cloud server 64.

[0138] The vehicle control unit (VCU) 63 is provided with a vehicle as shown in Figure 6 . A vehicle control unit (VCU) system is provided for Figure 6 the vehicle model, a software system simulating the vehicle operation and battery communication mode control is provided. The software system of the battery pack control device of the present disclosure is stored in the battery management system (BMS) 61, the vehicle control unit (VCU) 63 and the cloud server 64.

[0139] The vehicle control unit (VCU) 63 is configured to receive signals from the battery management system (BMS) 61 through the CAN (controller area network) bus, process the signals through the software system, and send control signals to the bus through the CAN line to control other actuators.

[0140] The cloud server 64 is configured to perform multi-parameter monitoring.

[0141] The optical fiber sensor 62 is configured to transmit signals to the battery management system (BMS) 61 through the demodulator 65, and then send the signals to the cloud server 64 through the network.

[0142] The cloud server 64 is configured to transmit the multi-element data calculated by the intelligent algorithm to the battery management system (BMS) 61, so as to complete real-time analysis and decision-making. In long-period data calculation, the predictability and efficiency of the battery management system (BMS) 61 can be improved through a big data model and artificial intelligence technology.

[0143] In some embodiments of the present disclosure, the cloud server 64 can be configured to compare the voltage, current, temperature and other data of the battery and the whole vehicle working condition change data after collecting all the data, obtain the battery internal resistance change value, and determine the current state executable charging and discharging capacity.

[0144] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to mainly analyze and decide the capacity of the external request for charging and discharging of the battery after completing real-time analysis and decision-making, such as any current demand of 500, 600, 100, 155A and the like required for charging and discharging in the next second; and estimate the safe service life of the battery through the subtle structure and temperature change of the battery.

[0145] In some embodiments of the present disclosure, the long-period calculation can be the difference value of several full charging and discharging cycles, such as 5-20 times of data change, which is estimated by algorithm comparison to improve the single machine estimation capacity of the BMS.

[0146] In some embodiments of the present disclosure, the optical fiber sensor 62 can be configured to identify the working condition information of the vehicle in special working conditions and dynamically monitor the surface strain of the optical fiber sensor 62 and the battery. The battery management system (BMS) 61 can be configured to compare the reference signal with the strain signal to identify the process of the surface strain of the battery. For example, the surface strain is obviously increased during charging, and the surface strain is obviously decreased during discharging. In order to increase the identification accuracy, the battery management system (BMS) 61 can intelligently change the initial value of the surface strain of the battery to adapt to the oscillation amplitude of the surface strain of the battery as the charging and discharging continues.

[0147] In some embodiments of the present disclosure, since the battery is a chemical performance, the reference value will change constantly, and the present disclosure can only ensure the accuracy of the data by continuously correcting the initial value through the algorithm.

[0148] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to compare the battery charging and discharging data with the same data of the last period each time to adjust the data change rule.

[0149] In some embodiments of the present disclosure, the reference signal is the predicted value of the database and algorithm, the strain signal is the real-time change or special change signal, and the prediction value and real-time value are compared. If there is a large difference, the fault can be predicted.

[0150] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to determine the working condition information through the optical fiber itself, and comprehensively determine and correct the execution information of each controller in combination with the data changes of the vehicle power demand, the motor, the brake, etc.

[0151] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to interact with the vehicle controller (VCU) for information changes of the battery pack 66.

[0152] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to control the charging and discharging of the battery after receiving the instruction signal of the vehicle controller (VCU) 63; record the change amplitude of the surface strain every 100 cycles, estimate the strain decline trend according to the rate cycle; record and send the battery degradation index information, early warning battery health status; perform availability judgment, determine the single body and system fault level, estimate the life, and determine the power, etc.

[0153] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to judge whether the battery charging and discharging is abnormal by monitoring the battery surface deformation, the tab temperature change, the pressure difference change, etc. under different charging and discharging currents.

[0154] In some embodiments of the present disclosure, the battery fault level is generally 4 levels, the voltage range is 2.6-3.2V, the temperature is -10-45 degrees, and the maximum fault is exceeded. If it changes linearly, it is normal. If the upper and lower line deviation in the range is large, it is a level fault.

[0155] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to perform different processing and early warning when the battery pack is in different fault levels, for example: in the case that the battery pack is in the first fault level, fault early warning is performed; in the case that the battery pack is in the second fault level, fault early warning is performed, and the first proportion of power limiting operation is performed; in the case that the battery pack is in the third fault level, fault early warning is performed, and the second proportion of power limiting operation is performed, and the first proportion is less than the second proportion; in the case that the battery pack is in the fourth fault level, fault early warning is performed, and shutdown and power-off processing is performed.

[0156] In some embodiments of the present disclosure, the first proportion is 50%; and the second proportion is 20%.

[0157] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to analyze and identify the vehicle load state, rough road, high-speed and low-speed turning, climbing, downhill state, charging and discharging, etc. by combining the deformation characteristics of the optical fiber sensor 62, the algorithm, the vehicle speed, the vehicle vertical acceleration, the vehicle lateral angular velocity, the vehicle pitch angle, etc. Real-time information such as battery discharge heat, current, battery pack gas pressure, etc. is monitored synchronously, the battery safety performance curve is analyzed, and the warning mode is adjusted.

[0158] In some embodiments of the present disclosure, the deformation characteristics and the algorithm include that the internal waveform change of the optical fiber sensor can form an infinite number of modes, the algorithm and the model are obtained from the database through calibration, and the change waveform of each feature is determined based on the algorithm. All stress changes can be obtained by waveform and algorithm to estimate the values of temperature, stress, gas pressure, etc.

[0159] In some embodiments of the present disclosure, the data change and the change trend of the strain are combined with the request change given by the vehicle controller, and are analyzed by the cloud big data to finally determine the component state and the execution information.

[0160] In some embodiments of the present disclosure, the optical fiber sensor is a more accurate sensing tool for the vehicle controller and the BMS, mainly for predicting the difference between the data and the actual data, and the battery safety change can be determined by the vehicle state change such as reducing power and thermal management adjustment. Any difference data is compared by the multi-controller algorithm and the cloud big data, and the battery safety value is obtained by comprehensive analysis.

[0161] The optical fiber conduction multi-dimensional information fusion battery pack and control system of the above-mentioned embodiments of the present disclosure includes: an optical fiber sensor, a battery monomer with a groove, a demodulator, a BMS, etc. The vehicle controller is installed on the vehicle, the cloud server is connected to the cloud server by a local computing device, the communication information is evaluated by the comprehensive data of the vehicle controller and the cloud server big data algorithm, the instructions of the vehicle controller and the BMS are determined by the vehicle working condition, and the battery pack control method is executed as described in any one of the above-mentioned embodiments of the present disclosure.

[0162] The above-mentioned embodiments of the present disclosure provide a new energy commercial vehicle optical fiber conduction multi-dimensional information fusion battery pack and a control method and system. The control system includes hardware and software. The hardware includes an optical fiber sensing battery pack composed of an optical fiber sensor, a battery monomer with a groove, a demodulator, a BMS, and the like. The software is composed of an input module, a special working condition identification module, an output module, a cloud transceiver module, and the like. The optical fiber sensor is a distributed multi-point monitoring method for sensing electrical parameters such as current, voltage, and internal resistance of the battery, and non-electrical parameters such as temperature, strain, deformation, air pressure, and gas type. The above-mentioned embodiments of the present disclosure combine the vehicle controller, the vehicle speed sensor, the cloud big data, and the like to analyze and identify the vehicle load state, the rough road, the high-low speed turning, the climbing, the downhill state, the charging and discharging, and the like. The battery safety and control method of the battery and the vehicle in the long-time use process and the special working condition are comprehensively monitored and analyzed.

[0163] According to another aspect of the present disclosure, a vehicle is provided, including the battery pack control system according to any one of the above-mentioned embodiments.

[0164] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein the computer program is executed by a processor to implement the battery pack control method according to any one of the above-mentioned embodiments.

[0165] According to another aspect of the present disclosure, a computer readable storage medium is provided, wherein the computer readable storage medium stores computer instructions, and the instructions are executed by a processor to implement the battery pack control method according to any one of the above-mentioned embodiments.

[0166] In some embodiments of the present disclosure, the computer readable storage medium can be a non-transitory computer readable storage medium.

[0167] The above-mentioned embodiments of the present disclosure provide a new energy commercial vehicle optical fiber conduction multi-dimensional information fusion battery pack and a control method, device, and system. The battery multi-dimensional parameters can be monitored in real time, and the vehicle networking, big data, cloud computing, and the like are combined to achieve more accurate analysis. Therefore, the above-mentioned embodiments of the present disclosure integrate the intelligent battery pack with various sensing units such as optical fiber fine perception, break through the limitations of the traditional electrical signal transmission mode, identify the special working condition information state of the vehicle through the change of the grating conduction waveform, analyze and identify the vehicle load state of the change of the waveform in the Z direction, the rough road of the change of the double-sided X and Y directions, the high-low speed turning of the change of the single-sided X and Y directions, the downhill state of the front and rear axle directions, and the charging and discharging of the change of the cell surface, so as to improve the multi-source fine information acquisition, analysis, and decision-making ability of the battery system in the whole life cycle.

[0168] Those skilled in the art will appreciate that embodiments of the present disclosure can be provided as methods, apparatus, or computer program products. Accordingly, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure can take the form of a computer program product on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, and the like) having computer-usable program code embodied in the medium.

[0169] The present disclosure is described in reference to the flowchart and / or block diagrams of the method, apparatus (system) and computer program product according to embodiments of the present disclosure. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as a combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the flow Figure 1 one or more flows and / or blocks Figure 1 an apparatus that implements the function specified in the flow or flows and / or block or blocks.

[0170] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions executed by the computer or other programmable apparatus provide the flow Figure 1 one or more flows and / or blocks Figure 1 a step that implements the function specified in the flow or flows and / or block or blocks.

[0171] The battery pack control device, the data acquisition module, the working condition determination module and the safety control module described above can be implemented as a general-purpose processor, a programmable logic controller (PLC), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or any appropriate combination thereof for performing the functions described in the present disclosure.

[0172] So far, the present disclosure has been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein according to the above description.

[0173] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiments can be completed by hardware, or can be instructed by a program to complete the related hardware, and the program can be stored in a non-transitory computer readable storage medium. The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0174] The description of the present disclosure is given for the purpose of illustration and description, and is not intended to be exhaustive or to limit the present disclosure to the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are chosen and described in order to best explain the principles of the present disclosure and its practical application, and to enable others skilled in the art to understand the present disclosure in order to design various embodiments with various modifications for specific use cases.

Claims

1. A battery pack control method, comprising: acquiring multi-dimensional sensing data of a vehicle battery pack by an optical fiber sensor, wherein the multi-dimensional sensing data comprises at least one of electrical parameters and non-electrical parameters, the electrical parameters comprise at least one of current and voltage of the battery pack, and the non-electrical parameters comprise at least one of temperature and strain of the battery pack; determining a working condition of the vehicle according to the multi-dimensional sensing data; safely controlling the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

2. The battery pack control method according to claim 1, wherein The determining of the working condition of the vehicle according to the multi-dimensional sensing data comprises: determining multi-dimensional variation data according to the multi-dimensional sensing data, wherein the multi-dimensional variation data comprises at least one of first direction variation data, second direction variation data and third direction variation data, the first direction is a vertical direction, the second direction is a vehicle traveling direction, and the third direction is perpendicular to the first direction and the second direction; determining the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional variation data.

3. The battery pack control method according to claim 2, wherein The multi-dimensional sensing data comprises battery cell surface strain data, and the determining of the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional variation data comprises at least one of the following steps: determining a vehicle load state according to the first direction variation data; determining whether the working condition of the vehicle is a rough road according to second direction variation data and third direction variation data of both sides of the vehicle; determining whether the working condition of the vehicle is any one of a high-low speed turning working condition, a climbing working condition and a downhill working condition of front and rear axle directions according to second direction variation data and third direction variation data of one side of the vehicle; determining whether the working condition of the vehicle is a charging and discharging working condition according to the battery cell surface strain data. 4.The battery pack control method of any one of claims 1 to 3, wherein the safely controlling of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: controlling a working mode of the vehicle battery pack according to the working condition of the vehicle. 5.The battery pack control method of claim 4, wherein the controlling of the working mode of the vehicle battery pack according to the working condition of the vehicle comprises at least one of the following steps: controlling the vehicle battery pack to enter a high-power output mode when the vehicle is in at least one of a rough road, a high speed turning and a climbing working condition; controlling the vehicle battery pack power to change from low to high according to the vehicle load from small to large when the vehicle is in a load state; controlling the vehicle battery pack to perform kinetic energy recovery when the vehicle is in a downhill working condition.

6. The battery pack control method according to any one of claims 1 to 3, wherein The safely controlling of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: acquiring a battery pack charging state and an external environment condition, wherein the battery pack charging state comprises variation data of battery pack charging power and current, and the external environment condition is an ambient temperature; acquiring multi-dimensional variation data of the battery pack, wherein the multi-dimensional variation data comprises variation data of at least one of battery voltage, charging and discharging current and temperature; judging whether the battery is safe according to the battery pack charging state, the external environment condition, the multi-dimensional variation data and the multi-dimensional sensing data.

7. The battery pack control method according to claim 6, wherein The judging whether the battery is safe according to the battery pack charging state, the external environment condition, the multi-dimensional change data and the multi-dimensional sensing data comprises: Under different charging and discharging currents, judging whether the battery charging and discharging is abnormal according to at least one of the battery monomer surface strain data, the tab temperature change data and the pressure difference change data.

8. The battery pack control method according to any one of claims 1 to 3, wherein The safe control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: Determining multi-dimensional change data according to the multi-dimensional sensing data, wherein the multi-dimensional change data comprises change data of at least one of battery voltage, charging and discharging current and temperature; Estimating the safe life of the battery pack according to the multi-dimensional sensing data and the multi-dimensional change data.

9. The battery pack control method according to any one of claims 1 to 3, wherein The multi-dimensional sensing data of the vehicle battery pack obtained by the optical fiber sensor comprises: Obtaining the multi-dimensional sensing data of a plurality of battery points of each battery monomer in the vehicle battery pack by the optical fiber sensor, wherein the optical fiber sensor is arranged in a groove on the inner side of the battery shell of each battery monomer in the vehicle battery pack, and the battery points comprise at least one of the battery tab and the battery shell.

10. The battery pack control method of claim 9, wherein, The safe control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: Monitoring the battery temperature change of all battery monomers, wherein the battery temperature change comprises the heating state change of the battery tab and the battery shell; According to the battery temperature change, the battery monomer with a battery temperature change greater than a predetermined value is cooled.

11. The battery pack control method according to any one of claims 1 to 3, wherein The multi-dimensional sensing data comprises battery monomer surface strain data, and the safe control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: Monitoring the battery monomer surface strain data; Judging whether the difference between the current predetermined time period battery monomer surface strain data and the previous predetermined time period battery monomer surface strain data is greater than a predetermined value; In the case that the difference is greater than the predetermined value, it is determined that the battery pack fails and a warning is given.

12. The battery pack control method according to any one of claims 1 to 3, wherein The multi-dimensional sensing data comprises battery monomer surface strain data, and the safe control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises: Monitoring the battery monomer surface strain data; Judging whether the current battery monomer surface strain data is greater than a first distance; In the case that the current battery monomer surface strain data is greater than the first distance, judging whether the current battery monomer surface strain data is restored after a predetermined time interval; In the case that the current battery monomer surface strain data is not restored after a predetermined time interval, it is determined that the battery pack fails and a warning is given.

13. The battery pack control method according to any one of claims 1 to 3, wherein The determining the working condition of the vehicle according to the multi-dimensional sensing data comprises: Obtaining vehicle data, wherein the vehicle data comprises at least one of vehicle speed, vehicle vertical acceleration, vehicle lateral angular velocity and vehicle pitch angle; Determining the working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

14. A battery pack control device, comprising: a data acquisition module configured to acquire multi-dimensional sensing data of a battery pack of a vehicle via a fiber optic sensor, wherein the multi-dimensional sensing data comprises at least one of electrical parameters and non-electrical parameters, the electrical parameters comprising at least one of current and voltage of the battery pack, and the non-electrical parameters comprising at least one of temperature and strain of the battery pack; a working condition determination module configured to determine a working condition of the vehicle based on the multi-dimensional sensing data; a safety control module configured to perform safety control on the battery pack based on the multi-dimensional sensing data and the working condition of the vehicle.

15. A battery pack control device, comprising: a memory configured to store instructions; a processor coupled to the memory, the processor configured to execute the battery pack control method according to any one of claims 1 to 13 based on the instructions stored in the memory.

16. A battery pack, comprising a plurality of battery cells, each battery cell comprising a fiber optic sensor disposed in a groove on an inner side of a shell of the battery cell, wherein: the fiber optic sensor is configured to acquire multi-dimensional sensing data of a plurality of battery points of each battery cell in the battery pack of the vehicle and send the multi-dimensional sensing data to a battery pack control device, wherein the multi-dimensional sensing data comprises at least one of electrical parameters and non-electrical parameters, the electrical parameters comprising at least one of current and voltage of the battery pack, and the non-electrical parameters comprising at least one of temperature and strain of the battery pack, the multi-dimensional sensing data being used by the battery pack control device to determine a working condition of the vehicle and perform safety control on the battery pack based on the multi-dimensional sensing data and the working condition of the vehicle.

17. A battery pack control system, comprising the battery pack control device according to claim 14 or 15.

18. The battery pack control system according to claim 17, further comprising the battery pack according to claim 16.

19. A vehicle, comprising the battery pack control system according to claim 17 or 18.

20. A computer readable storage medium, wherein, the computer readable storage medium stores computer instructions, the instructions being executed by the processor to implement the battery pack control method according to any one of claims 1 to 13.

21. A computer program product comprising a computer program, wherein, the computer program is executed by the processor to implement the battery pack control method according to any one of claims 1 to 13.

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