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

Abstract

The present disclosure relates to a battery pack and a control method, device and system thereof, a vehicle and a storage medium. The battery pack control method comprises: acquiring multi-dimensional sensing data of a vehicle battery pack through an optical fiber sensor, wherein the multi-dimensional sensing data comprises at least one of an electrical parameter and a non-electrical parameter, the electrical parameter comprises at least one of a current and a voltage of the battery pack, and the non-electrical parameter comprises at least one of a temperature and a strain of the battery pack; determining a working condition of the vehicle according to the multi-dimensional sensing data; and performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle. The present disclosure can collect dynamic information of multi-dimensional data such as force, electricity, heat and gas 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.

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 demand for high efficiency, long life, safety and fast charging of battery systems in new energy commercial vehicle application scenarios is rapidly growing. The metal sensors commonly used in current battery pack information acquisition and transmission technology 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 acquisition 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 acquire real-time multi-dimensional data dynamic information of force, electricity, heat and gas of the battery, 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:

[0005] acquiring 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;

[0006] determining a working condition of the vehicle according to the multi-dimensional sensing data;

[0007] performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

[0008] In some embodiments of the present disclosure, the determining the working condition of the vehicle according to the multi-dimensional sensing data comprises:

[0009] 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;

[0010] determining the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional change data.

[0011] In some embodiments of the present disclosure, the multi-dimensional sensing data comprises battery cell surface strain data, and the determining 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:

[0012] determining the whole vehicle load state according to the first direction change data;

[0013] determining whether the working condition of the vehicle is a rough road according to the second direction change data and the third direction change data of the two sides of the vehicle;

[0014] determining whether the working condition of the vehicle is any one of the high-low speed turning working condition, the climbing working condition, and the downhill working condition of the front and rear axle directions according to the second direction change data and the third direction change data of the single side of the vehicle;

[0015] determining whether the working condition of the vehicle is the charging and discharging working condition according to the battery cell surface strain data.

[0016] 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:

[0017] controlling the working mode of the vehicle battery pack according to the working condition of the vehicle.

[0018] In some embodiments of the present disclosure, the controlling the working mode of the vehicle battery pack according to the working condition of the vehicle comprises at least one of the following steps:

[0019] controlling the vehicle battery pack to enter the high-power output mode when the vehicle is in at least one of the rough road, high-speed turning, and climbing working conditions;

[0020] 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 the load state;

[0021] controlling the vehicle battery pack to perform kinetic energy recovery when the vehicle is in the downhill working condition.

[0022] 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:

[0023] obtaining the battery pack charging state and the external environment condition, wherein the battery pack charging state comprises the change data of the battery pack charging power and current, and the external environment condition is the ambient temperature;

[0024] obtaining the multi-dimensional change data of the battery pack, wherein the multi-dimensional change data comprises the change data of at least one of the battery voltage, the charging and discharging current, and the temperature;

[0025] Determine 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.

[0026] In some embodiments of the present disclosure, the determining 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:

[0027] Determine 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 under different charging and discharging currents.

[0028] In some embodiments of the present disclosure, the performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises:

[0029] Determine 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;

[0030] Estimate the safe life of the battery pack according to the multi-dimensional sensing data and the multi-dimensional change data.

[0031] In some embodiments of the present disclosure, the obtaining the multi-dimensional sensing data of the vehicle battery pack by the optical fiber sensor comprises:

[0032] Obtain 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.

[0033] In some embodiments of the present disclosure, the performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises:

[0034] Monitor 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;

[0035] According to the battery temperature change, use heat management to dissipate heat for the battery monomer whose battery temperature change is greater than a predetermined value.

[0036] In some embodiments of the present disclosure, the multi-dimensional sensing data comprises battery monomer surface strain data, and the performing safety control on the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle comprises:

[0037] Monitor the battery monomer surface strain data;

[0038] determining whether a difference between the current battery cell surface strain data and the battery cell surface strain data of the previous predetermined time period is greater than a predetermined value;

[0039] in a case where the difference is greater than the predetermined value, determining that the battery pack is in failure, and performing a pre-warning.

[0040] In some embodiments of the present disclosure, the multi-dimensional sensing data comprises battery cell 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:

[0041] monitoring the battery cell surface strain data;

[0042] determining whether the current battery cell surface strain data is greater than a first distance;

[0043] in a case where the current battery cell surface strain data is greater than the first distance, determining whether the current battery cell surface strain data is restored after a predetermined time interval;

[0044] in a case where the current battery cell surface strain data is not restored after the predetermined time interval, determining that the battery pack is in failure, and performing a pre-warning.

[0045] In some embodiments of the present disclosure, the determining the working condition of the vehicle according to the multi-dimensional sensing data comprises:

[0046] obtaining vehicle data, wherein the vehicle data comprises at least one of a vehicle speed, a vehicle vertical acceleration, a vehicle lateral angular velocity, and a vehicle pitch angle;

[0047] determining the working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

[0048] According to another aspect of the present disclosure, a battery pack control device is provided, comprising:

[0049] a data acquisition module configured to acquire multi-dimensional sensing data of a vehicle battery pack through an optical fiber sensor, wherein the multi-dimensional sensing data comprises at least one of an electrical parameter and a non-electrical parameter, the electrical parameter comprises at least one of a current and a voltage of the battery pack, and the non-electrical parameter comprises at least one of a temperature and a strain of the battery pack;

[0050] a working condition determination module configured to determine a working condition of the vehicle according to the multi-dimensional sensing data;

[0051] a safety control module configured to perform safety control of the battery pack according to the multi-dimensional sensing data and the working condition of the vehicle.

[0052] According to another aspect of the present disclosure, a battery pack control device is provided, comprising:

[0053] a memory configured to store instructions;

[0054] a processor coupled to the memory, the processor configured to perform the battery pack control method according to any one of the preceding embodiments based on the instructions stored in the memory.

[0055] 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 a shell of the battery cell, wherein:

[0056] The optical fiber sensor is configured to collect 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 the battery pack control device, wherein the multi-dimensional sensing data comprises at least one of an electrical parameter and a non-electrical parameter, the electrical parameter comprises at least one of a current and a voltage of the battery pack, the non-electrical parameter comprises at least one of a temperature and a strain of the battery pack, and the multi-dimensional sensing data is used for the battery pack control device to determine a 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.

[0057] 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 preceding embodiments.

[0058] In some embodiments of the present disclosure, the battery pack control system further comprises the battery pack according to any one of the preceding embodiments.

[0059] According to another aspect of the present disclosure, a vehicle is provided, comprising the battery pack control system according to any one of the preceding embodiments.

[0060] 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 according to any one of the preceding embodiments.

[0061] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program, when executed by a processor, implements the battery pack control method according to any one of the preceding embodiments.

[0062] 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

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0064] Figure 1 A schematic diagram of some embodiments of the battery pack control method of the present disclosure.

[0065] Figure 2 A schematic diagram of the connection of the battery and the optical fiber of the battery pack of some embodiments of the present disclosure.

[0066] Figure 3 A schematic diagram of some embodiments of the battery pack control device of the present disclosure.

[0067] Figure 4 A structural schematic diagram of other embodiments of the battery pack control device of the present disclosure.

[0068] Figure 5 A structural schematic diagram of some embodiments of the battery pack control system of the present disclosure.

[0069] Figure 6 A structural schematic diagram of other embodiments of the battery pack control system of the present disclosure. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only some of the embodiments of the present disclosure, but not all the embodiments. The description of the at least one exemplary 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 skilled in the art without creative labor are within the scope of protection of the present disclosure.

[0071] Unless otherwise specified, the relative arrangement, numerical expressions and values of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0072] At the same time, it should be understood that the sizes of the various parts shown in the drawings are not drawn in accordance with the actual proportional relationship for the convenience of description.

[0073] The technologies, methods and devices known to those skilled in the relevant art can not be discussed in detail, but should be considered as part of the authorized description under appropriate circumstances.

[0074] In all examples shown and discussed herein, any specific values should be interpreted as merely exemplary, and not as a limitation. Thus, other examples of the exemplary embodiments can have different values.

[0075] It should be noted that like reference numerals and letters refer to like items throughout the attached drawings, and once an item is defined in one drawing, it is not necessary to discuss it further in subsequent drawings.

[0076] Figure 1 A schematic diagram of some embodiments of the battery pack control method of the present disclosure. Preferably, Figure 1 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 shown, Figure 1 The method of the present disclosure can include at least one of steps 100 to 300.

[0077] 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.

[0078] In some embodiments of the present disclosure, the electrical parameters can further include internal resistance, etc.

[0079] In some embodiments of the present disclosure, the non-electrical parameters can further include deformation, air pressure, gas species, etc.

[0080] In some embodiments of the present disclosure, the strain of the battery pack can be replaced by the expansion force of the battery, the expansion displacement of the battery, the surface deformation of the battery, or the surface strain of the battery.

[0081] In some embodiments of the present disclosure, step 100 can include acquiring 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.

[0082] Figure 2 A schematic diagram of the connection of the battery and the optical fiber of the battery pack of some embodiments of the present disclosure. As Figure 2 shown, the connection method of the battery and the optical fiber of the battery pack can include at least one of steps 1 to 4.

[0083] Step 1, the optical fiber sensor 1 is continuously bent in U shape along the length direction from the battery tab to the shell, the optical fiber sensor 1 is embedded through the aluminum plate fixing support to form an integrated optical fiber sensing unit, so as to ensure the effective layout of the optical fiber sensor 1 at the tab, the edge and the center of the shell.

[0084] The optical fiber sensor of the present disclosure has the advantages of corrosion resistance and electromagnetic interference resistance, and can realize simultaneous monitoring of multiple points through distributed measurement.

[0085] Step 2, the battery monomer shell 2 is guided according to the direction of the integrated optical fiber sensing unit, a groove with a depth of 0.8 mm and a width of 2 mm is formed on one side to form a compatible battery monomer, so as to ensure smooth surface and no concave or convex phenomenon on the overall surface of the shell.

[0086] 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 the assembly process, a plurality of battery monomers 3 are assembled.

[0087] 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.

[0088] In some embodiments of the present disclosure, step 100 can include: using optical fiber sensor distributed multi-point monitoring to sense and collect 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; 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, etc. during long-term use of the battery, and providing a low-cost optical fiber sensing system for realizing simultaneous monitoring of multiple parameters of the battery through some special structural design.

[0089] In some embodiments of the present disclosure, the special structural design is a U-shaped layout of the optical fiber, which is arranged outward from the center along the edge of the battery, so that the optical fiber can be closer to the tab while effectively reducing the length of the optical fiber.

[0090] In some embodiments of the present disclosure, step 100 can include: collecting multi-dimensional data dynamic information of the battery in real time, such as real-time data of surface micron changes, tab temperature rise change rate, etc. during charging and discharging of the battery, 0.01% full data, etc.

[0091] In step 200, the working condition of the vehicle is determined according to the multi-dimensional sensing data.

[0092] In some embodiments of the present disclosure, step 200 can comprise: acquiring vehicle data, wherein the vehicle data comprises at least one of a vehicle speed, a vehicle vertical acceleration, a vehicle lateral angular velocity and a vehicle pitch angle; and determining a working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

[0093] In some embodiments of the present disclosure, step 200 can comprise at least one of steps 210 to 220.

[0094] In step 210, multi-dimensional variation data is determined according to the multi-dimensional sensing data, wherein the multi-dimensional variation data comprises at least one of first direction (Z direction) variation data, second direction (X direction) variation data and third direction (Y direction) variation data, the first direction being a vertical direction, the second direction being a vehicle travel direction, and the third direction being perpendicular to the first direction and the second direction.

[0095] In step 220, a working condition of the vehicle is determined according to the multi-dimensional sensing data and the multi-dimensional variation data.

[0096] In step 300, a battery pack is controlled according to the multi-dimensional sensing data and the working condition of the vehicle.

[0097] In some embodiments of the present disclosure, the multi-dimensional sensing data can comprise battery cell surface strain data. Step 300 can comprise at least one of steps 310 to 340.

[0098] In step 310, a vehicle load state is determined according to the first direction variation data.

[0099] In some embodiments of the present disclosure, step 310 can comprise: determining the vehicle load state according to the waveform in the Z direction variation data.

[0100] In step 320, whether the working condition of the vehicle is a rough road is determined according to the second direction variation data and the third direction variation data of both sides of the vehicle.

[0101] In some embodiments of the present disclosure, step 320 can comprise: determining whether the working condition of the vehicle is a rough road according to the X and Y direction data of both sides.

[0102] In step 330, 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 is determined according to the second direction variation data and the third direction variation data of one side of the vehicle.

[0103] In some embodiments of the present disclosure, step 330 can comprise: 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-rear axle direction, according to the single-side X and Y direction data.

[0104] In step 340, it is determined whether the working condition of the vehicle is a charging and discharging working condition, according to the battery cell surface strain data.

[0105] In some embodiments of the present disclosure, step 340 can comprise: determining whether the working condition of the vehicle is a charging and discharging working condition, according to the battery cell surface strain data.

[0106] In some embodiments of the present disclosure, step 300 can comprise: controlling the working mode of the vehicle battery pack according to the working condition of the vehicle.

[0107] 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 comprise at least one of steps 301 to 303.

[0108] 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, high-speed turning, and climbing working condition.

[0109] In some embodiments of the present disclosure, step 301 can comprise: identifying that the vehicle is in at least one of a rough road, high-speed turning, and climbing working condition by detecting vehicle state and battery shell physical change conditions, to support the decision of the vehicle entering a high-power output mode.

[0110] In step 302, the power of the vehicle battery pack is controlled 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.

[0111] In step 303, the vehicle battery pack is controlled to perform kinetic energy recovery when the vehicle is in a downhill working condition, and the battery is instantaneously heated.

[0112] 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 comprise: controlling the maximum amount of battery heating in charging mode, and monitoring the high and low changes of the battery interval in discharging mode.

[0113] In some embodiments of the present disclosure, the multi-dimensional sensing data can comprise battery cell surface strain data. Step 300 can comprise at least one of steps 350 to 370.

[0114] 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.

[0115] 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.

[0116] In step 370, whether the battery is safe is determined according to the battery pack charging state, the external environmental conditions, the multi-dimensional change data, and the multi-dimensional sensing data.

[0117] In some embodiments of the present disclosure, step 370 can include determining whether the battery charging and discharging is abnormal according to at least one of battery monomer surface strain data, tab temperature change data, and pressure difference change data under different charging and discharging currents.

[0118] 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 the like state through battery system charging state and external environmental conditions, and adopting corresponding battery pack power mode and thermal management mode.

[0119] 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.

[0120] In some embodiments of the present disclosure, the external environment refers to air temperature, and the optical fiber can identify the external environment through waveform change. Whether the change of the battery under extremely high or low environmental temperature affects the service life of the battery compared with the change under normal data.

[0121] In some embodiments of the present disclosure, step 300 can include adopting a full-load thermal management mode in the case of high-power charging, and monitoring whether the battery is in a safe temperature range.

[0122] In some embodiments of the present disclosure, step 300 can include adopting a multi-mode power and thermal management mode in the case of long-time charging and discharging, and corresponding different modes through different driving such as vehicle high-speed driving and climbing. The above embodiments of the present disclosure mainly depend on the deviation size of data and algorithm in the database to determine the mode change and the safety of the battery.

[0123] In some embodiments of the present disclosure, step 300 can comprise determining multi-dimensional change data from the multi-dimensional sensing data, wherein the multi-dimensional change data comprises change data of at least one of the battery voltage, the charge-discharge current and the temperature; and estimating the safe life of the battery pack from the multi-dimensional sensing data and the multi-dimensional change data.

[0124] In some embodiments of the present disclosure, step 300 can comprise monitoring the battery temperature change of all battery monomers, wherein the battery temperature change comprises the heat generation state change of the battery tab and the battery shell; and performing heat dissipation on the battery monomer with the battery temperature change greater than a predetermined value by using heat management according to the battery temperature change.

[0125] In some embodiments of the present disclosure, step 300 can comprise determining the rate current according to the heat generation state of the battery tab and the shell, calculating the current of the battery charge-discharge by the heat change model data, and determining the heat management working mode.

[0126] In some embodiments of the present disclosure, step 300 can comprise monitoring the tab temperature change by using an optical fiber sensor, or converting an electrical signal into an optical signal by using optical signal modulation; and then estimating the current change by an algorithm.

[0127] In some embodiments of the present disclosure, the battery is generally charged and discharged at a rate of 2C-3C, and the peak value of the charge-discharge is the maximum battery maximum rate, and the battery always works at the maximum rate under normal circumstances.

[0128] In some embodiments of the present disclosure, step 300 can comprise monitoring the battery temperature change to accurately dissipate heat from the battery by using heat management to achieve the maximum working capacity of the battery in order to make the battery work at the maximum rate.

[0129] In some embodiments of the present disclosure, the multi-dimensional sensing data can comprise battery monomer surface strain data, and step 300 can comprise at least one of steps 304-306.

[0130] In step 304, the battery monomer surface strain data is monitored.

[0131] In step 305, it is determined whether the difference between the battery monomer surface strain data of a current predetermined time period and the battery monomer surface strain data of a previous predetermined time period is greater than a predetermined value.

[0132] 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.

[0133] 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.

[0134] In step 311, battery cell surface strain data is monitored.

[0135] In step 312, it is determined whether the current battery cell surface strain data is greater than a first distance.

[0136] 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.

[0137] 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.

[0138] 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, etc. according to changes in vehicle light, medium and heavy load modes, analyzing battery safety performance curves, and adjusting warning modes.

[0139] In some embodiments of the present disclosure, in the case of heavy load, the change in the battery heating 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 the previous data. Through comparison by algorithm, the basis for directly affecting the battery life is given, and a warning can be given at the same time.

[0140] 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.

[0141] The above embodiments of the present disclosure solve the limitation of the battery management system of new energy commercial vehicles, which only monitors the current, voltage and external temperature of some points of the battery, and cannot fully perform precise and efficient management and control. The above embodiments of the present disclosure integrate multi-parameter sensors that can monitor temperature, stress, deformation, gas and other parameters of the internal chemical and physical reactions of the battery, analyze and identify the vehicle load state, rough road, high and low speed turning, climbing, descending state, charging and discharging and other working conditions, and can perform real-time diagnosis, safety management and performance optimization, thereby improving the safety and energy saving of the whole life cycle of the vehicle battery system.

[0142] Figure 3 A schematic diagram of some embodiments of the battery pack control device of the present disclosure is shown in FIG. 1. Figure 3 As shown in FIG. 1, 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.

[0143] The data acquisition module 31 is configured to acquire multi-dimensional sensing data of the vehicle battery pack by the 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.

[0144] 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 the optical fiber sensor, wherein the optical fiber sensor is arranged in a groove on the inside of the battery shell of each battery monomer in the vehicle battery pack, and the battery points comprise at least one of a battery tab and a battery shell.

[0145] The working condition determination module 32 is configured to determine the working condition of the vehicle according to the multi-dimensional sensing data.

[0146] In some embodiments of the present disclosure, the working condition determination module 32 can be configured to acquire vehicle data, wherein the vehicle data comprises at least one of vehicle speed, vehicle vertical acceleration, vehicle lateral angular velocity and vehicle pitch angle; and determine the working condition of the vehicle according to the multi-dimensional sensing data and the vehicle data.

[0147] In some embodiments of the present disclosure, the working condition determination module 32 can be configured to determine 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 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 variation data.

[0148] In some embodiments of the present disclosure, the multi-dimensional sensing data can comprise battery monomer surface strain data, and the working condition determination module 32, in the case of determining the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional variation data, can be configured to perform at least one of the following operations: 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 the second direction variation data and the 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 the second direction variation data and the third direction variation data of one side of the vehicle; and determining whether the working condition of the vehicle is a charging and discharging working condition according to the battery monomer surface strain data.

[0149] 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.

[0150] 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.

[0151] 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, and at least one of the following operations: in the case that the vehicle is in at least one of the working conditions of rough road, high-speed turning and climbing, the vehicle battery pack is controlled to enter the high-power output mode; in the case that the vehicle is in the loaded state, the vehicle battery pack power is controlled to change from low to high according to the load from small to large; in the case that the vehicle is in the downhill working condition, the vehicle battery pack is controlled to perform kinetic energy recovery.

[0152] In some embodiments of the present disclosure, the safety control module 33 can be configured to obtain the battery pack charging state and the external environmental condition, wherein the battery pack charging state includes the change data of the battery pack charging power and current, and the external environmental condition is the ambient temperature; obtain the multi-dimensional change data of the battery pack, wherein the multi-dimensional change data includes the change data of at least one of the battery voltage, the charging and discharging current and the temperature; according to the battery pack charging state, the external environmental condition, the multi-dimensional change data and the multi-dimensional sensing data, judge whether the battery is safe.

[0153] In some embodiments of the present disclosure, the safety control module 33 can be configured to judge 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 differential pressure change data under different charging and discharging currents, in the case that the safety control module 33 judges whether the battery is safe according to the battery pack charging state, the external environmental condition, the multi-dimensional change data and the multi-dimensional sensing data.

[0154] In some embodiments of the present disclosure, the safety control module 33 can be configured to determine the multi-dimensional change data according to the multi-dimensional sensing data, wherein the multi-dimensional change data includes the change data of at least one of the battery voltage, the charging and discharging current and the temperature; estimate the safe life of the battery pack according to the multi-dimensional sensing data and the multi-dimensional change data.

[0155] In some embodiments of the present disclosure, the safety control module 33 can be configured to monitor the battery temperature change of all battery monomers, wherein the battery temperature change includes the heating state change of the battery tab and the battery shell; according to the battery temperature change, heat dissipation is performed on the battery monomer whose battery temperature change is greater than a predetermined value by using heat management.

[0156] In some embodiments of the present disclosure, the multi-dimensional sensing data can include battery cell surface strain data, the safety control module 33 can be configured to monitor the battery cell surface strain data; determine whether the difference between the battery cell surface strain data of the current predetermined time period and the battery cell surface strain data of the previous predetermined time period is greater than a predetermined value; in the case where the difference is greater than the predetermined value, determine that the battery pack fails and give a warning.

[0157] In some embodiments of the present disclosure, the multi-dimensional 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; in the case where 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; in the case where the current battery cell surface strain data does not recover after the predetermined time interval, determine that the battery pack fails and give a warning.

[0158] In some embodiments of the present disclosure, the battery pack control device of the present disclosure can also be configured to execute the battery pack control method of any one of the above-mentioned embodiments of the present disclosure.

[0159] Figure 4 The structural schematic diagram of another embodiment of the battery pack control device of the present disclosure is shown in FIG. 4. As shown in FIG. 4, the battery pack control device includes a memory 41 and a processor 42. Figure 4

[0160] The memory 41 is used to store instructions, and the processor 42 is coupled to the memory 41. The processor 42 is configured to execute the battery pack control method of any one of the above-mentioned embodiments of the present disclosure based on the instructions stored in the memory.

[0161] As shown in FIG. 4, the battery pack control device further includes a communication interface 43 for information interaction with other devices. At the same time, the battery pack control device further includes a bus 44, and the processor 42, the communication interface 43, and the memory 41 complete mutual communication through the bus 44. Figure 4

[0162] The memory 41 can include 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.

[0163] 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 the embodiments of the present disclosure.

[0164] ​​Figure 2 A schematic diagram of a battery pack of some embodiments of the present disclosure is also given. As shown in Figure 2 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, each battery monomer 3 including a battery shell 2 and an optical fiber sensor 1.

[0165] The optical fiber sensor 1 is arranged in a groove on the inside of the shell 2 of the battery monomer 3.

[0166] 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 battery pack of the vehicle, 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.

[0167] Figure 5 A structural schematic diagram of some embodiments of the battery pack control system of the present disclosure is given. As shown in Figure 5 The battery pack control system includes a battery pack control device 51 and an optical fiber sensor 52.

[0168] The battery pack control device 51 can be implemented as the battery pack control device described in any of the above embodiments.

[0169] The optical fiber sensor 52 is arranged in a groove on the inside of the battery shell of each battery monomer in the battery pack of the vehicle, and is configured to collect multi-dimensional sensing data of a plurality of battery points of each battery monomer in the battery pack of the vehicle, and send the multi-dimensional sensing data to the battery pack control device 51.

[0170] Figure 6 A structural schematic diagram of some other embodiments of the battery pack control system of the present disclosure is given. As shown in Figure 6 The battery pack control system includes a battery management system (BMS) 61, an optical fiber sensor 62, a vehicle controller (VCU) 63, a cloud server 64, a demodulator 65 and a battery pack 66.

[0171] 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.

[0172] 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 orFigure 5 Optical fiber sensor 52 of the embodiment.

[0173] In some embodiments of the present disclosure, as shown in Figure 6 The optical fiber sensor 62 can include a grating, a cladding, and a core, the grating is used for reflecting and transmitting incident light, generating reflected light and transmitted light, and realizing grating conduction.

[0174] 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.

[0175] 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 a vehicle model as shown in Figure 6 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.

[0176] 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.

[0177] The cloud server 64 is configured to perform multi-parameter monitoring.

[0178] 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.

[0179] The cloud server 64 is configured to calculate multi-element data through intelligent algorithms and then transmit the data 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 big data models and artificial intelligence technology.

[0180] 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 vehicle working condition change data after collecting all the data, obtain the battery resistance change value, and determine the current state executable charging and discharging capacity.

[0181] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to mainly analyze and decide the ability of the external request for the charge and discharge demand of the battery, the current required for the next second, such as any current demand of 500, 600, 100, 155A, etc., through the subtle structure and temperature change of the battery, to estimate the safe service life of the battery.

[0182] In some embodiments of the present disclosure, long-period calculation can be several full charge and discharge cycles, such as 5-20 times of data change difference, and the single-machine estimation ability of the BMS is improved through algorithm comparison and estimation.

[0183] 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, when charging, the surface strain is obviously increased; when discharging, the surface strain is obviously decreased; 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.

[0184] 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 constantly correcting the initial value through the algorithm.

[0185] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to compare the battery charge and discharge data each time with the same data of the last period to adjust the data change rule.

[0186] In some embodiments of the present disclosure, the reference signal is the predicted value of the database and algorithm, and the strain signal is the real-time change or special change signal, and the predicted value and the real-time value are compared, and if there is a large difference, the fault can be predicted.

[0187] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to judge the working condition information by the optical fiber itself, and then combine the data changes of the vehicle request power demand, the motor, the brake, etc. to comprehensively judge and correct the execution information of each controller.

[0188] In some embodiments of the present disclosure, the battery management system (BMS) 61 can be configured to interact with the vehicle controller (VCU) for the information change of the battery pack 66.

[0189] 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 from the vehicle control unit (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 failure level, estimated life, and power, etc.

[0190] 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 surface deformation of the battery, the temperature change of the tab, the pressure difference change, etc. under different charging and discharging currents.

[0191] In some embodiments of the present disclosure, the battery failure level is usually 4 levels, the voltage range is 2.6-3.2V, and the temperature is -10-45 degrees. If it exceeds the range, it is the maximum failure. If it changes linearly, it is normal. If the upper and lower line deviation in the range is large, it is a level failure.

[0192] 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 failure levels, for example: in the case that the battery pack is in the first failure level, the fault early warning is performed; in the case that the battery pack is in the second failure level, the 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 failure level, the 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 failure level, the fault early warning is performed and the shutdown and power-off processing is performed.

[0193] In some embodiments of the present disclosure, the first proportion is 50%, and the second proportion is 20%.

[0194] 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-low speed turning, climbing, downhill state, charging and discharging, etc. by combining the deformation characteristics and algorithm of the optical fiber sensor 62, the vehicle speed, the vehicle vertical acceleration, the vehicle lateral angular velocity, the vehicle pitch angle, etc. information; synchronously monitor the real-time information such as the battery discharge heat, the current, and the battery pack gas pressure, analyze the battery safety performance curve, and adjust the early warning mode.

[0195] In some embodiments of the present disclosure, the deformation characteristics and algorithm include that the internal waveform change of the optical fiber sensor can form an infinite number of modes, the algorithm and model are a database obtained through calibration, and the change waveform of each feature is determined based on the algorithm. All stress changes can obtain the estimated values of temperature, stress, and gas pressure through the waveform and the algorithm.

[0196] In some embodiments of the present disclosure, the data change and the change of the strain trend, combined with the change of the request given by the vehicle controller, are uniformly analyzed by the cloud big data to finally determine the component state and the execution information.

[0197] 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 change of the data and the actual data, which can be determined by the change of the vehicle state, such as reducing the power, adjusting the thermal management, etc. The difference data is compared by the multi-controller algorithm and the cloud big data, and the battery safety value is comprehensively obtained.

[0198] The optical fiber conduction multi-dimensional information fusion battery pack and control system of the above-mentioned embodiments of the present disclosure comprises an optical fiber sensor, a battery monomer with a groove, a demodulator, a BMS and the like. 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 vehicle controller and the BMS are determined by the instructions of the vehicle working condition. The battery pack control method is executed as described in any one of the above-mentioned embodiments of the present disclosure.

[0199] The above-mentioned embodiments of the present disclosure provide a new energy commercial vehicle optical fiber conduction multi-dimensional information fusion battery pack and control method and system. The control system comprises hardware and software. The hardware comprises 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 comprises 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 the electrical parameters of the battery such as current, voltage, internal resistance and the like, and the non-electrical parameters such as temperature, strain, deformation, air pressure, gas type and the like. 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 and low speed turning, the climbing, the downhill state, the charging and discharging and the like. The battery safety and control method under the special working condition of the battery and the vehicle in the long-term use process are comprehensively monitored and analyzed.

[0200] According to another aspect of the present disclosure, a vehicle is provided, comprising the battery pack control system as described in any one of the above-mentioned embodiments.

[0201] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program is executed by a processor to implement the battery pack control method as described in any one of the above-mentioned embodiments.

[0202] According to another aspect of the present disclosure, a computer readable storage medium is provided, wherein the computer readable storage medium stores computer instructions, which, when executed by a processor, implement the battery pack control method according to any one of the above embodiments.

[0203] In some embodiments of the present disclosure, the computer readable storage medium can be a non-transitory computer readable storage medium.

[0204] The above 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, which can realize more precision through real-time monitoring of battery multi-dimensional parameters and in combination with technologies such as Internet of Vehicles, big data and cloud computing. For this purpose, the above embodiments of the present disclosure integrate an intelligent battery pack of various sensing units such as optical fiber fine perception, break through the limitations of traditional electrical signal transmission mode, identify the special working condition information state of the vehicle by using multi-dimensional algorithm through the change of grating conduction waveform, analyze and identify the whole vehicle load state of the waveform change in the Z direction, the rugged road of the double-sided X and Y direction change, the high and low speed turning of the single-sided X and Y direction change, the downhill state of the front and rear axle direction, and the charging and discharging of the cell surface change, thereby improving the multi-source fine information collection, analysis and decision-making ability of the whole life cycle of the battery system.

[0205] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, device or computer program product. Therefore, the present disclosure can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer usable non-transitory storage media (including but not limited to disk storage, optical storage, CD-ROM, etc.) containing computer usable program code.

[0206] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each flow and / or block in the flowcharts and / or block diagrams and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general purpose computer, a special purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the computer or other programmable data processing device produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks

[0207] These computer program instructions can also be loaded into 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 which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks

[0208] 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 device, a discrete gate or transistor logic device, a discrete hardware component, or any appropriate combination thereof for performing the functions described in the present application.

[0209] 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.

[0210] 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 by a program instructing relevant hardware, and the program can be stored in a non-transitory computer-readable storage medium, which can be a read-only memory, a magnetic disk or an optical disk.

[0211] The description of the present disclosure is given for the purpose of illustration and description, and is not exhaustive or limiting to the present disclosure. Many modifications and variations will be apparent to those skilled 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.

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; wherein the determining 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; wherein the multi-dimensional sensing data comprises battery cell surface strain data, and the determining 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. 2.The battery pack control method of claim 1, wherein the safely controlling 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. 3.The battery pack control method of claim 2, wherein the controlling 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 load amount 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.

4. The battery pack control method according to any one of claims 1 to 3, wherein The safely controlling 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.

5. The battery pack control method according to claim 4, wherein The step of determining whether the battery is safe based on the battery pack charging status, the external environmental conditions, the multidimensional change data, and the multidimensional sensor data includes: Under different charging and discharging currents, determine whether the battery charging and discharging is abnormal based on at least one of the following: battery cell surface strain data, tab temperature change data, and differential pressure change data.

6. The battery pack control method according to any one of claims 1 to 3, wherein The step of performing safety control on the battery pack based on the multi-dimensional sensing data and the vehicle's operating conditions includes: Multidimensional change data is determined 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; The safe lifespan of the battery pack is estimated based on the multidimensional sensing data and the multidimensional change data.

7. The battery pack control method according to any one of claims 1 to 3, wherein The acquisition of multi-dimensional sensing data of the vehicle battery pack via fiber optic sensors includes: Multidimensional sensing data of multiple battery points of each battery cell in the vehicle battery pack is acquired by fiber optic sensors. The fiber optic sensors are disposed in grooves inside the battery casing of each battery cell in the vehicle battery pack. The battery points include at least one of battery tabs and battery casing.

8. The battery pack control method of claim 7, wherein, The step of performing safety control on the battery pack based on the multi-dimensional sensing data and the vehicle's operating conditions includes: Monitor the temperature changes of all individual battery cells, including the changes in the heating state of the battery tabs and battery casing. Based on the battery temperature changes, heat dissipation is carried out on battery cells whose temperature changes exceed a predetermined value.

9. The battery pack control method according to any one of claims 1 to 3, wherein, The multidimensional sensing data includes surface strain data of individual battery cells, and the safety control of the battery pack based on the multidimensional sensing data and the operating conditions of the vehicle includes: Monitor the surface strain data of individual battery cells; Determine whether the difference between the surface strain data of a battery cell in the current predetermined time period and the surface strain data of a battery cell in the previous predetermined time period is greater than a predetermined value. If the difference is greater than a predetermined value, a battery pack malfunction is determined, and an early warning is issued.

10. The battery pack control method according to any one of claims 1 to 3, wherein The multidimensional sensing data includes surface strain data of individual battery cells, and the safety control of the battery pack based on the multidimensional sensing data and the operating conditions of the vehicle includes: Monitor the surface strain data of individual battery cells; Determine whether the current surface strain data of the battery cell is greater than the first distance; If the current strain data of a single battery cell surface is greater than the first distance, determine whether the current strain data of a single battery cell surface has recovered after a predetermined time interval. If the surface strain data of the current battery cell is not recovered after a predetermined time interval, the battery pack is deemed to be faulty and an early warning is issued.

11. The battery pack control method according to any one of claims 1 to 3, wherein Determining the vehicle's operating condition based on the multidimensional sensing data includes: Acquire vehicle data, wherein the vehicle data includes at least one of the following: vehicle speed, vehicle vertical acceleration, vehicle lateral angular velocity, and vehicle pitch angle; The vehicle's operating condition is determined based on the multidimensional sensor data and the vehicle data.

12. A battery pack control device, comprising: a data acquisition module configured to acquire multi-dimensional sensing data of a battery pack of a vehicle by an optical fiber sensor, wherein the multi-dimensional sensing data comprises at least one of an electrical parameter and a non-electrical parameter, the electrical parameter comprises at least one of a current and a voltage of the battery pack, and the non-electrical parameter comprises at least one of a temperature and a strain of the battery pack; a working condition determination module configured to determine a 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; wherein the working condition determination module is configured to determine 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; and determine the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional variation data; wherein the multi-dimensional sensing data comprises battery cell surface strain data, and the working condition determination module is configured to perform at least one of the following operations in determining the working condition of the vehicle according to the multi-dimensional sensing data and the multi-dimensional variation data: determine a whole vehicle load state according to the first direction variation data; determine whether the working condition of the vehicle is a rough road condition according to the second direction variation data and the third direction variation 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 downhill condition of front and rear axle directions according to the second direction variation data and the third direction variation data of one side of the vehicle; and determine whether the working condition of the vehicle is a charging and discharging condition according to the battery cell surface strain data.

13. 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 11 based on the instructions stored in the memory.

14. A battery pack comprising a plurality of battery cells, each battery cell comprising an optical fiber sensor disposed in a groove on an inner side of a 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 monomer in a vehicle battery pack and send the multi-dimensional sensing data to a battery pack control device, wherein the multi-dimensional sensing data includes battery monomer surface strain data, 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, 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 a working condition of the vehicle, and the battery pack is controlled safely according to the multi-dimensional sensing data and the working condition of the vehicle. The working condition of the vehicle is determined according to the multi-dimensional sensing data, including: 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 traveling direction, and the third direction is perpendicular to the first direction and the second direction, respectively. The working condition of the vehicle is determined according to the multi-dimensional sensing data and the multi-dimensional change data; the working condition of the vehicle is determined according to the multi-dimensional sensing data and the multi-dimensional change data, including at least one of the following steps: determining a whole vehicle load state according to the first direction change data, determining whether the working condition of the vehicle is a rough road according to the second direction change data and the third direction change 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 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 working condition according to the battery monomer surface strain data.

15. A battery pack control system comprising the battery pack control device of claim 12 or 13.

16. The battery pack control system of claim 15, further comprising the battery pack of claim 14.

17. A vehicle comprising the battery pack control system of claim 15 or 16.

18. A computer readable storage medium, wherein, The computer readable storage medium stores computer instructions, and the instructions are executed by the processor to implement the battery pack control method of any one of claims 1 to 11.

19. A computer program product comprising a computer program, wherein, The computer program is executed by the processor to implement the battery pack control method of any one of claims 1 to 11.

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