Vehicle battery, self-adaptive adjusting method and module for pressure of vehicle battery and automobile

Abstract

The invention discloses a vehicle battery, a self-adaptive pressure adjusting method and module thereof and an automobile, and relates to the field of battery safety. The method comprises the following steps: monitoring training data of a battery cell in a contraction scene and an expansion scene at regular time, wherein the training data comprises actual battery cell pressure, actual battery cell pressing force, and displacement and displacement direction required by a pressure control device to adjust the actual battery cell pressing force to a safe pressing force range; training the training data to obtain an adaptive adjustment relation between the cell pressure and the displacement and the displacement direction thereof in different scenes; and adjusting the pressure control device according to the self-adaptive adjustment relationship between the cell pressure and the displacement and the displacement direction thereof in different scenes. According to different use states of the battery cell, the pressure control device can be adjusted through the adaptive displacement and displacement direction, so that the battery cell pressure is adaptively adjusted, and the period of the battery cell in the optimal pressure range and the service life of the battery cell are further prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of battery safety, in particular to a vehicle battery and a self-adaptive pressure adjusting method and module thereof, and a vehicle. BACKGROUND

[0002] The expansion rate of the battery cell of a vehicle battery (especially a solid-state battery) is high, which may exceed 10% of the battery cell body. The expansion of the battery cell may cause: (1) increase the internal pressure of the battery cell, thereby affecting the performance and service life of the battery cell; (2) long-term high pressure may cause the battery cell shell to rupture or leak, thereby causing a safety accident; (3) expansion may lengthen the movement path of lithium ions inside the battery cell, increase the resistance, thereby affecting the charging and discharging efficiency of the battery cell, and also cause the problem of increased risk of thermal runaway due to large heat generation.

[0003] Currently, the methods for handling the expansion of the battery cell are generally: (1) physical restriction, which is generally achieved by optimizing the module structure (such as welding, fasteners, etc.) to resist the expansion force; (2) reserving appropriate expansion gap and filling buffer material (such as sponge) to balance the expansion requirement of the battery cell and the stability of the module structure.

[0004] However, as the battery usage period increases and the number of charging and discharging cycles of the battery increases, the expansion characteristics of the battery cell may change, which may exceed the bearing limit of the above-mentioned physical restriction or buffer material. Therefore, the above-mentioned methods are difficult to ensure that the battery cell is always in the optimal pressure range (safe pressure range), and there is still a safety risk under the abuse condition of the battery. SUMMARY

[0005] In view of the defects in the prior art, the technical problem solved by the present application is how to self-adaptively adjust the pressure of the battery according to the usage of the battery, thereby prolonging the period of the battery cell in the safe pressure range.

[0006] To achieve the above-mentioned purpose, in a first aspect, the present application provides a self-adaptive pressure adjusting method for a vehicle battery, which comprises the following steps: timely monitoring the training data of the battery cell in the contraction scenario and the expansion scenario, the training data comprising the actual battery cell pressure, the actual battery cell pressure beam force, and the displacement amount and displacement direction required for the pressure control device to adjust the actual battery cell pressure beam force to the safe pressure beam force range; after training the training data, obtaining the self-adaptive adjustment relationship between the battery cell pressure and its displacement amount and displacement direction under different scenarios; adjusting the pressure control device according to the self-adaptive adjustment relationship between the battery cell pressure and its displacement amount and displacement direction under different scenarios.

[0007] In conjunction with the first aspect, in one implementation, the process of training the training data to obtain the adaptive adjustment relationship between cell pressure and its displacement amount and direction under different scenarios includes: Use actual cell stress as the training set; The displacement amount and direction corresponding to the actual cell pressure are used as the verification set; The training results are obtained from the training set, and the training results are the predicted displacement and displacement direction; Compare the training results with the information in the validation set: When the training results are matched with the information in the validation set, the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios is obtained.

[0008] In conjunction with the first aspect, in one embodiment, the process of adjusting the pressure control device according to the adaptive adjustment relationship between cell pressure and its displacement amount and direction under different scenarios includes: When an abnormal cell pressure is detected, the displacement of the pressure control device is reset to zero.

[0009] In conjunction with the first aspect, in one embodiment, the cell shrinkage scenario includes discharging the battery pack; the cell expansion scenario includes charging the battery pack.

[0010] In conjunction with the first aspect, in one implementation, the period of the timed monitoring is determined based on the charging rate or discharging rate of the battery pack.

[0011] Secondly, embodiments of this application provide an adaptive adjustment module for vehicle battery pressure, the module including an adaptive pressure adjustment training module and the pressure control device; The adaptive pressure regulation training module is used to: execute the training data to obtain the adaptive regulation relationship between cell pressure and its displacement and displacement direction under different scenarios; and adjust the process of the pressure control device according to the adaptive regulation relationship between cell pressure and its displacement and displacement direction under different scenarios. The pressure control device is used to: transmit the cell pressure to the adaptive pressure regulation training module, and adjust the displacement amount and direction according to the adaptive pressure regulation training module.

[0012] In conjunction with the second aspect, in one embodiment, the pressure control device includes a side plate located on the thickness side of the battery pack's cell assembly, and a cell pressure transmission device is disposed between the side plate and the cell assembly for adjusting the cell pressure by means of displacement; the pressure control device also includes a sensor for acquiring cell pressure.

[0013] In conjunction with the second aspect, in one embodiment, the side plates are two pieces, located on opposite sides of the cell assembly in the thickness direction; the transmission device is a hydraulic transmission device, which is disposed between at least one side plate and the cell assembly.

[0014] Thirdly, embodiments of this application provide a vehicle battery that includes the adaptive adjustment module provided in the second aspect.

[0015] Fourthly, embodiments of this application provide an automobile that includes the vehicle battery provided in the third aspect.

[0016] Compared with the prior art, the advantages of this application are: This application can adjust the pressure control device by adapting the displacement amount and displacement direction according to the different usage states of the battery cell (expansion or contraction), thereby achieving adaptive adjustment of the battery cell pressure, which in turn extends the period during which the battery cell is in the optimal pressure range, and thus extends the service life of the battery cell. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the adaptive adjustment method for vehicle battery pressure in the embodiments of this application; Figure 2 This is a schematic diagram of the battery pack structure in an embodiment of this application; Figure 3 This is a schematic diagram of the pressure control device structure in an embodiment of this application. Figure 4 This is a schematic diagram of the hardware structure of the adaptive adjustment device for vehicle battery pressure involved in the embodiments of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0022] In a first aspect, embodiments of this application provide an adaptive adjustment method for the pressure of a vehicle battery, the method comprising the following steps: Training data of the battery cell during contraction and expansion scenarios is monitored periodically. The training data includes the actual battery cell pressure, the actual battery cell clamping force, and the displacement amount and direction required for the pressure control device to adjust the actual battery cell clamping force to the safe clamping force range. The principle is that when the battery cell expands or contracts, the battery cell pressure will change. When the battery cell pressure exceeds the safe pressure range, a reaction force (battery cell clamping force) is required to restore the battery cell pressure to the safe pressure range. That is, the safe clamping force range is preset according to the safe pressure range.

[0023] After training the data, the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios is obtained. This relationship includes the displacement and direction corresponding to different cell pressures.

[0024] Based on the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios, the pressure control device is adjusted to achieve adaptive adjustment of battery pressure.

[0025] Therefore, this application can adjust the pressure control device by adapting the displacement amount and displacement direction according to the different usage states of the battery cell (expansion or contraction), thereby achieving adaptive adjustment of the battery cell pressure, thus extending the period during which the battery cell is in the optimal pressure range, and consequently extending the service life of the battery cell.

[0026] At the same time, this application can learn the corresponding cell pressure control method (displacement of the pressure control device) according to different cell characteristics, which means it can be used for cells of different systems.

[0027] In one embodiment, the above-mentioned cell shrinkage scenario includes: discharging the battery pack, at which time the cells will shrink; The aforementioned scenarios of cell expansion include: charging the battery pack, during which the cells will expand.

[0028] Furthermore, the period of the aforementioned timed monitoring is determined based on the charging or discharging rate of the battery pack. The monitoring period and the monitoring accuracy are inversely proportional, and the specific period is selected according to the accuracy requirements.

[0029] Specifically: When the battery pack is discharged at full power (3C), the discharge time (SOC from 100% to 0%) is 20 minutes, and the monitoring is performed at a timer period of 0.5 to 10 seconds. When fast charging the battery pack at a 2C charging rate, the charging time (SOC from 0% to 100%) is 30 minutes, and the monitoring is performed at a time interval of 1 to 15 seconds. When the battery pack is slowly charged at a charging rate of 0.33C, the charging time (SOC from 0% to 100%) is 3 hours, and the monitoring is performed at a time interval of 50 to 80 seconds.

[0030] In one embodiment, the above-described process of training with training data includes: Use actual cell stress as the training set; The displacement amount and direction corresponding to the actual cell pressure are used as the verification set; The training results are obtained from the training set, and the training results are the predicted displacement and displacement direction; Compare the training results with the information in the validation set: When the training results are matched with the information in the validation set (i.e., the predicted displacement direction is the same as the corresponding displacement direction in the validation set, the predicted displacement amount is the same as the corresponding displacement amount in the validation set, or is within the specified error range), the adaptive adjustment relationship between cell pressure and its displacement amount and displacement direction under different scenarios is obtained.

[0031] When the training results do not match the information in the validation set, the training parameters required to obtain the training results are adjusted and the training results are obtained again.

[0032] The above training process can be implemented using known training models, such as the BP (Back Propagation) neural network model. The input layer data of this model includes actual cell pressure and actual cell clamping force; the training parameters are the weights and biases from the input layer to the hidden layer, and the output layer is the displacement and displacement direction. To put it simply: The input layer is used to receive raw data; The hidden layer automatically analyzes the relationship between pressure and stroke (displacement and direction); The output layer outputs results, such as when the battery is fast-charged to 30%, the hydraulic rod is loosened by 1mm (to buffer the expansion force).

[0033] In one embodiment, the process of adjusting the pressure control device according to the adaptive adjustment relationship between cell pressure and its displacement amount and direction under different scenarios includes: When abnormal cell pressure is detected (greater than the preset upper limit or less than the preset lower limit), it indicates that the battery may be being abused. For safety reasons, the adaptive adjustment relationship will not be used, the displacement of the pressure control device will be reduced to zero, and an alarm will be triggered.

[0034] See below. Figure 1 As shown, the above method is illustrated through a specific embodiment.

[0035] S1: Determine the battery pack parameters, including the length x (cm), width y (cm), and height z (cm) of the battery pack casing, the number of battery cells d, and the maximum expansion rate of the battery cells b (range: generally 0-10% depending on the characteristics of different battery cells).

[0036] S2: Periodically monitor the training data of the battery cells under different scenarios, specifically including: (1) When discharging the battery pack, the cells will shrink. According to the 3C full power discharge calculation, it takes 20 minutes for a full battery pack to discharge from 100% SOC to 0% SOC. Starting from 0s, record the current pressure sensor measured pressure Pr (t0), cell clamping force F (t0, generally 550-2500N), and at the same time, according to the current battery pack box length x (cm), width y (cm), height z (cm), number of cells d, cell limit expansion rate b, etc., adjust the pressure control device to constrain the clamping force on the cells within the optimal range (safe range), and record the current stroke distance S (t0) of the hydraulic pressure control device; after an interval of 10s, record the pressure Pr of the second detection. (t1), the cell beat force F(t1) and the optimal stroke distance S(t1) of the hydraulic pressure control device; data were recorded every 10 seconds to obtain 121 sets of input and output data for 20 minutes of continuous discharge: [Pr(t0), F(t0), x, y, z, d, b; S(t0)], [Pr(t1), F(t1), x, y, z, d, b; S(t1)], ..., [Pr(t120), F(t120), x, y, z, d, b; S(t120)].

[0037] (2) When the battery pack is fast charged, the cells will expand. According to the 2C charging rate, it takes 30 minutes to charge the battery pack from 0% SOC to 100% SOC. Starting from 0s, record the current pressure sensor measured pressure Pr (t0) and cell clamping force F (t0). At the same time, according to the current battery pack box length x (cm), width y (cm), height z (cm), number of cells d, cell limit expansion rate b, etc., adjust the pressure control device to keep the clamping force on the cells within the optimal range, and record the current stroke distance S (t0) of the hydraulic pressure control device. After an interval of 1 minute, record the pressure Pr (t1) and cell clamping force detected for the second time. F(t1) and the optimal stroke distance S(t1) of the hydraulic pressure control device; data is recorded every 1 minute to obtain 181 sets of input and output data for continuous charging for 30 minutes: [Pr(t0), F(t0), x,y,z,d,b; S(t0)], [Pr(t1), F(t1), x,y,z,d,b; S(t1)], ..., [Pr(t120), F(t180), x,y,z,d,b; S(t180)].

[0038] During slow charging of the battery pack, the cells will expand. Based on a 0.33C charging rate, it takes 3 hours to charge the battery pack from 0% SOC to 100% SOC. Starting from second 0, record the current pressure sensor readings Pr(t0) and cell clamping force F(t0). Simultaneously, based on the current battery pack dimensions (length x (cm), width y (cm), height z (cm), number of cells d, and cell expansion limit b), adjust the pressure control device to keep the clamping force on the cells within the optimal range, and record the current travel distance S(t0) of the hydraulic pressure control device. After a 1-minute interval, record the second measured pressure Pr(t1) and cell clamping force F(t0). The optimal travel distance S(t1) of the force F(t1) and hydraulic pressure control device was recorded every 1 minute to obtain 181 sets of input and output data for continuous charging for 3 hours: [Pr(t0), F(t0), x,y,z,d,b; S(t0)], [Pr(t1), F(t1), x,y,z,d,b; S(t1)], ..., [Pr(t120), F(t180), x,y,z,d,b; S(t180)].

[0039] S3: Establish a self-learning database to store the training data in S2.

[0040] S4: A single-layer BP neural network model is used to predict and self-learn from the training data to obtain the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios; the training process of the BP neural network model includes: (1) Input the data obtained from discharging, fast charging and slow charging into the model respectively to obtain the output value of the BP neural network; (2) Calculate the error E(i) between the network output value and the actual value: If E(i) > 5%, then the weights are adjusted according to the gradient descent method, the network output value is recalculated, and the output value is obtained again. If E(i) ≤ 5%, then E(i) is considered to meet the requirements, and training ends.

[0041] S5: Monitors cell voltage in real time under different scenarios, and adjusts the displacement and direction of the pressure control device accordingly based on the adaptive adjustment relationship between cell pressure and its displacement amount and direction.

[0042] S6: When abnormal cell pressure is detected (greater than the preset upper limit or less than the preset lower limit), the pressure control device will retract the hydraulic transmission device to its shortest position. At the same time, the BMS will send an alarm to the vehicle system (the instrument panel lights up red) after sensing that the pressure value exceeds the range.

[0043] Secondly, this application provides an adaptive adjustment module for vehicle battery pressure, which includes an adaptive pressure adjustment training module and the aforementioned pressure control device.

[0044] The adaptive pressure regulation training module is used to: after training the training data as described above, obtain the adaptive regulation relationship between cell pressure and its displacement and displacement direction under different scenarios; and adjust the process of the pressure control device according to the adaptive regulation relationship between cell pressure and its displacement and displacement direction under different scenarios.

[0045] The pressure control device is used to: transmit the cell pressure to the adaptive pressure regulation training module, and adjust the displacement amount and direction according to the adaptive pressure regulation training module.

[0046] In one embodiment, see Figure 2 and Figure 3 As shown, the pressure control device includes a side plate fixed to the thickness side of the battery pack's cell assembly. A transmission device (used to adjust the cell pressure by displacement) is provided between the side plate and the cell assembly. A sensor for collecting cell pressure is provided on the side plate, and a low-pressure sampling port for sending the sensor data to the adaptive pressure regulation training module is provided.

[0047] For details, see Figure 2 and Figure 3 As shown, the pressure control device includes two side plates located on opposite sides of the cell assembly in the thickness direction. The side plates are locked to the crossbeam, and the side plates can act as end plates when the cells are inserted into the box. The transmission device is a hydraulic transmission device, which is located between at least one side plate and the cell assembly; similarly, a pressure sensor is installed on at least one side plate.

[0048] At the same time, this is because the expansion is most pronounced and the pressure is greatest in the center of the battery cell when it expands. Therefore, the pressure acquisition range of the pressure sensor and the adjustment range of the hydraulic transmission device should ideally cover the center and sides of the battery cell. See also Figure 3 As shown, in this embodiment, there are three pressure sensors and three hydraulic transmission devices: one located at the position corresponding to the middle of the side plate and the battery cell, and the other two located at the positions corresponding to the sides of the side plate and the battery cell, respectively.

[0049] Thirdly, embodiments of this application provide a vehicle battery that includes the adaptive adjustment module for vehicle battery pressure mentioned in the second aspect.

[0050] Fourthly, embodiments of this application provide an automobile that includes the vehicle battery mentioned in the third aspect.

[0051] Fifthly, embodiments of this application provide an adaptive adjustment device for vehicle battery pressure. The adaptive adjustment device for vehicle battery pressure can be a device with data processing capabilities, such as a personal computer (PC), a laptop computer, or a server.

[0052] Reference Figure 4 , Figure 4 This is a schematic diagram of the hardware structure of the adaptive adjustment device for vehicle battery pressure involved in the embodiments of this application. In the embodiments of this application, the adaptive adjustment device for vehicle battery pressure may include a processor, a memory, a communication interface, and a communication bus.

[0053] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0054] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting internal components of the adaptive regulation device for vehicle battery pressure, as well as interfaces for interconnecting the adaptive regulation device for vehicle battery pressure with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0055] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0056] The processor can be a general-purpose processor, which can call the adaptive adjustment program for vehicle battery pressure stored in the memory and execute the adaptive adjustment method for vehicle battery pressure provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the adaptive adjustment program for vehicle battery pressure is called can refer to the various embodiments of the adaptive adjustment method for vehicle battery pressure of this application, and will not be repeated here.

[0057] Those skilled in the art will understand that Figure 4 The hardware structure shown does not constitute a limitation of this application and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0058] Sixthly, embodiments of this application also provide a computer-readable storage medium.

[0059] The computer-readable storage medium of this application stores an adaptive adjustment program for vehicle battery pressure, wherein when the adaptive adjustment program for vehicle battery pressure is executed by a processor, it implements the steps of the adaptive adjustment method for vehicle battery pressure as described above.

[0060] The method implemented when the adaptive adjustment program for vehicle battery pressure is executed can be referred to in various embodiments of the adaptive adjustment method for vehicle battery pressure of this application, and will not be repeated here.

[0061] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0062] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0063] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0064] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0065] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0066] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0067] The above are merely specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the scope of the claims.

Claims

1. An adaptive adjustment method for vehicle battery pressure, characterized in that, The method includes the following steps: The training data of the battery cell is monitored periodically in both contraction and expansion scenarios. The training data includes the actual battery cell pressure, the actual battery cell clamping force, and the displacement amount and direction required for the pressure control device to adjust the actual battery cell clamping force to a safe clamping force range. After training with the training data, the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios is obtained. The pressure control device is adjusted according to the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios.

2. The adaptive adjustment method for vehicle battery pressure as described in claim 1, characterized in that: The process of training the data to obtain the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios includes: Use actual cell stress as the training set; The displacement amount and direction corresponding to the actual cell pressure are used as the verification set; The training results are obtained from the training set, and the training results are the predicted displacement and displacement direction; Compare the training results with the information in the validation set: When the training results are matched with the information in the validation set, the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios is obtained.

3. The adaptive adjustment method for vehicle battery pressure as described in claim 1, characterized in that: The process of adjusting the pressure control device according to the adaptive adjustment relationship between cell pressure and its displacement and direction under different scenarios includes: When an abnormal cell pressure is detected, the displacement of the pressure control device is reset to zero.

4. The adaptive adjustment method for vehicle battery pressure as described in any one of claims 1 to 3, characterized in that: The cell shrinkage scenario includes discharging the battery pack; the cell expansion scenario includes charging the battery pack.

5. The adaptive adjustment method for vehicle battery pressure as described in claim 4, characterized in that: The period for the timed monitoring is determined based on the charging or discharging rate of the battery pack.

6. An adaptive adjustment module for automotive battery pressure, characterized in that: This module includes an adaptive pressure regulation training module and the pressure control device; The adaptive pressure regulation training module is used to: execute the training data to obtain the adaptive regulation relationship between cell pressure and its displacement and displacement direction under different scenarios; and adjust the process of the pressure control device according to the adaptive regulation relationship between cell pressure and its displacement and displacement direction under different scenarios. The pressure control device is used to: transmit the cell pressure to the adaptive pressure regulation training module, and adjust the displacement amount and direction according to the adaptive pressure regulation training module.

7. The adaptive adjustment module for vehicle battery pressure as described in claim 6, characterized in that: The pressure control device includes a side plate located on the thickness side of the battery pack's cell assembly, and a cell pressure transmission device is provided between the side plate and the cell assembly for adjusting the cell pressure by means of displacement; the pressure control device also includes a sensor for collecting cell pressure.

8. The adaptive adjustment module for vehicle battery pressure as described in claim 7, characterized in that: The side plates consist of two pieces, located on opposite sides of the cell assembly in the thickness direction; the transmission device is a hydraulic transmission device, which is disposed between at least one side plate and the cell assembly.

9. A vehicle battery, characterized in that: The battery includes the adaptive adjustment module mentioned in any one of claims 6 to 8.

10. A car, characterized in that: The vehicle includes the vehicle battery mentioned in claim 9.

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