A battery management system SOF computing system, a power battery and an electric vehicle

Abstract

The application relates to a battery management system SOF calculation system, which comprises a battery BMS, a BMS, an integrated simulator, an exceeding threshold value module, a threshold value meeting module, a parameter checking module, a correction algorithm module, a correction exit module, a mapping true value module, a cloud data center, a test database and a mapping system; the battery BMS is connected with the cloud data center through the mapping system, the integrated simulator, the threshold value meeting module and the correction exit module; the mapping system is connected with the BMS and the integrated simulator through the test database; the integrated simulator is connected with the cloud data center through the exceeding threshold value module, the parameter checking module, the correction algorithm module and the mapping true value module; the battery BMS can independently and autonomously calculate a SOF value, and the SOF value is reported to the integrated simulator through the mapping system; or required input parameters are reported to the BMS through the mapping system; the application has high SOF estimation precision, SOF errors are not easy to accumulate, and remote control can be realized.

Description

Technical Field

[0001] This invention belongs to the field of power battery technology, specifically relating to a battery management system SOF calculation system. Background Technology

[0002] Power batteries are a key component of new energy electric vehicles, and battery state of factor (SOF) estimation is a core technology of power battery management systems. Currently, there are two major problems with power battery SOF management: 1. Poor estimation accuracy; 2. Errors easily accumulate, seriously affecting battery safety. Therefore, there is an urgent need to develop a battery management system for calculating SOF. Summary of the Invention

[0003] The purpose of this invention is to provide a battery management system SOF calculation system, as well as a power battery and an electric vehicle including such a battery SOF management system, to solve the problems of poor battery SOF estimation accuracy, easy accumulation of SOF error, and inability to be remotely controlled in the prior art.

[0004] The objective of this invention is achieved through the following technical solution:

[0005] A battery management system SOF calculation system includes a battery BMS1, BMS2, an integrated simulator 3, an over-threshold module 4, a threshold compliance module 5, a parameter verification module 6, a correction algorithm module 7, a correction exit module 8, a mapping truth module 9, a cloud data center 10, an experimental database 11, and a mapping system 12.

[0006] The battery BMS1 is connected to the cloud data center 10 via the mapping system 12, the integrated simulator 3, the threshold matching module 5, and the correction exit module 8.

[0007] The mapping system 12 is connected to the integrated simulator 3 via BMS2, the test database 11, and respectively.

[0008] The integrated simulator 3 is connected to the cloud data center 10 via the threshold exceeding module 4, parameter verification module 6, correction algorithm module 7, and mapping truth module 9;

[0009] The battery BMS1 can independently calculate its internal SOF value and report it to the integrated simulator 3 through the mapping system 12; it can also report the input parameters required for calculating SOF to the BMS2 through the mapping system 12; the battery BMS1 can report the input parameters required for calculating SOF to the test database 11 through the mapping system 12.

[0010] The threshold value estimated by the integrated simulator 3 determines whether to enter the threshold 5 module or exceed the threshold 4 module; the parameter verification module 6 is used to verify whether all parameters mapped by BMS2 are error-free; the correction algorithm module 7 is used to perform SOF correction; the correction exit module 8 can feed back instructions to the battery BMS1 without performing SOF management control; the mapping truth value module 9 can assign the mapping value to the battery BMS1.

[0011] Furthermore, the battery BMS1 is a real battery BMS system, arranged inside the battery pack, and uses a separate SOF estimation algorithm, defining the calculated SOF value as SZ1.

[0012] Furthermore, the SOF calculated using the same algorithm as that used for battery BMS1 is defined as SZ2.

[0013] Furthermore, the SOF obtained by the test database 11 by retrieving the input parameters of the corresponding battery BMS1 to calculate SOF is defined as the value SZ2.

[0014] Furthermore, the BMS2 is located in the data cloud, and its arrangement is exactly the same as that of the battery BMS1, arranged one-to-one.

[0015] Furthermore, the integrated simulator 3 includes a simulation system and an SOF database. The simulation system can take the form of, but is not limited to, numerical models, large-scale games, simulation models, etc.; the SOF database receives SOF computing fault case parameter updates from the cloud data center 10.

[0016] Furthermore, during the actual operation of the vehicle, the integrated simulator 3 performs SOF value correction every 32 seconds, and uses the corrected value to make judgments and execute actions, with the judgment and execution process lasting ≤20ms.

[0017] Define the threshold estimated by the integrated simulator 3 as YZ=|SZ1-((SZ2+SZ3)*tanS / 2+√(SZ2*SZ3)*lnS) / 2*sin(expS)*100%|;

[0018] If YZ≤0.6%*exp(lgA)*sin(e-expS)*exp(e+sinC), then enter the threshold 5 module, exit the 8 module after correction, and send a command to the battery BMS1. No SOF management control is performed, and the battery uses the SOF value estimated by the battery BMS1. Then, enter the next 32s interval correction. A is the actual estimated coefficient of SOF of the power battery; S is the vehicle operating condition parameter.

[0019] If 0.6%*sexp(lgA)*sin(e-expS)*exp(e+sinC)<YZ≤5.34%*sexp(lgA)*sin(e-expS)*exp(e+sinC), then proceed to the threshold exceedance module 4, and then to the parameter verification module 6: verify whether all parameters mapped to BMS2 have errors. If so, perform a new SOF algorithm estimation in the integrated simulator 3 and continue with a new round of judgment; otherwise, perform SOF correction in the correction algorithm module 7: define the correction SOF as SY. SY=YZ*lg(e-expS)*ln(e+sinC), where C is the SOF verification estimation compensation coefficient; after calculating SJ, map and assign it to battery BMS1. Battery BMS1 uses the new SOF value SJ as the basis for the next round of 90s estimation.

[0020] If 5.34%*sexp(lgA)*sin(e-expS)*exp(e+sinC)<YZ, an alarm will be triggered, SOF estimates that there is a major fault, and feedback will be sent to battery BMS1 as a secondary high-level fault.

[0021] Furthermore, the cloud data center 10 is located in a remote cloud and can remotely receive all SOF estimation information for storage and recording. During the estimation process of the integrated simulator 3, the cloud data center 10 can retrieve previous SOF estimation information for auxiliary calculation and judgment.

[0022] A power battery, including the aforementioned battery management system and SOF calculation system.

[0023] A vehicle comprising the aforementioned power battery.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] This invention relates to a battery management system (BMS) SOF calculation system, comprising a battery BMS, an integrated simulator, an over-threshold module, a compliant-threshold module, a parameter verification module, a correction algorithm module, a correction exit module, a mapping truth module, a cloud data center, an experimental database, and a mapping system. It provides high accuracy in battery SOF estimation, minimizes SOF error accumulation, and allows for remote control. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A schematic diagram of the SOF (Structure of the Battery Management System) calculation system. Detailed Implementation

[0028] The present invention will be further described below with reference to embodiments:

[0029] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0030] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] like Figure 1 As shown, the battery management system SOF calculation system includes...

[0032] Battery BMS1;

[0033] BMS2;

[0034] Integrated emulator 3;

[0035] Module 4 exceeds the threshold;

[0036] Meets threshold module 5;

[0037] Parameter verification module 6;

[0038] Correction algorithm module 7;

[0039] Correction exit module 8;

[0040] Mapping Truth Module 9;

[0041] Cloud Data Center 10;

[0042] Experimental database 11;

[0043] Mapping system 12.

[0044] The battery BMS1 is connected to the cloud data center 10 via the mapping system 12, the integrated simulator 3, the threshold matching module 5, and the correction exit module 8.

[0045] The mapping system 12 is connected to the integrated simulator 3 via BMS2, the test database 11, and respectively.

[0046] The integrated simulator 3 is connected to the cloud data center 10 via the threshold exceeding module 4, parameter verification module 6, correction algorithm module 7, and mapping truth module 9.

[0047] The battery BMS1 is a real battery BMS system, located inside the battery pack, and employs a separate SOF estimation algorithm. The battery BMS1 can independently calculate its internal SOF value and report it to the integrated simulator 3 via the mapping system 12. The calculated SOF value is defined as SZ1.

[0048] The battery BMS1 can report the input parameters required for calculating SOF to BMS2 through the mapping system 12. The battery BMS1 can also report the input parameters required for calculating SOF to the test database 11 through the mapping system 12.

[0049] The SOF calculated using the same algorithm as that used for battery BMS1 is defined as SZ2.

[0050] The SOF obtained by retrieving the input parameters of the corresponding battery BMS1 from the test database 11 is defined as SZ2.

[0051] The BMS2 is located in the data cloud and its arrangement is exactly the same as that of the battery BMS1, arranged in a one-to-one manner.

[0052] The integrated simulator 3 includes a simulation system and an SOF database. The simulation system can take the form of, but is not limited to, numerical models, large-scale games, simulation models, etc. The SOF database receives SOF computing fault case parameter updates from the cloud data center 10.

[0053] During actual vehicle operation, the integrated simulator 3 performs SOF value correction every 32 seconds, and uses the corrected value to make judgments and execute actions. The judgment and execution process is ≤20ms.

[0054] Define the threshold estimated by the integrated simulator 3 as YZ=|SZ1-((SZ2+SZ3)*tanS / 2+√(SZ2*SZ3)*lnS) / 2*sin(expS)*100%|;

[0055] If YZ≤0.6%*exp(lgA)*sin(e-expS)*exp(e+sinC), then enter the threshold 5 module, exit the 8 module after correction, and send a command to the battery BMS1. No SOF management control is performed, and the battery uses the SOF value estimated by the battery BMS1. Then, enter the next 32s interval correction. A is the actual estimated coefficient of SOF of the power battery; S is the vehicle operating condition parameter.

[0056] If 0.6%*sexp(lgA)*sin(e-expS)*exp(e+sinC)<YZ≤5.34%*sexp(lgA)*sin(e-expS)*exp(e+sinC), then proceed to the threshold exceedance module 4, and then to the parameter verification module 6: verify whether all parameters mapped to BMS2 have errors. If so, perform a new SOF algorithm estimation in the integrated simulator 3 and continue with a new round of judgment; otherwise, perform SOF correction in the correction algorithm module 7: define the correction SOF as SY. SY=YZ*lg(e-expS)*ln(e+sinC), where C is the SOF verification estimation compensation coefficient; after calculating SJ, map and assign it to battery BMS1. Battery BMS1 uses the new SOF value SJ as the basis for the next round of 90s estimation.

[0057] If 5.34%*sexp(lgA)*sin(e-expS)*exp(e+sinC)<YZ, an alarm will be triggered, SOF estimates that there is a major fault, and feedback will be sent to battery BMS1 as a secondary high-level fault.

[0058] The cloud data center 10 is located in a remote cloud and can remotely receive all SOF estimation information for storage and recording. During the estimation process of the integrated simulator 3, the cloud data center 10 can retrieve previous SOF estimation information for auxiliary calculation and judgment.

[0059] The present invention also provides a power battery, including the battery management system SOF calculation system.

[0060] The present invention also provides a vehicle including the aforementioned power battery.

[0061] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A battery management system SOF calculation system, characterized in that: It includes a battery BMS (1), a metaverse BMS (2), an integrated simulator (3), a threshold exceeding module (4), a threshold meeting module (5), a parameter verification module (6), a correction algorithm module (7), a correction exit module (8), a mapping truth module (9), a cloud data center (10), an experimental database (11), and a mapping system (12). The battery BMS (1) is connected to the cloud data center (10) via the mapping system (12), the integrated simulator (3), the threshold compliance module (5), and the correction exit module (8); the mapping system (12) is connected to the integrated simulator (3) via the metaverse BMS (2) and the experimental database (11); the integrated simulator (3) is connected to the cloud data center (10) via the threshold exceedance module (4), the parameter verification module (6), the correction algorithm module (7), and the mapping truth module (9); The battery BMS (1) can independently calculate the internal SOF value and report it to the integrated simulator (3) through the mapping system (12); it can also report the input parameters required for calculating SOF to the metaverse BMS (2) through the mapping system (12); the battery BMS (1) can report the input parameters required for calculating SOF to the experimental database (11) through the mapping system (12). The threshold value estimated by the integrated simulator (3) determines whether to enter the module that meets the threshold (5) or exceeds the threshold (4); the parameter verification module (6) is used to verify whether the parameters mapped by all metaverse BMS (2) are errored; the correction algorithm module (7) is used to perform SOF correction; the correction exit (8) module can feed back instructions to the battery BMS (1) without performing SOF management control; the mapping truth module (9) can assign the mapping value to the battery BMS (1). The battery BMS (1) is a real battery BMS system, arranged inside the battery pack, and uses a separate SOF estimation algorithm. The calculated SOF value is defined as SZ1. The metaverse BMS (2) uses the same algorithm as the battery BMS (1) to calculate the SOF, and the value is defined as SZ2. The test database (11) retrieves the SOF obtained from the input parameters of the corresponding battery BMS (1) to calculate the SOF, and the value is defined as SZ3. The metaverse BMS (2) is arranged in the data cloud, and the arrangement is exactly the same as the battery BMS (1) in function, arranged one to one. The integrated simulator (3) includes a simulation system and an SOF database. The simulation system includes, but is not limited to, numerical models, large games, simulation models, etc. The SOF database receives SOF calculation fault case parameter updates from the cloud data center (10). The integrated simulator (3) performs SOF value correction every 32s during the actual operation of the vehicle, and judges and executes based on the corrected value. The judgment and execution process is ≤20ms. Define the threshold estimated by the integrated simulator (3) as YZ=|SZ1-((SZ2+SZ3)*tanS / 2+√(SZ2*SZ3)*lnS) / 2*sin(expS)*100% If YZ≤0.6%*exp(lgA) *sin(e-expS) *exp(e+sinC), then enter the threshold (5) module, exit the (8) module through correction, and send a command to the battery BMS (1). No SOF management control is performed. The battery uses the SOF value estimated by the battery BMS (1) and enters the next 32s interval correction. A is the actual estimated coefficient of SOF of the power battery; S is the vehicle operating condition parameter. If 0.6%*sexp(lgA) *sin(e-expS) *exp(e+sinC)<YZ≤5.34%*sexp(lgA) *sin(e-expS) *exp(e+sinC), then enter the threshold (4) module and enter the parameter verification (6) module: verify whether the parameters mapped by all metaverse BMS (2) are wrong. If so, perform a new SOF algorithm estimation in the integrated simulator (3) and continue to make a new round of judgment; otherwise, perform SOF correction in the correction algorithm module (7): define the correction SOF as SY, SY=YZ*lg(e-expS) *ln(e+sinC), where C is the SOF verification estimation compensation coefficient; after calculating SJ, map it to the battery BMS (1), and the battery BMS (1) uses the new SOF value SJ as the basis for the next round of 90s estimation. If 5.34%*sexp(lgA) *sin(e-expS) *exp(e+sinC)<YZ, then an alarm is triggered, SOF estimates that there is a major fault, and feedback is sent to the battery BMS according to the second-highest level fault (1). The cloud data center (10) is located in the remote cloud and can remotely receive all SOF estimation information for information storage and recording; the cloud data center (10) can retrieve previous SOF estimation information for auxiliary calculation and judgment during the estimation process of the integrated simulator (3).

2. A power battery, characterized in that: Includes the battery management system SOF calculation system as described in claim 1.

3. A vehicle, characterized in that: Includes the power battery described in claim 2.

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