CN112798968A - Battery parallel connection method, method for estimating SOC of battery parallel connection system and related equipment - Google Patents
Battery parallel connection method, method for estimating SOC of battery parallel connection system and related equipment Download PDFInfo
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- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 description 4
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 3
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- IVUGBSGLHRJSSP-UHFFFAOYSA-N LimKi 3 Chemical compound S1C(NC(=O)C(C)C)=NC=C1C1=CC(C(F)F)=NN1C1=C(Cl)C=CC=C1Cl IVUGBSGLHRJSSP-UHFFFAOYSA-N 0.000 description 2
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3835—Arrangements for monitoring battery or accumulator variables, e.g. SoC involving only voltage measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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Abstract
The application provides a battery parallel connection method, which comprises the following steps: collecting a first voltage of a master battery pack and a plurality of second voltages of a plurality of slave battery packs; and if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to a preset voltage, controlling the two battery packs corresponding to the voltage difference value smaller than or equal to the preset voltage to be connected in parallel to obtain a battery parallel system. The application also provides a method for estimating the SOC of the battery parallel system constructed by the battery parallel method and related equipment. According to the method and the device, the estimation precision of the state of charge of the battery parallel system can be improved.
Description
Technical Field
The present application relates to the field of battery technologies, and in particular, to a battery parallel connection method, a method for estimating a system SOC of a battery parallel connection system, and related devices.
Background
In order to solve the problems of difficult charging and slow charging of new energy vehicles, the current policy is greatly promoting the development of a new energy vehicle battery changing mode so as to realize the common development and application of battery charging and changing, emphasize the construction of a high-efficiency recycling system of a power battery, support the innovative application of a power battery echelon product in the fields of energy storage, energy backup, battery charging and changing and the like, and realize battery modularization, standardization and generalization.
The existing box-dividing and battery-changing technology adopts a low-voltage battery pack series connection mode, and the lowest value of the charge state in the series battery packs is used as the charge state of the whole series system in the using process. In the actual use process, the short plate effect of the discharge capacity of the low-voltage battery pack in the series connection mode is very obvious, namely, when the capacity of one battery pack in the series connection system is inconsistent with the capacities of other battery packs, the finally excessive electric quantity of the other battery packs cannot be utilized. Therefore, in order to utilize the electric quantity of each group of battery packs as efficiently as possible, the series connection of the low-voltage battery packs has high requirements on the capacity consistency and the voltage consistency of the group of battery packs, and the battery packs of different batches cannot be used in a mixed manner.
Disclosure of Invention
In view of the above, it is desirable to provide a battery parallel method, a method for estimating SOC of a battery parallel system, and related devices, so as to solve the above problems.
An embodiment of the present application provides a battery parallel connection method, including: collecting a first voltage of a master battery pack and a plurality of second voltages of a plurality of slave battery packs; and if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to a preset voltage, controlling the two battery packs corresponding to the voltage difference value smaller than or equal to the preset voltage to be connected in parallel to obtain a battery parallel system.
According to some embodiments of the application, the method further comprises: if the voltage difference between any two of the first voltage and the second voltages is larger than the preset voltage, controlling the battery pack with the highest voltage in the master battery pack and the plurality of slave battery packs to be in a working state; continuously collecting a first voltage of the master battery pack and a plurality of second voltages of a plurality of slave battery packs; if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to the preset voltage through comparison; and controlling the two corresponding battery packs to be connected in parallel when the voltage difference value is smaller than or equal to the preset voltage until the main battery pack and the plurality of slave battery packs are connected in parallel to obtain the battery parallel system.
According to some embodiments of the present application, the master battery pack has a capacity different from that of the slave battery packs.
An embodiment of the present application provides a method of estimating an SOC of a battery parallel system including a master battery pack including a master battery management system and a plurality of slave battery packs including slave battery management systems, the method including: the main battery management system collects first historical state data of the main battery pack in a recycling process; sending the first historical state data to a cloud big data platform, wherein the cloud big data platform estimates to obtain a first capacity and a first charge state according to the first historical state data and a first initial parameter of the main battery pack stored in advance; the slave battery management system collects second historical state data of the slave battery pack in the recycling process; sending the second historical state data to a cloud big data platform, wherein the cloud big data platform estimates a second capacity and a second charge state according to the second historical state data and a second initial parameter of the slave battery pack stored in advance; the master battery management system receives the first capacity and the first charge state sent by the cloud big data platform, and the slave battery management system receives the second capacity and the second charge state sent by the cloud big data platform; the main battery management system calculates the current load of the parallel system according to the first capacity, the first charge state and the second capacity and the second charge stateState of charge SOCAnd are。
According to some embodiments of the present application, the current state of charge SOC of the parallel system is calculated by the following formulaAnd are：
Wherein n is the sum of the master battery pack and the plurality of slave battery packs, C1For the first capacity, SOC1In the first state of charge, C2…CnFor the second capacity, SOC2…SOCnThe second state of charge.
According to some embodiments of the present application, the first historical state data comprises first historical voltage data, first historical current data, first historical temperature data, first historical state of charge data, and a first number of cycles, and the first initial parameters comprise a first factory date and a first initial capacity; the second historical state data comprises second historical voltage data, second historical current data, second historical temperature data, second historical state-of-charge data and second cycle number, and the second initial parameters comprise a second delivery date and a second initial capacity.
According to some embodiments of the present application, the estimating, by the cloud big data platform, a first capacity and a first state of charge according to the first historical state data and a first pre-stored initial parameter of the master battery pack includes: dynamically updating the current SOC-OCV corresponding relation of the master battery pack based on the first historical state data; correcting the rated capacity of the master battery pack according to the first historical state data and the initial parameters of the master battery pack to obtain the first capacity; and estimating the first state of charge according to the updated SOC-OCV corresponding relation, the first capacity and the received state data of the main battery pack in the last recycling process.
According to some embodiments of the present application, modifying the rated capacity of the battery according to the first historical state data and the initial parameter of the master battery pack, the obtaining the first capacity includes: counting the times and duration of charge and discharge exceeding rated multiplying power in the first historical state data; determining the attenuation of the capacity of the master battery pack according to the times and the duration; and correcting the rated capacity of the main battery pack according to the attenuation of the capacity of the main battery pack and the first initial capacity to obtain the first capacity.
According to some embodiments of the present application, the cloud big data platform estimating a second capacity and a second state of charge according to the second historical state data and the pre-stored initial parameters of the slave battery pack includes: dynamically updating the current SOC-OCV correspondence of the slave battery pack based on the second historical state data; correcting the rated capacity of the battery according to the second historical state data and the initial parameters of the slave battery pack to obtain a second capacity; and estimating the second state of charge according to the updated SOC-OCV corresponding relation, the second capacity and the received state data of the slave battery pack in the latest recycling process.
According to some embodiments of the present application, modifying the rated capacity of the battery according to the second historical state data and the initial parameter of the slave battery pack, and obtaining the second capacity comprises: counting the times and duration of charge and discharge exceeding rated multiplying power in the second historical state data; determining the attenuation of the capacity of the slave battery pack according to the times and the duration; and correcting the rated capacity of the slave battery pack according to the attenuation of the capacity of the slave battery pack and the second initial capacity to obtain the second capacity.
According to some embodiments of the application, the method further comprises: estimating and obtaining the actual state of charge of the battery parallel system by combining an ampere-hour integration method and an open-circuit voltage method; and determining a target state of charge of the battery parallel system based on the current state of charge and the actual state of charge, wherein the priority of the current state of charge is higher than the priority of the actual state of charge.
According to some embodiments of the present application, the estimating the actual state of charge of the battery parallel system by combining the ampere-hour integration method and the open-circuit voltage method includes: respectively dividing SOC-OCV curves corresponding to the master battery pack and the slave battery packs into a voltage flat area, a low-voltage area and a high-voltage area; calculating the actual state of charge of the main battery pack and the actual state of charge of the auxiliary battery pack in the high-voltage area and the low-voltage area respectively through an open-circuit voltage method, and calculating the actual state of charge of the battery parallel system based on the actual state of charge of the main battery pack and the actual state of charge of the auxiliary battery pack; and in the voltage leveling area, respectively calculating the actual charge states of the main battery pack and the slave battery pack through an ampere-hour integration method, and calculating the actual charge state of the battery parallel system based on the actual charge states of the main battery pack and the slave battery pack.
An embodiment of the present application provides a powered device, which includes a battery parallel system and a processor, wherein the processor is configured to execute the battery parallel method and the method for estimating the SOC of the battery parallel system as described above.
An embodiment of the present application provides a storage medium having at least one computer instruction stored thereon, the computer instruction being loaded by a processor and used for executing the battery parallel method and the method for estimating the SOC of the battery parallel system as described above.
According to the implementation mode of the application, batteries are connected in parallel according to the voltage difference to construct a battery parallel system, historical state data of a main battery pack and historical state data of a slave battery pack in the battery parallel system are received through a cloud big data platform, state analysis of the battery parallel system in a full life cycle is achieved, the latest maximum available capacity of the battery parallel system in practical application, which is different from rated capacity when the battery parallel system leaves a factory, is obtained, and a more accurate SOC value is obtained.
Drawings
Fig. 1 is a diagram of an application environment for estimating SOC of a parallel battery system according to an embodiment of the present application.
Fig. 2 is a schematic diagram of a parallel battery system according to an embodiment of the present application.
Fig. 3 is a flowchart of a battery parallel method according to an embodiment of the present application.
Fig. 4 is a flowchart of a method of estimating SOC of a parallel battery system according to an embodiment of the present application.
FIG. 5 is a block diagram of an estimation system according to an embodiment of the present application.
Description of the main elements
Electrical consumer 1
Cloud big data platform 2
Estimation system 100
Communication unit 10
Battery parallel system 11
Load 12
Acquisition module 101
Control module 102
Sending module 103
Receiving module 104
Calculation Module 105
The following detailed description will explain the present application in further detail in conjunction with the above-described figures.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application.
In the description of the embodiments of the present application, it should be noted that, unless explicitly stated or limited otherwise, the term "connected" is to be interpreted broadly, e.g. as a fixed connection, a detachable connection, or an integral connection; may be mechanically connected, may be electrically connected or may be in communication with each other; either directly or indirectly through intervening components, either internally or in cooperative relationship to each other. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
The terms "first", "second", and "third", etc. in the description of the present application and the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "comprises" and any variations thereof, are intended to cover non-exclusive inclusions.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
Referring to fig. 1, the present application provides a method for estimating a battery parallel system SOC, which is applied in an application environment consisting of an electric device 1 and a cloud big data platform 2. The electric device 1 includes, but is not limited to, a communication unit 10, a battery parallel system 11, and a load 12, and the communication unit 10, the battery parallel system 11, and the load 12 may be connected via a bus or may be directly connected.
In this embodiment, the communication unit 10 may provide wired or wireless network communication for the electric device 1. In this embodiment, the wired network may be any type of conventional wired communication, such as the internet, a local area network. The Wireless network may be of any type of conventional Wireless communication, such as radio, Wireless Fidelity (WIFI), cellular, satellite, broadcast, etc. For example, the electric device 1 may be communicatively connected to the cloud big data platform 2 through the communication unit 10. It is understood that the cloud big data platform 2 page includes a communication unit (not shown in the figure) to provide the communication function for the cloud big data platform 2.
As shown in fig. 2, the battery parallel system 11 includes one master battery pack 111 and a plurality of slave battery packs 112 connected in parallel. In the present embodiment, a Battery Management System (BMS) may be provided in each of the master Battery pack 111 and the plurality of slave Battery packs 112, wherein each Battery pack is cell-managed by the corresponding BMS. For example, the master battery pack 111 includes a master battery management system BMS1, and the slave battery pack 112 includes slave battery management systems BMS2, BMS3 … BMSn. The master battery management system BMS1 is communicatively connected to the slave battery management systems BMS2, BMS3 … BMSn. In the present application, a battery parallel method is also disclosed to construct the battery parallel system 11, and please refer to fig. 3 for a detailed description of the battery parallel method.
In one embodiment, each of the master battery pack 111 and the plurality of slave battery packs 112 is a rechargeable battery for supplying electric power to the electric device 1. For example, the battery pack may be a lithium ion battery, a lithium polymer battery, a lithium iron phosphate battery, or the like. The battery pack comprises at least one battery cell, and the battery pack can be repeatedly charged in a mode of recycling and recharging.
Each of the master battery pack 111 and the plurality of slave battery packs 112 is used to store electric power, and the positive electrode and the negative electrode of the battery pack are capable of extracting and receiving energy-carrying particles. According to the application scenario of the battery pack, the battery pack in the embodiment of the present application may include a power battery and an energy storage battery, where the power battery may be applied to the fields of electric vehicles, electric bicycles, and other electric tools, and the energy storage battery may be applied to the fields of energy storage power stations, renewable energy grid connection, micro-grids, and the like. Taking a power battery as an example, from the category of the battery pack, the battery pack may be, but is not limited to, a lithium iron phosphate system battery or a silicon-added system battery, where the lithium iron phosphate system battery is a lithium ion battery with a positive electrode active material containing lithium iron phosphate, and the silicon-added system battery is a lithium ion battery with a negative electrode active material containing silicon.
Although not shown, the electric device 1 may further include a Wireless Fidelity (WiFi) unit, a bluetooth unit, a speaker, and other components, which are not described in detail herein.
Fig. 1 is only an example of the electric device 1. In other embodiments, powered device 1 may include more or fewer elements, or have a different configuration of elements. The electric equipment 1 may be an electric motorcycle, an electric bicycle, an electric automobile, a mobile phone, a tablet computer, a digital assistant, a personal computer, or any other suitable rechargeable equipment.
Referring to fig. 3, fig. 3 is a flowchart illustrating a method for parallel connection of batteries according to an embodiment of the present disclosure. In the present embodiment, in order to solve the problem that the existing battery series system is easy to have the short plate effect, the present application provides a method for constructing a battery parallel system according to the condition of the voltage difference between the battery packs. Specifically, the method for parallel connection of the batteries can comprise the following steps:
step S31: a first voltage of a master battery pack and a plurality of second voltages of a plurality of slave battery packs are collected.
In this embodiment, assuming that N battery packs are required to be connected in parallel, one of the N battery packs is set as a master battery pack, and the other N-1 battery packs are set as slave battery packs. The main battery pack comprises a main battery management system, and the main battery management system collects a first voltage of the main battery pack.
In the embodiment, each of the N-1 slave battery packs comprises a slave battery management system, and the slave battery management system can collect the second voltage of each slave battery pack to obtain N-1 second voltages. The slave battery management system sends the N-1 second voltages to the master battery management system.
Step S32: and comparing whether the voltage difference value between any two of the first voltage and the plurality of second voltages is less than or equal to a preset voltage. If the voltage difference is smaller than or equal to the preset voltage, the process proceeds to step S33; if the voltage difference is greater than the preset voltage, the process proceeds to step S34.
In the present embodiment, before the master battery pack is connected in parallel with the plurality of slave battery packs, it is necessary to determine how to construct the battery parallel system according to the first voltage of the master battery pack and the second voltages of the plurality of slave battery packs. And only when the voltage difference value between any two of the first voltage and the plurality of second voltages is less than or equal to a preset voltage, the two corresponding battery packs can be connected in parallel when the voltage difference value is less than or equal to the preset voltage.
Step S33: and controlling the two battery packs corresponding to the voltage difference value smaller than or equal to the preset voltage to be connected in parallel to obtain a battery parallel system.
In this embodiment, when the voltage difference satisfies a battery parallel condition, that is, the voltage difference is less than or equal to the preset voltage, two battery packs corresponding to the voltage difference that is less than or equal to the preset voltage are controlled to be connected in parallel, so as to obtain a battery parallel system. It is understood that the voltage difference value less than or equal to the preset voltage describes that the voltages between the two battery packs are not different or have the same magnitude.
Step S34: the master battery pack and the battery pack having the highest voltage among the plurality of slave battery packs are controlled to be in an operating state, and then the flow returns to step S31.
In this embodiment, if the voltage difference values between the first voltage and the plurality of second voltages are greater than the preset voltage, it is determined that the master battery pack and the slave battery packs do not satisfy the parallel connection condition, and it is required to perform power-on processing on the battery pack with a high voltage first to make the battery pack in a working state for a preset time, and then it is determined whether the voltage difference value between the battery pack with a high voltage and any one of the other battery packs is less than or equal to the preset voltage; and if the voltage difference value between the battery pack with the high voltage and any one battery pack in other battery packs is determined to be less than or equal to the preset voltage, confirming that a battery parallel condition is met, controlling the battery pack with the high voltage to be in parallel connection with any one battery pack in other battery packs, and so on until the main battery pack and the plurality of slave battery packs are in parallel connection.
Specifically, the parallel connection method of the batteries further comprises the following steps: if the voltage difference value between any two of the first voltage and the second voltages is larger than the preset voltage through comparison; controlling the master battery pack and the battery pack with the highest voltage in the plurality of slave battery packs to be in an operating state; continuously collecting a first voltage of the master battery pack and a plurality of second voltages of a plurality of slave battery packs; if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to the preset voltage through comparison; and controlling the two corresponding battery packs to be connected in parallel when the voltage difference value is smaller than or equal to the preset voltage until the main battery pack and the plurality of slave battery packs are connected in parallel to obtain the battery parallel system.
For example, if three battery packs need to be connected in parallel, the voltages of the three battery packs are respectively collected, and if the voltage difference between any two of the three battery packs is smaller than or equal to the preset voltage, any two battery packs with the voltage difference smaller than or equal to the preset voltage are connected in parallel to obtain the battery parallel system. And if the voltage difference value between any two of the three battery packs is greater than the preset voltage, controlling the battery pack with the highest voltage in the three battery packs to be in a working state. And after the preset time, continuously comparing whether the voltage difference value between any two of the first voltage and the plurality of second voltages is smaller than or equal to a preset voltage. Continuously collecting a first voltage of the master battery pack and a plurality of second voltages of a plurality of slave battery packs; if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to the preset voltage through comparison; and controlling the two corresponding battery packs to be connected in parallel when the voltage difference value is smaller than or equal to the preset voltage until the main battery pack and the plurality of slave battery packs are connected in parallel to obtain the battery parallel system.
It should be noted that the capacities of the master battery pack and the slave battery packs do not need to be consistent during the parallel connection, and the capacity of the master battery pack may be different from or the same as the capacity of the slave battery packs. The capacity difference between any two parallel battery packs is allowed, and the battery packs with the capacity difference in different batches are favorably mixed. Specifically, the capacity difference may be a difference in design itself, or a difference caused by different use conditions under the same design.
The battery parallel system can be obtained by the battery parallel method, and the battery parallel system can bring more convenience and flexibility in use. Different numbers of battery packs can be placed according to different electric devices (such as electric automobiles). By adopting the parallel connection mode of the batteries, the rationality of the pressure difference between the battery packs is only controlled, the requirement on the capacity difference between the battery packs is not as high as that of the serial connection mode, and the mixed use of the battery packs with the capacity difference in different batches is facilitated. Meanwhile, the battery pack capacity can be reasonably configured according to different vehicle types and different endurance mileage requirements.
Referring to fig. 4, fig. 4 is a flowchart illustrating a method for estimating a battery state of charge of the battery parallel system constructed as shown in fig. 3 according to an embodiment of the present disclosure. The battery parallel system comprises a master battery pack and a plurality of slave battery packs, the master battery pack comprises a master battery management system, the slave battery packs comprise slave battery management systems, and the method for estimating the state of charge of the batteries in parallel can comprise the following steps:
step S41: the main battery management system collects first historical state data of the main battery pack in the recycling process.
In this embodiment, in order to estimate the state of charge of the battery parallel system more accurately, the master battery management system may collect the first historical state data during the recycling process of the battery parallel system. Wherein the first historical state data comprises first historical voltage data, first historical current data, first historical temperature data, first historical state of charge data, and a first number of cycles.
Step S42: and sending the first historical state data to a cloud big data platform, wherein the cloud big data platform estimates to obtain a first capacity and a first charge state according to the first historical state data and a first initial parameter of the main battery pack stored in advance.
In this embodiment, the cloud big data platform receives the first historical state data, and stores all the first historical state data of the master battery pack from factory operation. The cloud big data platform also pre-stores first initial parameters of the master battery pack, and the first initial parameters comprise a first factory date, a first initial capacity and the like. The cloud big data platform can obtain a first capacity and a first charge state according to the first historical state data and the first initial parameter estimation of the master battery pack.
Specifically, the estimating, by the cloud big data platform, a first capacity and a first state of charge according to the first historical state data and a first initial parameter of the master battery pack stored in advance includes:
(1) and dynamically updating the current SOC-OCV corresponding relation of the master battery pack based on the first historical state data. In the present embodiment, the stored first historical voltage data and the first historical state of charge data are subjected to matching analysis, so that the current state of charge-OCV correspondence can be dynamically updated.
(2) And correcting the rated capacity of the master battery pack according to the first historical state data and the initial parameters of the master battery pack to obtain the first capacity.
The capacity attenuation of the battery pack is influenced by rate charging and rate discharging in the use process, and the influence is larger when the rate is larger. Therefore, the number and time of charge and discharge exceeding the rated rate need to be counted. In the method, all the first historical current data are analyzed, all the multiplying power charging and multiplying power discharging exceeding the rated multiplying power existing in the using process are classified and accumulated according to the respective corresponding multiplying power values, and the time of all the multiplying power charging and multiplying power discharging exceeding the rated multiplying power under each multiplying power value is counted, so that the current rated capacity can be corrected according to the influence relationship of different multiplying power charging and discharging on the capacity.
Specifically, modifying the rated capacity of the battery according to the first historical state data and the initial parameter of the master battery pack to obtain the first capacity comprises: counting the times and duration of charge and discharge exceeding rated multiplying power in the first historical state data; determining the attenuation of the capacity of the master battery pack according to the times and the duration; and correcting the rated capacity of the main battery pack according to the attenuation of the capacity of the main battery pack and the first initial capacity to obtain the first capacity. It should be noted that, the cloud big data platform stores in advance the capacity attenuation of the master battery pack under different discharge rates.
For example, experiments have shown that a charge-discharge cycle (half an hour of charging and half an hour of discharging) of the main battery using a rate of 2C results in a capacity fade from a first preset capacity to a second preset capacity of the battery. And storing the capacity attenuation of the battery after the battery is charged and discharged for a preset time under the multiplying power of 2C to the cloud big data platform. If the master battery pack is actually recycled, 3600 times of current with 2C multiplying power appear, and the duration of each time is 1 second. After 3600 times of charge and discharge processes with 2C multiplying power, the capacity of the corresponding master battery pack should be the second preset capacity.
C is a charge/discharge rate, which is a current value required for charging to a rated capacity or discharging the rated capacity within a predetermined time, and is equal in value to the charge/discharge current/battery rated capacity. For example, when a battery with a rated capacity of 10Ah is discharged at 2A, the discharge rate is 0.2C; when the discharge is performed at 20A, the discharge rate is 2C.
In another embodiment, said modifying the rated capacity of the battery based on the first historical state data and the initial parameter of the master battery pack to obtain the first capacity further comprises: combining the first delivery date and the first historical temperature data of the main battery to obtain the standing time and the standing temperature of the main battery pack in the recycling process; calculating the attenuation of the capacity of the main battery pack according to the standing temperature and the standing time; and correcting the rated capacity of the master battery pack according to the attenuation of the capacity of the master battery pack and the first initial capacity to obtain the first capacity.
(3) And estimating the first state of charge according to the updated SOC-OCV corresponding relation, the corrected rated capacity and timely state data of the main battery pack (for example, the state data of the main battery pack in the last cycle use) of the battery in the use process received by the platform. Specifically, according to the current latest SOC-OCV corresponding relation, the corrected rated capacity and timely state data of the main battery pack received by the platform in the using process of the main battery pack, the cloud big data platform calculates a state of charge estimated value which is more consistent with the real state of charge of the main battery pack, and sends the state of charge estimated value to a corresponding main battery management system.
Step S43: and the slave battery management system collects second historical state data of the slave battery pack in the recycling process.
In this embodiment, the second historical state data includes second historical voltage data, second historical current data, second historical temperature data, second historical state of charge data, and a second number of cycles.
Step S44: and sending the second historical state data to a cloud big data platform, wherein the cloud big data platform estimates a second capacity and a second charge state according to the second historical state data and a second initial parameter of the slave battery pack stored in advance.
In this embodiment, the method for estimating the second capacity and the second state of charge by the cloud big data platform is the same as the method for estimating the first capacity and the first state of charge.
Specifically, the estimating, by the cloud big data platform, a second capacity and a second state of charge according to the second historical state data and the pre-stored initial parameters of the slave battery pack includes: dynamically updating the current SOC-OCV correspondence of the slave battery pack based on the second historical state data; correcting the rated capacity of the battery according to the second historical state data and the initial parameters of the slave battery pack to obtain a second capacity; and estimating the second state of charge according to the updated SOC-OCV corresponding relation, the second capacity and the received state data of the slave battery pack in the latest recycling process.
In this embodiment, the obtaining the second capacity by correcting the rated capacity of the battery based on the second historical state data and the initial parameter of the slave battery pack includes: counting the times and duration of charge and discharge exceeding rated multiplying power in the second historical state data; determining the attenuation of the capacity of the slave battery pack according to the times and the duration; and correcting the rated capacity of the slave battery pack according to the attenuation of the capacity of the slave battery pack and the second initial capacity to obtain the second capacity.
Step S45: the master battery management system receives the first capacity and the first state of charge sent by the cloud big data platform, and the slave battery management system receives the second capacity and the second state of charge sent by the cloud big data platform.
Calculating and calculating second historical state data according to the first historical state data on the cloud data scattering platform
Step S46: the main battery management system calculates the current state of charge SOC of the parallel system according to the first capacity, the first state of charge and the second capacity and the second state of chargeAnd are。
In this embodiment, ideally, the capacity of the battery parallel system is the capacity of a single battery pack multiplied by the number of battery packs, regardless of how many batteries are connected in parallel; the state of charge of the parallel battery system is the state of charge of one of the battery packs. However, in practical situations, due to different working conditions of each battery pack, even if the battery packs leave a factory, the capacities of the battery packs are different after the battery packs are used for a period of time, then the internal resistances are different, so that the states of charge are also different, and in another situation, the battery packs with the same voltage platform but different capacities are allowed to be connected in parallel, so that the calculated capacity and the state of charge of the whole parallel system cannot be in accordance with ideal conditions. Therefore, in the present application, the current state of charge SOC of the parallel system is calculated by the following formulaAnd are：
Wherein n is the sum of the master battery pack and the plurality of slave battery packs, C1For the first capacity, SOC1In the first state of charge, C2…CnFor the second capacity, SOC2…SOCnThe second state of charge.
In the present embodiment, the state of charge of the battery parallel system calculated by the electric device itself does not take into account the influence of the history data, and therefore, a certain error may exist. Thus, upon receiving the present state of charge SOCAnd areThen, the current state of charge SOC is usedAnd areAs the state of charge of the parallel battery system.
It should be noted that, in the box-splitting battery-swapping mode of the parallel connection mode of the high-voltage battery pack (i.e., the battery parallel connection system), the estimation of the execution state of charge based on the number of the box-splitting modules (the number of the battery packs) can be realized. For example, in a vehicle with only 1 battery pack, the total battery capacity calculated by the master battery management system is the battery pack capacity of the battery pack, and the state of charge calculated by the master battery management system is the state of charge of the battery pack. For the case of configuring more than 1 battery pack, the total battery capacity calculated by the main battery management system should be the sum of the total capacities of all the battery packs participating in parallel connection, and the state of charge calculated by the main battery management system should be the ratio of the total capacity to the remaining value obtained by subtracting the currently consumed electric quantity from the sum of the total actually available electric quantity.
Therefore, when the total battery capacity is adjusted modularly in a split-box battery changing mode, the main battery management system needs to realize adaptive matching of capacity and state of charge according to data uploaded from the battery management system in the battery pack in consideration of different numbers of battery packs and capacity difference of each battery pack, so that the electric vehicle can be guaranteed to obtain better power and cruising experience when in use.
In this application, the method for estimating the state of charge of the parallel battery system further includes: estimating and obtaining the actual state of charge of the battery parallel system (namely the state of charge of the battery parallel system calculated by the electric equipment) by combining an ampere-hour integration method and an open-circuit voltage method; determining a target charge for the battery parallel system based on the current state of charge and the actual state of chargeAn electrical state, wherein the current state of charge has a higher priority than the actual state of charge. Namely, the electric equipment receives the current state of charge SOC sent by the cloud big data platformAnd areAnd when the actual state of charge is estimated again, the current state of charge SOC is preferentially usedAnd areAs the state of charge of the parallel battery system.
In this embodiment, the actual state of charge may be a state of charge of the battery parallel system when the electric device is in a non-network state. Or when the network charge problem of the electric equipment is considered, the current state of charge SOC sent by the cloud big data platform is not received any moreAnd areIn the case of (3), the actual state of charge may be used as the state of charge of the battery.
In the present embodiment, the SOC-OCV curve of the battery has a steep gradient at both ends. The capacity change of the main battery and the slave battery pack at the early stage and the later stage of charging and discharging is obvious in corresponding voltage change, and the performance of the capacity change at the middle stage of charging and discharging on the voltage change is not obvious. And calculating the actual state of charge by adopting different methods in different charging and discharging stages.
Specifically, the estimation of the actual state of charge by combining the ampere-hour integration method and the open-circuit voltage method includes:
(1) and respectively dividing the SOC-OCV curves corresponding to the master battery pack and the slave battery packs into a voltage plateau area, a low voltage area and a high voltage area.
In this embodiment, the low-voltage region corresponds to a battery discharge later period, the plateau region corresponds to a battery charge/discharge intermediate period, and the high-voltage region corresponds to a battery charge later period. The slope of the curve corresponding to the voltage platform area changes slowly, and the span of the state of charge corresponding to the platform area is large; the slope of the SOC-OCV curve varies greatly in the low-voltage region and the high-voltage region. And respectively dividing the SOC-OCV curves corresponding to the master battery pack and the slave battery packs into a voltage plateau area, a low voltage area and a high voltage area.
(2) And calculating the actual charge states of the main battery pack and the auxiliary battery pack in the high-voltage area and the low-voltage area respectively through an open-circuit voltage method, and calculating the actual charge state of the battery parallel system based on the actual charge states of the main battery pack and the auxiliary battery pack.
At each charge, if the OCV of the battery satisfies the distinct characteristic point at the later stage of charge, or each discharge satisfies the distinct characteristic point at the later stage of discharge. That is, when the voltage reaches a certain value, it can be determined that the state of charge value corresponding to the value better conforms to the current true state of charge, and the priority of the open-circuit voltage method is higher than that of the ampere-hour integration method. The actual state of charge is calculated by the open circuit voltage method. Therefore, the accumulated error of the ampere-hour integration method can be eliminated, which is equal to zero clearing of the error when the charging or discharging is finished, and the error accumulation is prevented from increasing.
Specifically, the actual states of charge of the master battery pack and the slave battery pack are respectively calculated in the high-voltage area and the low-voltage area through an open-circuit voltage method, and the actual states of charge of the battery parallel system is calculated based on the actual states of charge of the master battery pack and the slave battery pack.
(3) And in the voltage leveling area, the actual charge states of the main battery pack and the slave battery pack are respectively calculated by an ampere-hour integration method, and the actual charge states of the battery parallel system are calculated and obtained based on the actual charge states of the main battery pack and the slave battery pack.
In the present embodiment, the priority level is high by the ampere-hour integration method in all stages except the later stage of charge and discharge. Namely, in the voltage leveling area, the second state of charge is calculated by an ampere-hour integration method. It is thus possible to avoid introducing large deviations of the open circuit voltage method when the cell voltage falls near its voltage plateau. And in the voltage leveling area, the actual charge states of the main battery pack and the slave battery pack are respectively calculated by an ampere-hour integration method, and the actual charge states of the battery parallel system are calculated and obtained based on the actual charge states of the main battery pack and the slave battery pack.
It should be noted that the ampere-hour integration method and the open-circuit voltage method are both existing methods for estimating the state of charge, and are not described in detail in this application.
According to the method, historical state data of the master battery pack and the slave battery packs are received through the cloud big data platform, state analysis of the battery parallel system in the whole life cycle is achieved, and the latest maximum available capacity and the more accurate SOC value, different from the rated capacity of the battery parallel system when the battery parallel system leaves a factory, in practical application are obtained; and meanwhile, the battery packs with the same voltage and different capacities are allowed to be used in a mixed mode, and the capacity value and the SOC value which are more consistent with the current battery parallel system can be obtained by the main battery management system according to data reported from the battery management system in the mixed mode. And the capacity adjustment of the battery parallel system can be realized by changing the number of the battery packs in the battery parallel system or changing the capacity of the battery packs, and the main battery management system can dynamically calculate the capacity and the SOC of the whole battery parallel system according to the number and the capacity of the battery packs.
Referring to fig. 5, in the present embodiment, the estimation system 100 may be divided into one or more modules, the one or more modules may be stored in the battery parallel system 11, and the battery parallel system 11 performs the method for estimating the SOC of the battery parallel system according to the embodiment of the present disclosure. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the estimation system 100 in the electric device 1. For example, the estimation system 100 may be divided into an acquisition module 101, a control module 102, a transmission module 103, a reception module 104, and a calculation module 105 in fig. 5.
The acquisition module 101 is configured to acquire a first voltage of a master battery pack and a plurality of second voltages of a plurality of slave battery packs; the control module 102 is configured to, if a voltage difference between any two of the first voltage and the plurality of second voltages is smaller than or equal to a preset voltage, control two battery packs corresponding to the voltage difference smaller than or equal to the preset voltage to be connected in parallel, so as to obtain a battery parallel system.
The acquisition module 101 is further configured to acquire first historical state data of the master battery pack in a recycling process; the sending module 103 is configured to send the first historical state data to a cloud big data tableThe cloud big data platform estimates to obtain a first capacity and a first charge state according to the first historical state data and a first initial parameter of the master battery pack stored in advance; the acquisition module 101 is further configured to acquire second historical state data of the slave battery pack in a recycling process; the sending module 103 is further configured to send the second historical state data to a cloud big data platform, where the cloud big data platform estimates a second capacity and a second state of charge according to the second historical state data and a second initial parameter of the slave battery pack stored in advance; the receiving module 104 is configured to receive the first capacity and the first state of charge sent by the cloud big data platform, and receive the second capacity and the second state of charge sent by the cloud big data platform from the battery management system; the calculation module 105 is configured to calculate a current state of charge SOC of the parallel system according to the first capacity, the first state of charge, and the second capacity and the second state of chargeAnd are。
The estimation system 100 can estimate the state of charge of the battery parallel system according to the historical data of the main battery pack and the slave battery pack in the battery parallel system in the charging and discharging process, and the estimation accuracy of the state of charge of the battery is improved. For details, reference may be made to the above-mentioned embodiments of the method for estimating the state of charge of the parallel battery system, and details will not be described here.
The modules in the evaluation system 100, if implemented in software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the embodiments of the methods described above can be realized. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It is understood that the above described module division is a logical function division, and there may be other division ways in actual implementation. In addition, functional modules in the embodiments of the present application may be integrated into the same processing unit, or each module may exist alone physically, or two or more modules are integrated into the same unit. The integrated module can be realized in a hardware form, and can also be realized in a form of hardware and a software functional module.
In another embodiment, the electric device 1 may further include a memory (not shown), and the one or more modules may be further stored in the memory and executed by the processor 11. The memory may be an internal memory of the powered device 1, i.e. a memory built into the powered device 1. In other embodiments, the memory may also be an external memory of the electric device 1, that is, a memory externally connected to the electric device 1.
In some embodiments, the memory is used for storing program codes and various data, for example, program codes of the evaluation system 100 installed in the electric device 1, and realizes high-speed and automatic access to programs or data during the operation of the electric device 1.
The memory may include random access memory and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (14)
1. A method of parallel connection of batteries, the method comprising:
collecting a first voltage of a master battery pack and a plurality of second voltages of a plurality of slave battery packs;
and if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to a preset voltage, controlling the two battery packs corresponding to the voltage difference value smaller than or equal to the preset voltage to be connected in parallel to obtain a battery parallel system.
2. The battery parallel method of claim 1, further comprising:
if the voltage difference between any two of the first voltage and the second voltages is larger than the preset voltage, controlling the battery pack with the highest voltage in the master battery pack and the plurality of slave battery packs to be in a working state;
continuously collecting a first voltage of the master battery pack and a plurality of second voltages of a plurality of slave battery packs;
if the voltage difference value between any two of the first voltage and the second voltages is smaller than or equal to the preset voltage through comparison;
and controlling the two corresponding battery packs to be connected in parallel when the voltage difference value is smaller than or equal to the preset voltage until the main battery pack and the plurality of slave battery packs are connected in parallel to obtain the battery parallel system.
3. The battery parallel method according to claim 2, wherein the capacity of the master battery pack is different from the capacity of the slave battery packs.
4. A method of estimating an SOC of a battery parallel system obtained by the battery parallel method according to any one of claims 1 to 3, the battery parallel system including a master battery pack including a master battery management system and a plurality of slave battery packs including slave battery management systems, the method comprising:
the main battery management system collects first historical state data of the main battery pack in a recycling process;
sending the first historical state data to a cloud big data platform, wherein the cloud big data platform estimates to obtain a first capacity and a first charge state according to the first historical state data and a first initial parameter of the main battery pack stored in advance;
the slave battery management system collects second historical state data of the slave battery pack in the recycling process;
sending the second historical state data to a cloud big data platform, wherein the cloud big data platform estimates a second capacity and a second charge state according to the second historical state data and a second initial parameter of the slave battery pack stored in advance;
the master battery management system receives the first capacity and the first charge state sent by the cloud big data platform, and the slave battery management system receives the second capacity and the second charge state sent by the cloud big data platform;
the main battery management system calculates the current state of charge SOC of the parallel system according to the first capacity, the first state of charge and the second capacity and the second state of chargeAnd are。
5. The method of estimating SOC of a parallel battery system according to claim 4, wherein the current SOC of the parallel battery system is calculated by the following formulaAnd are：
Wherein n is the sum of the master battery pack and the plurality of slave battery packs, C1For the first capacity, SOC1In the first state of charge, C2...CnFor the second capacity, SOC2...SOCnThe second state of charge.
6. The method of estimating the SOC of the parallel battery system according to claim 4, wherein:
the first historical state data comprises first historical voltage data, first historical current data, first historical temperature data, first historical state-of-charge data and first cycle times, and the first initial parameters comprise a first delivery date and a first initial capacity;
the second historical state data comprises second historical voltage data, second historical current data, second historical temperature data, second historical state-of-charge data and second cycle number, and the second initial parameters comprise a second delivery date and a second initial capacity.
7. The method for estimating SOC of a battery parallel system according to claim 6, wherein the estimating by the cloud big data platform a first capacity and a first state of charge based on the first historical state data and a first pre-stored initial parameter of the master battery pack comprises:
dynamically updating the current SOC-OCV corresponding relation of the master battery pack based on the first historical state data;
correcting the rated capacity of the master battery pack according to the first historical state data and the initial parameters of the master battery pack to obtain the first capacity;
and estimating the first state of charge according to the updated SOC-OCV corresponding relation, the first capacity and the received state data of the main battery pack in the last recycling process.
8. The method of estimating SOC of a battery parallel system of claim 7, wherein modifying the rated capacity of the battery based on the first historical state data and the initial parameter of the master battery pack to obtain the first capacity comprises:
counting the times and duration of charge and discharge exceeding rated multiplying power in the first historical state data;
determining the attenuation of the capacity of the master battery pack according to the times and the duration; and
and correcting the rated capacity of the master battery pack according to the attenuation of the capacity of the master battery pack and the first initial capacity to obtain the first capacity.
9. The method for estimating SOC of a battery parallel system according to claim 6, wherein the estimating by the cloud big data platform a second capacity and a second state of charge based on the second historical state data and the pre-stored initial parameters of the slave battery pack comprises:
dynamically updating the current SOC-OCV correspondence of the slave battery pack based on the second historical state data;
correcting the rated capacity of the battery according to the second historical state data and the initial parameters of the slave battery pack to obtain a second capacity;
and estimating the second state of charge according to the updated SOC-OCV corresponding relation, the second capacity and the received state data of the slave battery pack in the latest recycling process.
10. The method of estimating SOC of a battery parallel system according to claim 9, wherein modifying the rated capacity of the battery based on the second historical state data and the initial parameters of the slave battery pack, and obtaining the second capacity comprises:
counting the times and duration of charge and discharge exceeding rated multiplying power in the second historical state data;
determining the attenuation of the capacity of the slave battery pack according to the times and the duration; and
and correcting the rated capacity of the slave battery pack according to the attenuation of the capacity of the slave battery pack and the second initial capacity to obtain the second capacity.
11. The method of estimating SOC of a parallel battery system of claim 4, further comprising:
estimating and obtaining the actual state of charge of the battery parallel system by combining an ampere-hour integration method and an open-circuit voltage method; and
determining a target state of charge of the battery parallel system based on the current state of charge and the actual state of charge, wherein the priority of the current state of charge is higher than the priority of the actual state of charge.
12. The method for estimating the SOC of the battery parallel system according to claim 4, wherein the estimating the actual state of charge of the battery parallel system by combining an ampere-hour integration method and an open-circuit voltage method comprises:
respectively dividing SOC-OCV curves corresponding to the master battery pack and the slave battery packs into a voltage flat area, a low-voltage area and a high-voltage area;
calculating the actual state of charge of the main battery pack and the actual state of charge of the auxiliary battery pack in the high-voltage area and the low-voltage area respectively through an open-circuit voltage method, and calculating the actual state of charge of the battery parallel system based on the actual state of charge of the main battery pack and the actual state of charge of the auxiliary battery pack; and
and in the voltage leveling area, the actual charge states of the main battery pack and the slave battery pack are respectively calculated by an ampere-hour integration method, and the actual charge states of the battery parallel system are calculated and obtained based on the actual charge states of the main battery pack and the slave battery pack.
13. An electrical device, comprising:
a battery parallel system;
and a processor for performing the battery parallel method according to any one of claims 1 to 3 or the method of estimating the SOC of the battery parallel system according to any one of claims 4 to 12.
14. A storage medium having stored thereon at least one computer instruction, wherein the instruction is loaded by a processor and used to perform the battery parallel method according to any of claims 1 to 3 or to perform the method of estimating SOC of a battery parallel system according to any of claims 4 to 12.
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