CN118017037A - Intelligent battery management system - Google Patents

Intelligent battery management system Download PDF

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Publication number
CN118017037A
CN118017037A CN202311790827.2A CN202311790827A CN118017037A CN 118017037 A CN118017037 A CN 118017037A CN 202311790827 A CN202311790827 A CN 202311790827A CN 118017037 A CN118017037 A CN 118017037A
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China
Prior art keywords
charging
battery
battery pack
intelligent
management system
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Pending
Application number
CN202311790827.2A
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Chinese (zh)
Inventor
汪大海
司武标
潘萍
谢亮亮
刘想
宋飞
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Hefei Ecolite Software Co ltd
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Hefei Ecolite Software Co ltd
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Priority to CN202311790827.2A priority Critical patent/CN118017037A/en
Publication of CN118017037A publication Critical patent/CN118017037A/en
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Abstract

The application relates to the technical field of battery management, and discloses an intelligent battery management system, which comprises a battery pack, an electronic switch matrix, a plurality of state detection modules and an intelligent management module, wherein the intelligent management module is electrically connected with the electronic switch matrix, the battery pack and the state detection modules and is configured to: and controlling the battery pack to execute a charge-discharge task based on the control instruction, performing safety protection on the battery pack based on the detected state parameter, and performing optimal management on charge and discharge of the battery pack based on the detected state parameter. The application realizes the management and safety protection of the battery pack, and avoids the situation that the operation of the whole battery pack needs to be blocked when an abnormal state occurs to the individual battery units. Meanwhile, based on detection of state parameters, analysis of user behavior habits is achieved, and further charge and discharge of the battery pack are optimally managed, so that the service life of the battery pack is ensured and the user experience is improved on the premise that actual use requirements of users are met.

Description

Intelligent battery management system
Technical Field
The application relates to the technical field of battery management, in particular to an intelligent battery management system.
Background
The BATTERY management system (BATTERY MANAGEMENT SYSTEM, BMS) is an important link for connecting a power BATTERY and a load, and is used for estimating the State of Charge (SOC) of a BATTERY pack through a specific algorithm and preventing the BATTERY pack from being overcharged and overdischarged in a fault alarm mode, so that the service life of the BATTERY pack is prolonged, and general functions include: battery physical parameter acquisition, battery state estimation, charge, discharge and pre-charge control, balance management, communication and the like.
In the existing battery management systems, only some basic functional modules are generally constructed to perform task scheduling, and state division and adjustment cannot be realized based on the use environment and user behaviors, namely, the problems of unclear work scheduling and imperfect functions exist.
Disclosure of Invention
The present application is directed to an intelligent battery management system, which solves the above-mentioned technical problems.
In order to achieve the above purpose, the present application discloses the following technical solutions: an intelligent battery management system, comprising:
The battery pack comprises a plurality of battery units;
The electronic switch matrix comprises a plurality of electronic switches, each of which is electrically connected with one of the battery units and is configured to: controlling the conduction or blocking of a power supply circuit corresponding to the battery unit;
each state detection module is electrically connected with one battery unit and is configured to: the state parameters are used for collecting the battery units;
The intelligent management module is electrically connected with the electronic switch matrix, the battery pack and the state detection module and is configured to: and controlling the corresponding battery unit to execute a charge-discharge task based on the control instruction, performing safety protection on the battery unit based on the detected state parameter, and further configuring to: based on the detected state parameters, optimally managing the charging and discharging of the battery unit; the optimal management of charging specifically comprises the following steps:
s1: analyzing the charging behavior habit of the user according to the detected state parameters;
s2: based on the charging behavior habit obtained by analysis, various charging strategies are formulated;
S3: sequencing the formulated charging strategies according to the charging time length corresponding to the charging behavior habit to obtain a strategy set { STR 1,STR2,...,STRN }, wherein the charging time length corresponding to STR 1 is smaller than the charging time length corresponding to STR 2;
S4: and when the charging task is executed, the charging strategies are sequentially executed according to the sequence in the strategy set { STR 1,STR2,...,STRN }, and the charging is ended until the battery pack reaches a full-charge state or the user stops the charging task actively.
Preferably, the battery unit includes a battery cell and/or a battery unit formed by a plurality of batteries.
Preferably, the battery unit comprises a plurality of battery cells connected in series or in parallel.
Preferably, the state acquisition module includes: the device comprises a voltage acquisition unit, a current acquisition unit and a temperature acquisition unit; the state parameters include a current parameter, a voltage parameter, and a temperature parameter.
Preferably, the safety protection of the battery unit based on the detected state parameter specifically includes:
Inputting the detected state parameters into a state judgment model, wherein the state judgment model is obtained by deep learning by taking any two or more of all the state parameters of the battery pack when the state parameters of the battery pack are normal, any one of the state parameters of the battery pack is abnormal and any two or more of the state parameters of the battery pack are abnormal as learning characteristics, and the state judgment model outputs a corresponding judgment result based on the input state parameters;
and carrying out safety protection on the battery pack based on the judging result output by the state judging model.
Preferably, the judging result includes: one or more of cell over temperature, cell over current, cell open circuit, cell short circuit, cell under voltage, cell over voltage hysteresis.
Preferably, the safety protection includes: the intelligent management module starts a protection circuit corresponding to the judging result or controls an electronic switch corresponding to the battery unit to block the battery unit; the protection circuit includes: one or more of an over-temperature protection circuit, an over-current protection circuit, an under-voltage protection circuit, an over-voltage protection circuit and an over-voltage hysteresis protection circuit.
Preferably, the analyzing the charging behavior habit of the user specifically includes:
Acquiring single charging time t Δtime, single charging amount w ΔQ and electric quantity Q over of the battery pack at the end of charging of a user;
Generating a user charging habit based on a single charge amount of a user and an amount of electricity of a battery pack at the end of charging, the charging habit including: the method comprises the steps of defining that each charging is full of corresponding full-charge charging habit and defining that the electric quantity of each charging determines corresponding on-demand charging habit according to use requirements;
Making an electric value trend chart based on the single charging time length, the single charging amount and the electric quantity of the battery pack at the end of charging corresponding to the on-demand charging habit;
Dividing the electric quantity of the battery pack at the end of charging in the electric value trend graph according to a plurality of preset distribution intervals, acquiring on-demand charging behavior judgment intervals taking the electric quantity of the battery pack at the end of charging as a decision element, calculating the required power corresponding to each judgment interval, and calculating the required power according to the following formula:
Wherein w' ΔQ is the maximum value in the single charge amount within the determination section, To determine the average value of the single charge in the interval, t' Δtime is the maximum value of the single charge duration in the interval,/>Is the average value of the single charging duration in the judging section.
Preferably, the charging strategy includes: duration of charging, required power of charging.
Preferably, the optimization management of the discharge specifically comprises the following steps:
and based on the number of battery units adopted by the user in the past discharging task process and the total electric quantity of the battery pack, carrying out configuration coordination on the battery units required to be used in the upcoming discharging task.
The beneficial effects are that: the intelligent battery management system realizes the management and the safety protection of the battery pack based on the detection of the state parameters, and realizes the function of partition/separate management through the configuration of the electronic switch matrix and the battery units, thereby avoiding the need of blocking the operation of the whole battery pack when the individual battery units are abnormal, and further improving the practicability. Further, the application realizes analysis of behavior habits of users based on detection of state parameters, and further optimizes and manages charging and discharging of the battery unit, thereby ensuring the service life of the battery pack and improving the use experience of users on the premise of meeting the actual use demands of users.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an intelligent battery management system according to an embodiment of the present application;
Fig. 2 is a flow chart of optimization management of charging according to an embodiment of the present application.
Detailed Description
The following description of the technical solutions in the embodiments of the present application will be clear and complete, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In a first aspect, the present embodiment discloses an intelligent battery management system as shown in fig. 1, which includes a battery pack, an electronic switch matrix, a plurality of status detection modules, and an intelligent management module.
Specific: the battery pack comprises a plurality of battery units. In this embodiment, the battery unit includes a battery unit and/or a battery unit formed by a plurality of batteries, and the battery unit includes a plurality of battery units connected in series or in parallel.
Specific: the electronic switch matrix comprises a plurality of electronic switches, each of which is electrically connected with one of the battery units and is configured to: and controlling the conduction or blocking of a power supply circuit corresponding to the battery unit.
Specific: each state detection module is electrically connected with one battery unit respectively and is configured to: for collecting state parameters of the battery cells. In this embodiment, the state acquisition module includes: the device comprises a voltage acquisition unit, a current acquisition unit and a temperature acquisition unit; the state parameters include a current parameter, a voltage parameter, and a temperature parameter.
Specific: the intelligent management module is electrically connected with the electronic switch matrix, the battery pack and the state detection module and is configured to: and controlling the corresponding battery unit to execute a charge-discharge task based on the control instruction, performing safety protection on the battery unit based on the detected state parameter, and further configuring to: and optimally managing the charging and discharging of the battery unit based on the detected state parameters.
As a possible implementation manner of this embodiment, the performing safety protection on the battery unit based on the detected state parameter specifically includes:
Inputting the detected state parameters into a state judgment model, wherein the state judgment model is obtained by deep learning by taking any two or more of all the state parameters of the battery pack when the state parameters of the battery pack are normal, any one of the state parameters of the battery pack is abnormal and any two or more of the state parameters of the battery pack are abnormal as learning characteristics, and the state judgment model outputs a corresponding judgment result based on the input state parameters;
and carrying out safety protection on the battery pack based on the judging result output by the state judging model.
Wherein, the judging result comprises: one or more of cell over temperature, cell over current, cell open circuit, cell short circuit, cell under voltage, cell over voltage hysteresis. The safety protection includes: the intelligent management module starts a protection circuit corresponding to the judging result or controls an electronic switch corresponding to the battery unit to block the battery unit; the protection circuit includes: one or more of an over-temperature protection circuit, an over-current protection circuit, an under-voltage protection circuit, an over-voltage protection circuit and an over-voltage hysteresis protection circuit.
In this embodiment, as shown in fig. 2, the optimization management of charging specifically includes the following steps:
s1: analyzing the charging behavior habit of the user according to the detected state parameters;
s2: based on the charging behavior habit obtained by analysis, various charging strategies are formulated;
S3: sequencing the formulated charging strategies according to the charging time length corresponding to the charging behavior habit to obtain a strategy set { STR 1,STR2,...,STRN }, wherein the charging time length corresponding to STR 1 is smaller than the charging time length corresponding to STR 2;
S4: and when the charging task is executed, the charging strategies are sequentially executed according to the sequence in the strategy set { STR 1,STR2,...,STRN }, and the charging is ended until the battery pack reaches a full-charge state or the user stops the charging task actively.
It is possible that the charging strategy includes: duration of charging, required power of charging. Correspondingly, as a preferred implementation manner of the optimal management of charging, the analyzing the charging behavior habit of the user specifically includes:
Acquiring single charging time t Δtime, single charging amount w ΔQ and electric quantity Q over of the battery pack at the end of charging of a user;
Generating a user charging habit based on a single charge amount of a user and an amount of electricity of a battery pack at the end of charging, the charging habit including: the method comprises the steps of defining that each charging is full of corresponding full-charge charging habit and defining that the electric quantity of each charging determines corresponding on-demand charging habit according to use requirements;
Making an electric value trend chart based on the single charging time length, the single charging amount and the electric quantity of the battery pack at the end of charging corresponding to the on-demand charging habit;
Dividing the electric quantity of the battery pack at the end of charging in the electric value trend graph according to a plurality of preset distribution intervals, acquiring on-demand charging behavior judgment intervals taking the electric quantity of the battery pack at the end of charging as a decision element, calculating the required power corresponding to each judgment interval, and calculating the required power according to the following formula:
Wherein w' ΔQ is the maximum value in the single charge amount within the determination section, To determine the average value of the single charge in the interval, t' Δtime is the maximum value of the single charge duration in the interval,/>Is the average value of the single charging duration in the judging section.
In this embodiment, the optimized management of discharge specifically includes the following steps:
And based on the number of battery units adopted by the user in the past discharging task process and the total electric quantity of the battery pack, carrying out configuration coordination on the battery units required to be used in the upcoming discharging task. The configuration coordination here includes: the number of battery cells used, the discharge power, etc.
In summary, the intelligent battery management system provided in this embodiment realizes management and safety protection of the battery pack based on detection of the state parameter, and realizes the function of partition/separate management through configuration of the electronic switch matrix and the battery units, so as to avoid that when an abnormality occurs in an individual battery unit, the operation of the whole battery pack needs to be blocked, thereby improving practicality. Further, the application realizes analysis of behavior habits of users based on detection of state parameters, and further optimizes and manages charging and discharging of the battery unit, thereby ensuring the service life of the battery pack and improving the use experience of users on the premise of meeting the actual use demands of users.
In the embodiments provided by the present application, it is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For a hardware implementation, the processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the flow of an embodiment may be accomplished by a computer program to instruct the associated hardware. When implemented, the above-described programs may be stored in or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. The computer-readable storage media may include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that: the foregoing description is only illustrative of the preferred embodiments of the present application, and although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described, or equivalents may be substituted for elements thereof, and any modifications, equivalents, improvements or changes may be made without departing from the spirit and principles of the present application.

Claims (10)

1. An intelligent battery management system, comprising:
The battery pack comprises a plurality of battery units;
The electronic switch matrix comprises a plurality of electronic switches, each of which is electrically connected with one of the battery units and is configured to: controlling the conduction or blocking of a power supply circuit corresponding to the battery unit;
each state detection module is electrically connected with one battery unit and is configured to: the state parameters are used for collecting the battery units;
The intelligent management module is electrically connected with the electronic switch matrix, the battery pack and the state detection module and is configured to: and controlling the corresponding battery unit to execute a charge-discharge task based on the control instruction, performing safety protection on the battery unit based on the detected state parameter, and further configuring to: based on the detected state parameters, optimally managing the charging and discharging of the battery unit; the optimal management of charging specifically comprises the following steps:
s1: analyzing the charging behavior habit of the user according to the detected state parameters;
s2: based on the charging behavior habit obtained by analysis, various charging strategies are formulated;
S3: sequencing the formulated charging strategies according to the charging time length corresponding to the charging behavior habit to obtain a strategy set { STR 1,STR2,...,STRN }, wherein the charging time length corresponding to STR 1 is smaller than the charging time length corresponding to STR 2;
S4: and when the charging task is executed, the charging strategies are sequentially executed according to the sequence in the strategy set { STR 1,STR2,...,STRN }, and the charging is ended until the battery pack reaches a full-charge state or the user stops the charging task actively.
2. The intelligent battery management system of claim 1, wherein the battery cell comprises a single cell and/or a plurality of cells.
3. The intelligent battery management system of claim 2, wherein the battery unit comprises a plurality of battery cells connected in series or parallel.
4. The intelligent battery management system of claim 1, wherein the status acquisition module comprises: the device comprises a voltage acquisition unit, a current acquisition unit and a temperature acquisition unit; the state parameters include a current parameter, a voltage parameter, and a temperature parameter.
5. The intelligent battery management system according to any one of claims 1 or 4, wherein the safety protection for the battery cell based on the detected state parameter comprises:
Inputting the detected state parameters into a state judgment model, wherein the state judgment model is obtained by deep learning by taking any two or more of all the state parameters of the battery pack when the state parameters of the battery pack are normal, any one of the state parameters of the battery pack is abnormal and any two or more of the state parameters of the battery pack are abnormal as learning characteristics, and the state judgment model outputs a corresponding judgment result based on the input state parameters;
and carrying out safety protection on the battery pack based on the judging result output by the state judging model.
6. The intelligent battery management system according to claim 5, wherein the determination result includes: one or more of cell over temperature, cell over current, cell open circuit, cell short circuit, cell under voltage, cell over voltage hysteresis.
7. The intelligent battery management system of claim 5, wherein the safety guard comprises: the intelligent management module starts a protection circuit corresponding to the judging result or controls an electronic switch corresponding to the battery unit to block the battery unit; the protection circuit includes: one or more of an over-temperature protection circuit, an over-current protection circuit, an under-voltage protection circuit, an over-voltage protection circuit and an over-voltage hysteresis protection circuit.
8. The intelligent battery management system according to claim 1, wherein the analyzing the charging behavior habit of the user comprises:
Acquiring single charging time t Δtime, single charging amount w ΔQ and electric quantity Q over of the battery pack at the end of charging of a user;
Generating a user charging habit based on a single charge amount of a user and an amount of electricity of a battery pack at the end of charging, the charging habit including: the method comprises the steps of defining that each charging is full of corresponding full-charge charging habit and defining that the electric quantity of each charging determines corresponding on-demand charging habit according to use requirements;
Making an electric value trend chart based on the single charging time length, the single charging amount and the electric quantity of the battery pack at the end of charging corresponding to the on-demand charging habit;
Dividing the electric quantity of the battery pack at the end of charging in the electric value trend graph according to a plurality of preset distribution intervals, acquiring on-demand charging behavior judgment intervals taking the electric quantity of the battery pack at the end of charging as a decision element, calculating the required power corresponding to each judgment interval, and calculating the required power according to the following formula:
Wherein w' ΔQ is the maximum value in the single charge amount within the determination section, To determine the average value of the single charge in the interval, t' Δtime is the maximum value of the single charge duration in the interval,/>Is the average value of the single charging duration in the judging section.
9. The intelligent battery management system of claim 8, wherein the charging strategy comprises: duration of charging, required power of charging.
10. The intelligent battery management system according to claim 1, wherein the optimized management of discharge comprises the steps of:
and based on the number of battery units adopted by the user in the past discharging task process and the total electric quantity of the battery pack, carrying out configuration coordination on the battery units required to be used in the upcoming discharging task.
CN202311790827.2A 2023-12-25 2023-12-25 Intelligent battery management system Pending CN118017037A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311790827.2A CN118017037A (en) 2023-12-25 2023-12-25 Intelligent battery management system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311790827.2A CN118017037A (en) 2023-12-25 2023-12-25 Intelligent battery management system

Publications (1)

Publication Number Publication Date
CN118017037A true CN118017037A (en) 2024-05-10

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Application Number Title Priority Date Filing Date
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