CN113391210A - Lithium battery BMS distributed data analysis management system - Google Patents
Lithium battery BMS distributed data analysis management system Download PDFInfo
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- CN113391210A CN113391210A CN202110616428.9A CN202110616428A CN113391210A CN 113391210 A CN113391210 A CN 113391210A CN 202110616428 A CN202110616428 A CN 202110616428A CN 113391210 A CN113391210 A CN 113391210A
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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]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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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
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current 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]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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Abstract
The invention discloses a lithium battery BMS distributed data analysis management system, and particularly relates to the technical field of battery BMS systems, wherein the system comprises a data acquisition module, a BMS system and a vehicle MCU which are sequentially connected through a CAN communication bus; the data acquisition module is used for acquiring voltage, temperature, current and insulation resistance of the battery system and providing real-time data of the battery system for the BMS; the BMS system comprises an SOC calculation module, an SOH calculation module, a charging management module, a discharging management module and a safety protection module; the SOC calculation module is used for calculating the charge state of the power battery system and is the percentage of the residual electric quantity of the power battery system to the battery capacity. The invention can dynamically monitor the temperature, voltage, charge and discharge and other related parameters of the power battery system in real time, and actively take emergency measures to protect the power battery system when necessary, thereby preventing the danger of overcharge, overdischarge, overhigh temperature, short circuit and the like of the internal battery cell.
Description
Technical Field
The invention relates to the technical field of battery BMS systems, in particular to a distributed data analysis management system of a lithium battery BMS.
Background
As is well known, the power output of a pure electric vehicle depends on a battery, and a battery Management system bms (battery Management system) is a core thereof and is responsible for controlling the charging and discharging of the battery and implementing functions such as battery state estimation. If an electric vehicle is compared to the human body, the battery system is his heart, and the BMS battery management system is the brain that governs the operation of his body. The BMS battery system is mainly to intelligently manage and maintain each battery cell, prevent overcharge and overdischarge of the battery, extend the life span of the battery, and monitor the state of the battery.
Disclosure of Invention
In order to achieve the purpose, the invention provides the following technical scheme: a lithium battery BMS distributed data analysis management system comprises a data acquisition module, a BMS system and a vehicle MCU which are sequentially connected through a CAN communication bus;
the data acquisition module is used for acquiring voltage, temperature, current and insulation resistance of the battery system and providing real-time data of the battery system for the BMS;
the BMS system comprises an SOC calculation module, an SOH calculation module, a charging management module, a discharging management module and a safety protection module;
the SOC calculation module is used for calculating the charge state of the power battery system, and the charge state is the percentage of the residual electric quantity of the power battery system to the battery capacity;
the SOH calculation module is used for calculating the health state of the power battery system, and the health state is the percentage of the number of the full charging times of the power battery system and the available charging times of the service life cycle of the battery;
the safety protection module is used for protecting the power battery system, measures for limiting the working mode of the battery are adopted in a grading manner, and the maximum working efficiency of the power battery system is kept on the premise of safety;
the charging management module linearly looks up a table of charging power MAP of the battery system based on the current cell temperature and SOC of the power battery system, so as to determine the current maximum allowable charging current of the system;
the discharging management module carries out linear table look-up on 10s/30s peak discharging power MAP and continuous discharging power MAP of the power battery system based on the temperature collected in real time and the estimated SOC to obtain the current 10s/30s peak discharging power value and continuous discharging power value of the battery system, and reports the peak discharging power value and the continuous discharging power value to a vehicle MCU (microprogrammed control Unit) to realize charging management;
wherein the SOC in the discharged state is calculated as:
the SOC at state of charge is calculated as:
in the formula: lSOCThe state of health of the battery of the power battery system is shown; alpha is alpha1The rated capacity of the power battery system under the corresponding current is obtained; i istThe current is the current at any time in the discharging process of the power battery system.
In a preferred embodiment, the data acquisition module acquires voltage, temperature, current and insulation resistance, the voltage acquisition refers to the voltage of each string of cells in the power battery system, the total internal voltage Vbat of the battery system and the total external voltage Vlink of the battery system, the temperature acquisition refers to the temperature of the surface of the cell and the tab, the temperature of the liquid cooling water inlet/outlet, the temperature of the quick-charging pile interface and the internal working temperature of the BMS system, the current acquisition refers to the current value of the main loop part of the battery system, and the insulation resistance acquisition refers to the insulation resistance between the total positive and the box of the battery system and the insulation resistance between the total negative and the box of the battery system.
A lithium battery BMS distributed data analysis management method comprises the following steps:
the method comprises the following steps that firstly, a data acquisition module acquires voltage, temperature, current and insulation resistance data, and a BMS calculates and acquires an SOC value and an SOC value of a power battery system;
step two, the BMS reports voltage, temperature, current, SOC and SOH data of the power battery system to a vehicle MCU through a CAN communication bus, the vehicle MCU processes the data, when the power battery system has an abnormal fault, the BMS needs to timely protect the battery system, and power limiting and immediate power-off protection measures are taken in a grading manner according to the severity of the fault, so that the battery system is ensured to utilize the stored energy to the maximum extent under the safety premise;
step three, in the charging and discharging process of the power battery system, the BMS system reports the temperature of the surface and the lug of the battery cell in the power battery system and the temperature of the liquid cooling inlet and outlet interface to the vehicle MCU, the vehicle MCU analyzes the temperature data reported by the BMS system, and the liquid cooling system is started to heat or radiate the power battery system, so that the battery system is charged and discharged at a proper environment temperature;
and step four, the BMS linearly looks up the charging power MAP of the battery system according to the current core temperature and SOC of the battery system so as to determine the current maximum allowable charging current of the system, and estimates the charging remaining time according to the maximum output capacity of the charger and the charging state of the battery system.
In a preferred embodiment, the BMS system may further store historical information, and reduce an operation load of the main system through comparison and analysis of the historical information.
In a preferred embodiment, the BMS formulates a fault pre-determination table including a fault name, a fault threshold, a fault return difference, fault detection time, and response time according to a change trend of historical data and a change curve of the SOC and SOH values collected by the data collection module, and generates corresponding fault level data.
The invention has the technical effects and advantages that:
the invention can dynamically monitor the temperature, voltage, charge and discharge and other related parameters of the power battery system in real time, and actively take emergency measures to protect the power battery system when necessary, thereby preventing the danger of overcharge, overdischarge, overhigh temperature, short circuit and the like of the internal battery cell, effectively monitoring, protecting, balancing energy and giving fault alarm to the battery pack, further improving the working efficiency and prolonging the service life of the whole power battery pack.
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FIG. 1 is a schematic diagram of the system framework of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. The embodiments of the present invention have been presented for purposes of illustration and description, and are not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
The distributed data analysis and management system for the lithium battery BMS as shown in FIG. 1 comprises a data acquisition module, a BMS system and a vehicle MCU which are sequentially connected through a CAN communication bus;
the data acquisition module is used for acquiring voltage, temperature, current and insulation resistance of the battery system and providing real-time data of the battery system for the BMS;
the BMS system comprises an SOC calculation module, an SOH calculation module, a charging management module, a discharging management module and a safety protection module;
the SOC calculation module is used for calculating the charge state of the power battery system, and the charge state is the percentage of the residual electric quantity of the power battery system to the battery capacity;
the SOH calculation module is used for calculating the health state of the power battery system, and the health state is the percentage of the number of the full charging times of the power battery system and the available charging times of the service life cycle of the battery;
the safety protection module is used for protecting the power battery system, measures for limiting the working mode of the battery are adopted in a grading manner, and the maximum working efficiency of the power battery system is kept on the premise of safety;
the charging management module linearly looks up a table of charging power MAP of the battery system based on the current cell temperature and SOC of the power battery system, so as to determine the current maximum allowable charging current of the system;
the discharging management module carries out linear table look-up on 10s/30s peak discharging power MAP and continuous discharging power MAP of the power battery system based on the temperature collected in real time and the estimated SOC to obtain the current 10s/30s peak discharging power value and continuous discharging power value of the battery system, and reports the peak discharging power value and the continuous discharging power value to a vehicle MCU (microprogrammed control Unit) to realize charging management;
wherein the SOC in the discharged state is calculated as:
the SOC at state of charge is calculated as:
in the formula: lSOCThe state of health of the battery of the power battery system is shown; alpha is alpha1The rated capacity of the power battery system under the corresponding current is obtained; i istThe current is the current at any time in the discharging process of the power battery system.
The collection of data acquisition module includes voltage, temperature, electric current, insulation resistance, voltage acquisition is the voltage of every cluster of electric core in the power battery system, the inside total voltage Vbat of battery system and the outside total voltage Vlink of battery system, temperature acquisition is the temperature of electric core surface and utmost point ear, the temperature of liquid cooling inlet outlet, fill stake interface temperature and BMS system work internal temperature soon, current acquisition is the current value of battery system major loop part, insulation resistance acquisition is for gathering the total positive and the box between insulation resistance of battery system, and the total burden of battery system and the box between insulation resistance.
A lithium battery BMS distributed data analysis management method comprises the following steps:
the method comprises the following steps that firstly, a data acquisition module acquires voltage, temperature, current and insulation resistance data, and a BMS calculates and acquires an SOC value and an SOC value of a power battery system;
step two, the BMS reports voltage, temperature, current, SOC and SOH data of the power battery system to a vehicle MCU through a CAN communication bus, the vehicle MCU processes the data, when the power battery system has an abnormal fault, the BMS needs to timely protect the battery system, and power limiting and immediate power-off protection measures are taken in a grading manner according to the severity of the fault, so that the battery system is ensured to utilize the stored energy to the maximum extent under the safety premise;
step three, in the charging and discharging process of the power battery system, the BMS system reports the temperature of the surface and the lug of the battery cell in the power battery system and the temperature of the liquid cooling inlet and outlet interface to the vehicle MCU, the vehicle MCU analyzes the temperature data reported by the BMS system, and the liquid cooling system is started to heat or radiate the power battery system, so that the battery system is charged and discharged at a proper environment temperature;
step four, the BMS linearly looks up a table for the charging power MAP of the battery system according to the current core temperature and SOC of the battery system, so that the current maximum allowable charging current of the system is determined, and the charging remaining time is estimated according to the maximum output capacity of a charger and the charging state of the battery system;
the BMS system can also store historical information, and reduces the operation load of the main system through the comparison and analysis of the historical information.
The BMS system formulates a fault pre-judgment table according to the change trend of historical data acquired by the data acquisition module and the change curve of the SOC and SOH values, wherein the fault pre-judgment table comprises fault names, fault threshold values, fault return differences, fault detection time and response time, and corresponding fault grade data are generated.
Further, the BMS system also acquires the temperature of the quick charging interface, and in order to judge whether the quick charging interface is connected well or the interface is over-temperature caused by over-current, safety accidents are prevented;
and the BMS linearly looks up the 10s/30s peak discharge power MAP and the continuous discharge power MAP of the power battery system according to the temperature collected in real time and the estimated SOC to obtain the current 10s/30s peak discharge power value and continuous discharge power value of the battery system, and reports the peak discharge power value and the continuous discharge power value to the whole vehicle MCU.
The MCU compares the motor requested power P1 (which is converted from the motor speed at which the vehicle is running) with the peak discharge power Pmax and the sustained discharge power Pc reported by the BMS.
When P1 is larger than Pmax, discharging and timing the peak discharge power Pmax of the battery system, and reducing to the continuous discharge power Pc to discharge after time out; when P1 < Pc, the next peak discharge power Pmax discharge occurs in the BMS.
It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by one of ordinary skill in the art and related arts based on the embodiments of the present invention without any creative effort, shall fall within the protection scope of the present invention. Structures, devices, and methods of operation not specifically described or illustrated herein are generally practiced in the art without specific recitation or limitation.
Claims (5)
1. A lithium battery BMS distributed data analysis management system is characterized by comprising a data acquisition module, a BMS system and a vehicle MCU which are sequentially connected through a CAN communication bus;
the data acquisition module is used for acquiring voltage, temperature, current and insulation resistance of the battery system and providing real-time data of the battery system for the BMS;
the BMS system comprises an SOC calculation module, an SOH calculation module, a charging management module, a discharging management module and a safety protection module;
the SOC calculation module is used for calculating the charge state of the power battery system, and the charge state is the percentage of the residual electric quantity of the power battery system to the battery capacity;
the SOH calculation module is used for calculating the health state of the power battery system, and the health state is the percentage of the number of the full charging times of the power battery system and the available charging times of the service life cycle of the battery;
the safety protection module is used for protecting the power battery system, measures for limiting the working mode of the battery are adopted in a grading manner, and the maximum working efficiency of the power battery system is kept on the premise of safety;
the charging management module linearly looks up a table of charging power MAP of the battery system based on the current cell temperature and SOC of the power battery system, so as to determine the current maximum allowable charging current of the system;
the discharging management module carries out linear table look-up on 10s/30s peak discharging power MAP and continuous discharging power MAP of the power battery system based on the temperature collected in real time and the estimated SOC to obtain the current 10s/30s peak discharging power value and continuous discharging power value of the battery system, and reports the peak discharging power value and the continuous discharging power value to a vehicle MCU (microprogrammed control Unit) to realize charging management;
wherein the SOC in the discharged state is calculated as:
the SOC at state of charge is calculated as:
in the formula: lSOCThe state of health of the battery of the power battery system is shown; alpha is alpha1The rated capacity of the power battery system under the corresponding current is obtained; i istThe current is the current at any time in the discharging process of the power battery system.
2. The lithium battery BMS distributed data analysis management system of claim 1, wherein: the collection of data acquisition module includes voltage, temperature, electric current, insulation resistance, voltage acquisition is the voltage of every cluster of electric core in the power battery system, the inside total voltage Vbat of battery system and the outside total voltage Vlink of battery system, temperature acquisition is the temperature of electric core surface and utmost point ear, the temperature of liquid cooling inlet outlet, fill stake interface temperature and BMS system work internal temperature soon, current acquisition is the current value of battery system major loop part, insulation resistance acquisition is for gathering the total positive and the box between insulation resistance of battery system, and the total burden of battery system and the box between insulation resistance.
3. A lithium battery BMS distributed data analysis management method is characterized by comprising the following steps:
the method comprises the following steps that firstly, a data acquisition module acquires voltage, temperature, current and insulation resistance data, and a BMS calculates and acquires an SOC value and an SOC value of a power battery system;
step two, the BMS reports voltage, temperature, current, SOC and SOH data of the power battery system to a vehicle MCU through a CAN communication bus, the vehicle MCU processes the data, when the power battery system has an abnormal fault, the BMS needs to timely protect the battery system, and power limiting and immediate power-off protection measures are taken in a grading manner according to the severity of the fault, so that the battery system is ensured to utilize the stored energy to the maximum extent under the safety premise;
step three, in the charging and discharging process of the power battery system, the BMS system reports the temperature of the surface and the lug of the battery cell in the power battery system and the temperature of the liquid cooling inlet and outlet interface to the vehicle MCU, the vehicle MCU analyzes the temperature data reported by the BMS system, and the liquid cooling system is started to heat or radiate the power battery system, so that the battery system is charged and discharged at a proper environment temperature;
and step four, the BMS linearly looks up the charging power MAP of the battery system according to the current core temperature and SOC of the battery system so as to determine the current maximum allowable charging current of the system, and estimates the charging remaining time according to the maximum output capacity of the charger and the charging state of the battery system.
4. The lithium battery BMS distributed data analysis and management method according to claim 3, wherein: the BMS system can also store historical information, and reduces the operation load of the main system through the comparison and analysis of the historical information.
5. The lithium battery BMS distributed data analysis and management method according to claim 3, wherein: the BMS system formulates a fault pre-judgment table according to the change trend of historical data acquired by the data acquisition module and the change curve of the SOC and SOH values, wherein the fault pre-judgment table comprises fault names, fault threshold values, fault return differences, fault detection time and response time, and corresponding fault grade data are generated.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113954682A (en) * | 2021-11-25 | 2022-01-21 | 中国汽车工程研究院股份有限公司 | Electric vehicle charging detection system and method |
| CN114084045A (en) * | 2021-11-10 | 2022-02-25 | 轻橙时代(深圳)科技有限责任公司 | Power battery life cycle management method |
| CN114114017A (en) * | 2021-12-24 | 2022-03-01 | 广州巨湾技研有限公司 | Method, device and system for testing power-down logic of battery management system |
| CN115347652A (en) * | 2022-10-18 | 2022-11-15 | 江西江铃集团新能源汽车有限公司 | Low-temperature charging optimization method and system for lithium battery and storage medium |
| CN115626062A (en) * | 2022-12-21 | 2023-01-20 | 中汽研汽车检验中心（天津）有限公司 | Battery pack temperature early warning method and system based on battery pack thermal management system modeling |
| CN117169733A (en) * | 2023-11-01 | 2023-12-05 | 车城智能装备(武汉)有限公司 | Power battery monitoring method, system, equipment and storage medium |
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- 2021-06-02 CN CN202110616428.9A patent/CN113391210A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114084045A (en) * | 2021-11-10 | 2022-02-25 | 轻橙时代(深圳)科技有限责任公司 | Power battery life cycle management method |
| CN114084045B (en) * | 2021-11-10 | 2023-11-03 | 轻橙时代(深圳)科技有限责任公司 | Power battery life cycle management method |
| CN113954682A (en) * | 2021-11-25 | 2022-01-21 | 中国汽车工程研究院股份有限公司 | Electric vehicle charging detection system and method |
| CN114114017A (en) * | 2021-12-24 | 2022-03-01 | 广州巨湾技研有限公司 | Method, device and system for testing power-down logic of battery management system |
| CN114114017B (en) * | 2021-12-24 | 2024-04-02 | 广州巨湾技研有限公司 | Method, device and system for testing power-down logic of battery management system |
| CN115347652A (en) * | 2022-10-18 | 2022-11-15 | 江西江铃集团新能源汽车有限公司 | Low-temperature charging optimization method and system for lithium battery and storage medium |
| CN115347652B (en) * | 2022-10-18 | 2023-01-31 | 江西江铃集团新能源汽车有限公司 | Low-temperature charging optimization method and system for lithium battery and storage medium |
| CN115626062A (en) * | 2022-12-21 | 2023-01-20 | 中汽研汽车检验中心（天津）有限公司 | Battery pack temperature early warning method and system based on battery pack thermal management system modeling |
| CN115626062B (en) * | 2022-12-21 | 2023-08-04 | 中汽研汽车检验中心（天津）有限公司 | Battery pack temperature early warning method and system based on battery pack thermal management system modeling |
| CN117169733A (en) * | 2023-11-01 | 2023-12-05 | 车城智能装备(武汉)有限公司 | Power battery monitoring method, system, equipment and storage medium |
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