CN114966422A - Real-time monitoring and early warning system based on power battery parameters - Google Patents
Real-time monitoring and early warning system based on power battery parameters Download PDFInfo
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- CN114966422A CN114966422A CN202210522938.4A CN202210522938A CN114966422A CN 114966422 A CN114966422 A CN 114966422A CN 202210522938 A CN202210522938 A CN 202210522938A CN 114966422 A CN114966422 A CN 114966422A
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
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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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
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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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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Abstract
The invention discloses a real-time monitoring and early warning system based on power battery parameters, relates to the technical field of battery monitoring, and solves the technical problems that in the power battery monitoring process in the prior art, the health state of a power battery is determined according to a single battery parameter, accidental factors exist, the power battery monitoring is inaccurate, and false alarm is easily caused; according to the invention, the control acquisition module acquires and reports the charging data and the battery parameters of the power battery, the running state of the power battery is analyzed according to the battery parameters, the charging state of the power battery is analyzed according to the charging data, and the early warning signal can be accurately generated by combining the charging data and the charging state, so that the accuracy of monitoring the power battery can be improved; according to the invention, the capacity and the temperature among the single batteries are analyzed by a mathematical method to judge whether the capacity of the single batteries in the power battery is balanced and the temperature is uniform, so as to judge whether the running state of the power battery is normal, the data processing efficiency can be improved, and the accuracy of an analysis result can be ensured.
Description
Technical Field
The invention belongs to the field of battery monitoring, relates to a real-time monitoring technology based on power battery parameters, and particularly relates to a real-time monitoring and early warning system based on power battery parameters.
Background
The power battery is a power source of the electric vehicle, and the working performance of the power battery can have great influence on the vehicle operation, so that the real-time monitoring of the power battery is necessary.
The prior art (patent invention with publication number CN 113787914A) discloses a method, an apparatus, a server and a storage medium for monitoring a power battery, which are used for determining the working state of the power battery based on monitoring parameters such as temperature rise rate and the like, so as to monitor the power battery. In the prior art, in the process of monitoring a power battery, the health state of the power battery is determined according to a single battery parameter, and accidental factors exist, so that the monitoring of the power battery is inaccurate, and false alarm is easily caused; therefore, a real-time monitoring and early warning system based on power battery parameters is needed.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art; therefore, the invention provides a real-time monitoring and early warning system based on power battery parameters, which is used for solving the technical problems that the power battery monitoring is inaccurate and false alarm is easily caused due to accidental factors caused by the fact that the health state of the power battery is determined according to a single battery parameter in the power battery monitoring process in the prior art.
According to the invention, the control acquisition module acquires and reports the charging data and the battery parameters of the power battery, the running state of the power battery is analyzed according to the battery parameters, the charging state of the power battery is analyzed according to the charging data, and the early warning signal can be accurately generated by combining the charging data and the battery parameters, so that the accuracy of monitoring the power battery can be improved.
In order to achieve the above object, a first aspect of the present invention provides a real-time monitoring and early warning system based on power battery parameters, which includes an analysis and early warning module and a control and acquisition module connected to the analysis and early warning module, wherein the control and acquisition module is connected to a power battery;
the control acquisition module: monitoring the charging process of the power battery, and collecting and reporting charging data; wherein the charging data comprises a charging interval and a corresponding mileage consumed; and
collecting and reporting battery parameters of the power battery in real time; wherein the battery parameters include battery capacity and battery temperature;
an analysis early warning module: acquiring environmental data through an on-board sensor, wherein the environmental data is associated with the charging data; and
performing combined analysis on the battery parameters and the charging data, and generating an early warning signal according to an analysis result; wherein the charging data is analyzed by an intelligent evaluation model.
Preferably, the analysis early warning module is respectively in communication and/or electrical connection with the control acquisition module and the vehicle-mounted sensor; wherein the on-board sensors include a temperature sensor and a humidity sensor;
the control acquisition module is used for acquiring and reporting charging data and battery parameters of the power battery, and is connected with a plurality of equalization units, and the equalization units are used for adjusting the capacity of each single battery in the power battery.
Preferably, the analysis early warning module collects environmental data in real time through the vehicle-mounted sensor connected with the analysis early warning module; wherein the environmental data includes temperature, humidity, and air pressure;
associating the environmental data with the corresponding charging data.
Preferably, the analysis and early warning module performs joint analysis on the battery parameters and the charging data, and generates an early warning signal according to an analysis result, including:
acquiring a battery state label and a battery charging label;
identifying the battery state label to judge the running state of the power battery, and identifying the battery charging label to judge the charging state of the power battery;
generating a battery abnormal signal only when the operation state is abnormal;
and when the running state is normal and the charging state is abnormal, generating an environment abnormal signal.
Preferably, the analysis early warning module analyzes the battery parameters to obtain a battery state label corresponding to the power battery, and the analysis early warning module includes:
acquiring the battery capacity and the battery temperature of each single battery in the power battery;
analyzing the battery capacity to obtain a capacity state, and analyzing the battery temperature to obtain a temperature state; wherein, the analysis and acquisition modes of the capacity state and the temperature state are consistent;
when the capacity state and the temperature state corresponding to the power battery are both normal, setting the battery state label to be 0; otherwise, the battery status flag is set to 1.
Preferably, the analysis and early warning module analyzes the battery capacity to obtain the corresponding capacity state, and the analysis and early warning module comprises:
acquiring the absolute value of the difference value of the battery capacity between the single batteries and the mean square error;
comparing the absolute value and the mean square error of the difference with corresponding set thresholds respectively; the set threshold is set according to empirical data and comprises a difference threshold and a mean square error threshold;
when the absolute value of the difference and the mean square error are both smaller than or equal to the corresponding set threshold, judging that the capacity state of the corresponding power battery is normal; otherwise, judging that the corresponding capacity state of the power battery is abnormal.
Preferably, the analysis and early warning module analyzes the charging data through the intelligent evaluation model to obtain a battery charging tag corresponding to the power battery, and the analysis and early warning module includes:
performing data preprocessing on the charging data to obtain a standard charging sequence; the data preprocessing refers to screening and sorting the charging data;
inputting the standard charging sequence into the intelligent evaluation model to obtain the output battery charging label; wherein the intelligent evaluation model is established based on an artificial intelligence model.
Preferably, the analysis early warning module performs data preprocessing on the charging data, including:
screening and acquiring a plurality of charging data corresponding to the power battery according to charging time;
sorting and splicing the corresponding charging interval, the corresponding mileage and the corresponding environmental data to generate a standard sequence;
and integrating the plurality of standard sequences according to the charging time corresponding to the charging data to generate the standard charging sequence.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the control acquisition module acquires and reports the charging data and the battery parameters of the power battery, the running state of the power battery is analyzed according to the battery parameters, the charging state of the power battery is analyzed according to the charging data, and the early warning signal can be accurately generated by combining the charging data and the battery parameters, so that the accuracy of monitoring the power battery can be improved.
2. According to the invention, the capacity and the temperature among the single batteries are analyzed by a mathematical method to judge whether the capacity of the single batteries in the power battery is balanced and the temperature is uniform, so as to judge whether the running state of the power battery is normal, the data processing efficiency can be improved, and the accuracy of an analysis result can be ensured.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the working steps of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The prior art (patent of invention with publication number CN 113787914A) discloses a method, an apparatus, a server and a storage medium for monitoring a power battery, which determine the working state of the power battery based on monitoring parameters such as temperature rise rate, and implement monitoring of the power battery. In the prior art, in the process of monitoring the power battery, the health state of the power battery is determined according to a single battery parameter, and accidental factors exist, so that the monitoring of the power battery is inaccurate, and false alarm is easily caused.
According to the invention, the control acquisition module acquires and reports the charging data and the battery parameters of the power battery, the running state of the power battery is analyzed according to the battery parameters, the charging state of the power battery is analyzed according to the charging data, and the early warning signal can be accurately generated by combining the charging data and the battery parameters, so that the accuracy of monitoring the power battery can be improved.
Referring to fig. 1, a first embodiment of the present application provides a real-time monitoring and early warning system based on power battery parameters, which includes an analysis and early warning module and a control and acquisition module connected to the analysis and early warning module, where the control and acquisition module is connected to a power battery;
the control acquisition module: monitoring the charging process of the power battery, and collecting and reporting charging data; collecting and reporting battery parameters of the power battery in real time;
an analysis early warning module: acquiring environmental data through a vehicle-mounted sensor, wherein the environmental data is associated with charging data; and performing joint analysis on the battery parameters and the charging data, and generating an early warning signal according to an analysis result.
The analysis early warning module is equivalent to a data server and is mainly used for data processing; the control acquisition module is equivalent to a data transfer station with data processing capacity. The analysis early warning module and the control acquisition module are both arranged in a service main body of the power battery, such as a new energy automobile.
The charging data comprises a charging interval and a corresponding consumption mileage, and can be used for evaluating the running environment of the power battery; the charging interval refers to the time difference between two times of charging, and the consumed mileage is the mileage of the power battery correspondingly consumed by the time difference. The battery parameters comprise battery capacity and battery temperature, and the running state of the power battery body can be evaluated. It will be appreciated that in other preferred embodiments, the charging data and battery parameters also include other data having the same attributes.
The charging data in the application are analyzed through an intelligent evaluation model, the intelligent evaluation model is obtained through training an artificial intelligent model, and the artificial intelligent model comprises a deep convolution neural network model, a RBF neural network model and other models with strong nonlinear capacity.
The analysis early warning module is respectively in communication and/or electrical connection with the control acquisition module and the vehicle-mounted sensor;
the control acquisition module is used for acquiring and reporting charging data and battery parameters of the power battery, and is connected with the plurality of equalization units, and the equalization units are used for adjusting the capacity of each single battery in the power battery.
The vehicle-mounted sensors comprise a temperature sensor, a humidity sensor, an air pressure sensor and the like and are used for collecting data which can affect the charging data of the power battery. The control acquisition module can also be connected with a central control of the power battery service main body to read the environmental data.
The control acquisition module is also connected with a plurality of equalizing units, and each equalizing unit corresponds to a single battery, namely the power battery corresponds to a plurality of equalizing units. And the balancing unit balances the capacities of the plurality of single batteries in the working process of the power battery.
The analysis early warning module in the application acquires environmental data in real time through a vehicle-mounted sensor connected with the analysis early warning module; environmental data includes temperature, humidity, and air pressure; the environmental data is associated with corresponding charging data.
The environmental data and the charging data are combined to realize the charging state analysis of the power battery, so that the time between the environmental data and the charging data is matched.
The analysis early warning module in this application carries out joint analysis to battery parameter and charging data, generates early warning signal according to the analysis result, includes:
acquiring a battery state label and a battery charging label;
identifying a battery state label to judge the running state of the power battery, and identifying a battery charging label to judge the charging state of the power battery;
generating a battery abnormal signal only when the running state is abnormal;
and when the running state is normal and the charging state is abnormal, generating an environment abnormal signal.
Analyzing the power battery body, identifying and acquiring a corresponding running state, and if the running state is abnormal, generating a battery abnormal signal if the power battery breaks down; when the power battery is normal, identifying and acquiring the charging state of the power battery, and if the charging state is abnormal, generating an environment abnormal signal if the environment where the power battery is located is abnormal. And otherwise, judging that the power battery is not abnormal.
In a preferred embodiment, the analyzing and warning module analyzes the battery parameters to obtain the battery status label corresponding to the power battery, and includes:
acquiring the battery capacity and the battery temperature of each single battery in the power battery;
analyzing the battery capacity to obtain a capacity state, and analyzing the battery temperature to obtain a temperature state;
when the capacity state and the temperature state corresponding to the power battery are both normal, setting the battery state label to be 0; otherwise, the battery status flag is set to 1.
Evaluating the running state of the power battery, and judging whether the capacities of the single batteries are balanced or not and whether the temperatures of the single batteries are uniform or not, wherein the two data are external expressions of the running state of the power battery. When the capacities among the single batteries are balanced and the temperatures are uniform, the power battery is judged to be wholly normal, namely the battery label is set to be 0.
In an optional embodiment, the analyzing and warning module analyzes the battery capacity to obtain a corresponding capacity state, including:
acquiring absolute values of differences of battery capacities among the single batteries and mean square deviations;
comparing the absolute value and the mean square error of the difference with corresponding set thresholds respectively;
when both the absolute value of the difference and the mean square error are less than or equal to the corresponding set threshold, judging that the capacity state of the corresponding power battery is normal; otherwise, judging that the capacity state of the corresponding power battery is abnormal.
The set threshold is set according to empirical data, and includes a difference threshold and a mean square error threshold, i.e., the absolute value of the difference is compared with the difference threshold, and the mean square error is compared with the mean square error threshold. The capacity difference between the single batteries is used for evaluating whether the capacities are balanced or not, the mean square error is used for evaluating whether the capacities of all the single batteries are concentrated or not, and the two data are combined to judge whether the capacity state of the power battery is normal or not.
The temperature state is obtained in a manner consistent with the capacity state, namely whether the temperature state of the power battery is normal or not is judged according to the temperature difference and the temperature mean square error. The capacity imbalance and the temperature imbalance have influences on the health of the power battery.
The analysis early warning module in this application carries out the analysis to charging data through intelligent evaluation model, acquires the battery charging label that corresponds power battery, includes:
performing data preprocessing on the charging data to obtain a standard charging sequence;
and inputting the standard charging sequence into the intelligent evaluation model to obtain the output battery charging label.
Both the environmental data and the charging data are included in the standard charging sequence, so the standard charging sequence is analyzed by a non-linear model. Establishing an intelligent evaluation model based on an artificial intelligence model, comprising:
acquiring standard training data; the standard training data comprises input data and corresponding output data, wherein the input data are acquired by a laboratory and are consistent with the content attribute of the standard charging sequence, and the output data are analyzed and set by a worker;
training the constructed artificial intelligence model through standard training data, marking the trained artificial intelligence model as an intelligent evaluation model, and regularly updating and storing the model in an analysis early warning module.
In a preferred embodiment, the analysis and early warning module performs data preprocessing on the charging data, including:
screening and acquiring a plurality of charging data corresponding to the power battery according to the charging time;
sorting and splicing the corresponding charging interval, the consumed mileage and the environment data to generate a standard sequence;
and integrating the plurality of standard sequences according to the charging time of the corresponding charging data to generate a standard charging sequence.
And integrating the corresponding charging interval, the consumption mileage and the environment data in the charging data to generate a standard sequence, and integrating the standard sequence in sequence to obtain the standard charging sequence.
The working principle of the invention is as follows:
controlling an acquisition module to monitor the charging process of the power battery and acquiring and reporting charging data; and collecting and reporting battery parameters of the power battery in real time.
The analysis early warning module performs combined analysis on the battery parameters and the charging data according to the environment data, and generates an early warning signal according to an analysis result.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (8)
1. Real-time supervision early warning system based on power battery parameter, including analysis early warning module to and the control acquisition module who is connected with it, just control acquisition module is connected with power battery, its characterized in that:
the control acquisition module: monitoring the charging process of the power battery, and collecting and reporting charging data; the charging data comprises charging intervals and corresponding consumed mileage; and
collecting and reporting battery parameters of the power battery in real time; wherein the battery parameters include battery capacity and battery temperature;
an analysis early warning module: acquiring environmental data through an on-board sensor, wherein the environmental data is associated with the charging data; and
performing combined analysis on the battery parameters and the charging data, and generating an early warning signal according to an analysis result; wherein the charging data is analyzed by an intelligent evaluation model.
2. The real-time monitoring and early warning system based on the power battery parameters as claimed in claim 1, wherein the analysis and early warning module is respectively in communication and/or electrical connection with the control acquisition module and the vehicle-mounted sensor; wherein the on-board sensors include a temperature sensor and a humidity sensor;
the control acquisition module is used for acquiring and reporting the charging data and the battery parameters of the power battery, and is connected with a plurality of equalization units, and the equalization units are used for adjusting the capacity of each single battery in the power battery.
3. The real-time monitoring and early warning system based on the power battery parameters as claimed in claim 2, wherein the analysis and early warning module collects environmental data in real time through the vehicle-mounted sensor connected with the analysis and early warning module; wherein the environmental data includes temperature, humidity, and air pressure;
associating the environmental data with the corresponding charging data.
4. The real-time monitoring and early warning system based on power battery parameters as claimed in claim 1, wherein the analysis and early warning module performs joint analysis on the battery parameters and the charging data, and generates an early warning signal according to the analysis result, including:
acquiring a battery state label and a battery charging label;
identifying the battery state label to judge the running state of the power battery, and identifying the battery charging label to judge the charging state of the power battery;
generating a battery abnormal signal only when the operation state is abnormal;
and when the running state is normal and the charging state is abnormal, generating an environment abnormal signal.
5. The real-time monitoring and early warning system based on power battery parameters as claimed in claim 1 or 4, wherein the analysis and early warning module analyzes the battery parameters to obtain a battery status label corresponding to the power battery, and comprises:
acquiring the battery capacity and the battery temperature of each single battery in the power battery;
analyzing the battery capacity to obtain a capacity state, and analyzing the battery temperature to obtain a temperature state; wherein, the analysis and acquisition modes of the capacity state and the temperature state are consistent;
when the capacity state and the temperature state corresponding to the power battery are both normal, setting the battery state label to be 0; otherwise, the battery status flag is set to 1.
6. The real-time monitoring and early warning system based on power battery parameters of claim 5, wherein the analysis and early warning module analyzes the battery capacity to obtain the corresponding capacity state, and comprises:
acquiring the absolute value of the difference value of the battery capacity between the single batteries and the mean square error;
comparing the absolute value and the mean square error of the difference with corresponding set thresholds respectively; the set threshold is set according to empirical data and comprises a difference threshold and a mean square error threshold;
when the absolute value of the difference and the mean square error are both smaller than or equal to the corresponding set threshold, judging that the capacity state of the corresponding power battery is normal; otherwise, judging that the corresponding capacity state of the power battery is abnormal.
7. The real-time monitoring and early warning system based on power battery parameters as claimed in claim 1 or 4, wherein the analysis and early warning module analyzes the charging data through the intelligent evaluation model to obtain the battery charging label corresponding to the power battery, and the system comprises:
performing data preprocessing on the charging data to obtain a standard charging sequence; the data preprocessing refers to screening and sorting the charging data;
inputting the standard charging sequence into the intelligent evaluation model to obtain the output battery charging label; wherein the intelligent evaluation model is established based on an artificial intelligence model.
8. The real-time monitoring and early warning system based on power battery parameters as claimed in claim 7, wherein the analysis and early warning module performs data preprocessing on the charging data, and comprises:
screening and acquiring a plurality of charging data corresponding to the power battery according to charging time;
sorting and splicing the corresponding charging interval, the consumed mileage and the environment data to generate a standard sequence;
and integrating a plurality of standard sequences according to the charging time corresponding to the charging data to generate the standard charging sequence.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115792629A (en) * | 2022-11-21 | 2023-03-14 | 惠州恒立能源科技有限公司 | Alarm monitoring system and method for lithium battery energy storage |
| CN115963423A (en) * | 2022-12-21 | 2023-04-14 | 广州辰创科技发展有限公司 | Power health state monitoring system |
| CN117289147A (en) * | 2023-11-24 | 2023-12-26 | 珠海科创储能科技有限公司 | Battery monitoring method and device, storage medium and electronic equipment |
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2022
- 2022-05-13 CN CN202210522938.4A patent/CN114966422A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115792629A (en) * | 2022-11-21 | 2023-03-14 | 惠州恒立能源科技有限公司 | Alarm monitoring system and method for lithium battery energy storage |
| CN115792629B (en) * | 2022-11-21 | 2024-04-02 | 惠州因博利电子科技有限公司 | Alarm monitoring system and method for lithium battery energy storage |
| CN115963423A (en) * | 2022-12-21 | 2023-04-14 | 广州辰创科技发展有限公司 | Power health state monitoring system |
| CN115963423B (en) * | 2022-12-21 | 2023-11-14 | 广州辰创科技发展有限公司 | Power supply health state monitoring system |
| CN117289147A (en) * | 2023-11-24 | 2023-12-26 | 珠海科创储能科技有限公司 | Battery monitoring method and device, storage medium and electronic equipment |
| CN117289147B (en) * | 2023-11-24 | 2024-04-02 | 珠海科创储能科技有限公司 | Battery monitoring method and device, storage medium and electronic equipment |
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