CN111983494B - Method and system for prolonging service life of battery system - Google Patents
Method and system for prolonging service life of battery system Download PDFInfo
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- CN111983494B CN111983494B CN202010836529.2A CN202010836529A CN111983494B CN 111983494 B CN111983494 B CN 111983494B CN 202010836529 A CN202010836529 A CN 202010836529A CN 111983494 B CN111983494 B CN 111983494B
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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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- 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]
- G01R31/385—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]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
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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
Abstract
The invention discloses a method and a system for improving the service life of a battery system, wherein a BMS (battery management system) carries an influence factor of a service temperature, a service discharge rate and a service charge time to service life into a residual service life estimation by analyzing the temperature, the service discharge rate and the service charge time in the historical service process of the battery system, and predicts the residual service life of the battery system in real time, if the predicted residual service life of the battery system does not meet the design service life, a service life curve corresponding to different upper limit voltages obtained by a previous test is checked, so that the reasonable adjustment of the upper limit voltage of the battery is completed, and the service life of the battery system reaches the design requirement.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a method and a system for prolonging the service life of a battery system.
Background
With the development of electric automobiles and energy storage industries, the service life of battery systems is required to be higher and higher. The longer the service life of the battery system is, the better the service life of the battery system is, but in a complex use environment of the terminal, the service life of the battery system can reach the design service life as a risk item, and the situation of too fast attenuation may occur, so that the user experience is affected.
The existing battery system life prediction method only considers temperature factors, does not consider two factors of discharge multiplying power and charging times, only predicts the life, and does not provide a certain strategy after life prediction to prolong the service life of the battery, so that the life of the battery system reaches the design life;
disclosure of Invention
Aiming at the problem that the service life of a battery system possibly cannot reach the design service life in the prior art, the invention provides a method and a system for improving the service life of the battery system, wherein the historical service temperature, the discharge multiplying power and the charging times of the battery system are used for predicting the residual service life of the battery system, and the BMS is used for intelligently adjusting the upper limit voltage of the battery system to improve the service life of the battery system, so that the service life of the battery system is ensured to reach the design value.
In order to achieve the above object, the present invention provides the following technical solutions:
a method for prolonging service life of a battery system specifically comprises the following steps:
s1: establishing a residual life prediction algorithm model of the battery system, and carrying out real-time statistical analysis on performance parameters of the battery system in the use process;
s2: obtaining a life influence factor of the performance parameter on the battery system through table lookup;
s3: inputting a life influence factor of the battery system into a residual life prediction model of the battery system to obtain a real-time residual life L_domain of the battery system;
s4: if L_domain is less than L_design-L_used, reducing the upper limit voltage of the single body of the battery system; l_design represents the design lifetime and l_used represents the lifetime.
Preferably, in the step S1, the remaining life prediction algorithm model of the battery system is:
L_remain＝L-L_used (1)
in the formula (1), l_domain represents the remaining life of the battery system, L represents the usable life of the battery system, and l_used represents the usable life of the battery system.
Preferably, in S1, the performance parameters include temperature, discharge rate, and number of times of charging.
Preferably, in the step S3, the remaining life calculation formula of the battery system is:
L_remain＝r1*r2*r3*L_initial-L_used (2)
in the formula (2), l_domain represents the remaining life of the battery system, l_used represents the service life of the battery system, r1 represents the life influence factor of the temperature interval determined by table lookup on the battery system, r2 represents the life influence factor of the discharge rate determined by table lookup on the battery system, r3 represents the life influence factor of the charge number determined by table lookup on the battery system, and l_initial represents the specific temperature of the battery system, the discharge rate, and the service life of the battery system at the upper limit of use.
Preferably, in S3, the upper limit voltage of the monomer corresponds to the service life of the battery system one by one.
The invention also provides a system for improving the service life of the battery system, which comprises a model building unit, a service life analysis unit, a BMS control module, a comparison unit and an upper limit voltage regulation prediction unit;
the model building unit, the life analyzing unit, the comparing unit and the upper limit voltage regulation predicting unit are respectively connected with the BMS control module in a bidirectional manner; wherein, the liquid crystal display device comprises a liquid crystal display device,
the model building unit is used for building a battery system residual life prediction algorithm model;
the service life analysis unit is used for calculating the real-time residual service life of the battery system;
the comparison unit is used for comparing the real-time residual life of the battery system with the designed residual life and transmitting the result to the BMS control module;
an upper limit voltage adjustment prediction unit for predicting an upper limit voltage that satisfies a design life of the battery system;
and the BMS control module is used for realizing information interaction among the units and adjusting the upper limit voltage.
In summary, due to the adoption of the technical scheme, compared with the prior art, the invention has at least the following beneficial effects:
the invention predicts the residual life of the battery by collecting the historical use temperature, the discharge multiplying power and the charging times of the battery system, thereby improving the prediction precision; meanwhile, when the predicted service life of the battery system cannot reach the design service life, the service life of the battery system is prolonged by intelligently adjusting the upper limit voltage of the battery through the BMS, the service life of the battery system is ensured to reach the design value, the use experience of a user is improved, and the battery system has a large market application prospect.
Description of the drawings:
fig. 1 is a flowchart illustrating a method for improving the service life of a battery system according to an exemplary embodiment of the present invention.
Fig. 2 is a schematic diagram of upper limit voltage adjustment of a battery system cell according to an exemplary embodiment of the present invention.
Fig. 3 is a schematic diagram of a system for improving the service life of a battery system according to an exemplary embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and embodiments. It should not be construed that the scope of the above subject matter of the present invention is limited to the following embodiments, and all techniques realized based on the present invention are within the scope of the present invention.
In the description of the present invention, it should be understood that the terms "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
As shown in fig. 1, the present invention provides a method for improving the service life of a battery system, which specifically includes the following steps:
s1: and establishing a residual life prediction algorithm model of the battery system.
L_remain＝L-L_used (1)
In the formula (1), l_domain represents the real-time remaining life of the battery system, L represents the design life of the battery system, and l_used represents the service life of the battery system.
S2: and importing the influence factors of different temperature intervals, different discharge multiplying factors and different charging times, which are obtained through experiments in the development process of the battery system, on the residual life of the battery system into a residual life prediction algorithm model of the battery system.
In this embodiment, in the development work of the battery system, the staff may perform various experiments, such as the influence of temperature, discharge rate and charge times on the remaining life of the battery system, so that in order to improve the prediction accuracy, it is necessary to input experimental data into the remaining life prediction algorithm model of the battery system for correction.
And S3, counting the duty ratio of different temperature intervals, the duty ratio of different discharge multiplying factors and the number of times of charging in the using process of the battery, obtaining corresponding life influence factors by looking up a table (a life influence factor table of the discharge multiplying factors, different using temperatures and the number of times of charging on the battery system can be obtained through the step S2), and importing the life influence factors into a residual life prediction algorithm model to obtain the real-time residual life of the battery system.
L_remain＝r1*r2*r3*L_initial-L_used (2)
In the formula (2), l_domain represents the real-time remaining life of the battery system, l_used represents the service life of the battery system, r1 represents the life influence factor of the temperature interval determined by table lookup on the battery system, r2 represents the life influence factor of the discharge rate determined by table lookup on the battery system, r3 represents the life influence factor of the charge number determined by table lookup on the battery system, l_initial represents the service life of the battery system at a specific temperature, a specific discharge rate and a specific upper limit voltage (for example, 25 ℃ and 1C charge/discharge) of the battery system, and the service life can be obtained through experiments.
And S4, comparing the predicted real-time residual life with the designed residual life, and if the real-time residual life is smaller than the designed residual life, the BMS intelligently adjusts the upper limit voltage of the battery system, prolongs the residual life of the battery system and improves the service life of the battery system.
In this embodiment, under the same test condition, the upper limit voltage of one battery system has a corresponding service life, i.e. the service lives of the battery systems are different under different upper limit voltages. In this embodiment, when L_remain < L_design-L_used, L_design represents design lifetime. And searching a cycle life curve corresponding to different upper limit voltages of the leading-in software in the early stage according to the difference value between the residual life and the residual life to be met, and determining the adjusted upper limit value of the voltage.
As shown in fig. 2, when the upper limit voltage of the cell of the battery system is V 2 When the cycle use frequency of the battery system is Cls 2; when the upper limit voltage of the single cell of the battery system is V 1 When the cycle use frequency of the battery system is Cls 1; v (V) 2 ＜V 1 While Cls 2 > Cls 1. V2 is a value intelligently determined by the BMS according to battery life corresponding to different upper use limit voltages of the pre-written software and based on historical use data.
In this embodiment, the prediction of the remaining life and the intelligent regulation of the battery system use upper limit voltage are continuously performed, and the life prediction model and the intelligent regulation of the battery system use upper limit voltage model are continuously trained and optimized.
Based on the method, as shown in fig. 3, the invention also provides a system for improving the service life of the battery system, which comprises a model building unit, a life analysis unit, a BMS control module, a comparison unit and an upper limit voltage adjustment prediction unit; the model building unit, the life analyzing unit, the comparing unit and the upper limit voltage adjusting and predicting unit are respectively connected with the BMS control module in a bidirectional manner; wherein, the liquid crystal display device comprises a liquid crystal display device,
and the model construction unit is used for constructing a battery system residual life prediction algorithm model.
And the service life analysis unit is used for calculating the residual service life of the battery system.
And the comparison unit is used for comparing the residual life and the design life of the battery system and transmitting the result to the BMS control module.
An upper limit voltage adjustment prediction unit for predicting an upper limit voltage that satisfies a design life of the battery system;
and the BMS control module is used for realizing information interaction among the units and adjusting the upper limit voltage.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples of carrying out the invention and that various changes in form and details may be made therein without departing from the spirit and scope of the invention.
Claims (5)
1. A method for improving the service life of a battery system, comprising the steps of:
s1: establishing a residual life prediction algorithm model of the battery system, and carrying out real-time statistical analysis on performance parameters in the use process of the battery system, wherein the performance parameters comprise temperature, discharge multiplying power and charging times;
s2: obtaining a life influence factor of the performance parameter on the battery system through table lookup;
s3: inputting a life influence factor of the battery system into a residual life prediction algorithm model of the battery system to obtain a real-time residual life L_domain of the battery system;
s4: if L_domain is less than L_design-L_used, reducing the upper limit voltage of the single body of the battery system; l_design represents the design lifetime and l_used represents the lifetime.
2. The method for improving the service life of a battery system according to claim 1, wherein in S1, a remaining life prediction algorithm model of the battery system is:
L_remain＝L-L_used (1)
in the formula (1), l_domain represents the real-time remaining life of the battery system, L represents the usable life of the battery system, and l_used represents the usable life of the battery system.
3. The method for improving the service life of a battery system according to claim 2, wherein the calculation formula of the residual life prediction algorithm model of the battery system is as follows:
L_remain＝r1*r2*r3*L_initial-L_used (2)
in the formula (2), l_domain represents the real-time remaining life of the battery system, l_used represents the service life of the battery system, r1 represents the life influence factor of the temperature interval determined by table lookup on the battery system, r2 represents the life influence factor of the discharge rate determined by table lookup on the battery system, r3 represents the life influence factor of the charge number determined by table lookup on the battery system, and l_initial represents the service life of the battery system at a specific temperature, discharge rate and upper limit voltage of use.
4. The method of claim 1, wherein in S4, the upper limit voltage of the cell corresponds to the service life of the battery system.
5. A system for improving the service life of a battery system based on the method of any one of claims 1 to 4, comprising a model construction unit, a life analysis unit, a BMS control module, an alignment unit and an upper limit voltage adjustment prediction unit;
the model building unit, the life analyzing unit, the comparing unit and the upper limit voltage regulation predicting unit are respectively connected with the BMS control module in a bidirectional manner; wherein, the liquid crystal display device comprises a liquid crystal display device,
the model building unit is used for building a battery system residual life prediction algorithm model;
the service life analysis unit is used for calculating the real-time residual service life of the battery system;
the comparison unit is used for comparing the real-time residual life of the battery system with the designed residual life and transmitting the result to the BMS control module;
an upper limit voltage adjustment prediction unit for predicting an upper limit voltage that satisfies a design life of the battery system;
and the BMS control module is used for realizing information interaction among the units and adjusting the upper limit voltage.
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