CN103760494B - Method and system for estimating battery capacity online - Google Patents
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 abstract description 3
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 2
- 238000010277 constant-current charging Methods 0.000 description 2
- 229910001416 lithium ion Inorganic materials 0.000 description 2
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
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- 239000010439 graphite Substances 0.000 description 1
- 229910002804 graphite Inorganic materials 0.000 description 1
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 description 1
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Abstract
The invention belongs to the technical field of lithium batteries, and discloses a method for estimating a battery capacity online. The method comprises the steps that S1, a capacity attenuation model is provided, and capacity attenuation model parameters are initialized; S2, a battery to be measured is charged and discharged repeatedly delta n times; S3, the estimated relative capacity attenuation of the current battery to be measured is obtained through calculation; S4, the real relative capacity attenuation of the battery to be measured is obtained in a testing mode; S5, an estimation error is calculated; S6, if the estimation error is larger than a preset permissible error, the capacity attenuation model parameters are corrected and updated through the estimation error, and then the step S2 is carried out; S7, if the estimation error is smaller than or equal to the preset permissible error, the capacity attenuation model parameters corrected the last time are determined to be the final capacity attenuation model parameters, the accurate capacity attenuation model corresponding to the battery to be measured is obtained, and then the relative capacity attenuation and the battery capacity of the battery to be measured are estimated in the future. The invention further discloses a system for estimating the battery capacity online. The method and system are convenient and easy to operate and high in accuracy.
Description
Technical Field
The invention relates to the technical field of lithium batteries, in particular to a method and a system for estimating battery capacity on line.
Background
Under the large background that the problems of environmental pollution, energy crisis, greenhouse effect and the like are becoming serious day by day, the development of a novel energy technology becomes important, and among them, a battery technology is increasingly receiving general attention as one of the novel energy technologies. Particularly, lithium ion power batteries are developed rapidly at present and widely applied to the fields of electric vehicles, energy storage stations and the like. However, as the battery is cyclically charged and discharged, the battery is gradually aged, and its performance is gradually degraded, particularly, its capacity is gradually decreased.
In practical situations, the capacity of the battery is reduced, which affects the amount of energy stored in the battery, such as in an electric vehicle, and directly affects the driving range of the electric vehicle. Without an accurate estimate of the degradation of battery capacity, accidents such as breakdown in the field may occur due to a false estimate of driving range. Moreover, if there is no reasonable knowledge of the capacity fade, it may lead to excessive use of the battery, which in turn leads to a dramatic decline in the life of the battery. Therefore, during actual battery usage, the corresponding battery management system should have a reasonable estimation algorithm for the battery capacity.
The most accurate estimation method for the battery capacity is to accurately measure the battery capacity through a battery capacity test in a laboratory, and the method is generally a small-rate constant-current charge and discharge test. However, for a battery on an actual vehicle, charging may be performed on a charging pile, so the charging condition may be standard constant current charging or constant current and constant voltage charging, but discharging is usually determined by actual road conditions, habits of a driver, and the like, and it is certainly impossible to be the standard constant current discharging condition, and the battery cannot be discharged to be empty every time, so the electric quantity discharged by the battery every time is often not equal to the capacity of the battery, and estimation of the capacity of the battery under a dynamic condition is very difficult. If the correction is made regularly, an accurate value can be obtained, but if the correction is too frequent, the user experience is poor, while the correction frequency is too low, and the effect is poor at other times than a period of time immediately after the correction.
The invention aims to provide a battery capacity estimation method based on model capacity open-loop estimation and periodic calibration correction, so that the battery capacity can be reasonably estimated in an actual battery management system.
Disclosure of Invention
The invention aims to at least solve the problems of complex operation and low accuracy in the prior art.
Therefore, the invention aims to provide an online estimation method for battery capacity, which is simple and convenient to operate and high in accuracy.
Another objective of the present invention is to provide an online estimation system for battery capacity, which is simple and convenient to operate and has high accuracy.
In order to achieve the above object, an embodiment of the battery capacity online estimation method according to an aspect of the present invention includes s1, providing a capacity fading model and initializing capacity fading model parameters; s2, circulating charge and discharge of the battery to be tested for delta n times, wherein delta n is a preset positive integer; s3, obtaining the estimated relative capacity attenuation of the current battery to be tested according to the capacity attenuation model and the capacity attenuation model parameters; s4, testing the real capacity of the current battery to be tested to obtain the real relative capacity attenuation of the battery to be tested; s5, subtracting the real relative capacity attenuation amount from the estimated relative capacity attenuation amount to obtain an estimation error; s6, if the estimation error is larger than a preset allowable error, correcting and updating the capacity attenuation model parameters by using the estimation error, and then jumping to the step S2; and S7, if the estimation error is less than or equal to the preset allowable error, determining the capacity attenuation model parameter after the last correction as a final capacity attenuation model parameter to obtain an accurate capacity attenuation model corresponding to the battery to be measured, wherein the accurate capacity attenuation model is used for estimating the relative capacity attenuation and the battery capacity of the battery to be measured in the future.
The online estimation method for the battery capacity has the advantages of simplicity and convenience in operation and high accuracy.
In addition, the online estimation method for the battery capacity according to the embodiment of the invention also has the following additional technical characteristics:
in an example of the present invention, the capacity fading model of the battery under test is:wherein,the estimated relative capacity attenuation of the battery to be tested after the nth charge-discharge cycle,is the estimated relative capacity attenuation of the battery to be tested after the n-1 th charge-discharge cycle, T is the ambient temperature of the battery to be tested when the battery to be tested is subjected to the n-th charge-discharge cycle, A represents a first parameter,representing a second parameter and z representing a third parameter.
In one example of the present invention, the initializing capacity fade model parameters includes: selecting the reference battery with the same type as the battery to be tested and known final capacity attenuation model parameters, initializing the A as a first parameter in a capacity attenuation model corresponding to the reference battery, and initializing the AInitializing z as the capacity attenuation corresponding to the reference battery for a second parameter in the capacity attenuation model corresponding to the reference batterySubtracting the third parameter in the model.
In one example of the invention, the calculation formula of the real relative capacity attenuation amount of the battery to be tested isWherein C is the detected real capacity of the current battery to be detected, C0And the initial capacity of the battery to be tested.
In an example of the present invention, the updating the capacity fade model parameters by using the estimation error specifically includes: updating the first parameter, wherein a first parameter correction formula is as follows: a. thek＝Ak-1+k1× delta ξ, and updating the second parameter, wherein the second parameter correction formula is as follows:updating the third parameter, wherein a third parameter correction formula is as follows: z is a radical ofk＝zk-1+k3× Δ ξ, where k in the subscript denotes the parameter after correction, k-1 in the subscript denotes the parameter before correction, k1Representing a preset first correction factor, k2Representing a preset second correction factor, k3Represents a preset third correction coefficient, and Δ ξ represents the estimation error.
The battery capacity online estimation system according to an embodiment of another aspect of the present invention includes: the charging and discharging cycle counting module is used for recording the charging and discharging cycle times of the battery to be tested, and counting from zero again when the charging and discharging cycle times reach delta n times; a capacity fading model parameter storage unit for storing capacity fading model parameters; the estimated relative capacity attenuation calculation module is respectively connected with the charge-discharge cycle counting module and the capacity attenuation model parameter storage unit and is used for substituting the capacity attenuation model parameters into a capacity attenuation model to obtain the estimated relative capacity attenuation of the battery to be measured every time 1 charge-discharge cycle is completed; the real relative capacity attenuation quantity testing module is connected with the charging and discharging cycle counting module and used for testing the real capacity of the battery to be tested and calculating the real relative capacity attenuation quantity of the battery to be tested when the charging and discharging cycle times are delta n times; the comparison and judgment module is respectively connected with the estimation relative capacity attenuation calculation module and the real relative capacity attenuation test module, and is used for comparing the real relative capacity attenuation with the estimation relative capacity attenuation to obtain an estimation error and judging the size relationship between the estimation error and a preset allowable error; the capacity attenuation model parameter correction module is respectively connected with the comparison judgment module and the capacity attenuation model parameter storage unit, and when the judgment result of the comparison judgment module is that the estimation error is larger than a preset allowable error, the capacity attenuation model parameter correction module corrects and updates the capacity attenuation model parameter by using the estimation error and stores the updated capacity attenuation model parameter into the capacity attenuation model parameter storage unit; and the final capacity attenuation model output module is respectively connected with the comparison and judgment module and the capacity attenuation model parameter storage unit, and when the judgment result of the comparison and judgment module is that the estimation error is less than or equal to a preset allowable error, the final capacity attenuation model output module takes the capacity attenuation model parameters stored in the capacity attenuation model parameter storage unit as final capacity attenuation model parameters to obtain and output a final capacity attenuation model, wherein the final capacity attenuation model is used for estimating the relative capacity attenuation and the battery capacity of the battery to be detected in the future.
The battery capacity online estimation system provided by the embodiment of the invention has the advantages of simplicity and convenience in operation and high accuracy.
In addition, the online estimation system for the battery capacity according to the embodiment of the invention also has the following additional technical characteristics:
in an example of the present invention, the capacity fading model of the battery under test is:wherein,the estimated relative capacity attenuation of the battery to be tested after the nth charge-discharge cycle,is the estimated relative capacity attenuation of the battery to be tested after the n-1 th charge-discharge cycle, T is the ambient temperature of the battery to be tested when the battery to be tested is subjected to the n-th charge-discharge cycle, A represents a first parameter,representing a second parameter and z representing a third parameter.
In one example of the present invention, in the capacity fade model parameter storage unit, the initialized capacity fade model parameters include: selecting the reference battery with the same type as the battery to be tested and known final capacity attenuation model parameters, initializing the A as a first parameter in a capacity attenuation model corresponding to the reference battery, and initializing the AInitializing z as a third parameter in the capacity fading model corresponding to the reference battery for a second parameter in the capacity fading model corresponding to the reference battery.
In an example of the present invention, in the true relative capacity decrement test module, the calculation formula of the true relative capacity decrement of the battery to be tested is as followsWherein C is the detected real capacity of the current battery to be detected, C0Is that it isInitial capacity of the battery to be tested.
In an example of the present invention, the capacity fading model parameter modification module specifically includes: a first parameter modification module, configured to update the first parameter, where the first parameter modification formula is: a. thek＝Ak-1+k1× delta ξ, and a second parameter correction module for updating the second parameter, wherein the second parameter correction formula is as follows:a third parameter modification module, configured to update the third parameter, where the third parameter modification formula is: z is a radical ofk＝zk-1+k3× Δ ξ, where k in the subscript denotes the parameter after correction, k-1 in the subscript denotes the parameter before correction, k1Representing a preset first correction factor, k2Representing a preset second correction factor, k3Represents a preset third correction coefficient, and Δ ξ represents the estimation error.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a battery capacity online estimation method according to an embodiment of the present invention.
Fig. 2 is a block diagram of a battery capacity online estimation system according to an embodiment of the present invention.
Fig. 3 is a block diagram of the internal structure of a capacity fading model parameter correction module in the battery capacity online estimation system according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a variation of a capacity fading model parameter and a variation of an estimation error according to an embodiment of the present invention.
FIG. 5 is a graph comparing an online estimation curve and an experimental test curve for one embodiment of the present invention.
Fig. 6 is a schematic diagram of the on-line estimation of battery capacity of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In the description of the present invention, it is to be understood that the terms "first", "second" and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments. The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
As shown in fig. 1, the method for estimating the capacity of the battery on-line according to an embodiment of the present invention may include the steps of:
s1, providing a capacity attenuation model and initializing capacity attenuation model parameters.
In one example of the present invention, the capacity fade model of the battery under test is:wherein,the estimated relative capacity decrement of the battery to be tested after the nth charge-discharge cycle,is the estimated relative capacity attenuation of the battery to be tested after the n-1 th charge-discharge cycle, T is the ambient temperature of the battery to be tested when the battery to be tested is subjected to the n-th charge-discharge cycle, A represents a first parameter,representing a second parameter and z representing a third parameter.
In one example of the invention, a process specific package for initializing capacity fade model parametersComprises the following steps: selecting a reference battery with the same type as the battery to be tested and known final capacity attenuation model parameters, initializing A as a first parameter in a capacity attenuation model corresponding to the reference battery, and initializingAnd initializing z to be a third parameter in the capacity attenuation model corresponding to the reference battery.
And S2, circulating the charge and discharge of the battery to be tested for delta n times, wherein delta n is a preset positive integer.
For example, Δ n may be set to 90 times, or may be set to any other number of times.
And S3, obtaining the estimated relative capacity attenuation of the current battery to be tested according to the capacity attenuation model and the capacity attenuation model parameters.
Specifically, once per charge-discharge cycle, the estimated relative capacity attenuation of the battery to be tested is calculated once by using the capacity attenuation model and the capacity attenuation model parameters. And if the previous accumulative charge and discharge cycle is performed k x delta n times, calculating the current estimated relative capacity attenuation of the battery to be measured through k x delta n times.
And S4, testing the real capacity of the current battery to be tested to obtain the real relative capacity attenuation of the battery to be tested.
In one example of the present invention, the calculation formula of the real relative capacity attenuation of the battery to be tested isWherein C is the detected real capacity of the current battery to be detected, C0Is the initial capacity of the battery to be tested. It should be noted that, testing the real capacity of the current battery to be tested usually needs to be performed in a laboratory, which is troublesome to operate. Therefore, preferably, the real capacity of the battery to be tested is not tested after each charge and discharge cycle, but the real capacity of the current battery to be tested is tested 1 time after each charge and discharge cycle is delta n times.
And S5, subtracting the real relative capacity attenuation amount from the estimated relative capacity attenuation amount to obtain an estimation error.
I.e. the estimation errorWherein ξ is the real relative capacity decrement of the battery to be tested,the calculated estimated relative capacity decrement of the battery to be tested.
S6, if the estimation error is larger than the preset allowable error, the estimation error is used for correcting and updating the capacity attenuation model parameters, and then the step S2 is carried out.
In one example of the present invention, specifically, the first parameter is updated, and the first parameter modification formula is: a. thek＝Ak-1+k1× delta ξ, and updating the second parameter, wherein the second parameter correction formula is as follows:updating the third parameter, wherein the third parameter correction formula is as follows: z is a radical ofk＝zk-1+k3× Δ ξ, where k in the subscript denotes the parameter after correction, k-1 in the subscript denotes the parameter before correction, k1Representing a preset first correction factor, k2Representing a preset second correction factor, k3And representing a preset third correction coefficient, and delta ξ represents an estimation error, and jumping to step S2 to start a new iteration correction after correction.
And S7, if the estimation error is smaller than or equal to the preset allowable error, determining the capacity attenuation model parameter after the last correction as a final capacity attenuation model parameter to obtain an accurate capacity attenuation model corresponding to the battery to be measured, wherein the accurate capacity attenuation model is used for estimating the relative capacity attenuation of the battery to be measured and the battery capacity in the future.
Specifically, after the first parameter, the second parameter, and the third parameter are finally determined, an accurate capacity fade model can be obtained, and from this accurate capacity fade model, the relative capacity fade amount after each charge-discharge cycle can be obtained, and then according to the formula C ═ C (1- ξ) C0The battery capacity can be estimated online.
The online estimation method for the battery capacity has the advantages of being simple to operate and high in accuracy.
As shown in fig. 2, the battery capacity online estimation system according to an embodiment of the present invention may include the following parts: the device comprises a charge-discharge cycle counting module 10, a capacity attenuation model parameter storage unit 20, an estimated relative capacity attenuation calculation module 30, a real relative capacity attenuation test module 40, a comparison and judgment module 50, a capacity attenuation model parameter correction module 60 and a final capacity attenuation model output module 70.
The charge-discharge cycle counting module 10 is configured to record the number of charge-discharge cycles of the battery to be tested, and start counting from zero again each time the number of charge-discharge cycles reaches Δ n times.
The capacity fade model parameter storage unit 20 is used to store capacity fade model parameters.
In one example of the present invention, in the capacity fade model parameter storage unit 20, the initially stored (i.e., initialized) capacity fade model parameters include: selecting a reference battery with the same type as the battery to be tested and known final capacity attenuation model parameters, initializing A as a first parameter in a capacity attenuation model corresponding to the reference battery, and initializingAnd initializing z to be a third parameter in the capacity attenuation model corresponding to the reference battery.
The estimated relative capacity attenuation amount calculation module 30 is connected to the charge-discharge cycle counting module 10 and the capacity attenuation model parameter storage unit 20, respectively. The estimated relative capacity attenuation calculation module 30 is configured to bring the capacity attenuation model parameters into the capacity attenuation model to obtain the estimated relative capacity attenuation of the battery to be tested every time 1 charge-discharge cycle is completed.
In one example of the present invention, the capacity fade model of the battery under test is:wherein,the estimated relative capacity decrement of the battery to be tested after the nth charge-discharge cycle,is the estimated relative capacity attenuation of the battery to be tested after the n-1 th charge-discharge cycle, T is the ambient temperature of the battery to be tested when the battery to be tested is subjected to the n-th charge-discharge cycle, A represents a first parameter,representing a second parameter and z representing a third parameter.
It should be noted that, the estimated relative capacity attenuation calculating module 30 calculates the estimated relative capacity attenuation of the battery to be tested once by using the capacity attenuation model and the capacity attenuation model parameters every time the battery to be tested is charged and discharged for one cycle. And if the previous accumulative charge and discharge cycle is performed k x delta n times, calculating the current estimated relative capacity attenuation of the battery to be measured through k x delta n times.
The real relative capacity decrement calculation module 40 is connected to the charge and discharge cycle counting module 10. The real relative capacity attenuation testing module 40 is configured to test the real capacity of the battery to be tested each time the number of charge and discharge cycles is Δ n times, and calculate the real relative capacity attenuation of the battery to be tested.
In one example of the present invention, the true relative capacity fade of the battery under test in the true relative capacity fade test module 40The decrement is calculated by the formulaWherein C is the detected real capacity of the current battery to be detected, C0Is the initial capacity of the battery to be tested.
The comparison and judgment module 50 is respectively connected with the estimated relative capacity attenuation amount calculation module 30 and the real relative capacity attenuation amount test module 40. The comparing and determining module 50 is configured to compare the real relative capacity attenuation with the estimated relative capacity attenuation to obtain an estimation error, and determine a magnitude relationship between the estimation error and a preset allowable error.
Specifically, an estimation error is calculatedWherein ξ is the real relative capacity decrement of the battery to be tested,the calculated estimated relative capacity decrement of the battery to be tested. And then judging the comparison size of the estimation error and a preset allowable error.
The capacity attenuation model parameter modification module 60 is connected to the comparison and judgment module 50 and the capacity attenuation model parameter storage unit 20, respectively. When the judgment result of the comparison and judgment module 50 is that the estimation error is greater than the preset allowable error, the capacity attenuation model parameter modification module 60 modifies and updates the capacity attenuation model parameter by using the estimation error, and stores the updated capacity attenuation model parameter into the capacity attenuation model parameter storage unit 20.
In an example of the present invention, as shown in fig. 3, the capacity fade model parameter modification module 60 specifically includes: a first parameter modification module 610, a second parameter modification module 620, and a third parameter modification module 630. The first parameter modification module 610 is configured to update a first parameter, and the first parameter modification formula is as follows: a. thek＝Ak-1+k1× Δ ξ second parameter correction module 620 is used for updating the second parameter, and the second parameter modification formula is as follows:the third parameter modification module 630 is configured to update the third parameter, and the third parameter modification formula is: z is a radical ofk＝zk-1+k3× Δ ξ. in the above formula, k in the subscript represents the parameter after correction, k-1 in the subscript represents the parameter before correction, k1Representing a preset first correction factor, k2Representing a preset second correction factor, k3Indicating a preset third correction factor and Δ ξ indicating the estimation error.
The final capacity attenuation model output module 70 is connected to the comparison and judgment module 50 and the capacity attenuation model parameter storage unit 20, respectively. When the judgment result of the comparison judgment module 50 is that the estimation error is less than or equal to the preset allowable error, the final capacity attenuation model output module 70 takes the capacity attenuation model parameters stored in the capacity attenuation model parameter storage unit 20 as final capacity attenuation model parameters to obtain and output a final capacity attenuation model. And the final capacity fading model is used for estimating the relative capacity fading quantity and the battery capacity of the battery to be tested in the future.
Specifically, after the first parameter, the second parameter, and the third parameter are finally determined, an accurate capacity fade model can be obtained, and from this accurate capacity fade model, the relative capacity fade amount after each charge-discharge cycle can be obtained, and then according to the formula C ═ C (1- ξ) C0The battery capacity can be estimated online.
The battery capacity online estimation system provided by the embodiment of the invention has the advantages of simplicity and convenience in operation and high accuracy.
In order to make the person skilled in the art better understand the effects of the present invention, the applicant refers to a specific example as follows.
In a lithium ion battery with a positive electrode made of lithium iron phosphate and a negative electrode made of graphite, firstly, determining initial battery capacity fading model parameters by using a reference battery with known determination parameters of the same type as the reference battery: a is 0.15, Ea/R is 1400, and z is 0.5. This capacity fade model parameter is slightly different from the actual model parameter of the battery. Through the estimation method and the estimation system, step-by-step iterative correction is performed, after a period of time, the battery capacity attenuation model parameters are gradually corrected, the estimation error of the capacity is basically less than 1% in the open-loop estimation, and the model parameters are gradually converged to a fixed value, referring to fig. 4. After the final capacity fade model parameters are determined, the battery is estimated online. As can be seen from FIG. 5, the coincidence degree of the relative capacity online estimation curve of the lithium battery obtained by the method and the system of the invention and the experimental test curve is very high, which shows that the result of online estimation has high accuracy.
In summary, the idea of the online estimation of battery capacity of the present invention is that in the battery grouping and management system stage, in order to reduce cost, the battery capacity attenuation model parameters are not specifically tested, but the same type of battery capacity attenuation standard parameters are adopted; during operation, a capacity attenuation model is utilized, the capacity of the battery is estimated in an open loop mode according to key parameters such as charge and discharge current, environment temperature, charge and discharge depth and the like of the battery, and the result of capacity estimation can be used for a management algorithm of a battery management system, so that an energy management algorithm of a whole vehicle and the like; and calibrating the battery at intervals, measuring the real capacity of the battery, comparing the measurement result with the model estimation result, correcting the model parameters by using the model estimation error feedback, and updating the battery capacity value of the battery management system by using the actually measured capacity data. A logical block diagram of the entire capacity online estimation is shown in fig. 6. The estimation algorithm has high estimation precision and low system cost, and can be adaptive to batteries of different manufacturers and different batches.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples described in this specification can be combined and combined by one skilled in the art.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (6)
1. An online estimation method for battery capacity is characterized by comprising the following steps:
s1, providing a capacity attenuation model and initializing capacity attenuation model parameters, wherein the capacity attenuation model of the battery to be tested is as follows:wherein,the estimated relative capacity attenuation of the battery to be tested after the nth charge-discharge cycle,is the estimated relative capacity attenuation of the battery to be tested after the n-1 th charge-discharge cycle, T is the ambient temperature of the battery to be tested when the battery to be tested is subjected to the n-th charge-discharge cycle, A represents a first parameter,represents a second parameter, z represents a third parameter;
s2, circulating charge and discharge of the battery to be tested for delta n times, wherein delta n is a preset positive integer;
s3, obtaining the estimated relative capacity attenuation of the current battery to be tested according to the capacity attenuation model and the capacity attenuation model parameters;
s4, testing the current real capacity of the battery to be tested to obtain the real relative capacity attenuation of the battery to be tested, wherein the calculation formula of the real relative capacity attenuation of the battery to be tested isWherein C is the detected real capacity of the current battery to be detected, C0The initial capacity of the battery to be tested is obtained;
s5, subtracting the real relative capacity attenuation amount from the estimated relative capacity attenuation amount to obtain an estimation error;
s6, if the estimation error is larger than a preset allowable error, correcting and updating the capacity attenuation model parameters by using the estimation error, and then jumping to the step S2;
and S7, if the estimation error is less than or equal to the preset allowable error, determining the capacity attenuation model parameter after the last correction as a final capacity attenuation model parameter to obtain an accurate capacity attenuation model corresponding to the battery to be measured, wherein the accurate capacity attenuation model is used for estimating the relative capacity attenuation and the battery capacity of the battery to be measured in the future.
2. The online estimation method of battery capacity according to claim 1, characterized in that the initializing capacity fading model parameters comprises: selecting a reference battery with the same type as the battery to be tested and known final capacity attenuation model parameters, initializing the A as a first parameter in a capacity attenuation model corresponding to the reference battery, and initializing the AInitializing z as a third parameter in the capacity fading model corresponding to the reference battery for a second parameter in the capacity fading model corresponding to the reference battery.
3. The method according to claim 1, wherein the modifying and updating the capacity fading model parameters by using the estimation error specifically comprises:
updating the first parameter, wherein a first parameter correction formula is as follows: a. thek＝Ak-1+k1×Δξ；
Updating the second parameter, wherein the second parameter modification formula is as follows:
updating the third parameter, wherein a third parameter correction formula is as follows: z is a radical ofk＝zk-1+k3×Δξ，
Wherein k in the subscript represents the parameter after correction, k-1 in the subscript represents the parameter before correction, k1Representing a preset first correction factor, k2Representing a preset second correction factor, k3Represents a preset third correction coefficient, and Δ ξ represents the estimation error.
4. An online estimation system for battery capacity, comprising:
the charging and discharging cycle counting module is used for recording the charging and discharging cycle times of the battery to be tested, and counting from zero again when the charging and discharging cycle times reach delta n times;
a capacity fading model parameter storage unit is used for storing capacity fading model parameters, wherein a capacity fading model of a battery to be tested is as follows:wherein,the estimated relative capacity attenuation of the battery to be tested after the nth charge-discharge cycle,is the estimated relative capacity attenuation of the battery to be tested after the n-1 th charge-discharge cycle, T is the ambient temperature of the battery to be tested when the battery to be tested is subjected to the n-th charge-discharge cycle, A represents a first parameter,represents a second parameter, z represents a third parameter;
the estimated relative capacity attenuation calculation module is respectively connected with the charge-discharge cycle counting module and the capacity attenuation model parameter storage unit and is used for substituting the capacity attenuation model parameters into a capacity attenuation model to obtain the estimated relative capacity attenuation of the battery to be measured every time 1 charge-discharge cycle is completed;
the real relative capacity attenuation testing module is connected with the charging and discharging cycle counting module and used for testing the real capacity of the battery to be tested and calculating the real relative capacity attenuation of the battery to be tested when the charging and discharging cycle times are delta n times, wherein in the real relative capacity attenuation testing module, the calculation formula of the real relative capacity attenuation of the battery to be tested is thatWherein C is the detected real capacity of the current battery to be detected, C0The initial capacity of the battery to be tested is obtained;
the comparison and judgment module is respectively connected with the estimation relative capacity attenuation calculation module and the real relative capacity attenuation test module, and is used for comparing the real relative capacity attenuation with the estimation relative capacity attenuation to obtain an estimation error and judging the size relationship between the estimation error and a preset allowable error;
the capacity attenuation model parameter correction module is respectively connected with the comparison judgment module and the capacity attenuation model parameter storage unit, and when the judgment result of the comparison judgment module is that the estimation error is larger than a preset allowable error, the capacity attenuation model parameter correction module corrects and updates the capacity attenuation model parameter by using the estimation error and stores the updated capacity attenuation model parameter into the capacity attenuation model parameter storage unit;
and the final capacity attenuation model output module is respectively connected with the comparison and judgment module and the capacity attenuation model parameter storage unit, and when the judgment result of the comparison and judgment module is that the estimation error is less than or equal to a preset allowable error, the final capacity attenuation model output module takes the capacity attenuation model parameters stored in the capacity attenuation model parameter storage unit as final capacity attenuation model parameters to obtain and output a final capacity attenuation model, wherein the final capacity attenuation model is used for estimating the relative capacity attenuation and the battery capacity of the battery to be detected in the future.
5. The battery capacity online estimation system according to claim 4, wherein in the capacity fading model parameter storage unit, the initialized capacity fading model parameters include: selecting the power to be testedInitializing a reference battery with the same type of battery and known final capacity attenuation model parameters, wherein A is a first parameter in a capacity attenuation model corresponding to the reference battery, and initializing the reference batteryInitializing z as a third parameter in the capacity fading model corresponding to the reference battery for a second parameter in the capacity fading model corresponding to the reference battery.
6. The system for online estimation of battery capacity according to claim 4, wherein the capacity fading model parameter modification module specifically comprises:
a first parameter modification module, configured to update the first parameter, where the first parameter modification formula is: a. thek＝Ak-1+k1×Δξ；
A second parameter modification module, configured to update the second parameter, where the second parameter modification formula is:
a third parameter modification module, configured to update the third parameter, where the third parameter modification formula is: z is a radical ofk＝zk-1+k3×Δξ，
Wherein k in the subscript represents the parameter after correction, k-1 in the subscript represents the parameter before correction, k1Representing a preset first correction factor, k2Representing a preset second correction factor, k3Represents a preset third correction coefficient, and Δ ξ represents the estimation error.
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| CN106291386B (en) * | 2016-09-20 | 2019-06-11 | 深圳市鑫彩翼科技有限公司 | A kind of method of quick detection rechargeable battery capacity |
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| CN110764009B (en) * | 2019-10-31 | 2021-09-28 | 重庆长安新能源汽车科技有限公司 | Method for estimating battery pack circulation capacity and health state of electric automobile |
| CN112345954B (en) * | 2020-10-21 | 2024-04-09 | 一汽解放汽车有限公司 | Battery life prediction method, device, electronic equipment and medium |
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