CN117783907B - Method and system for estimating soc of power lithium battery of electric automobile - Google Patents
Method and system for estimating soc of power lithium battery of electric automobile Download PDFInfo
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Abstract
本发明提供一种电动汽车动力锂电池soc估算方法、系统，其中，方法包括：获取电动汽车的动力锂电池的soc显示值；预测所述动力锂电池的老化状态值；基于所述老化状态值、预设的修正系数库，确定修正系数；基于所述修正系数、所述soc显示值，确定soc最终值。本发明的电动汽车动力锂电池soc估算方法、系统，预测电动汽车的动力锂电池的老化状态值，引入修正系数库，基于老化状态值、修正系数库确定修正系数，利用修正系数对动力锂电池的soc显示值进行修正，获得soc最终值，将动力锂电池的老化因素纳入soc估算中，提升了动力锂电池soc估算的精准性。
The present invention provides a method and system for estimating the SOC of a power lithium battery of an electric vehicle, wherein the method comprises: obtaining the SOC display value of the power lithium battery of the electric vehicle; predicting the aging state value of the power lithium battery; determining the correction coefficient based on the aging state value and a preset correction coefficient library; and determining the final SOC value based on the correction coefficient and the SOC display value. The method and system for estimating the SOC of a power lithium battery of an electric vehicle of the present invention predict the aging state value of the power lithium battery of the electric vehicle, introduce a correction coefficient library, determine the correction coefficient based on the aging state value and the correction coefficient library, use the correction coefficient to correct the SOC display value of the power lithium battery, obtain the final SOC value, incorporate the aging factor of the power lithium battery into the SOC estimation, and improve the accuracy of the SOC estimation of the power lithium battery.
Description
Technical Field
The invention relates to the technical field of battery soc estimation, in particular to a method and a system for estimating the soc of a power lithium battery of an electric automobile.
Background
Currently, a soc (State of Charge) of a lithium battery of an electric automobile has a great influence on a cruising mileage of the automobile at a point. Conventionally, there are ampere-hour integration methods and the like in methods for estimating the soc of the lithium battery of the electric automobile, but these soc estimation methods have high requirements on the lithium battery itself, and require that the lithium battery is in a newer state. Thus, a solution is needed.
Disclosure of Invention
The invention aims to provide a method for estimating the soc of a power lithium battery of an electric automobile, which is used for predicting the aging state value of the power lithium battery of the electric automobile, introducing a correction coefficient library, determining a correction coefficient based on the aging state value and the correction coefficient library, correcting the soc display value of the power lithium battery by using the correction coefficient to obtain a soc final value, and taking the aging factor of the power lithium battery into the soc estimation to improve the accuracy of the soc estimation of the power lithium battery.
The embodiment of the invention provides a method for estimating the soc of an electric automobile power lithium battery, which comprises the following steps:
Step S1: acquiring a soc display value of a power lithium battery of the electric automobile;
step S2: predicting an aging state value of the power lithium battery;
step S3: determining a correction coefficient based on the aging state value and a preset correction coefficient library;
step S4: and determining a final value of the soc based on the correction coefficient and the soc display value.
Preferably, the step S2: predicting an aging state value of the power lithium battery, comprising:
Obtaining a plurality of prediction test vehicles for predicting the aging state value of the power lithium battery of the electric automobile at the last time;
acquiring first incremental driving data of the electric automobile;
traversing the test vehicle for prediction in sequence;
Each time of traversing, obtaining second incremental driving data of the traversed test vehicle for prediction;
matching the second increment driving data with the first increment driving data to obtain a data matching condition;
Determining the evaluation value sum of the traversed test vehicle for prediction based on the data matching condition and a preset condition evaluation system;
after traversing the prediction test vehicle, acquiring the latest test aging state value of each prediction test vehicle;
Calculating the aging state value of the power lithium battery:
Wherein Old' is the aging state value of the power lithium battery, f (Eva i) is an intermediate variable function, eva i is the sum of the evaluation values of the ith test vehicle for prediction, old i is the latest test aging state value of the ith test vehicle for prediction, n is the total number of test vehicles for prediction, and Eva 0 is a preset evaluation value and threshold.
Preferably, the method for estimating the soc of the lithium battery of the electric automobile further comprises the following step S5:
updating the correction coefficient library.
Preferably, the step S5: updating the correction coefficient library, comprising:
Based on a preset event monitoring template, monitoring a plurality of soc error events of the electric automobile;
classifying the soc error event based on a preset event classification template to obtain event sets of a plurality of event categories;
determining whether the event set meets a standard set condition;
when the correlation correction coefficients are matched, determining correlation correction coefficients and corresponding coefficient correlation times which are correlated with the soc error events in the corresponding event set in the correction coefficient library;
Generating a template based on a preset updating requirement, and generating a library updating requirement according to the association correction coefficient and the corresponding coefficient association times;
determining nodes to be issued meeting standard node conditions from a plurality of preset library updating nodes;
Issuing the library update demand to the node to be issued;
Acquiring library updating content returned by the node to be issued;
updating the correction coefficient library based on the library updating content;
wherein the standard set condition includes:
The preset category weight corresponding to the event category to which the event set belongs is greater than or equal to a preset weight threshold;
The total number of the soc error events in the event set is greater than or equal to a preset number threshold;
Wherein the standard node conditions include:
At least one mapping relation of a preset standard relation class exists between the library updating node and the library updating requirement.
Preferably, the method for estimating the soc of the lithium battery of the electric automobile further comprises the following step S6:
determining whether the final value of the soc is greater than or equal to a preset soc threshold value;
If yes, obtaining a reduction amplitude value of the final value of the soc;
When the reduced amplitude value is greater than or equal to a preset amplitude value threshold, determining whether the correction coefficient meets a standard coefficient condition;
when the final value is consistent, displaying the final value of the soc to a driver of the electric automobile; otherwise, displaying the soc display value to a driver of the electric automobile;
wherein the standard coefficient conditions include:
the correction factor is greater than 1.
The embodiment of the invention provides a soc estimation system for an electric automobile power lithium battery, which comprises the following components:
the acquisition module is used for acquiring a soc display value of a power lithium battery of the electric automobile;
The prediction module is used for predicting the aging state value of the power lithium battery;
the first determining module is used for determining a correction coefficient based on the aging state value and a preset correction coefficient library;
And the second determining module is used for determining a final value of the soc based on the correction coefficient and the soc display value.
Preferably, the prediction module step S2: predicting an aging state value of the power lithium battery, comprising:
Obtaining a plurality of prediction test vehicles for predicting the aging state value of the power lithium battery of the electric automobile at the last time;
acquiring first incremental driving data of the electric automobile;
traversing the test vehicle for prediction in sequence;
Each time of traversing, obtaining second incremental driving data of the traversed test vehicle for prediction;
matching the second increment driving data with the first increment driving data to obtain a data matching condition;
Determining the evaluation value sum of the traversed test vehicle for prediction based on the data matching condition and a preset condition evaluation system;
after traversing the prediction test vehicle, acquiring the latest test aging state value of each prediction test vehicle;
Calculating the aging state value of the power lithium battery:
Wherein Old' is the aging state value of the power lithium battery, f (Eva i) is an intermediate variable function, eva i is the sum of the evaluation values of the ith test vehicle for prediction, old i is the latest test aging state value of the ith test vehicle for prediction, n is the total number of test vehicles for prediction, and Eva 0 is a preset evaluation value and threshold.
Preferably, the electric automobile power lithium battery soc estimation system further comprises an updating module for:
updating the correction coefficient library.
Preferably, in the system for estimating soc of a lithium battery of an electric vehicle, the updating module updates the correction coefficient library, including:
Based on a preset event monitoring template, monitoring a plurality of soc error events of the electric automobile;
classifying the soc error event based on a preset event classification template to obtain event sets of a plurality of event categories;
determining whether the event set meets a standard set condition;
when the correlation correction coefficients are matched, determining correlation correction coefficients and corresponding coefficient correlation times which are correlated with the soc error events in the corresponding event set in the correction coefficient library;
Generating a template based on a preset updating requirement, and generating a library updating requirement according to the association correction coefficient and the corresponding coefficient association times;
determining nodes to be issued meeting standard node conditions from a plurality of preset library updating nodes;
Issuing the library update demand to the node to be issued;
Acquiring library updating content returned by the node to be issued;
updating the correction coefficient library based on the library updating content;
wherein the standard set condition includes:
The preset category weight corresponding to the event category to which the event set belongs is greater than or equal to a preset weight threshold;
The total number of the soc error events in the event set is greater than or equal to a preset number threshold;
Wherein the standard node conditions include:
At least one mapping relation of a preset standard relation class exists between the library updating node and the library updating requirement.
Preferably, the electric automobile power lithium battery soc estimation system further comprises a display module for:
determining whether the final value of the soc is greater than or equal to a preset soc threshold value;
If yes, obtaining a reduction amplitude value of the final value of the soc;
When the reduced amplitude value is greater than or equal to a preset amplitude value threshold, determining whether the correction coefficient meets a standard coefficient condition;
when the final value is consistent, displaying the final value of the soc to a driver of the electric automobile; otherwise, displaying the soc display value to a driver of the electric automobile;
wherein the standard coefficient conditions include:
the correction factor is greater than 1.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic diagram of a method for estimating soc of an electric vehicle power lithium battery according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a soc estimation system for an electric vehicle power lithium battery according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a method for estimating the soc of an electric automobile power lithium battery, which is shown in fig. 1 and comprises the following steps:
Step S1: acquiring a soc display value of a power lithium battery of the electric automobile;
step S2: predicting an aging state value of the power lithium battery;
step S3: determining a correction coefficient based on the aging state value and a preset correction coefficient library;
step S4: and determining a final value of the soc based on the correction coefficient and the soc display value.
The soc display value is a value obtained by performing soc estimation on the power lithium battery according to an ampere-hour integration method and the like; predicting an aging state value of the power lithium battery, wherein the aging state value represents the aging degree of the power lithium battery, and the aging state value is expressed in a form of percentage, for example: 5%, 10%, etc.; the correction coefficient library is provided with correction coefficients corresponding to different aging state values, a large number of test power lithium batteries with the same model and different aging states are selected in advance for charge and discharge tests, in the test process, the estimated value and the actual soc value of the test power lithium battery for soc estimation according to an ampere-hour integration method and the like are measured (the actual soc value can be measured based on a special lithium battery soc tester and the like), and the correction coefficient is determined based on the numerical ratio between the actual soc value and the estimated value; when the correction coefficient is used, the soc display value is multiplied by the correction coefficient to obtain the soc final value.
According to the method, the aging state value of the power lithium battery of the electric automobile is predicted, the correction coefficient library is introduced, the correction coefficient is determined based on the aging state value and the correction coefficient library, the soc display value of the power lithium battery is corrected by using the correction coefficient, the soc final value is obtained, the aging factor of the power lithium battery is taken into the soc estimation, and the accuracy of the soc estimation of the power lithium battery is improved.
In one embodiment, the step S2: predicting an aging state value of the power lithium battery, comprising:
Obtaining a plurality of prediction test vehicles for predicting the aging state value of the power lithium battery of the electric automobile at the last time;
acquiring first incremental driving data of the electric automobile;
traversing the test vehicle for prediction in sequence;
Each time of traversing, obtaining second incremental driving data of the traversed test vehicle for prediction;
matching the second increment driving data with the first increment driving data to obtain a data matching condition;
Determining the evaluation value sum of the traversed test vehicle for prediction based on the data matching condition and a preset condition evaluation system;
after traversing the prediction test vehicle, acquiring the latest test aging state value of each prediction test vehicle;
Calculating the aging state value of the power lithium battery:
Wherein Old' is the aging state value of the power lithium battery, f (Eva i) is an intermediate variable function, eva i is the sum of the evaluation values of the ith test vehicle for prediction, old i is the latest test aging state value of the ith test vehicle for prediction, n is the total number of test vehicles for prediction, and Eva 0 is a preset evaluation value and threshold.
The prediction test vehicles are divided into two types, wherein the first type is set by an electric automobile manufacturer, and the second type is driven by other automobile owners, and the vehicle types of the prediction test vehicles are the same as those of the electric automobiles; the first incremental running data is the vehicle running data (such as average speed per hour, highest speed per hour, average load capacity, running environment average temperature, charging times and the like) of the electric vehicle during the period of predicting the current moment when the electric vehicle carries out the power lithium battery aging state value last time; the second incremental running data is the running data (such as average speed per hour, highest speed per hour, average load capacity, running environment average temperature, charging times and the like) of the prediction test vehicle during the period from when the prediction test vehicle is used as the electric vehicle to predict the power lithium battery aging state value to when the lithium battery aging state test is performed by the special lithium battery aging state tester; The data matching cases include: matching between data of different data categories, such as: average speed per hour, matching degree 70%; the condition evaluation system is provided with evaluation value tables corresponding to different data types, the evaluation value tables are provided with evaluation values corresponding to different matching degrees under the data types, and the larger the matching degree is, the more the corresponding prediction test vehicle is provided with a value for predicting the aging state value of the power lithium battery of the electric automobile, the larger the value is; when the evaluation value sum is determined, inquiring a corresponding evaluation value table according to the matching degree among different data types in the data matching condition, determining the evaluation value, and finally, carrying out accumulation calculation on each determined evaluation value to obtain the evaluation value sum; the latest test aging state value of the test vehicle for prediction is a value obtained by the latest test of the lithium battery aging state of the test vehicle for prediction through a special lithium battery aging state tester, and the latest test aging state value is also expressed in percentage form; The aging state value of the power lithium battery is comprehensively calculated by the above formula, wherein the evaluation value and the threshold value Eva 0 may be, for example, 80, and when the evaluation value and Eva i of the ith test vehicle for prediction are equal to or less than the evaluation value and the threshold value Eva 0, The value of the intermediate variable function f (Eva i) is 0, otherwise, the degree that the evaluation value of the ith test vehicle for prediction and Eva i are larger than the evaluation value and Eva 0 is larger, Giving a larger increasing weight to the evaluation value of the i-th test vehicle for prediction and Eva i, and giving a function value of the intermediate variable function f (Eva i) of Eva i·(Evai-Eva0); After the aging state value of the power lithium battery is calculated, each prediction test vehicle is used as the power lithium battery aging state value for predicting once again by the electric vehicle, and becomes a plurality of prediction test vehicles for predicting the power lithium battery aging state value which is the last time the electric vehicle predicts the power lithium battery aging state value next time, and the technology forms a closed loop.
Generally, the test of the correction coefficient library has smaller workload, but the aging of the power lithium battery of the electric automobile is influenced by a large number of factors such as driving habits, service environment conditions and the like, the aging degree of the power lithium battery can be accurately obtained only by carrying out the aging state test of the lithium battery through a special lithium battery aging state tester, and the library cannot be tested in advance (for example, the library is built in the same principle as the correction coefficient library, and the aging state value library is built), so that the embodiment of the invention can solve the problem. The manufacturer of the electric automobile can set a plurality of test vehicles to run in the city, the regular factory return is carried out the lithium battery ageing state test through the lithium battery ageing state tester, the lithium battery ageing state test can be carried out through the lithium battery ageing state tester when the electric automobile of other car owners returns to the factory for maintenance, power change and the like, the second increment running data are recorded, the second increment running data are matched with the first increment running data of the electric automobile, a condition evaluation system is introduced, the evaluation value sum is determined, the ageing state value of the power lithium battery is comprehensively calculated, the prediction accuracy and the prediction efficiency of the ageing state value of the power lithium battery are greatly improved, and meanwhile, the electric automobile power lithium battery power supply system is particularly suitable for use.
In one embodiment, the step S5: updating the correction coefficient library, comprising:
Based on a preset event monitoring template, monitoring a plurality of soc error events of the electric automobile;
classifying the soc error event based on a preset event classification template to obtain event sets of a plurality of event categories;
determining whether the event set meets a standard set condition;
when the correlation correction coefficients are matched, determining correlation correction coefficients and corresponding coefficient correlation times which are correlated with the soc error events in the corresponding event set in the correction coefficient library;
Generating a template based on a preset updating requirement, and generating a library updating requirement according to the association correction coefficient and the corresponding coefficient association times;
determining nodes to be issued meeting standard node conditions from a plurality of preset library updating nodes; each node to be issued corresponds to at least one electric automobile expert;
Issuing the library update demand to the node to be issued;
Acquiring library updating content returned by the node to be issued;
updating the correction coefficient library based on the library updating content;
wherein the standard set condition includes:
The preset category weight corresponding to the event category to which the event set belongs is greater than or equal to a preset weight threshold;
The total number of the soc error events in the event set is greater than or equal to a preset number threshold;
Wherein the standard node conditions include:
At least one mapping relation of a preset standard relation class exists between the library updating node and the library updating requirement.
The soc error event includes: the driver of the electric automobile reflects the event of the electric automobile endurance deficiency mark and the like; the associated correction coefficients are, for example: the soc error event is that a driver of the electric automobile reflects a continuous meter of the electric automobile, at the moment, the final value of the soc seen by the driver is 20%, the associated correction coefficient is the correction coefficient used at the moment for correcting the soc display value to 20% of the final value of the soc, and one association exists between the correction coefficient and the soc error event; the coefficient association times are the total times of the association between the soc error event and the existing association; library update requirements are, for example: the association correction coefficient and the corresponding coefficient association times are respectively 1.0003 and 30 times, and the generated library updating requirement is that the correction coefficient 1.003 is reflected for 30 times and has errors, and verification is needed; when the issuing node receives the library update requirement, performing a corresponding test to redetermine the library update content, for example: new correction coefficients; the category weight represents the degree of urgency that the soc error event of the event category needs to be solved; the weight threshold may be, for example: 7, preparing a base material; when the class weight is greater than or equal to the weight threshold, the urgent degree that the soc error event corresponding to the event class needs to be solved is large, and the corresponding library update requirement needs to be generated; the number threshold may be, for example: 10; the more the total number of the soc error events in the event set is, the more the soc error events representing the same event category are, the more the soc error events need to be solved; the mapping relation of the standard relation category comprises: the associated correction factors are historically provided by the library update node, etc. The embodiment of the invention timely updates the correction coefficient library and ensures the capability of the correction coefficient library for determining the correction coefficient so as to correct the soc display value.
In one embodiment, the method for estimating the soc of the lithium battery of the electric automobile further includes step S6:
determining whether the final value of the soc is greater than or equal to a preset soc threshold value;
If yes, obtaining a reduction amplitude value of the final value of the soc;
When the reduced amplitude value is greater than or equal to a preset amplitude value threshold, determining whether the correction coefficient meets a standard coefficient condition;
when the final value is consistent, displaying the final value of the soc to a driver of the electric automobile; otherwise, displaying the soc display value to a driver of the electric automobile;
wherein the standard coefficient conditions include:
the correction factor is greater than 1.
The soc threshold may be, for example: 40%; the reduction amplitude value of the final value of the soc is the absolute value of the difference value between the final value of the soc and the final value of the soc obtained by last power lithium battery soc estimation; when the correction coefficient is larger than 1, the correction coefficient expands the displayed value of the soc, the final value of the soc is displayed to the driver of the electric automobile, the situation that the user sees the jump of the soc display is reduced, and the method is more humanized.
The embodiment of the invention provides a soc estimation system for an electric automobile power lithium battery, as shown in fig. 2, comprising:
the acquisition module 1 is used for acquiring a soc display value of a power lithium battery of the electric automobile;
the prediction module 2 is used for predicting the aging state value of the power lithium battery;
A first determining module 3, configured to determine a correction coefficient based on the aging state value and a preset correction coefficient library;
A second determining module 4, configured to determine a soc final value based on the correction coefficient and the soc display value.
The prediction module 2 step S2: predicting an aging state value of the power lithium battery, comprising:
Obtaining a plurality of prediction test vehicles for predicting the aging state value of the power lithium battery of the electric automobile at the last time;
acquiring first incremental driving data of the electric automobile;
traversing the test vehicle for prediction in sequence;
Each time of traversing, obtaining second incremental driving data of the traversed test vehicle for prediction;
matching the second increment driving data with the first increment driving data to obtain a data matching condition;
Determining the evaluation value sum of the traversed test vehicle for prediction based on the data matching condition and a preset condition evaluation system;
after traversing the prediction test vehicle, acquiring the latest test aging state value of each prediction test vehicle;
Calculating the aging state value of the power lithium battery:
Wherein Old' is the aging state value of the power lithium battery, f (Eva i) is an intermediate variable function, eva i is the sum of the evaluation values of the ith test vehicle for prediction, old i is the latest test aging state value of the ith test vehicle for prediction, n is the total number of test vehicles for prediction, and Eva 0 is a preset evaluation value and threshold.
The electric automobile power lithium cell soc estimation system still includes the update module for:
updating the correction coefficient library.
The updating module updates the correction coefficient library, including:
Based on a preset event monitoring template, monitoring a plurality of soc error events of the electric automobile;
classifying the soc error event based on a preset event classification template to obtain event sets of a plurality of event categories;
determining whether the event set meets a standard set condition;
when the correlation correction coefficients are matched, determining correlation correction coefficients and corresponding coefficient correlation times which are correlated with the soc error events in the corresponding event set in the correction coefficient library;
Generating a template based on a preset updating requirement, and generating a library updating requirement according to the association correction coefficient and the corresponding coefficient association times;
determining nodes to be issued meeting standard node conditions from a plurality of preset library updating nodes;
Issuing the library update demand to the node to be issued;
Acquiring library updating content returned by the node to be issued;
updating the correction coefficient library based on the library updating content;
wherein the standard set condition includes:
The preset category weight corresponding to the event category to which the event set belongs is greater than or equal to a preset weight threshold;
The total number of the soc error events in the event set is greater than or equal to a preset number threshold;
Wherein the standard node conditions include:
At least one mapping relation of a preset standard relation class exists between the library updating node and the library updating requirement.
The electric automobile power lithium cell soc estimation system still includes display module for:
determining whether the final value of the soc is greater than or equal to a preset soc threshold value;
If yes, obtaining a reduction amplitude value of the final value of the soc;
When the reduced amplitude value is greater than or equal to a preset amplitude value threshold, determining whether the correction coefficient meets a standard coefficient condition;
when the final value is consistent, displaying the final value of the soc to a driver of the electric automobile; otherwise, displaying the soc display value to a driver of the electric automobile;
wherein the standard coefficient conditions include:
the correction factor is greater than 1.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. The method for estimating the soc of the power lithium battery of the electric automobile is characterized by comprising the following steps of:
Step S1: acquiring a soc display value of a power lithium battery of the electric automobile;
step S2: predicting an aging state value of the power lithium battery;
step S3: determining a correction coefficient based on the aging state value and a preset correction coefficient library;
step S4: determining a soc final value based on the correction coefficient and the soc display value;
The step S2: predicting an aging state value of the power lithium battery, comprising:
Obtaining a plurality of prediction test vehicles for predicting the aging state value of the power lithium battery of the electric automobile at the last time;
acquiring first incremental driving data of the electric automobile;
traversing the test vehicle for prediction in sequence;
Each time of traversing, obtaining second incremental driving data of the traversed test vehicle for prediction;
matching the second increment driving data with the first increment driving data to obtain a data matching condition;
Determining the evaluation value sum of the traversed test vehicle for prediction based on the data matching condition and a preset condition evaluation system;
after traversing the prediction test vehicle, acquiring the latest test aging state value of each prediction test vehicle;
Calculating the aging state value of the power lithium battery:
；
；
wherein, For the aging state value of the power lithium battery,As a function of the intermediate variables,Is the firstThe sum of the evaluation values of the prediction test vehicles,Is the firstThe latest test aging state value of each of the test vehicles for prediction,For the total number of the test cars for prediction,Is a preset evaluation value and threshold value.
2. The method for estimating soc of an electric vehicle power lithium battery as claimed in claim 1, further comprising step S5:
updating the correction coefficient library.
3. The method for estimating soc of a lithium battery for electric automobile as claimed in claim 2, wherein the step S5: updating the correction coefficient library, comprising:
Based on a preset event monitoring template, monitoring a plurality of soc error events of the electric automobile;
classifying the soc error event based on a preset event classification template to obtain event sets of a plurality of event categories;
determining whether the event set meets a standard set condition;
when the correlation correction coefficients are matched, determining correlation correction coefficients and corresponding coefficient correlation times which are correlated with the soc error events in the corresponding event set in the correction coefficient library;
Generating a template based on a preset updating requirement, and generating a library updating requirement according to the association correction coefficient and the corresponding coefficient association times;
determining nodes to be issued meeting standard node conditions from a plurality of preset library updating nodes;
Issuing the library update demand to the node to be issued;
Acquiring library updating content returned by the node to be issued;
updating the correction coefficient library based on the library updating content;
wherein the standard set condition includes:
The preset category weight corresponding to the event category to which the event set belongs is greater than or equal to a preset weight threshold;
The total number of the soc error events in the event set is greater than or equal to a preset number threshold;
Wherein the standard node conditions include:
At least one mapping relation of a preset standard relation class exists between the library updating node and the library updating requirement.
4. The method for estimating soc of an electric vehicle power lithium battery as claimed in claim 1, further comprising step S6:
determining whether the final value of the soc is greater than or equal to a preset soc threshold value;
If yes, obtaining a reduction amplitude value of the final value of the soc;
When the reduced amplitude value is greater than or equal to a preset amplitude value threshold, determining whether the correction coefficient meets a standard coefficient condition;
when the final value is consistent, displaying the final value of the soc to a driver of the electric automobile; otherwise, displaying the soc display value to a driver of the electric automobile;
wherein the standard coefficient conditions include:
the correction factor is greater than 1.
5. The utility model provides an electric automobile power lithium cell soc estimation system which characterized in that includes:
the acquisition module is used for acquiring a soc display value of a power lithium battery of the electric automobile;
The prediction module is used for predicting the aging state value of the power lithium battery;
the first determining module is used for determining a correction coefficient based on the aging state value and a preset correction coefficient library;
the second determining module is used for determining a final value of the soc based on the correction coefficient and the soc display value;
The prediction module step S2: predicting an aging state value of the power lithium battery, comprising:
Obtaining a plurality of prediction test vehicles for predicting the aging state value of the power lithium battery of the electric automobile at the last time;
acquiring first incremental driving data of the electric automobile;
traversing the test vehicle for prediction in sequence;
Each time of traversing, obtaining second incremental driving data of the traversed test vehicle for prediction;
matching the second increment driving data with the first increment driving data to obtain a data matching condition;
Determining the evaluation value sum of the traversed test vehicle for prediction based on the data matching condition and a preset condition evaluation system;
after traversing the prediction test vehicle, acquiring the latest test aging state value of each prediction test vehicle;
Calculating the aging state value of the power lithium battery:
；
；
wherein, For the aging state value of the power lithium battery,As a function of the intermediate variables,Is the firstThe sum of the evaluation values of the prediction test vehicles,Is the firstThe latest test aging state value of each of the test vehicles for prediction,For the total number of the test cars for prediction,Is a preset evaluation value and threshold value.
6. The electric vehicle power lithium battery soc estimation system of claim 5, further comprising an update module to:
updating the correction coefficient library.
7. The system of claim 6, wherein the updating module updates the correction coefficient library, comprising:
Based on a preset event monitoring template, monitoring a plurality of soc error events of the electric automobile;
classifying the soc error event based on a preset event classification template to obtain event sets of a plurality of event categories;
determining whether the event set meets a standard set condition;
when the correlation correction coefficients are matched, determining correlation correction coefficients and corresponding coefficient correlation times which are correlated with the soc error events in the corresponding event set in the correction coefficient library;
Generating a template based on a preset updating requirement, and generating a library updating requirement according to the association correction coefficient and the corresponding coefficient association times;
determining nodes to be issued meeting standard node conditions from a plurality of preset library updating nodes;
Issuing the library update demand to the node to be issued;
Acquiring library updating content returned by the node to be issued;
updating the correction coefficient library based on the library updating content;
wherein the standard set condition includes:
The preset category weight corresponding to the event category to which the event set belongs is greater than or equal to a preset weight threshold;
The total number of the soc error events in the event set is greater than or equal to a preset number threshold;
Wherein the standard node conditions include:
At least one mapping relation of a preset standard relation class exists between the library updating node and the library updating requirement.
8. The electric vehicle power lithium battery soc estimation system of claim 5, further comprising a display module configured to:
determining whether the final value of the soc is greater than or equal to a preset soc threshold value;
If yes, obtaining a reduction amplitude value of the final value of the soc;
When the reduced amplitude value is greater than or equal to a preset amplitude value threshold, determining whether the correction coefficient meets a standard coefficient condition;
when the final value is consistent, displaying the final value of the soc to a driver of the electric automobile; otherwise, displaying the soc display value to a driver of the electric automobile;
wherein the standard coefficient conditions include:
the correction factor is greater than 1.
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