CN117429303A - Electric automobile battery replacement method, system and equipment based on Internet of things - Google Patents

Electric automobile battery replacement method, system and equipment based on Internet of things Download PDF

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Publication number
CN117429303A
CN117429303A CN202311302170.0A CN202311302170A CN117429303A CN 117429303 A CN117429303 A CN 117429303A CN 202311302170 A CN202311302170 A CN 202311302170A CN 117429303 A CN117429303 A CN 117429303A
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battery
electric automobile
state
internet
driving mileage
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CN117429303B (en
Inventor
李建武
李明贤
曹洋
董义鹏
刘玉庆
张哲杰
刘凯
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Advanced Technology Research Institute of Beijing Institute of Technology
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Advanced Technology Research Institute of Beijing Institute of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/80—Exchanging energy storage elements, e.g. removable batteries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/042—Backward inferencing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/043—Distributed expert systems; Blackboards
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/02—Computing arrangements based on specific mathematical models using fuzzy logic
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • 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, a system and equipment for replacing batteries of an electric vehicle based on the Internet of things, which belong to the technical field of battery replacement of the electric vehicle, and the method is based on the electric vehicle supporting the battery replacement operation and specifically comprises the following steps: s1: acquiring battery state information, and analyzing the battery driving mileage state by using a fuzzy hierarchy; s2: acquiring the geographic position of an electric automobile of a battery to be replaced, and traversing a battery replacement station in a preset range by using the geographic position of the electric automobile as a center through the Internet of things; s3: and establishing a game model, obtaining the optimal battery replacement station position based on the game model, and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced. The invention ensures the service life of the battery and the driving safety, greatly saves the charging time, realizes higher automation level and provides high-quality driving service for users.

Description

Electric automobile battery replacement method, system and equipment based on Internet of things
Technical Field
The invention relates to the technical field of battery replacement of electric automobiles, in particular to a method, a system and equipment for battery replacement of electric automobiles based on the Internet of things.
Background
The replenishment of electric energy into electric vehicles has been a troublesome problem. In order to improve the usability and the convenience, the main technical means in the prior application is a quick charging technology. However, quick charge has several problems:
the fast charging has higher requirements on the pressure resistance and the safety of the battery pack, the fast charging mode is far greater than the slow charging mode, the generated high temperature can directly cause the accelerated aging inside the battery, the service life of the battery is greatly shortened, and the battery is frequently failed if serious; the charging efficiency of the fast charging is not improved much compared with that of the slow charging, and the charging time of the fast charging and the slow charging is almost the same, so that the battery pack with the power shortage can be charged to a full-charge state only after taking a few hours.
At present, although most battery replacing stations of the electric automobile built and put into operation are equipped with special robot equipment to finish the carrying and loading and unloading work of the battery, the service life of the battery of the electric automobile is not concerned excessively, the number of the battery replacing stations is small, most users are uncertain in the mileage or the long time of battery replacement, the battery replacement is good, and the automation level is low.
Therefore, how to provide a better battery replacement scheme for an electric automobile for users is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides a method, a system and a device for replacing batteries of an electric vehicle based on the internet of things, which are used for solving the technical problems in the prior art.
In order to achieve the above object, the present invention provides the following technical solutions:
an electric automobile battery replacement method based on the Internet of things, based on an electric automobile supporting a battery replacement operation, comprises the following steps:
s1: acquiring battery state information, and analyzing the battery driving mileage state by using a fuzzy hierarchy;
s2: acquiring the geographic position of an electric automobile of a battery to be replaced, and traversing a battery replacement station in a preset range by using the geographic position of the electric automobile as a center through the Internet of things;
s3: and establishing a game model, obtaining the optimal battery replacement station position based on the game model, and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
Optionally, the analyzing the battery driving mileage state by using the fuzzy hierarchy includes:
based on the battery state information, analyzing the factors influencing the battery driving mileage, deriving the sub-factors influencing the battery driving mileage according to the factors influencing the battery driving mileage, and generating each sub-factor set;
determining the weight of each factor by adopting analytic hierarchy process, and establishing a weight coefficient matrix;
dividing the driving mileage state of the battery and determining the state level;
and (5) using an expert scoring method to give an index evaluation matrix, establishing a comprehensive target evaluation decision matrix, and solving a battery driving mileage state prediction result.
Optionally, based on the battery state information, analyzing the state factors affecting the battery driving mileage, deriving the state subfractions affecting the battery driving mileage according to the state factors affecting the battery, and generating the subfractions as follows:
in U 1 、U 2 …,U n Expressed as n different battery state factors; u (U) 11 …,U nm Representing corresponding m sub-factors.
Optionally, determining the weight of each factor by adopting analytic hierarchy process, and establishing a weight coefficient matrix as follows:
wherein w is a different weight coefficient.
Optionally, the battery driving mileage state is divided, and three state levels are determined:
V＝{v 1 ,v 2 ,v 3 }；
in the formula, v 1 The electric quantity of the battery is sufficient; v 2 Is the general electric quantity of the battery; v 3 The battery needs to be charged.
Optionally, an expert scoring method is used for giving an index evaluation matrix, and a comprehensive target evaluation decision matrix is established as follows:
wherein r is a scoring score for different experts;
C＝WR；
wherein, C represents the comprehensive prediction result of the battery driving mileage state.
Optionally, the method further comprises: obtaining a risk assessment score according to the battery state prediction result:
f＝CS T ；
in the formula, S is a score vector corresponding to the evaluation set.
Optionally, step S3, establishing a game model, obtaining an optimal battery replacement station position based on the game model and pushing the optimal battery replacement station position to the electric automobile user terminal to be replaced, including:
A＝{α 1 ,α 2 ,…α x }；
S＝{α|(α x )x∈N} x ；
G＝{N,S}；
wherein N is a main influence factor set participating in games; the method comprises the steps that A is a set of battery replacement stations in a preset range, S is a strategy set of site-selection game, and G is a game model;
and solving the game model to obtain the optimal battery replacement station position and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
An electric automobile battery replacement system based on thing networking, based on support trades electric automobile of electric operation, includes:
the battery state analysis module is used for acquiring battery state information and analyzing the battery driving mileage state by utilizing a fuzzy hierarchy;
the geographic position acquisition module acquires the geographic position of the electric automobile of the battery to be replaced, and traverses a battery replacement station in a preset range by taking the geographic position of the electric automobile as a center through the Internet of things;
and the pushing module is used for establishing a game model, obtaining the optimal battery replacement station position based on the game model and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
An electronic device comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes an electric vehicle battery replacement method based on the Internet of things when executing the computer program.
According to the technical scheme, compared with the prior art, the invention discloses and provides the method, the system and the equipment for replacing the battery of the electric automobile based on the Internet of things, the driving mileage state of the battery of the electric automobile is accurately known based on the Internet of things, when the battery needing to be charged is detected, nearby replacement stations are searched, and the optimal replacement station is selected to push the battery to a user for battery replacement. Therefore, the service life of the battery and the driving safety are ensured, the charging time is greatly saved, the higher automation level is realized, and high-quality driving service is provided for the user.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of the method of the present invention;
fig. 2 is a schematic diagram of a system structure according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a method, a system and equipment for replacing batteries of an electric vehicle based on the Internet of things, which belong to the technical field of battery replacement of the electric vehicle, and the method is based on the electric vehicle supporting the battery replacement operation and specifically comprises the following steps: s1: acquiring battery state information, and analyzing the battery driving mileage state by using a fuzzy hierarchy; s2: acquiring the geographic position of an electric automobile of a battery to be replaced, and traversing a battery replacement station in a preset range by using the geographic position of the electric automobile as a center through the Internet of things; s3: and establishing a game model, obtaining the optimal battery replacement station position based on the game model, and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced. The invention ensures the service life of the battery and the driving safety, greatly saves the charging time, realizes higher automation level and provides high-quality driving service for users.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the embodiment of the invention discloses an electric vehicle battery replacement method based on the internet of things, and the electric vehicle based on supporting battery replacement operation comprises the following steps:
s1: acquiring battery state information, and analyzing the battery driving mileage state by using a fuzzy hierarchy;
s2: acquiring the geographic position of an electric automobile of a battery to be replaced, and traversing a battery replacement station in a preset range by using the geographic position of the electric automobile as a center through the Internet of things;
s3: and establishing a game model, obtaining the optimal battery replacement station position based on the game model, and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
In one embodiment, the battery mileage state using fuzzy hierarchy analysis includes:
based on the battery state information, analyzing the factors influencing the battery driving mileage, deriving the sub-factors influencing the battery driving mileage according to the factors influencing the battery driving mileage, and generating each sub-factor set;
determining the weight of each factor by adopting analytic hierarchy process, and establishing a weight coefficient matrix;
dividing the driving mileage state of the battery and determining the state level;
and (5) using an expert scoring method to give an index evaluation matrix, establishing a comprehensive target evaluation decision matrix, and solving a battery driving mileage state prediction result.
In one embodiment, based on the battery state information, analyzing the factors influencing the battery driving mileage, deriving the sub-factors influencing the battery driving mileage according to the factors influencing the battery driving mileage, and generating the sub-factor sets as follows:
in U 1 、U 2 …,U n Expressed as n different battery state factors; u (U) 11 …,U nm Representing corresponding m sub-factors.
In one particular embodiment, the battery status information may include: depth of charge and discharge, current capacity of battery, battery temperature, and battery duration.
Specifically, the charge-discharge depth can be calculated by the following formula:
depth of charge and discharge (DOD) = (1-remaining amount/total amount) ×100%.
The total electric quantity is the fully full capacity of the battery, and the residual electric quantity is the electric quantity still remained in the current battery. For example, if the total capacity of one battery is 100Ah and the current charge is 20Ah, its depth of charge and discharge (DOD) is 80%.
When DOD exceeds a certain value, battery life may be affected. Battery manufacturers typically give a recommended DOD range to ensure optimal battery life.
Current capacity of battery: the current capacity of the battery is one of main parameters representing the health degree of the battery, and when the current capacity of the battery is lower than 80% of rated capacity, the aging and the performance degradation of the battery are more serious 1.
Depth of charge and discharge: the depth of charge and discharge has an effect on the health degree of the battery, the depth of charge and discharge is increased, the active substances in the battery are activated more, the electric quantity released by the battery is large, and the health degree of the battery is further remarkably attenuated by 1.
Temperature: temperature is a key factor affecting the life of the battery, and variations in the temperature of the battery may cause variations in parameters of the battery itself, such as an increase in internal resistance and a jitter 1 in the charge-discharge rate.
In addition, the battery mileage status is also affected by the charging mode, the charging frequency, the usage time, software and hardware, etc.
In a specific embodiment, the weight of each factor is determined by hierarchical analysis, and a weight coefficient matrix is established as follows:
wherein w is a different weight coefficient.
In one embodiment, battery mileage states are divided to determine three state levels:
V＝{v 1 ,v 2 ,v 3 }；
in the formula, v 1 The electric quantity of the battery is sufficient; v 2 Is the general electric quantity of the battery; v 3 The battery needs to be charged.
In a specific embodiment, an expert scoring method is used to give an index evaluation matrix, and a comprehensive target evaluation decision matrix is established as follows:
wherein r is a scoring score for different experts;
C＝WR；
wherein, C represents the comprehensive prediction result of the battery driving mileage state.
Specifically, the comprehensive prediction result is any result of sufficient battery power, general battery power or battery charging.
In a specific embodiment, the method further comprises: obtaining a risk assessment score according to the battery state prediction result:
f＝CS T ；
in the formula, S is a score vector corresponding to the evaluation set.
In a specific embodiment, step S3, a game model is established, and an optimal battery replacement station position is obtained based on the game model and pushed to an electric vehicle user terminal to be replaced, which includes:
A＝{α 1 ,α 2 ,…α x }；
S＝{α|(α x )x∈N} x ；
G＝{N,S}；
wherein N is a main influence factor set participating in games; the method comprises the steps that A is a set of battery replacement stations in a preset range, S is a strategy set of site-selection game, and G is a game model;
and solving the game model to obtain the optimal battery replacement station position and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
As shown in fig. 2, the embodiment of the invention also discloses an electric vehicle battery replacement system based on the internet of things, and an electric vehicle based on supporting battery replacement operation, comprising:
the battery state analysis module is used for acquiring battery state information and analyzing the battery driving mileage state by utilizing a fuzzy hierarchy;
the geographic position acquisition module acquires the geographic position of the electric automobile of the battery to be replaced, and traverses a battery replacement station in a preset range by taking the geographic position of the electric automobile as a center through the Internet of things;
and the pushing module is used for establishing a game model, obtaining the optimal battery replacement station position based on the game model and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
An electronic device comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of an electric vehicle battery replacement method based on the Internet of things when executing the computer program.
In particular, it will be understood by those skilled in the art that implementing all or part of the above-described methods of the embodiments may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be, but are not limited to, general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing based data processing logic, and the like.
For the system device disclosed in the embodiment, since the system device corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. An electric automobile battery replacement method based on the Internet of things and based on an electric automobile supporting a battery replacement operation is characterized by comprising the following steps:
s1: acquiring battery state information, and analyzing the battery driving mileage state by using a fuzzy hierarchy;
s2: acquiring the geographic position of an electric automobile of a battery to be replaced, and traversing a battery replacement station in a preset range by using the geographic position of the electric automobile as a center through the Internet of things;
s3: and establishing a game model, obtaining the optimal battery replacement station position based on the game model, and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
2. The method for replacing the battery of the electric vehicle based on the internet of things according to claim 1, wherein the analyzing the battery driving mileage state by using the fuzzy hierarchy includes:
based on the battery state information, analyzing the factors influencing the battery driving mileage, deriving the sub-factors influencing the battery driving mileage according to the factors influencing the battery driving mileage, and generating each sub-factor set;
determining the weight of each factor by adopting analytic hierarchy process, and establishing a weight coefficient matrix;
dividing the driving mileage state of the battery and determining the state level;
and (5) using an expert scoring method to give an index evaluation matrix, establishing a comprehensive target evaluation decision matrix, and solving a battery driving mileage state prediction result.
3. The method for replacing the battery of the electric vehicle based on the internet of things according to claim 2, wherein the method is characterized in that based on the battery state information, the battery driving mileage influencing state factors are analyzed, the battery driving mileage influencing state subfractions are derived according to the battery driving mileage influencing state factors, and the generation of the subfractions is as follows:
in U 1 、U 2 …,U n Expressed as n different battery state factors; u (U) 11 …,U nm Representing corresponding m subfactor。
4. The method for replacing the battery of the electric vehicle based on the internet of things according to claim 2, wherein the steps of determining the weight of each factor by using hierarchical analysis and establishing a weight coefficient matrix are as follows:
wherein w is a different weight coefficient.
5. The method for replacing the battery of the electric automobile based on the internet of things according to claim 2, wherein the battery driving mileage state is divided, and three state levels are determined:
V＝{v 1 ,v 2 ,v 3 }；
in the formula, v 1 The electric quantity of the battery is sufficient; v 2 Is the general electric quantity of the battery; v 3 The battery needs to be charged.
6. The method for replacing the battery of the electric automobile based on the internet of things according to claim 2, wherein the step of giving an index evaluation matrix by using an expert scoring method and establishing a comprehensive target evaluation decision matrix is as follows:
wherein r is a scoring score for different experts;
C＝WR；
wherein, C represents the comprehensive prediction result of the battery driving mileage state.
7. The method for replacing the battery of the electric automobile based on the internet of things according to claim 2, further comprising: obtaining a risk assessment score according to the battery state prediction result:
f＝CS T ；
in the formula, S is a score vector corresponding to the evaluation set.
8. The method for replacing the battery of the electric vehicle based on the internet of things according to claim 1, wherein the step S3 of establishing a game model, obtaining the optimal battery replacing station position based on the game model and pushing the optimal battery replacing station position to the electric vehicle user terminal to be replaced, comprises the following steps:
A＝{α 1 ,α 2 ,…α x ]；
S＝{α|(α x )x∈N} x ；
G＝{N,S}；
wherein N is a main influence factor set participating in games; the method comprises the steps that A is a set of battery replacement stations in a preset range, S is a strategy set of site-selection game, and G is a game model;
and solving the game model to obtain the optimal battery replacement station position and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
9. Electric automobile battery replacement system based on thing networking, based on support electric automobile who trades electric operation, its characterized in that includes:
the battery state analysis module is used for acquiring battery state information and analyzing the battery driving mileage state by utilizing a fuzzy hierarchy;
the geographic position acquisition module acquires the geographic position of the electric automobile of the battery to be replaced, and traverses a battery replacement station in a preset range by taking the geographic position of the electric automobile as a center through the Internet of things;
and the pushing module is used for establishing a game model, obtaining the optimal battery replacement station position based on the game model and pushing the optimal battery replacement station position to the electric automobile user terminal of the battery to be replaced.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the internet of things-based battery replacement method of an electric vehicle according to any one of claims 1 to 8 when executing the computer program.
CN202311302170.0A 2023-10-10 2023-10-10 Electric automobile battery replacement method, system and equipment based on Internet of things Active CN117429303B (en)

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