CN115214410B - Electric automobile electric energy online intelligent monitoring guide system based on big data analysis - Google Patents
Electric automobile electric energy online intelligent monitoring guide system based on big data analysis Download PDFInfo
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- CN115214410B CN115214410B CN202210729740.3A CN202210729740A CN115214410B CN 115214410 B CN115214410 B CN 115214410B CN 202210729740 A CN202210729740 A CN 202210729740A CN 115214410 B CN115214410 B CN 115214410B
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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
- B60L53/60—Monitoring or controlling charging stations
- B60L53/66—Data transfer between charging stations and vehicles
- B60L53/665—Methods related to measuring, billing or payment
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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
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/12—Recording operating variables ; Monitoring of operating variables
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Abstract
The invention discloses an electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis, which carries out real-time monitoring on battery core parameters and battery appearance parameters of an electric vehicle to be monitored, analyzes and obtains battery performance indexes of the electric vehicle to be monitored, and evaluates and processes the battery performance of the electric vehicle to be monitored in the running process according to the battery performance indexes of the electric vehicle to be monitored, thereby realizing comprehensive and comprehensive data analysis on the battery performance of the electric vehicle, improving the accuracy and reliability of the electric vehicle monitoring and guiding system.
Description
Technical Field
The invention relates to the field of electric automobile electric energy monitoring, in particular to an electric automobile electric energy online intelligent monitoring guiding system based on big data analysis.
Background
The large use of automobiles brings a series of problems of energy consumption, resource shortage, environmental pollution and the like, and the problems promote various large automobile companies to compete to develop various novel pollution-free environment-friendly automobiles. Electric vehicles have been rapidly developed as an important approach to solve the problems of resource shortage, environmental pollution, and the like.
The electric automobile brings convenience to people, but has hidden dangers in the aspects of batteries and endurance, such as poor battery performance and no effective charging scheme when the battery power is insufficient, so that the electric automobile electric energy monitoring and guiding device has important significance in monitoring and guiding electric energy of the electric automobile.
At present, to the monitoring guide of electric automobile electric energy among the prior art, mainly embody the position that provides available charging station when monitoring electric automobile battery current electric quantity and battery electric quantity not enough, this technique is practical, but has some drawbacks:
the battery can generate heat after being used for a long time, spontaneous combustion can be caused due to overhigh temperature, huge hidden dangers are brought to the life and property safety of electric automobile users, the current electric quantity of the electric automobile is only analyzed, and comprehensive data analysis is not carried out on the battery performance of the electric automobile, so that the accuracy and the reliability of the monitoring result of the electric automobile are reduced.
The charging system has the advantages that the charging system only provides the positions of the available charging stations when the electric quantity of the battery is insufficient, the available charging stations cannot be screened, factors such as the distance length and the required time of each charging station are not comprehensively considered, accordingly, the optimal charging scheme cannot be recommended for the electric automobile user, the intelligence and the flexibility of the electric automobile monitoring and guiding system are low, and the experience of the electric automobile user is greatly reduced.
Disclosure of Invention
Aiming at the problems, the invention provides an electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis, and the electric vehicle electric energy online intelligent monitoring and guiding system realizes the function of electric vehicle electric energy monitoring and guiding.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention provides an electric automobile electric energy online intelligent monitoring and guiding system based on big data analysis, which comprises:
the electric automobile database is used for storing the initial position and the initial battery electric quantity of the electric automobile to be monitored, and storing the battery temperature safety value and the battery unit distance power consumption of the electric automobile to be monitored;
the battery performance parameter acquisition module is used for acquiring battery performance parameters in the running process of the electric automobile to be monitored in real time, wherein the battery performance parameters comprise battery core parameters and battery appearance parameters;
the battery performance parameter analysis module is used for analyzing and processing battery performance parameters in the running process of the electric automobile to be monitored to obtain a battery performance index in the running process of the electric automobile to be monitored;
the battery performance evaluation processing module is used for evaluating the battery performance of the electric vehicle to be monitored in the running process through the battery performance index of the electric vehicle to be monitored in the running process and carrying out corresponding processing according to the evaluation result;
the charging demand judging module is used for judging the charging demand of the electric automobile to be monitored according to the current battery capacity of the electric automobile to be monitored and the current position of the electric automobile to be monitored, and if the electric automobile to be monitored has the charging demand, the charging scheme planning and analyzing module is executed;
the charging scheme planning and analyzing module is used for acquiring the destination position of the electric automobile to be monitored, and planning the charging scheme of the electric automobile to be monitored according to the destination position of the electric automobile to be monitored and the current position of the electric automobile to be monitored to obtain a recommended charging scheme of the electric automobile to be monitored;
the charging prompt module is used for carrying out corresponding prompt through a built-in display screen of the electric automobile to be monitored according to the recommended charging scheme of the electric automobile to be monitored.
On the basis of the above embodiment, the battery performance parameter acquiring module includes a battery core parameter acquiring unit and a battery appearance parameter acquiring unit, the battery core parameter acquiring unit is configured to acquire a battery core parameter of the electric vehicle to be monitored in real time, where the battery core parameter includes a temperature of each detection point on a surface of the battery, a noise around the battery, a current battery capacity, and a distance traveled, and the temperature of each detection point on the surface of the battery is recorded as R i I =1, 2.. N, the battery ambient noise is denoted as Z, the current battery power is denoted as Q, and the traveled distance is denoted as Δ S.
On the basis of the above embodiment, the battery appearance parameter acquiring unit is configured to acquire, in real time, battery appearance parameters of the electric vehicle to be monitored in a driving process, where the battery appearance parameters include a battery surface damage area, a battery surface scratch length, and a battery surface foreign matter area, the battery surface damage area is denoted as P, the battery surface scratch length is denoted as H, and the battery surface foreign matter area is denoted as Y.
On the basis of the above embodiment, the specific steps of analyzing and processing the battery performance parameters in the battery performance parameter analysis module during the driving process of the electric vehicle to be monitored to obtain the battery performance index are as follows:
D 1 the temperature R of each detection point on the surface of the battery in the running process of the electric automobile to be monitored i Substituting the battery ambient noise Z, the current battery electric quantity Q and the traveled distance Delta S of the electric automobile to be monitored into a formula in the traveling process of the electric automobile to be monitored
Obtaining a core parameter coincidence coefficient X of the electric automobile battery to be monitored, wherein R An Representing the safety value, Z, of the temperature of the electric vehicle battery to be monitored, stored in the electric vehicle database Threshold value Representing a preset ambient noise threshold value of the electric automobile battery to be monitored, f representing unit distance power consumption of the electric automobile battery to be monitored stored in an electric automobile database, and Q 0 Represents the initial battery capacity, mu, of the electric vehicle to be monitored stored in the electric vehicle database 1 、μ 2 、μ 3 Respectively representing preset weight factors of a battery temperature coefficient, a battery ambient noise coefficient and a battery power consumption coefficient, wherein e represents a natural constant, and n represents the number of detection points on the surface of the battery;
D 2 substituting the damaged area P of the battery surface, the scratch length H of the battery surface and the foreign matter area Y of the battery surface into a formula
Obtaining the appearance integrity coefficient W of the electric automobile battery to be monitored, wherein P Threshold(s) 、H Threshold(s) 、Y Threshold value Respectively a preset threshold value, lambda, of the surface damage area of the battery, the scratch length of the surface of the battery and the area of foreign matters on the surface of the battery 1 、λ 2 、λ 3 Weighting factors of a preset battery surface damage area, a preset battery surface scratch length and a preset battery surface foreign matter area are respectively set, and e represents a natural constant;
D 3 substituting the core parameter conformity coefficient X of the electric automobile to be monitored and the appearance integrity coefficient W of the electric automobile battery to be monitored into a formula sigma = eta 1 *X+η 2 * W is obtainedThe battery performance index sigma of the electric vehicle to be monitored, wherein eta 1 Correction factor, eta, representing a predetermined electric vehicle core parameter fit coefficient 2 And the correction factor represents a preset appearance integrity coefficient of the battery of the electric automobile.
On the basis of the embodiment, the specific steps of evaluating the battery performance of the electric vehicle to be monitored in the battery performance evaluation processing module during the driving process and performing corresponding processing according to the evaluation result are as follows:
the battery performance index of the electric automobile to be monitored is compared with a preset battery performance index standard value of the electric automobile, if the battery performance index of the electric automobile to be monitored is smaller than the preset battery performance index standard value of the electric automobile, the battery of the electric automobile to be monitored has problems, and early warning reminding is carried out through a built-in display screen of the electric automobile to be monitored.
On the basis of the above embodiment, the specific method for judging the charging requirement of the electric vehicle to be monitored in the charging requirement judging module is as follows:
acquiring a destination position of the electric automobile to be monitored by a GPS positioning technology, and acquiring a distance between the current position and the destination position of the electric automobile to be monitored according to the destination position, and recording the distance as S';
substituting the current battery capacity Q of the electric automobile to be monitored and the distance S' between the current position and the destination position of the electric automobile to be monitored into a formula
Obtaining the current charging demand index alpha of the electric automobile to be monitored, wherein f represents the unit distance power consumption Q of the electric automobile battery to be monitored stored in the electric automobile database Damage to The method comprises the steps of representing the loss electric quantity of a preset electric automobile battery to be monitored, and gamma representing a preset charging demand index compensation coefficient;
and comparing the current charging demand index of the electric automobile to be monitored with a preset charging demand index threshold, and if the current charging demand index of the electric automobile to be monitored is greater than the preset charging demand index threshold, indicating that the electric automobile to be monitored has a charging demand.
On the basis of the above embodiment, the specific steps of planning the charging scheme of the electric vehicle to be monitored in the charging scheme planning and analyzing module to obtain the recommended charging scheme of the electric vehicle to be monitored include:
F 1 taking the current position of the electric automobile to be monitored as the center of a circle and a preset distance as a radius to make a circle, recording the circle as a chargeable area corresponding to the electric automobile to be monitored, detecting the number of the chargeable power stations in the chargeable area corresponding to the electric automobile to be monitored by using a GPS technology, and executing F if the number of the chargeable power stations in the chargeable area corresponding to the electric automobile to be monitored is greater than zero 2 If not, the recommended charging scheme of the electric automobile to be monitored is a call reinforcement scheme;
F 2 : the method comprises the steps of obtaining the position of each charging station in a chargeable area corresponding to an electric vehicle to be monitored, classifying each charging station in the chargeable area corresponding to the electric vehicle to be monitored according to a forward route set by the electric vehicle to be monitored, dividing each charging station in the chargeable area corresponding to the electric vehicle to be monitored into each forward charging station and each detour charging station, and numbering each forward charging station in the chargeable area corresponding to the electric vehicle to be monitored into 1,2, a.
F 3 : acquiring the arrival point corresponding to the forward route set by each forward charging station to the electric automobile to be monitored, recording the arrival point as the arrival point of each forward charging station, acquiring the optimal distance between each forward charging station and the corresponding arrival point, and recording the optimal distance between each forward charging station and the corresponding arrival point as S j Acquiring the distance between the current position of the electric automobile to be monitored and the arrival point position of each on-road charging station, and recording the distance as L j J represents the number of the jth forward charging station;
by the formula l 0 ＝min{L 1 +S 1 ,L 2 +S 2 ,...,L j +S j ,...,L m +S m Obtaining the shortest path between the current position of the electric automobile to be monitored and each on-road charging station, recording the shortest path as the ideal on-road charging station path of the electric automobile to be monitored, and obtaining the ideal on-road corresponding to the ideal on-road charging station path of the electric automobile to be monitoredA charging station travel route;
F 4 : similarly, according to the ideal forward path charging station path analysis formula of the electric automobile to be monitored, the ideal detour charging station path of the electric automobile to be monitored can be obtained and recorded as l 1 Acquiring an ideal detour charging station driving route corresponding to the ideal detour charging station distance of the electric automobile to be monitored;
F 5 : comparing the ideal forward charging station with the ideal bypass charging station, wherein the specific method is that the ideal forward charging station route l of the electric automobile to be monitored 0 And the ideal detour charging station distance l of the electric automobile to be monitored 1 Substitution formula
Obtaining the ideal charging station recommendation coefficient of the electric vehicle to be monitored, wherein zeta 0 And ζ 1 Weight factors, L, for the respectively predetermined ideal on-road and off-road charging station routes Is provided with And indicating a preset route, if the recommended coefficient of the ideal charging station of the electric automobile to be monitored is smaller than a preset recommended coefficient threshold value of the ideal charging station, determining that the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal forward path charging station, and otherwise, determining that the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal detour charging station.
On the basis of the above embodiment, the method for obtaining the optimal distance between each forward charging station and its corresponding arrival point includes:
acquiring each path between each forward charging station and a corresponding arrival point thereof through a GPS positioning technology, counting each path between each forward charging station and the corresponding arrival point thereof, and numbering each path between each forward charging station and the corresponding arrival point thereof in sequence according to a preset sequence to be 1,2,. Once, k,. Once, t;
obtaining the distance of each path between each forward charging station and the corresponding arrival point, and recording the distance as S " jk J represents the number of the jth off-road charging station, j =1, 2.. The m, k represents the number of the kth path, k =1, 2.. The t, the pre-detection of each path between each off-road charging station and its corresponding arrival point is obtainedEstimate the time required, let it be T j ” k ；
By the formula
Obtaining the path coefficient tau of each path between each forward charging station and the corresponding arrival point jk In which beta is 1 And beta 2 Respectively representing the path weight factor and the time weight factor of the path between the preset forward charging station and the corresponding arrival point, screening out the path of the minimum path coefficient of each path between each forward charging station and the corresponding arrival point, recording the path as the appointed path of each forward charging station, and recording the path of the appointed path of each forward charging station as the optimal path between each forward charging station and the corresponding arrival point.
On the basis of the embodiment, the specific method for performing corresponding prompt through the built-in display screen of the electric vehicle to be monitored in the charging prompt module according to the recommended charging scheme of the electric vehicle to be monitored comprises the following steps:
if the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal off-road charging station, displaying an ideal off-road charging station driving route corresponding to the ideal off-road charging station route on an internal display screen of the electric automobile to be monitored;
if the recommended charging scheme of the electric vehicle to be monitored is a scheme for going to an ideal detour charging station, displaying a driving route of the ideal detour charging station corresponding to the ideal detour charging station on an internal display screen of the electric vehicle to be monitored;
and if the recommended charging scheme of the electric automobile to be monitored is a call-aid scheme, displaying an early warning prompt by a built-in display screen of the electric automobile to be monitored.
Compared with the prior art, the electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis has the following beneficial effects:
according to the electric vehicle electric energy online intelligent monitoring guide system based on big data analysis, the battery surface temperature, the battery surrounding noise and the battery electric quantity of an electric vehicle to be monitored are monitored in real time, the core parameter conformity coefficient of the electric vehicle battery to be monitored is obtained, the damaged area, the scratch length and the foreign matter area of the surface of the electric vehicle battery to be monitored are monitored, the appearance integrity coefficient of the electric vehicle battery to be monitored is obtained, the electric vehicle battery performance index to be monitored is comprehensively obtained, the battery performance of the electric vehicle to be monitored in the running process is evaluated according to the electric vehicle battery performance index to be monitored, corresponding processing is carried out, comprehensive and comprehensive data analysis of the electric vehicle battery performance is realized, and the accuracy and the reliability of the electric vehicle monitoring guide system are improved.
According to the electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis, whether the electric vehicle to be monitored has a charging requirement is judged by acquiring the current position of the electric vehicle to be monitored and the current battery capacity, the positions of the charging stations in the chargeable area of the electric vehicle to be monitored are acquired under the charging requirement of the electric vehicle to be monitored, the distance from the electric vehicle to be monitored to each charging station and the required time are integrated, an ideal charging station and a corresponding path are screened, a recommended charging scheme of the electric vehicle to be monitored is obtained, corresponding display is carried out, the intelligence and flexibility of the electric vehicle monitoring and guiding system are greatly improved, and the experience of users using the electric vehicle is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a system module connection diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention provides an electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis, which includes an electric vehicle database, a battery performance parameter obtaining module, a battery performance parameter analyzing module, a battery performance evaluation processing module, a charging demand judging module, a charging scheme planning and analyzing module, and a charging prompting module.
The battery performance parameter analysis module is respectively connected with the battery performance parameter acquisition module and the battery performance evaluation processing module, the charging scheme planning analysis module is respectively connected with the charging demand judgment module and the charging prompt module, and the electric vehicle database is respectively connected with the battery performance parameter analysis module and the charging demand judgment module.
The electric automobile database is used for storing the initial position and the initial battery electric quantity of the electric automobile to be monitored, and storing the battery temperature safety value and the battery unit distance power consumption of the electric automobile to be monitored.
The battery performance parameter acquisition module is used for acquiring battery performance parameters in the running process of the electric automobile to be monitored in real time, wherein the battery performance parameters comprise battery core parameters and battery appearance parameters.
Further, the battery performance parameter acquisition module comprises a battery core parameter acquisition unit and a battery appearance parameter acquisition unit, the battery core parameter acquisition unit is used for acquiring battery core parameters in the running process of the electric vehicle to be monitored in real time, the battery core parameters comprise the temperature of each detection point on the surface of the battery, the noise around the battery, the current battery electric quantity and the running distance, and the temperature of each detection point on the surface of the battery is recorded as R i I =1, 2., n, the battery ambient noise is denoted as Z, the current battery charge is denoted as Q, and the traveled distance is denoted as Δ S.
As a preferred scheme, the battery core parameter acquiring unit acquires battery core parameters in the driving process of the electric vehicle to be monitored, and the method specifically comprises the following steps:
arranging all detection points on the surface of the electric automobile battery to be monitored according to a preset detection point arrangement mode, sequentially numbering the detection points on the surface of the electric automobile battery to be monitored according to a preset sequence, wherein the number of the detection points is 1,2, a.
Monitoring the noise around the battery in the running process of the electric automobile to be monitored by a built-in noise detector of the electric automobile to be monitored to obtain the noise around the battery in the running process of the electric automobile to be monitored;
obtaining the current battery electric quantity of the electric automobile to be monitored through the intelligent central control platform of the electric automobile to be monitored;
the current position of the electric automobile to be monitored is obtained through a GPS positioning technology, and the distance between the current position of the electric automobile to be monitored and the corresponding initial position of the electric automobile to be monitored is obtained according to the current position of the electric automobile to be monitored.
Furthermore, the battery appearance parameter acquiring unit is used for acquiring the battery appearance parameters of the electric vehicle to be monitored in the driving process in real time, wherein the battery appearance parameters comprise a battery surface damage area, a battery surface scratch length and a battery surface foreign matter area, the battery surface damage area is recorded as P, the battery surface scratch length is recorded as H, and the battery surface foreign matter area is recorded as Y.
As a preferred scheme, the battery appearance parameter acquiring unit acquires the battery appearance parameters of the electric vehicle to be monitored in the driving process, and the specific method comprises the following steps:
the method comprises the steps of scanning a battery of the electric automobile to be monitored through an X-ray detector arranged in the electric automobile to be monitored to obtain a gray image of the surface of the battery in the running process of the electric automobile to be monitored, and obtaining the damaged area of the surface of the battery, the scratch length of the surface of the battery and the foreign matter area of the surface of the battery in the running process of the electric automobile to be monitored according to the gray image of the surface of the battery in the running process of the electric automobile to be monitored.
The battery performance parameter analysis module is used for analyzing and processing battery performance parameters in the running process of the electric automobile to be monitored to obtain a battery performance index in the running process of the electric automobile to be monitored.
Further, the battery performance parameter analysis module analyzes and processes the battery performance parameters of the electric vehicle to be monitored in the running process to obtain the battery performance index, and the specific steps of the battery performance index analysis module are as follows:
D 1 the temperature R of each detection point on the surface of the battery in the running process of the electric automobile to be monitored i Substituting the battery ambient noise Z, the current battery electric quantity Q and the traveled distance Delta S of the electric automobile to be monitored into a formula in the traveling process of the electric automobile to be monitored
Obtaining a core parameter coincidence coefficient X of the electric automobile battery to be monitored, wherein R An Representing a safety value Z of the temperature of the battery of the electric vehicle to be monitored, stored in the electric vehicle database Threshold(s) Representing a preset ambient noise threshold value of the electric automobile battery to be monitored, f representing unit distance power consumption of the electric automobile battery to be monitored stored in an electric automobile database, and Q 0 Represents the initial battery capacity, mu, of the electric vehicle to be monitored stored in the electric vehicle database 1 、μ 2 、μ 3 Respectively representing preset weight factors of a battery temperature coefficient, a battery ambient noise coefficient and a battery power consumption coefficient, wherein e represents a natural constant, and n represents the number of detection points on the surface of the battery;
D 2 substituting the damaged area P of the battery surface, the scratch length H of the battery surface and the foreign matter area Y of the battery surface into a formula
Obtaining the appearance integrity coefficient W of the electric automobile battery to be monitored, wherein P Threshold(s) 、H Threshold(s) 、Y Threshold value Respectively a preset threshold value, lambda, of the surface damage area of the battery, the scratch length of the surface of the battery and the area of foreign matters on the surface of the battery 1 、λ 2 、λ 3 Weighting factors of a preset battery surface damage area, a preset battery surface scratch length and a preset battery surface foreign matter area are respectively set, and e represents a natural constant;
D 3 substituting the core parameter conformity coefficient X of the electric automobile to be monitored and the appearance integrity coefficient W of the electric automobile battery to be monitored into a formula sigma = eta 1 *X+η 2 * W obtaining the performance index sigma of the electric automobile battery to be monitored, wherein eta 1 Correction factor, eta, representing a predetermined electric vehicle core parameter conformity factor 2 And the correction factor represents a preset battery appearance integrity coefficient of the electric automobile.
The battery performance evaluation processing module is used for evaluating the battery performance of the electric vehicle to be monitored in the running process through the battery performance index of the electric vehicle to be monitored in the running process, and carrying out corresponding processing according to the evaluation result.
Further, the specific steps of evaluating the battery performance of the electric vehicle to be monitored in the running process in the battery performance evaluation processing module and performing corresponding processing according to the evaluation result are as follows:
the battery performance index of the electric automobile to be monitored is compared with a preset battery performance index standard value of the electric automobile, if the battery performance index of the electric automobile to be monitored is smaller than the preset battery performance index standard value of the electric automobile, the battery of the electric automobile to be monitored has problems, and early warning reminding is carried out through a built-in display screen of the electric automobile to be monitored.
The method comprises the steps of monitoring the surface temperature of the battery of the electric automobile to be monitored, the noise around the battery and the electric quantity of the battery in real time to obtain a core parameter conformity coefficient of the battery of the electric automobile to be monitored, monitoring the damage area, the scratch length and the foreign matter area of the surface of the battery of the electric automobile to be monitored to obtain an appearance integrity coefficient of the battery of the electric automobile to be monitored, comprehensively obtaining a performance index of the battery of the electric automobile to be monitored, evaluating the performance of the battery of the electric automobile to be monitored in the running process according to the performance index of the battery of the electric automobile to be monitored, and carrying out corresponding processing, so that the comprehensive and comprehensive data analysis of the performance of the battery of the electric automobile is realized, and the accuracy and the reliability of a monitoring and guiding system of the electric automobile are improved.
The charging demand judging module is used for judging the charging demand of the electric automobile to be monitored according to the current battery capacity of the electric automobile to be monitored and the current position of the electric automobile to be monitored, and if the electric automobile to be monitored has the charging demand, the charging scheme planning and analyzing module is executed.
Further, the specific method for judging the charging requirement of the electric vehicle to be monitored in the charging requirement judging module is as follows:
acquiring a destination position of the electric automobile to be monitored by a GPS positioning technology, acquiring a distance between the current position and the destination position of the electric automobile to be monitored according to the destination position, and recording the distance as S';
substituting the current battery capacity Q of the electric automobile to be monitored and the distance S' between the current position and the destination position of the electric automobile to be monitored into a formula
Obtaining the current charging demand index alpha of the electric automobile to be monitored, wherein f represents the unit distance power consumption Q of the electric automobile battery to be monitored stored in the electric automobile database Decrease in the thickness of the steel The method comprises the steps of representing the loss electric quantity of a preset electric vehicle battery to be monitored, and representing a preset charging demand index compensation coefficient by gamma;
and comparing the current charging demand index of the electric automobile to be monitored with a preset charging demand index threshold, and if the current charging demand index of the electric automobile to be monitored is greater than the preset charging demand index threshold, indicating that the electric automobile to be monitored has a charging demand.
The charging scheme planning and analyzing module is used for acquiring a destination position of the electric automobile to be monitored, and planning a charging scheme of the electric automobile to be monitored according to the destination position of the electric automobile to be monitored and the current position of the electric automobile to be monitored to obtain a recommended charging scheme of the electric automobile to be monitored;
further, the charging scheme planning and analyzing module plans the charging scheme of the electric vehicle to be monitored, and the specific steps of obtaining the recommended charging scheme of the electric vehicle to be monitored include:
F 1 taking the current position of the electric automobile to be monitored as the center of a circle and a preset distance as a radius to make a circle, recording the circle as a chargeable area corresponding to the electric automobile to be monitored, detecting the number of the chargeable power stations in the chargeable area corresponding to the electric automobile to be monitored by using a GPS technology, and executing F if the number of the chargeable power stations in the chargeable area corresponding to the electric automobile to be monitored is greater than zero 2 If not, the recommended charging scheme of the electric automobile to be monitored is a call reinforcement scheme;
F 2 : the method comprises the steps of obtaining the position of each charging station in a chargeable area corresponding to an electric vehicle to be monitored, classifying each charging station in the chargeable area corresponding to the electric vehicle to be monitored according to a forward route set by the electric vehicle to be monitored, dividing each charging station in the chargeable area corresponding to the electric vehicle to be monitored into each forward charging station and each detour charging station, and numbering each forward charging station in the chargeable area corresponding to the electric vehicle to be monitored into 1,2, a.
F 3 : acquiring the arrival point corresponding to the forward route set by each forward charging station to the electric automobile to be monitored, recording the arrival point as the arrival point of each forward charging station, acquiring the optimal distance between each forward charging station and the corresponding arrival point, and recording the optimal distance between each forward charging station and the corresponding arrival point as S j Acquiring the distance between the current position of the electric automobile to be monitored and the arrival point position of each on-road charging station, and recording the distance as L j J represents the number of the jth forward charging station;
by the formula l 0 ＝min{L 1 +S 1 ,L 2 +S 2 ,...,L j +S j ,...,L m +S m Obtaining the shortest distance between the current position of the electric automobile to be monitored and each on-road charging station, recording the shortest distance as the ideal on-road charging station distance of the electric automobile to be monitored, and obtaining an ideal on-road charging station driving route corresponding to the ideal on-road charging station distance of the electric automobile to be detected;
F 4 : similarly, according to the route analysis formula of the ideal forward charging station of the electric automobile to be monitored, the route analysis formula canObtaining the ideal detour charging station distance of the electric automobile to be monitored, and recording the ideal detour charging station distance as l 1 Acquiring an ideal detour charging station driving route corresponding to the ideal detour charging station distance of the electric automobile to be monitored;
F 5 : comparing the ideal forward charging station with the ideal bypass charging station, wherein the specific method is that the ideal forward charging station route l of the electric automobile to be monitored 0 And the ideal detour charging station distance l of the electric automobile to be monitored 1 Substituting into formula
Obtaining the ideal charging station recommendation coefficient of the electric vehicle to be monitored, wherein zeta 0 And ζ 1 Weight factors, L, for the respectively predetermined ideal forward and detour charging station routes Is provided with And indicating a preset route, if the recommended coefficient of the ideal charging station of the electric automobile to be monitored is smaller than a preset recommended coefficient threshold value of the ideal charging station, determining that the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal forward path charging station, and otherwise, determining that the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal detour charging station.
As a preferred scheme, the method for classifying each charging station in the chargeable area corresponding to the electric vehicle to be monitored according to the forward route set by the electric vehicle to be monitored comprises the following steps:
the method comprises the steps of obtaining the current position of an electric vehicle to be monitored and the destination position of the electric vehicle to be monitored, further obtaining a directed line segment pointing to the destination position of the electric vehicle to be monitored from the current position of the electric vehicle to be monitored, recording the directed line segment as a destination pointing line of the electric vehicle to be monitored, obtaining a directed line segment pointing to the position of each charging station in a chargeable area corresponding to the current position of the electric vehicle to be monitored, recording the directed line segment as a pointing line of each charging station in the chargeable area, obtaining an included angle between the destination pointing line of the electric vehicle to be monitored and the pointing line of each charging station in the chargeable area, recording the charging station corresponding to the pointing line of each charging station in the chargeable area with the included angle smaller than a preset included angle threshold value as each direct-route charging station, and on the contrary, recording the directed line segment as each route charging station.
Furthermore, the method for obtaining the optimal distance between each on-road charging station and the corresponding arrival point comprises the following steps:
acquiring each path between each forward charging station and a corresponding arrival point thereof through a GPS positioning technology, counting each path between each forward charging station and the corresponding arrival point thereof, and numbering each path between each forward charging station and the corresponding arrival point thereof in sequence according to a preset sequence to be 1,2,. Once, k,. Once, t;
obtaining the distance of each path between each forward charging station and the corresponding arrival point, and recording the distance as S " jk J represents the number of the jth on-road charging station, j =1, 2.. The m, k represents the number of the kth path, k =1, 2.. The T, the estimated required time of each path between each on-road charging station and the corresponding arrival point is obtained and is recorded as T' jk ；
By the formula
Obtaining the path coefficient tau of each path between each forward charging station and the corresponding arrival point jk Wherein beta is 1 And beta 2 Respectively representing the path weight factor and the time weight factor of the path between the preset forward charging station and the corresponding arrival point, screening out the path of the minimum path coefficient of each path between each forward charging station and the corresponding arrival point, recording the path as the appointed path of each forward charging station, and recording the path of the appointed path of each forward charging station as the optimal path between each forward charging station and the corresponding arrival point.
The charging prompt module is used for carrying out corresponding prompt through a built-in display screen of the electric automobile to be monitored according to the recommended charging scheme of the electric automobile to be monitored.
Further, according to the recommended charging scheme of the electric vehicle to be monitored, the charging prompt module performs corresponding prompting through the built-in display screen of the electric vehicle to be monitored, and the specific method comprises the following steps:
if the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal off-road charging station, displaying an ideal off-road charging station driving route corresponding to the ideal off-road charging station route on an internal display screen of the electric automobile to be monitored;
if the recommended charging scheme of the electric vehicle to be monitored is a scheme for going to an ideal detour charging station, displaying a driving route of the ideal detour charging station corresponding to the ideal detour charging station on an internal display screen of the electric vehicle to be monitored;
and if the recommended charging scheme of the electric automobile to be monitored is a call-aid scheme, displaying an early warning prompt by a built-in display screen of the electric automobile to be monitored.
It should be noted that, the present invention determines whether the electric vehicle to be monitored has a charging demand by acquiring the current position of the electric vehicle to be monitored and the current battery power, acquires the position of each charging station in the chargeable area of the electric vehicle to be monitored when the electric vehicle to be monitored has a charging demand, synthesizes the distance from the electric vehicle to be monitored to each charging station and the required time, screens an ideal charging station and a corresponding path, obtains a recommended charging scheme of the electric vehicle to be monitored, and performs corresponding display, thereby greatly improving the intelligence and flexibility of the electric vehicle monitoring guidance system, and further improving the experience of the user using the electric vehicle.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (8)
1. The utility model provides an electric automobile electric energy on-line intelligent monitoring bootstrap system based on big data analysis which characterized in that includes:
the electric automobile database is used for storing the initial position and the initial battery electric quantity of the electric automobile to be monitored, and storing the battery temperature safety value and the battery unit distance power consumption of the electric automobile to be monitored;
the battery performance parameter acquisition module is used for acquiring battery performance parameters in the running process of the electric automobile to be monitored in real time, wherein the battery performance parameters comprise battery core parameters and battery appearance parameters;
the battery performance parameter analysis module is used for analyzing and processing battery performance parameters in the running process of the electric automobile to be monitored to obtain a battery performance index in the running process of the electric automobile to be monitored;
the battery performance evaluation processing module is used for evaluating the battery performance of the electric vehicle to be monitored in the running process through the battery performance index of the electric vehicle to be monitored in the running process and carrying out corresponding processing according to the evaluation result;
the charging demand judging module is used for judging the charging demand of the electric automobile to be monitored according to the current battery capacity of the electric automobile to be monitored and the current position of the electric automobile to be monitored, and if the electric automobile to be monitored has the charging demand, the charging scheme planning and analyzing module is executed;
the charging scheme planning and analyzing module is used for acquiring the destination position of the electric automobile to be monitored, and planning the charging scheme of the electric automobile to be monitored according to the destination position of the electric automobile to be monitored and the current position of the electric automobile to be monitored to obtain a recommended charging scheme of the electric automobile to be monitored;
the charging prompting module is used for carrying out corresponding prompting through a built-in display screen of the electric automobile to be monitored according to a recommended charging scheme of the electric automobile to be monitored;
the battery performance parameter analysis module analyzes and processes battery performance parameters in the running process of the electric automobile to be monitored, and the specific steps of obtaining the battery performance index are as follows:
D 1 the temperature R of each detection point on the surface of the battery in the running process of the electric automobile to be monitored i Substituting the battery ambient noise Z, the current battery electric quantity Q and the traveled distance Delta S of the electric automobile to be monitored into a formula in the traveling process of the electric automobile to be monitored
Obtaining a core parameter coincidence coefficient X of the electric automobile battery to be monitored, wherein R An Representing the safety value, Z, of the temperature of the electric vehicle battery to be monitored, stored in the electric vehicle database Threshold(s) Representing a preset ambient noise threshold value of the electric automobile battery to be monitored, f representing unit distance power consumption of the electric automobile battery to be monitored stored in an electric automobile database, and Q 0 Represents the initial battery capacity, mu, of the electric vehicle to be monitored stored in the electric vehicle database 1 、μ 2 、μ 3 Weighting factors respectively representing preset battery temperature coefficients, battery surrounding noise coefficients and battery power consumption coefficients, wherein e represents a natural constant, and n represents the number of battery surface detection points;
D 2 substituting the damaged area P of the battery surface, the scratch length H of the battery surface and the foreign matter area Y of the battery surface into a formula
Obtaining the appearance integrity coefficient W of the electric automobile battery to be monitored, wherein P Threshold(s) 、H Threshold(s) 、Y Threshold(s) Respectively is a preset threshold value, lambda, of the surface damage area of the battery, the scratch length of the surface of the battery and the area of foreign matters on the surface of the battery 1 、λ 2 、λ 3 Weighting factors of a preset battery surface damage area, a preset battery surface scratch length and a preset battery surface foreign matter area are respectively set, and e represents a natural constant;
D 3 substituting a core parameter coincidence coefficient X of the electric automobile to be monitored and an appearance integrity coefficient W of the electric automobile battery to be monitored into a formula sigma = eta 1 *X+η 2 * W obtaining the performance index sigma of the electric automobile battery to be monitored, wherein eta 1 Correction factor, eta, representing a predetermined electric vehicle core parameter conformity factor 2 And the correction factor represents a preset battery appearance integrity coefficient of the electric automobile.
2. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis as claimed in claim 1, characterized in that: the battery performance parameter acquisition module comprises a battery core parameter acquisition unit and a battery appearance parameter acquisition unit, wherein the battery core parameter acquisition unit is used for acquiring battery core parameters in the running process of the electric automobile to be monitored in real timeCounting, wherein the core parameters of the battery comprise the temperature of each detection point on the surface of the battery, the noise around the battery, the current battery electric quantity and the traveled distance, and recording the temperature of each detection point on the surface of the battery as R i I =1, 2.. N, the battery ambient noise is denoted as Z, the current battery power is denoted as Q, and the traveled distance is denoted as Δ S.
3. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis according to claim 2, characterized in that: the battery appearance parameter acquisition unit is used for acquiring the battery appearance parameters of the electric automobile to be monitored in the running process in real time, wherein the battery appearance parameters comprise a battery surface damage area, a battery surface scratch length and a battery surface foreign matter area, the battery surface damage area is recorded as P, the battery surface scratch length is recorded as H, and the battery surface foreign matter area is recorded as Y.
4. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis according to claim 1, characterized in that: the battery performance evaluation processing module evaluates the battery performance of the electric automobile to be monitored in the running process, and the specific steps of carrying out corresponding processing according to an evaluation result are as follows:
the battery performance index of the electric automobile to be monitored is compared with a preset battery performance index standard value of the electric automobile, if the battery performance index of the electric automobile to be monitored is smaller than the preset battery performance index standard value of the electric automobile, the battery of the electric automobile to be monitored has problems, and early warning reminding is carried out through a built-in display screen of the electric automobile to be monitored.
5. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis as claimed in claim 1, characterized in that: the specific method for judging the charging requirement of the electric automobile to be monitored in the charging requirement judging module comprises the following steps:
acquiring a destination position of the electric automobile to be monitored by a GPS positioning technology, and acquiring a distance between the current position and the destination position of the electric automobile to be monitored according to the destination position, and recording the distance as S';
substituting the current battery capacity Q of the electric automobile to be monitored and the distance S' between the current position and the destination position of the electric automobile to be monitored into a formula
Obtaining the current charging demand index alpha of the electric automobile to be monitored, wherein f represents the unit distance power consumption Q of the electric automobile battery to be monitored stored in the electric automobile database Decrease in the thickness of the steel The method comprises the steps of representing the loss electric quantity of a preset electric vehicle battery to be monitored, and representing a preset charging demand index compensation coefficient by gamma;
and comparing the current charging demand index of the electric automobile to be monitored with a preset charging demand index threshold, and if the current charging demand index of the electric automobile to be monitored is greater than the preset charging demand index threshold, indicating that the electric automobile to be monitored has a charging demand.
6. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis as claimed in claim 1, characterized in that: the method comprises the following specific steps of planning a charging scheme of the electric vehicle to be monitored in the charging scheme planning and analyzing module to obtain a recommended charging scheme of the electric vehicle to be monitored:
F 1 taking the current position of the electric automobile to be monitored as the center of a circle and a preset distance as a radius to make a circle, recording the circle as a chargeable area corresponding to the electric automobile to be monitored, detecting the number of the chargeable power stations in the chargeable area corresponding to the electric automobile to be monitored by using a GPS technology, and executing F if the number of the chargeable power stations in the chargeable area corresponding to the electric automobile to be monitored is greater than zero 2 If not, the recommended charging scheme of the electric automobile to be monitored is a call reinforcement scheme;
F 2 : acquiring the position of each charging station in the chargeable area corresponding to the electric automobile to be monitored, classifying each charging station in the chargeable area corresponding to the electric automobile to be monitored according to the set forward route of the electric automobile to be monitored, and dividing each charging station in the chargeable area corresponding to the electric automobile to be monitored into each forward path chargingThe system comprises a power station and each detour charging station, wherein each direct-road charging station in a chargeable area corresponding to an electric vehicle to be monitored is numbered as 1,2, a.
F 3 : acquiring the arrival point corresponding to the forward route set by each forward charging station to the electric automobile to be monitored, recording the arrival point as the arrival point of each forward charging station, acquiring the optimal distance between each forward charging station and the corresponding arrival point, and recording the optimal distance between each forward charging station and the corresponding arrival point as S j Acquiring the distance between the current position of the electric automobile to be monitored and the arrival point position of each on-road charging station, and recording the distance as L j J represents the number of the jth off-road charging station;
by the formula l 0 ＝min{L 1 +S 1 ,L 2 +S 2 ,...,L j +S j ,...,L m +S m Obtaining the shortest distance between the current position of the electric automobile to be monitored and each on-road charging station, recording the shortest distance as the ideal on-road charging station distance of the electric automobile to be monitored, and obtaining an ideal on-road charging station driving route corresponding to the ideal on-road charging station distance of the electric automobile to be detected;
F 4 : similarly, according to the ideal forward path charging station path analysis formula of the electric automobile to be monitored, the ideal detour charging station path of the electric automobile to be monitored can be obtained and recorded as l 1 Acquiring an ideal detour charging station driving route corresponding to the ideal detour charging station distance of the electric automobile to be monitored;
F 5 : comparing the ideal on-road charging station with the ideal detour charging station, wherein the specific method is that the ideal on-road charging station distance l of the electric automobile to be monitored 0 And the ideal detour charging station distance l of the electric automobile to be monitored 1 Substituting into formula
Obtaining the recommendation coefficient of the ideal charging station of the electric vehicle to be monitored, wherein zeta 0 And ζ 1 Weight factors, L, for the respectively predetermined ideal forward and detour charging station routes Is provided with The distance is indicated to be a preset distance,if the recommended coefficient of the ideal charging station of the electric vehicle to be monitored is smaller than the preset recommended coefficient threshold value of the ideal charging station, the recommended charging scheme of the electric vehicle to be monitored is a scheme for going to an ideal forward-road charging station, and on the contrary, the recommended charging scheme of the electric vehicle to be monitored is a scheme for going to an ideal detour charging station.
7. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis according to claim 6, characterized in that: the method for acquiring the optimal distance between each forward charging station and the corresponding arrival point comprises the following steps:
acquiring each path between each forward charging station and a corresponding arrival point thereof through a GPS positioning technology, counting each path between each forward charging station and the corresponding arrival point thereof, and numbering each path between each forward charging station and the corresponding arrival point thereof in sequence according to a preset sequence to be 1,2,. Once, k,. Once, t;
obtaining the path of each path between each forward charging station and the corresponding arrival point, and marking the path as S ″ jk J represents the number of the jth on-road charging station, j =1, 2.. The m, k represents the number of the kth path, k =1, 2.. The T, the estimated required time of each path between each on-road charging station and the corresponding arrival point is obtained and is marked as T ″ jk ；
By the formula
Obtaining the path coefficient tau of each path between each forward charging station and the corresponding arrival point jk Wherein beta is 1 And beta 2 Respectively representing a path weight factor and a time weight factor of a path between a preset on-road charging station and a corresponding arrival point, screening out the path of the minimum path coefficient of each path between each on-road charging station and the corresponding arrival point, recording the path as an appointed path of each on-road charging station, and recording the path of the appointed path of each on-road charging station as the optimal path between each on-road charging station and the corresponding arrival point.
8. The electric vehicle electric energy online intelligent monitoring and guiding system based on big data analysis as claimed in claim 1, characterized in that: the specific method for carrying out corresponding prompt through the built-in display screen of the electric automobile to be monitored in the charging prompt module according to the recommended charging scheme of the electric automobile to be monitored comprises the following steps:
if the recommended charging scheme of the electric automobile to be monitored is a scheme for going to an ideal off-road charging station, displaying an ideal off-road charging station driving route corresponding to the ideal off-road charging station route on an internal display screen of the electric automobile to be monitored;
if the recommended charging scheme of the electric vehicle to be monitored is a scheme for going to an ideal detour charging station, displaying a driving route of the ideal detour charging station corresponding to the ideal detour charging station on an internal display screen of the electric vehicle to be monitored;
and if the recommended charging scheme of the electric automobile to be monitored is a call enhancement scheme, displaying an early warning prompt by a built-in display screen of the electric automobile to be monitored.
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