CN116039576B - Intelligent replacement system for new energy automobile battery - Google Patents
Intelligent replacement system for new energy automobile battery Download PDFInfo
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- CN116039576B CN116039576B CN202310283761.1A CN202310283761A CN116039576B CN 116039576 B CN116039576 B CN 116039576B CN 202310283761 A CN202310283761 A CN 202310283761A CN 116039576 B CN116039576 B CN 116039576B
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- 238000011156 evaluation Methods 0.000 claims abstract description 9
- 238000001514 detection method Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000013528 artificial neural network Methods 0.000 claims description 5
- 238000013507 mapping Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 2
- 238000004891 communication Methods 0.000 claims description 2
- 229910052744 lithium Inorganic materials 0.000 description 12
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 9
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 description 6
- 238000000034 method Methods 0.000 description 4
- 239000005955 Ferric phosphate Substances 0.000 description 3
- 229940032958 ferric phosphate Drugs 0.000 description 3
- 229910052739 hydrogen Inorganic materials 0.000 description 3
- 239000001257 hydrogen Substances 0.000 description 3
- WBJZTOZJJYAKHQ-UHFFFAOYSA-K iron(3+) phosphate Chemical compound [Fe+3].[O-]P([O-])([O-])=O WBJZTOZJJYAKHQ-UHFFFAOYSA-K 0.000 description 3
- 229910000399 iron(III) phosphate Inorganic materials 0.000 description 3
- PXHVJJICTQNCMI-UHFFFAOYSA-N Nickel Chemical compound [Ni] PXHVJJICTQNCMI-UHFFFAOYSA-N 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 229910052987 metal hydride Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910052759 nickel Inorganic materials 0.000 description 1
- 230000002269 spontaneous effect Effects 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60S—SERVICING, CLEANING, REPAIRING, SUPPORTING, LIFTING, OR MANOEUVRING OF VEHICLES, NOT OTHERWISE PROVIDED FOR
- B60S5/00—Servicing, maintaining, repairing, or refitting of vehicles
- B60S5/06—Supplying batteries to, or removing batteries from, vehicles
-
- 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
-
- 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
-
- 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
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Secondary Cells (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention relates to a new energy automobile battery intelligent replacement system, which comprises: the prediction execution mechanism is used for predicting the residual chargeable residual of the target charging pile at the reference charging moment according to various charging related information of the target charging pile and outputting the residual chargeable residual as a predicted charging residual; and the replacement request mechanism is used for sending a battery replacement request to locally wait for battery replacement when all the target charging piles do not meet the evaluation condition that the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging piles and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile. According to the invention, the charging piles with enough chargeable electric quantity can be selected for charging according to the residual electric quantity of the vehicle and the charging related information of each charging pile nearby, and when the charging pile meeting the conditions does not exist nearby, the battery is selected to be replaced locally, so that the intelligent level of battery management is improved.
Description
Technical Field
The invention relates to the field of new energy automobiles, in particular to an intelligent battery replacement system for a new energy automobile.
Background
Currently, three general types of batteries of new energy automobiles are mainly: ternary lithium batteries, lithium iron phosphate batteries, and nickel hydrogen batteries. The energy density of the ternary lithium battery and the energy density of the ferric phosphate lithium battery are high, the performance of the ternary lithium battery and the ferric phosphate lithium battery are stable, and the application of the ternary lithium battery and the ferric phosphate lithium battery to electric automobiles is the most extensive. The nickel-hydrogen battery is also a storage battery with good performance and is gradually applied to the field of new energy automobiles.
The low-temperature performance of the ternary lithium battery is better, so that the ternary lithium battery is generally suitable for being applied to cold areas, and the ternary lithium battery can work even in an environment of 30 ℃ below zero. However, the ternary lithium battery has the disadvantage that the thermal runaway temperature is relatively low, namely, about 200 degrees, and is not suitable for being used in hot areas, and the spontaneous combustion phenomenon is easy to occur.
Compared with the lithium iron phosphate battery, the lithium iron phosphate battery has better stability, and meanwhile, the thermal runaway temperature of the lithium iron phosphate battery is higher, can reach more than 800 ℃, and is applicable to even hot areas. However, on the contrary, the lithium iron phosphate battery has poor low-temperature performance, is not suitable for being used in cold areas, and can reduce the service life of the battery.
Although ternary lithium batteries and lithium iron phosphate batteries are mostly used for new energy automobiles at present, nickel-hydrogen batteries are used for some automobile types. In the battery design, the safety performance of the nickel-metal hydride battery is better, and if the internal working pressure of the battery rises due to the conditions of improper overcharge, overdischarge, short circuit and the like in the use process, the recoverable safety valve can be automatically opened to prevent the explosion of the battery.
Obviously, the battery is the most critical unstable element of the new energy automobile, and if the new energy automobile runs in an extremely-content area or runs in an underpowered state, the user of the new energy automobile is most concerned about whether a nearby charging pile is close to a position where the charging pile can reach with the current residual electric quantity. However, the power consumption of the new energy automobile per unit time, the complex road condition, the uncertain driving environment and the uncertain charging pile use condition result in the dilemma that the new energy automobile easily reaches the charging pile but the electric quantity of the charging pile is completely charged by other vehicles, or the charging pile which the new energy automobile does not reach is depleted of the electric quantity of the battery. It follows that the choice of the target charging stake and the choice of the battery replacement timing are of paramount importance.
Disclosure of Invention
In order to solve the technical problems in the related art, the invention provides a new energy automobile battery intelligent replacement system, which can select a charging pile with enough chargeable electric quantity for a charging pile to charge at the moment of arrival of the residual electric quantity of an automobile based on various pieces of automobile information and charging related information of nearby charging piles, and select to wait for replacing a battery locally when the nearby charging pile meeting the conditions does not exist so as to avoid wasting time and electric quantity cost of the charging pile.
According to an aspect of the present invention, there is provided a new energy automobile battery intelligent replacement system, the system comprising:
the distance measuring device is arranged in the new energy automobile, and is used for measuring the running distance of the new energy automobile to the target charging pile and outputting the running distance as the instant running distance;
the vehicle speed judging device is arranged in the new energy automobile and is used for analyzing the running average speed of the new energy automobile based on the historical vehicle speed of the new energy automobile;
the time analysis device is respectively connected with the distance measurement device and the vehicle speed judgment device and is used for dividing the instant running distance by the running average speed of the new energy automobile to obtain the time length required by the new energy automobile to reach the target charging pile and outputting the time length as a reference time length;
the consumption identification mechanism is respectively connected with the distance measurement device and the vehicle speed judgment device and is used for determining the consumed electric quantity of the new energy automobile for completing the running of the instant running distance at the running uniform speed and obtaining the local residual electric quantity when the new energy automobile reaches a target charging pile based on the current residual electric quantity of the new energy automobile minus the consumed electric quantity;
the historical detection mechanism is arranged in the new energy automobile and connected with the time analysis device, and is used for delaying the current time backwards by a reference time length to serve as a reference charging time, and acquiring each residual chargeable allowance of the target charging pile corresponding to the same time of each historical day as the reference charging time;
the prediction execution mechanism is connected with the history detection mechanism and is used for predicting the residual chargeable residual of each residual chargeable pile of the target charging pile at the reference charging moment based on the full chargeable quantity of the target charging pile, the quantity of charging piles around the target charging pile and the residual chargeable residual of each residual chargeable pile of the target charging pile, which corresponds to the same moment of the reference charging moment in each history day, and outputting the residual chargeable residual as the predicted chargeable residual;
the strategy customizing mechanism is respectively connected with the consumption identifying mechanism and the prediction executing mechanism and is used for determining that the target charging pile is an effective charging pile when the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile, otherwise, searching the next target charging pile to perform evaluation processing of the full capacity of the new energy automobile when the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile;
and the replacement request mechanism is connected with the strategy customizing mechanism and is used for sending a battery replacement request to locally wait for battery replacement when all the target charging piles do not meet the evaluation condition that the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging piles and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile.
The invention has at least the following three important invention points:
firstly, in the running process of a new energy automobile, aiming at each charging pile nearby as a target charging pile, estimating the local residual electric quantity when the new energy automobile reaches the target charging pile, dividing the distance from the current position of the new energy automobile to the position of the target charging pile by the running average speed of the new energy automobile to obtain the time length required by the new energy automobile to reach the target charging pile, and taking the time length as the reference time length;
secondly, predicting the residual chargeable residual of the target charging pile at the reference charging moment based on the full chargeable electric quantity of the target charging pile, the number of charging piles around the target charging pile and the residual chargeable residual of the target charging pile, which correspond to the same moment of the reference charging moment in each historical day, and taking the residual chargeable residual as the predicted chargeable residual;
and when the local residual capacity is larger than zero and the sum of the predicted charge margin corresponding to the target charge pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile, determining that the target charge pile is an effective charge pile so as to facilitate the new energy automobile to select to charge, otherwise, searching the next target charge pile to perform evaluation processing of the local residual capacity which is larger than zero and the sum of the predicted charge margin corresponding to the target charge pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile, and when all the target charge piles do not meet the evaluation condition that the local residual capacity is larger than zero and the sum of the predicted charge margin corresponding to the target charge pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile, sending a battery replacement request to the nearest new energy automobile supplier to locally wait for battery replacement, so that intelligent analysis of the battery replacement time of the new energy automobile is realized.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings, in which:
fig. 1 is a schematic view showing an internal structure of a battery intelligent replacement system for a new energy vehicle according to a first embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating an internal structure of a battery intelligent replacement system for a new energy vehicle according to a second embodiment of the present invention.
Fig. 3 is a schematic view illustrating an internal structure of a battery intelligent replacement system for a new energy vehicle according to a third embodiment of the present invention.
Detailed Description
An embodiment of the intelligent battery replacement system for a new energy automobile according to the present invention will be described in detail with reference to the accompanying drawings.
Fig. 1 is a schematic view showing an internal structure of a battery intelligent replacement system for a new energy vehicle according to a first embodiment of the present invention, the system comprising:
the distance measuring device is arranged in the new energy automobile, and is used for measuring the running distance of the new energy automobile to the target charging pile and outputting the running distance as the instant running distance;
the vehicle speed judging device is arranged in the new energy automobile and is used for analyzing the running average speed of the new energy automobile based on the historical vehicle speed of the new energy automobile;
the time analysis device is respectively connected with the distance measurement device and the vehicle speed judgment device and is used for dividing the instant running distance by the running average speed of the new energy automobile to obtain the time length required by the new energy automobile to reach the target charging pile and outputting the time length as a reference time length;
the consumption identification mechanism is respectively connected with the distance measurement device and the vehicle speed judgment device and is used for determining the consumed electric quantity of the new energy automobile for completing the running of the instant running distance at the running uniform speed and obtaining the local residual electric quantity when the new energy automobile reaches a target charging pile based on the current residual electric quantity of the new energy automobile minus the consumed electric quantity;
the historical detection mechanism is arranged in the new energy automobile and connected with the time analysis device, and is used for delaying the current time backwards by a reference time length to serve as a reference charging time, and acquiring each residual chargeable allowance of the target charging pile corresponding to the same time of each historical day as the reference charging time;
the prediction execution mechanism is connected with the history detection mechanism and is used for predicting the residual chargeable residual of each residual chargeable pile of the target charging pile at the reference charging moment based on the full chargeable quantity of the target charging pile, the quantity of charging piles around the target charging pile and the residual chargeable residual of each residual chargeable pile of the target charging pile, which corresponds to the same moment of the reference charging moment in each history day, and outputting the residual chargeable residual as the predicted chargeable residual;
the strategy customizing mechanism is respectively connected with the consumption identifying mechanism and the prediction executing mechanism and is used for determining that the target charging pile is an effective charging pile when the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile, otherwise, searching the next target charging pile to perform evaluation processing of the full capacity of the new energy automobile when the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile;
and the replacement request mechanism is connected with the strategy customizing mechanism and is used for sending a battery replacement request to locally wait for battery replacement when all the target charging piles do not meet the evaluation condition that the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging piles and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile.
Fig. 2 is a schematic diagram illustrating an internal structure of a battery intelligent replacement system for a new energy vehicle according to a second embodiment of the present invention.
In fig. 2, unlike fig. 1, the new energy vehicle battery intelligent replacement system in fig. 2 may further include the following components:
and the directional transmission mechanism is connected with the replacement request mechanism and is used for transmitting a battery replacement request to a server where the nearest new energy automobile provider is located through a wireless communication link.
Fig. 3 is a schematic view illustrating an internal structure of a battery intelligent replacement system for a new energy vehicle according to a third embodiment of the present invention.
In fig. 3, unlike fig. 1, the new energy vehicle battery intelligent replacement system in fig. 3 may further include the following components:
the data temporary storage mechanism is connected with the prediction execution mechanism and used for temporarily storing full chargeable electric quantity of the target charging piles, the number of the charging piles around the target charging piles and each residual chargeable allowance of the target charging piles, which corresponds to the same time of the reference charging time in each historical day.
Next, a specific structure of the intelligent battery replacement system for a new energy automobile according to the present invention will be further described.
In the new energy automobile battery intelligent replacement system according to any one of the embodiments of the present invention:
the method for predicting the residual chargeable residual of the target charging pile at the reference charging moment based on the full chargeable electric quantity of the target charging pile, the number of charging piles around the target charging pile and the residual chargeable residual of the target charging pile, which correspond to the same moment of the reference charging moment in each historical day, respectively, and outputting the residual chargeable residual as the predicted chargeable residual comprises the following steps: the prediction processing is executed by adopting the trained deep neural network;
the method for predicting the residual chargeable residual of the target charging pile at the reference charging time and outputting the residual chargeable residual as the predicted charging residual based on the full chargeable electric quantity of the target charging pile, the number of charging piles around the target charging pile and the residual chargeable residual of the target charging pile at the reference charging time, which correspond to the same time of the reference charging time on each day of history, comprises the following steps: and the full-scale chargeable electric quantity of the target charging pile, the number of the charging piles around the target charging pile and the residual chargeable residual quantity of the target charging pile, which are respectively corresponding to the same time of the reference charging time in each historical day, are all input contents of the trained deep neural network.
In the new energy automobile battery intelligent replacement system according to any one of the embodiments of the present invention:
the measuring of the driving distance of the new energy automobile to the target charging pile and outputting the driving distance as the instant driving distance comprises the following steps: acquiring current positioning data of the new energy automobile and current positioning data of a target charging pile, and determining the driving distance of the new energy automobile to the target charging pile based on the difference value of the two current positioning data;
the analyzing the running average speed of the new energy automobile based on the historical speed of the new energy automobile comprises the following steps: calculating an arithmetic average value of each vehicle speed corresponding to each time uniformly spaced before the current time to obtain the running average speed of the new energy vehicle;
wherein, calculating the arithmetic average value of the respective vehicle speeds corresponding to respective times of the uniform interval before the current time to obtain the running average speed of the new energy automobile comprises: the farther the new energy automobile reaches the target charging pile, the longer the corresponding time length of the time interval occupied by each time evenly spaced before the current time.
In the new energy automobile battery intelligent replacement system according to any one of the embodiments of the present invention:
the longer the driving distance of the new energy automobile reaching the target charging pile is, the longer the corresponding time length of the time interval occupied by each time evenly spaced before the current time is, comprising: the numerical mapping formula is used for expressing the forward association relation of the running distance of the new energy automobile reaching the target charging pile and the corresponding time length of the time interval occupied by each time evenly spaced before the corresponding current time;
the forward association relationship for expressing the time length corresponding to the time interval occupied by each time uniformly spaced before the corresponding current time and the travel distance of the new energy automobile reaching the target charging pile by adopting a numerical mapping formula comprises the following steps: and the MATLAB tool box is used for expressing the forward association relation of the running distance of the new energy automobile reaching the target charging pile and the corresponding time length of the time interval occupied by each time uniformly spaced before the corresponding current time.
In addition, in the new energy automobile battery intelligent replacement system, predicting remaining chargeable residual of each remaining chargeable residual of the target charging pile at the reference charging time based on full chargeable quantity of the target charging pile, the number of charging piles around the target charging pile and remaining chargeable residual of each remaining chargeable pile respectively corresponding to the target charging pile at the same time of each history day as the reference charging time, and outputting the remaining chargeable residual as the predicted chargeable residual comprises: and the residual chargeable allowance of the target charging pile at the reference charging moment is the single output content of the trained deep neural network.
The intelligent replacement system for the new energy automobile battery aims at solving the technical problem that in the prior art, the target charging pile selection and the battery replacement time selection of the new energy automobile are difficult to accurately implement, the charging pile which can reach with the residual electric quantity of the automobile and has enough chargeable electric quantity of the charging pile at the moment of reaching can be selected to charge based on various pieces of information of the automobile and charging related information of each nearby charging pile, and when the nearby charging pile which meets the conditions does not exist, the local waiting battery replacement is selected, so that the intelligent level of battery management is improved.
While the present invention has been described with reference to certain exemplary embodiments thereof, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit or scope of the invention as defined in the appended claims and their equivalents.
Claims (6)
1. An intelligent replacement system for a new energy automobile battery, the system comprising:
the distance measuring device is arranged in the new energy automobile, and is used for measuring the running distance of the new energy automobile to the target charging pile and outputting the running distance as the instant running distance;
the vehicle speed judging device is arranged in the new energy automobile and is used for analyzing the running average speed of the new energy automobile based on the historical vehicle speed of the new energy automobile;
calculating arithmetic average value of each vehicle speed corresponding to each time uniformly spaced before the current time to obtain the running average speed of the new energy automobile;
the longer the new energy automobile reaches the target charging pile, the longer the corresponding time length of the time interval occupied by each time evenly spaced before the current time;
the time analysis device is respectively connected with the distance measurement device and the vehicle speed judgment device and is used for dividing the instant running distance by the running average speed of the new energy automobile to obtain the time length required by the new energy automobile to reach the target charging pile and outputting the time length as a reference time length;
the consumption identification mechanism is respectively connected with the distance measurement device and the vehicle speed judgment device and is used for determining the consumed electric quantity of the new energy automobile for completing the running of the instant running distance at the running uniform speed and obtaining the local residual electric quantity when the new energy automobile reaches a target charging pile based on the current residual electric quantity of the new energy automobile minus the consumed electric quantity;
the historical detection mechanism is arranged in the new energy automobile and connected with the time analysis device, and is used for delaying the current time backwards by a reference time length to serve as a reference charging time, and acquiring each residual chargeable allowance of the target charging pile corresponding to the same time of each historical day as the reference charging time;
the prediction execution mechanism is connected with the history detection mechanism and is used for predicting the residual chargeable residual of each residual chargeable pile of the target charging pile at the reference charging moment based on the full chargeable quantity of the target charging pile, the quantity of charging piles around the target charging pile and the residual chargeable residual of each residual chargeable pile of the target charging pile, which corresponds to the same moment of the reference charging moment in each history day, and outputting the residual chargeable residual as the predicted chargeable residual;
the prediction processing is executed by adopting the trained deep neural network;
the full-scale chargeable electric quantity of the target charging pile, the number of the charging piles around the target charging pile and the residual chargeable allowance of the target charging pile, which correspond to each other at the same moment of the reference charging moment in each history day, are all input contents of the trained deep neural network;
the strategy customizing mechanism is respectively connected with the consumption identifying mechanism and the prediction executing mechanism and is used for determining that the target charging pile is an effective charging pile when the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile, otherwise, searching the next target charging pile to perform evaluation processing of the full capacity of the new energy automobile when the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging pile and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile;
and the replacement request mechanism is connected with the strategy customizing mechanism and is used for sending a battery replacement request to locally wait for battery replacement when all the target charging piles do not meet the evaluation condition that the local residual capacity is larger than zero and the sum of the predicted charging allowance corresponding to the target charging piles and the local residual capacity exceeds or is equal to the full capacity of the new energy automobile.
2. The intelligent battery replacement system for a new energy vehicle of claim 1, further comprising:
and the directional transmission mechanism is connected with the replacement request mechanism and is used for transmitting a battery replacement request to a server where the nearest new energy automobile provider is located through a wireless communication link.
3. The intelligent battery replacement system for a new energy vehicle of claim 2, further comprising:
the data temporary storage mechanism is connected with the prediction execution mechanism and used for temporarily storing full chargeable electric quantity of the target charging piles, the number of the charging piles around the target charging piles and each residual chargeable allowance of the target charging piles, which corresponds to the same time of the reference charging time in each historical day.
4. The intelligent replacement system for a battery of a new energy automobile according to any one of claims 1 to 3, wherein:
the measuring of the driving distance of the new energy automobile to the target charging pile and outputting the driving distance as the instant driving distance comprises the following steps: and acquiring the current positioning data of the new energy automobile and the current positioning data of the target charging pile, and determining the driving distance of the new energy automobile to the target charging pile based on the difference value of the two current positioning data.
5. The intelligent replacement system for a battery of a new energy automobile according to any one of claims 1 to 3, wherein:
the longer the driving distance of the new energy automobile reaching the target charging pile is, the longer the corresponding time length of the time interval occupied by each time evenly spaced before the current time is, comprising: and a numerical mapping formula is used for expressing the forward association relation of the running distance of the new energy automobile reaching the target charging pile and the corresponding time length of the time interval occupied by each time uniformly spaced before the corresponding current time.
6. The intelligent replacement system for the battery of the new energy automobile according to claim 5, wherein:
the forward association relation for expressing the time length corresponding to the time interval occupied by each time evenly spaced before the corresponding current time and the travel distance of the new energy automobile reaching the target charging pile by adopting a numerical mapping formula comprises the following steps: and the MATLAB tool box is used for expressing the forward association relation of the running distance of the new energy automobile reaching the target charging pile and the corresponding time length of the time interval occupied by each time uniformly spaced before the corresponding current time.
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