CN116476691A

CN116476691A - New energy automobile endurance mileage management method and system

Info

Publication number: CN116476691A
Application number: CN202310523488.5A
Authority: CN
Inventors: 程源
Original assignee: Individual
Current assignee: Individual
Priority date: 2023-05-10
Filing date: 2023-05-10
Publication date: 2023-07-25

Abstract

The application relates to the field of new energy automobiles, and provides a new energy automobile endurance mileage management method and system. Obtaining a battery attenuation coefficient based on the running environment information of the automobile, obtaining energy consumption parameters based on the load, road surface and speed information, and obtaining initial endurance mileage and initial endurance time by combining the real-time battery capacity; calculating according to the initial endurance time and the battery attenuation coefficient to obtain the attenuation battery capacity and the actual battery capacity; and calculating according to the actual battery capacity and the driving energy consumption parameters to obtain the corrected endurance mileage, and obtaining a management scheme according to the position of the charging station and the corrected endurance mileage. The technical problem that the application degree of the new energy automobile is low due to the fact that the application degree of the new energy automobile is not high due to the fact that the application degree of the new energy automobile is low in the new energy automobile is solved, the new energy automobile is subjected to the application degree of the new energy automobile according to the fact that the new energy automobile is driven in the actual mode and the driving environment, and the technical effects of the new energy automobile are improved.

Description

New energy automobile endurance mileage management method and system

Technical Field

The application relates to the field of new energy automobiles, in particular to a new energy automobile endurance mileage management method and system.

Background

With the continuous development of new energy automobile markets, the problem of continuous voyage mileage becomes one of the important points of consumer attention. In order to better manage the cruising performance of new energy automobiles, various manufacturers and research institutions are constantly exploring and researching new cruising management methods.

The most common new energy automobile endurance management method at present dynamically manages the charge and discharge of the battery, and automatically adjusts the charge and discharge strategy of the battery according to the actual condition of the vehicle, so that the service life of the battery and the endurance mileage of the vehicle are improved to the greatest extent.

At present, the method for managing the cruising of the new energy automobile is often focused on energy multidimensional utilization and battery charge and discharge control according to the running condition of the new energy automobile, and no scheme for managing the cruising of the automobile by combining with the driving environment of the new energy automobile exists at present.

In summary, in the prior art, there is a technical problem that the fit between the endurance mileage management scheme of the new energy automobile and the actual driving situation of the automobile, and the battery usage situation is not high, resulting in lower fit between the endurance management strategy and the new energy automobile.

Disclosure of Invention

Based on the above, it is necessary to provide a new energy automobile endurance mileage management method and system capable of realizing endurance management according to the actual driving situation and driving environment of the new energy automobile and improving the adaptation degree of the new energy automobile endurance management and the actual use situation of the automobile.

A new energy automobile endurance mileage management method comprises the following steps: responding to a continuous voyage mileage management instruction, collecting current real-time load information and traveling information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile; collecting various environmental information of the current environment of the target automobile to obtain an environmental information set, and inputting the environmental information set into a battery attenuation analysis model to obtain a battery attenuation coefficient; inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial endurance mileage and initial endurance time by combining the real-time battery capacity; according to the initial endurance time and the battery attenuation coefficient, calculating to obtain the attenuation battery capacity of the battery in the initial endurance time, and calculating to obtain the actual battery capacity; calculating to obtain a corrected endurance mileage according to the actual battery capacity and the driving energy consumption parameter; and acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and obtaining a driving mileage management scheme by combining the corrected driving mileage to display.

A new energy vehicle range management system, the system comprising: the management instruction response module is used for responding to a continuous voyage mileage management instruction, collecting current real-time load information and running information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile; the environment information acquisition module is used for acquiring various environment information of the current environment of the target automobile to obtain an environment information set, and inputting the environment information set into the battery attenuation analysis model to obtain a battery attenuation coefficient; the cruising data calculation module is used for inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial cruising mileage and initial cruising time by combining the real-time battery capacity; the battery capacity calculation module is used for calculating and obtaining the attenuation battery capacity of the battery in the initial endurance time according to the initial endurance time and the battery attenuation coefficient, and calculating and obtaining the actual battery capacity; the cruising mileage correction module is used for calculating and obtaining corrected cruising mileage according to the actual battery capacity and the driving energy consumption parameter; and the management scheme generation module is used for acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and acquiring a driving mileage management scheme by combining the corrected driving mileage to display.

A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:

responding to a continuous voyage mileage management instruction, collecting current real-time load information and traveling information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile;

collecting various environmental information of the current environment of the target automobile to obtain an environmental information set, and inputting the environmental information set into a battery attenuation analysis model to obtain a battery attenuation coefficient;

inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial endurance mileage and initial endurance time by combining the real-time battery capacity;

according to the initial endurance time and the battery attenuation coefficient, calculating to obtain the attenuation battery capacity of the battery in the initial endurance time, and calculating to obtain the actual battery capacity;

calculating to obtain a corrected endurance mileage according to the actual battery capacity and the driving energy consumption parameter;

And acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and obtaining a driving mileage management scheme by combining the corrected driving mileage to display.

A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

The new energy automobile endurance mileage management method and system solve the technical problem that in the prior art, the endurance mileage management scheme of the new energy automobile is not high in fit with the actual driving condition of the automobile and the service condition of the battery, so that the endurance management strategy is low in fit with the new energy automobile, and the technical effects of carrying out endurance management according to the actual driving condition and the driving environment of the new energy automobile and improving the endurance management of the new energy automobile and the fit of the actual service condition of the automobile are achieved.

The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.

Drawings

Fig. 1 is a schematic flow chart of a new energy automobile endurance mileage management method in an embodiment;

fig. 2 is a schematic flow chart of a new energy vehicle endurance mileage management scheme obtained by analysis in the new energy vehicle endurance mileage management method according to an embodiment;

FIG. 3 is a block diagram illustrating a new energy vehicle range management system according to an embodiment;

fig. 4 is an internal structural diagram of a computer device in one embodiment.

Reference numerals illustrate: the system comprises a management instruction response module 1, an environment information acquisition module 2, a continuous voyage data calculation module 3, a battery capacity calculation module 4, a continuous voyage mileage correction module 5 and a management scheme generation module 6.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

As shown in fig. 1, the present application provides a new energy automobile endurance mileage management method, which includes:

s100, responding to a continuous voyage mileage management instruction, collecting current real-time load information and traveling information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile;

In one embodiment, current real-time load information and travel information of a target automobile and current real-time battery capacity of a battery of the target automobile are collected in response to a range management instruction. The range management command may be a command that is executed periodically and automatically, for example, based on the vehicle control computer executing every 10 minutes, or may be executed by triggering the "range management" function for the user using the target vehicle. The method provided in the present application further includes step S100:

s110, acquiring current real-time load information of the target automobile, and combining full load information of the target automobile to calculate and obtain the load information;

s120, collecting pavement information of a current driving road of the target automobile;

s130, acquiring driving route information and speed information of the current driving of the target automobile, and combining the road surface information to obtain the driving information;

and S140, collecting the current real-time battery capacity of the battery of the target automobile.

Specifically, in this embodiment, the target vehicle is a new energy vehicle. The load information is real-time load capacity of the target automobile, and the running information specifically comprises speed information of real-time running speed data of the target automobile and road surface information representing gradient and road surface friction of a running road of the target automobile. The real-time battery capacity is the current target automobile battery remaining capacity, such as 75% of the capacity.

It should be appreciated that the power system of the new energy automobile is powered by a battery, and the energy reserve of the battery is limited, so that the energy consumption of the new energy automobile is related to the load of the automobile, the endurance mileage of the new energy automobile is affected by the load of the automobile, and the greater the load capacity of the automobile is, the more energy is required to be consumed to drive the automobile to run, resulting in the reduction of the endurance mileage of the automobile. When the new energy automobile climbs a slope or descends a slope, more energy is required to be consumed to keep stable running on a road section with smaller road friction force (such as a muddy road surface, a wet road surface and the like), and the endurance mileage is reduced.

Therefore, the embodiment generates the range management instruction, sends the range management instruction to an ECU (engine control unit) to obtain the current real-time battery capacity and the vehicle speed information of the battery of the target vehicle and the current real-time load information of the target vehicle, and invokes the full load information of the target vehicle, wherein the full load information is the upper load limit of safe driving of the target vehicle, and the load information is obtained based on the calculated ratio of the full load information to the real-time load information.

And sending the endurance mileage management instruction to a vehicle-mounted camera management system, or acquiring the road gradient and road surface friction information of the target automobile through a level meter system. And integrating the vehicle driving road gradient, the road surface friction information and the vehicle speed information to generate the driving information of the target vehicle.

S200, collecting various environmental information of the current environment of the target automobile to obtain an environmental information set, and inputting the environmental information set into a battery attenuation analysis model to obtain a battery attenuation coefficient;

in one embodiment, a plurality of environmental information of the current environment of the target automobile is collected to obtain an environmental information set, the environmental information set is input into a battery attenuation analysis model to obtain a battery attenuation coefficient, and the method step S200 provided in the present application further includes:

s210, acquiring temperature information and temperature information of the current environment of the target automobile to obtain the environment information set;

s210, acquiring a sample temperature information set and a sample humidity information set, and combining to acquire a plurality of sample environment information sets;

s220, under the plurality of sample environment information sets, carrying out attenuation coefficient test on the battery of the target automobile to obtain a sample battery attenuation coefficient set;

s230, constructing a battery attenuation analysis model by adopting the plurality of sample environment information sets and the sample battery attenuation coefficient sets, wherein the battery attenuation analysis model comprises an analysis coordinate system and a plurality of sample coordinate points, and each sample coordinate point is marked by a corresponding sample battery attenuation coefficient;

S240, inputting the environment information set into the battery attenuation analysis model to obtain real-time coordinate points, and obtaining K sample coordinate points nearest to the real-time coordinate points, wherein K is an odd number greater than or equal to 3;

s250, obtaining K sample battery attenuation coefficients marked by the K sample coordinate points, and taking the sample battery attenuation coefficient with the highest occurrence frequency as the battery attenuation coefficient.

In one embodiment, the battery attenuation analysis model is constructed by using the plurality of sample environment information sets and the sample battery attenuation coefficient set, and the method step S230 provided in the present application further includes:

s231, constructing an abscissa axis and an ordinate axis which are mutually perpendicular in the analysis coordinate system based on the ambient temperature and the ambient humidity;

s232, inputting the plurality of sample environment information sets into the analysis coordinate system to obtain a plurality of sample coordinate points;

and S233, marking the plurality of sample coordinate points by adopting a plurality of sample battery attenuation coefficients in the sample battery attenuation coefficient set as a plurality of markers to obtain the battery attenuation analysis model.

Specifically, it should be understood that high temperature accelerates the chemical reaction in the battery, causing corrosion and damage to the electrolyte and electrode materials inside the battery, thereby affecting the performance and life of the battery, and low temperature reduces the discharge capacity of the battery, resulting in a reduction in the range of the battery. Electrolyte and electrode materials in the battery are easy to be affected by moisture and damaged in a humidity environment, so that the performance and service life of the battery are affected, and the endurance mileage of the battery is reduced.

Therefore, the battery attenuation coefficient is obtained based on the analysis of the environmental temperature and humidity condition of the target automobile, and reflects the percentage of the influence loss of high temperature and high humidity on the battery because the battery capacity of the target automobile is disturbed by the environment in unit time in the driving process of the battery of the target automobile in the current environment, and the electric energy is not converted into the automobile kinetic energy. For example, the battery decay factor of 2.7% characterizes 2.7% of the total battery power lost by the unit applied internal battery to eliminate ambient temperature, humidity effects.

Because the temperature and humidity conditions of the environment where the target automobile is located have little fluctuation, the embodiment collects the temperature information and the temperature information of the current environment where the target automobile is located, obtains the environment information set, and takes the environment information set as the environment temperature and humidity conditions representing the environment where the target automobile is located.

The battery attenuation coefficient of the target automobile battery is determined based on the environmental temperature and humidity information analysis, and in order to ensure the accuracy of the obtained battery attenuation coefficient, the battery attenuation analysis model is constructed in the embodiment, and the data analysis is performed on the environmental information set based on the battery attenuation analysis model to replace manual experience so as to improve the accuracy of the obtained battery attenuation coefficient.

The method for constructing the battery attenuation analysis model comprises the following steps:

the method comprises the steps of obtaining a plurality of sample batteries of the same type as a target automobile battery, setting sample temperature information and sample humidity information of the plurality of sample batteries, integrating the sample temperature information of the plurality of sample batteries to obtain a sample temperature information set, integrating the sample humidity information of the plurality of sample batteries to obtain a sample humidity information set, and combining the sample humidity information set and the sample temperature information set to obtain a plurality of sample environment information sets.

And controlling other variables to be unchanged, and singly changing the ambient temperature and the ambient humidity to realize charge and discharge control by placing the plurality of sample batteries under the combination of the ambient temperature and the ambient humidity of the plurality of sample ambient information sets, and performing attenuation coefficient test on the plurality of sample batteries of the target automobile to obtain a sample battery attenuation coefficient set corresponding to the plurality of sample batteries, wherein each sample battery attenuation coefficient corresponds to one set of sample humidity information and sample temperature information.

And constructing the analysis coordinate system based on the environment temperature and the environment humidity, wherein the analysis coordinate system is a two-dimensional analysis coordinate system, and the abscissa axis X which is mutually perpendicular in the analysis coordinate system is the environment temperature and the ordinate axis Y is the environment humidity.

And filling a group of sample humidity information and sample temperature information corresponding to the first sample battery attenuation coefficient into the constructed two-dimensional analysis coordinate system, taking the intersection point of the group of sample humidity information and sample temperature information in the two-dimensional analysis coordinate system as a sample coordinate point of the group of data, and marking by using the first sample battery attenuation coefficient.

And constructing a plurality of sample coordinate points based on the plurality of sample environment information sets and the sample battery attenuation coefficient sets by adopting a filling method that the first sample battery attenuation coefficient and a group of sample humidity information-sample temperature information corresponding to the first sample battery attenuation coefficient are the same in an analysis coordinate system, and marking each sample coordinate point by the corresponding sample battery attenuation coefficient to finish the construction of the battery attenuation analysis model.

And inputting the environment information set into the battery attenuation analysis model to obtain real-time coordinate points, wherein the real-time coordinate points are coordinate points where temperature information and temperature information data of the current environment of the target automobile intersect in an analysis coordinate system of the battery attenuation analysis model.

Based on the real-time coordinate points, K sample coordinate points nearest to the real-time coordinate points are obtained, K is an odd number greater than or equal to 3, K sample battery attenuation coefficients marked by the K sample coordinate points are obtained, occurrence frequency statistics is carried out on the K sample battery attenuation coefficients, and the sample battery attenuation coefficient with the highest occurrence frequency is used as the battery attenuation coefficient.

According to the embodiment, through constructing the battery attenuation analysis model and acquiring the temperature information and the temperature information of the current environment of the target automobile battery, the technical effect of obtaining the battery attenuation coefficient which scientifically and accurately reflects the maximum capacity attenuation condition of the target automobile battery and providing updated data reference for the subsequent updating of the target automobile battery capacity is achieved.

S300, inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial endurance mileage and initial endurance time by combining the real-time battery capacity;

in one embodiment, the load information, the road surface information in the driving information and the speed information are input into a driving energy consumption analysis model to obtain driving energy consumption parameters, and the initial endurance mileage and the initial endurance time are calculated and obtained by combining the real-time battery capacity, so that the method step S300 provided by the present application further includes:

s310, acquiring a sample load information set, a sample pavement information set and a sample speed information set of the target automobile;

s320, combining the data in the sample load information set, the sample pavement information set and the sample speed information set, and carrying out running energy consumption test detection on the target automobile to obtain a sample running energy consumption parameter set;

S330, randomly selecting M groups of data from the sample load information set, the sample pavement information set, the sample speed information set and the sample driving energy consumption parameter set respectively, wherein M is an integer which is more than 1 and less than the number in the sample load information set;

s340, constructing and training to obtain a first driving energy consumption analysis unit in the driving energy consumption analysis model based on a BP neural network by adopting the first construction data set;

s350, randomly selecting M groups of data from the sample load information set, the sample pavement information set, the sample speed information set and the sample driving energy consumption parameter set respectively to obtain a second construction data set,

s360, constructing and training to obtain a second driving energy consumption analysis unit in the driving energy consumption analysis model by adopting the second construction data set;

s370, continuously constructing N-2 running energy consumption analysis units in the running energy consumption analysis model, wherein N is an integer greater than 3, and obtaining the running energy consumption analysis model according to the N running energy consumption analysis units;

and S380, inputting the load information and the running information into the N running energy consumption analysis units to obtain N output results, and taking the highest occurrence frequency in the N output results as the running energy consumption parameter.

Specifically, in the present embodiment, a load zone range of the target vehicle is obtained, a travel speed zone range, T pieces of sample load information are set based on the load zone range, the sample load information set is configured, K pieces of sample speed information are set based on the travel speed zone range, the present speed information set is configured, W sets of road surface gradient and road surface friction data are set, and the sample road surface information set is configured. The T, K, W is an unspecified positive integer greater than 100.

And carrying out repeated random permutation and combination on the data in the sample load information set, the sample road surface information set and the sample speed information set to obtain a plurality of groups of sample speed, sample load sample road surface gradient and road surface friction data.

The method comprises the steps of controlling temperature and humidity and other variables to be fixed, controlling initial performance states of a target automobile to be consistent, controlling running distances of the target automobile to be consistent, detecting running energy consumption tests of a plurality of target automobiles with consistent initial performance states one by one based on a plurality of groups of sample speeds, sample load sample road gradients and road friction data, and obtaining a sample running energy consumption parameter set, wherein the sample running energy consumption set comprises a plurality of sample running energy consumption data mapped with the plurality of groups of sample speeds, sample load sample road gradients and road friction data, and the running energy consumption data is the running unit distance from the battery power consumption of the target automobile under certain speed, load, road gradients and road friction conditions.

M groups of data are randomly selected from the sample load information set, the sample road surface information set, the sample speed information set and the sample running energy consumption parameter set in a replaced mode, M sample running energy consumption corresponding to the M groups of data is obtained in the sample running energy consumption set, M sample running energy consumption of the M groups of data is used as the first construction data set, and M is an integer which is larger than 1 and smaller than the number in the sample load information set.

In this embodiment, the driving energy consumption analysis model includes an input layer, a data analysis layer, and an output layer, where the data analysis layer includes N driving energy consumption analysis units that are parallel and running in a non-interfering manner, and in this embodiment, a training method is described by taking a first driving energy consumption analysis unit for training construction as an example, and implementing N driving energy consumption analysis units that are parallel and running in a non-interfering manner.

Based on BP neural network, a first driving energy consumption analysis unit in the driving energy consumption analysis model is constructed, the input data of the first driving energy consumption analysis unit are data of automobile speed, load, driving road surface gradient and road surface friction force, and the output result is driving energy consumption data.

Dividing the first construction data set identifier into a training set, a testing set and a verification set, training the first running energy consumption analysis unit based on the training set and the testing set, verifying the accuracy of the output result of the first running energy consumption analysis unit based on the verification set, and stopping training the first running energy consumption analysis unit when the output accuracy of the first running energy consumption analysis unit is higher than 97%.

And randomly selecting M groups of data from the sample load information set, the sample pavement information set, the sample speed information set and the sample running energy consumption parameter set respectively with a place of return to obtain a second construction data set, carrying out data division identification on the second construction data set by adopting the same processing method of the first construction data set, and carrying out construction training of the second running energy consumption analysis unit by adopting a construction training method of the first running energy consumption analysis unit.

And carrying out N-2 running energy consumption analysis units in the running energy consumption analysis model by adopting the same construction training method of the first running energy consumption analysis unit and the second running energy consumption analysis unit, wherein N is an integer greater than 3, generating a data analysis layer of the running energy consumption analysis model based on parallel layout of the N running energy consumption analysis units according to the N running energy consumption analysis units, setting an input layer and an output layer, and completing construction of the running energy consumption analysis model.

And inputting the load information and the running information into the N running energy consumption analysis units through an input layer of the running energy consumption analysis model, analyzing and processing the load information and the running information based on the N running energy consumption analysis units to obtain N output results, wherein the N output results are N running energy consumption data, the highest occurrence frequency in the N output results is used as the running energy consumption parameter, and the running energy consumption parameter is the battery power consumption of the target automobile running unit distance under the conditions of the speed, the load, the road gradient and the road friction force of the target automobile corresponding to the load information and the running information.

Further, the real-time battery capacity of the target automobile is obtained based on an ECU (engine control unit), the distance representing the distance that the target automobile can travel under the real-time battery capacity is obtained based on the real-time battery capacity and the running energy consumption parameter calculation, and the initial endurance mileage is obtained based on the initial endurance mileage and the vehicle speed calculation under the conditions of the load information, the speed of the target automobile corresponding to the running information, the load, the road gradient and the road friction.

According to the method, the device and the system, the running energy consumption analysis model of the multi-running energy consumption analysis unit is built, and data analysis is carried out based on the load information and the running information of the target automobile, so that the technical effects of obtaining the running energy consumption parameters of the target automobile with high accuracy and reliability, and reflecting the initial endurance mileage and the initial endurance time of the target automobile in the running distance and the running time under the real-time battery capacity are achieved.

S400, calculating to obtain the attenuation battery capacity of the battery in the initial endurance time according to the initial endurance time and the battery attenuation coefficient, and calculating to obtain the actual battery capacity;

S500, calculating and obtaining a corrected endurance mileage according to the actual battery capacity and the driving energy consumption parameter;

specifically, in this embodiment, the battery attenuation coefficient, the initial duration and the real-time battery capacity are multiplied to obtain the attenuated battery capacity of the target automobile, where the attenuated battery capacity is an electric quantity loss value of the target automobile battery in order to offset the environmental temperature and humidity effects during the running of the automobile in the initial duration.

And performing difference calculation on the attenuated battery capacity and the real-time battery capacity to obtain the actual battery capacity reflecting the running energy supply electric quantity of the automobile in the battery of the current target automobile. And calculating and obtaining a corrected endurance mileage according to the actual battery capacity and the driving energy consumption parameter, wherein the corrected endurance mileage is the distance length of the current target automobile electric quantity capable of supporting the target automobile to drive.

And S600, acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and obtaining a driving mileage management scheme by combining the corrected driving mileage to display.

In one embodiment, as shown in fig. 2, according to the driving route information in the driving information, a charging station near the driving route information is obtained, and in combination with the corrected driving range, a driving range management scheme is obtained by analysis, and is displayed, and the method step S600 provided in the present application further includes:

S610, acquiring a critical range, and combining the driving route information and the corrected range to acquire a critical position;

s620, acquiring a plurality of charging stations in the preset range of the critical position and a plurality of distance information between the plurality of charging stations and the critical position;

s630, formulating a plurality of display schemes according to the plurality of distance information;

and S640, displaying the plurality of charging stations and the plurality of distance information by adopting the plurality of display schemes, and displaying the corrected endurance mileage.

In one embodiment, according to the plurality of distance information, a plurality of display schemes are formulated, and the method provided in step S630 further includes:

s631, acquiring a plurality of order information which are ordered according to the order from small to large of the distance information;

s632, constructing a plurality of corresponding sample display schemes according to the plurality of order information;

and S633, sequencing the plurality of distance information according to the sequence from small to large to obtain a plurality of real-time sequence information, and obtaining a plurality of corresponding sample display schemes as the plurality of display schemes.

Specifically, in this embodiment, the critical endurance mileage is a distance length that can be travelled from the emergency electric power to the exhaustion of the electric power of the target automobile after the emergency electric power of the target automobile. The critical endurance mileage can be set according to the density degree of the new energy automobile charging station in the city, and the numerical value of the critical endurance mileage is not particularly limited in this embodiment, and can be set according to the infrastructure condition of the actual city charging station.

In this embodiment, a critical range is obtained, and the driving route information and the corrected range are combined to obtain a critical position, where the critical position is a specific position on the driving route when the target automobile drives to the critical range on the driving route.

The preset range is a circle taking the critical position as a circle center and taking a mileage difference value of the critical mileage and the corrected mileage as a radius. Acquiring a plurality of charging stations in the preset range of the critical position, and a plurality of distance information between the plurality of charging stations and the critical position, and formulating a plurality of display schemes according to the plurality of distance information.

In this embodiment, the scheme generating method of the multiple display schemes is as follows:

a plurality of sample presentation schemes are constructed, each sample presentation scheme comprising a charging station and distance information of the charging station from a critical location. The sorting rule of the plurality of distance information of the plurality of charging stations is to sort the distance information from small to large.

In this embodiment, the plurality of distance information is sorted in order of distance from small to large, and a plurality of order information corresponding to the plurality of distance information is generated. Among the plurality of order information, the higher the ranking, the smaller the distance data, i.e., the closer the charging station and the critical location distance.

And sequencing the plurality of distance information according to the sequence from small to large to obtain a plurality of real-time sequence information, wherein the plurality of real-time sequence information is the sequencing sequence of the plurality of distances, namely the priority selected by the plurality of charging stations. And obtaining a plurality of corresponding distance information and a plurality of sample display schemes specifically corresponding to the plurality of distance information based on the plurality of real-time sequence information, wherein the plurality of sample display schemes are used as the plurality of display schemes.

Based on the multiple display schemes, a target automobile driver can intuitively know that when the target automobile reaches a critical position, the target automobile needs to be charged with a battery, and priorities of multiple charging stations selectable at the critical position.

According to the embodiment, the continuous voyage management is carried out according to the actual driving situation and the driving environment of the new energy automobile, the continuous voyage management of the new energy automobile and the adaptation degree of the actual using situation of the automobile are improved, and meanwhile, the technical effect that a target automobile driver can conveniently select a charging station to supplement electric energy is achieved.

In one embodiment, as shown in fig. 3, there is provided a new energy vehicle range management system, including: the system comprises a management instruction response module 1, an environment information acquisition module 2, a continuous voyage data calculation module 3, a battery capacity calculation module 4, a continuous voyage mileage correction module 5 and a management scheme generation module 6, wherein:

The management instruction response module 1 is used for responding to a continuous voyage mileage management instruction, collecting current real-time load information and running information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile;

the environment information acquisition module 2 is used for acquiring various environment information of the current environment of the target automobile to obtain an environment information set, and inputting the environment information set into the battery attenuation analysis model to obtain a battery attenuation coefficient;

the cruising data calculation module 3 is used for inputting the load information, the road surface information in the driving information and the speed information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial cruising mileage and initial cruising time by combining the real-time battery capacity;

the battery capacity calculation module 4 is used for calculating and obtaining the attenuation battery capacity of the battery in the initial endurance time according to the initial endurance time and the battery attenuation coefficient, and calculating and obtaining the actual battery capacity;

the cruising mileage correction module 5 is used for calculating and obtaining a corrected cruising mileage according to the actual battery capacity and the driving energy consumption parameter;

And the management scheme generation module 6 is used for acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and acquiring a driving mileage management scheme by combining the corrected driving mileage to display.

In one embodiment, the system further comprises:

the load information calculation unit is used for acquiring current real-time load information of the target automobile and calculating and obtaining the load information by combining full load information of the target automobile;

the road surface information acquisition unit is used for acquiring the road surface information of the current running road of the target automobile;

the driving information obtaining unit is used for collecting driving route information and speed information of the current driving of the target automobile and obtaining the driving information by combining the road surface information;

and the battery capacity acquisition unit is used for acquiring the current real-time battery capacity of the battery of the target automobile.

In one embodiment, the system further comprises:

the environment information acquisition unit is used for acquiring temperature information and temperature information of the current environment of the target automobile to obtain the environment information set;

the sample data acquisition unit is used for acquiring a sample temperature information set and a sample humidity information set, and combining to acquire a plurality of sample environment information sets;

The attenuation coefficient obtaining unit is used for carrying out attenuation coefficient test on the battery of the target automobile under the plurality of sample environment information sets to obtain a sample battery attenuation coefficient set;

the model construction execution unit is used for constructing the battery attenuation analysis model by adopting the plurality of sample environment information sets and the sample battery attenuation coefficient sets, wherein the battery attenuation analysis model comprises an analysis coordinate system and a plurality of sample coordinate points, and each sample coordinate point is marked by a corresponding sample battery attenuation coefficient;

the model analysis execution unit is used for inputting the environment information set into the battery attenuation analysis model to obtain real-time coordinate points, and obtaining K sample coordinate points nearest to the real-time coordinate points, wherein K is an odd number greater than or equal to 3;

and the attenuation coefficient generation unit is used for acquiring K sample battery attenuation coefficients marked by the K sample coordinate points, and taking the sample battery attenuation coefficient with the highest occurrence frequency as the battery attenuation coefficient.

In one embodiment, the system further comprises:

the coordinate assignment execution unit is used for constructing an abscissa axis and an ordinate axis which are mutually perpendicular in the analysis coordinate system based on the ambient temperature and the ambient humidity;

The coordinate position generating unit is used for inputting the plurality of sample environment information sets into the analysis coordinate system to obtain a plurality of sample coordinate points;

the coordinate point marking unit is used for marking the plurality of sample coordinate points by adopting a plurality of sample battery attenuation coefficients in the sample battery attenuation coefficient set as a plurality of markers to obtain the battery attenuation analysis model.

In one embodiment, the system further comprises:

the sample information acquisition unit is used for acquiring a sample load information set, a sample road surface information set and a sample speed information set of the target automobile;

the test detection execution unit is used for combining the data in the sample load information set, the sample pavement information set and the sample speed information set, and carrying out running energy consumption test detection on the target automobile to obtain a sample running energy consumption parameter set;

the data set construction unit is used for randomly selecting M groups of data from the sample load information set, the sample pavement information set, the sample speed information set and the sample driving energy consumption parameter set respectively, so as to obtain a first construction data set, wherein M is an integer which is more than 1 and less than the number in the sample load information set;

The analysis unit construction unit is used for constructing and training to obtain a first driving energy consumption analysis unit in the driving energy consumption analysis model based on a BP neural network by adopting the first construction data set;

a data set construction generating unit for randomly selecting M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample driving energy consumption parameter set again to obtain a second construction data set,

the analysis unit generation unit is used for constructing and training to obtain a second running energy consumption analysis unit in the running energy consumption analysis model by adopting the second construction data set;

the analysis model generation unit is used for continuously constructing N-2 running energy consumption analysis units in the running energy consumption analysis model, wherein N is an integer greater than 3, and the running energy consumption analysis model is obtained according to the N running energy consumption analysis units;

and the energy consumption parameter obtaining unit is used for inputting the load information and the running information into the N running energy consumption analysis units to obtain N output results, and taking the highest occurrence frequency in the N output results as the running energy consumption parameter.

In one embodiment, the system further comprises:

The critical position obtaining unit is used for obtaining critical cruising mileage and obtaining a critical position by combining the driving route information and the corrected cruising mileage;

a distance information obtaining unit, configured to obtain a plurality of charging stations within a preset range of the critical position, and a plurality of distance information of the plurality of charging stations and the critical position;

the display scheme customizing unit is used for formulating a plurality of display schemes according to the plurality of distance information;

the information display execution unit is used for displaying the plurality of charging stations and the plurality of distance information by adopting the plurality of display schemes and displaying the corrected endurance mileage.

In one embodiment, the system further comprises:

an order information generating unit for acquiring a plurality of order information ordered in order of the distance information from small to large;

the display scheme construction unit is used for constructing a plurality of corresponding sample display schemes according to the plurality of order information;

the display scheme obtaining unit is used for sequencing the plurality of distance information according to the sequence from small to large, obtaining a plurality of real-time sequence information, and obtaining a plurality of corresponding sample display schemes as the plurality of display schemes.

For a specific embodiment of the new energy vehicle range management system, reference may be made to the above embodiment of a new energy vehicle range management method, which is not described herein. All or part of each module in the new energy automobile endurance mileage management system can be realized by software, hardware and combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing news data, time attenuation factors and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by the processor is used for realizing the new energy automobile endurance mileage management method.

Those skilled in the art will appreciate that the structures shown in FIG. 4 are block diagrams only and do not constitute a limitation of the computer device on which the present aspects apply, and that a particular computer device may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer readable storage medium is provided, comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program: responding to a continuous voyage mileage management instruction, collecting current real-time load information and traveling information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile; collecting various environmental information of the current environment of the target automobile to obtain an environmental information set, and inputting the environmental information set into a battery attenuation analysis model to obtain a battery attenuation coefficient; inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial endurance mileage and initial endurance time by combining the real-time battery capacity; according to the initial endurance time and the battery attenuation coefficient, calculating to obtain the attenuation battery capacity of the battery in the initial endurance time, and calculating to obtain the actual battery capacity; calculating to obtain a corrected endurance mileage according to the actual battery capacity and the driving energy consumption parameter; and acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and obtaining a driving mileage management scheme by combining the corrected driving mileage to display.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. The new energy automobile endurance mileage management method is characterized by comprising the following steps:

2. The method of claim 1, wherein responsive to the range management command, collecting current real-time load information and travel information for the target vehicle, and current real-time battery capacity for a battery of the target vehicle, comprises:

acquiring current real-time load information of the target automobile, and calculating to obtain the load information by combining full load information of the target automobile;

Collecting the pavement information of the current running road of the target automobile;

acquiring driving route information and speed information of the current driving of the target automobile, and combining the road surface information to obtain the driving information;

and collecting the current real-time battery capacity of the battery of the target automobile.

3. The method of claim 1, collecting a plurality of environmental information of an environment in which the target automobile is currently located, inputting the set of environmental information into a battery attenuation analysis model, and obtaining a battery attenuation coefficient, comprising:

acquiring temperature information and temperature information of the current environment of the target automobile to obtain the environment information set;

acquiring a sample temperature information set and a sample humidity information set, and combining to acquire a plurality of sample environment information sets;

under the plurality of sample environment information sets, carrying out attenuation coefficient test on the battery of the target automobile to obtain a sample battery attenuation coefficient set;

the battery attenuation analysis model is constructed by adopting the plurality of sample environment information sets and the sample battery attenuation coefficient sets, wherein the battery attenuation analysis model comprises an analysis coordinate system and a plurality of sample coordinate points, and each sample coordinate point is marked by a corresponding sample battery attenuation coefficient;

Inputting the environment information set into the battery attenuation analysis model to obtain real-time coordinate points, and obtaining K sample coordinate points nearest to the real-time coordinate points, wherein K is an odd number greater than or equal to 3;

and obtaining K sample battery attenuation coefficients marked by the K sample coordinate points, and taking the sample battery attenuation coefficient with the highest occurrence frequency as the battery attenuation coefficient.

4. The method of claim 3, wherein constructing the battery decay analysis model using the plurality of sample environmental information sets and the sample battery decay coefficient set comprises:

based on the ambient temperature and the ambient humidity, constructing an abscissa axis and an ordinate axis which are mutually perpendicular in the analysis coordinate system;

inputting the plurality of sample environment information sets into the analysis coordinate system to obtain a plurality of sample coordinate points;

and marking the plurality of sample coordinate points by adopting a plurality of sample battery attenuation coefficients in the sample battery attenuation coefficient set as a plurality of markers to obtain the battery attenuation analysis model.

5. The method of claim 1, wherein inputting the load information and the travel information into a travel energy consumption analysis model to obtain travel energy consumption parameters comprises:

Acquiring a sample load information set, a sample pavement information set and a sample speed information set of the target automobile;

combining the data in the sample load information set, the sample pavement information set and the sample speed information set, and carrying out running energy consumption test detection on the target automobile to obtain a sample running energy consumption parameter set;

randomly selecting M groups of data from the sample load information set, the sample road surface information set, the sample speed information set and the sample driving energy consumption parameter set respectively in a put-back way to obtain a first construction data set, wherein M is an integer which is more than 1 and less than the number in the sample load information set;

adopting the first construction data set, constructing and training based on a BP neural network to obtain a first driving energy consumption analysis unit in the driving energy consumption analysis model;

randomly selecting M groups of data from the sample load information set, the sample pavement information set, the sample speed information set and the sample driving energy consumption parameter set respectively with a place of return to obtain a second construction data set,

constructing and training to obtain a second driving energy consumption analysis unit in the driving energy consumption analysis model by adopting the second construction data set;

Continuously constructing N-2 running energy consumption analysis units in the running energy consumption analysis model, wherein N is an integer greater than 3, and obtaining the running energy consumption analysis model according to the N running energy consumption analysis units;

and inputting the load information and the running information into the N running energy consumption analysis units to obtain N output results, and taking the highest occurrence frequency in the N output results as the running energy consumption parameter.

6. The method of claim 1, wherein obtaining the plurality of location information of the plurality of charging stations within the preset range of the travel route information according to the travel route information in the travel information, and analyzing to obtain the range management scheme in combination with the corrected range, comprises:

obtaining a critical endurance mileage, and combining the driving route information and the corrected endurance mileage to obtain a critical position;

acquiring a plurality of charging stations in the preset range of the critical position and a plurality of distance information between the plurality of charging stations and the critical position;

according to the distance information, a plurality of display schemes are formulated;

and displaying the plurality of charging stations and the plurality of distance information by adopting the plurality of display schemes, and displaying the corrected endurance mileage.

7. The method of claim 6, wherein formulating a plurality of display scenarios based on the plurality of distance information comprises:

acquiring a plurality of order information which are ordered according to the order from small to large of the distance information;

constructing a plurality of corresponding sample display schemes according to the plurality of order information;

and sequencing the plurality of distance information according to the sequence from small to large to obtain a plurality of real-time sequence information, and obtaining a plurality of corresponding sample display schemes as the plurality of display schemes.

8. The utility model provides a new energy automobile continuation of journey mileage management system which characterized in that, the system includes:

the management instruction response module is used for responding to a continuous voyage mileage management instruction, collecting current real-time load information and running information of a target automobile and current real-time battery capacity of a battery of the target automobile, wherein the target automobile is a new energy automobile;

the environment information acquisition module is used for acquiring various environment information of the current environment of the target automobile to obtain an environment information set, and inputting the environment information set into the battery attenuation analysis model to obtain a battery attenuation coefficient;

the cruising data calculation module is used for inputting the load information, the road surface information and the speed information in the driving information into a driving energy consumption analysis model to obtain driving energy consumption parameters, and calculating to obtain initial cruising mileage and initial cruising time by combining the real-time battery capacity;

The battery capacity calculation module is used for calculating and obtaining the attenuation battery capacity of the battery in the initial endurance time according to the initial endurance time and the battery attenuation coefficient, and calculating and obtaining the actual battery capacity;

the cruising mileage correction module is used for calculating and obtaining corrected cruising mileage according to the actual battery capacity and the driving energy consumption parameter;

and the management scheme generation module is used for acquiring a charging station near the driving route information according to the driving route information in the driving information, and analyzing and acquiring a driving mileage management scheme by combining the corrected driving mileage to display.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.