CN109827588A

CN109827588A - A kind of processing method and electronic equipment

Info

Publication number: CN109827588A
Application number: CN201910174531.5A
Authority: CN
Inventors: 王耀晖; 杨帆; 张成松
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2019-03-08
Filing date: 2019-03-08
Publication date: 2019-05-31
Anticipated expiration: 2039-03-08
Also published as: CN109827588B

Abstract

This application discloses a kind of processing method and electronic equipments, determine that electric car needs the vehicle traveling information of the road segment classification and multiple electric cars in each section in the section passed through in the road segment classification when driving first, and then determine characteristic, the whole of required consumption estimates energy when being determined according to the characteristic in each section and energy rebound model or traveling duration regression model and estimate energy consumption or estimate traveling duration, and further determining that electric car by its whole section to be passed through.Estimating energy consumption and estimating traveling duration for every a road section is determined by energy rebound model and traveling duration regression model in this programme, so that it is determined that is consumed needed for all estimates energy consumption, it realizes and energy consumption during electric automobile during traveling is estimated, the possibility energy consumed required for reminding the user that the electric automobile during traveling in the process, avoids the case where energy is used up in the process of moving.

Description

A kind of processing method and electronic equipment

Technical field

This application involves process field more particularly to a kind of processing method and electronic equipments.

Background technique

Currently, have the advantages that environmental protection relative to fuel vehicle for pure electric automobile, but its mileage travelled is limited, The problem of this will lead in the process of moving, not arrive at the destination also, and the electricity of electric car has just been used up.

Summary of the invention

In view of this, the application provides a kind of processing method and electronic equipment, concrete scheme are as follows:

A kind of processing method, comprising:

The starting point and terminal determined according to user determine electric car wait for by no less than in a section each road The road segment classification of section；

For the road segment classification in each section no less than in a section and in the road segment classification when driving Vehicle traveling information extract characteristic；

Determine energy rebound model and traveling duration regression model；

The characteristic extracted according to each described section and the energy rebound model determine on each described road Energy consumption is estimated in section, and, the characteristic and traveling duration regression model extracted according to each described section determine and exist Traveling duration is estimated in each described section；

According to each section estimate energy consumption and estimate traveling duration determine the electric car by it is described to The whole consumed required for all sections in the no less than section passed through estimates energy consumption.

Further, the characteristic and the energy rebound model that described each section according to is extracted determine Energy consumption is estimated in each described section, comprising:

If the section is the first section, the starting point that first section is determined using the user is starting point, then according to institute The characteristic and the energy rebound model for stating the first section, which determine, estimates energy consumption in first section；

If the section is the second section, second section is non-first section, then is passed through according to the electric car At the time of the preceding a road section in second section and the characteristic that energy consumption determines second section is estimated, according to described second The characteristic in section and the energy rebound model, which determine, estimates energy consumption in second section.

Further, the characteristic and traveling duration regression model that described each section according to is extracted determine Traveling duration is estimated in each described section, comprising:

If the section is the first section, the starting point that first section is determined using the user is starting point, then according to institute The characteristic and traveling duration regression model for stating the first section determine and estimate traveling duration in first section；

If the section is the second section, second section is non-first section, then is passed through according to the electric car At the time of the preceding a road section in second section and the characteristic that energy consumption determines second section is estimated, according to described second The characteristic and traveling duration regression model in section determine and estimate traveling duration in second section.

Further, the characteristic includes at least: the onboard parameter of the electric car, environmental parameter, period And road section information.

Further, further includes:

Determine the physical configuration of the electric car；

It is first electronic to obtain no less than one identical with the physical configuration of the electric car stored in historical record Automobile is by characteristic, energy consumption data and the long data when driving in a no less than section when each section；

It is no less than when being no less than each section in a section described in the first electric car process according to described Characteristic, energy consumption data and long data training pattern when driving obtain energy rebound model and traveling duration regression model.

A kind of electronic equipment, comprising: processor and memory, in which:

The processor be used for according to user determine starting point and terminal determine electric car wait for by no less than one The road segment classification in each section in section, for the road segment classification in each section no less than in a section and in institute It states the vehicle traveling information in road segment classification when driving and extracts characteristic；Determine that energy rebound model and traveling duration return mould Type, the characteristic extracted according to each described section and the energy rebound model determine in each described section Energy consumption is estimated, and, the characteristic and traveling duration regression model extracted according to each described section are determined described every Estimate traveling duration in one section, according to each section estimate energy consumption and estimate traveling duration determine the electricity Whole of the electrical automobile by consumption required for all sections in a no less than section to be passed through estimates energy consumption；

The memory be used to store the electric car wait for by the road in each section no less than in a section Segment type.

Further, characteristic and the energy rebound model of the processor according to each section extraction Determination estimates energy consumption in each described section, comprising:

Further, the characteristic and travel duration regression model that the processor is extracted according to each described section Determination estimates traveling duration in each described section, comprising:

Further, the processor is also used to:

Determine the physical configuration of the electric car, it is being stored in acquisition historical record to match with electric car physics Set identical no less than first electric car by a no less than section when each section characteristic, Energy consumption data and when driving long data；According to no less than first electric car by a no less than section Characteristic, energy consumption data when each section and when driving long data training pattern, obtain energy rebound model and traveling Duration regression model.

It can be seen from the above technical proposal that processing method disclosed in the present application and electronic equipment, it is first determined electronic vapour Vehicle need the road segment classification in each section in the section passed through and multiple electric cars in the road segment classification when driving Vehicle traveling information, and then determine characteristic, according to the characteristic in each section and energy rebound model or when driving Long regression model determination estimates energy consumption or estimates traveling duration, and further determines that electric car by its whole to be passed through The whole of required consumption estimates energy when section.It is determined in this programme by energy rebound model and traveling duration regression model Every a road section estimates energy consumption and estimates traveling duration, so that it is determined that is consumed needed for all estimates energy consumption, realizes to electronic Energy consumption is estimated in vehicle traveling process, the possibility energy consumed required for reminding the user that during the electric automobile during traveling Amount, avoids the case where energy is used up in the process of moving.

Detailed description of the invention

In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this Some embodiments of application for those of ordinary skill in the art without creative efforts, can be with It obtains other drawings based on these drawings.

Fig. 1 is a kind of flow chart of processing method disclosed in the embodiment of the present application；

Fig. 2 is a kind of flow chart of processing method disclosed in the embodiment of the present application；

Fig. 3 is a kind of flow chart of processing method disclosed in the embodiment of the present application；

Fig. 4 is a kind of flow chart of processing method disclosed in the embodiment of the present application；

Fig. 5 is the structural schematic diagram of a kind of electronic equipment disclosed in the embodiment of the present application.

Specific embodiment

Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete Site preparation description, it is clear that described embodiments are only a part of embodiments of the present application, instead of all the embodiments.It is based on Embodiment in the application, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall in the protection scope of this application.

This application discloses a kind of information processing method, flow chart is as shown in Figure 1, comprising:

Step S11, the starting point and terminal determined according to user determine electric car wait for by no less than in a section The road segment classification in each section；

Determine that starting point and terminal can determine only in the case where starting point and terminal determine from starting point to end first The section of required process and the road segment classification in each section in this entire road of point.

Specifically, section can be divided according to the length of road, it may be assumed that as soon as when link length is more than first threshold, Multiple sections are divided into, specifically, can divide from the position of first threshold, such as: the first road total length is L, first threshold The first road is then determined as the first section to B since starting point A for L1, L > L1, wherein the length of A to B be L1, from B to It is determined as the second section at location of C, wherein if the distance between position is less than L1 to terminal from B location, location of C is eventually Point position, if the distance between position is greater than L1 to terminal from B, location of C is the position between terminal and B location, and B The distance set to location of C is L1, and so on, until position of reaching home；Alternatively, it is also possible to locate to divide road from the central position Section, such as: the first road total length is L, first threshold L1, L > L1, it is determined that the center between the first road starting point A and terminal B A to the section between C is determined as the first section, C to the section between B if the distance between A and C are less than L1 by position C Be determined as the second section, if the distance between A and C are greater than L1, it is determined that the center D of road between A and C, if A and D it Between distance be less than L1, then the section between A and D is determined as the first section, the section between D and C is determined as the second section, And determine the center E between C and B, the section between C and E is determined as third section, the section between E and B is determined Continue to determine the center between A and D, up to starting point and most if the distance between A and D are still greater than L1 for the 4th section Newly the distance between determining center is less than L1.

Section, the bending even occurred from this road of starting point to the end can also be divided according to the bending angle of road Angle is greater than second threshold, then this road is determined as two sections, wherein the bending that road occurs may be to go out at crossing The case where existing turn, it is also possible to for a road and non-straight, but have certain bend；

Section can also be divided according to road name, i.e., different road names is divided into different sections；

Section can also be divided according to traffic information, i.e., there may be relatively fixed different grades of on certain roads Congestion regions, such as: there are market or school on a road, then, it is possible to will appear congestion in fixed time period, gather around Stifled grade also has difference, and the section of different jam levels can be divided into different sections.

Road segment classification can be determining according to the average overall travel speed of vehicle, average acceleration, averagely parking waiting number, can also To be determined according to jam level.

Such as: average overall travel speed section first range in of the vehicle on road is determined as first kind road Section, is determined as Second Type section for section of average overall travel speed of the vehicle on road in the second range, vehicle is existed Section of the average waiting number within the scope of third is determined as third type section etc. on road.

Step S12, it the road segment classification for each section in a no less than section and is travelled in the road segment classification When vehicle traveling information extract characteristic；

Wherein, characteristic includes at least: onboard parameter, environmental parameter, period and the road section information of electric car.

Wherein, onboard parameter may include: vehicle interior temperature, vehicle internal-external temperature difference, mobile unit starting state, drive into the road Energy when section, energy when being driven out to the section etc., wherein the starting state of mobile unit such as: the starting state of air-conditioning, rain brush Deng；Environmental parameter may include: outside temperature, weather condition etc.；Road section information may include: road section length, road segment classification, road Section congestion level etc..

Specifically, vehicle interior temperature includes: the statistical values such as extreme value, mean value, quantile, segmentation statistics；Outside temperature includes: pole The statistical values such as value, mean value, quantile, segmentation statistics；Vehicle internal-external temperature difference includes: the systems such as extreme value, mean value, quantile, segmentation statistics Evaluation；Section congestion level includes: the statistical values such as extreme value, mean value, quantile, segmentation statistics；

Period can be there are two types of division mode, and equal length divides, such as: by the hour, half an hour equigranular divided；Or Person divides according to service conditions, such as: peak period morning and evening, and off-peak period etc. is divided.

For different periods or different parameter areas, it is different for travelling and complete its required energy consumption of section 's.Such as: in the identical situation of other parameters, outside temperature energy consumption required when being 30 degree spends when institute with outside temperature for -10 The energy consumption needed is different；It is also different in congested link and energy consumption needed for non-congested link；Energy when driving into section is 100% with energy when driving into be 50% needed for energy consumption be also different.

Further, the onboard parameter of electric car can be with specifically: the parameter of all mobile units of electric car, All parameters that i.e. only the model of electric car, driving parameters etc. are related to electric car identical can just think electric car Onboard parameter it is identical.

Step S13, energy rebound model and traveling duration regression model are determined；

Model is established according to the characteristic of extraction and the corresponding road segment classification of different characteristics and period, can be obtained To energy rebound model and traveling duration regression model, wherein energy rebound model, i.e., for the electricity with different vehicle parameter Electrical automobile passes through energy model required when different types of section under different environmental parameters；Duration regression model is travelled, Pass through under different environmental parameters for the electric car with different vehicle parameter required when different types of section Duration modeling.

Step S14, the characteristic and energy rebound model extracted according to each section determine in each section Estimate energy consumption, and, the characteristic and traveling duration regression model extracted according to each section determine on each road Traveling duration is estimated in section；

On the basis of establishing energy rebound model and traveling duration regression model, according to the determining electric car of user The road segment classification in each section to be passed through, can be by the road segment classification in each section, the vehicle of the electric car of user Parameter and its period that pass through each section be calculated by energy rebound model, so that it is determined that disappearing required for each section The energy of consumption；Can also by the road segment classification in each section, the electric car of user vehicle parameter and its will be by each The period in section is calculated by traveling duration regression model, so that it is determined that electric car traveling required for each section Duration.

Step S15, according to each section estimate energy consumption and estimate traveling duration determine electric car pass through wait pass through The whole no less than consumed required for all sections in a section estimate energy consumption.

Due to road segment classification be possible to by the period in the section it is relevant, when determining road segment classification, It first has to determine and therefore to determine the road segment classification in a section by the period in the section, it is necessary first to determine by upper A road section estimates traveling duration, is determining estimating traveling duration and in upper a road section estimate energy by upper a road section Consumption；Further determine that estimating energy consumption and estimating traveling duration for current road segment, and then determine lower a road section estimates energy consumption and pre- Estimate traveling duration.

All sections estimate energy consumption and estimate traveling duration determine after, can just determine from starting point to the end institute What is needed all estimates energy consumption.

Such as: 3 sections, i.e. the first section, the second section and third section are shared from starting point to the end；By the first via The Duan Shiwei non-peak period period, the energy of electric car is 100% when from starting point, is by the energy consumption of estimating in the first section 5%, it estimates a length of 30 minutes when driving；When the second section is set out, the energy of electric car is 95%, when by the second section For the non-peak period period, it is 7% by the energy consumption of estimating in the second section, estimates a length of 40 minutes when driving；Go out in third section The energy of electric car is 88% when hair, by being the non-peak period period when third section, estimates energy consumption by third section It is 10%, estimates a length of 57 minutes when driving.So, 127 minutes are needed altogether from starting point to the end, required energy consumption totally 22%.

The energy consumption that every a road section is estimated is and the parameter of current electric car, environmental parameter, period and section class Type is closely bound up, therefore, in entire distance, needs successively to calculate from starting point and estimates energy consumption and estimate traveling duration, thus It just can determine that and estimate energy consumption needed for entire complete distance and estimate traveling duration.

Processing method disclosed in the present embodiment, it is first determined in the section that electric car needs to pass through the road in each section The vehicle traveling information of segment type and multiple electric cars in the road segment classification when driving, and then determine characteristic, root Energy consumption is estimated according to the characteristic and energy rebound model or traveling duration regression model determination in each section or estimates traveling Duration, and further determine that the whole of required consumption when electric car passes through its whole section to be passed through estimates energy. Estimating energy consumption and estimating when driving for every a road section is determined by energy rebound model and traveling duration regression model in this programme It is long, so that it is determined that is consumed needed for all estimates energy consumption, realizes and energy consumption during electric automobile during traveling is estimated, to mention The possibility energy consumed required for user's electric automobile during traveling wake up in the process, avoids the feelings that energy in the process of moving is used up Condition.

Present embodiment discloses a kind of processing method, flow chart is as shown in Figure 2, comprising:

Step S21, the starting point and terminal determined according to user determine electric car wait for by no less than in a section The road segment classification in each section；

Step S22, the road segment classification for each section in a no less than section and in road segment classification when driving Vehicle traveling information extract characteristic；

Step S23, energy rebound model and traveling duration regression model are determined；

If step S24, section is the first section, the starting point that the first section is determined using user is starting point, then according to the first via The characteristic and energy rebound model of section, which determine, estimates energy consumption in the first section；

Since the energy that battery has in electric car is different, its required when finishing current road segment disappears of being expert at will lead to The energy of consumption is different；Also, electric automobile during traveling is different in the period of current road segment, will lead to it in the time of lower a road section Duan Butong, and it is different to further result in its energy for finishing and consuming required for current road segment and lower a road section of being expert at.Therefore, it is necessary to First confirm that whether current road segment is the first section, and the first section is i.e. the first section using the determining starting point of user as starting point It is first section of the required process from this entire road of starting point to the end.

If current road segment is the first section, only it needs to be determined that the characteristic and electric car in the first section are wanted Which period belonged to from the time of starting point, and is returned according to the characteristic in the first section, period and energy Return what model determined electric car consumption required for the first section to estimate energy consumption.

Such as: electric car is 9 points of the morning from the time of starting point, belongs to non-peak period period, and electric car institute The energy having is 100%, and air-conditioning, rain brush etc. are in closed state, and outdoor temperature is 20 degree, required for the first section It is 10% that the energy of consumption, which is estimated,；

If electric car is 7 points of the morning from the time of starting point, belong to the peak period period, and electric car has Energy is 100%, and air-conditioning, rain brush etc. are in closed state, and outdoor temperature is 20 degree, the consumption required for the first section It is 20% that energy, which is estimated,；

If electric car is 9 points of the morning from the time of starting point, belong to the non-peak period period, and electric car is had Energy be 70%, air-conditioning, rain brush etc. are in closed state, and outdoor temperature is 20 degree, the consumption required for the first section Energy to estimate be 15%.

By the example above it can be shown that electric car estimates energy consumption and congestion in road degree and initial in certain a road section Energy is related, it is thus necessary to determine that whether current road segment is the first section, so that whether clear need to consider that current road segment is non- When the first section, by duration required for preceding a road section and remaining energy behind whole sections before.

If step S25, section is the second section, the second section is non-first section, then passes through second according to electric car At the time of the preceding a road section in section and estimate the characteristic that energy consumption determines the second section, according to the characteristic in the second section and Energy rebound model, which determines, estimates energy consumption in the second section；

If section is the first section, only it needs to be determined that the characteristic in the first section and period, that is, can determine the A road section estimates energy consumption；If section is the second section, i.e., non-first section is then determining the same of the characteristic in the second section When, it is also necessary to determine period of electric car when by preceding a road section, and, electric car is before by the second section All sections after the energy that is consumed, i.e. primary power and electric car of the electric car when from starting point passing through Estimate the difference of energy consumption in all sections before second section required for each section, as electric car is from the second tunnel Dump energy when section is set out.

According to the characteristic in the second section of above-mentioned determination, period when by the second section, electric car from Dump energy and energy rebound model when second section is set out, that is, can determine that electric car estimates energy in the second section Consumption.

When electric car has been determined in every a road section after estimating energy consumption, energy consumption addition is estimated by every a road section With can determine that electric car all estimates energy consumption required for starting point to the end.So as to before starting point, In the case where the current primary power of known electric car, determine whether primary power can support electric car to travel from starting point To terminal, it to remind user, is used up to avoid energy in the process of moving, the problem of vehicle can not travel.

Step S26, the characteristic and traveling duration regression model extracted according to each section determine on each road Traveling duration is estimated in section；

Step S27, according to each section estimate energy consumption and estimate traveling duration determine electric car pass through wait pass through The whole no less than consumed required for all sections in a section estimate energy consumption.

Present embodiment discloses a kind of processing method, flow chart is as shown in Figure 3, comprising:

Step S31, the starting point and terminal determined according to user determine electric car wait for by no less than in a section The road segment classification in each section；

Step S32, it the road segment classification for each section in a no less than section and is travelled in the road segment classification When vehicle traveling information extract characteristic；

Step S33, energy rebound model and traveling duration regression model are determined；

If step S34, section is the first section, the starting point that the first section is determined using user is starting point, then according to the first via The characteristic and traveling duration regression model of section determine and estimate traveling duration in the first section；

If step S35, section is the second section, the second section is non-first section, then passes through second according to electric car At the time of the preceding a road section in section and estimate the characteristic that energy consumption determines the second section, according to the characteristic in the second section and Traveling duration regression model, which determines, estimates traveling duration in the second section；

Since the period exercised in section in electric car is different, its institute when finishing current road segment of being expert at will lead to The energy for needing to consume is different；Also, electric automobile during traveling is different in the period of current road segment, will lead to it in lower a road section Period it is different, and it is different to further result in its energy for finishing and consuming required for current road segment and lower a road section of being expert at.Cause This, needs to first confirm that whether current road segment is the first section, and the first section is the starting point that is determined using user as starting point, i.e., the A road section is first section of the required process from this entire road of starting point to the end.

If current road segment is the first section, only it needs to be determined that the characteristic and electric car in the first section are wanted Belong to which period from the time of starting point, and according to the characteristic in the first section, period and when driving Long regression model determines that electric car estimates traveling duration in the first section.

Such as: electric car is 9 points of the morning from the time of starting point, belongs to non-peak period period, and electric car institute The energy having is 100%, and air-conditioning, rain brush etc. are in closed state, and outdoor temperature is 20 degree, required for the first section Estimate a length of 30 minutes when driving；

If electric car is 7 points of the morning from the time of starting point, belong to the peak period period, and electric car has Energy is 100%, and air-conditioning, rain brush etc. are in closed state, and outdoor temperature is 20 degree, is estimated required for the first section A length of 50 minutes when driving.

By the example above it can be shown that electric car estimates traveling duration and congestion in road degree in certain a road section, I.e. the traveling period is related, it is thus necessary to determine that whether current road segment is the first section, so that whether clear need to consider currently When section is non-first section, by duration required for preceding a road section and remaining energy behind whole sections before Amount.

If section is the first section, only it needs to be determined that the characteristic in the first section and period, that is, can determine the A road section estimates traveling duration；If section is the second section, i.e., non-first section, then in the characteristic for determining the second section While, it is also necessary to determine period of electric car when by preceding a road section, and, electric car is passing through the second section The primary power and electric car of the energy consumed behind all sections before, i.e. electric car when from starting point exist By estimating the difference of energy consumption required for each section in all sections before the second section, as electric car is from Dump energy when two sections are set out.

According to the characteristic in the second section of above-mentioned determination, period when by the second section, electric car from Dump energy and traveling duration regression model when second section is set out, that is, can determine electric car estimating in the second section Travel duration.

When determined electric car every a road section estimate traveling duration after, row can be estimated according to every a road section That sails that duration determines every a road section estimates energy consumption, and the sum of energy consumption addition is estimated by every a road section, that is, can determine electric car from Energy consumption is all estimated required for starting point to the end.So as to before starting point, it is known that electric car it is current just In the case where beginning energy, determine primary power whether can support electric car from starting point traveling to terminal, thus to user into The problem of row is reminded, and is used up to avoid energy in the process of moving, and vehicle can not travel.

Step S36, the characteristic and energy rebound model extracted according to each section determine in each section Estimate energy consumption；

Step S37, according to each section estimate energy consumption and estimate traveling duration determine electric car pass through wait pass through The whole no less than consumed required for all sections in a section estimate energy consumption.

Present embodiment discloses a kind of processing method, flow chart is as shown in Figure 4, comprising:

Step S41, the starting point and terminal determined according to user determine electric car wait for by no less than in a section The road segment classification in each section；

Step S42, it the road segment classification for each section in a no less than section and is travelled in the road segment classification When vehicle traveling information extract characteristic；

Step S43, the physical configuration of electric car is determined；

Step S44, no less than one first identical with the physical configuration of electric car stored in historical record is obtained Electric car is by the characteristic, energy consumption data and the long data when driving that are no less than when each section in a section；

Step S45, through when being no less than each section in a section according to no less than first electric car Characteristic, energy consumption data and long data training pattern when driving obtain energy rebound model and traveling duration regression model；

The physical configuration of electric car may include: engine configuration parameter, battery capacity, torque, wheelbase, vehicle body weight Amount, wheel braking etc..

Only in the case that vehicle model, physical configuration are identical, when passing through at the same time with a road section, Required energy and duration just can be identical, have either case different, then will lead to the energy difference for needing to consume or duration not Together, therefore, when carrying out model training, the identical multiple electric cars of physical configuration can be passed through to spy when different sections of highway It levies data, energy consumption data and long data carries out model training respectively when driving, to obtain more accurate two training patterns, i.e., Energy rebound model and traveling duration regression model, in order to when carrying out energy consumption and estimating or travel duration and estimate, according to road conditions, Characteristic, period and the regression model of vehicle obtain estimating energy consumption and estimate traveling duration.

Step S46, the characteristic and energy rebound model extracted according to each section determine in each section Estimate energy consumption, and, the characteristic and traveling duration regression model extracted according to each section determine on each road Traveling duration is estimated in section；

Step S47, according to each section estimate energy consumption and estimate traveling duration determine electric car pass through wait pass through The whole no less than consumed required for all sections in a section estimate energy consumption.

Present embodiment discloses a kind of electronic equipment, structural schematic diagram is as shown in Figure 5, comprising:

Processor 51 and memory 52.

Wherein, processor 51 be used for according to user determine starting point and terminal determine electric car wait for by no less than one The road segment classification in each section in a section, for the road road segment classification Ji Gai in each section in a no less than section Vehicle traveling information in segment type when driving extracts characteristic；Determine energy rebound model and traveling duration regression model, The characteristic and energy rebound model extracted according to each section determine the energy consumption of estimating in each section, and, The characteristic and traveling duration regression model extracted according to each section determine estimating when driving in each section It is long, estimating energy consumption and estimating traveling duration and determine electric car by a no less than road to be passed through according to each section The whole consumed required for all sections in section estimates energy consumption；

Memory 52 be used to store electric car wait for by the road segment classification in each section no less than in a section, The characteristic etc. of extraction can also be stored with storage energy regression model and traveling duration regression model.

Further, the characteristic and energy rebound model that processor 51 is extracted according to each section are determined each Energy consumption is estimated in a section, specifically:

If section is the first section, the starting point that the first section is determined using user is starting point, then according to the feature in the first section Data and energy rebound model, which determine, estimates energy consumption in the first section；If section is the second section, the second section is non-first The characteristic that energy consumption determines the second section at the time of then passing through the preceding a road section in the second section according to electric car and is estimated in section According to being determined according to the characteristic in the second section and energy rebound model and estimate energy consumption in the second section；

Further, the characteristic and traveling duration regression model that processor 51 is extracted according to each section determine Traveling duration is estimated in each section, specifically:

If section is the first section, the starting point that the first section is determined using user is starting point, then according to the feature in the first section Data and traveling duration regression model determine and estimate traveling duration in the first section；If section is the second section, the second section For non-first section, then at the time of passing through the preceding a road section in the second section according to electric car and estimates energy consumption and determine the second section Characteristic, according to the characteristic in the second section and traveling duration regression model determine estimating when driving in the second section It is long.

Processor 51 is also used to: being determined the physical configuration of electric car, is obtained store in historical record and electric car Identical no less than first electric car of physical configuration by the feature that is no less than when each section in a section Data, energy consumption data and long data when driving, it is every in a section by being no less than according to no less than first electric car Characteristic, energy consumption data when one section and when driving long data training pattern obtain energy rebound model and when driving Long regression model.

Electronic equipment disclosed in the present embodiment, processor determine that electric car needs each road in the section passed through first Vehicle traveling information of the road segment classification and multiple electric cars of section in the road segment classification when driving, and then determine characteristic According to determining according to the characteristic in each section and energy rebound model or traveling duration regression model and estimate energy consumption or estimate The whole of required consumption estimates energy when travelling duration, and further determining that electric car by its whole section to be passed through Amount.Estimating energy consumption and estimating traveling for every a road section is determined by energy rebound model and traveling duration regression model in this programme Duration is realized and is estimated to energy consumption during electric automobile during traveling so that it is determined that is consumed needed for all estimates energy consumption, thus User's electric automobile during traveling required possibility energy consumed in the process is reminded, avoids what energy in the process of moving was used up Situation.

Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part It is bright.

Professional further appreciates that, unit described in conjunction with the examples disclosed in the embodiments of the present disclosure And algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware and The interchangeability of software generally describes each exemplary composition and step according to function in the above description.These Function is implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Profession Technical staff can use different methods to achieve the described function each specific application, but this realization is not answered Think beyond scope of the present application.

The step of method described in conjunction with the examples disclosed in this document or algorithm, can directly be held with hardware, processor The combination of capable software module or the two is implemented.Software module can be placed in random access memory (RAM), memory, read-only deposit Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology In any other form of storage medium well known in field.

The foregoing description of the disclosed embodiments makes professional and technical personnel in the field can be realized or use the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein General Principle can be realized in other embodiments without departing from the spirit or scope of the application.Therefore, the application It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one The widest scope of cause.

Claims

1. a kind of processing method, comprising:

The starting point and terminal determined according to user determine electric car wait for by each section no less than in a section Road segment classification；

Road segment classification for each section in a no less than section and the vehicle in the road segment classification when driving Driving information extracts characteristic；

Determine energy rebound model and traveling duration regression model；

The characteristic extracted according to each described section and the energy rebound model determine in each described section Estimate energy consumption, and, the characteristic and traveling duration regression model extracted according to each described section are determined described Traveling duration is estimated in each section；

Estimating energy consumption and estimating traveling duration and determine the electric car by described wait pass through according to each section The whole no less than consumed required for all sections in a section estimate energy consumption.

2. according to the method described in claim 1, wherein, characteristic that described each section according to is extracted and described The determination of energy rebound model estimates energy consumption in each described section, comprising:

If the section is the first section, the starting point that first section is determined using the user is starting point, then according to described the The characteristic of a road section and the energy rebound model, which determine, estimates energy consumption in first section；

If the section is the second section, second section is non-first section, then according to electric car process At the time of the preceding a road section in the second section and the characteristic that energy consumption determines second section is estimated, according to second section Characteristic and the energy rebound model determine and in second section estimate energy consumption.

3. according to the method described in claim 1, wherein, characteristic and traveling that described each section according to is extracted The determination of duration regression model estimates traveling duration in each described section, comprising:

If the section is the first section, the starting point that first section is determined using the user is starting point, then according to described the The characteristic and traveling duration regression model of a road section determine and estimate traveling duration in first section；

If the section is the second section, second section is non-first section, then according to electric car process At the time of the preceding a road section in the second section and the characteristic that energy consumption determines second section is estimated, according to second section Characteristic and traveling duration regression model determine and in second section estimate traveling duration.

4. according to the method described in claim 1, wherein, the characteristic includes at least: the vehicle-mounted ginseng of the electric car Number, environmental parameter, period and road section information.

5. according to the method described in claim 1, wherein, further includes:

Determine the physical configuration of the electric car；

Obtain no less than first electric car identical with the physical configuration of the electric car stored in historical record By the characteristic no less than in a section when each section, energy consumption data and long data when driving；

According to no less than first electric car by the feature in a no less than section when each section Data, energy consumption data and long data training pattern when driving obtain energy rebound model and traveling duration regression model.

6. a kind of electronic equipment, comprising: processor and memory, in which:

The processor be used for according to user determine starting point and terminal determine electric car wait for by no less than a section In each section road segment classification, for the road segment classification in each section no less than in a section and on the road Vehicle traveling information in segment type when driving extracts characteristic；Determine energy rebound model and traveling duration regression model, The characteristic extracted according to each described section and energy rebound model determination are pre- in each described section Estimate energy consumption, and, the characteristic and traveling duration regression model extracted according to each described section are determined described each Estimate traveling duration in a section, according to each section estimate energy consumption and estimate traveling duration determine it is described electronic Whole of the automobile by consumption required for all sections in a no less than section to be passed through estimates energy consumption；

The memory be used to store the electric car wait for by the section class in each section no less than in a section Type.

7. electronic equipment according to claim 6, wherein the feature that the processor is extracted according to each described section Data and energy rebound model determination estimate energy consumption in each described section, comprising:

8. electronic equipment according to claim 6, wherein the feature that the processor is extracted according to each described section Data and traveling duration regression model determination estimate traveling duration in each described section, comprising:

9. electronic equipment according to claim 6, wherein the characteristic includes at least: the vehicle of the electric car Carry parameter, environmental parameter, period and road section information.

10. electronic equipment according to claim 6, wherein the processor is also used to:

It determines the physical configuration of the electric car, obtains the physical configuration phase with the electric car stored in historical record Same no less than first electric car is by characteristic, the energy consumption in a no less than section when each section Data and when driving long data；According to no less than first electric car by each in a no less than section Characteristic, energy consumption data when a section and when driving long data training pattern obtain energy rebound model and traveling duration Regression model.