CN115837863A

CN115837863A - Method and device for detecting driving mileage of vehicle

Info

Publication number: CN115837863A
Application number: CN202211603747.7A
Authority: CN
Inventors: 董文孔
Original assignee: Chongqing Changan Automobile Co Ltd
Current assignee: Chongqing Changan Automobile Co Ltd
Priority date: 2022-12-13
Filing date: 2022-12-13
Publication date: 2023-03-24

Abstract

The application relates to the technical field of new energy automobiles, in particular to a method and a device for detecting the endurance mileage of a vehicle, wherein the method comprises the following steps: the method comprises the steps of recognizing the current driving scene of a vehicle, the actual habit of a driver and the environmental factors of the environment, reading the actual vehicle parameters of the vehicle, respectively calculating the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, arbitrating the final energy consumption coefficient, and obtaining the actual driving mileage of the vehicle according to the final energy consumption coefficient. The embodiment of the application can arbitrate the final energy consumption coefficient based on different driving scene recognition, driver habit recognition, environmental factor recognition and vehicle parameter reading, so that the endurance mileage detection of the vehicle can be suitable for different vehicle working conditions, the accuracy and the reliability of the endurance mileage calculation result are guaranteed, the mileage anxiety of a user is reduced, and the use requirements of the user are met.

Description

Method and device for detecting driving mileage of vehicle

Technical Field

The application relates to the technical field of new energy automobiles, in particular to a method and a device for detecting the endurance mileage of a vehicle.

Background

With the popularization of new energy automobiles, the number of electric car users is increased, and charging public facilities are gradually improved, but the problems of difficult charging and slow charging still exist in the use process of the electric car, and the electric car is limited by the charging convenience, so that accurate driving mileage estimation is needed to solve the mileage anxiety brought to the users by the charging problem.

In the related art, the practical engineering application of driving range estimation generally refers to battery residual energy and vehicle energy consumption to calculate driving range, or an algorithm for calculating driving range based on SOC (State of Charge) is used to map SOC and driving range to represent the distance that a certain amount of residual energy can drive under the design condition, or an algorithm for calculating driving range based on energy consumption is used to estimate driving range based on current energy consumption under different conditions from the ratio of residual energy to energy consumption.

However, in the related art, because there is a deviation in calculating the remaining energy of the battery, the energy consumption of the vehicle driving changes dynamically in real time, and the difference between the actual driving range and the estimated value is large due to the large difference between the specific calibration working conditions in the actual use and the research and development process of the vehicle, and because the selection of the time slice has an influence on the accuracy of the estimated driving range value during the real-time calculation of the energy consumption, it is difficult to ensure the reliability of the driving range detection under different working conditions of the vehicle during the actual driving, the universality and the accuracy of the driving range detection are reduced, the user experience is reduced, and the need to be solved urgently.

Disclosure of Invention

The application provides a method and a device for detecting the driving range of a vehicle, and aims to solve the problems that in the related technology, because the calculation of the residual energy of a battery has deviation, the energy consumption of the vehicle running changes dynamically in real time, and the difference between the actual use of the vehicle and the specific calibration working condition in the research and development process is large, the error between the actual driving range and the estimated value is obvious, and because of the real-time calculation of the energy consumption, the selection of a time segment has the influence on the accuracy of the estimated driving range value, so that the reliability of the driving range detection of the vehicle under different working conditions is difficult to ensure in the actual driving, the universality and the accuracy of the driving range detection are reduced, and the use experience of a user is influenced.

An embodiment of a first aspect of the present application provides a method for detecting a driving range of a vehicle, including the following steps: the method comprises the steps of recognizing the current driving scene of a vehicle, the actual habits of a driver and the environmental factors of the environment, and simultaneously reading the actual vehicle parameters of the vehicle; calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value and an energy consumption correction coefficient according to the current driving scene, the actual habit of the driver, the environmental factors of the environment and the actual vehicle parameters; arbitrating a final energy consumption coefficient according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, and obtaining the actual endurance mileage of the vehicle according to the final energy consumption coefficient.

According to the technical means, the final energy consumption coefficient can be arbitrated based on different driving scene recognition, driver habit recognition, environmental factor recognition and vehicle parameter reading, the endurance mileage detection of the vehicle can be suitable for different vehicle working conditions, the accuracy and the reliability of the endurance mileage calculation result are guaranteed, accordingly, the mileage anxiety of a user is reduced, and the use requirements of the user are met.

Optionally, in an embodiment of the application, the obtaining the actual driving range of the vehicle according to the final energy consumption coefficient includes: acquiring an actual battery state of charge (SOC) value of the vehicle, and matching a first endurance mileage of the vehicle according to the actual SOC value; calculating a second driving range of the vehicle according to the available residual energy and real-time energy consumption of the battery of the vehicle; and calculating the actual endurance mileage according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient.

According to the technical means, the actual SOC value of the battery of the vehicle can be obtained, the first endurance mileage of the vehicle is matched according to the actual SOC value, the second endurance mileage of the vehicle is calculated according to the available residual energy and the real-time energy consumption of the battery of the vehicle, the actual endurance mileage is calculated according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient, the second endurance mileage is calculated by selecting the latest time segment, the accuracy of the actual endurance mileage calculation result is guaranteed, multiple algorithms are combined for operation, the comprehensiveness of the obtained actual endurance mileage data is improved, and the error rate of the mileage result is reduced.

Optionally, in an embodiment of the present application, the calculation formula of the actual mileage is:

S＝S _SOC +r*(S _R -S _SOC )，

wherein S is the estimated driving range, S _SOC Is the first endurance mileage, r is the energy consumption coefficient, S _E And the second endurance mileage.

According to the technical means, the calculation formula of the actual endurance mileage can be provided, and the calculation effect of reducing the estimation deviation under the condition of adapting to different driving conditions can be achieved by presetting the parameters of the relevant influence factors according to the algorithm and calibrating and optimizing the actual vehicle model according to the formula.

Optionally, in an embodiment of the present application, the method further includes: and generating interactive content according to the actual driving mileage, and controlling at least one acoustic reminding device and/or at least one optical reminding device of the vehicle to remind the interactive content.

According to the technical means, the interactive content can be generated according to the actual endurance mileage, the at least one acoustic reminding device and/or the at least one optical reminding device of the vehicle are controlled to prompt the interactive content, the actual endurance state of the current vehicle can be rapidly and intuitively known by a user through information interaction of the endurance mileage to the user, and the interaction level of the vehicle is improved.

Optionally, in an embodiment of the present application, the generating interactive content according to the actual driving range includes: and generating an optimal charging SOC based on the actual driving mileage, the actual environment temperature and the current battery state, and determining an optimal charging position, charging time and/or prompt information according to the current driving scene.

According to the technical means, the optimal charging SOC can be generated based on the actual driving mileage, the actual environment temperature and the current battery state, the optimal charging position, the charging time and/or the prompt information are determined according to the current driving scene, and the comprehensive driving related information is provided for the user, so that the mileage anxiety of the user in the vehicle using process can be effectively reduced, the vehicle automation degree is improved, and the use by the user is facilitated.

Optionally, in an embodiment of the present application, the calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value, and an energy consumption correction coefficient according to the current driving scene, the actual habit of the driver, the environmental factor of the environment, and the actual vehicle parameter respectively includes: importing the current driving scene into a preset driving scene model, and outputting the scene energy consumption correction coefficient; importing the actual habit into a preset driver model, and outputting the initial energy consumption correction coefficient; matching corresponding energy consumption correction coefficients according to the actual vehicle parameters; and identifying the state of the vehicle thermal management system according to the environmental factors to calculate the energy consumption coefficient compensation value.

According to the technical means, the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient can be respectively obtained, and the obtained related data of different vehicles are respectively processed, so that the required specific numerical value is provided for the endurance mileage calculation, and the data processing level in the endurance mileage calculation process is improved.

An embodiment of a second aspect of the present application provides a driving range detection apparatus for a vehicle, including: the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for reading the actual vehicle parameters of a vehicle while identifying the current driving scene of the vehicle, the actual habits of a driver and the environmental factors of the environment where the driver is located; the calculation module is used for calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value and an energy consumption correction coefficient according to the current driving scene, the actual habit of the driver, the environmental factors of the environment and the actual vehicle parameters; and the detection module is used for arbitrating a final energy consumption coefficient according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, and obtaining the actual endurance mileage of the vehicle according to the final energy consumption coefficient.

Optionally, in an embodiment of the present application, the detection module includes: the first matching unit is used for acquiring the actual SOC value of the battery of the vehicle and matching the first endurance mileage of the vehicle according to the actual SOC value; the first calculation unit is used for calculating a second endurance mileage of the vehicle according to the available residual energy of the battery of the vehicle and the real-time energy consumption; and the second calculating unit is used for calculating the actual endurance mileage according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient.

Optionally, in an embodiment of the present application, the calculation formula of the actual driving range is:

S＝S _SOC +r*(S _E -S _SOC )，

Optionally, in an embodiment of the present application, the apparatus further includes: and the interaction module is used for generating interaction content according to the actual endurance mileage and controlling at least one acoustic reminding device and/or at least one optical reminding device of the vehicle to remind the interaction content.

Optionally, in an embodiment of the present application, the interaction module includes: and the generating unit is used for generating the optimal charging SOC based on the actual driving mileage, the actual environment temperature and the current battery state, and determining the optimal charging position, the charging time and/or the prompt information according to the current driving scene.

Optionally, in an embodiment of the present application, the calculation module includes: the first output unit is used for importing the current driving scene into a preset driving scene model and outputting the scene energy consumption correction coefficient; the second output unit is used for importing the actual habits into a preset driver model and outputting the initial energy consumption correction coefficient; the second matching unit is used for matching the corresponding energy consumption correction coefficient according to the actual vehicle parameter; and the third calculation unit is used for identifying the state of the vehicle thermal management system according to the environmental factors so as to calculate the energy consumption coefficient compensation value.

An embodiment of a third aspect of the present application provides a vehicle, comprising: the device comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the driving range detection method of the vehicle according to the embodiment.

A fourth aspect of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements a range detection method for a vehicle as above.

The beneficial effect of this application:

(1) The embodiment of the application can arbitrate the final energy consumption coefficient based on different driving scene recognition, driver habit recognition, environmental factor recognition and vehicle parameter reading, so that the endurance mileage detection of the vehicle can be suitable for different vehicle working conditions, the accuracy and the reliability of the endurance mileage calculation result are guaranteed, the mileage anxiety of a user is reduced, and the use requirements of the user are met.

(2) The embodiment of the application can acquire the actual SOC value of the battery of the vehicle, and the first endurance mileage of the vehicle is matched according to the actual SOC value, the second endurance mileage of the vehicle is calculated according to the available residual energy of the battery of the vehicle and the real-time energy consumption, the actual endurance mileage is calculated according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient, the second endurance mileage is calculated by selecting the latest time segment, the accuracy of the actual endurance mileage calculation result is guaranteed, multiple algorithms are combined for operation, the comprehensiveness of the obtained actual endurance mileage data is improved, and the error rate of the mileage result is reduced.

(3) The embodiment of the application can generate the optimal charging SOC based on the actual endurance mileage, the actual environment temperature and the current battery state, determine the optimal charging position, charging time and/or prompt information according to the current driving scene, and effectively reduce the mileage anxiety of the user in the vehicle using process by providing the user with comprehensive endurance related information, thereby improving the vehicle automation degree and facilitating the use of the user.

Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 is a flowchart of a method for detecting a driving range of a vehicle according to an embodiment of the present disclosure;

FIG. 2 is a diagram illustrating a relationship between SOC and estimated driving range according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a range estimation software architecture according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of a mileage detecting device of a vehicle according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a vehicle according to an embodiment of the present application.

10-a driving range detection device of the vehicle; 100-an acquisition module, 200-a calculation module and 300-a detection module; 501-memory, 502-processor and 503-communication interface.

Detailed Description

Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.

The following describes a driving range detection method and device of a vehicle according to an embodiment of the present application with reference to the drawings. In the related technology mentioned in the background technology center, because the calculation of the residual energy of the battery has deviation, the energy consumption of the running of the vehicle dynamically changes in real time, and the difference between the actual use of the vehicle and the specific calibration working condition in the research and development process is large, so that the error between the actual driving range and the estimated value is obvious, and because the energy consumption is calculated in real time, the selection of the time segment has influence on the accuracy of the estimated driving range value, so that the reliability of the driving range detection under different working conditions of the vehicle is difficult to ensure in the actual driving, the universality and the accuracy of the driving range detection are reduced, and the user experience is influenced. Therefore, the problems that in the related art, due to the fact that deviation exists in calculation of the residual energy of the battery, the energy consumption of vehicle running changes dynamically in real time, and the difference between the actual use of the vehicle and the specific calibration working condition in the research and development process is large, the error between the actual driving range and the estimated value is obvious, and due to the fact that the energy consumption is calculated in real time, the accuracy of the estimated driving range value is affected due to the fact that time segments are selected, the reliability of driving range detection under different working conditions of the vehicle is difficult to ensure in actual driving, the universality and the accuracy of the driving range detection are reduced, and the use experience of a user is affected are solved.

Specifically, fig. 1 is a schematic flowchart of a method for detecting a driving range of a vehicle according to an embodiment of the present disclosure.

As shown in fig. 1, the method for detecting the driving range of the vehicle includes the following steps:

in step S101, the actual vehicle parameters of the vehicle are read while recognizing the current driving scene of the vehicle, the actual habits of the driver, and the environmental factors of the environment in which the vehicle is located.

It can be understood that, in the embodiment of the present application, the current driving scenario of the vehicle may be a geographic location of a road driven by the current vehicle, road condition information, a traffic condition, a driving speed, and the like, an actual habit of the driver may be a driving style corresponding to the driver, the vehicle may perform statistics by driving for a duration of the driver, an environmental factor of the environment where the vehicle is located may be an environmental temperature of the environment where the vehicle is located, and an actual vehicle parameter of the vehicle may be a real-time running state corresponding to the vehicle.

In some embodiments, the current driving scene of the vehicle may be identified by a human-computer interaction system whether a navigation plan exists, if the navigation plan exists, information such as a distance of a navigation planned path, a maximum vehicle speed, a minimum vehicle speed, a congestion index and the like is acquired from the navigation system in real time, the actual habit of the driver may be identified by inputting different driver IDs to identify corresponding IDs to match driving styles accumulated by the driver, the environmental factor identifying the environment may be acquired by detecting the ambient temperature in real time, and the actual vehicle parameters of the identified vehicle may include states such as whether a static thermal management system works, static charging, driving, feedback and the like.

The embodiment of the application can identify the current driving scene of the vehicle, the actual habits of the driver and the environmental factors of the environment, read the actual vehicle parameters of the vehicle, and improve the comprehensiveness of data preparation by performing multi-aspect data identification and data acquisition on the current vehicle state, thereby providing a sufficient data source for further performing data processing in the following steps.

In step S102, a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value, and an energy consumption correction coefficient are calculated according to the current driving scene, the actual habits of the driver, the environmental factors of the environment, and the actual vehicle parameters, respectively.

It can be understood that in the embodiment of the present application, the scene energy consumption correction coefficient is calculated according to the identified driving scene, the initial energy consumption correction coefficient is calculated according to the driving habit of the identified driver, the energy consumption coefficient compensation value is calculated according to the environmental factor of the environment where the identified vehicle is located, and the energy consumption correction coefficient is calculated according to the identified actual vehicle parameter.

According to the method and the device, the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient can be calculated according to the current driving scene, the actual habit of the driver, the environmental factors of the environment and the actual vehicle parameters, the corresponding vehicle state value is obtained by further analyzing and processing the identified data, the variable factor of the vehicle endurance mileage is further analyzed, and the accuracy and the intelligence of the vehicle endurance mileage data processing process are improved.

Optionally, in an embodiment of the present application, calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value, and an energy consumption correction coefficient according to a current driving scene, an actual habit of a driver, an environmental factor of an environment, and an actual vehicle parameter, respectively, includes: importing a current driving scene into a preset driving scene model, and outputting a scene energy consumption correction coefficient; importing the actual habit into a preset driver model, and outputting an initial energy consumption correction coefficient; matching corresponding energy consumption correction coefficients according to actual vehicle parameters; and identifying the state of the vehicle thermal management system according to the environmental factors to calculate the energy consumption coefficient compensation value.

It can be understood that the preset driving scene model in the embodiment of the application can process driving scene information in the navigation plan identified by the human-computer interaction system, and the preset model performs data processing to obtain the scene energy consumption correction coefficient. The preset driver model can process the driving style of the driver with the corresponding ID counted in a certain time to obtain an initial energy consumption correction coefficient.

It should be noted that the preset driving scene model and the preset driver model are trained and constructed by those skilled in the art according to actual situations, and are not limited specifically herein.

In some embodiments, the driving scene information in the identified navigation system may be imported into the corresponding driving scene model, and the energy consumption correction coefficient of the corresponding scene may be output according to the model. And importing the actual driving habits of the drivers corresponding to the ID into a driver model to output a corresponding driver energy consumption correction coefficient, and storing the parameter when the driver is powered off so as to read and directly use the parameter when the driver is powered on again in the follow-up process, wherein the parameter is used as the initial energy consumption correction coefficient of the driver ID. And selecting the corresponding energy consumption correction coefficient by matching the identified actual vehicle parameters, and simultaneously considering the smoothness of working condition switching. And obtaining an environmental parameter according to the environmental temperature of the environment where the identified vehicle is located, judging the state of the vehicle thermal management system, and calculating to obtain the energy consumption coefficient compensation so as to compensate the energy consumption in advance.

According to the method and the device, the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient can be obtained respectively, and the obtained related data of different vehicles are processed respectively, so that a required specific numerical value is provided for the endurance mileage calculation, and the data processing level in the endurance mileage calculation process is improved.

In step S103, a final energy consumption coefficient is arbitrated according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value, and the energy consumption correction coefficient, and an actual cruising mileage of the vehicle is obtained according to the final energy consumption coefficient.

It can be understood that in the embodiment of the present application, the final energy consumption coefficient may be obtained by data processing of the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value, and the energy consumption correction coefficient, and the actual cruising range of the vehicle is the actual cruising range of the vehicle obtained by the final detection.

For example, the obtained scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient may be injected into a preset calculation model for data processing, so as to obtain a final energy consumption coefficient, at this time, the calculation model may perform calculation according to real-time data to obtain a real-time final energy consumption coefficient value, or the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient are added to obtain a final energy consumption coefficient, or the final energy consumption coefficient is matched based on the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient. The specific arbitration rules in the embodiments of the present application are not specifically limited herein, and those skilled in the art can set the arbitration rules according to actual situations.

According to the method and the device, the final energy consumption coefficient can be arbitrated according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, the actual endurance mileage of the vehicle can be obtained according to the final energy consumption coefficient, the endurance mileage of the vehicle can be detected to be suitable for different vehicle working conditions, and the obtained final endurance mileage result is more comprehensive and accurate.

Optionally, in an embodiment of the present application, obtaining the actual driving range of the vehicle according to the final energy consumption coefficient includes: acquiring an actual SOC value of a battery of the vehicle, and matching a first endurance mileage of the vehicle according to the actual SOC value; calculating a second endurance mileage of the vehicle according to the available residual energy and the real-time energy consumption of the battery of the vehicle; and calculating the actual endurance mileage according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient.

It is understood that, in the embodiment of the present application, the first mileage may be a mileage calculation result obtained by matching the actual SOC value, and the second mileage may be a mileage calculation result obtained by matching the available remaining energy of the battery and the real-time energy consumption of the vehicle.

Specifically, as shown in fig. 2, a corresponding relationship diagram of the SOC and the estimated driving range according to an embodiment of the present application may implement a matching process between the actual SOC value and the first driving range of the vehicle.

The corresponding relation between the actual SOC value and the estimated endurance mileage is solidified through a vehicle power system design stage, vehicle economy simulation, vehicle endurance mileage design and battery capacity matching, actual vehicle test verification and optimized calibration parameters, so that the specific corresponding relation between different SOCs and the first endurance mileage is obtained finally, and the electric quantity attenuation in the life cycle of the battery is also considered. In the figure, 100% of the battery SOC corresponds to the initial maximum mileage, the maximum available SOC corresponds to the maximum driving range, and the minimum available SOC corresponds to the minimum driving range, i.e., 0km. And the remaining energy available from the battery of the vehicle can be supplied by

Battery available remaining energy = battery nominal capacity (SOC-minimum available SOC)

And (6) obtaining. The real-time energy consumption can be estimated by calculating the average energy consumption of every 1km driven in real time and storing the latest 300 average energy consumption of 1km by an array. Calculating a second range of the vehicle based on the remaining battery energy and the real-time energy consumption as the second range = remaining energy available from the battery/real-time energy consumption,

wherein, the real-time energy consumption is the average energy consumption of the selected latest time slice.

The method and the device can acquire the actual SOC value of the battery of the vehicle, match the first endurance mileage of the vehicle according to the actual SOC value, calculate the second endurance mileage of the vehicle according to the available residual energy and the real-time energy consumption of the battery of the vehicle, calculate the actual endurance mileage according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient, calculate the second endurance mileage by selecting the latest time segment, ensure the accuracy of the calculation result of the actual endurance mileage, and combine operation by using multiple algorithms, improve the comprehensiveness of the actual endurance mileage data, and reduce the error rate of the mileage result.

Optionally, in an embodiment of the present application, the calculation formula of the actual endurance mileage is:

S＝S _SOC +r*(S _E -S _SOC )，

In the actual implementation process, the energy consumption coefficient r ranges from 0 to 1, so that if r is larger, the result is biased to S _E With smaller r the result is biased towards S _SOC . And setting initial energy consumption setting, namely rapidly approaching to real-time energy consumption when the difference between the initial energy consumption and the current driving actual energy consumption is large.

According to the formula, the calculation effect of reducing the estimation deviation under the condition of adapting to different driving conditions can be achieved by presetting the parameters of the relevant influence factors according to the algorithm and calibrating and optimizing the actual vehicle type.

It can be understood that, the generated interactive content in the embodiment of the present application may be human-vehicle interactive information containing actual driving mileage content, the acoustic prompting device may be a vehicle-mounted device capable of performing voice information transmission, such as a vehicle-mounted voice broadcasting system, a vehicle-mounted ring sound box or a vehicle-mounted voice early warning system, and the optical prompting device may be a vehicle-mounted device capable of performing information transmission visually, such as a vehicle-mounted central control electronic screen or an in-vehicle indicator light. For example, the interactive information can be subjected to voice broadcasting through the vehicle-mounted intelligent voice broadcasting system, and interactive information characters can be projected through the vehicle-mounted central control electronic screen.

According to the embodiment of the application, the interactive content can be generated according to the actual endurance mileage, the at least one acoustic reminding device and/or the at least one optical reminding device of the vehicle are controlled to prompt the interactive content, the actual endurance state of the current vehicle can be rapidly and intuitively known by a user through information interaction of the endurance mileage to the user, and the interaction level of the vehicle is improved.

Optionally, in an embodiment of the present application, generating the interactive content according to the actual driving mileage includes: and generating an optimal charging SOC based on the actual driving mileage, the actual environment temperature and the current battery state, and determining an optimal charging position, charging time and/or prompt information according to the current driving scene.

In the actual execution process, the optimal charging SOC can obtain a corresponding numerical value by importing the actual cruising mileage, the actual environment temperature and the current battery state into a corresponding algorithm model, can determine the optimal charging position which is closest to the current position of the vehicle and has the optimal distance according to the current driving scene and a navigation map, estimates the corresponding charging time according to the optimal charging SOC and the vehicle electric quantity, and carries out related text and voice prompt on the obtained optimal charging SOC, the optimal charging position and the charging time.

The embodiment of the application can generate the optimal charging SOC based on the actual endurance mileage, the actual environment temperature and the current battery state, determine the optimal charging position, charging time and/or prompt information according to the current driving scene, and effectively reduce the mileage anxiety of the user in the vehicle using process by providing the user with comprehensive endurance related information, thereby improving the vehicle automation degree and facilitating the use of the user.

Fig. 3 is a schematic diagram of a driving range estimation software architecture according to an embodiment of the present application, including average energy consumption calculation, energy consumption coefficient calculation, driving range estimation, and human-computer interaction information.

And inputting the human-computer interaction, the vehicle parameters and the energy management into the average energy consumption calculation, the energy consumption coefficient calculation, the driving range estimation and the human-computer interaction information, and finally outputting in a human-computer interaction mode.

The average energy consumption calculation comprises real-time energy consumption calculation, the calculation of the latest 300 energy of 1km, actual average energy consumption calculation, display average energy calculation, energy consumption calculation of different driving modes and mileage calculation of different driving modes.

The energy consumption coefficient calculation comprises navigation information identification and fusion, environment parameter identification and fusion, driving habit judgment, vehicle state judgment and energy consumption coefficient calculation.

The driving range estimation comprises estimating the driving range based on energy consumption, estimating the driving range based on SOC, calculating the driving range, searching the SOC for a range 2 limit value, calculating the driving range and calculating an energy consumption coefficient.

The human-computer interaction information comprises the driving range under different vehicle modes, whether the driving range of the air conditioner is started, a recommended charging navigation function, prompt in-time charging text prompt, battery maintenance charging start prompt and battery maintenance charging end prompt.

According to the method for detecting the endurance mileage of the vehicle, the actual vehicle parameters of the vehicle can be read while the current driving scene, the actual habits of the driver and the environment factors of the environment where the driver is located are identified, the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient are calculated according to the current driving scene, the actual habits of the driver, the environment factors of the environment where the driver is located and the actual vehicle parameters, the final energy consumption coefficient is arbitrated according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, the actual endurance mileage of the vehicle is obtained according to the final energy consumption coefficient, the endurance mileage of the vehicle can be suitable for different vehicle working conditions, the accuracy and the reliability of endurance calculation results are guaranteed, the mileage anxiety of users is reduced, and the use requirements of the users are met. Therefore, the problems that in the related art, due to the fact that deviation exists in calculation of the residual energy of the battery, the energy consumption of vehicle running changes dynamically in real time, and the difference between the actual use of the vehicle and the specific calibration working condition in the research and development process is large, the error between the actual driving range and the estimated value is obvious, and due to the fact that the energy consumption is calculated in real time, the accuracy of the estimated driving range value is affected due to the fact that time segments are selected, the reliability of driving range detection under different working conditions of the vehicle is difficult to ensure in actual driving, the universality and the accuracy of the driving range detection are reduced, and the use experience of a user is affected are solved.

Next, a driving range detection device of a vehicle according to an embodiment of the present application will be described with reference to the drawings.

Fig. 4 is a block diagram schematically illustrating a range detection apparatus of a vehicle according to an embodiment of the present application.

As shown in fig. 4, the driving range detection device 10 of the vehicle includes: an acquisition module 100, a calculation module 200 and a detection module 300.

The obtaining module 100 is configured to read an actual vehicle parameter of the vehicle while identifying a current driving scene of the vehicle, an actual habit of a driver, and an environmental factor of an environment where the vehicle is located.

And the calculating module 200 is used for calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value and an energy consumption correction coefficient according to the current driving scene, the actual habit of the driver, the environmental factors of the environment and the actual vehicle parameters.

The detection module 300 is configured to arbitrate a final energy consumption coefficient according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value, and the energy consumption correction coefficient, and obtain an actual cruising mileage of the vehicle according to the final energy consumption coefficient.

Optionally, in an embodiment of the present application, the detection module 300 includes: the device comprises a first matching unit, a first calculating unit and a second calculating unit.

The first matching unit is used for acquiring an actual battery state of charge (SOC) value of the vehicle and matching a first driving range of the vehicle according to the actual SOC value.

And the first calculating unit is used for calculating a second driving range of the vehicle according to the available residual energy of the battery of the vehicle and the real-time energy consumption.

And the second calculating unit is used for calculating the actual endurance mileage according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient.

S＝S _SOC +r*(S _E -S _SOC )，

Optionally, in an embodiment of the present application, the apparatus 10 further includes: and (6) interacting the template.

The interaction module is used for generating interaction content according to the actual driving mileage and controlling at least one acoustic reminding device and/or at least one optical reminding device of the vehicle to remind the interaction content.

Optionally, in an embodiment of the present application, the interaction module includes: and a generating unit.

The generating unit is used for generating the optimal charging SOC based on the actual driving mileage, the actual environment temperature and the current battery state, and determining the optimal charging position, the charging time and/or the prompt information according to the current driving scene.

Optionally, in an embodiment of the present application, the computing module 200 includes: the device comprises a first output unit, a second matching unit and a third calculating unit.

And the first output unit is used for importing the current driving scene into a preset driving scene model and outputting a scene energy consumption correction coefficient.

And the second output unit is used for leading the actual habit into a preset driver model and outputting the initial energy consumption correction coefficient.

And the second matching unit is used for matching the corresponding energy consumption correction coefficient according to the actual vehicle parameter.

And the third calculating unit is used for identifying the state of the vehicle thermal management system according to the environmental factors so as to calculate the energy consumption coefficient compensation value.

It should be noted that the explanation of the embodiment of the method for detecting the driving range of the vehicle is also applicable to the device for detecting the driving range of the vehicle of the embodiment, and the details are not repeated herein.

According to the endurance mileage detection device of the vehicle, the actual vehicle parameters of the vehicle can be read while the current driving scene, the actual habits of the driver and the environment factors of the environment are identified, the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient are calculated according to the current driving scene, the actual habits of the driver, the environment factors of the environment and the actual vehicle parameters respectively, the final energy consumption coefficient is arbitrated according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, and the actual endurance mileage of the vehicle is obtained according to the final energy consumption coefficient, so that the endurance mileage detection of the vehicle can be suitable for different vehicle working conditions, the accuracy and the reliability of endurance calculation results are guaranteed, the mileage anxiety of users is reduced, and the use requirements of the users are met. Therefore, the problems that in the related technology, due to the fact that deviation exists in calculation of the residual energy of the battery, the energy consumption of vehicle driving is dynamically changed in real time, and the difference between the actual driving range and the estimated value is large due to the fact that the difference between the actual use of the vehicle and the specific calibration working condition in the research and development process is large, and due to the fact that the time slice is selected during real-time calculation of the energy consumption, the accuracy of the estimated driving range value is affected are solved, the reliability of driving range detection under different working conditions of the vehicle is difficult to ensure in actual driving, the universality and the accuracy of the driving range detection are reduced, and the use experience of a user is affected.

Fig. 5 is a schematic structural diagram of a vehicle according to an embodiment of the present application. The vehicle may include:

a memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.

The processor 502, when executing the program, implements the range detection method of the vehicle provided in the above-described embodiment.

Further, the vehicle further includes:

a communication interface 503 for communication between the memory 501 and the processor 502.

A memory 501 for storing computer programs that can be run on the processor 502.

The memory 501 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.

Alternatively, in practical implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 may complete communication with each other through an internal interface.

The processor 502 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.

The present embodiment also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the cruising range detection method of a vehicle as above.

In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.

The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.

The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims

1. A method for detecting the driving mileage of a vehicle is characterized by comprising the following steps:

the method comprises the steps of recognizing the current driving scene of a vehicle, the actual habits of a driver and the environmental factors of the environment, and simultaneously reading the actual vehicle parameters of the vehicle;

calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value and an energy consumption correction coefficient according to the current driving scene, the actual habit of the driver, the environmental factors of the environment and the actual vehicle parameters; and

arbitrating a final energy consumption coefficient according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, and obtaining the actual endurance mileage of the vehicle according to the final energy consumption coefficient.

2. The method of claim 1, wherein said deriving an actual range of the vehicle from the final energy consumption coefficient comprises:

acquiring an actual battery state of charge (SOC) value of the vehicle, and matching a first endurance mileage of the vehicle according to the actual SOC value;

calculating a second driving range of the vehicle according to the available residual energy and real-time energy consumption of the battery of the vehicle;

and calculating the actual endurance mileage according to the first endurance mileage, the second endurance mileage and the final energy consumption coefficient.

3. The method of claim 1, wherein the actual range is calculated by the formula:

S＝S _SOC +r*(S _E -S _SOC )，

4. The method of claim 1, further comprising:

and generating interactive content according to the actual driving mileage, and controlling at least one acoustic reminding device and/or at least one optical reminding device of the vehicle to remind the interactive content.

5. The method of claim 4, wherein generating interactive content based on the actual range comprises:

and generating an optimal charging SOC based on the actual driving mileage, the actual environment temperature and the current battery state, and determining an optimal charging position, charging time and/or prompt information according to the current driving scene.

6. The method of claim 1, wherein calculating a scene energy consumption correction factor, an initial energy consumption correction factor, an energy consumption factor compensation value, and an energy consumption correction factor based on the current driving scene, the actual habits of the driver, the environmental factors of the environment, and the actual vehicle parameters, respectively, comprises:

importing the current driving scene into a preset driving scene model, and outputting the scene energy consumption correction coefficient;

importing the actual habit into a preset driver model, and outputting the initial energy consumption correction coefficient;

matching corresponding energy consumption correction coefficients according to the actual vehicle parameters;

and identifying the state of the vehicle thermal management system according to the environmental factors to calculate the energy consumption coefficient compensation value.

7. A driving range detection device of a vehicle, characterized by comprising:

the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for reading the actual vehicle parameters of a vehicle while identifying the current driving scene of the vehicle, the actual habits of a driver and the environmental factors of the environment where the driver is located;

the calculation module is used for calculating a scene energy consumption correction coefficient, an initial energy consumption correction coefficient, an energy consumption coefficient compensation value and an energy consumption correction coefficient according to the current driving scene, the actual habit of the driver, the environmental factors of the environment and the actual vehicle parameters; and

and the detection module is used for arbitrating a final energy consumption coefficient according to the scene energy consumption correction coefficient, the initial energy consumption correction coefficient, the energy consumption coefficient compensation value and the energy consumption correction coefficient, and obtaining the actual endurance mileage of the vehicle according to the final energy consumption coefficient.

8. The apparatus of claim 7, wherein the detection module comprises:

the matching unit is used for acquiring the actual SOC value of the battery of the vehicle and matching the first endurance mileage of the vehicle according to the actual SOC value;

the first calculation unit is used for calculating a second endurance mileage of the vehicle according to the available residual energy of the battery of the vehicle and the real-time energy consumption;

9. A vehicle, characterized by comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement a range detection method of a vehicle as claimed in any one of claims 1 to 6.

10. A computer-readable storage medium, on which a computer program is stored, the program being executable by a processor for implementing a range detection method of a vehicle according to any one of claims 1 to 6.