CN111409467B - Automobile braking energy recovery method, terminal equipment, vehicle and server - Google Patents
Automobile braking energy recovery method, terminal equipment, vehicle and server Download PDFInfo
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- CN111409467B CN111409467B CN202010298481.4A CN202010298481A CN111409467B CN 111409467 B CN111409467 B CN 111409467B CN 202010298481 A CN202010298481 A CN 202010298481A CN 111409467 B CN111409467 B CN 111409467B
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- 238000011084 recovery Methods 0.000 title claims abstract description 40
- 230000007613 environmental effect Effects 0.000 claims abstract description 85
- 230000009471 action Effects 0.000 claims abstract description 49
- 230000002708 enhancing effect Effects 0.000 claims abstract description 5
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L7/00—Electrodynamic brake systems for vehicles in general
- B60L7/10—Dynamic electric regenerative braking
Abstract
The application relates to an automobile braking energy recovery method, terminal equipment, a vehicle and a server, wherein the automobile braking energy recovery method comprises the following steps: acquiring environment information of the vehicle in running; judging the probability of the current braking action of the vehicle based on the environmental information; and when the probability of the current braking action of the vehicle reaches a first preset value, enhancing the energy recovery amplitude. According to the automobile braking energy recovery method, when the probability of the current braking action of the automobile reaches the first preset value, the energy recovery amplitude is enhanced, so that the energy recovery efficiency is improved, energy conservation is facilitated, and the energy utilization efficiency is improved.
Description
Technical Field
The application relates to the technical field of computers, in particular to an automobile braking energy recovery method, terminal equipment, a vehicle and a server.
Background
The hybrid vehicle or the electric vehicle has larger demand on energy recovery, and when the vehicle decelerates, the energy recovery amplitude can be enhanced under the condition of not influencing the vehicle control so as to improve the energy utilization efficiency, however, the scheme of energy recovery according to the pre-judging of the braking behavior of the user does not appear yet.
Disclosure of Invention
In order to solve the technical problems, an object of the present application is to provide an automobile braking energy recovery method, which enhances energy recovery amplitude when the probability of the current braking action of the automobile reaches a first preset value, thereby improving energy recovery efficiency, further being beneficial to saving energy and improving energy utilization efficiency.
Another object of the present application is to provide a method for recovering braking energy of an automobile.
Still another object of the present application is to provide a terminal device for implementing the above method for recovering braking energy of an automobile.
It is a further object of the present application to provide a vehicle comprising the above terminal device.
It is still another object of the present application to provide a server for implementing the above-mentioned method for recovering braking energy of an automobile.
In order to achieve the above purpose, the application adopts the following technical scheme:
according to an embodiment of the first aspect of the application, a method for recovering braking energy of an automobile comprises the following steps:
acquiring environment information of the vehicle in running;
judging the probability of the current braking action of the vehicle based on the environmental information;
and when the probability of the current braking action of the vehicle reaches a first preset value, enhancing the energy recovery amplitude.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs currently includes:
based on the environmental information, a first braking probability is obtained through a first braking judgment model, and the probability of the current braking behavior of the vehicle is judged based on the first braking probability;
the first brake judgment model is obtained based on historical brake data of a plurality of vehicles.
Preferably, the historical braking data includes historical vehicle driving state data and one or more of historical road attribute data, historical vehicle surrounding environment data and historical traffic signal data corresponding to the historical vehicle driving state data.
Preferably, the first brake judgment model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the obtaining the first braking probability through the first braking judgment model based on the environmental information comprises:
determining a current scene by the first braking judgment model based on the environmental information,
and obtaining the first braking probability based on the current scene.
Preferably, the historical brake data further includes historical brake operation data including one or more of a historical brake amplitude, a historical brake start position, and a historical brake end position.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs currently further includes:
obtaining a second braking probability according to a second braking judgment model based on the environmental information, wherein the second braking judgment model is obtained based on the historical braking data of the vehicle;
and judging the probability of the current braking action of the vehicle based on the first braking probability and the second braking probability.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs currently further includes:
obtaining a third braking probability according to a third braking judgment model based on the environmental information, wherein the third braking judgment model is obtained based on the environmental information related to the preset braking behavior;
and judging the probability of the braking action of the vehicle currently based on the first braking probability, the second braking probability and the third braking probability.
Preferably, when the third braking probability reaches a second predetermined value or more, the third braking probability is higher than the weight of the first braking probability and the second braking probability.
Preferably, the environmental information associated with the predetermined braking behavior includes one or more of front vehicle start-stop and acceleration-deceleration state data, signal lamp state data, intersection pedestrian and vehicle states, and lane-level road conditions in a predetermined braking behavior state.
Preferably, the environmental information of the host vehicle includes one or more of host vehicle state data, host vehicle road data, host vehicle surrounding environment data, and host vehicle traffic signal data.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs at present specifically includes:
the method comprises the steps that braking probability query information is sent to a server, wherein the braking probability query information comprises environment information of a vehicle and is used for requesting the server to judge braking probability according to the environment information of the vehicle;
and receiving a response of the braking probability sent by the server.
According to a second aspect of the present application, an automobile brake energy recovery method includes:
the method comprises the steps that a server receives braking probability query information, wherein the braking probability query information comprises environment information of a vehicle;
the server judges the braking probability according to the environmental information of the vehicle;
the server sends a response to the braking probability.
The terminal device according to the embodiment of the third aspect of the present application includes:
the acquisition module is used for acquiring the environmental information of the vehicle in running;
the first judging module is used for judging the probability of the current braking action of the vehicle based on the environmental information;
and the energy recovery adjusting module is used for enhancing the energy recovery amplitude when the probability of the current braking action of the vehicle reaches a first preset value.
Preferably, the first judging module is specifically configured to obtain a first braking probability through a first braking judging model based on the environmental information, and judge a probability of a braking behavior of the vehicle according to the first braking probability;
the first brake judgment model is obtained based on historical brake data of a plurality of vehicles.
Preferably, the historical braking data includes historical vehicle driving state data and one or more of historical road attribute data, historical vehicle surrounding environment data and historical traffic signal data corresponding to the historical vehicle driving state data.
Preferably, the first brake judgment model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the first judging module is specifically configured to determine, based on the environmental information, a current scene through the first braking judging model, and obtain the first braking probability based on the current scene.
Preferably, the historical brake data further includes historical brake operation data including one or more of a historical brake amplitude, a historical brake start position, and a historical brake end position.
Preferably, the first judging module is specifically configured to,
obtaining a second braking probability according to a second braking judgment model based on the environmental information, wherein the second braking judgment model is obtained based on the historical braking data of the vehicle;
and judging the probability of the current braking action of the vehicle based on the first braking probability and the second braking probability.
Preferably, the first judging module is specifically configured to,
obtaining a third braking probability according to a third braking judgment model based on the environmental information, wherein the third braking judgment model is obtained based on the environmental information related to the preset braking behavior;
and judging the probability of the braking action of the vehicle currently based on the first braking probability, the second braking probability and the third braking probability.
Preferably, when the third braking probability reaches a second predetermined value or more, the third braking probability is higher than the weight of the first braking probability and the second braking probability.
Preferably, the environmental information associated with the predetermined braking behavior includes one or more of front vehicle start-stop and acceleration-deceleration state data, signal lamp state data, intersection pedestrian and vehicle states, and lane-level road conditions in a predetermined braking behavior state.
Preferably, the environmental information of the host vehicle includes one or more of host vehicle state data, host vehicle road data, host vehicle surrounding environment data, and host vehicle traffic signal data.
Preferably, the first judging module is specifically configured to,
the method comprises the steps that braking probability query information is sent to a server, wherein the braking probability query information comprises environment information of a vehicle and is used for requesting the server to judge braking probability according to the environment information of the vehicle;
and receiving a response of the braking probability sent by the server.
A vehicle according to a fourth aspect of the present application has the terminal device according to any one of the above embodiments.
The server according to an embodiment of the fifth aspect of the present application includes:
the receiving module is used for receiving brake probability query information by the server, wherein the brake probability query information comprises environment information of the vehicle;
the second judging module is used for judging the braking probability according to the environmental information of the vehicle by the server;
and the sending module is used for sending the response of the braking probability by the server.
The application has the beneficial effects that:
the vehicle braking energy recovery method is beneficial to saving energy and improving the energy utilization efficiency.
The foregoing description is only an overview of the present application, and is intended to provide a better understanding of the present application, as it is embodied in the following description, with reference to the preferred embodiments of the present application and the accompanying drawings.
Drawings
FIG. 1 is a schematic diagram of an application scenario of vehicle braking energy recovery according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for recovering braking energy of an automobile according to an embodiment of the application;
fig. 3 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
The following describes in further detail the embodiments of the present application with reference to the drawings and examples. The following examples are only illustrative of the present application and are not intended to limit the scope of the application.
It is to be appreciated that as used herein, the term "module" may refer to or include an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and/or memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable hardware components that provide the described functionality, or may be part of such hardware components.
It is to be appreciated that in various embodiments of the application, the processor may be a microprocessor, a digital signal processor, a microcontroller, or the like, and/or any combination thereof. According to another aspect, the processor may be a single core processor, a multi-core processor, or the like, and/or any combination thereof.
As shown in fig. 1, according to an application scenario schematic of the technical solution of the present application,
the hybrid vehicle or the electric vehicle has a larger demand on energy recovery, and the energy recovery amplitude can be enhanced to improve the energy utilization efficiency when the vehicle decelerates, however, the prior art does not have a scheme for energy recovery according to the pre-judgment of the braking action of the user, the application acquires the environmental information in the running process of the vehicle 10, further judges the probability of the current braking action of the vehicle 10 based on the acquired environmental information, and when the probability of the current braking action of the vehicle 10 reaches a first preset value, the energy recovery amplitude is enhanced, thereby being beneficial to saving energy and improving the energy utilization efficiency.
As shown in fig. 2, the method for recovering braking energy of an automobile based on terminal equipment according to an embodiment of the application comprises the following steps:
step S1, obtaining environment information of the vehicle in running.
Preferably, the environmental information of the host vehicle includes one or more of host vehicle state data, host vehicle road data, host vehicle surrounding environment data, and host vehicle traffic signal data.
The vehicle state data may include a position coordinate of the vehicle, a current lane of the vehicle, a speed of the vehicle, an angle between the vehicle and a road where the vehicle is located, a recommended lane of the vehicle and a driving direction in front of the vehicle, which are obtained by a navigator, the vehicle road data may include a gradient and a curvature of the road where the vehicle is located, a pothole degree of the road where the vehicle is located, an attribute of the road where the vehicle is located, such as whether a school road section is a road section or not, whether an accident is multiple road sections, and the like, the vehicle surrounding environment data may include a distance between the vehicle and a road junction in front, a front vehicle speed and a start-stop state, a rear vehicle speed and an acceleration, a road junction pedestrian and a vehicle state in front, a road condition of the vehicle class, a traveling plan of other vehicles in the vehicle driving range, and the like, and the vehicle traffic signal data may include a traffic light state in front of the vehicle, and the like.
And step S2, judging the probability of the current braking action of the vehicle based on the environment information.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs currently includes:
based on the environmental information, a first braking probability is obtained through a first braking judgment model, and the probability of the current braking behavior of the vehicle is judged based on the first braking probability;
the first brake judgment model is obtained based on historical brake data of a plurality of vehicles.
The first braking judgment model is obtained based on the historical braking data of a plurality of vehicles, the probability of the current braking behavior of the vehicle, which is obtained based on the first braking probability judgment, is obtained according to the analysis of the historical braking data of a large number of vehicles, and the result is accurate.
Preferably, the historical braking data includes historical vehicle driving state data and one or more of historical road attribute data, historical vehicle surrounding environment data and historical traffic signal data corresponding to the historical vehicle driving state data.
Specifically, the historical vehicle driving state data may include position coordinates of the historical vehicle, a lane where the historical vehicle is located, a speed of the historical vehicle, an angle between the historical vehicle and a road where the vehicle is located, the historical vehicle driving state data may further include a recommended lane of the historical vehicle and a driving direction in front of the historical vehicle, which are obtained through a navigator, the historical road attribute data may include gradient and curvature of the road where the historical vehicle is located, pothole degree of the road where the historical vehicle is located, and may include whether the road where the historical vehicle is located is a school road section, whether an accident multiple road section or not, and the like, the historical vehicle surrounding environment data may include a distance from the historical vehicle to the road junction in front, a speed and a start-stop state of the historical vehicle, a speed and acceleration of the historical vehicle in front of the road junction, a pedestrian and a vehicle state in front of the historical vehicle, a blind area state of the historical vehicle, a road condition of the historical road class, a running plan of other vehicles in the historical vehicle driving range, and the like, and the historical vehicle traffic signal data may include a traffic light state in front of the vehicle road junction, and the like.
Preferably, the first brake judgment model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the obtaining the first braking probability through the first braking judgment model based on the environmental information comprises:
determining a current scene by the first braking judgment model based on the environmental information,
and obtaining the first braking probability based on the current scene.
Specifically, historical braking data of a plurality of vehicles during braking and decelerating are obtained, then scene division can be performed through one or more of statistics, machine learning, data mining and deep learning based on the historical braking data of the plurality of vehicles, so that a plurality of scenes, such as front congestion, straight-going intersections, left-turning intersections, right-turning intersections, downhill slopes, lane changes and the like, are obtained, and a first braking judgment model is obtained based on corresponding braking probabilities respectively corresponding to different scenes.
The first braking judgment model is obtained by dividing scenes based on historical braking data and further according to corresponding braking probabilities corresponding to different scenes, the first braking judgment model is simple, and the first braking probability obtained by the first braking judgment model is accurate and reliable.
Preferably, the historical brake data further includes historical brake operation data including one or more of a historical brake amplitude, a historical brake start position, and a historical brake end position.
Specifically, when the first braking judgment model is constructed, different scenes can be associated with corresponding historical braking operation data, so that the first braking probability and the first expected braking operation can be obtained through the first braking judgment model based on the environmental information of the vehicle, and the energy recovery amplitude can be adjusted according to the first expected braking operation.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs currently further includes:
obtaining a second braking probability according to a second braking judgment model based on the environmental information, wherein the second braking judgment model is obtained based on the historical braking data of the vehicle;
and judging the probability of the current braking action of the vehicle based on the first braking probability and the second braking probability.
When judging the probability of the current braking action of the vehicle, the weights of the first braking probability and the second braking probability can be adjusted according to the actual situation in specific implementation.
The probability of the current braking action of the vehicle is judged through the first braking probability and the second braking probability, so that the historical braking data of a plurality of vehicles are considered, the historical braking data of the vehicle are considered, the obtained probability of the current braking action of the vehicle is more accurate, and the braking habit of the vehicle is more met.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs currently further includes:
obtaining a third braking probability according to a third braking judgment model based on the environmental information, wherein the third braking judgment model is obtained based on the environmental information related to the preset braking behavior;
and judging the probability of the braking action of the vehicle currently based on the first braking probability, the second braking probability and the third braking probability.
The probability of the braking action of the vehicle is judged based on the first braking probability, the second braking probability and the third braking probability, so that the first braking probability and the second braking probability are corrected based on the third braking probability obtained by the environment information related to the preset braking action, and the probability of the braking action of the vehicle is more accurate.
Preferably, the environmental information associated with the predetermined braking behavior includes one or more of front vehicle start-stop and acceleration-deceleration state data, signal lamp state data, intersection pedestrian and vehicle states, and lane-level road conditions in a predetermined braking behavior state.
Preferably, when the third braking probability reaches a second predetermined value or more, the third braking probability is higher than the weight of the first braking probability and the second braking probability.
Specifically, for example, when the third braking probability reaches 90% or more, the third braking probability has a higher weight than the first braking probability and the second braking probability when judging the probability that the braking action of the vehicle currently occurs, for example, the weight of the third braking probability may be 80%. Therefore, the accuracy of the probability of the current braking action of the vehicle judged by the first braking probability, the second braking probability and the third braking probability is further ensured.
Preferably, the determining, based on the environmental information, the probability that the braking action of the vehicle occurs at present specifically includes:
the method comprises the steps that braking probability query information is sent to a server, wherein the braking probability query information comprises environment information of a vehicle and is used for requesting the server to judge braking probability according to the environment information of the vehicle;
and receiving a response of the braking probability sent by the server.
Specifically, the braking probability query information is sent to the server, and the probability of the braking behavior of the vehicle is judged according to the received response of the braking probability sent by the server, so that the probability of the braking behavior of the vehicle is conveniently and quickly judged.
More specifically, the first brake judgment model, the second brake judgment model and the third brake judgment model may be all set in the server, the server obtains the brake probability by judging the first brake judgment model, the second brake judgment model and the third brake judgment model based on the environmental information of the vehicle, and the server may update the first brake judgment model and the second brake judgment model according to the continuously obtained historical brake data, so that the obtained brake probability is more accurate.
In addition, according to some embodiments of the present application, the first braking judgment model and the second braking judgment model may be set in the server, the third braking judgment model may be set in the terminal device, the terminal device may be a mobile phone end, or a terminal device set in the vehicle, or other terminal devices, the server may obtain the first braking probability and the second braking probability through the first braking judgment model and the second braking judgment model based on the environmental information of the vehicle, and send the responses of the first braking probability and the second braking probability, and the terminal device may obtain the third braking probability through the third braking judgment model based on the environmental information of the vehicle, and determine the probability that the vehicle currently generates braking action according to the received responses of the first braking probability and the second braking probability.
Of course, according to other embodiments of the present application, the first brake determination model, the second brake determination model, and the third brake determination model may be all set in the terminal device, and the terminal device determines the probability of the present vehicle braking behavior according to the first brake determination model, the second brake determination model, and the third brake determination model based on the environmental information, where the first brake determination model and the second brake determination model may be updated periodically or according to the actual requirement.
And step S3, enhancing the energy recovery amplitude when the probability of the current braking action of the vehicle reaches a first preset value.
Specifically, for example, the first predetermined value may be 80%, and the energy recovery amplitude is enhanced when the probability of the present occurrence of the braking behavior of the own vehicle reaches 80%.
The vehicle braking energy recovery method is beneficial to saving energy and improving the energy utilization efficiency.
According to the embodiment of the application, the automobile braking energy recovery method based on the server comprises the following steps:
step S100, a server receives braking probability query information, wherein the braking probability query information comprises environment information of the vehicle;
step S200, the server judges the braking probability according to the environmental information of the vehicle;
step S300, the server transmits a response of the braking probability.
The braking probability query information is received through the server, the braking probability is judged according to the environment information of the vehicle and is sent to the terminal equipment, so that the terminal equipment can judge the probability of the current braking action of the vehicle according to the received response of the braking probability, and the probability of the current braking action of the vehicle can be conveniently and rapidly judged.
As shown in fig. 3, the terminal device according to the embodiment of the application for implementing the method for recovering braking energy of an automobile based on the terminal device according to the embodiment of the application includes an acquisition module 20, a first judgment module 30, and an energy recovery adjustment module 40.
The acquiring module 20 is configured to acquire environmental information during running of the vehicle.
The first judging module 30 is configured to judge, based on the environmental information, a probability that the braking action of the vehicle occurs currently.
The energy recovery adjustment module 40 is configured to enhance the energy recovery amplitude when the probability of the current braking action of the vehicle reaches a first predetermined value.
The probability of the braking action of the vehicle is judged based on the environmental information in the running process of the vehicle, and the energy recovery amplitude is enhanced when the probability of the braking action reaches the first preset value, so that the energy recovery efficiency is improved.
Preferably, the first judging module 30 is specifically configured to obtain, based on the environmental information, a first braking probability through a first braking judging model, and judge, based on the first braking probability, a probability that a braking action of the vehicle occurs currently;
the first brake judgment model is obtained based on historical brake data of a plurality of vehicles.
Preferably, the historical braking data includes historical vehicle driving state data and one or more of historical road attribute data, historical vehicle surrounding environment data and historical traffic signal data corresponding to the historical vehicle driving state data.
Preferably, the first brake judgment model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the first judging module 30 is specifically configured to determine, based on the environmental information, a current scene through the first braking judging model, and obtain the first braking probability based on the current scene.
Preferably, the historical brake data further includes historical brake operation data including one or more of a historical brake amplitude, a historical brake start position, and a historical brake end position.
Preferably, the first judging module 30 is specifically configured to,
obtaining a second braking probability according to a second braking judgment model based on the environmental information, wherein the second braking judgment model is obtained based on the historical braking data of the vehicle;
and judging the probability of the current braking action of the vehicle based on the first braking probability and the second braking probability.
Preferably, the first judging module 30 is specifically configured to,
obtaining a third braking probability according to a third braking judgment model based on the environmental information, wherein the third braking judgment model is obtained based on the environmental information related to the preset braking behavior;
and judging the probability of the braking action of the vehicle currently based on the first braking probability, the second braking probability and the third braking probability.
Preferably, when the third braking probability reaches a second predetermined value or more, the third braking probability is higher than the weight of the first braking probability and the second braking probability.
Preferably, the environmental information associated with the predetermined braking behavior includes one or more of front vehicle start-stop and acceleration-deceleration state data, signal lamp state data, intersection pedestrian and vehicle states, and lane-level road conditions in a predetermined braking behavior state.
Preferably, the environmental information of the host vehicle includes one or more of host vehicle state data, host vehicle road data, host vehicle surrounding environment data, and host vehicle traffic signal data.
Preferably, the first judging module 30 is specifically configured to,
the method comprises the steps that braking probability query information is sent to a server, wherein the braking probability query information comprises environment information of a vehicle and is used for requesting the server to judge braking probability according to the environment information of the vehicle;
and receiving a response of the braking probability sent by the server.
A vehicle having a terminal device as in any one of the embodiments above. The vehicle is beneficial to saving energy and improving the energy utilization efficiency.
The server according to the embodiment of the application for realizing the method for recovering braking energy of the automobile based on the server according to the embodiment of the application comprises a receiving module, a second judging module and a sending module.
The receiving module is used for receiving braking probability query information by the server, wherein the braking probability query information comprises environment information of the vehicle.
And the second judging module is used for judging the braking probability according to the environmental information of the vehicle by the server.
And the sending module is used for sending the response of the braking probability by the server.
The braking probability query information is received, the braking probability is obtained according to the environmental information of the vehicle, and the braking probability is sent to the terminal equipment, so that the terminal equipment can judge the probability of the current braking behavior of the vehicle according to the received response of the braking probability, and the server can conveniently and rapidly judge the probability of the current braking behavior of the vehicle.
In the several embodiments provided in the present application, it should be understood that the disclosed methods and apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may be physically included separately, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A method for recovering braking energy of an automobile, comprising:
acquiring environment information of the vehicle in running;
obtaining a first braking probability through a first braking judgment model based on the environmental information, wherein the first braking judgment model is obtained based on historical braking data of a plurality of vehicles, a second braking probability is obtained according to a second braking judgment model based on the environmental information, the second braking judgment model is obtained based on the historical braking data of the vehicle, a third braking probability is obtained according to a third braking judgment model based on the environmental information, the third braking judgment model is obtained based on the environmental information related to a preset braking action, and the probability of the vehicle on which the braking action occurs currently is judged based on the first braking probability, the second braking probability and the third braking probability, wherein when the third braking probability reaches more than a second preset value, the third braking probability is higher than the weight of the first braking probability and the second braking probability;
enhancing energy recovery when the probability of the present braking behavior of the host vehicle reaches a first predetermined value
The amplitude of the signal is calculated,
the first brake judging model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the obtaining the first braking probability through the first braking judgment model based on the environmental information comprises:
determining a current scene by the first braking judgment model based on the environmental information,
and obtaining the first braking probability based on the current scene.
2. The vehicle braking energy recovery method according to claim 1, wherein the historical braking data includes historical vehicle travel state data and one or more of historical road attribute data, historical vehicle surroundings data, and historical traffic signal data corresponding to the historical vehicle travel state data.
3. The vehicle braking energy recovery method according to claim 2, wherein the historical braking data further includes historical braking operation data including one or more of a historical braking amplitude, a historical braking start position, and a historical braking end position.
4. The method of claim 1, wherein the environmental information associated with the predetermined braking behavior includes one or more of front stop and acceleration/deceleration state data, signal lamp state data, crossing pedestrian and vehicle states, and lane-level road conditions in a predetermined braking behavior state.
5. The method of claim 1, wherein the environmental information of the vehicle during driving includes one or more of vehicle state data, vehicle road data, vehicle surrounding environment data, and vehicle traffic signal data.
6. The method for recovering braking energy of an automobile according to claim 1, wherein determining the probability of occurrence of a braking action of the automobile based on the environmental information specifically comprises:
the method comprises the steps that braking probability query information is sent to a server, wherein the braking probability query information comprises the running environment information of a vehicle and is used for requesting the server to judge the braking probability according to the environment information of the vehicle;
and receiving a response of the braking probability sent by the server.
7. A method for recovering braking energy of an automobile, comprising:
the method comprises the steps that a server receives braking probability query information, wherein the braking probability query information comprises environment information in the running process of a vehicle;
the server obtains a first braking probability through a first braking judgment model based on the environmental information, the first braking judgment model is obtained based on historical braking data of a plurality of vehicles, a second braking probability is obtained according to a second braking judgment model based on the environmental information, the second braking judgment model is obtained based on the historical braking data of the vehicle, a third braking probability is obtained according to a third braking judgment model based on the environmental information, the third braking judgment model is obtained based on environmental information related to preset braking behaviors, and the probability of the vehicle currently generating braking behaviors is judged based on the first braking probability, the second braking probability and the third braking probability, wherein when the third braking probability reaches more than a second preset value, the third braking probability is higher than the weight of the first braking probability and the second braking probability;
the server sends a response to the braking probability,
the first brake judging model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the obtaining the first braking probability through the first braking judgment model based on the environmental information comprises:
determining a current scene by the first braking judgment model based on the environmental information,
and obtaining the first braking probability based on the current scene.
8. A terminal device, comprising:
the acquisition module is used for acquiring the environmental information of the vehicle in running;
the first judging module is used for obtaining first braking probability through a first braking judging model based on the environmental information, wherein the first braking judging model is obtained based on historical braking data of a plurality of vehicles, the second braking probability is obtained according to a second braking judging model based on the environmental information, the second braking judging model is obtained based on the historical braking data of the vehicle, the third braking probability is obtained according to a third braking judging model based on the environmental information, the third braking judging model is obtained based on environmental information related to preset braking behaviors, and the probability that the vehicle currently generates braking behaviors is judged based on the first braking probability, the second braking probability and the third braking probability, wherein when the third braking probability reaches more than a second preset value, the third braking probability is higher than the weight of the first braking probability and the second braking probability;
the energy recovery adjusting module is used for enabling the probability of the current braking action of the vehicle to reach a first value
At a predetermined value, the energy recovery amplitude is enhanced,
the first brake judging model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the obtaining the first braking probability through the first braking judgment model based on the environmental information comprises:
determining a current scene by the first braking judgment model based on the environmental information,
and obtaining the first braking probability based on the current scene.
9. A vehicle characterized by having a terminal device according to claim 8.
10. A server, comprising:
the receiving module is used for receiving brake probability query information by the server, wherein the brake probability query information comprises environment information of the vehicle;
the second judging module is configured to obtain, based on the environmental information, a first braking probability through a first braking judging model, where the first braking judging model is obtained based on historical braking data of a plurality of vehicles, based on the environmental information, obtain, based on a second braking judging model, a second braking probability based on the historical braking data of the vehicle, obtain, based on the environmental information, a third braking probability based on a third braking judging model, and obtain, based on environmental information associated with a predetermined braking behavior, a probability that the vehicle currently generates braking behavior based on the first braking probability, the second braking probability, and the third braking probability, where the third braking probability is higher than a weight of the first braking probability and the second braking probability when the third braking probability reaches a second predetermined value or more;
a transmitting module, configured to transmit a response of the braking probability by the server,
the first brake judging model is obtained by the following method:
obtaining the historical braking data of a plurality of vehicles;
performing scene division based on the historical brake data;
based on different scenes, corresponding braking probabilities respectively, obtaining a first braking judgment model;
the obtaining the first braking probability through the first braking judgment model based on the environmental information comprises:
determining a current scene by the first braking judgment model based on the environmental information,
and obtaining the first braking probability based on the current scene.
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