CN114590242B - Vehicle control method and device - Google Patents

Vehicle control method and device Download PDF

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Publication number
CN114590242B
CN114590242B CN202110352836.8A CN202110352836A CN114590242B CN 114590242 B CN114590242 B CN 114590242B CN 202110352836 A CN202110352836 A CN 202110352836A CN 114590242 B CN114590242 B CN 114590242B
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vehicle
road type
road
target
level
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CN114590242A (en
Inventor
贾具宾
刘天培
何介夫
牛小锋
张英富
徐波
郝兴
范琦辉
郭真龙
邢晓猛
刘刚
李熙
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Great Wall Motor Co Ltd
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Great Wall Motor Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/10—Conjoint control of vehicle sub-units of different type or different function including control of change-speed gearings
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/22—Conjoint control of vehicle sub-units of different type or different function including control of suspension systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/30—Conjoint control of vehicle sub-units of different type or different function including control of auxiliary equipment, e.g. air-conditioning compressors or oil pumps
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B60W2520/105—Longitudinal acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/12—Lateral speed
    • B60W2520/125—Lateral acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/28—Wheel speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/05—Type of road, e.g. motorways, local streets, paved or unpaved roads
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/06—Combustion engines, Gas turbines
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/10—Change speed gearings
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/22—Suspension systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

本发明提供了一种车辆控制方法及装置，涉及车辆技术领域。所述方法包括：获取车辆当前所行使道路的一级道路类型；控制车辆进入与一级道路类型对应的驾驶模式，其驾驶模式包括车辆各电控系统的控制参数；在此驾驶模式下，获取车辆的轮速信息、车辆动态信息；根据轮速信息，从一级道路类型包括的二级道路类型中获取目标二级道路类型；根据车辆动态信息，从目标二级道路类型包括的三级道路类型中获取目标三级道路类型；根据目标三级道路类型，确定对各电控系统的补偿参数；基于各电控系统补偿参数调节相应电控系统的控制参数。本申请中，自动将道路类型多次细分并相应微调车辆各电控系统的控制参数，使车辆在各种道路环境中均能保持优良性能。

The present invention provides a vehicle control method and device, which relate to the field of vehicle technology. The method includes: obtaining the primary road type of the road currently traveled by the vehicle; controlling the vehicle to enter a driving mode corresponding to the primary road type, wherein the driving mode includes control parameters of each electronic control system of the vehicle; in this driving mode, obtaining the wheel speed information and vehicle dynamic information of the vehicle; obtaining the target secondary road type from the secondary road types included in the primary road type according to the wheel speed information; obtaining the target third-level road type from the third-level road types included in the target secondary road type according to the vehicle dynamic information; determining the compensation parameters for each electronic control system according to the target third-level road type; and adjusting the control parameters of the corresponding electronic control system based on the compensation parameters of each electronic control system. In the present application, the road type is automatically subdivided multiple times and the control parameters of each electronic control system of the vehicle are fine-tuned accordingly, so that the vehicle can maintain excellent performance in various road environments.

Description

Vehicle control method and device
Technical Field
The invention relates to the technical field of vehicles, in particular to a vehicle control method and device.
Background
With the development of the automobile industry, the passing and handling of vehicles under non-paved roads is of interest to drivers. Off-road conditions are typical application scenarios of non-paved roads, and off-road conditions generally comprise various road surface types such as snow, sand, mud, mountain, and the like.
In the prior art, many host factories develop driving modes for off-road conditions, such as snow mode, sand mode, mud mode, mountain mode, etc., each of which is controlled by an independent switch or key. The driver only needs to start the corresponding driving mode, the main controller of the vehicle controls each electric control system of the vehicle to switch to the corresponding mode, and the off-road performance of the vehicle is improved by utilizing preset performance parameters, so that the driver can pass through complex off-road conditions. However, in actual driving, each road condition may involve different road characteristics and various complexities, and the above manner needs to be manually performed by the user, and only different types of road conditions can be roughly divided, even if each road condition has different road characteristics and various complexities, the performance parameters of the vehicle still remain unchanged. At this time, excellent vehicle performance cannot be ensured in various road environments, and the driving experience of the driver is also degraded.
Disclosure of Invention
In view of the above, the present invention is directed to a vehicle control method and device, so as to solve the problems that the vehicle control method in the prior art cannot automatically determine the road environment and cannot ensure the excellent performance of the vehicle in various road environments.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
In a first aspect, an embodiment of the present invention provides a vehicle control method, including:
Acquiring a first-level road type of a road on which a vehicle is currently travelling;
Controlling the vehicle to enter a driving mode corresponding to the primary road type, wherein the driving mode comprises control parameters of each electric control system of the vehicle;
Acquiring wheel speed information of the vehicle and vehicle dynamic information of the vehicle in the driving mode;
acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information;
Acquiring a target tertiary road type from tertiary road types included in the target secondary road type according to the vehicle dynamic information;
determining compensation parameters for each electric control system according to the target three-level road type;
and adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system.
Preferably, the acquiring wheel speed information of the vehicle includes:
sampling the speed of each wheel to obtain a plurality of speed values;
The obtaining, according to the wheel speed information, a target secondary road type from the secondary road types included in the primary road type includes:
determining a power spectral density value of each wheel by using the Basseva formula and a plurality of speed values of each wheel;
Acquiring a target secondary road type from the secondary road types included in the primary road type according to the power spectrum density values of the wheels and preset conditions corresponding to the secondary road types included in the primary road type;
wherein, the Basseva formula is:
PSDi[n,k]＝Fi[n,k]Fi *[n,k];
Wherein the said PSD i [ N, k ] is the power spectrum density value of wheel i, i is any one wheel of left front wheel fl, right front wheel fr, left rear wheel rl and right rear wheel rr, N is each sampling time, k is frequency, m is the sampling point of wheel speed information, N is the total number of sampling points, V i (m, k) is the wheel speed of the wheel i at the frequency k and the m sampling point, e is an index, the value is 2.71828, j is an imaginary unit, and the value is an imaginary unit
Wherein F i * [ n, k ] is the complex conjugate of F i [ n, k ].
Preferably, the obtaining the target secondary road type from the secondary road types included in the primary road type according to the power spectrum density value of each wheel and the preset condition corresponding to the secondary road type included in the primary road type includes:
calculating the sum of the power spectrum density values of all the wheels to obtain a total power spectrum density value;
Comparing the total power spectral density value with a maximum preset threshold value and a minimum preset threshold value of the power spectral density of the primary road type respectively to obtain a comparison result;
Determining preset conditions which are met by the comparison result;
and taking the secondary road type corresponding to the preset condition as a target secondary road type.
Preferably, the acquiring the vehicle dynamic information of the vehicle includes:
Sampling the acceleration of the vehicle in a preset time period to obtain multiple groups of acceleration information, wherein each group of acceleration information comprises a transverse acceleration value and a longitudinal acceleration value;
The obtaining the target tertiary road type from the tertiary road types included in the target secondary road type according to the vehicle dynamic information includes:
weighting operation is carried out on each group of acceleration values, and a single group of vehicle dynamic indexes are obtained;
determining an average vehicle dynamic index in the preset time period according to a plurality of single-group vehicle dynamic indexes;
And acquiring a target three-level road type from the three-level road types included in the target two-level road type according to the average vehicle dynamic index and a preset condition corresponding to the three-level road type included in the target two-level road type.
Preferably, the determining the average vehicle dynamic index in the preset time period according to the plurality of single-group vehicle dynamic indexes includes:
Calculating the sum of the dynamic indexes of each single group of vehicles to obtain a total dynamic index of the vehicle;
Dividing the duration of a preset time period by a sampling period to obtain sampling times;
dividing the total vehicle dynamic index by the sampling times to obtain the average vehicle dynamic index.
Preferably, the obtaining the first-level road type of the road on which the vehicle is currently travelling includes:
acquiring image information of a road on which the vehicle is currently travelling;
Inputting the image information into a pre-trained pavement recognition model;
And determining the first-level road type according to the road type similarity output by the road surface recognition model.
Preferably, the determining the compensation parameter for each electric control system according to the target three-level road type includes:
And searching a preset three-level road type parameter table according to the target three-level road type, and determining compensation parameters for each electric control system, wherein the three-level road type parameter table comprises compensation parameters of each three-level road type for an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system and an ESP vehicle body stability control system.
In a second aspect, an embodiment of the present invention further provides a vehicle control apparatus, including:
The first acquisition module is used for acquiring a first-level road type of a road on which the vehicle is currently travelling;
the control module is used for controlling the vehicle to enter a driving mode corresponding to the primary road type, wherein the driving mode comprises control parameters of each electric control system of the vehicle;
the second acquisition module is used for acquiring the wheel speed information of the vehicle and acquiring the vehicle dynamic information of the vehicle in the driving mode;
The third acquisition module is used for acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information;
the fourth acquisition module is used for acquiring a target three-level road type from three-level road types included in the target two-level road type according to the vehicle dynamic information;
the determining module is used for determining compensation parameters for each electric control system according to the target three-level road type;
And the adjusting module is used for adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a processor, a memory, and a program or an instruction stored in the memory and executable on the processor, where the program or the instruction implements the steps of the foregoing vehicle control method when executed by the processor.
In a fourth aspect, embodiments of the present application also provide a readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps of the aforementioned vehicle control method.
In the embodiment of the invention, the first-level road type of the road on which the vehicle is currently travelling is firstly obtained, and the vehicle is controlled to enter a driving mode corresponding to the first-level road type, wherein the driving mode comprises control parameters of each electric control system of the vehicle. And in the driving mode, acquiring wheel speed information and vehicle dynamic information of the vehicle, acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information, and acquiring a target tertiary road type from tertiary road types included in the target secondary road type according to the vehicle dynamic information. And finally, after determining the compensation parameters of each electric control system according to the target three-level road type, adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system. According to the invention, the wheel speed information and the vehicle dynamic information are acquired to further progressively subdivide the first-class road type, and the vehicle can finely adjust the control parameters of each electric control system of the vehicle according to the subdivided road type, so that the finely adjusted control parameters are most matched with the characteristics of the road on which the vehicle is currently running, and the vehicle can maintain excellent performance in various road environments. Meanwhile, the method and the device do not need to judge the road type and manually select the driving mode by a driver, and are automatically executed by the vehicle, so that the driving experience is improved. In addition, the wheel speed information and the vehicle dynamic information obtained by the invention are essentially driven and controlled by a driver, and indirectly embody the operation style of the driver. Therefore, the finely-adjusted control parameters of each electric control system of the vehicle also accord with the operation style of a driver, and the driving experience of the user is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a vehicle control method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of road type classification according to an embodiment of the present invention;
FIG. 3 is a flow chart of another vehicle control method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of three-level road progressive three-level classification according to an embodiment of the present invention;
fig. 5 is a block diagram of a vehicle control apparatus according to an embodiment of the present invention;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present invention;
fig. 7 is a schematic hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Prior to describing the present invention, the prior art will be described:
In the prior art, a plurality of driving modes are preset by a person skilled in the art, a standard mode is set for paved roads, and a snow mode, a sand mode, a mud mode, a rock mode and the like can be set for non-paved roads. And, for each electric control system of each driving mode, corresponding control parameters are preset. One skilled in the art also provides a rotary switch or a plurality of keys on the vehicle, which are activated to switch to the corresponding driving mode. As shown in the following table 1,
In the driving process of the driver, the driver can manually select a corresponding driving mode according to the road condition observed by the sight line, at the moment, the main controller of the vehicle can inquire the table 1, and each electric control system (an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system and an ESP vehicle body stability control system) is controlled to operate according to preset control parameters.
However, the inventor found that in practical application, the complexity of the road and the diversity of the road characteristics are far more than the limited cases. For example, under snowy road conditions, there are soft and compacted snow conditions, and under different snow conditions, the control parameters required by the various electrical control systems of the vehicle are not the same. In the prior art, under different snowfields, if manual adjustment is not performed, the control parameters adopted by each electric control system are not automatically changed, so that the vehicle cannot maintain excellent performance in various road environments.
The inventor of the application proposes the following ideas that after the primary road type of the current road of the vehicle is primarily determined, the vehicle is controlled to enter a corresponding driving mode, and then the current road is progressively determined by acquiring wheel speed information and vehicle dynamic information, so as to determine compensation parameters according to the finally determined target tertiary road type, and the compensation parameters are utilized to compensate the control parameters of each electric control system. Therefore, the vehicle can be flexibly and conveniently regulated and controlled according to the characteristics and the complexity of an actual road, excellent performance can be kept in various road environments, manual judgment is not needed, and the driving experience of a user is improved.
The following is a detailed description:
referring to fig. 1, a flowchart of a vehicle control method provided by an embodiment of the present invention is shown.
Step S101, obtaining a first-level road type of a road on which a vehicle is currently travelling;
In the application, the first-level road can be an off-road in a non-paved road, and the first-level road type can comprise various road types such as a sand road, a mud road, a snow road, a mountain road and the like in the off-road condition. Specifically, a camera mounted on a front bumper or a front windshield of the vehicle may be used to obtain which primary road type the vehicle is currently traveling on.
Step S102, controlling the vehicle to enter a driving mode corresponding to the primary road type, wherein the driving mode comprises control parameters of each electric control system of the vehicle;
In the application, different first-level road types correspond to different driving modes, and the control parameters of each electric control system of the vehicle corresponding to each driving mode are different. The electric control system of the vehicle comprises an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system and an ESP vehicle body stability control system. For each electric control system, corresponding control parameters in different driving modes are preset. The driving mode corresponding to the sand road is a sand mode, the driving mode corresponding to the mud road is a mud mode, the driving mode corresponding to the snow road is a snow mode, and the driving mode corresponding to the mountain road is a mountain mode.
Specifically, by way of example, when the road on which the vehicle is currently running is obtained as a sand, the vehicle enters a sand driving mode, and respective control parameters are adjusted to the sand driving mode by corresponding control of each electric control system, such as an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system and an ESP body stability control system. In the embodiment of the application, the vehicle is controlled by the vehicle ECU (electronic control unit) to enter the driving mode corresponding to the primary road type.
It should be noted that in the prior art, the road type is judged by the user by eyes and the corresponding driving mode is manually selected, and the judgment of the first-level road type and the entering of the corresponding driving mode are automatically executed by the vehicle system, so that the user experience is improved.
Step 103, acquiring wheel speed information of the vehicle and vehicle dynamic information of the vehicle in the driving mode;
In the application, in order to realize the further division of the primary road types, after entering a driving mode corresponding to the primary road types, the wheel speed information and the vehicle dynamic information of the vehicle are acquired to sequentially determine which secondary road type and which tertiary road type the vehicle is currently driving on. Specifically, wheel speed information of the vehicle is acquired by a four-wheel speed sensor of the vehicle, and vehicle dynamic information is acquired by a longitudinal acceleration sensor and a lateral acceleration sensor of the vehicle.
Step S104, acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information;
In the application, when the first-level road type is a sand road, the second-level road type included in the sand road is a soft sand road and a hard sand road, when the first-level road type is a mud road, the second-level road type included in the mud road is a smooth mud road and a deep mud road, when the first-level road type is a mountain road, the second-level road type included in the mountain road is a pothole road and a cross axle, and when the first-level road type is a snow road, the second-level road type included in the snow road is a snow road. It should be noted that, for the snowfield road, those skilled in the art may not set the secondary road type of the snowfield road, which is within the protection scope of the present application.
Specifically, after the vehicle ECU obtains the wheel speed information of the vehicle according to the four-wheel speed sensor of the vehicle, the vehicle ECU can further judge which secondary road type the current road of the vehicle belongs to based on the current primary road type of the vehicle.
Step 105, according to the vehicle dynamic information, acquiring a target tertiary road type from tertiary road types included in the target secondary road type;
In the application, when the secondary road type is a soft sand road, the three-level road type included in the soft sand road comprises a rolling soft sand road and a leveling soft sand road, when the secondary road type is a hard sand road, the three-level road type included in the hard sand road comprises a rolling hard sand road and a leveling hard sand road, when the secondary road type is a smooth mud road, the three-level road type included in the smooth mud road comprises a smooth mud road, when the secondary road type is a deep mud road, the three-level road type included in the deep mud road comprises a deep mud track road and a deep mud pool road, when the secondary road type is a snow road, the three-level road type included in the snow road comprises a soft snow road and a compacting snow road, when the secondary road type is a pothole road, the three-level road type included in the snow road comprises a cross road, and when the secondary road type is a cross road, the cross road comprises a cross road. It should be noted that, for smooth mud roads, hollow roads and crossed-axis roads, those skilled in the art may not set the respective three-level road types, which are all within the scope of the present application. As in fig. 2, a road type classification diagram is shown. From fig. 2, the person skilled in the art can see the dependency between the primary road type, the secondary road type and the tertiary road type.
Specifically, after the vehicle ECU obtains the vehicle dynamic information according to the longitudinal acceleration sensor and the lateral acceleration sensor of the vehicle, it can further determine which three-level road type the current road of the vehicle belongs to based on the current two-level road type of the vehicle.
Step S106, determining compensation parameters for each electric control system according to the target three-level road type;
In the application, as shown in the following table 2, the adjustment mode comparison table of EMS, TCU, four-wheel drive, suspension and ESP under the road conditions of each three-level road type is specifically shown:
After the target three-level road type is determined, referring to the adjustment mode comparison table, the adjustment mode of each electric control system of the corresponding target three-level road type can be found. After a specific adjustment mode is found from the above table 2, a preset three-level road type parameter table may be queried according to the specific adjustment mode. The preset three-level road type parameter table comprises specific compensation parameters corresponding to the adjustment modes of the electric control systems of each three-level road type, namely compensation parameters of an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system and an ESP vehicle body stability control system corresponding to each three-level road type. After the target three-level road type is determined, the specific compensation parameters of each electric control system of the target three-level road type are obtained by searching a parameter adjustment comparison table.
And step S107, adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system.
In the application, after the first-level road type is acquired, the vehicle is controlled to enter a corresponding driving mode, that is, each electric control system of the vehicle is controlled to run with preset control parameters, and after the target third-level road type is determined subsequently, the preset control parameters of each electric control system are compensated by using the corresponding compensation parameters. In the application, the running of the vehicle is controlled by adopting parameter compensation in a mode of fine adjustment of the control parameters of each electric control system of the target driving mode, so that the vehicle system can correspondingly fine-adjust the control parameters even facing roads with different complexity in the running process of the vehicle, and the complexity of the vehicle control logic is reduced.
In the embodiment of the invention, the first-level road type of the road on which the vehicle is currently travelling is firstly obtained, and the vehicle is controlled to enter a driving mode corresponding to the first-level road type, wherein the driving mode comprises control parameters of each electric control system of the vehicle. And in the driving mode, acquiring wheel speed information and vehicle dynamic information of the vehicle, acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information, and acquiring a target tertiary road type from tertiary road types included in the target secondary road type according to the vehicle dynamic information. And finally, after determining the compensation parameters of each electric control system according to the target three-level road type, adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system. According to the invention, the wheel speed information and the vehicle dynamic information are acquired to further progressively subdivide the first-class road type, and the vehicle can finely adjust the control parameters of each electric control system of the vehicle according to the subdivided road type, so that the finely adjusted control parameters are most matched with the characteristics of the road on which the vehicle is currently running, and the vehicle can maintain excellent performance in various road environments. Meanwhile, the method and the device do not need to judge the road type and manually select the driving mode by a driver, and are automatically executed by the vehicle, so that the driving experience is improved. In addition, the wheel speed information and the vehicle dynamic information obtained by the invention are essentially driven and controlled by a driver, and indirectly embody the operation style of the driver. Therefore, the finely-adjusted control parameters of each electric control system of the vehicle also accord with the operation style of a driver, and the driving experience of the user is improved.
Referring to fig. 3, a flowchart of another vehicle control method provided by an embodiment of the present invention is shown.
Step 301, obtaining image information of a road on which the vehicle is currently travelling;
In the application, when the vehicle runs in the off-road condition, the camera installed on the front bumper or the front windshield of the vehicle collects the image information in front of the vehicle running. When the image information is acquired, the camera acquires a plurality of images in front of the vehicle, so that enough samples are ensured, and the accuracy of primary road type judgment is improved. After the vehicle ECU acquires a plurality of images of the color base of the camera, de-duplication and key frame extraction are carried out on the images, images with representativeness and high resolution are selected, then the screened images are input into a pre-trained pavement recognition model,
Step S302, inputting the image information into a pre-trained pavement recognition model;
In the embodiment of the invention, a pavement recognition model is preset, and the pavement recognition model is used for determining which primary road type is closest to the input image information according to preset judging conditions. The preset judging conditions of the road surface recognition model can be set as the similarity of the image information and the textures, colors and gray scales of each level of road type. The image information collected by the camera comprises color characteristics, texture characteristics and gray scale characteristics. The person skilled in the art can set different judging conditions according to the actual requirements, and the invention is not limited to the above, and the invention is within the protection scope.
Step S303, determining the first-level road type according to the road type similarity output by the road surface recognition model;
Specifically, after the image information collected by the camera is input into the road surface recognition model, the road surface recognition model determines the road type similarity of the input image and each first-level road type by judging the similarity of the color features, texture features and gray features of the image and the color, texture and gray of each first-level road type, and the road surface input model sorts the similarity of each road type from high to low and outputs the sorted similarity to the ECU, so that the ECU can determine the first-level road type of the road on which the vehicle is currently running according to the sorting of the similarity.
The steps S301 to S303 are specific descriptions of the step S101.
Step S304, controlling the vehicle to enter a driving mode corresponding to the primary road type, wherein the driving mode comprises control parameters of each electric control system of the vehicle;
In the present application, the implementation manner of step S304 refers to step S102, and is not described herein.
Step S305, acquiring wheel speed information of the vehicle and acquiring vehicle dynamic information of the vehicle in the driving mode;
optionally, the acquiring wheel speed information of the vehicle comprises sampling a vehicle speed of each wheel to acquire a plurality of speed values;
specifically, wheel speed information of the vehicle is acquired by a vehicle four-wheel speed sensor. Typically, the left front wheel speed V fl, the right front wheel speed V fr, the left rear wheel speed V rl, and the right rear wheel speed V rr of the vehicle are acquired, respectively. Meanwhile, when the wheel speed information of the vehicle is acquired, sampling is performed for the vehicle speed of each wheel, and a plurality of speed values are acquired. For example, the vehicle speed of the left front wheel is sampled a plurality of times, and 10 pieces of left front wheel speed information are acquired. Those skilled in the art may also obtain wheel speed information through the CAN bus of the vehicle or software internal variables, which are not limited in this regard and are all within the scope of protection.
Optionally, the acquiring the vehicle dynamic information of the vehicle comprises sampling the acceleration of the vehicle in a preset time period to acquire multiple groups of acceleration information, wherein each group of acceleration information comprises a transverse acceleration value and a longitudinal acceleration value;
Specifically, a longitudinal acceleration sensor and a lateral acceleration sensor of the vehicle are utilized to acquire a lateral acceleration value and a longitudinal acceleration value of the vehicle within a preset time period. The preset time period can be set by those skilled in the art according to actual needs.
Step S306, acquiring a target secondary road type from the secondary road types included in the primary road type according to the wheel speed information;
According to the wheel speed information obtained, the first-level road type on which the vehicle is currently running can be further subdivided. For example, the type of the primary road on which the vehicle is currently running is a sandy road, and after the wheel speed information is obtained and calculated, it is further determined that the type of the secondary road on which the vehicle is currently running is a soft sandy road, that is, the type of the target secondary road is a soft sandy road.
Optionally, the step S306 includes the following steps:
step S3061, determining a power spectrum density value of each wheel by using the Basseva formula and the speed values of each wheel;
specifically, the bazival formula is:
PSDi[n,k]＝Fi[n,k]Fi *[n,k];
Wherein the said PSD i [ N, k ] is the power spectrum density value of wheel i, i is any one wheel of left front wheel fl, right front wheel fr, left rear wheel rl and right rear wheel rr, N is each sampling time, k is frequency, m is the sampling point of wheel speed information, N is the total number of sampling points, V i (m, k) is the wheel speed of the wheel i at the frequency k and the m sampling point, e is an index, the value is 2.71828, j is an imaginary unit, and the value is an imaginary unit
Wherein F i * [ n, k ] is the complex conjugate of F i [ n, k ].
In the embodiment of the invention, the left front wheel power spectrum density PSD fl, the right front wheel power spectrum density PSD fr, the left rear wheel power spectrum density PSD rl and the right rear wheel power spectrum density PSD rr can be respectively calculated by adopting the Basseva formula.
Step S3062, obtaining a target secondary road type from the secondary road types included in the primary road type according to the power spectral density values of the wheels and preset conditions corresponding to the secondary road types included in the primary road type;
In the application, the first-level road type has a corresponding power spectrum density maximum preset threshold value and a corresponding power spectrum density minimum preset threshold value. For example, when the primary road type is a sand road, it has a power spectral density maximum preset threshold of 1.5×10 3 and a minimum preset threshold of 1×10 3 for the sand road. Accordingly, other primary road types are also similar having a power spectral density maximum preset threshold and a minimum preset threshold.
And corresponding preset conditions are set for each secondary road type under the primary road type. The road type is a soft sand road, the preset condition is that the total power spectrum density value of the wheels is larger than or equal to the maximum preset threshold value 1.5X10 3 of the sand power spectrum density, the preset condition is that the total power spectrum density value of the wheels is smaller than the minimum preset threshold value 1×10 3 of the sand power spectrum density when the road type is a hard sand road, the preset condition is that the total power spectrum density value of the wheels is larger than or equal to the maximum preset threshold value 2×10 3 of the sand power spectrum density when the road type is a deep mud road, the preset condition is that the total power spectrum density value of the wheels is larger than or equal to the maximum preset threshold value 2×10 3 of the sand power spectrum density when the road type is a smooth mud road, the preset condition is that the total power spectrum density value of the wheels is smaller than the minimum preset threshold value 1×10 3 of the sand power spectrum density when the road type is a pothole road, the preset condition is that the total power spectrum density value of the wheels is larger than or equal to the maximum preset threshold value 5×10 3 of the mountain power spectrum density when the road type is a cross axle, and the preset condition is that the total power spectrum density value of the wheels is smaller than the minimum preset threshold value 3×10 3 of the mountain power spectrum density when the road type is a cross axle.
Optionally, step S3062 may further include the sub-steps of:
Step S30321, calculating the sum of the power spectral density values of all the wheels to obtain a total power spectral density value;
Specifically, after the front left power spectral density PSD fl, the front right power spectral density PSD fr, the rear left power spectral density PSD rl and the rear right power spectral density PSD rr are calculated in the aforementioned step S3061, the total power spectral density value PSD total＝PSDfl+PSDfr+PSDrl+PSDrr is calculated.
Step S30622, comparing the total power spectral density value with a maximum preset threshold value and a minimum preset threshold value of the power spectral density of the primary road type respectively to obtain a comparison result;
In the application, after the total power common density value is determined, the total power spectrum density value is compared with the maximum preset threshold value and the minimum preset threshold value of the power spectrum density of the first-level road type on which the vehicle is currently running. For example, if the type of the first-level road on which the vehicle is currently traveling is a sand road, it is determined that the total power spectral density value is 1.7x10 3, and the maximum preset threshold value of the power spectral density of the sand road is 1.5x10 3 and the minimum preset threshold value is 1 x 10 3, then 1.7x10 3 is respectively compared with 1.5x10 3、1×103, and the final comparison result is that the total power spectral density value is greater than the maximum preset threshold value of the power spectral density of the sand road.
Sub-step S30623, determining preset conditions which are met by the comparison result;
Specifically, referring to the exemplary illustration of substep S30622, the comparison results in a total power spectral density value greater than the maximum preset threshold for the power spectral density of the sand road, and the preset condition is that the wheel total power spectral density value is greater than or equal to the maximum preset threshold for the sand power spectral density of 1.5X10 3 when the secondary road type is a soft sand road. Obviously, the comparison result meets the preset conditions of the soft sandy road.
And a substep S30624, namely taking the secondary road type corresponding to the preset condition as a target secondary road type.
Specifically, referring to the exemplary description of substep S30623, since the comparison result meets the preset condition of the soft sandy road, the target secondary road type is the soft sandy road.
In the present application, the above sub-steps S30622 to S30624 can be simplified as follows:
if the PSD total≥PSD sand land is the maximum preset threshold, the type of the target secondary road is a soft sandy road;
If the minimum preset threshold of the PSD total＜PSD sand land is set, the type of the target secondary road is a hard sand road;
if the PSD total≥PSD Mud land is the maximum preset threshold, the target secondary road type is a deep mud road;
if the minimum preset threshold of the PSD total＜PSD Mud land is set, the target secondary road type is a smooth mud road;
If the PSD total≥PSD Mountain land is the maximum preset threshold, the target secondary road type is a hollow road;
If the minimum preset threshold of PSD total＜PSD Mountain land is reached, the target secondary road type is cross-axis.
When the first road type is a snowfield road, the second road type of the snowfield road is not divided. In the embodiment of the invention, when the first-level road type is determined to be a snowfield road, the total power spectral density of vehicles under the snowfield road is not calculated any more. It should be noted that, those skilled in the art may further divide the snowfield road into two road types according to actual needs, and the embodiments of the present invention are not limited thereto, and are all within the scope of protection.
Step S307, according to the vehicle dynamic information, acquiring a target three-level road type from three-level road types included in the target two-level road type;
in the application, the off-road condition also relates to the condition of relief of the terrain. And on the basis of determining the type of the target secondary road, the road conditions are further divided. For example, after the dynamic information of the vehicle is obtained, it is further determined in step S307 that the road on which the vehicle is currently running is a rough and soft sandy road, and then the three-level road type of the target is a rough and soft sandy road.
Alternatively, step S307 may include the steps of:
Step S3071, carrying out weighting operation on each group of acceleration values to obtain a single group of vehicle dynamic indexes;
in the embodiment of the invention, the single-group vehicle dynamic index adopts the following calculation mode:
Wherein, Is the firstThe vehicle dynamics index, k 1(0<k1 < 1), of the individual sampling points is the vehicle longitudinal-lateral acceleration distribution coefficient,Is the firstThe lateral acceleration of the vehicle at the sampling points,Is the firstThe longitudinal acceleration of the vehicle at the sampling points,Is a sampling point of the dynamic information of the vehicle,For example, if three sets of vehicle dynamic information are obtained within a preset time, the vehicle dynamic indexes of each single set are respectively calculated to be Veh_Index 1,Veh_Index2,Veh_Index3.
Step S3072, determining an average vehicle dynamic index in the preset time period according to a plurality of single-group vehicle dynamic indexes;
Alternatively, step S3072 may be implemented by:
Calculating the sum of the dynamic indexes of each single group of vehicles to obtain a total dynamic index of the vehicle;
Dividing the duration of a preset time period by a sampling period to obtain sampling times;
dividing the total vehicle dynamic index by the sampling times to obtain the average vehicle dynamic index.
That is, in the embodiment of the present invention, the average vehicle dynamic index is obtained by the following calculation method:
Where veh_index_avg is the average vehicle dynamic Index, time is the preset Time period, T is the sampling period, Is a sampling point of the dynamic information of the vehicle,
It should be noted that, those skilled in the art can use other calculation methods, as long as the concept of summing and averaging is satisfied to obtain the average vehicle dynamic index, which is within the scope of the present invention.
And step S3073, obtaining a target three-level road type from the three-level road types included in the target two-level road type according to the average vehicle dynamic index and preset conditions corresponding to the three-level road types included in the target two-level road type.
In the application, corresponding preset conditions are set for three-level road types. The three-level road type is a smooth soft sand, and the preset condition is that the average dynamic index is smaller than the minimum threshold value of the dynamic index of the vehicle when the vehicle runs on the soft sand, wherein the minimum threshold value of the dynamic index of the vehicle when the vehicle runs on the soft sand can take the value of 6;
When the three-level road type is a smooth hard sand, the preset condition is that the average dynamic index is smaller than the minimum threshold value of the vehicle dynamic index when the vehicle runs on the hard sand, wherein the minimum threshold value of the vehicle dynamic index when the vehicle runs on the hard sand can take the value of 5;
When the three-level road type is a deep mud rut, the preset condition is that the average dynamic index is larger than or equal to the minimum threshold value of the vehicle dynamic index when the vehicle runs in the deep mud rut, and when the three-level road type is a deep mud puddle, the preset condition is that the average dynamic index is smaller than the minimum threshold value of the vehicle dynamic index when the vehicle runs in the deep mud rut, wherein the minimum threshold value of the vehicle dynamic index when the vehicle runs in the deep mud rut can take the value of 4;
When the three-level road type is soft snow, the preset condition is that the average dynamic index is larger than or equal to the minimum threshold value of the vehicle dynamic index when the vehicle runs on the snow, and when the three-level road type is compacted snow, the preset condition is that the average dynamic index is smaller than the minimum threshold value of the vehicle dynamic index when the vehicle runs on the snow, wherein the minimum threshold value of the vehicle dynamic index when the vehicle runs on the snow can take the value of 3.
Specifically, if Veh_Index_Avg is equal to or greater than Veh_Index_min Soft sandy land , the target three-level road type is a rough and soft sand;
if Veh_Index_Avg < Veh_Index_min Soft sandy land , the target three-level road type is smooth and soft sand;
If Veh_Index_Avg is more than or equal to Veh_Index_min hard sand , the target three-level road type is a rolling hard sand;
if Veh_Index_Avg < Veh_Index_min hard sand , the target three-level road type is a smooth hard sand;
If Veh_Index_Avg is more than or equal to Veh_Index_min Deep mud land , the target three-level road type is deep mud rutting;
if Veh_Index_Avg < Veh_Index_min Deep mud land , then the target three-level road type is deep puddle;
If Veh_Index_Avg is more than or equal to Veh_Index_min Snow field , the target three-level road type is soft snowfield;
If Veh_Index_Avg < Veh_Index_min Snow field , then the target three-level road type is compacted snow;
For the two-level road types of smooth mud, hollow roads and crossed shafts, the respective three-level road types are not divided. In the embodiment of the invention, when the type of the secondary road is determined to be smooth mud land, a hollow road or a cross axle, the average vehicle dynamic indexes of the secondary road are not calculated. It should be noted that, those skilled in the art may further divide the smooth mud land, the hollow road and the cross axle according to actual needs, and the embodiments of the present invention are not limited thereto, and are all within the scope of protection.
It should be noted that, in the above-mentioned progressive three-layer classification process, reference may be made to the schematic diagram of fig. 4.
Step 308, determining compensation parameters for each electric control system according to the target three-level road type;
in the application, three-level road type parameter tables are preset. And searching a preset three-level road type parameter table according to the determined target three-level road type, and determining compensation parameters for each electric control system. The three-level road type parameter table comprises compensation parameters of each three-level road type for an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system and an ESP vehicle body stability control system.
Step 309, adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system.
In the present application, the implementation process of step S309 is referred to the above-mentioned step S107, and will not be described herein.
In summary, in the embodiment of the present invention, a first-level road type of a road on which a vehicle is currently traveling is obtained first, and the vehicle is controlled to enter a driving mode corresponding to the first-level road type, where the driving mode includes control parameters of each electronic control system of the vehicle. And in the driving mode, acquiring wheel speed information and vehicle dynamic information of the vehicle, acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information, and acquiring a target tertiary road type from tertiary road types included in the target secondary road type according to the vehicle dynamic information. And finally, after determining the compensation parameters of each electric control system according to the target three-level road type, adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system. According to the invention, the wheel speed information and the vehicle dynamic information are acquired to further progressively subdivide the first-class road type, and the vehicle can finely adjust the control parameters of each electric control system of the vehicle according to the subdivided road type, so that the finely adjusted control parameters are most matched with the characteristics of the road on which the vehicle is currently running, and the vehicle can maintain excellent performance in various road environments. Meanwhile, the method and the device do not need to judge the road type and manually select the driving mode by a driver, and are automatically executed by the vehicle, so that the driving experience is improved. In addition, the wheel speed information and the vehicle dynamic information obtained by the invention are essentially driven and controlled by a driver, and indirectly embody the operation style of the driver. Therefore, the finely-adjusted control parameters of each electric control system of the vehicle also accord with the operation style of a driver, and the driving experience of the user is improved.
Referring to fig. 5, a block diagram of a vehicle control apparatus 400 according to an embodiment of the present invention is shown, where the apparatus 400 includes the following modules:
a first obtaining module 401, configured to obtain a first-level road type of a road on which the vehicle is currently traveling;
A control module 402, configured to control the vehicle to enter a driving mode corresponding to the first-level road type, where the driving mode includes control parameters of each electronic control system of the vehicle;
A second obtaining module 403, configured to obtain wheel speed information of the vehicle and obtain vehicle dynamic information of the vehicle in the driving mode;
A third obtaining module 404, configured to obtain a target secondary road type from secondary road types included in the primary road type according to the wheel speed information;
A fourth obtaining module 405, configured to obtain, according to the vehicle dynamic information, a target tertiary road type from tertiary road types included in the target secondary road type;
a determining module 406, configured to determine compensation parameters for each of the electronic control systems according to the target three-level road type;
an adjusting module 407, configured to adjust the control parameters of the corresponding electronic control system based on the compensation parameters of each electronic control system.
Optionally, the second obtaining module 403 is specifically configured to sample a vehicle speed of each wheel to obtain a plurality of speed values;
optionally, the third obtaining module 404 includes:
The power spectrum density determining module is used for determining the power spectrum density value of each wheel by using the Basselva formula and a plurality of speed values of each wheel;
The target secondary road type acquisition module is used for acquiring a target secondary road type from the secondary road types included in the primary road type according to the power spectrum density values of all the wheels and preset conditions corresponding to the secondary road types included in the primary road type;
wherein, the Basseva formula is:
PSDi[n,k]＝Fi[n,k]Fi *[n,k];
Wherein the said PSD i [ N, k ] is the power spectrum density value of wheel i, i is any one wheel of left front wheel fl, right front wheel fr, left rear wheel rl and right rear wheel rr, N is each sampling time, k is frequency, m is the sampling point of wheel speed information, N is the total number of sampling points, V i (m, k) is the wheel speed of the wheel i at the frequency k and the m sampling point, e is an index, the value is 2.71828, j is an imaginary unit, and the value is an imaginary unit
Wherein F i * [ n, k ] is the complex conjugate of F i [ n, k ].
Optionally, the target secondary road type obtaining module includes:
The total power spectrum density value acquisition module is used for calculating the sum of the power spectrum density values of all the wheels to obtain a total power spectrum density value;
the comparison module is used for comparing the total power spectrum density value with a maximum preset threshold value and a minimum preset threshold value of the power spectrum density of the primary road type respectively to obtain a comparison result;
the result determining module is used for determining preset conditions which are met by the comparison result;
and the target secondary road type determining module is used for taking the secondary road type corresponding to the preset condition as a target secondary road type.
Optionally, the second obtaining module 403 is specifically configured to sample acceleration of the vehicle in a preset period of time to obtain multiple sets of acceleration information, where each set of acceleration information includes a lateral acceleration value and a longitudinal acceleration value;
the fourth obtaining module 405 includes:
the single-group index acquisition module is used for carrying out weighting operation on each group of acceleration values to acquire a single-group vehicle dynamic index;
The average index acquisition module is used for determining average vehicle dynamic indexes in the preset time period according to a plurality of single-group vehicle dynamic indexes;
And the target three-level road type acquisition module is used for acquiring the target three-level road type from the three-level road types included in the target two-level road type according to the average vehicle dynamic index and the preset condition corresponding to the three-level road type included in the target two-level road type.
The average index obtaining module is specifically configured to calculate a sum of the vehicle dynamic indexes of each single group to obtain a total vehicle dynamic index, divide a duration of a preset time period by a sampling period to obtain a sampling number, and divide the total vehicle dynamic index by the sampling number to obtain the average vehicle dynamic index.
Optionally, the first obtaining module 401 includes:
the image information acquisition module is used for acquiring image information of a road on which the vehicle is currently travelling;
the input module is used for inputting the image information into a pre-trained pavement recognition model;
And the output module is used for determining the first-level road type according to the road type similarity output by the road surface recognition model.
Optionally, the determining module 406 is specifically configured to search a preset three-level road type parameter table according to the target three-level road type, and determine compensation parameters for each electronic control system, where the three-level road type parameter table includes compensation parameters for each three-level road type respectively for an EMS engine management system, a TCU automatic gearbox control unit, a four-wheel drive system, a suspension system, and an ESP body stability control system.
In summary, in the embodiment of the present invention, a first-level road type of a road on which a vehicle is currently traveling is obtained first, and the vehicle is controlled to enter a driving mode corresponding to the first-level road type, where the driving mode includes control parameters of each electronic control system of the vehicle. And in the driving mode, acquiring wheel speed information and vehicle dynamic information of the vehicle, acquiring a target secondary road type from secondary road types included in the primary road type according to the wheel speed information, and acquiring a target tertiary road type from tertiary road types included in the target secondary road type according to the vehicle dynamic information. And finally, after determining the compensation parameters of each electric control system according to the target three-level road type, adjusting the control parameters of the corresponding electric control system based on the compensation parameters of each electric control system. According to the invention, the wheel speed information and the vehicle dynamic information are acquired to further progressively subdivide the first-class road type, and the vehicle can finely adjust the control parameters of each electric control system of the vehicle according to the subdivided road type, so that the finely adjusted control parameters are most matched with the characteristics of the road on which the vehicle is currently running, and the vehicle can maintain excellent performance in various road environments. Meanwhile, the method and the device do not need to judge the road type and manually select the driving mode by a driver, and are automatically executed by the vehicle, so that the driving experience is improved. In addition, the wheel speed information and the vehicle dynamic information obtained by the invention are essentially driven and controlled by a driver, and indirectly embody the operation style of the driver. Therefore, the finely-adjusted control parameters of each electric control system of the vehicle also accord with the operation style of a driver, and the driving experience of the user is improved.
Referring to fig. 6, an embodiment of the present invention further provides an electronic device 500, including a processor 502, a memory 501, and a computer program or instructions stored in the memory 501 and capable of running on the processor 502, where the program or instructions implement each process of the vehicle control method described above when executed by the processor 502, and achieve the same technical effects, and for avoiding repetition, a detailed description is omitted herein.
Referring to fig. 7, a schematic diagram of the hardware structure of an electronic device implementing the present application is shown.
The electronic device 600 includes, but is not limited to, a radio frequency unit 601, a network module 602, an audio output unit 603, an input unit 604, a sensor 605, a display unit 606, a user input unit 607, an interface unit 608, a memory 609, and a processor 610.
Those skilled in the art will appreciate that the electronic device 600 may further include a power source (e.g., a battery) for powering the various components, which may be logically connected to the processor 610 by a power management system to perform functions such as managing charge, discharge, and power consumption by the power management system. The electronic device structure shown in fig. 6 does not constitute a limitation of the electronic device, and the electronic device may include more or less components than shown, or may combine certain components, or may be arranged in different components, which are not described in detail herein.
Optionally, the present invention provides a readable storage medium, where a program or an instruction is stored, where the program or the instruction realizes each process of the vehicle control method when executed by a processor, and the same technical effect can be achieved, and for avoiding repetition, a description is omitted here.
Wherein the processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium such as a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and the like.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.

Claims (8)

1.一种车辆控制方法，其特征在于，包括：1. A vehicle control method, comprising: 获取车辆当前所行使道路的一级道路类型；Get the primary road type of the road the vehicle is currently traveling on; 控制所述车辆进入与所述一级道路类型相对应的驾驶模式；其中，所述驾驶模式包括所述车辆的各电控系统的控制参数；Controlling the vehicle to enter a driving mode corresponding to the primary road type; wherein the driving mode includes control parameters of each electronic control system of the vehicle; 在所述驾驶模式下，获取所述车辆的轮速信息，及获取所述车辆的车辆动态信息；In the driving mode, obtaining wheel speed information of the vehicle and obtaining vehicle dynamic information of the vehicle; 根据所述轮速信息，从所述一级道路类型包括的二级道路类型中获取目标二级道路类型；According to the wheel speed information, acquiring a target secondary road type from the secondary road types included in the primary road type; 根据所述车辆动态信息，从所述目标二级道路类型包括的三级道路类型中获取目标三级道路类型；According to the vehicle dynamic information, obtaining a target third-level road type from the third-level road types included in the target second-level road type; 根据所述目标三级道路类型，确定对各所述电控系统的补偿参数；Determining compensation parameters for each of the electronic control systems according to the target third-level road type; 基于各所述电控系统补偿参数调节相应电控系统的所述控制参数；adjusting the control parameters of the corresponding electronic control system based on the compensation parameters of each electronic control system; 所述获取所述车辆的车辆动态信息，包括：The obtaining of vehicle dynamic information of the vehicle comprises: 在预设时间段内对所述车辆的加速度进行采样，获取多组加速度信息；其中，每组加速度信息包括横向加速度值和纵向加速度值；Sampling the acceleration of the vehicle within a preset time period to obtain multiple sets of acceleration information; wherein each set of acceleration information includes a lateral acceleration value and a longitudinal acceleration value; 所述根据所述车辆动态信息，从所述目标二级道路类型包括的三级道路类型中获取目标三级道路类型，包括：The step of acquiring the target third-level road type from the third-level road types included in the target second-level road type according to the vehicle dynamic information comprises: 对每组加速度值进行加权运算，获取单组车辆动态指数；Perform weighted calculation on each group of acceleration values to obtain a single group of vehicle dynamic index; 根据多个所述单组车辆动态指数，确定所述预设时间段内的平均车辆动态指数；Determining an average vehicle dynamic index within the preset time period according to the plurality of single-group vehicle dynamic indexes; 根据所述平均车辆动态指数，以及所述目标二级道路类型包括的三级道路类型所对应的预设条件，从所述目标二级道路类型包括的三级道路类型中获取目标三级道路类型；According to the average vehicle dynamic index and the preset conditions corresponding to the third-level road types included in the target secondary road types, a target third-level road type is obtained from the third-level road types included in the target secondary road types; 所述根据所述目标三级道路类型，确定对各所述电控系统的补偿参数，包括：Determining compensation parameters for each of the electronic control systems according to the target third-level road type includes: 根据所述目标三级道路类型，查找预设的三级道路类型参数表，确定对各所述电控系统的补偿参数；所述三级道路类型参数表包括：每个三级道路类型分别针对EMS发动机管理系统、TCU自动变速箱控制单元、四轮驱动系统、悬架系统、ESP车身稳定控制系统的补偿参数。According to the target third-level road type, a preset third-level road type parameter table is searched to determine the compensation parameters for each of the electronic control systems; the third-level road type parameter table includes: compensation parameters for each third-level road type respectively for the EMS engine management system, TCU automatic transmission control unit, four-wheel drive system, suspension system, and ESP body stability control system. 2.根据权利要求1所述的方法，其特征在于，所述获取所述车辆的轮速信息，包括：2. The method according to claim 1, characterized in that the obtaining of the wheel speed information of the vehicle comprises: 针对每个车轮的车速进行采样，获取多个速度值；Sampling the vehicle speed of each wheel to obtain multiple speed values; 所述根据所述轮速信息，从所述一级道路类型包括的二级道路类型中获取目标二级道路类型，包括：The step of acquiring a target secondary road type from the secondary road types included in the primary road type according to the wheel speed information comprises: 利用巴塞伐公式以及每个车轮的多个速度值，确定各个车轮的功率谱密度值；Using the Basval formula and multiple speed values of each wheel, the power spectral density value of each wheel is determined; 根据各个车轮功率谱密度值，以及所述一级道路类型包括的二级道路类型所对应的预设条件，从所述一级道路类型包括的二级道路类型中获取目标二级道路类型；According to the power spectrum density values of each wheel and the preset conditions corresponding to the secondary road types included in the primary road types, a target secondary road type is obtained from the secondary road types included in the primary road types; 其中，所述巴塞伐公式为：Wherein, the Basval formula is: PSDi[n,k]＝Fi[n,k]Fi *[n,k]；PSD i [n, k] = F i [n, k] F i * [n, k]; 其中，所述PSDi[n,k]为车轮i的功率谱密度值；i为左前轮fl、右前轮fr、左后轮rl、右后轮rr中的任一车轮；n为每一个采样时刻；k为频率；m为轮速信息的采样点；N为采样点总数；Vi(m,k)为车轮i在频率k下，第m个采样点的车轮速度；e为指数，取值为2.71828；j为虚数单位，取值为 Among them, the PSD i [n,k] is the power spectrum density value of wheel i; i is any wheel among the left front wheel fl, the right front wheel fr, the left rear wheel rl, and the right rear wheel rr; n is each sampling moment; k is the frequency; m is the sampling point of the wheel speed information; N is the total number of sampling points; Vi (m,k) is the wheel speed of the mth sampling point of wheel i at frequency k; e is the exponent, with a value of 2.71828; j is the imaginary unit, with a value of 其中，Fi *[n,k]为Fi[n,k]的共轭复数。Here, Fi * [n,k] is the conjugate complex number of Fi [n,k]. 3.根据权利要求2所述的方法，其特征在于，所述根据各个车轮功率谱密度值，以及所述一级道路类型包括的二级道路类型所对应的预设条件，从所述一级道路类型包括的二级道路类型中获取目标二级道路类型，包括：3. The method according to claim 2, characterized in that the step of obtaining a target secondary road type from the secondary road types included in the primary road type according to the power spectrum density values of each wheel and the preset conditions corresponding to the secondary road types included in the primary road type comprises: 计算各个车轮功率谱密度值之和，获得总功率谱密度值；Calculate the sum of the power spectrum density values of each wheel to obtain the total power spectrum density value; 将所述总功率谱密度值分别与所述一级道路类型的功率谱密度最大预设阈值、最小预设阈值进行比较，得到比较结果；Compare the total power spectrum density value with the maximum preset threshold value and the minimum preset threshold value of the power spectrum density of the first-level road type respectively to obtain a comparison result; 确定所述比较结果符合的预设条件；Determining a preset condition that the comparison result meets; 将所述预设条件相对应的二级道路类型作为目标二级道路类型。The secondary road type corresponding to the preset condition is used as the target secondary road type. 4.根据权利要求1所述的方法，其特征在于，所述根据多个所述单组车辆动态指数，确定所述预设时间段内的平均车辆动态指数，包括：4. The method according to claim 1, characterized in that the step of determining the average vehicle dynamic index within the preset time period based on the plurality of single-group vehicle dynamic indexes comprises: 计算各个单组车辆动态指数之和，获得总车辆动态指数；Calculate the sum of the vehicle dynamic indexes of each single group to obtain the total vehicle dynamic index; 将预设时间段时长除以采样周期，获得采样次数；Divide the preset time period by the sampling period to obtain the number of sampling times; 将所述总车辆动态指数除以所述采样次数，获得所述平均车辆动态指数。The total vehicle dynamic index is divided by the sampling number to obtain the average vehicle dynamic index. 5.根据权利要求1所述的方法，其特征在于，所述获取车辆当前所行使道路的一级道路类型，包括：5. The method according to claim 1, characterized in that the step of obtaining the primary road type of the road currently traveled by the vehicle comprises: 获取所述车辆当前所行使道路的图像信息；Acquiring image information of the road currently traveled by the vehicle; 将所述图像信息，输入预先训练的路面识别模型；Inputting the image information into a pre-trained road surface recognition model; 依据所述路面识别模型输出的道路类型相似度，确定所述一级道路类型。The primary road type is determined according to the road type similarity output by the road surface recognition model. 6.一种车辆控制装置，其特征在于，包括：6. A vehicle control device, comprising: 第一获取模块，用于获取车辆当前所行使道路的一级道路类型；A first acquisition module is used to acquire the primary road type of the road currently traveled by the vehicle; 控制模块，用于控制所述车辆进入与所述一级道路类型相对应的驾驶模式；其中，所述驾驶模式包括所述车辆的各电控系统的控制参数；A control module, used to control the vehicle to enter a driving mode corresponding to the primary road type; wherein the driving mode includes control parameters of each electronic control system of the vehicle; 第二获取模块，用于在所述驾驶模式下，获取所述车辆的轮速信息，及获取所述车辆的车辆动态信息；第三获取模块，用于根据所述轮速信息，从所述一级道路类型包括的二级道路类型中获取目标二级道路类型；a second acquisition module, configured to acquire wheel speed information of the vehicle and vehicle dynamic information of the vehicle in the driving mode; and a third acquisition module, configured to acquire a target secondary road type from the secondary road types included in the primary road type according to the wheel speed information; 第四获取模块，用于根据所述车辆动态信息，从所述目标二级道路类型包括的三级道路类型中获取目标三级道路类型；A fourth acquisition module, configured to acquire a target third-level road type from the third-level road types included in the target second-level road type according to the vehicle dynamic information; 确定模块，用于根据所述目标三级道路类型，确定对各所述电控系统的补偿参数；A determination module, used for determining compensation parameters for each of the electronic control systems according to the target third-level road type; 调节模块，用于基于各所述电控系统补偿参数调节相应电控系统的所述控制参数；an adjustment module, configured to adjust the control parameters of the corresponding electronic control system based on the compensation parameters of each electronic control system; 其中，所述获取所述车辆的车辆动态信息，包括：Wherein, the obtaining of vehicle dynamic information of the vehicle includes: 在预设时间段内对所述车辆的加速度进行采样，获取多组加速度信息；其中，每组加速度信息包括横向加速度值和纵向加速度值；Sampling the acceleration of the vehicle within a preset time period to obtain multiple sets of acceleration information; wherein each set of acceleration information includes a lateral acceleration value and a longitudinal acceleration value; 所述根据所述车辆动态信息，从所述目标二级道路类型包括的三级道路类型中获取目标三级道路类型，包括：The step of acquiring the target third-level road type from the third-level road types included in the target second-level road type according to the vehicle dynamic information comprises: 对每组加速度值进行加权运算，获取单组车辆动态指数；Perform weighted calculation on each group of acceleration values to obtain a single group of vehicle dynamic index; 根据多个所述单组车辆动态指数，确定所述预设时间段内的平均车辆动态指数；Determining an average vehicle dynamic index within the preset time period according to the plurality of single-group vehicle dynamic indexes; 根据所述平均车辆动态指数，以及所述目标二级道路类型包括的三级道路类型所对应的预设条件，从所述目标二级道路类型包括的三级道路类型中获取目标三级道路类型；According to the average vehicle dynamic index and the preset conditions corresponding to the third-level road types included in the target secondary road types, a target third-level road type is obtained from the third-level road types included in the target secondary road types; 其中，所述根据所述目标三级道路类型，确定对各所述电控系统的补偿参数，包括：Wherein, determining the compensation parameters for each of the electronic control systems according to the target third-level road type includes: 根据所述目标三级道路类型，查找预设的三级道路类型参数表，确定对各所述电控系统的补偿参数；所述三级道路类型参数表包括：每个三级道路类型分别针对EMS发动机管理系统、TCU自动变速箱控制单元、四轮驱动系统、悬架系统、ESP车身稳定控制系统的补偿参数。According to the target third-level road type, a preset third-level road type parameter table is searched to determine the compensation parameters for each of the electronic control systems; the third-level road type parameter table includes: compensation parameters for each third-level road type respectively for the EMS engine management system, TCU automatic transmission control unit, four-wheel drive system, suspension system, and ESP body stability control system. 7.一种电子设备，其特征在于，包括处理器，存储器及存储在所述存储器上并可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如权利要求1-5任一项所述的车辆控制方法的步骤。7. An electronic device, characterized in that it comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the vehicle control method as described in any one of claims 1 to 5. 8.一种可读存储介质，其特征在于，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如权利要求1-5任一项所述的车辆控制方法的步骤。8. A readable storage medium, characterized in that the readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the vehicle control method according to any one of claims 1 to 5 are implemented.
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