Gradient recognition method, electronic equipment and computer readable storage medium

Abstract

The invention relates to the technical field of new energy automobiles, in particular to a slope recognition method, electronic equipment and a computer readable storage medium. Step S11, acquiring vehicle data based on vehicle starting; step S12, acquiring a vehicle state based on the parking slope data in the first range before starting, the acceleration sensor data and the vehicle speed data; step S13, acquiring first gradient data B based on the vehicle state as a first gradient state; step S14, based on the obtained parking slope data A and the first slope data B, obtaining the slope C of the road where the current vehicle is located; therefore, the problem that slope recognition is inaccurate when the vehicle is started is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicles, and in particular to a slope recognition method, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the development of science and technology, vehicles are being used more and more widely. However, during the operation of vehicles, due to the uncertainty of road conditions, vehicles often travel on unpaved roads, and these roads often lack accurate and detailed terrain data, resulting in low vehicle operation efficiency. Existing vehicles are usually equipped with slope recognition devices, and then the vehicle adjusts the working state of the vehicle according to the recognized slope information to ensure the safety and stability of vehicle operation.

[0003] Existing slope recognition devices usually determine the slope data of the road surface by the motion change of the vehicle. However, when the vehicle starts and the speed is low, the slope data obtained based on the motion change has too large an error, and the safety and stability of the vehicle operation cannot be guaranteed. Summary of the invention

[0004] In order to solve the problem of inaccurate slope recognition when a vehicle is started, the present invention provides a slope recognition method, an electronic device, and a computer-readable storage medium.

[0005] In a first aspect, the present invention provides a slope recognition method, the slope recognition method comprising:

[0006] Step S11, based on the vehicle starting, obtaining vehicle data; wherein the vehicle data includes parking slope data A before starting, acceleration sensor data, and vehicle speed data; the parking slope data before starting includes road slope data calculated after the vehicle stops;

[0007] Step S12, acquiring a vehicle state based on the parking slope data before starting in the first range, the acceleration sensor data, and the vehicle speed data; wherein the vehicle state includes a first slope state;

[0008] Step S13, based on the vehicle state being the first slope state, obtaining first slope data B; wherein the first slope state includes the acceleration sensor being in a normal state and the vehicle speed data being less than or equal to a first set value;

[0009] Step S14, based on the parking slope data A and the first slope data B, the slope C of the road where the vehicle is currently located is obtained; wherein C=A*K+B*(1-K), 0<K<1.

[0010] In some embodiments, the vehicle speed data of the vehicle in the first slope state is inversely proportional to K.

[0011] In some embodiments, the vehicle speed data in the first slope state includes a first interval and a second interval; K≥0.9 in the first interval; wherein the first interval includes the vehicle speed data being less than or equal to a second set value.

[0012] In some embodiments, K is less than 0.9 in the second interval; wherein the second interval includes the vehicle speed data being greater than a second set value and less than or equal to the first set value.

[0013] In some embodiments, the second interval includes a first segment and a second segment; in the first segment, 0.1≤K<0.9; wherein, the first segment includes the vehicle speed data being greater than a second set value and less than or equal to a third set value.

[0014] In some embodiments, K is less than 0.1 in the second segment; wherein, the second segment includes the vehicle speed data being greater than a third set value and less than or equal to a first set value.

[0015] In some embodiments, the pre-start parking slope data is the last slope data calculated after the vehicle stops for a set time before starting.

[0016] In some embodiments, the slope identification method further includes:

[0017] Step S131, based on the vehicle state including a second slope state, obtaining second slope data D; wherein the second slope state includes that the acceleration sensor is in a normal state and the vehicle speed data is greater than a first set value;

[0018] Step S132, based on the second slope data D, obtain the slope C of the road where the vehicle is currently located; wherein C=D.

[0019] In a second aspect, the present invention provides an electronic device, comprising: a memory for storing instructions; and a processor for calling the instructions stored in the memory to execute the slope recognition method as described in any one of the first aspects.

[0020] In a third aspect, the present invention provides a computer-readable storage medium storing instructions, which, when executed by a processor, executes the slope identification method as described in any one of the first aspects.

[0021] In order to solve the problem of inaccurate slope recognition when the vehicle is started, the present invention has the following advantages:

[0022] Before the vehicle is started, the parking slope data A of the vehicle is obtained. When the vehicle is started, due to the low vehicle speed, the acceleration sensor is not sensitive enough, the motion change collected is not accurate enough, and the first slope data B obtained through acceleration is not accurate enough. The slope C of the road where the current vehicle is located is determined by the vehicle weight coefficient of the parking slope data and the first slope data, thereby improving the accuracy of the vehicle slope data obtained when the vehicle is started. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flow chart of a slope identification method according to an embodiment is shown;

[0024] Figure 2 A schematic diagram of an electronic device is shown.

[0025] Reference numerals:

[0026] Electronic device 400 ; memory 401 ; processor 402 ; input / output (I / O) interface 403 . DETAILED DESCRIPTION

[0027] The present disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and thus implement the present disclosure, rather than implying any limitation on the scope of the present disclosure.

[0028] As used herein, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to". The term "based on" is to be interpreted as "based at least in part on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment". The term "another embodiment" is to be interpreted as "at least one other embodiment". The orientation or position relationship indicated by the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "vertical", "horizontal", "lateral", "longitudinal" and the like is based on the orientation or position relationship shown in the accompanying drawings. These terms are mainly for better describing the present application and its embodiments, and are not used to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation. In addition, in addition to being used to indicate an orientation or position relationship, some of the above terms may also be used to indicate other meanings, such as the term "upper" may also be used to indicate a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to the specific circumstances. In addition, the terms "install", "set", "provided with", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be an internal connection between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, "plurality" means two or more.

[0029] This embodiment discloses a slope recognition method, such as Figure 1 and Figure 2 As shown, it may include:

[0030] In this embodiment, during the operation of the vehicle, due to the uncertainty of the road conditions, the vehicle often travels on unpaved roads, and these roads often lack accurate and detailed terrain data, resulting in low vehicle operation efficiency. Existing new energy vehicles usually install slope recognition devices on the vehicle. However, when the vehicle starts and the speed is low, the acceleration sensor is not sensitive enough, the collected motion changes are not accurate enough, and the slope data obtained according to the motion changes has too large an error, and the safety and stability of the vehicle operation cannot be guaranteed. The present invention discloses a slope recognition method, which may include steps S11 to S14, and each step is described in detail as follows:

[0031] Step S11, based on the vehicle startup, obtain vehicle data. The vehicle data includes parking slope data A before the vehicle starts, acceleration sensor data and vehicle speed data. The parking slope data before startup includes the road slope data calculated after the vehicle stops. The output acceleration a of the vehicle can be obtained through the acceleration sensor data 输出 , and then obtain the actual acceleration a of the vehicle based on the real-time speed data of the vehicle 实际 , and then we can get the parking slope data of the vehicle A= , where g is the acceleration due to gravity.

[0032] Step S12, based on the parking slope data before the vehicle starts being in the first range (the first range may include 5° to 16.7°), the vehicle state is obtained by obtaining sensor data and vehicle speed data. The slope calculation method is determined by obtaining the vehicle state. The vehicle state includes a first slope state.

[0033] Step S13, based on the vehicle state being the first slope state, first slope data B is obtained, the first slope state may include the acceleration sensor being in a normal state, the vehicle speed data being less than or equal to a first set value (the first set value may include 3 km / h). At this time, since the vehicle speed is relatively low, the slope data error obtained according to the motion change is too large, so the accuracy of the slope data may be improved through the parking slope data.

[0034] Step S14, based on the acquired parking slope data A and the first slope data B, the slope C of the road where the current vehicle is located can be acquired. Wherein, C=A*K+B*(1-K), 0<K<1. K is the vehicle weight coefficient, and the vehicle weight coefficient K can be calculated by the acceleration data of the acceleration sensor. The slope C of the road where the current vehicle is located is determined by the vehicle weight coefficient of the parking slope data and the first slope data, which improves the accuracy of the vehicle slope data acquired when the vehicle is started.

[0035] In this embodiment, the vehicle speed data of the vehicle in the first slope state is inversely proportional to the vehicle weight coefficient K. The vehicle speed data can be determined by the specific change value within a period of time. When the vehicle speed data is small, the slope data error obtained according to the movement change is too large, and the accuracy of the slope data can be improved by increasing the weight of the parking slope data.

[0036] In this embodiment, the vehicle speed data in the first slope state may include a first interval and a second interval. In the first interval, K≥0.9, the first interval includes the vehicle speed data being less than or equal to the second set value, and the second set value may be 1km / h. When the vehicle speed data is less than or equal to the second set value, the acceleration sensor is not sensitive enough, and the collected motion change is not accurate enough. The weight of the parking slope data may be increased to improve the accuracy of the slope data.

[0037] In this embodiment, K<0.9 may be used in the second interval, and the second interval may include vehicle speed data greater than the second set value and less than or equal to the first set value. The first set value may be 3 km / h. When the vehicle speed data is greater than the second set value and less than or equal to the first set value, the sensitivity of the acceleration sensor increases, and the weight of the first slope data may be increased to improve the accuracy of the slope data.

[0038] In this embodiment, the second interval may include a first segment and a second segment. In the first segment, 0.1≤K<0.9 may be sufficient. The first segment may include vehicle speed data greater than a second set value and less than or equal to a third set value. The third set value may be 2km / h. When the vehicle speed data is greater than the second set value and less than or equal to the third set value, as the vehicle speed increases, the sensitivity of the acceleration sensor increases, and the weight of the first slope data may be increased to improve the accuracy of the slope data.

[0039] In this embodiment, K<0.1 can be used in the second segment. The second segment can include vehicle speed data greater than the third set value and less than the first set value. When the vehicle speed data is greater than the third set value and less than the first set value, as the vehicle speed further increases, the sensitivity of the acceleration sensor also further increases, and the weight of the first slope data can be increased again to improve the accuracy of the slope data.

[0040] In this embodiment, since it takes a certain amount of time to collect data, analyze and calculate the vehicle, the parking slope data before starting can be the final slope data calculated after the vehicle stops for a set time, to ensure the accuracy of the calculation result.

[0041] In this embodiment, the vehicle driving slope identification method may further include step S131 and step S132, each of which is described in detail as follows:

[0042] In step S131, when the vehicle state is in the second slope state, the second slope data D may be acquired. The second slope state may include that the acceleration sensor is in a normal state and the vehicle speed data is greater than a first set value.

[0043] Step S132: Based on the acquired second slope data D, the slope C of the road where the vehicle is currently located can be acquired, where C = D. When the vehicle speed data is greater than the first set value, the sensitivity of the acceleration sensor increases and the data is reliable, and the slope data can be calculated through the acceleration data and the vehicle speed data.

[0044] In other embodiments, the vehicle data in step S11 may also include a steering wheel output angle, and the slope recognition method may also include: step S111, when the parking slope data before starting is in the first range, the acceleration sensor data and the vehicle speed data are normal, and the steering wheel output angle is less than the set angle, the set angle may be a fixed value, such as 160°, 180°, 200°, or a variable value, step S12 may be continued to obtain the slope data to avoid the steering wheel output angle being too large to affect the accuracy of the slope data. step S112, when the steering wheel output angle is greater than the set angle, the acceleration component of the vehicle acceleration acquired by the acceleration sensor along the slope direction is not accurate enough, and at this time, the slope data calculated by the component of the gravity acceleration g along the slope direction is not accurate enough, so the acquisition of the vehicle state is stopped.

[0045] In other embodiments, the vehicle driving slope identification method may further include: step S153, when the vehicle state is the third slope state, the last collected second slope data E may be obtained. The third slope state includes that the acceleration sensor is in an abnormal state and / or the steering wheel output angle is greater than the set angle. Step S154, when the speed sensor is in an abnormal state and / or the steering wheel output angle is greater than the set angle, accurate slope data cannot be obtained through the acceleration sensor data, so the slope C of the road where the current vehicle is located may be obtained through the last collected second slope data E, where C=E. This ensures the accuracy and reliability of the slope data.

[0046] like Figure 2 As shown, an embodiment of the present disclosure provides an electronic device 400. The electronic device 400 includes a memory 401, a processor 402, and an input / output (I / O) interface 403. The memory 401 is used to store instructions. The processor 402 is used to call the instructions stored in the memory 401 to execute the slope recognition method of the above embodiment. The processor 402 is connected to the memory 401 and the I / O interface 403, respectively, for example, through a bus system and / or other forms of connection mechanisms (not shown). The memory 401 can be used to store programs and data, including the programs of the slope recognition method involved in the above embodiments. The processor 402 executes various functional applications and data processing of the electronic device 400 by running the programs stored in the memory 401.

[0047] In the embodiment of the present disclosure, the processor 402 can be implemented in at least one hardware form of a digital signal processor (DSP), a field programmable gate array (FPGA), and a programmable logic array (PLA). The processor 402 can be a central processing unit (CPU) or one or a combination of other forms of processing units with data processing capabilities and / or instruction execution capabilities.

[0048] The memory 401 in the embodiment of the present disclosure may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.

[0049] In the embodiment of the present disclosure, the input / output (I / O) interface 403 may be used to receive input instructions (such as digital or character information, and key signal input related to user settings and function control of the electronic device 400), and may also output various information (such as images or sounds) to the outside. In the embodiment of the present disclosure, the input / output (I / O) interface 403 may include one or more of a physical keyboard, a function key (such as a volume control key, a switch key, etc.), a mouse, a joystick, a trackball, a microphone, a speaker, and a touch panel.

[0050] It is to be understood that, although the operations are described in a specific order in the drawings in the embodiments of the present disclosure, it should not be understood as requiring the operations to be performed in the specific order shown or in a serial order, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

[0051] The methods and devices involved in the embodiments of the present disclosure can be implemented using standard programming techniques, using rule-based logic or other logic to implement various method steps. It should also be noted that the words "device" and "module" used herein and in the claims are intended to include implementations using one or more lines of software code and / or hardware implementations and / or devices for receiving input.

[0052] Any steps, operations or procedures described herein may be performed or implemented using one or more hardware or software modules, either alone or in combination with other devices. In one embodiment, the software module is implemented using a computer program product including a computer-readable medium containing computer program code, which can be executed by a computer processor to perform any or all of the described steps, operations or procedures.

[0053] The foregoing description of the implementation of the present disclosure has been given for the purpose of illustration and description. The foregoing description is not exhaustive nor is it intended to limit the present disclosure to the exact form disclosed, and various variations and modifications may exist in accordance with the above teachings or may be obtained from the practice of the present disclosure. These embodiments are selected and described in order to illustrate the principles of the present disclosure and its practical application, so that those skilled in the art can utilize the present disclosure in various embodiments and various modifications suitable for the specific purpose contemplated.

Claims

1. A slope recognition method, characterized in that: The slope recognition method comprises: Step S11, based on the vehicle starting, obtaining vehicle data; wherein the vehicle data includes parking slope data A before starting, acceleration sensor data, and vehicle speed data; the parking slope data before starting includes road slope data calculated after the vehicle stops; Step S12, acquiring a vehicle state based on the parking slope data before starting in the first range, the acceleration sensor data, and the vehicle speed data; wherein the vehicle state includes a first slope state; Step S13, based on the vehicle state being the first slope state, obtaining first slope data B; wherein the first slope state includes the acceleration sensor being in a normal state and the vehicle speed data being less than or equal to a first set value; Step S14, based on the parking slope data A and the first slope data B, the slope C of the road where the vehicle is currently located is obtained; wherein C=A*K+B*(1-K), 0<K<1.

2. A slope recognition method according to claim 1, characterized in that: The vehicle speed data of the vehicle in the first slope state is inversely proportional to K.

3. A slope recognition method according to claim 2, characterized in that: The vehicle speed data in the first slope state includes a first interval and a second interval; K≥0.9 in the first interval; wherein the first interval includes the vehicle speed data being less than or equal to a second set value.

4. A slope recognition method according to claim 3, characterized in that: In the second interval, K is less than 0.9; wherein, the second interval includes the vehicle speed data being greater than a second set value and less than or equal to the first set value.

5. A slope recognition method according to claim 4, characterized in that: The second interval includes a first segment and a second segment; in the first segment, 0.1≤K<0.9; wherein, the first segment includes the vehicle speed data being greater than a second set value and less than or equal to a third set value.

6. A slope recognition method according to claim 5, characterized in that: In the second segment, K is less than 0.1; wherein, the second segment includes the vehicle speed data being greater than the third set value and less than or equal to the first set value.

7. A slope recognition method according to claim 1, characterized in that: The pre-start parking slope data is the final slope data calculated after the vehicle stops for a set time before starting.

8. A slope recognition method according to claim 1, characterized in that: The slope recognition method further comprises: Step S131, based on the vehicle state including a second slope state, obtaining second slope data D; wherein the second slope state includes that the acceleration sensor is in a normal state and the vehicle speed data is greater than a first set value; Step S132, based on the second slope data D, obtain the slope C of the road where the vehicle is currently located; wherein C=D.

9. An electronic device, characterized in that: include: A memory for storing instructions; and a processor, configured to call the instructions stored in the memory to execute the slope recognition method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed by the processor, the slope recognition method according to any one of claims 1 to 8 is executed.

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