Vehicle control method, device and vehicle-mounted controller

Abstract

The present application provides a vehicle control method, device and on-board controller. The method includes: the on-board controller obtains the vehicle's driving information in real time. The on-board controller determines the score corresponding to each driving information based on the driving information. The on-board controller calculates the driving index based on the preset correction coefficient and the score corresponding to each driving information. The on-board controller makes a decision based on the driving index and determines the target driving mode at the current moment. If the target driving mode at the current moment is the same as the actual driving mode at the current moment, the on-board controller does not process it. Otherwise, if the target driving mode at the current moment is different from the actual driving mode at the current moment, the on-board controller controls the vehicle to automatically switch to the target driving mode. The method of the present application improves the control efficiency of the vehicle.

Description

Technical Field

[0001] The present application relates to the field of control, and in particular to a vehicle control method, device, and vehicle-mounted controller. Background Art

[0002] With the continuous development of science and technology and the continuous centralization of vehicle control systems, users' requirements for vehicle control are constantly developing towards speed and simplicity.

[0003] Currently, vehicles have three main driving modes: ECO, Normal, and Sport. In the prior art, users can manually switch between these driving modes. For example, users can switch between driving modes by clicking a button.

[0004] However, the existing technology relies on manpower to complete the switching of the driving mode, which has the problem of low control efficiency. Summary of the Invention

[0005] The present application provides a vehicle control method, device and vehicle-mounted controller to solve the problem of low control efficiency in the prior art which relies on manpower to switch the driving mode.

[0006] In a first aspect, the present application provides a vehicle control method, comprising:

[0007] Get vehicle driving information in real time;

[0008] Calculating the vehicle's current driving index in real time based on the driving information;

[0009] According to the driving index, a target driving mode of the vehicle is determined and automatically switched.

[0010] Optionally, adjusting the driving index of the vehicle in real time according to the driving information specifically includes:

[0011] The driving index of the vehicle at the current moment is determined based on the accelerator pedal opening score, accelerator pedal change rate, ambient temperature correction coefficient, brake pedal change rate score, yaw angular velocity score, remaining power correction coefficient, battery health correction coefficient and the driving index of the vehicle at the previous moment in the driving information at the current moment.

[0012] Optionally, determining and automatically switching the target driving mode of the vehicle according to the driving index specifically includes:

[0013] When the driving index is less than or equal to a first index, determining and automatically switching the target driving mode of the vehicle to the first mode;

[0014] When the driving index is greater than or equal to the second index and less than or equal to the third index, determining and automatically switching the target driving mode of the vehicle to the second mode;

[0015] When the driving index is greater than or equal to a fourth index, the target driving mode of the vehicle is determined and automatically switched to the third mode.

[0016] Optionally, when the vehicle is powered on, the method further includes:

[0017] A historical driving index stored in the vehicle is obtained, and the historical driving index is used as the driving index at the previous moment when the driving index is calculated for the first time after power-on.

[0018] Optionally, when the vehicle is powered off, the method further includes:

[0019] Determining a driving index mean value based on the historical driving index and the current driving index;

[0020] The driving index average is stored so that the driving index average covers the historical driving index.

[0021] Optionally, the method further includes:

[0022] Determining current traffic conditions from navigation information;

[0023] According to the road condition information, a target driving mode of the vehicle is determined and automatically switched.

[0024] In a second aspect, the present application provides a vehicle control device, comprising:

[0025] Acquisition module, used to obtain vehicle driving information in real time;

[0026] The processing module is used to calculate the driving index of the vehicle at the current moment in real time based on the driving information; and determine and automatically switch the target driving mode of the vehicle based on the driving index.

[0027] Optionally, the processing module is specifically configured to:

[0028] The driving index of the vehicle at the current moment is determined based on the accelerator pedal opening score, accelerator pedal change rate, ambient temperature correction coefficient, brake pedal change rate score, yaw angular velocity score, remaining power correction coefficient, battery health correction coefficient and the driving index of the vehicle at the previous moment in the driving information at the current moment.

[0029] Optionally, the processing module is specifically configured to:

[0030] When the driving index is less than or equal to a first index, determining and automatically switching the target driving mode of the vehicle to the first mode;

[0031] When the driving index is greater than or equal to the second index and less than or equal to the third index, determining and automatically switching the target driving mode of the vehicle to the second mode;

[0032] When the driving index is greater than or equal to a fourth index, the target driving mode of the vehicle is determined and automatically switched to the third mode.

[0033] Optionally, when the vehicle is powered on, the processing module is further configured to:

[0034] A historical driving index stored in the vehicle is obtained, and the historical driving index is used as the driving index at the previous moment when the driving index is calculated for the first time after power-on.

[0035] Optionally, when the vehicle is powered off, the processing module is further configured to:

[0036] Determining a driving index mean value based on the historical driving index and the current driving index;

[0037] The driving index average is stored so that the driving index average covers the historical driving index.

[0038] Optionally, the processing module is further configured to:

[0039] Determining current traffic conditions from navigation information;

[0040] According to the road condition information, a target driving mode of the vehicle is determined and automatically switched.

[0041] In a third aspect, the present application provides a vehicle-mounted controller, comprising: a memory and a processor;

[0042] The memory is used to store computer programs; the processor is used to execute the vehicle control method in the first aspect and any possible design of the first aspect according to the computer programs stored in the memory.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When at least one processor of an on-board controller executes the computer program, the on-board controller executes the vehicle control method in the first aspect and any possible design of the first aspect.

[0044] In a fifth aspect, the present application provides a computer program product, which includes a computer program. When at least one processor of a vehicle-mounted controller executes the computer program, the vehicle-mounted controller executes the vehicle control method in the first aspect and any possible design of the first aspect.

[0045] The vehicle control method, device and on-board controller provided in the present application obtain the vehicle's driving information in real time; determine the score corresponding to each driving information based on the driving information; calculate the driving index based on a preset correction coefficient and the score corresponding to each driving information; make a decision based on the driving index to determine the target driving mode at the current moment; if the target driving mode at the current moment is the same as the actual driving mode at the current moment, no processing is performed; otherwise, if the target driving mode at the current moment is different from the actual driving mode at the current moment, the vehicle is controlled to automatically switch to the target driving mode, thereby improving the control efficiency of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 A schematic diagram of a scenario of a vehicle control method provided in one embodiment of the present application;

[0048] Figure 2 A flow chart of a vehicle control method provided in one embodiment of the present application;

[0049] Figure 3 A pedal opening-score curve provided in one embodiment of the present application;

[0050] Figure 4 An SOC-coefficient curve provided in one embodiment of the present application;

[0051] Figure 5 An SOH coefficient curve provided in one embodiment of the present application;

[0052] Figure 6 A schematic diagram of a driving mode determination provided in one embodiment of the present application;

[0053] Figure 7 A flow chart of a vehicle control method provided in one embodiment of the present application;

[0054] Figure 8 A flow chart of a vehicle control method provided in one embodiment of the present application;

[0055] Figure 9 A schematic structural diagram of a vehicle control device provided in one embodiment of the present application;

[0056] Figure 10 A schematic diagram of the hardware structure of a vehicle-mounted controller provided in one embodiment of the present application. DETAILED DESCRIPTION

[0057] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0058] In the specification and claims of this application, as well as in the accompanying drawings, the terms "first," "second," "third," "fourth," and the like are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that such terms are interchangeable where appropriate. For example, first information could be referred to as second information, and similarly, second information could be referred to as first information without departing from the scope of this disclosure.

[0059] The word "if" as used herein may be interpreted as "when" or "when" or "in response to determining," depending on the context.

[0060] Furthermore, as used herein, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise.

[0061] It should be further understood that the terms “comprises” and “includes” indicate the existence of features, steps, operations, elements, components, items, types, and / or groups, but do not preclude the existence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, types, and / or groups.

[0062] The terms "or" and "and / or" as used herein are to be interpreted as inclusive, or mean any one or any combination. Thus, "A, B, or C" or "A, B, and / or C" means "any one of the following: A; B; C; A and B; A and C; B and C; A, B, and C." An exception to this definition occurs only when a combination of elements, functions, steps, or operations are inherently mutually exclusive in some manner.

[0063] With the continuous advancement of technology, the intelligence level of new energy vehicles continues to improve. Traditionally, driving mode switching is typically achieved manually. For example, users can switch driving modes by clicking a button. Currently, vehicle driving modes mainly include ECO, Normal, and Sport. Existing technologies rely on manual control to switch driving modes, resulting in low control efficiency. Furthermore, with increasing demands for traffic, the environment, and vehicle performance from drivers, fixed, unchanging driving modes are no longer able to meet drivers' needs. Dynamic and predictive driving mode switching based on factors such as individual drivers, driving habits / behaviors, and road conditions can free the driver's hands in appropriate situations and improve vehicle control efficiency. Existing intelligent driving mode switching algorithms are generally fuzzy algorithms. Existing technologies are generally unable to accurately calculate the driver's driving intensity across multiple dimensions and can only provide a rough control logic based on logic diagrams. Existing technologies lack powerful algorithms to predict driver driving behavior.

[0064] In the vehicle control method proposed in this application, an onboard controller can predict driver behavior by acquiring the driver's habitual movements, thereby enabling driving mode switching. During the specific judgment process, the onboard controller can determine a correction coefficient based on the driver's accelerator and brake pedal pressing and the vehicle's yaw angle, thereby correcting the driver's behavior score. The onboard controller can then determine and switch driving modes based on this score. During the aforementioned control process, the onboard controller can utilize modules such as a probability algorithm module, a driving behavior algorithm module, a driving mode arbitration module, and a mode switching module to achieve more efficient and accurate quantitative response to driving behavior. Furthermore, in this application, navigation map information is also incorporated into the onboard control. After acquiring navigation map information, the onboard controller can directly determine the corresponding driving mode based on road condition information. The use of this navigation map information can better integrate the vehicle into the surrounding environment and automatically switch driving modes based on road conditions such as whether the surrounding road is congested, mountainous, or desert.

[0065] The following specific embodiments are used to describe the technical solution of the present application in detail. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0066] Figure 1 FIG. 1 shows a schematic diagram of a vehicle control method provided by an embodiment of the present application. Figure 1 As shown, when the user clicks the "Driving Style" button in the vehicle, the vehicle can enter the driving mode and automatically switch scenes.

[0067] When the vehicle enters driving mode and automatically switches scenes, the vehicle's AI intelligent recognition module can obtain driver information. For example, the AI ​​intelligent recognition module may include a camera. The camera can capture a facial image of the driver. The AI ​​intelligent recognition module can determine the driver's driving information based on the facial image. For another example, the AI ​​intelligent recognition module may include Bluetooth, NFC, or IC modules. These modules can obtain the driver's driving information from the driver's work card or work phone. Based on this driver information, the onboard controller can read the driver's corresponding historical cycle score from the vehicle's storage device. This historical cycle score can be the average cycle score calculated and stored by the onboard controller the last time the vehicle was powered off. The onboard controller can also switch to the driver's driving style based on this driver information. Furthermore, the onboard controller can also switch other vehicle settings based on this driver information. These other settings may include seat position, air conditioning temperature, air conditioning air volume, radio frequency, etc.

[0068] When the vehicle enters the automatic driving mode switching scenario, if the driver information does not have a corresponding historical cycle score stored, the vehicle controller may default the driver's initial score to 50 points. The driving mode corresponding to the 50 points is Normal.

[0069] The vehicle may include multiple components, including an onboard controller, a pedal analysis module, and a yaw angle calculation module. The pedal analysis module is used to obtain information such as the accelerator pedal position, accelerator pedal change rate, and brake pedal change rate. The pedal analysis module can transmit this information to the onboard controller. The yaw angle calculation module is used to obtain the yaw angular velocity and transmit it to the onboard controller.

[0070] The onboard controller can adjust the score based on the accelerator pedal opening. When the accelerator pedal opening is greater than 30%, the onboard controller can refer to the change curve and determine whether to increase the score based on the duration of the opening. When the accelerator pedal opening is between 20% and 30%, the onboard controller does not adjust the score. When the accelerator pedal opening is less than 20%, the onboard controller deducts the score. For example, the onboard controller can perform a deduction of 4 points each time the accelerator pedal opening is detected.

[0071] The on-board controller can complete the second score adjustment based on the accelerator pedal change rate. When the accelerator pedal change rate is greater than 0 and greater than the indicator TBD2, the on-board controller adds points to the score. For example, the on-board controller can perform a +4 point operation each time it is detected. When the accelerator pedal change rate is greater than 0 and is between the indicator TBD1 and the indicator TBD2, the on-board controller does not adjust the score. When the accelerator pedal change rate is equal to 0 and less than the indicator TBD1, the on-board controller subtracts points from the score. For example, the on-board controller can perform a -4 point operation each time it is detected.

[0072] The on-board controller can complete the third score adjustment based on the brake pedal change rate. When the brake pedal change rate is greater than 0 and greater than the indicator TBD2, the on-board controller will add points to the score. For example, the on-board controller can perform a +2 point operation each time it is detected. When the brake pedal change rate is greater than 0 and between the indicator TBD1 and the indicator TBD2, the on-board controller does not adjust the score. When the brake pedal change rate is equal to 0 and less than the indicator TBD1, the on-board controller will subtract points from the score. For example, the on-board controller can perform a -2 point operation each time it is detected.

[0073] The vehicle controller can adjust the score based on the yaw rate. When the yaw rate is greater than or equal to the indicator TBD, the vehicle controller adds points to the score. For example, the vehicle controller might add 2 points each time the yaw rate is detected. When the yaw rate is less than the indicator TBD, the vehicle controller does not adjust the score. Indicator TBD, indicator TBD1, and indicator TBD2 are parameter values ​​set by the administrator based on experience.

[0074] The onboard controller can also obtain other parameters from sensors in the vehicle. Based on these parameters, the onboard controller can derive an environmental correction factor. For example, this parameter may include ambient temperature. The onboard controller can also obtain battery information such as the vehicle's State of Charge (SOC) and State of Health (SOH) from the vehicle's battery controller. Based on this battery information, the onboard controller can derive a battery correction factor.

[0075] The on-board controller can input information such as the accelerator pedal opening, accelerator pedal change rate, brake pedal change rate, as well as the environmental correction factor and battery correction factor, into the driver scoring module. In this module, the on-board controller can calculate a score based on the above data. The score is the driver's driving index. When the score is the last score of the vehicle before power is turned off, the on-board controller can also store the score in the vehicle's storage device. The driving style arbitration module in the on-board controller can use the score calculated in the driver scoring module. The driving style arbitration module can determine whether the vehicle's driving mode needs to be switched and which driving mode it needs to switch to based on the score. After the driving style arbitration module determines the arbitration result, the driving style arbitration module can send the arbitration result to the driving mode switching module. The driving mode switching module can complete the switching of the driving mode based on the arbitration result.

[0076] When the vehicle enters the driving mode and automatically switches scenes, the on-board controller can turn on the on-board navigation. The on-board controller can read the planned route and the road condition information of the planned route from the on-board navigation. The road condition information may include the congestion of the road. If the road is congested, the on-board controller can collect the current speed of the vehicle through the vehicle speed collection module. The on-board controller can send the current speed to the driving style arbitration module. The driving style arbitration module can determine the arbitration result based on the current speed. Alternatively, the road condition information may include the driving environment. For example, desert, snow, mountain roads, mudflats, etc. The on-board controller can send the driving environment to the driving style arbitration module. The driving style arbitration module can determine the arbitration result based on the driving environment.

[0077] In this application, the vehicle control method of the following embodiments is executed with the vehicle controller as the execution subject. Specifically, the execution subject can be a hardware device of the vehicle controller, or a software application in the vehicle controller that implements the following embodiments, or a computer-readable storage medium that has the software application that implements the following embodiments installed, or the code that implements the software application of the following embodiments.

[0078] Figure 2 FIG1 shows a flow chart of a vehicle control method provided by an embodiment of the present application. Figure 1 Based on the embodiment shown, Figure 2 As shown, with the vehicle controller as the execution body, the method of this embodiment may include the following steps:

[0079] S101. Acquire vehicle driving information in real time.

[0080] In this embodiment, the vehicle controller can trigger an enable signal for the vehicle controller to obtain driving information when the driver clicks the "driving behavior" button. Thereafter, the vehicle controller can obtain the vehicle's driving information in real time.

[0081] In one example, the driving information may include accelerator pedal opening, accelerator pedal change rate, brake pedal change rate, yaw angular velocity, etc. Specifically, Figure 1 As shown, this driving information can be calculated separately by the pedal analysis module and the yaw angle calculation module in the vehicle controller. The accelerator pedal opening is the degree of change in the accelerator pedal after the driver presses the accelerator pedal. The value of the accelerator pedal opening can range from 0 to 100%. The accelerator pedal change rate indicates the degree of change in the accelerator pedal position per unit time. For example, if the accelerator pedal opening changes from 0 to 25% in 1 second, the accelerator pedal change rate is 25% / s. For another example, if the accelerator pedal opening changes from 0 to 30% in 2 seconds, the accelerator pedal change rate is 15% / s. The brake pedal change rate indicates the degree of change in the brake pedal position per unit time. For example, if the brake pedal opening changes from 0 to 25% in 1 second, the brake pedal change rate is 25% / s. For another example, if the brake pedal opening changes from 0 to 30% in 2 seconds, the brake pedal change rate is 15% / s. The yaw angular velocity indicates the vehicle's deflection angle per unit time. For example, if the vehicle's direction of travel deflects 10 degrees in 1 second, the yaw rate is 10 degrees per second. For another example, if the vehicle's direction of travel deflects 30 degrees in 2 seconds, the yaw rate is 15 degrees per second.

[0082] In one example, the driving information may also include information such as ambient temperature, SOC, and SOH. The ambient temperature may be obtained via a network. Alternatively, the ambient temperature may be obtained via a temperature sensor external to the vehicle. The SOC and SOH may be obtained via a battery controller within the vehicle.

[0083] S102: Calculate the vehicle's current driving index in real time based on the driving information.

[0084] In this embodiment, the vehicle controller can obtain the current driving information and determine the score corresponding to each driving information based on the driving information. The vehicle controller can calculate the driving index based on the preset correction coefficient and the score corresponding to each driving information.

[0085] In one example, the vehicle controller determines the vehicle's current driving index based on the accelerator pedal opening, accelerator pedal change rate, ambient temperature correction factor, brake pedal change rate, yaw rate, remaining battery power correction factor, battery health correction factor, and the vehicle's previous driving index. Specific steps may include:

[0086] When the vehicle is powered on or the "Driving Behavior" button is clicked, the onboard controller can retrieve the last stored driving index from the vehicle's storage device. When the onboard controller first calculates the driving index after the vehicle is powered on or the "Driving Behavior" button is clicked, the last stored driving index is used as the driving index at the previous moment. In subsequent calculations, the onboard controller will record the current driving index and use it as the driving index for the next moment in the calculation.

[0087] Step 1. During the calculation of the driving index, the vehicle controller may determine the acceleration pedal opening score, the acceleration pedal change rate score, the brake pedal change rate score, and the yaw angular velocity score based on the acceleration pedal opening, the acceleration pedal change rate, the brake pedal change rate, and the yaw angular velocity.

[0088] The accelerator pedal opening score calculation rules may include:

[0089] When the accelerator pedal opening is greater than 30%, the accelerator pedal opening score can be as follows: Figure 3 As shown in the reference curve. When the duration is in [0,1), the accelerator pedal opening score is 2. When the duration is in [1,2), the accelerator pedal opening score is 2. When the duration is greater than or equal to 2, the calculation formula for the accelerator pedal opening score is:

[0090] Accelerator pedal opening score = duration + 2

[0091] When the accelerator pedal opening is greater than 20% and less than or equal to 30%, the accelerator pedal opening score is 0. When the accelerator pedal opening is less than or equal to 20%, the accelerator pedal opening score is -4. This accelerator pedal opening score is mainly used to evaluate different scenarios of long-term accelerator acceleration, single accelerator pedaling, and frequent accelerator pedaling.

[0092] The accelerator pedal change rate score calculation rules may include:

[0093] When the accelerator pedal change rate is greater than 25% / s, the accelerator pedal change rate score is 4 points / time. When the accelerator pedal change rate is greater than 15% / s and less than or equal to 25% / s, the accelerator pedal change rate score is 0 points / time. When the accelerator pedal change rate is equal to 0, the accelerator pedal change rate can be as follows Figure 3As shown in the reference curve. The onboard controller can count the duration of the accelerator pedal change rate being 0 when the accelerator pedal change rate is 0. When the accelerator pedal change rate is 0, the accelerator pedal opening remains unchanged. Therefore, the duration of the accelerator pedal change rate being 0 is the accelerator pedal opening duration. The onboard controller can calculate the duration of the accelerator pedal change rate being 0 according to the accelerator pedal change rate being 0 and the following examples: Figure 3 The calculation rule for the accelerator pedal change rate focuses on distinguishing between the scenarios of hard accelerator pedaling and rapid acceleration.

[0094] The calculation rules for the brake pedal change rate score may include:

[0095] When the brake pedal rate of change is greater than 20% / s, the brake pedal rate score is 2 points per time. When the brake pedal rate of change is greater than 10% / s but less than or equal to 20% / s, the brake pedal rate score is 0 points per time. When the brake pedal rate of change is greater than 0 but less than or equal to 10% / s, the brake pedal rate score is -2 points per time. This brake pedal rate score calculation rule allows for differentiation between hard braking and sudden deceleration scenarios.

[0096] The yaw rate score calculation rules may include:

[0097] When the yaw rate is greater than 10 degrees per second, the yaw rate score is 2 points per time. When the yaw rate is 10 degrees per second or less, the yaw rate score is 0 points per time. This yaw rate score calculation rule standardizes and simulates scenarios where the driver makes sharp turns or violent steering movements on the road, causing the vehicle's posture to deviate.

[0098] Step 2: Determine an ambient temperature correction factor, a remaining power correction factor, and a battery health correction factor based on the ambient temperature, the remaining power, and the battery health.

[0099] The vehicle controller can sense the ambient temperature through a sensor. The ambient temperature correction coefficient is set to x1 = 1 when the temperature is normal. When the ambient temperature is extremely low (ambient temperature ≤ -7°C), the ambient temperature will affect the use of the battery. Therefore, in extremely low temperature environments, the ambient temperature coefficient can be set to x1 = 0.8.

[0100] The on-board controller can obtain the battery SOC and SOH signals through the battery controller.

[0101] Among them, the relationship between the SOC value and the remaining power correction coefficient x2 can be as follows: Figure 4As shown. When the remaining battery power is greater than or equal to 50, the remaining power correction coefficient x2 is 1. When the remaining battery power is less than 50, the efficiency of the remaining battery power will decrease as the remaining battery power decreases. Therefore, when the remaining battery power is less than 50, the remaining power correction coefficient x2 will decrease as the remaining battery power decreases. The formula is:

[0102] Remaining power correction coefficient = 0.004 × SOC value + 0.8

[0103] Among them, the relationship between the SOH value and the battery health correction coefficient x3 can be as follows: Figure 5 As shown. When the SOH value is greater than or equal to 70, the battery health correction coefficient x3 of the battery is 1. When the SOH value is less than 70, the battery efficiency will decrease as the battery health decreases. Therefore, when the SOH value is less than 70, the battery health correction coefficient x3 of the battery will decrease as the battery SOH value decreases. The formula is:

[0104]

[0105] Step 3: Determine the vehicle's current driving index based on the accelerator pedal opening, accelerator pedal change rate, ambient temperature correction factor, brake pedal change rate, yaw rate, remaining power correction factor, battery health correction factor, and the vehicle's previous driving index. The formula can be:

[0106]

[0107] Where D is the driving index. a1 is the base score, which is the default score assigned by the system after the driver turns on the "Driving Behavior" mode. This score is 50 points. The onboard controller can perform calculations based on this base score. a2 is the average score of the driver's historical cycles, obtained from the storage device. When a2 is not 0, the onboard controller uses the second formula for calculation. Otherwise, it uses the first formula for calculation. b is the accelerator pedal opening score. c is the accelerator pedal change rate score. x1 is the ambient temperature correction factor. d is the brake pedal change rate score. e is the yaw rate score. x2 is the SOC impact coefficient on the total score. x3 is the SOH impact coefficient on the total score. The above formula implements the calculation of the driving index. The driving index is calculated based on the same basis. Initially, each user has an initial score of 50. This initial score of 50 corresponds to the Normal driving mode. Subsequently, as the driver drives, the driving index will continuously learn and optimize based on the driver, driving environment, and driving scenario. Moreover, the driving index will be continuously calculated for the same driver, so that the driving index will fully take into account the changes in the user's index under different drivers, different environments, and different scenarios in subsequent use, so as to avoid interference from other factors and be closer to the driver's actual driving level.

[0108] S103: Determine and automatically switch the target driving mode of the vehicle based on the driving index.

[0109] In this embodiment, the onboard controller can make a decision based on the driving indicators to determine the current target driving mode. If the current target driving mode is the same as the current actual driving mode, the onboard controller does not process the decision. Otherwise, if the current target driving mode is different from the current actual driving mode, the onboard controller controls the vehicle to automatically switch to the target driving mode.

[0110] In one example, the decision conditions for the driving mode can be specifically as follows: Figure 6 Shown, including:

[0111] When the driving index is less than or equal to the first index, the target driving mode of the vehicle is determined and automatically switched to the first mode. The first index can be determined based on the first limit plus the hysteresis interval. For example, Figure 6 As shown, the first limit value may be 40. The hysteresis interval may be ±2. Based on the first limit value and the hysteresis interval, the first index can be calculated to be 38. That is, when the driving index is less than or equal to 38, the target driving mode of the vehicle is the first mode. The first mode may be ECO mode. If the actual driving mode at the current moment is Normal mode, the vehicle will switch from Normal mode to ECO mode.

[0112] When the driving index is greater than or equal to the second index and less than or equal to the third index, the target driving mode of the vehicle is determined and automatically switched to the second mode. The second index can be determined based on the first limit plus the hysteresis interval. For example, Figure 6 As shown, the first limit value can be 40. The hysteresis interval can be ±2. Based on the first limit value and the hysteresis interval, the second indicator can be calculated to be 42. The third indicator can be determined based on the second limit value plus the hysteresis interval. For example, Figure 6 As shown, the second limit value may be 60. The hysteresis interval may be ±2. Based on the second limit value and the hysteresis interval, the third index can be calculated to be 58. That is, when the driving index is greater than or equal to 42 and less than or equal to 58, the target driving mode of the vehicle is the second mode. The second mode may be Normal mode. If the actual driving mode at the current moment is ECO mode or Sport mode, the vehicle will switch from ECO mode or Sport mode to Normal mode.

[0113] When the driving index is greater than or equal to the fourth index, the target driving mode of the vehicle is determined and automatically switched to the third mode. The fourth index can be determined based on the second limit plus the hysteresis interval. For example, Figure 6 As shown, the second limit value may be 60. The hysteresis interval may be ±2. Based on the second limit value and the hysteresis interval, the fourth index can be calculated to be 62. That is, when the driving index is greater than or equal to 62, the target driving mode of the vehicle is the third mode. The third mode may be Sport mode. If the actual driving mode at the current moment is Normal mode, the vehicle will switch from Normal mode to Sport mode.

[0114] Among the three criteria above, the 40±2 interval between the first and second indicators, and the 60±2 interval between the third and fourth indicators, constitute the hysteresis interval. These hysteresis intervals ensure more stable and durable driving mode switching, preventing frequent switching of the vehicle's driving module when the driving indicator fluctuates between 40 and 60.

[0115] The vehicle control method provided herein enables an onboard controller to obtain real-time vehicle driving information. Based on this driving information, the onboard controller can determine a score corresponding to each piece of driving information. Furthermore, the onboard controller can calculate a driving index based on a preset correction coefficient and the score corresponding to each piece of driving information.

[0116] The onboard controller can make decisions based on driving indicators and determine the target driving mode at the current moment. If the target driving mode at the current moment is the same as the actual driving mode at the current moment, the onboard controller does not process the decision. Otherwise, if the target driving mode at the current moment is different from the actual driving mode at the current moment, the onboard controller controls the vehicle to automatically switch to the target driving mode. In this application, the onboard controller calculates the driving indicators and makes decisions on the target driving mode, thereby achieving automatic switching of the vehicle's driving mode, improving vehicle control efficiency, reducing the driver's workload during driving, and improving the user experience.

[0117] Figure 7 FIG1 shows a flow chart of a vehicle control method provided by an embodiment of the present application. Figures 1 to 6 Based on the embodiment shown, Figure 7 As shown, with the vehicle controller as the execution body, the method of this embodiment may include the following steps:

[0118] S201: Acquire a historical driving index stored in the vehicle. When the historical driving index is calculated for the first time after power-on, it is used as the driving index at the previous moment.

[0119] In this embodiment, the vehicle controller can retrieve historical driving indicators stored in the vehicle from the vehicle's storage device. These historical driving indicators are those stored before the vehicle was last powered off. The vehicle controller can automatically retrieve these historical driving indicators after the vehicle is powered on. Alternatively, the vehicle controller can automatically retrieve these historical driving indicators when the driver clicks a "Driving Behavior" button.

[0120] The steps for the vehicle controller to obtain the historical driving index may specifically include:

[0121] Step 1: The vehicle controller uses a camera installed in the vehicle to capture the driver's facial features and identify the driver's information. The camera in the vehicle can be installed in the rearview mirror. The vehicle controller can also obtain the driver's information through devices such as an IC card reader, Bluetooth module, and NFC module.

[0122] Step 2: The onboard controller can read the driver's historical driving indicators from the storage device based on the driver information. Specifically, the onboard controller can compare the information with the database and issue a command to activate the driver's historical driving indicators, thereby calling / reading the driver's historical driving indicators in the onboard controller.

[0123] S202: Acquire vehicle driving information in real time.

[0124] S203: Calculate the vehicle's current driving index in real time based on the driving information.

[0125] S204: Determine and automatically switch the target driving mode of the vehicle based on the driving index.

[0126] Among them, steps S202 to S204 are Figure 2 The implementation of steps S101 to S103 in the embodiment is similar and will not be repeated here in this embodiment.

[0127] S205: Determine a driving index average based on the historical driving index and the current driving index.

[0128] In this embodiment, due to the limited storage space of the vehicle's storage device, the onboard controller may calculate an average driving index based on the current driving index and historical driving indexes, store the average driving index in the storage device, and wait for the next read. The average driving index may be the sum of the historical driving index and the current driving index divided by two.

[0129] In one example, to more accurately obtain the historical driving index, the storage device may record all of the driver's historical driving indexes. Each time a new driving index is stored, the onboard controller may calculate an average driving index based on the stored historical driving indexes and the current driving index.

[0130] In one example, to more accurately obtain the historical driving index, the storage device may also record the number of times the historical driving index was stored. The onboard controller may determine the sum of all historical indicators for the driver based on the number of times the historical driving index was stored and the product of the historical driving index. The onboard controller may calculate the current driving index average based on the sum of all historical indicators, the current driving index, and the number of times the historical driving index was stored.

[0131] S206: Store the driving index average value so that the driving index average value covers the historical driving index value.

[0132] In this embodiment, the vehicle controller may store the average driving index in a storage device of the vehicle, and the average driving index will overwrite the historical driving index in the storage device.

[0133] In one example, the vehicle-mounted controller may also upload the driving index mean value and / or the current driving index to a server.

[0134] In one example, after determining the driver information, the onboard controller may store the driving index average in a location corresponding to the driver information.

[0135] The vehicle control method provided by the present application is that the on-board controller can obtain the historical driving indicators stored in the vehicle from the vehicle's storage device. The on-board controller can obtain the vehicle's driving information in real time. The on-board controller can calculate the vehicle's driving indicators at the current moment in real time based on the driving information. The on-board controller can determine and automatically switch the vehicle's target driving mode based on the driving indicators. The on-board controller can calculate the average driving indicator based on the current driving indicator and the historical driving indicator, store the average driving indicator in the storage device, and wait for the next reading. In the present application, the storage of the average driving indicator and the reading of historical driving indicators are realized through the interaction between the on-board controller and the storage device, thereby improving the learning effect and learning persistence of a driver's behavioral habits, and improving the effectiveness and personalization of the driving indicator.

[0136] Figure 8 FIG1 shows a flow chart of a vehicle control method provided by an embodiment of the present application. Figures 1 to 7 Based on the embodiment shown, Figure 8 As shown, with the vehicle controller as the execution body, the method of this embodiment may include the following steps:

[0137] S301: Determine current traffic information from navigation information.

[0138] In this embodiment, the vehicle controller may also obtain navigation information. This navigation information may be navigation information obtained by the vehicle controller through the vehicle computer when the navigation system in the vehicle computer is in use. This navigation information may include the vehicle's departure point, destination, route, road condition information corresponding to the route, and road condition information at the vehicle's current location.

[0139] In one example, the road condition information may include the predicted vehicle speed for each road section on the route, extracted by the onboard controller through parsing navigation information. When the predicted vehicle speed is less than or equal to a first speed index, the onboard controller may determine that the congestion level in the road condition information is congested. The first speed index may be 30 km / h. The onboard controller may further determine whether the congestion level of each road section is lightly congested or severely congested based on a second speed index. When the predicted vehicle speed is greater than the first speed index, the onboard controller may determine that the congestion level in the road condition information is unobstructed.

[0140] In one example, the road condition information may include the driving environment of the route identified by the vehicle controller through parsing navigation information. The driving environment may include deserts, snowy areas, mountain roads, mudflats, etc.

[0141] S302: Determine and automatically switch the target driving mode of the vehicle based on road condition information.

[0142] In this embodiment, the vehicle controller makes a decision based on the road condition information to determine the target driving mode. The vehicle controller can also automatically switch the driving mode based on the target driving mode.

[0143] In one example, when the predicted vehicle speed is less than the first speed index, the road section is in a congested state. In order to improve the acceleration and overtaking performance of the vehicle on the congested road section, the driving mode of the vehicle can be switched to ECO mode.

[0144] In one example, once the driving environment is determined, the vehicle controller can determine the driving mode based on the driving environment. For example, if a driving environment such as desert, snow, or mudflat is identified, the target driving mode can be four-wheel drive mode. For another example, if a driving environment such as a mountain road is identified, the target driving mode can be Sport mode.

[0145] In the vehicle control method provided in this application, the onboard controller can also obtain navigation information. The onboard controller makes decisions based on road condition information and determines the target driving mode. The onboard controller can also automatically switch driving modes based on the target driving mode. In this application, road condition information is determined through navigation information, thereby enabling the vehicle's target driving mode to be determined. This improves the vehicle's adaptability in different environments, reduces the driver's operations in different environments, and improves the user experience.

[0146] Based on the above embodiment, the vehicle controller can give priority to using the following when detecting navigation information: Figure 8 The method shown in FIG. 1 completes the decision of the target driving mode. If and only if the onboard controller cannot obtain navigation information, the onboard controller can make the decision according to the following example: Figure 2 The method shown completes the decision of the target driving mode.

[0147] Alternatively, the vehicle controller may prioritize the use of navigation information when detecting navigation information. Figure 8 The method shown in FIG. 1 is used to determine the target driving mode. Figure 8 After switching to the target driving mode according to the method shown in FIG. Figure 2 The method shown in FIG. 1 determines whether the target driving mode needs to be switched. If the vehicle controller Figure 2 The method shown in FIG. 1 determines that the target driving mode needs to be switched, and then switches the target driving mode.

[0148] Alternatively, the vehicle controller may ask the driver to use the following when the driver clicks the "Driving Behavior" button: Figure 2 The method shown is still to use Figure 8 The vehicle controller can determine the decision-making method of the target driving mode based on the user's selection.

[0149] Figure 9 A schematic diagram of the structure of a vehicle control device provided by an embodiment of the present application is shown in FIG. Figure 9 As shown, the vehicle control device 10 of this embodiment is used to implement the operations corresponding to the vehicle controller in any of the above method embodiments. The vehicle control device 10 of this embodiment includes:

[0150] The acquisition module 11 is used to acquire the vehicle's driving information in real time.

[0151] The processing module 12 is used to calculate the vehicle's current driving index in real time based on the driving information, and to determine and automatically switch the vehicle's target driving mode based on the driving index.

[0152] In one example, the processing module 12 is specifically configured to:

[0153] The vehicle's driving index at the current moment is determined based on the accelerator pedal opening score, accelerator pedal change rate, ambient temperature correction coefficient, brake pedal change rate score, yaw angular velocity score, remaining power correction coefficient, battery health correction coefficient and the vehicle's driving index at the previous moment in the driving information at the current moment.

[0154] In one example, the processing module 12 is specifically configured to:

[0155] When the driving index is less than or equal to the first index, the target driving mode of the vehicle is determined and automatically switched to the first mode.

[0156] When the driving index is greater than or equal to the second index and less than or equal to the third index, the target driving mode of the vehicle is determined and automatically switched to the second mode.

[0157] When the driving index is greater than or equal to the fourth index, the target driving mode of the vehicle is determined and automatically switched to the third mode.

[0158] In one example, when the vehicle is powered on, the processing module 12 is further configured to:

[0159] The historical driving index stored in the vehicle is obtained. When the historical driving index is calculated for the first time after power-on, it is used as the driving index at the previous moment.

[0160] In one example, when the vehicle is powered off, the processing module 12 is further configured to:

[0161] The average driving index is determined based on the historical driving index and the current driving index.

[0162] The driving index average is stored so that the driving index average covers the historical driving index.

[0163] In one example, the processing module 12 is further configured to:

[0164] Determine the current traffic condition information from the navigation information.

[0165] Based on road condition information, the vehicle's target driving mode is determined and automatically switched.

[0166] The vehicle control device 10 provided in the embodiment of the present application can execute the above method embodiment. Its specific implementation principles and technical effects can be found in the above method embodiment, and this embodiment will not be repeated here.

[0167] Figure 10 FIG1 shows a hardware structure diagram of a vehicle-mounted controller provided by an embodiment of the present application. Figure 10 As shown, the vehicle-mounted controller 20 is used to implement the operations corresponding to the vehicle-mounted controller in any of the above method embodiments. The vehicle-mounted controller 20 of this embodiment may include: a memory 21, a processor 22 and a communication interface 24.

[0168] Memory 21 is used to store computer programs. Memory 21 may include high-speed random access memory (RAM) or non-volatile memory (NVM), such as at least one disk memory. It may also be a USB flash drive, a mobile hard drive, a read-only memory, a magnetic disk, or an optical disk.

[0169] The processor 22 is used to execute the computer program stored in the memory to implement the vehicle control method in the above embodiment. For details, please refer to the relevant description in the above method embodiment. The processor 22 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can be any conventional processor, etc. The steps of the method disclosed in the present invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0170] Optionally, the memory 21 may be independent or integrated with the processor 22 .

[0171] When the memory 21 is a device independent of the processor 22, the onboard controller 20 may further include a bus 23. The bus 23 is used to connect the memory 21 and the processor 22. The bus 23 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be divided into address buses, data buses, control buses, etc. For ease of presentation, the buses in the drawings of this application are not limited to only one bus or one type of bus.

[0172] The communication interface 24 can be connected to the processor 21 via the bus 23. The communication interface can be used to communicate with other controllers in the vehicle, obtain information sent by other controllers, or send information to other controllers.

[0173] The vehicle-mounted controller provided in this embodiment can be used to execute the above-mentioned vehicle control method. Its implementation method and technical effects are similar, and this embodiment will not be repeated here.

[0174] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided in the various embodiments described above.

[0175] Among them, the computer-readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, a computer-readable storage medium is coupled to a processor so that the processor can read information from the computer-readable storage medium and write information to the computer-readable storage medium. Of course, the computer-readable storage medium can also be an integral part of the processor. The processor and the computer-readable storage medium can be located in an application-specific integrated circuit (ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the computer-readable storage medium can also exist in a communication device as discrete components.

[0176] Specifically, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random-access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0177] The present application also provides a computer program product, comprising a computer program stored in a computer-readable storage medium. At least one processor of a device can read the computer program from the computer-readable storage medium, and at least one processor executes the computer program so that the device implements the methods provided in the various embodiments described above.

[0178] An embodiment of the present application also provides a chip, which includes a memory and a processor, the memory is used to store computer programs, and the processor is used to call and run the computer programs from the memory, so that a device equipped with the chip executes the methods in various possible implementation modes as described above.

[0179] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0180] The modules may be physically separate, for example, installed in different locations on a single device, or installed on different devices, or distributed across multiple network units, or distributed across multiple processors. The modules may also be integrated, for example, installed in the same device, or integrated into a set of codes. The modules may exist in the form of hardware, or in the form of software, or may be implemented in the form of software plus hardware. The present application may select some or all of the modules according to actual needs to achieve the purpose of the present embodiment.

[0181] When each module is implemented as an integrated module in the form of a software function module, it can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to perform some steps of the methods of each embodiment of the present application.

[0182] It should be understood that, although the various steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they may be performed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times, and their execution order is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of sub-steps or stages of other steps.

[0183] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the aforementioned embodiments, those skilled in the art will appreciate that they may modify the technical solutions described in the aforementioned embodiments or replace some or all of the technical features therein with equivalents. However, such modifications or replacements do not deviate from the essence of the corresponding technical solutions within the scope of the various embodiments of this application.

Claims

1. A vehicle control method, characterized in that: The method comprises: Get vehicle driving information in real time; Calculating the vehicle's current driving index in real time based on the driving information; determining and automatically switching a target driving mode of the vehicle based on the driving indicator; The step of calculating the vehicle's current driving index in real time based on the driving information specifically includes: determining an accelerator pedal opening score, an accelerator pedal change rate score, a brake pedal change rate score, and a yaw angular velocity score based on the accelerator pedal opening, the accelerator pedal change rate, the brake pedal change rate, and the yaw angular velocity in the driving information at the current moment; Determine the ambient temperature correction factor, the remaining power correction factor, and the battery health correction factor based on the ambient temperature, the remaining power, and the battery health; determining the driving index of the vehicle at the current moment based on the accelerator pedal opening score, the accelerator pedal change rate score, the ambient temperature correction coefficient, the brake pedal change rate score, the yaw rate score, the remaining battery power correction coefficient, the battery health correction coefficient, and the driving index of the vehicle at the previous moment in the driving information at the current moment; When the vehicle is powered on, the method further includes: Obtaining a historical driving index stored in the vehicle, wherein the historical driving index is used as the driving index of the vehicle at the previous moment when the driving index is calculated for the first time after power-on; when the vehicle is powered off, the method further includes: Determine a driving index average value according to the historical driving index and the current driving index; and store the driving index average value so that the driving index average value covers the historical driving index.

2. The method according to claim 1, characterized in that Determining and automatically switching the target driving mode of the vehicle according to the driving index specifically includes: When the driving index is less than or equal to a first index, determining and automatically switching the target driving mode of the vehicle to the first mode; When the driving index is greater than or equal to the second index and less than or equal to the third index, determining and automatically switching the target driving mode of the vehicle to the second mode; When the driving index is greater than or equal to a fourth index, the target driving mode of the vehicle is determined and automatically switched to the third mode.

3. The method according to claim 1 or 2, characterized in that The method further comprises: Determining current traffic conditions from navigation information; According to the road condition information, a target driving mode of the vehicle is determined and automatically switched.

4. A vehicle control device, characterized in that: The device comprises: Acquisition module, used to obtain vehicle driving information in real time; a processing module, configured to calculate, in real time based on the driving information, a driving index of the vehicle at a current moment; and determine and automatically switch a target driving mode of the vehicle based on the driving index; The processing module is specifically configured to determine an acceleration pedal opening degree score, an acceleration pedal change rate score, a brake pedal change rate score, and a yaw angular velocity score based on the acceleration pedal opening degree, the acceleration pedal change rate, the brake pedal change rate, and the yaw angular velocity in the driving information at a current moment; Determine the ambient temperature correction factor, the remaining power correction factor, and the battery health correction factor based on the ambient temperature, the remaining power, and the battery health; determining the driving index of the vehicle at the current moment based on the accelerator pedal opening score, the accelerator pedal change rate score, the ambient temperature correction coefficient, the brake pedal change rate score, the yaw rate score, the remaining battery power correction coefficient, the battery health correction coefficient, and the driving index of the vehicle at the previous moment in the driving information at the current moment; When the vehicle is powered on, the processing module is further configured to obtain a historical driving index stored in the vehicle, wherein the historical driving index is used as the driving index of the vehicle at the previous moment when the driving index is calculated for the first time after power-on; When the vehicle is powered off, the processing module is further configured to determine a driving index average based on the historical driving index and the current driving index; and store the driving index average so that the driving index average covers the historical driving index.

5. A vehicle-mounted controller, characterized in that: The vehicle-mounted controller includes: a memory and a processor; The memory is used to store a computer program; the processor is used to implement the vehicle control method according to any one of claims 1 to 3 according to the computer program stored in the memory.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which is used to implement the vehicle control method according to any one of claims 1 to 3 when executed by a processor.

7. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the vehicle control method according to any one of claims 1 to 3 is implemented.

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