Method and device for determining opening degree of accelerator, vehicle and storage medium

Abstract

The invention provides a method and device for determining the opening degree of an accelerator, a vehicle and a storage medium. According to the method, the current accelerator opening degree is detected in real time, and if the current accelerator opening degree is lower than the last learning value (historical learning value) and larger than the minimum self-learning threshold value, the learning value is gradually reduced through the current accelerator opening degree and the historical learning value so that the accelerator opening degree corresponding to the actual accelerator minimum position can be learned. The scheme does not completely depend on the current accelerator opening degree, and the current accelerator opening degree is a detection value and is prone to drifting due to change of a detection environment or aging of a detection device. According to the scheme, by taking the current accelerator opening degree as a reference and combining the historical learning value, the final learning value can reflect the real mechanical return-to-zero position, and the problem of zero drift caused by accelerator abrasion of the minimum accelerator opening degree is effectively solved. Furthermore, after the vehicle controller controls the vehicle on the basis of the final learning value, the accuracy of driving control can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of motorcycles, and more particularly, to a method, device, vehicle, and storage medium for determining a throttle opening in the technical field of motorcycles. Background Art

[0002] With the continuous advancement of motorcycle technology and the improvement of people's living standards, the audience of motorcycles is becoming more and more extensive. However, more and more motorcycle-related problems have also arisen.

[0003] The throttle zero position refers to the initial reference position when the motorcycle's throttle handle is completely released and not being operated, that is, the minimum throttle position. As the motorcycle is used more frequently, the throttle will also wear more, causing the minimum throttle position to change.

[0004] Therefore, it is necessary to self-learn the throttle opening corresponding to the actual minimum throttle position (i.e., the minimum throttle opening) to determine the learning value of the self-learning of the minimum throttle opening, i.e., the learned minimum throttle opening, and use the learned minimum throttle opening as a benchmark to control the driving process of the motorcycle and improve the accuracy of driving control. Summary of the Invention

[0005] The present application provides a method, device, vehicle and storage medium for determining the throttle opening. The method can accurately learn the throttle opening corresponding to the actual minimum throttle position. After controlling the vehicle based on the learned minimum throttle opening, the accuracy of driving control can be improved.

[0006] In a first aspect, a method for determining a throttle opening is provided, the method comprising: when the throttle opening of a throttle handle in a vehicle is within a normal opening range, determining whether a current throttle opening when the throttle handle is in a released state is less than a last learned value of self-learning a minimum throttle opening, the minimum throttle opening being the throttle opening when the throttle handle is in a throttle zero position; when the current throttle opening is less than the last learned value, determining whether the current throttle opening is greater than a minimum self-learning threshold for downward self-learning of the minimum throttle opening; when the current throttle opening is greater than the minimum self-learning threshold, determining a first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learned value.

[0007] In the above technical solution, the current throttle opening is detected in real time. If the current throttle opening is lower than the last learning value (historical learning value) and greater than the minimum self-learning threshold, the learning value is gradually adjusted downward according to the current throttle opening and the historical learning value to learn the throttle opening corresponding to the actual minimum throttle position. The above solution does not completely rely on the current throttle opening. The current throttle opening is a detection value, which is easily affected by changes in the detection environment or aging of the detection device and drift. The above solution uses the current throttle opening as a reference and combines it with the historical learning value to make the final learning value reflect the actual mechanical zero position, effectively solving the zero-point drift problem of the minimum throttle opening caused by throttle wear. Furthermore, after the vehicle controller controls the vehicle based on the final learning value, the accuracy of driving control can be improved.

[0008] In combination with the first aspect, in some possible implementations, the last learned value is the first learned value, and the method for determining the last learned value includes: when the vehicle is powered on and not started, obtaining a first throttle opening when the throttle handle is in a released state; in response to the throttle handle being twisted to release a first preset number of times within a first preset time period, obtaining the throttle opening after the throttle handle is completely released for each of the first preset times, the corresponding throttle opening before the release operation being greater than a first opening threshold; when the throttle opening after the throttle handle is completely released for each number of times is within a preset opening range, determining the first throttle opening as the last learned value.

[0009] In the above technical solution, in a stable environment where the vehicle is powered on but not started, multiple manual interventions are used to verify the first learning value to ensure that the first learning value can reflect the actual mechanical zero position. In a specific implementation, it is required to complete multiple twisting to loosening operations within a first preset time length, and only when the throttle opening after each loosening is within the preset opening range, the initial first throttle opening is determined as a valid learning value. The above method can significantly improve the reliability and accuracy of the first self-learning of the minimum throttle opening through static initialization calibration and a dual filtering mechanism (i.e., verification of the number of operations and consistency check of the opening range), thereby obtaining a more accurate first learning value.

[0010] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, based on the current throttle opening and the last learned value, the first learning value of the current time for self-learning the minimum throttle opening is determined, including: determining the filter coefficient when self-learning the minimum throttle opening; determining the first opening deviation between the current throttle opening and the last learned value, and determining the product value between the filter coefficient and the first opening deviation; and determining the sum of the last learned value and the product value as the first learning value of the current time.

[0011] In the above technical solution, the first opening deviation between the current throttle opening and the historical learning value is calculated, and based on the filter coefficient, a first-order filtering algorithm is used to progressively approximate the throttle opening corresponding to the actual minimum throttle position, rather than directly using the current throttle opening. In the above method, the filter coefficient is related to the fluctuation caused by the throttle position sensor being affected by noise. The influence of high-frequency noise can be suppressed by setting a small filter coefficient, and the convergence process of self-learning can be accelerated by setting a large filter coefficient. This method can reduce the self-learning error. Through the weighted fusion mechanism of filter coefficient adjustment and opening deviation, it can significantly improve the accuracy and noise resistance of self-learning of the minimum throttle opening, ensuring that each learning value smoothly converges to the true mechanical zero position.

[0012] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the method also includes: when the current throttle opening is greater than the last learning value, determining whether the current throttle opening is in an opening range between a second opening threshold and a third opening threshold, the second opening threshold being the throttle opening value that actually triggers upward self-learning of the minimum throttle opening, and the third opening threshold being the throttle opening value that activates upward self-learning of the minimum throttle opening; when the current throttle opening is in the opening range, determining whether the minimum throttle opening has been subjected to upward self-learning during the current driving of the vehicle; when the minimum throttle opening has not been subjected to upward self-learning during the process, determining the second learning value for upward self-learning of the minimum throttle opening based on the last learning value, the opening increment allowed for a single upward self-learning, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening.

[0013] In the above technical solution, when it is detected that the current throttle opening is higher than the historical learning value, it is verified whether it is between the second opening threshold and the third opening threshold. The design of this opening range is intended to filter out the influence of instantaneous interference (such as hand shaking) and extreme deviation (such as sensor failure). If the above conditions of the current throttle opening are met and upward self-learning has not been performed during this driving cycle, the learning value is gradually increased according to the single allowable opening increment, but the final learning result is strictly constrained by the maximum self-learning threshold. The above method is limited by various opening thresholds, which can avoid the erroneous opening values that occur when self-learning is always downward, and can also reduce the probability of false triggering of upward self-learning. At the same time, through the limitation mechanism of the opening increment of single-cycle single self-learning, it can achieve precise control of upward self-learning of the minimum throttle opening.

[0014] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, based on the previous learning value, the opening increment allowed for a single upward self-learning and the maximum self-learning threshold for upward self-learning of the minimum throttle opening, the second learning value for upward self-learning of the minimum throttle opening is determined, including: determining the sum of the previous learning value and the opening increment as the current opening learning value; and determining the minimum opening value among the current opening learning value, the current throttle opening and the maximum self-learning threshold as the current second learning value.

[0015] In the above technical solution, the theoretical learning value for that time (the current opening learning value) is generated based on the sum of the historical learning value and the single allowable opening increment. Among them, the opening increment is limited in the single self-learning, which can avoid overshoot and enable the learning value to gradually approach the throttle opening corresponding to the actual minimum throttle position. Subsequently, the minimum opening value among the theoretical learning value, the current throttle opening and the maximum self-learning threshold is used as the final learning value for that time (the second learning value for that time). This ensures that the second learning value for that time does not exceed the current actual opening (the current throttle opening), preventing abnormally high opening values from being mistakenly marked as the actual mechanical zero position. In addition, subject to the safety margin (the maximum self-learning threshold), the final learning value can also meet system safety requirements. At the same time, the solution establishes a balance between the theoretical learning value, the current throttle opening and the safety margin by minimizing the selector, which can not only ensure the tracking speed of self-learning for the minimum throttle opening but also eliminate the risk of overshoot, thereby achieving precise control of upward self-learning.

[0016] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the method also includes: during the use of the vehicle, when it is detected that the actual throttle opening of the throttle handle is less than the learned minimum throttle opening, adding a second preset number of times on the basis of the target number, and the target number of times is used to indicate the number of times the throttle handle is twisted in reverse; based on the increased target number of times, determining the degree of throttle wear of the vehicle; when the throttle wear degree is the first wear degree and the cruise function of the vehicle is turned on, exiting the cruise function; when the throttle wear degree is the second wear degree, outputting a prompt message, and the prompt message is used to prompt the replacement of components related to the throttle control, and the second wear degree is higher than the first wear degree.

[0017] In the above technical solution, when it is detected that the actual throttle opening is less than the minimum throttle opening that has been learned, it indicates that there is an abnormal reverse twisting operation. At this time, a second preset number (such as 1 time) is accumulated on the target number. Subsequently, the cumulative number of times the throttle handle is reversed is mapped to the wear degree model. When the cumulative number triggers the first wear degree, if the cruise function is turned on, the cruise is forced to exit. This can prevent the vehicle speed from being out of control due to throttle opening signal drift. When the cumulative number triggers the second wear degree, a prompt is triggered to replace the relevant components. This can avoid informing the user of the current condition of the throttle system in a timely manner when the throttle wear degree is relatively serious, urging the user to replace the relevant components, and improving the safety of the vehicle.

[0018] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the method also includes: when the deviation value between the first learning value at that time and the minimum self-learning threshold is less than a first preset deviation value, or the number of downward self-learning of the minimum throttle opening is greater than or equal to a third preset number, the first learning value at that time is determined as the last learning value of the downward self-learning of the minimum throttle opening; and when the deviation value between the second learning value at that time and the maximum self-learning threshold is less than a second preset deviation value, the second learning value at that time is determined as the last learning value of the upward self-learning of the minimum throttle opening.

[0019] In the above technical solution, hard thresholds and time limits are set during downward self-learning or upward self-learning, ensuring that the self-learning process ends within a reasonable range through multiple constraints. For example, during downward self-learning, if the first learned value meets any of the downward self-learning cutoff conditions, the downward self-learning process is immediately terminated to prevent overlearning and failure to learn the true mechanical zero position. During upward self-learning, if the second learned value approaches the cutoff condition of the maximum self-learning threshold, the self-learning process is immediately terminated to prevent the learned value from deviating from the throttle opening corresponding to the true mechanical zero position.

[0020] In a second aspect, a device for determining a throttle opening is provided, the device comprising: a first determination module for determining, when the throttle opening of the throttle handle in the vehicle is within a normal opening range, whether the current throttle opening when the throttle handle is in a released state is less than the last learned value of self-learning for a minimum throttle opening, the minimum throttle opening being the throttle opening when the throttle handle is in a throttle zero position; a second determination module for determining, when the current throttle opening is less than the last learned value, whether the current throttle opening is greater than a minimum self-learning threshold for downward self-learning of the minimum throttle opening; and a third determination module for determining, when the current throttle opening is greater than the minimum self-learning threshold, the first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learned value.

[0021] In combination with the second aspect, in some possible implementations, the last learned value is the first learned value, and the first determination module is specifically used to: obtain the first throttle opening when the throttle handle is in a released state when the vehicle is powered on and not started; in response to the throttle handle being twisted to release a first preset number of times within a first preset time period, obtain the throttle opening after the throttle handle is completely released for each of the first preset times, the corresponding throttle opening before the release operation is greater than a first opening threshold; when the throttle opening after the throttle handle is completely released for each number of times is within a preset opening range, determine the first throttle opening as the last learned value.

[0022] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the third determination module is specifically used to: determine the filter coefficient when self-learning the minimum throttle opening; determine the first opening deviation between the current throttle opening and the last learning value, and determine the product value between the filter coefficient and the first opening deviation; and determine the sum of the last learning value and the product value as the first learning value of that time.

[0023] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the second determination module is also used to determine whether the current throttle opening is in an opening range between a second opening threshold and a third opening threshold when the current throttle opening is greater than the last learning value, the second opening threshold being the throttle opening value that actually triggers upward self-learning of the minimum throttle opening, and the third opening threshold being the throttle opening value that activates upward self-learning of the minimum throttle opening; when the current throttle opening is in the opening range, determine whether the minimum throttle opening has been upward self-learned during the current driving of the vehicle; the third determination module is also used to determine the second learning value for upward self-learning of the minimum throttle opening based on the last learning value, the opening increment allowed for a single upward self-learning, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening when the minimum throttle opening has not been upward self-learned during the process.

[0024] In combination with the second aspect and the above-mentioned implementation method, in some possible implementation methods, the third determination module is further specifically used to: determine the sum of the previous learning value and the opening increment as the current opening learning value; and determine the minimum opening value among the current opening learning value, the current throttle opening and the maximum self-learning threshold as the current second learning value.

[0025] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the device also includes: a processing module for adding a second preset number of times on the basis of the target number of times when it is detected that the actual throttle opening of the throttle handle is less than the learned minimum throttle opening during the use of the vehicle. The target number of times is used to indicate the number of times the throttle handle is twisted in reverse; a fourth determination module for determining the degree of throttle wear of the vehicle based on the increased target number of times; an exit module for exiting the cruise function when the throttle wear degree is a first wear degree and the cruise function of the vehicle is turned on; an output module for outputting a prompt message when the throttle wear degree is a second wear degree, the prompt message being used to prompt the replacement of components related to the throttle control, and the second wear degree is higher than the first wear degree.

[0026] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the fourth determination module is also used to: when the deviation value between the first learning value at that time and the minimum self-learning threshold is less than the first preset deviation value, or the number of downward self-learning of the minimum throttle opening is greater than or equal to the third preset number, determine the first learning value at that time as the last learning value of the downward self-learning of the minimum throttle opening; and when the deviation value between the second learning value at that time and the maximum self-learning threshold is less than the second preset deviation value, determine the second learning value at that time as the last learning value of the upward self-learning of the minimum throttle opening.

[0027] In a third aspect, a vehicle is provided, comprising a memory and a processor. The memory is configured to store executable program code, and the processor is configured to retrieve and execute the executable program code from the memory, so that the vehicle executes the method of the first aspect or any possible implementation of the first aspect.

[0028] In a fourth aspect, a computer-readable storage medium is provided, which stores an executable program code. When the executable program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a schematic diagram of a scenario of using a vehicle provided in an embodiment of the present application;

[0030] Figure 2 is a schematic flow chart of a method for determining throttle opening provided in an embodiment of the present application;

[0031] Figure 3 This is a schematic diagram of the operation of a rapid self-learning process provided by an embodiment of the present application;

[0032] Figure 4 is a structural diagram of a device for determining throttle opening provided in an embodiment of the present application;

[0033] Figure 5 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following will clearly and thoroughly describe the technical solutions in this application in conjunction with the accompanying drawings. In the description of the embodiments of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more than two.

[0035] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0036] Figure 1 This is a schematic diagram of a scenario using a throttle handle provided by an embodiment of the present application. Figure 1 The motorcycle shown describes the process of using the throttle handle.

[0037] like Figure 1 As shown, in an actual driving scenario, the user can turn the accelerator handle in direction a from the accelerator zero position to achieve the desired vehicle speed and power requirements, thereby driving to the destination.

[0038] The throttle zero position refers to the initial reference position when the motorcycle's throttle grip is completely released and not being operated, i.e., the minimum throttle position. As the motorcycle is used more frequently, the throttle grip wears out, causing the minimum throttle position to change, so that the actual throttle opening corresponding to the minimum throttle position is no longer 0%.

[0039] Therefore, it is necessary to self-learn the throttle opening corresponding to the actual minimum throttle position (i.e., the minimum throttle opening) to determine the learning value for the minimum throttle opening, i.e., the learned minimum throttle opening. The learned minimum throttle opening is used as a benchmark to control the driving process of the motorcycle and improve the accuracy of driving control. The specific implementation process can be found in Figure 2 shown.

[0040] Figure 2This is a schematic flowchart of a method for determining the throttle opening provided in an embodiment of the present application.

[0041] It should be understood that the method for determining the throttle opening provided in the embodiment of the present application can be applied to the following examples: Figure 1 The vehicle shown (e.g., a motorcycle).

[0042] For example, Figure 2 As shown, the method 200 includes the following steps 201 to 203.

[0043] Step 201, when the throttle opening of the throttle handle in the vehicle is within the normal opening range, determine whether the current throttle opening when the throttle handle is in the released state is less than the last learned value of the minimum throttle opening self-learned, and the minimum throttle opening is the throttle opening when the throttle handle is in the throttle zero position.

[0044] It should be understood that the "vehicle" in step 201 is a vehicle whose engine speed and power output are controlled by a throttle handle. Optionally, the vehicle includes any one of a motorcycle, a motorboat, a motor scooter, and some karts.

[0045] It should also be understood that "the throttle opening of the throttle grip is within the normal opening range" in the above step 201 is used to indicate that there is no abnormality in the throttle opening signal detected by the throttle position sensor in the vehicle.

[0046] It should be noted that the "current throttle opening" in step 201 is the throttle opening currently detected by the throttle position sensor when the throttle grip is released. In practice, the throttle position sensor may drift due to environmental changes or component aging, resulting in inaccurate current throttle opening. Therefore, the current throttle opening cannot be used as the actual throttle opening corresponding to the minimum throttle position. A feasible solution is to use the current throttle opening as a reference to perform self-learning of the minimum throttle opening.

[0047] It should also be noted that the “last learning value” in the above step 201 can be regarded as the learning value after the N-1th self-learning of the minimum throttle opening, where N is greater than or equal to 2.

[0048] In one possible implementation, the last learned value is the first learned value, and the method for determining the last learned value includes: when the vehicle is powered on and not started, obtaining a first throttle opening when the throttle handle is in a released state; in response to the throttle handle being twisted to release a first preset number of times within a first preset time period, obtaining the throttle opening after the throttle handle is completely released for each of the first preset times, the corresponding throttle opening before the release operation being greater than a first opening threshold; when the throttle opening after the throttle handle is completely released for each number of times is within a preset opening range, determining the first throttle opening as the last learned value.

[0049] It should be understood that the "first learned value" in the above scheme refers to the value learned after the first self-learning of the minimum throttle opening. Furthermore, the "vehicle is powered on but not started" in the above scheme refers to a condition in which the vehicle's power switch (key or ignition lock) is on, the vehicle's low-voltage circuits are energized, but the engine has not yet started. Furthermore, the above-mentioned first throttle opening is within a preset opening range.

[0050] It should also be understood that the phrase "twisting the throttle grip a first preset number of times until it is released within a first preset duration" in the above solution means repeatedly turning the throttle grip to a specified position and releasing it a first preset number of times within the first preset duration, with the throttle opening corresponding to the specified position being greater than a first opening threshold. Subsequently, whenever the throttle opening after the throttle grip is fully released remains within the preset opening range, the first throttle opening is determined as the first learned value. The first preset number of times may be greater than one.

[0051] In the above technical solution, in a stable environment where the vehicle is powered on but not started, multiple manual interventions are used to verify the first learning value to ensure that the first learning value can reflect the actual mechanical zero position. In a specific implementation, it is required to complete multiple twisting to loosening operations within a first preset time length, and only when the throttle opening after each loosening is within the preset opening range, the initial first throttle opening is determined as a valid learning value. The above method can significantly improve the reliability and accuracy of the first self-learning of the minimum throttle opening through static initialization calibration and a dual filtering mechanism (i.e., verification of the number of operations and consistency check of the opening range), thereby obtaining a more accurate first learning value.

[0052] Optionally, the first preset time length is 5 seconds, the first preset number of times is 3 times, the first opening threshold is 90%, and the preset opening range is 0% to 0.5%.

[0053] In some embodiments, in response to the throttle handle being twisted and released a first preset number of times within a first preset time period, before obtaining the throttle opening after the throttle handle is completely released for each of the first preset times, the method 200 also includes: detecting whether the vehicle is in a cruise control mode; and, in response to the throttle handle being twisted and released a first preset number of times within the first preset time period, obtaining the throttle opening after the throttle handle is completely released for each of the first preset times, including: when the vehicle is in a cruise control mode, in response to the throttle handle being twisted and released a first preset number of times within the first preset time period, obtaining the throttle opening after the throttle handle is completely released for each of the first preset times.

[0054] It should be understood that in the above solution, when the cruise control main control button or the cruise "set / -" button or the "Resume / +" button (any of the three types of buttons) in the vehicle is pressed and held, the vehicle is in cruise control mode. Among them, after the cruise control main control button is pressed and held, the cruise control indicator light on the instrument panel in the vehicle will light up, indicating that the vehicle is in the cruise control stage. When the vehicle accelerates to the desired speed, press the cruise "set" button and the vehicle will start cruising at the current speed; if you need to reduce the speed, you can press the "-" button. If the cruise speed has been set before and the "Resume" button is pressed, the vehicle will return to the previously set cruise speed; if you need to fine-tune the speed, you can continue to press and hold the "+" button to increase the speed.

[0055] In the above technical solution, only when the vehicle is in cruise control mode is it allowed to repeatedly turn the throttle handle to a specified position and release it according to a first preset number of times within a first preset time period, that is, trigger the rapid self-learning process of the minimum throttle position (the process of determining the first learning value). This is because in cruise control mode, even if the throttle handle is turned, the power of the engine will be limited to the idle state, and the power output of the vehicle will be locked, which can avoid accidental acceleration. In addition, the cruise control mode in this method needs to be maintained continuously, and usually requires the coordinated operation of both hands (that is, the left hand holds down any of the three types of buttons mentioned above, and the right hand operates the throttle handle), which can greatly reduce the probability of the above rapid self-learning process being accidentally triggered. Furthermore, the functional attributes of any of the above types of buttons naturally have a high operating threshold. Professionals must have a clear intention of rapid self-learning before they will actively trigger it, avoiding non-professionals from arbitrarily triggering the rapid self-learning process.

[0056] Figure 3 This is a schematic diagram of the operation of a fast self-learning process provided by the embodiment of the present application. Figure 3 The process of determining the first learning value is described by taking a motorcycle as the vehicle, a first preset time length of 5 seconds, and a first preset number of times as 3 as an example.

[0057] For example, Figure 3 As shown, at time 0, when the vehicle is powered on and not started, the first throttle opening when the throttle handle is in the released state is obtained. Subsequently, within 5 seconds, the throttle handle is repeatedly turned to the specified position and released 3 times. Specifically, the first time (the first twisting to releasing operation): the throttle handle is controlled to twist from the first throttle opening until it exceeds the first opening threshold, and then the throttle handle is released. After releasing, the final throttle opening is opening a1, that is, the throttle opening after the throttle handle is completely released for the first time. Then the second time (the second twisting to releasing operation), the throttle handle is controlled to twist from opening a1 until it exceeds the first opening threshold, and then the throttle handle is released. After releasing, the final throttle opening is opening a2, that is, the throttle opening after the throttle handle is completely released for the second time. Furthermore, for the third time (the third twisting to releasing operation), the throttle handle is controlled to twist from opening a2 until it exceeds the first opening threshold, and then the throttle handle is released. The final throttle opening after releasing is opening a3, that is, the throttle opening after the throttle handle is completely released for the third time.

[0058] When it is determined that the opening degrees a1 , a2 , and a3 are within the preset opening range (ie, very close to the first accelerator opening), the first accelerator opening is determined as the first learning value.

[0059] Step 202 : When the current throttle opening is less than the last learned value, determine whether the current throttle opening is greater than a minimum self-learning threshold for downward self-learning of the minimum throttle opening.

[0060] It should be understood that the "minimum self-learning threshold" in step 202 is the minimum throttle opening threshold for downward self-learning of the minimum throttle opening. It serves as a lower limit critical value that can be used to assist in determining whether to perform downward self-learning and when to terminate learning after performing downward self-learning. Typically, learning is terminated when the deviation between the final learned minimum throttle opening (i.e., a learning value of a certain time, which can be the first learning value of that time) and the minimum self-learning threshold is less than a first preset deviation value.

[0061] It should also be noted that the learning may be terminated based on whether the number of downward self-learning is greater than or equal to a third preset number of times.

[0062] Optionally, the minimum self-learning threshold is 0.22%, and the first preset deviation value is 0.1%.

[0063] It should be understood that the minimum self-learning threshold is greater than or equal to 0%, and is generally the throttle opening corresponding to a relatively low degree of throttle wear.

[0064] Step 203 : When the current throttle opening is greater than the minimum self-learning threshold, a first learning value for downward self-learning of the minimum throttle opening is determined based on the current throttle opening and the last learning value.

[0065] It should be understood that in step 203, if the current throttle opening is less than the previously learned value and greater than the minimum self-learning threshold, this indicates that the learning of the minimum throttle opening has not yet met the requirements for downward self-learning, and the downward self-learning process can continue. The "first learned value of the current time" in step 203 is the current learned value after the downward self-learning process.

[0066] In one possible implementation, step 203 determines the first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learned value, including: determining a filter coefficient when self-learning the minimum throttle opening; determining a first opening deviation between the current throttle opening and the last learned value, and determining a product value between the filter coefficient and the first opening deviation; and determining the sum of the last learned value and the product value as the first learning value for the current time.

[0067] It should be understood that the above scheme uses a first-order filtering algorithm to self-learn the minimum throttle opening downward, gradually approaching the throttle opening corresponding to the actual minimum throttle position. In addition, the value range of the filter coefficient is (0,1).

[0068] In the above technical solution, the first opening deviation between the current throttle opening and the historical learning value is calculated, and based on the filter coefficient, a first-order filtering algorithm is used to progressively approximate the throttle opening corresponding to the actual minimum throttle position, rather than directly using the current throttle opening. In the above method, the filter coefficient is related to the fluctuation caused by the throttle position sensor being affected by noise. The influence of high-frequency noise can be suppressed by setting a small filter coefficient, and the convergence process of self-learning can be accelerated by setting a large filter coefficient. This method can reduce the self-learning error. Through the weighted fusion mechanism of filter coefficient adjustment and opening deviation, it can significantly improve the accuracy and noise resistance of self-learning of the minimum throttle opening, ensuring that each learning value smoothly converges to the true mechanical zero position.

[0069] In some embodiments, determining a filter coefficient when performing self-learning on a minimum throttle opening includes: determining the filter coefficient based on the following formula (1);

[0070]

[0071] Where K is the filter coefficient and σ is the signal standard deviation.

[0072] It should be understood that the above-mentioned signal standard deviation refers to the standard deviation of multiple throttle openings collected by the throttle position sensor within a current period of time.

[0073] In some embodiments, determining the sum of the previous learning value and the product value as the first learning value for the current time includes: determining the first learning value for the current time based on the following formula (2);

[0074] Y 1,n =Y n-1 +K*(X n -Y n-1 ) (2)

[0075] Among them, Y 1,m is the first learning value of the current time, Y n-1 is the last learning value, K*(X n -Y n-1 ) is the product value, X n is the current throttle opening.

[0076] Optionally, the filter coefficient is 0.4.

[0077] In some embodiments, before determining the first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learning value in step 203, the method 200 also includes: determining whether a second opening deviation between the maximum throttle opening and the minimum throttle opening corresponding to the throttle handle within the current second preset time period is less than an opening fluctuation range threshold; and, based on the current throttle opening and the last learning value, determining the first learning value for downward self-learning of the minimum throttle opening, including: when the second opening deviation is less than the opening fluctuation range threshold, determining the first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learning value.

[0078] It should be understood that the above solution is to perform steady-state verification on the throttle opening signal before performing downward self-learning on the minimum throttle opening, so as to ensure that the downward self-learning is triggered only in a reliable environment.

[0079] In some embodiments, after determining the first learning value of the current time for downward self-learning of the minimum throttle opening, the method 200 further includes: storing the first learning value of the current time to a target memory, and the storage content in the target memory can still be retained after power failure.

[0080] Optionally, the target memory is any one of a read-only memory, an electrically erasable programmable read-only memory, and a flash memory.

[0081] It should be noted that steps 202 and 203, and the corresponding implementations, specifically involve a downward self-learning process for the minimum throttle opening. This reduces throttle idle travel and compensates for mechanical zero drift due to wear throughout the throttle's lifecycle. If errors occur during the downward self-learning process, an upward self-learning process is necessary to adjust the minimum throttle opening. The specific process for this is described below.

[0082] In one possible implementation, the method 200 further includes: when the current throttle opening is greater than the last learned value, determining whether the current throttle opening is in an opening range between a second opening threshold and a third opening threshold, the second opening threshold being the throttle opening value that actually triggers upward self-learning of the minimum throttle opening, and the third opening threshold being the throttle opening value that activates upward self-learning of the minimum throttle opening; when the current throttle opening is in the opening range, determining whether upward self-learning of the minimum throttle opening has been performed during the current driving of the vehicle; when the minimum throttle opening has not been upward self-learned during the process, determining the second learning value for upward self-learning of the minimum throttle opening based on the last learned value, the opening increment allowed for a single upward self-learning, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening.

[0083] It should be understood that in the above scheme, if the current throttle opening is greater than the last learned value and is within the range between the second and third opening thresholds, it indicates that the minimum throttle opening has not yet met the requirements for upward self-learning, and the upward self-learning process can continue. The "second learned value" in the above scheme refers to the current learned value after upward self-learning.

[0084] It should also be understood that the "maximum self-learning threshold" in the above scheme is the maximum throttle opening threshold for upward self-learning of the minimum throttle opening. It serves as an upper limit critical value, which can be used to determine when to stop learning after upward self-learning and to assist in determining the current learning value during upward self-learning. Typically, learning is terminated when the deviation between the final learned minimum throttle opening (i.e., a certain learning value, which can be the second learning value of that time) and the maximum self-learning threshold is less than a second preset deviation value.

[0085] In the above technical solution, when it is detected that the current throttle opening is higher than the historical learning value, it is verified whether it is between the second opening threshold and the third opening threshold. The design of this opening range is intended to filter out the influence of instantaneous interference (such as hand shaking) and extreme deviation (such as sensor failure). If the above conditions of the current throttle opening are met and upward self-learning has not been performed during this driving cycle, the learning value is gradually increased according to the single allowable opening increment, but the final learning result is strictly constrained by the maximum self-learning threshold. The above method can reduce the probability of false triggering of upward self-learning by limiting various opening thresholds. At the same time, through the limitation mechanism of the opening increment of single self-learning in a single cycle, it can achieve precise control of upward self-learning of the minimum throttle opening.

[0086] In some embodiments, after determining whether the minimum throttle opening has been self-learned upward during the current driving of the vehicle, the method 200 also includes: in the case where the minimum throttle opening has been self-learned upward during the process, determining the first learning value for the minimum throttle opening when self-learning downward based on the current throttle opening and the last learning value.

[0087] That is, if the upward self-learning process has been performed during the current driving of the vehicle, the downward self-learning process is continued to further learn the throttle opening corresponding to the actual minimum throttle position.

[0088] Optionally, the second opening threshold is 0.2%, and the third opening threshold is 2%.

[0089] Optionally, the opening increment is 0.2%, and the maximum self-learning threshold is 1.2%.

[0090] It should be understood that the maximum self-learning threshold is greater than the minimum self-learning threshold, which is usually the throttle opening corresponding to a more serious degree of throttle wear.

[0091] It should be noted that due to throttle wear, it is usually necessary to self-learn the minimum throttle opening downward. In practice, the phenomenon of "the current throttle opening is less than the last learned value" is common. The above solution limits the number of upward self-learning cycles to avoid continuous upward adjustment of the learned value.

[0092] It should also be noted that before upward self-learning of the minimum throttle opening, steady-state verification of the throttle opening signal is also required to ensure that upward self-learning is triggered only under reliable circumstances. Specifically, when the third opening deviation between the maximum throttle opening value and the minimum throttle opening value corresponding to the throttle grip within the current third preset time period is less than the opening fluctuation range threshold, the second learned value for the current upward self-learning of the minimum throttle opening is determined based on the last learned value, the opening increment allowed for a single upward self-learning session, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening.

[0093] In one possible implementation, based on the last learned value, the opening increment allowed for a single upward self-learning, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening, the second learned value for the current upward self-learning of the minimum throttle opening is determined, including: determining the sum of the last learned value and the opening increment as the current opening learned value; and determining the minimum opening value among the current opening learned value, the current throttle opening, and the maximum self-learning threshold as the current second learned value.

[0094] In the above technical solution, the theoretical learning value for that time (the current opening learning value) is generated based on the sum of the historical learning value and the single allowable opening increment. Among them, the opening increment is limited in the single self-learning, which can avoid overshoot and enable the learning value to gradually approach the throttle opening corresponding to the actual minimum throttle position. Subsequently, the minimum opening value among the theoretical learning value, the current throttle opening and the maximum self-learning threshold is used as the final learning value for that time (the second learning value for that time). This ensures that the second learning value for that time does not exceed the current actual opening (the current throttle opening), preventing abnormally high opening values from being mistakenly marked as the actual mechanical zero position. In addition, subject to the safety margin (the maximum self-learning threshold), the final learning value can also meet system safety requirements. At the same time, the solution establishes a balance between the theoretical learning value, the current throttle opening and the safety margin by minimizing the selector, which can not only ensure the tracking speed of self-learning for the minimum throttle opening but also eliminate the risk of overshoot, thereby achieving precise control of upward self-learning.

[0095] In some embodiments, determining the minimum opening value among the current opening learning value, the current throttle opening, and the maximum self-learning threshold as the current second learning value comprises: determining the current second learning value based on the following formula (3) and formula (4);

[0096] Y 2,n =min(X n ,Y′ n ,Y max ) (3)

[0097] Y′ n =Y n+-1 +ΔY (4)

[0098] Among them, Y 2,n is the second learning value of the current time, Y′ n Y is the learning value of the opening at that time, max is the maximum self-learning threshold, and ΔY is the opening increment.

[0099] In some embodiments, after determining the second learning value for upward self-learning of the minimum throttle opening, the method 200 further includes: storing the second learning value to a target memory, and the storage content in the target memory can still be retained after power failure.

[0100] In one possible implementation, the method 200 further includes: when the deviation value between the first learning value at that time and the minimum self-learning threshold is less than a first preset deviation value, or the number of downward self-learning of the minimum throttle opening is greater than or equal to a third preset number, determining the first learning value at that time as the last learning value of the downward self-learning of the minimum throttle opening; and, when the deviation value between the second learning value at that time and the maximum self-learning threshold is less than a second preset deviation value, determining the second learning value at that time as the last learning value of the upward self-learning of the minimum throttle opening.

[0101] In the above technical solution, a hard threshold (when the deviation between the first learning value and the minimum self-learning threshold is less than the first preset deviation value, or when the first learning value is determined to be the last learning value for downward self-learning of the minimum throttle opening) and a number limit (the number of downward self-learning of the minimum throttle opening is greater than or equal to the third preset number) are set during the downward self-learning or upward self-learning process, and multiple constraints are used to ensure that the self-learning process ends within a reasonable range. For example, in downward self-learning, if the first learning value meets any of the end conditions of the downward self-learning process, the downward self-learning process is immediately terminated to prevent the true mechanical zero position from being learned due to over-learning. In upward self-learning, if the second learning value approaches the end condition of the maximum self-learning threshold, the self-learning process is immediately terminated to avoid the learning value deviating from the throttle opening corresponding to the true mechanical zero position.

[0102] Optionally, the first preset degree is that the deviation between the minimum self-learning threshold and the first learning value is less than 5%. The deviation is calculated as follows: (minimum self-learning threshold - first learning value) / minimum self-learning threshold.

[0103] Optionally, the second preset degree is that the deviation between the second learning value and the maximum self-learning threshold is less than 6%. The deviation is calculated as follows: (current second learning value - maximum self-learning threshold) / maximum self-learning threshold.

[0104] It should be understood that the above-mentioned downward self-learning process and upward self-learning process can be regarded as a dynamic self-learning process for self-learning the minimum throttle opening.

[0105] The following describes the process of self-learning the minimum throttle opening, taking the previous learning value as the third learning value and 0.45%, the minimum self-learning threshold as 0.22%, the filter coefficient as 0.4, the first preset deviation as 0.1%, the third preset number of times as 15 times, the opening increment as 0.2%, the maximum self-learning threshold as 1.2%, the second opening threshold as 0.2%, the third opening threshold as 2%, and the second preset deviation as 0.1% as an example.

[0106] 1) The fourth process: When the throttle handle is in the released state, the current throttle opening is 0.3%. The current throttle opening of 0.3% is less than the third learning value of 0.45%, and the current throttle opening of 0.3% is greater than the minimum self-learning threshold of 0.22%. Therefore, the fourth process is a downward self-learning process.

[0107] Specifically, combined with formula (2), we can get the fourth learning value Y 1,4 = 3rd learning value 0.45% + filter coefficient * (current throttle opening 0.3% - 3rd learning value 0.45%) = 0.39%. The deviation between the 4th learning value 0.39 and the minimum self-learning threshold of 0.22% is 0.17%. 0.17% is greater than the first preset deviation value of 0.1%, indicating that none of the above cutoff conditions are met, and the next self-learning process continues.

[0108] 2) The fifth process: The current throttle opening is 0.4%, which is greater than the fourth learning value of 0.39%, and the current throttle opening of 0.4% is within the opening range between the second opening threshold of 0.2% and the third opening threshold of 2%. Therefore, the fifth process is an upward self-learning process.

[0109] Specifically, combining formula (3) and formula (4), we can get the fifth learning value Y 2,5 = min(current throttle opening 0.4%, fifth learning value, maximum self-learning threshold) = 0.4%. The fifth learning value = the fourth learning value 0.39 + the opening increment 0.2% = 0.59%. The deviation between the fifth learning value 0.4 and the maximum self-learning threshold of 1.2% is 0.8%. This 0.8% is greater than the second preset deviation of 0.1%, indicating that none of the above cutoff conditions are met, and the next self-learning process continues.

[0110] 3) The 6th process: The current throttle opening is 0.41%, which is greater than the 5th learning value of 0.4%, and the current throttle opening of 0.41% is within the opening range between the second opening threshold of 0.2% and the third opening threshold of 2%. Therefore, the 6th process should be an upward self-learning process. However, an upward self-learning process already exists in the historical learning process. Therefore, the 6th process should be corrected to a downward self-learning process.

[0111] Specifically, combined with formula (2), we can get the 6th learning value Y 1,6 = 5th learned value 0.4% + filter coefficient * (current throttle opening 0.41% - 5th learned value 0.4%) = 0.404%. The deviation between the 6th learned value 0.404 and the minimum self-learning threshold of 0.22% is 0.184%. 0.184% is greater than the first preset deviation value of 0.1%, indicating that none of the above cutoff conditions are met, and the next self-learning process continues.

[0112] 4) The 7th process: The current throttle opening is 0.31%, which is less than the 6th learning value 0.404%, and the current throttle opening 0.31% is greater than the minimum self-learning threshold 0.22%. Therefore, the 7th process is a downward self-learning process.

[0113] Specifically, combined with formula (2), we get the 7th learning value Y 1,7 = 6th learned value 0.404% + filter coefficient * (current throttle opening 0.31% - 6th learned value 0.404%) ≈ 0.37%. The deviation between the 7th learned value 0.37 and the minimum self-learning threshold of 0.22% is 0.15%. 0.15% is greater than the first preset deviation of 0.1%, indicating that none of the above cutoff conditions are met, and the next self-learning process continues.

[0114] 5) The 8th process: the current throttle opening is 0.3%, which is less than the 7th learning value 0.37%, and the current throttle opening 0.3% is greater than the minimum self-learning threshold 0.22%. Therefore, the 8th process is a downward self-learning process.

[0115] Specifically, combined with formula (2), we get the 8th learning value Y 1,8 = 7th learning value 0.37% + filter coefficient * (current throttle opening 0.3% - 7th learning value 0.37%) ≈ 0.342%. The deviation between the 8th learning value 0.342 and the minimum self-learning threshold of 0.22% is 0.122%. 0.122% is greater than the first preset deviation value of 0.1%, indicating that none of the above cutoff conditions are met, and the next self-learning process continues.

[0116] 6) The 9th process: the current throttle opening is 0.28%, which is less than the 8th learning value 0.342%, and the current throttle opening 0.28% is greater than the minimum self-learning threshold 0.22%. Therefore, the 9th process is a downward self-learning process.

[0117] Specifically, combined with formula (2), we get the 9th learning value Y 1,9= 8th learned value 0.342% + filter coefficient * (current throttle opening 0.28% - 8th learned value 0.342%) ≈ 0.32%. The deviation between the 9th learned value 0.32 and the minimum self-learning threshold of 0.22% is 0.1%. 0.1% is equal to the first preset deviation value of 0.1%, indicating that none of the above cutoff conditions are met, and the next self-learning process continues.

[0118] 7) The 10th process: The current throttle opening is 0.28%, which is less than the 9th learning value 0.32%, and the current throttle opening 0.28% is greater than the minimum self-learning threshold 0.22%. Therefore, the 10th process is a downward self-learning process.

[0119] Specifically, combined with formula (2), we get the 10th learning value Y 1,10 = 9th learned value 0.32% + filter coefficient * (current throttle opening 0.28% - 9th learned value 0.32%) ≈ 0.3%. The deviation between the 10th learned value 0.3 and the minimum self-learning threshold of 0.22% is 0.08%. This 0.08% is less than the first preset deviation of 0.1%, thus satisfying the aforementioned "when the deviation between the first learned value and the minimum self-learning threshold is less than the first preset deviation" cutoff condition, the self-learning process is terminated. Therefore, the actual throttle opening corresponding to the minimum throttle position is considered to be 0.3%.

[0120] It should be understood that in the above-mentioned processes from the 4th to the 10th, the throttle opening (current throttle opening) when the throttle handle is in the released state is obtained through the throttle position sensor in each of the 6 times. Under normal circumstances, the current throttle openings of the 6 times should be relatively close, and the current throttle openings of the 5th and 6th processes are abnormal.

[0121] It should also be understood that the "current throttle opening when the throttle grip is released" in step 201 can also be changed to the "actual throttle opening corresponding to the throttle grip." That is, in the first strategy, during the self-learning of the minimum throttle opening, the current throttle opening when the throttle grip is released can be obtained at each step, ultimately learning the throttle opening corresponding to the actual minimum throttle position. Alternatively, in the second strategy, during the self-learning of the minimum throttle opening, the actual throttle opening corresponding to the throttle grip can be obtained at each step, ultimately learning the throttle opening corresponding to the actual minimum throttle position. The second strategy does not require the throttle grip to be released.

[0122] It's important to note that motorcycle throttle systems differ from those of passenger cars. The throttle grip on a motorcycle can be twisted backwards, and frequently twisting the throttle grip backwards can cause throttle wear. The following describes an implementation method to address the degree of throttle wear on motorcycles.

[0123] In one possible implementation, the method 200 further includes: during the use of the vehicle, when it is detected that the actual throttle opening of the throttle handle is less than the learned minimum throttle opening, adding a second preset number of times on the basis of the target number, and the target number of times is used to indicate the number of times the throttle handle is twisted in reverse; based on the increased target number of times, determining the degree of throttle wear of the vehicle; when the throttle wear degree is a first degree of wear and the cruise function of the vehicle is turned on, exiting the cruise function; when the throttle wear degree is a second degree of wear, outputting a prompt message, and the prompt message is used to prompt the replacement of components related to the throttle control, and the second degree of wear is higher than the first degree of wear.

[0124] It should be understood that the "learned minimum throttle opening" in the above scheme refers to the most recently learned minimum throttle opening, which is stored in the target memory. Furthermore, when the actual throttle grip opening is less than the learned minimum throttle opening, it indicates that the throttle grip has been reversed. The "second preset number" in the above scheme is 1. The above scheme updates the number of times the throttle grip has been reversed by adding the second preset number to the target number. The "increased target number" is the cumulative number of times the throttle grip has been reversed.

[0125] It should be noted that the logic behind cruise control disengagement is that even mild wear (the first degree of wear) can cause the cruise control throttle reference to drift, leading the vehicle controller to misjudge the user's driving intention and trigger unintended acceleration or braking. Furthermore, when determining whether the throttle grip has been reversed (the actual throttle opening of the throttle grip is less than the learned minimum throttle opening), it is necessary to ensure that the throttle opening signal is normal and that both the rapid self-learning process and the dynamic self-learning process have completed.

[0126] In the above technical solution, when it is detected that the actual throttle opening is less than the minimum throttle opening that has been learned, it indicates that there is an abnormal reverse twisting operation. At this time, a second preset number (such as 1 time) is accumulated on the target number. Subsequently, the cumulative number of times the throttle handle is reversed is mapped to the wear degree model. When the cumulative number triggers the first wear degree, if the cruise function is turned on, the cruise is forced to exit. This can prevent the vehicle speed from being out of control due to the drift of the throttle opening signal; when the cumulative number triggers the second wear degree, a prompt is triggered to replace the relevant components. This can avoid informing the user of the current condition of the throttle system in a timely manner when the throttle wear degree is relatively serious, urging the user to replace the relevant components and improving the safety of the vehicle. In addition, the scheme realizes closed-loop management from abnormal detection of throttle mechanical wear to safety response through the cumulative number of times the throttle handle is reversed and the graded wear warning mechanism, which can extend the service life of the relevant components.

[0127] In some embodiments, the degree of throttle wear of the vehicle is determined based on the increased target number, including: when the increased target number is less than or equal to the first number, determining the degree of throttle wear as a first degree of wear; when the increased target number is greater than the first number and less than the second number, determining the degree of throttle wear as a third degree of wear; when the increased target number is greater than the second number, determining the degree of throttle wear as a second degree of wear, the second degree of wear being higher than the third degree of wear, and the third degree of wear being higher than the first degree of wear.

[0128] Optionally, the first number is 100 times, and the second number is 500 times.

[0129] Figure 4 It is a structural diagram of a device for determining throttle opening provided in an embodiment of the present application.

[0130] For example, Figure 4 As shown, the apparatus 400 includes:

[0131] A first determining module 401 is configured to determine, when the throttle opening of the throttle grip of the vehicle is within a normal opening range, whether the current throttle opening when the throttle grip is in a released state is less than a last learned value of a minimum throttle opening, the minimum throttle opening being the throttle opening when the throttle grip is in a throttle zero position;

[0132] A second determining module 402 is configured to determine, when the current throttle opening is less than the last learned value, whether the current throttle opening is greater than a minimum self-learning threshold for downward self-learning of the minimum throttle opening;

[0133] The third determining module 403 is configured to determine a first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learning value when the current throttle opening is greater than the minimum self-learning threshold.

[0134] Optionally, the last learned value is the first learned value, and the first determination module 401 is specifically used to: obtain a first throttle opening when the throttle handle is in a released state when the vehicle is powered on and not started; in response to twisting the throttle handle to release a first preset number of times within a first preset time period, obtain the throttle opening after the throttle handle is completely released for each of the first preset times, the corresponding throttle opening before the release operation is greater than a first opening threshold; when the throttle opening after the throttle handle is completely released for each number of times is within a preset opening range, determine the first throttle opening as the last learned value.

[0135] Optionally, the third determination module 403 is specifically used to: determine the filter coefficient when self-learning the minimum throttle opening; determine the first opening deviation between the current throttle opening and the last learning value, and determine the product value between the filter coefficient and the first opening deviation; and determine the sum of the last learning value and the product value as the first learning value of the current time.

[0136] Optionally, the second determination module 402 is further used to determine whether the current throttle opening is in an opening range between a second opening threshold and a third opening threshold when the current throttle opening is greater than the last learning value, the second opening threshold being the throttle opening value that actually triggers upward self-learning of the minimum throttle opening, and the third opening threshold being the throttle opening value that activates upward self-learning of the minimum throttle opening; when the current throttle opening is in the opening range, determine whether upward self-learning has been performed on the minimum throttle opening during this driving of the vehicle; the third determination module 403 is further used to determine the second learning value for upward self-learning of the minimum throttle opening based on the last learning value, the opening increment allowed for a single upward self-learning, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening when the minimum throttle opening has not been upward self-learned during the process.

[0137] Optionally, the third determination module 403 is further specifically used to: determine the sum of the previous learning value and the opening increment as the current opening learning value; and determine the minimum opening value among the current opening learning value, the current throttle opening and the maximum self-learning threshold as the current second learning value.

[0138] Optionally, the device 400 also includes: a processing module for increasing a second preset number of times based on a target number of times when it is detected that the actual throttle opening of the throttle handle is less than a learned minimum throttle opening during the use of the vehicle, and the target number of times is used to indicate the number of times the throttle handle is twisted in reverse; a fourth determination module for determining the degree of throttle wear of the vehicle based on the increased target number of times; an exit module for exiting the cruise function when the throttle wear degree is a first degree of wear and the cruise function of the vehicle is turned on; an output module for outputting a prompt message when the throttle wear degree is a second degree of wear, and the prompt message is used to prompt the replacement of components related to the throttle control, and the second degree of wear is higher than the first degree of wear.

[0139] Optionally, the fourth determination module is also used to: when the deviation value between the first learning value at that time and the minimum self-learning threshold is less than a first preset deviation value, or the number of downward self-learning of the minimum throttle opening is greater than or equal to a third preset number, determine the first learning value at that time as the last learning value of downward self-learning of the minimum throttle opening; and when the deviation value between the second learning value at that time and the maximum self-learning threshold is less than a second preset deviation value, determine the second learning value at that time as the last learning value of upward self-learning of the minimum throttle opening.

[0140] Figure 5 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application.

[0141] For example, Figure 5 As shown, the vehicle 500 includes: a memory 501 and a processor 502, wherein the memory 501 stores an executable program code 503, and the processor 502 is used to call and execute the executable program code 503 to perform a method for determining the throttle opening.

[0142] In addition, an embodiment of the present application also protects a device, which may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a method for determining the throttle opening provided in an embodiment of the present application.

[0143] In this embodiment, the device can be divided into functional modules based on the above-described method examples. For example, each functional module can be mapped to a specific functional module, or two or more functions can be integrated into a single processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and represents only a logical functional division. In actual implementation, other division methods may be used.

[0144] In the case where the functional modules are divided according to their respective functions, the device may further include a first determination module, a second determination module, a third determination module, a processing module, a fourth determination module, an exit module, and an output module. It should be noted that all relevant contents involved in the above method embodiments can be referred to the functional descriptions of the corresponding functional modules and will not be repeated here.

[0145] It should be understood that the device provided in this embodiment is used to execute the above-mentioned method for determining the throttle opening, and thus can achieve the same effect as the above-mentioned implementation method.

[0146] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is used in a vehicle, the processing module may be used to control and manage the vehicle's movements. The storage module may be used to support the vehicle's execution of relevant executable program code, etc.

[0147] The processing module may be a processor or controller that implements or executes the various exemplary logic blocks, modules, and circuits described in conjunction with the present disclosure. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processing (DSP) and a microprocessor, and the storage module may be a memory.

[0148] In addition, the device provided in the embodiments of the present application can specifically be a chip, component or module, and the chip may include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a method for determining the throttle opening provided in the above embodiment.

[0149] This embodiment also provides a computer-readable storage medium, which stores executable program code. When the executable program code runs on a computer, the computer executes the above-mentioned related method steps to implement a method for determining the throttle opening provided in the above embodiment.

[0150] This embodiment further provides a computer program product. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement a method for determining the throttle opening provided in the above embodiment.

[0151] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0152] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0153] In the 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 merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, 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 units, which can be electrical, mechanical or other forms.

[0154] The above content is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for determining throttle opening, characterized in that: The method comprises: determining, when the throttle opening of the throttle grip in the vehicle is within a normal opening range, whether the current throttle opening when the throttle grip is in a released state is less than a last learned value of a minimum throttle opening during self-learning, the minimum throttle opening being the throttle opening when the throttle grip is in a throttle zero position; When the current throttle opening is less than the last learned value, determining whether the current throttle opening is greater than a minimum self-learning threshold for downward self-learning of the minimum throttle opening; When the current throttle opening is greater than the minimum self-learning threshold, a first learning value for downward self-learning of the minimum throttle opening is determined based on the current throttle opening and the last learning value.

2. The method according to claim 1, characterized in that The last learned value is a first learned value, and the method for determining the last learned value includes: When the vehicle is powered on and not started, obtaining a first throttle opening when the throttle handle is in a released state; In response to the throttle grip being twisted and released a first preset number of times within a first preset time period, obtaining a throttle opening after the throttle grip is completely released for each of the first preset number of times, the throttle opening corresponding to the release operation being greater than a first opening threshold; When the throttle opening after the throttle grip is completely released is within a preset opening range at each of the times, the first throttle opening is determined as the last learned value.

3. The method according to claim 1, characterized in that The determining, based on the current throttle opening and the last learned value, of the first learning value for downward self-learning of the minimum throttle opening includes: Determine the filter coefficient when performing self-learning on the minimum throttle opening; Determining a first opening deviation between the current throttle opening and the last learned value, and determining a product value between the filter coefficient and the first opening deviation; The sum of the previous learning value and the product value is determined as the first learning value of the current time.

4. The method according to claim 1, wherein The method further comprises: If the current throttle opening is greater than the last learned value, determining whether the current throttle opening is within an opening range between a second opening threshold and a third opening threshold, wherein the second opening threshold is a throttle opening value that actually triggers upward self-learning of the minimum throttle opening, and the third opening threshold is a throttle opening value that activates upward self-learning of the minimum throttle opening; When the current throttle opening is within the opening range, determining whether a minimum throttle opening has been self-learned upward during the current driving of the vehicle; In the case that the minimum throttle opening has not been self-learned upward during the process, the second learning value for the minimum throttle opening for upward self-learning is determined based on the last learning value, the opening increment allowed for a single upward self-learning and the maximum self-learning threshold for upward self-learning of the minimum throttle opening.

5. The method according to claim 4, characterized in that The determining of the second learning value for the upward self-learning of the minimum throttle opening based on the previous learning value, the opening increment allowed for a single upward self-learning, and the maximum self-learning threshold for upward self-learning of the minimum throttle opening comprises: Determine the sum of the previous learning value and the opening increment as the current opening learning value; The minimum opening value among the current opening learning value, the current throttle opening and the maximum self-learning threshold is determined as the current second learning value.

6. The method according to claim 4, characterized in that The method further comprises: During use of the vehicle, if it is detected that the actual throttle opening of the throttle grip is less than the learned minimum throttle opening, a second preset number is added to the target number, where the target number indicates the number of times the throttle grip is reversely twisted; determining a degree of throttle wear of the vehicle based on the increased target number of times; When the throttle wear degree is a first wear degree and the cruise function of the vehicle is turned on, exiting the cruise function; When the throttle wear degree is a second wear degree, a prompt message is output, wherein the prompt message is used to prompt the replacement of components related to the throttle control, and the second wear degree is higher than the first wear degree.

7. The method according to any one of claims 1 to 5, characterized in that The method further comprises: If the deviation between the first learning value and the minimum self-learning threshold is less than a first preset deviation, or the number of times the minimum throttle opening is self-learned downward is greater than or equal to a third preset number, the first learning value is determined as the last learning value of the minimum throttle opening; And, when the deviation between the second learning value and the maximum self-learning threshold is smaller than the second preset deviation, the second learning value is determined as the last learning value of the upward self-learning of the minimum throttle opening.

8. A device for determining throttle opening, characterized in that: The device comprises: a first determining module configured to determine, when a throttle opening of a throttle grip in a vehicle is within a normal throttle opening range, whether a current throttle opening when the throttle grip is in a released state is less than a last learned value of a minimum throttle opening during self-learning, the minimum throttle opening being a throttle opening when the throttle grip is in a throttle zero position; a second determining module, configured to determine, when the current throttle opening is less than the last learned value, whether the current throttle opening is greater than a minimum self-learning threshold for downward self-learning of the minimum throttle opening; The third determining module is configured to determine a first learning value for downward self-learning of the minimum throttle opening based on the current throttle opening and the last learning value when the current throttle opening is greater than the minimum self-learning threshold.

9. A vehicle, characterized in that: The vehicle comprises: a memory for storing executable program code; A processor is configured to call and run the executable program code from the memory, so that the vehicle executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores an executable program code, and when the executable program code is executed, the method according to any one of claims 1 to 7 is implemented.

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