A method for detecting handbrake malfunctions in electric bicycles, an electric bicycle, and a storage medium.

Abstract

This invention provides a method for detecting handbrake malfunctions on electric bicycles, an electric bicycle, and a storage medium. When the real-time braking distance changes from small to large, the method determines the time point when the real-time braking distance equals a first preset threshold. It then acquires the speed of the electric bicycle at the initial time point and collects braking distance node values ​​within a first preset time period starting from the initial time point at preset time intervals, obtaining a first braking distance dataset. Elements whose difference between the braking distance node value and the maximum braking distance is less than a second preset threshold are used as a second braking distance dataset. This determines the time interval from the initial time point to the minimum time point and acquires the speed of the electric bicycle at the minimum time point, thereby determining the average acceleration within the time period and thus determining whether the handbrake is currently malfunctioning. This application has high detection efficiency and can accurately reflect whether the brake is malfunctioning.

Description

Technical Field

[0001] This invention relates to the field of electric bicycle technology, and in particular to a method for detecting electric bicycle handbrake malfunctions, an electric bicycle, and a storage medium. Background Technology

[0002] To date, shared electric bicycles have been in operation for some time. With the increase in usage time, the mechanical handbrakes of many shared electric bicycles have problems such as being too tight or too loose. When the brake is too tight, when the user presses the brake lever while riding the electric bicycle, the speed will drop rapidly in a short period of time, causing a sudden stop, which is very likely to cause safety problems. When the brake is too loose, the speed is difficult to reduce to the desired speed in a short period of time, which is also very likely to cause safety problems.

[0003] Currently, the mechanical handbrakes of shared electric bicycles are generally inspected periodically by maintenance personnel. These personnel rely on their subjective experience to determine whether the handbrakes are too loose or too tight when the bicycles are stationary (e.g., parked at a parking spot). This method is quite subjective and cannot accurately reflect the braking effect during riding. Moreover, relying on manual inspections is time-consuming and labor-intensive, and it is easy to miss or misreport inspections. In reality, many shared electric bicycles still have mechanical handbrakes that are either too loose or too tight.

[0004] In view of this, it is necessary to propose a method for detecting handbrake malfunctions in electric bicycles, an electric bicycle, and a storage medium to solve or at least alleviate the above-mentioned defects. Summary of the Invention

[0005] The main objective of this invention is to provide a method for detecting handbrake faults in electric bicycles, an electric bicycle, and a storage medium, in order to solve the problems of low objectivity and low detection efficiency in the existing technology of relying on manual inspection for detecting mechanical handbrake faults in electric bicycles.

[0006] To achieve the above objectives, the present invention provides a method for detecting handbrake malfunctions in electric bicycles, comprising the following steps:

[0007] S1, obtain the real-time status information of the electric bicycle, and when the electric bicycle is in motion, obtain the maximum braking stroke of the handbrake under ideal conditions;

[0008] S2, determine the real-time braking stroke of the current handbrake, and determine whether the real-time braking stroke is changing from small to large;

[0009] S3, when the real-time braking stroke changes from small to large, determine the time node when the real-time braking stroke is equal to the first preset threshold, and use the time node as the initial time node;

[0010] S4, obtain the speed V1 of the electric bicycle at the initial time node, and collect the braking stroke node values ​​within a first preset time period after the initial time node according to the preset time interval to obtain the first braking stroke dataset; wherein, each element in the first braking stroke dataset includes a time node and the braking stroke node value corresponding to the time node.

[0011] S5, determine whether there are elements in the brake stroke dataset that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold. If so, take the elements that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than the second preset threshold as the second brake stroke dataset, and determine the minimum time node from the second brake stroke dataset.

[0012] S6, determine the time interval t between the initial time node and the minimum time node, and obtain the speed V2 of the electric bicycle at the minimum time node;

[0013] S7. Determine the average acceleration of the electric bicycle within the time interval t based on the vehicle speed V1, the vehicle speed V2 and the time interval t, and determine whether the current handbrake is in a fault state based on the average acceleration and the acceleration threshold.

[0014] Preferably, step S7, determining whether the current handbrake is in a fault state based on the average acceleration and acceleration threshold, specifically includes the following steps:

[0015] Determine the difference between the average acceleration and the acceleration threshold;

[0016] When the difference is less than or equal to a third preset threshold, the current handbrake is determined to be in an overly tight fault state.

[0017] When the difference is greater than or equal to a fourth preset threshold, the current handbrake is determined to be in a fault state of being too loose; wherein, the fourth preset threshold is greater than the third preset threshold;

[0018] When the difference is greater than the third preset threshold and less than the fourth preset threshold, the current handbrake is determined to be in a normal state.

[0019] Preferably, step S7, which determines the average acceleration of the electric bicycle within the time interval t based on vehicle speeds V1 and V2 and the time interval t, specifically includes the following steps:

[0020] Based on vehicle speeds V1 and V2, and the time interval t, the formula is used. The average acceleration a of the electric bicycle during the time period t is obtained.

[0021] Preferably, obtaining the maximum braking distance of the handbrake under ideal conditions in step S1 specifically includes the following steps:

[0022] Under ideal conditions, the angle θ1 between the brake lever and the handlebars of the electric bicycle is obtained when the brake lever of the current handbrake is furthest away from the handlebars of the electric bicycle; and the angle θ2 between the brake lever and the handlebars of the current handbrake is obtained when the brake lever of the current handbrake is closest to the handlebars of the electric bicycle.

[0023] Determine the angle difference between the included angle θ1 and the included angle θ2. and the angle difference This represents the maximum braking stroke of the electric bicycle under ideal conditions.

[0024] Preferably, determining the real-time braking stroke of the current handbrake in step S2 specifically includes the following steps:

[0025] The angle sensor detects the real-time angle θ3 between the current handbrake lever and the handlebars of the electric bicycle;

[0026] Determine the angle difference between the included angle θ1 and the real-time included angle θ3. and the angle difference This refers to the real-time braking stroke of the current handbrake.

[0027] Preferably, after determining that the current handbrake is in an overly tight fault state, the step further includes the following step:

[0028] Within a second preset time period after the moment when the current handbrake is determined to be in an over-tight fault state, the number of times n is determined to be in an over-tight fault state is counted, and it is determined whether the number n is greater than a first preset number.

[0029] If the number of times n is greater than a first preset number of times, the electric bicycle corresponding to the current handbrake is marked as a faulty vehicle;

[0030] Responding to the user's lock command and obtaining the return location of the electric bicycle, a first maintenance command is sent to the selected maintenance personnel based on the return location.

[0031] Preferably, after determining that the current handbrake is in a fault state of being too loose, the step further includes the following step:

[0032] Within a third preset time period after the moment when the current handbrake is determined to be in an overly loose fault state, the number of times m is determined to be in an overly loose fault state is counted, and it is determined whether the number m is greater than a second preset number.

[0033] If the number of times m is greater than the second preset number of times, mark the electric bicycle corresponding to the current handbrake as a faulty vehicle;

[0034] Responding to the user's lock command and obtaining the return location of the electric bicycle, a second maintenance command is sent to the selected maintenance personnel based on the return location.

[0035] Preferably, after determining whether the brake stroke dataset contains elements that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold in step S5, the method further includes the following step:

[0036] If there are no elements in the brake stroke dataset that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold, return to step S2.

[0037] The present invention also provides an electric bicycle, including a vehicle body, the vehicle body including a brake lever and a handlebar, and also including an angle sensor and a control system disposed within the vehicle body. The angle sensor is used to detect the angle between the brake lever and the handlebar. The angle sensor is connected to the control system. The control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the electric bicycle handbrake fault detection method described above.

[0038] The present invention also provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for detecting a handbrake fault in an electric bicycle.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] This invention provides a method for detecting handbrake malfunctions on electric bicycles, an electric bicycle, and a storage medium. When the real-time braking distance changes from small to large, the method determines the time point when the real-time braking distance equals a first preset threshold, acquires the speed of the electric bicycle at the initial time point, and collects braking distance node values ​​within a first preset time period starting from the initial time point at preset time intervals to obtain a first braking distance dataset. Elements that satisfy the condition that the difference between the braking distance node value and the maximum braking distance is less than a second preset threshold are used as a second braking distance dataset. This determines the time interval between the initial time point and the minimum time point, and acquires the speed of the electric bicycle at the minimum time point, thereby determining the average acceleration within the time period, and thus determining whether the handbrake is currently malfunctioning.

[0041] This application boasts high detection efficiency and the ability to accurately reflect whether the brakes are malfunctioning. Specifically, this application determines the corresponding acceleration change by measuring the speed change during braking, and judges whether the brakes are malfunctioning by comparing the average acceleration with the acceleration threshold under ideal conditions. It features high detection efficiency, utilizes real braking data generated during the user's actual riding process (non-stationary state) for detection, and has high authenticity and reliability. Furthermore, it reflects the change in braking distance by measuring the angle change between the brake lever and the motorcycle handlebars, resulting in high accuracy. Converting braking distance (distance value) into angle value enables the quantification of braking distance, thereby improving the accuracy of the final detection result. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of a process in one embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the detection principle in one embodiment of the present invention.

[0045] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings.

[0046] Explanation of icon numbers:

[0047] 100. Motorcycle handlebars; 200. Brake levers. Detailed Implementation

[0048] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0050] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0051] Furthermore, the use of terms such as "first" and "second" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. If the combination of technical solutions is contradictory or impossible to implement, such a combination should be considered non-existent and not within the scope of protection claimed by this invention.

[0052] Please see Figures 1 to 2 An embodiment of the present invention provides a method for detecting a faulty handbrake on an electric bicycle, comprising the following steps:

[0053] S1, acquire the real-time status information of the electric bicycle, and when the electric bicycle is in motion, acquire the maximum braking stroke of the handbrake under ideal conditions. It is worth noting that this application provides a method for detecting brake failure in a moving (non-stationary) electric bicycle. Specifically, the electric bicycle can be determined to be in motion by acquiring the motor's output current value, which is greater than a preset threshold, or by acquiring the electric bicycle's real-time speed. It is also worth noting that the braking stroke value referred to in this application is the position change value of the brake lever 200. Specifically, electric bicycles currently generally use mechanical handbrakes; see the appendix for details. Figure 2 In the structural configuration shown, the brake lever 200 is hinged to the handlebars 100 of the electric bicycle. When the user is not braking, the distance between the brake lever 200 and the handlebars 100 is the farthest. When the user fully presses down the brake, the distance between the brake lever 200 and the handlebars 100 is the shortest. Correspondingly, the positional change of the brake lever 200 is the braking stroke of the electric bicycle as referred to in this application. Furthermore, the state of not pressing the brake lever 200 can be regarded as the state of zero braking stroke, and the state of fully pressing down the brake can be regarded as the state of maximum braking stroke.

[0054] As a preferred implementation, the step S1 of obtaining the maximum braking stroke of the current handbrake under ideal conditions specifically includes the following steps: ideal conditions refer to the electric bicycle being in a normal state, which serves as a reference for whether there is a malfunction in the electric bicycle's brakes.

[0055] Under ideal conditions, the angle θ1 between the brake lever 200 and the motorcycle handlebar 100 is obtained when the brake lever 200 is furthest from the motorcycle handlebar 100; and the angle θ2 between the brake lever 200 and the motorcycle handlebar 100 is obtained when the brake lever 200 is closest to the motorcycle handlebar 100; the angle difference between the angles θ1 and θ2 is determined. and the angle difference This represents the maximum braking stroke of the electric bicycle under ideal conditions.

[0056] To fully illustrate the technical solution of this embodiment, please refer again to the appendix. Figure 2 L1 is the axis of the motorcycle handlebar 100, L2 is the parallel line offset from L1 to the hinge center of the brake lever 200, L3 is the straight line indicating the extension direction of the brake lever 200 when it is closest to the motorcycle handlebar 100 in an ideal state, L5 is the straight line indicating the extension direction of the brake lever 200 when it is furthest from the motorcycle handlebar 100 in an ideal state, and L4 is the straight line indicating the extension direction of the brake lever 200 after the brake is pressed at a certain time point.

[0057] It is worth noting that the motorcycle handlebars 100 and brake lever 200 form an "open triangle" with only two sides in space, that is, L3 to L5 and L2 form a triangle with an opening on the left. In this case, it is impossible to specifically quantify the braking stroke (the swing arc length of the brake lever 200 around the hinge fulcrum). Therefore, in this application, the braking stroke is reflected by determining the included angle between L3 to L5 and L2 and L2.

[0058] In an ideal state, the motorcycle's brakes are in normal operation. At this point, by determining the angle θ1 between the brake lever 200 and the handlebars 100 when the brake lever 200 is furthest from the handlebars 100 in this ideal state (corresponding to the angles L2 and L5), and by obtaining the angle θ2 between the brake lever 200 and the handlebars 100 when the brake lever 200 is closest to the handlebars 100 (corresponding to the angles L3 and L5), the maximum angle the brake lever 200 can swing in an ideal state can be obtained, i.e., the angle difference between angles θ1 and θ2.

[0059] S2, determine the real-time braking distance of the current handbrake, and determine whether the real-time braking distance is changing from small to large. It should be noted that if the real-time braking distance is changing from small to large, it indicates that the user is performing a braking operation. This application aims to detect and analyze whether there is a brake malfunction by observing the user's braking operation. Conversely, if the real-time braking distance is changing from large to small, it indicates that the user is releasing the brake, which is meaningless and not within the scope of this application.

[0060] In a preferred embodiment, step S2, determining the real-time braking distance of the current handbrake, specifically includes the following steps:

[0061] The angle sensor detects the real-time angle θ3 between the current handbrake lever 200 and the motorcycle handlebar 100; the angle difference between the angle θ1 and the real-time angle θ3 is determined. and the angle difference This refers to the real-time braking stroke of the current handbrake.

[0062] Similarly, during the ride, the user obtains the real-time angle θ3 between the current handbrake lever 200 and the handlebars 100 of the electric bicycle through the angle sensor, which corresponds to the angle between L4 and L5, and determines the angle difference between the angle θ1 and the real-time angle θ3. and the angle difference The real-time braking distance of the current handbrake is defined as the angle of rotation of the brake lever 200 in real time. This ensures that the real-time braking distance accurately reflects the current braking distance of the motorcycle's handbrake.

[0063] S3, when the real-time braking stroke changes from small to large, determine the time point when the real-time braking stroke equals a first preset threshold, and use this time point as the initial time point; as a preferred example, the first preset threshold can be set to 10% of the maximum braking stroke or other values. For example, if it is set to 100% of the maximum braking stroke, if the braking stroke reaches this value, it indicates that a braking operation is being performed. This step can prevent the brake lever 200 from making small-range movements due to user accidental contact or other external factors.

[0064] S4, obtain the speed V1 of the electric bicycle at the initial time node, and collect the braking stroke node values ​​within a first preset time period after the initial time node according to the preset time interval to obtain the first braking stroke dataset; wherein, each element in the first braking stroke dataset includes a time node and the braking stroke node value corresponding to the time node; for example, if the travel of the brake lever 200 reaches the first preset threshold at time t1, the braking stroke value at time t1 and the braking stroke value corresponding to time t1 are recorded. The first braking stroke dataset includes each time node and the braking stroke value corresponding to each time node. Since the braking process is generally completed in a short time, the preset time interval can be determined according to the total time of the entire braking process.

[0065] S5, determine whether the brake stroke dataset contains elements whose difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold. If so, use the elements whose difference between the brake stroke node value and the maximum brake stroke value is less than the second preset threshold as the second brake stroke dataset, and determine the minimum time node from the second brake stroke dataset. It should be noted that determining whether the brake stroke dataset contains elements whose difference between the brake stroke node value and the maximum brake stroke value is less than the second preset threshold is to detect whether the current braking operation is a relatively urgent / significantly large braking operation. This situation can better reflect the change in the speed of the electric bicycle caused by the braking operation (i.e., acceleration value). Specifically, if so, it means that a significantly large braking operation is being performed at this time; if not, it means that this operation is a slight braking and can be ignored.

[0066] In addition, the second preset threshold can be converted into a ratio of 10%, that is, when the difference between the brake stroke node value and the maximum stroke value is 10%, it indicates that the operation is a significantly large braking operation. The minimum time node is the time node within the first preset time period when the difference between the stroke node value and the maximum brake stroke value is less than the time corresponding to the second preset threshold.

[0067] S6, determine the time interval t between the initial time node and the minimum time node, and obtain the speed V2 of the electric bicycle at the minimum time node; the time interval t is the difference between the minimum time node and the initial time node.

[0068] S7, determine the average acceleration of the electric bicycle within the time interval t based on vehicle speeds V1 and V2 and the time interval t, and determine whether the current handbrake is in a faulty state based on the average acceleration and an acceleration threshold. Further, step S7, determining the average acceleration of the electric bicycle within the time interval t based on vehicle speeds V1 and V2 and the time interval t, specifically includes the following steps: using a formula based on vehicle speeds V1 and V2 and the time interval t... The average acceleration a of the electric bicycle during the time period t is obtained.

[0069] This application features high detection efficiency and the ability to accurately reflect whether the brakes are in a faulty state. Specifically, this application determines the corresponding acceleration change by measuring the speed change during braking, and judges whether the brakes are in a faulty state by comparing the average acceleration with the acceleration threshold under ideal conditions. It has high detection efficiency, and uses real braking data generated during the user's actual riding process (non-stationary state) for detection, thus having high authenticity and reliability. By reflecting the change in braking distance by the angle change between the brake lever 200 and the motorcycle handlebars 100, it has high accuracy. Converting the braking distance (distance value) into an angle value enables the quantification of the braking distance, thereby improving the accuracy of the final detection result.

[0070] In a preferred embodiment, step S7, which determines whether the current handbrake is in a fault state based on the average acceleration and the acceleration threshold, specifically includes the following steps:

[0071] Determine the difference between the average acceleration and the acceleration threshold; wherein, the acceleration threshold can be obtained by calculating the acceleration value corresponding to the vehicle speed change from the initial time point to the minimum time point under ideal conditions (when braking is normal). By comparing the magnitudes of these two accelerations, it can be determined whether the brakes are in a faulty state. Specifically:

[0072] When the difference is less than or equal to a third preset threshold, the current handbrake is determined to be in an over-tight fault state. This indicates that in this situation, the brake is too tight, and when the user performs the braking operation, the vehicle speed changes significantly, resulting in a large acceleration value. It should be noted that acceleration is a vector quantity with direction. For example, the rated speed of a typical electric bicycle is generally set at 25 km / h. If it decreases to 5 km / h within 0.5 seconds, the corresponding acceleration is: The ideal acceleration threshold is set to -9 to -511.1 m / s². A comparison shows that the average acceleration is significantly less than this threshold. The same logic applies to other cases.

[0073] When the difference is greater than or equal to a fourth preset threshold, the current handbrake is determined to be in a fault state of being too loose; wherein, the fourth preset threshold is greater than the third preset threshold;

[0074] When the difference is greater than the third preset threshold and less than the fourth preset threshold, the current handbrake is determined to be in a normal state.

[0075] In a preferred embodiment, after determining that the current handbrake is in an overly tight fault state, the step further includes the following step:

[0076] Within a second preset time period after the moment when the current handbrake is determined to be in an overly tight fault state, the number of times n is determined to be in an overly tight fault state is counted, and it is determined whether the number n is greater than a first preset number; the first preset number may need to be set by those skilled in the art, for example, the first preset number is set to 2 times; when the number n is greater than the first preset number, the electric bicycle corresponding to the current handbrake is marked as a faulty vehicle; respond to the user's locking command, obtain the return location of the electric bicycle, and send a first maintenance command to the selected maintenance personnel according to the return location.

[0077] As another preferred embodiment, after determining that the current handbrake is in a fault state of being too loose, the step further includes the following step:

[0078] Within a third preset time period after the moment when the current handbrake is determined to be in an overly loose fault state, the number of times m is determined to be in an overly loose fault state is counted, and it is determined whether the number m is greater than a second preset number; if the number m is greater than the second preset number, the electric bicycle corresponding to the current handbrake is marked as a faulty vehicle; respond to the user's locking command, obtain the return location of the electric bicycle, and send a second maintenance command to the selected maintenance personnel according to the return location.

[0079] It should be noted that if the number of times the current handbrake is determined to be in a faulty state, m, is greater than the second preset number, for example, if the second preset number is set to 3 times, the corresponding electric bicycle can be determined to be a faulty vehicle, and the current handbrake is in a faulty state of being too loose. Furthermore, when the user's locking command is received (e.g. when the helmet is successfully returned), the location of the electric bicycle is obtained at that moment.

[0080] As a preferred example, the selection of maintenance personnel can be achieved through the following steps:

[0081] Based on the vehicle return location, obtain the locations of multiple candidate maintenance personnel within a preset range from the vehicle return location, and obtain the current maintenance workload of each candidate maintenance personnel; wherein, the preset range can be set according to actual needs, for example, within a 2km range.

[0082] The selected maintenance personnel are determined from among the multiple candidate maintenance personnel who are closest to the vehicle return location and whose current maintenance workload is less than a preset value.

[0083] If there are multiple candidate maintenance personnel who are closest to the vehicle return location and whose current maintenance workload is less than the preset value, then one of the candidate maintenance personnel is randomly selected as the selected maintenance personnel.

[0084] This example provides a specific method for selecting the selected maintenance personnel. By obtaining the current return location of the electric bicycle and the personnel locations of multiple candidate maintenance personnel, and taking into account the current maintenance workload of each candidate maintenance personnel, the best maintenance personnel are selected to achieve a reasonable, fast and efficient arrangement.

[0085] The first maintenance instruction / second maintenance instruction can be to send the return location and fault type of the electric bicycle to the selected maintenance personnel.

[0086] Furthermore, after determining in step S5 whether there are elements in the brake stroke dataset that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold, the method further includes the step of: if there are no elements in the brake stroke dataset that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than the second preset threshold, then return to step S2. This indicates that in this case, the brake stroke generated by the user pressing the brake lever 200 did not reach the preset position; that is, the user may have lightly pressed the brake lever 200. In this situation, there is generally no obvious safety hazard. Therefore, in this case, it is sufficient to directly return to step S2 to obtain new data.

[0087] This invention provides an electric bicycle, including a vehicle body, which includes a brake lever 200 and a handlebar 100. It also includes an angle sensor and a control system disposed within the vehicle body. The angle sensor detects the angle between the brake lever 200 and the handlebar 100. The angle sensor is connected to the control system. The control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the electric bicycle handbrake fault detection method described above.

[0088] Specifically, an angle sensor is a sensor that can sense the angle being measured and convert it into a usable output signal. The angle sensor has a hole in its body that allows it to engage with a LEGO axle. When connected to the RCX, the angle sensor counts once for every 1 / 16th of a revolution of the axle. The count increases when rotating in one direction and decreases when the direction of rotation changes. The count is related to the initial position of the angle sensor. When the angle sensor is initialized, its count value is set to 0. Therefore, the angle sensor can be placed on the brake lever 200, and the brake lever 200 can theoretically (but in practice, it generally cannot coincide with the motorcycle handlebar 100) be rotated to a position parallel to the motorcycle handlebar 100, for example, as shown in the attached image. Figure 2 When the line L2 is in the middle, the angle at this time is set to 0.

[0089] The present invention also provides a storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method for detecting a handbrake fault in a motorcycle. It is understood that, since the above-described method for detecting a handbrake fault in a motorcycle is implemented when executed by the processor, all embodiments of the above method are applicable to this storage medium and can achieve the same or similar beneficial effects.

[0090] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for detecting handbrake malfunctions in electric bicycles, characterized in that, Including the following steps: S1, obtain the real-time status information of the electric bicycle, and when the electric bicycle is in motion, obtain the maximum braking stroke of the handbrake under ideal conditions; S2, determine the real-time braking stroke of the current handbrake, and determine whether the real-time braking stroke is changing from small to large; S3, when the real-time braking stroke changes from small to large, determine the time node when the real-time braking stroke is equal to the first preset threshold, and use the time node as the initial time node; S4, Obtain the speed of the electric bicycle at the initial time node. The system collects brake stroke node values ​​within a first preset duration starting from the initial time node at preset time intervals to obtain a first brake stroke dataset; wherein, each element in the first brake stroke dataset includes a time node and the brake stroke node value corresponding to the time node; S5, determine whether there are elements in the first brake stroke dataset that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold. If so, take the elements that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than the second preset threshold as the second brake stroke dataset, and determine the minimum time node from the second brake stroke dataset. S6, determine the time interval t between the initial time node and the minimum time node, and obtain the speed of the electric bicycle at the minimum time node. ; S7, based on vehicle speed and vehicle speed The time interval t determines the average acceleration of the electric bicycle within the time interval t, and the current handbrake is determined to be in a fault state based on the average acceleration and the acceleration threshold.

2. The method for detecting electric bicycle handbrake malfunctions according to claim 1, characterized in that, Step S7, which determines whether the current handbrake is in a faulty state based on the average acceleration and acceleration threshold, specifically includes the following steps: Determine the difference between the average acceleration and the acceleration threshold; When the difference is less than or equal to a third preset threshold, the current handbrake is determined to be in an overly tight fault state. When the difference is greater than or equal to a fourth preset threshold, the current handbrake is determined to be in a fault state of being too loose; wherein, the fourth preset threshold is greater than the third preset threshold; When the difference is greater than the third preset threshold and less than the fourth preset threshold, the current handbrake is determined to be in a normal state.

3. The method for detecting electric bicycle handbrake malfunctions according to claim 2, characterized in that, In step S7, based on vehicle speed and vehicle speed The determination of the average acceleration of the electric bicycle within the time interval t specifically includes the following steps: According to vehicle speed and vehicle speed And the time interval t is expressed by the formula The average acceleration a of the electric bicycle during the time period t is obtained.

4. The method for detecting handbrake malfunctions on electric bicycles according to claim 2, characterized in that, The step S1 of obtaining the maximum braking distance of the handbrake under ideal conditions specifically includes the following steps: Under ideal conditions, the angle between the brake lever and the motorcycle handlebars when the current handbrake lever is furthest from the handlebars is obtained. ; and obtain the angle between the brake lever and the motorcycle handlebars when the current handbrake lever is closest to the motorcycle handlebars. ; Determine the included angle and the included angle The angle difference between and the angle difference This represents the maximum braking stroke of the electric bicycle under ideal conditions.

5. The method for detecting electric bicycle handbrake malfunctions according to claim 4, characterized in that, Determining the real-time braking distance of the current handbrake in step S2 specifically includes the following steps: The angle sensor detects the real-time angle between the current handbrake lever and the motorcycle handlebars. ; Determine the included angle and the real-time angle angular difference and the angle difference This refers to the real-time braking stroke of the current handbrake.

6. The method for detecting handbrake malfunctions on electric bicycles according to claim 2, characterized in that, After determining that the current handbrake is in an overly tight fault state, the step further includes the following steps: Within a second preset time period after the moment when the current handbrake is determined to be in an over-tight fault state, the number of times n is determined to be in an over-tight fault state is counted, and it is determined whether the number n is greater than a first preset number. When the number of times n is greater than the first preset number of times, the electric bicycle corresponding to the current handbrake is marked as a faulty vehicle; Responding to the user's lock command and obtaining the return location of the electric bicycle, a first maintenance command is sent to the selected maintenance personnel based on the return location.

7. The method for detecting electric bicycle handbrake malfunctions according to claim 2, characterized in that, After determining that the current handbrake is in a faulty state of being too loose, the step further includes the following steps: Within a third preset time period after the moment when the current handbrake is determined to be in an overly loose fault state, the number of times m is determined to be in an overly loose fault state is counted, and it is determined whether the number m is greater than a second preset number. When the number of times m is greater than the second preset number of times, the electric bicycle corresponding to the current handbrake is marked as a faulty vehicle; Responding to the user's lock command and obtaining the return location of the electric bicycle, a second maintenance command is sent to the selected maintenance personnel based on the return location.

8. The method for detecting handbrake malfunctions on electric bicycles according to claim 1, characterized in that, After determining whether the first brake stroke dataset contains elements that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than a second preset threshold in step S5, the following step is also included: If there are no elements in the first brake stroke dataset that satisfy the condition that the difference between the brake stroke node value and the maximum brake stroke value is less than the second preset threshold, return to step S2.

9. An electric bicycle, comprising a frame, the frame including a brake lever and a handlebar, characterized in that, It also includes an angle sensor and a control system disposed in the vehicle body. The angle sensor is used to detect the angle between the brake lever and the handlebars of the motorcycle. The angle sensor is connected to the control system. The control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the motorcycle handbrake fault detection method as described in any one of claims 1 to 8.

10. A storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the electric bicycle handbrake fault detection method as described in any one of claims 1 to 8.

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