Electric vehicle control method based on variable-speed flywheel, variable-speed flywheel and storage medium

Abstract

The invention relates to an electric vehicle control method based on a variable-speed flywheel, the variable-speed flywheel and a storage medium, and relates to the technical field of electric bicycles. The riding environment parameters and the real-time bearing weight of the electric bicycle are obtained based on the riding trigger signal; the riding environment parameters and the real-time bearing weight are analyzed to determine actual assistance parameters and actual flywheel parameters; and the electric bicycle is adjusted and controlled according to the actual assistance parameters and the actual flywheel parameters. The power assisting device has the effect of improving the power assisting adjusting efficiency of the electric bicycle.

Description

Technical Field

[0001] The present application relates to the field of electric bicycle technology, and in particular to an electric bicycle control method based on a variable speed flywheel, a variable speed flywheel and a storage medium. Background Art

[0002] An electric bicycle is a bicycle that integrates an electric power-assist system. This type of bicycle is usually equipped with a motor, a battery, and a speed controller, which can provide additional power support when the rider pedals, thereby reducing the rider's physical exertion and making long-distance riding or climbing easier.

[0003] In the related art, electric bicycles are usually provided with power-assistance levels, such as off mode, low power-assistance mode, medium power-assistance mode, high power-assistance mode and walking mode. At the same time, a variable-speed flywheel is installed on the electric bicycle to control the speed of the electric bicycle. There are special buttons on the controller of the electric bicycle. Riders can switch between different power-assistance levels and variable-speed flywheels with different numbers of teeth by pressing these buttons, so that the electric bicycle can assist the rider's riding according to the rider's needs.

[0004] With respect to the above-mentioned related technologies, when a rider uses an electric bicycle, due to changes in the riding environment, the original power assist level and the speed flywheel cannot satisfy the rider's best riding experience in different riding environments. Therefore, the rider needs to constantly adjust the power assist level and the speed flywheel, and determine the current best power assist level and speed flywheel based on the rider's own feelings. This results in low power assist adjustment efficiency of electric bicycles, and there is still room for improvement. Summary of the invention

[0005] In order to improve the power-assistance adjustment efficiency of an electric bicycle, the present application provides an electric bicycle control method based on a variable-speed flywheel, a variable-speed flywheel and a storage medium.

[0006] In the first aspect, the present application provides a control method for an electric vehicle based on a variable speed flywheel, which adopts the following technical solution: A tram control method based on a variable speed flywheel, comprising: Obtain riding trigger signal of electric bicycle; Acquire riding environment parameters and real-time load weight of the electric bicycle based on the riding trigger signal; Analyze riding environment parameters and real-time load weight to determine actual power assist parameters and actual flywheel parameters; The electric bicycle is adjusted and controlled according to actual power-assist parameters and actual flywheel parameters.

[0007] By adopting the above technical solution, when a rider uses an electric bicycle, the actual flywheel parameters and the actual power-assistance parameters are determined according to the riding environment parameters and the real-time load weight, so that the power-assistance level and the variable-speed flywheel of the electric bicycle can adapt to different environments and riders, so that the rider can have a better riding experience no matter what environment he rides in, without the need for the rider to frequently adjust the power-assistance level and the variable-speed flywheel, thereby improving the power-assistance adjustment efficiency of the electric bicycle.

[0008] Optionally, the step of obtaining riding environment parameters and real-time load weight of the electric bicycle based on the riding trigger signal includes: Acquire the real-time moving position of the electric bicycle based on the riding trigger signal; Determine whether the real-time mobile position meets the requirements of the preset environment map position; If it is in compliance, the riding environment parameters are determined according to the relationship between the real-time mobile position and the preset position environment; If it does not meet the requirements, the moving position image and the position fluctuation angle are obtained; Performing image analysis on the mobile location image to determine the mobile location road condition, and correlating the mobile location road condition and the location undulation angle to generate riding environment parameters; The preset weight detection device is controlled according to the riding environment parameters to detect the rider to generate the real-time bearing weight.

[0009] By adopting the above technical solution, when it is determined that the real-time moving position meets the requirements of the environmental map position, it means that the environmental parameters at the real-time moving position have been recorded and can be directly called. When it does not meet the requirements, the road conditions and position fluctuation angles of the moving position are detected to obtain the riding environment parameters, and finally the real-time carrying weight is obtained according to the riding environment parameters, thereby improving the convenience of obtaining the riding environment parameters and the accuracy of obtaining the real-time carrying weight.

[0010] Optionally, the step of controlling a preset weight detection device to detect the rider according to the riding environment parameters to generate a real-time bearing weight includes: Controlling the weight detection device to detect the rider to generate a basic bearing weight; Analyze riding environment parameters to determine real-time riding angle; Determine whether the real-time riding angle meets the preset zero-force angle requirement; If it meets the requirements, the basic bearing weight is defined as the real-time bearing weight; If not, the real-time riding angle and basic load-bearing weight are analyzed to determine the real-time load-bearing weight.

[0011] By adopting the above technical solution, when the real-time riding angle meets the requirement of the zero-force angle, it indicates that the electric bicycle is ridden on a horizontal plane, and the basic load-bearing weight at this time is the real-time load-bearing weight. If it does not meet the requirement, it indicates that the electric bicycle is ridden on a slope. Therefore, the real-time load-bearing weight is obtained based on the real-time riding angle and the basic load-bearing weight, thereby improving the accuracy of obtaining the real-time load-bearing weight.

[0012] Optionally, the step of obtaining the real-time moving position of the electric bicycle based on the riding trigger signal includes: Acquire the basic positioning position of the electric bicycle based on the riding trigger signal; Determine whether the basic positioning position meets the requirements of the preset riding overlap position; If it does not match, the basic positioning position is defined as the real-time moving position; If it meets the requirements, the positioning position image is obtained; Determine a reference position image according to a relationship between a basic positioning position and a preset position image; The positioning position image and the reference position image are analyzed to determine the real-time moving position.

[0013] By adopting the above technical solution, when it is determined that the basic positioning position meets the requirements of the riding overlapping position, it indicates that there is an overlapping road at the location of the electric bicycle, such as an elevated road. Therefore, it is necessary to compare the positioning position image with the reference position image to determine the real-time moving position, thereby improving the accuracy of determining the real-time moving position.

[0014] Optionally, the step of analyzing the riding environment parameters and the real-time load weight to determine the actual power assist parameters and the actual flywheel parameters includes: Determine whether the riding environment parameters meet the requirements of the preset power-assisting environment parameters; If not, the preset non-assistance parameter is defined as the actual assistance parameter, and the first real-time moving speed is obtained; Analyzing the first real-time moving speed and the riding environment parameters to determine actual flywheel parameters of the preset speed-changing flywheel; If it meets the requirements, the basic power-assistance parameters are determined according to the real-time load-bearing weight and the preset weight-assistance relationship; The basic power assist parameters and riding environment parameters are analyzed to determine the actual power assist parameters and the actual flywheel parameters of the preset speed-changing flywheel.

[0015] By adopting the above technical solution, when it is determined that the riding environment parameters meet the requirements of the power-assisting environment parameters, the basic power-assisting parameters are determined according to the real-time load weight, and then the actual power-assisting parameters and the actual flywheel parameters are determined according to the basic power-assisting parameters and the riding environment parameters, thereby improving the convenience of determining the actual power-assisting parameters and the actual flywheel parameters.

[0016] Optionally, the step of analyzing the basic power-assisting parameters and the riding environment parameters to determine the actual power-assisting parameters and the actual flywheel parameters of the preset speed-changing flywheel includes: Get real-time weather data; Determine whether the real-time meteorological data meets the preset requirements of abnormal meteorological data; If it is in compliance, the actual power assist parameters and actual flywheel parameters are determined according to the preset complex road condition trigger signal; If not, the basic power-assistance parameters and riding environment parameters are analyzed to determine the actual power-assistance parameters and obtain the second real-time moving speed; The second real-time moving speed and riding environment parameters are analyzed to determine actual flywheel parameters.

[0017] By adopting the above technical solution, when it is determined that the real-time meteorological data does not meet the requirements of abnormal meteorological data, it indicates that the detected riding environment parameters will not change. Therefore, the basic power assist parameters and riding environment parameters are analyzed to determine the actual power assist parameters, and the actual flywheel parameters are determined based on the second real-time moving speed and the riding environment parameters, thereby improving the accuracy of determining the actual power assist parameters and the actual flywheel parameters.

[0018] Optionally, the step of determining the actual power assist parameter and the actual flywheel parameter according to the preset complex road condition trigger signal includes: Define the preset maximum number of flywheel teeth as the actual flywheel parameter; Analyze riding environment parameters to determine real-time moving road conditions; Determine the change of road condition according to the real-time moving road condition and the preset relationship between road condition changes; Determining whether the road condition change is a preset muddy road condition or a preset slippery road condition; If the road condition is slippery, the preset non-assistance parameter is defined as the actual assistance parameter; If the road condition is muddy, the additional resistance to movement is obtained, and the actual power assistance parameter is determined according to the additional resistance to movement.

[0019] By adopting the above technical solution, when it is determined that the real-time meteorological data meets the requirements of abnormal meteorological data, it indicates that the road conditions of the riding environment parameters will change. At this time, when it is determined that the road condition change is a slippery road condition, it is determined that there is no power assistance; when it is determined that the road condition change is a muddy road condition, the actual power assistance parameters are determined based on the additional resistance to movement, thereby improving the accuracy of determining the actual power assistance parameters.

[0020] In a second aspect, the present application provides a variable speed flywheel, which adopts the following technical solution: A variable speed flywheel comprises an outer sleeve, a flywheel sheet and a locking ring, wherein a plurality of flywheel sheets are provided, and the flywheel sheets are evenly spaced and sleeved on the outer sleeve, and the flywheel sheets and the outer sleeve abut against each other in a circumferential direction; The locking ring is arranged at one end of the outer sleeve, and a locking opening is opened on the outer sleeve for the locking ring to be inserted and fixed. The locking ring is inserted into the locking opening and abuts against the flywheel plate. A limiting ring is arranged on the end of the outer sleeve away from the locking ring, and the limiting ring abuts against the flywheel plate. The outer diameter of the flywheel plate gradually increases along the direction from the locking ring to the limiting ring.

[0021] By adopting the above technical solution, after the flywheel piece is sequentially mounted on the outer sleeve, the locking ring and the limiting ring limit the flywheel piece on the outer sleeve, thereby improving the stability of the connection between the flywheel piece and the outer sleeve.

[0022] Optionally, eight flywheels are provided, and the number of teeth of the flywheels along the direction from the locking ring to the limiting ring is set to 10 teeth, 13 teeth, 15 teeth, 17 teeth, 19 teeth, 21 teeth, 24 teeth and 28 teeth respectively.

[0023] By adopting the above technical solution, the minimum number of teeth of the flywheel is set to 10 teeth, which improves the speed ratio compared with the general minimum number of teeth.

[0024] In a third aspect, the present application provides a computer storage medium capable of storing corresponding programs, which has the characteristics of being convenient for improving the power-assistance adjustment efficiency of electric bicycles, and adopts the following technical solutions: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned electric vehicle control methods based on a variable speed flywheel.

[0025] By adopting the above technical solution, a computer program of an electric vehicle control method based on a variable-speed flywheel is stored in a computer-readable storage medium, so that a processor loads and executes the computer program in the storage medium, thereby determining actual flywheel parameters and actual power-assist parameters according to riding environment parameters and real-time load weight, so that the power-assist level and the variable-speed flywheel of the electric bicycle can adapt to different environments and riders, so that the rider can have a better riding experience no matter what environment he rides in, without the need for the rider to frequently adjust the power-assist level and the variable-speed flywheel, thereby improving the power-assist adjustment efficiency of the electric bicycle.

[0026] In summary, the present application includes at least one of the following beneficial technical effects: By determining the actual flywheel parameters and the actual power-assist parameters according to the riding environment parameters and the real-time load weight when the rider is using the electric bicycle, the power-assist level and the variable-speed flywheel of the electric bicycle can adapt to different environments and riders, so that the rider can have a good riding experience no matter what environment he rides in, without the rider having to frequently adjust the power-assist level and the variable-speed flywheel, thereby improving the power-assist adjustment efficiency of the electric bicycle; When it is determined that the real-time moving position meets the requirements of the environmental map position, it indicates that the environmental parameters at the real-time moving position have been recorded and can be directly called. When it does not meet the requirements, the road conditions and the position fluctuation angle of the moving position are detected to obtain the riding environment parameters, and finally the real-time carrying weight is obtained according to the riding environment parameters, thereby improving the convenience of obtaining the riding environment parameters and the accuracy of obtaining the real-time carrying weight. When it is determined that the basic positioning position meets the requirements of the riding overlapping position, it means that there is an overlapping road at the location of the electric bicycle, such as an elevated road. Therefore, it is necessary to compare the positioning position image with the reference position image to determine the real-time moving position, thereby improving the accuracy of determining the real-time moving position. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the electric vehicle control method based on the variable speed flywheel in the embodiment of the present application.

[0028] Figure 2 It is a flowchart of the steps of obtaining riding environment parameters and real-time load-bearing weight of an electric bicycle based on a riding trigger signal in an embodiment of the present application.

[0029] Figure 3 It is a flowchart of the steps of controlling a preset weight detection device to detect a rider according to riding environment parameters in an embodiment of the present application to generate a real-time load-bearing weight.

[0030] Figure 4 It is a flowchart of the steps of obtaining the real-time moving position of an electric bicycle based on a riding trigger signal in an embodiment of the present application.

[0031] Figure 5 It is a flowchart of the steps of analyzing the riding environment parameters and the real-time load weight in an embodiment of the present application to determine the actual power assist parameters and the actual flywheel parameters.

[0032] Figure 6 It is a flowchart of the steps of analyzing the basic power assist parameters and the riding environment parameters in the embodiment of the present application to determine the actual power assist parameters and the actual flywheel parameters of the preset speed-changing flywheel.

[0033] Figure 7It is a flow chart of the steps of determining actual power assist parameters and actual flywheel parameters according to a preset complex road condition trigger signal in an embodiment of the present application.

[0034] Figure 8 It is a schematic diagram of the structure of the variable speed flywheel in the embodiment of the present application.

[0035] Explanation of the reference numerals: 1. outer sleeve; 11. locking opening; 12. limiting ring; 2. flywheel; 3. locking ring. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 8 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0037] The embodiment of the present application discloses a control method for an electric bicycle based on a variable-speed flywheel, and specifically discloses a processing terminal, a sensor device and an electric bicycle. The processing terminal and the sensor device are both installed on the electric bicycle, and the processing terminal is respectively connected to the sensor device and the electric bicycle through a data wire to realize data interaction and control. After the sensor device sends a riding trigger signal of the electric bicycle to the processing terminal, the processing terminal responds to the riding trigger signal, thereby controlling the sensor device to detect the riding environment parameters and the real-time load-bearing weight of the electric bicycle and send them to the processing terminal. The processing terminal analyzes the riding environment parameters and the real-time load-bearing weight and determines the actual power-assisting parameters and the actual flywheel parameters, so that the processing terminal adjusts the motor and the variable-speed flywheel of the electric bicycle according to the actual power-assisting parameters and the actual flywheel parameters, respectively, so that the power-assisting level and the variable-speed flywheel of the electric bicycle can adapt to the use of different riders in different environments, without the need for the rider to repeatedly adjust the power-assisting level and the variable-speed flywheel, thereby improving the power-assisting adjustment efficiency of the electric bicycle.

[0038] Reference Figure 1 The present application embodiment discloses a control method for an electric vehicle based on a variable speed flywheel, comprising the following steps: Step S100: Acquire a riding trigger signal of the electric bicycle.

[0039] Among them, the riding trigger signal refers to the trigger signal that the rider starts to use the electric bicycle. When the force sensitive sensor installed on the electric bicycle detects that the rider is riding on the electric bicycle, the riding trigger signal is sent to the processing terminal.

[0040] Step S101: obtaining riding environment parameters and real-time load-bearing weight of the electric bicycle based on a riding trigger signal.

[0041] Among them, the riding environment parameters refer to the road conditions and road angles of the electric bicycle, and the real-time load weight refers to the weight of the rider. After the processing terminal receives the riding trigger signal, the processing terminal controls the sensor device to detect in response to the riding trigger signal. The specific method is referred to Figure 2 steps.

[0042] Step S102: Analyze the riding environment parameters and the real-time load weight to determine the actual power-assisting parameters and the actual flywheel parameters.

[0043] The actual power-assistance parameter refers to the actual power value when the electric bicycle motor is controlled to assist, and the actual flywheel parameter refers to the actual number of teeth of the flywheel for adjusting the speed, which is determined by the processing terminal after analyzing the riding environment parameters and the real-time load weight. For specific methods, refer to Figure 5 steps.

[0044] Step S103: regulating and controlling the electric bicycle according to the actual power-assisting parameters and the actual flywheel parameters.

[0045] Among them, after the processing terminal obtains the actual power-assisting parameters and the actual flywheel parameters, the processing terminal controls the motor on the electric bicycle to assist the rider in riding according to the output power value corresponding to the actual power-assisting parameters, and at the same time controls the speed-changing device to adjust the speed-changing flywheel to the number of teeth corresponding to the actual flywheel parameters, so that the power-assisting level and the speed-changing flywheel of the electric bicycle are suitable for the current rider to ride in the current environment. The speed-changing device refers to a device that controls the speed-changing flywheel to adjust to different numbers of teeth. In the embodiment of the present application, the speed-changing device is improved on the existing manual speed-changing device, that is, the manual adjustment part is changed to the motor rotation adjustment.

[0046] Reference Figure 2 The steps of obtaining riding environment parameters and real-time load weight of the electric bicycle based on the riding trigger signal include: Step S200: Acquire the real-time moving position of the electric bicycle based on the riding trigger signal.

[0047] The real-time mobile location refers to the specific location of the electric bicycle, which is located by the positioning system installed on the electric bicycle and sent to the processing terminal for analysis. The specific method is as follows Figure 4 steps.

[0048] Step S201: Determine whether the real-time moving position meets the requirements of the preset environment map position.

[0049] The environment map location refers to a location where the environment parameters have been recorded, and the environment map location requirement refers to a location that exists in a location corresponding to the environment map location and is stored in the processing terminal by an operator.

[0050] The processing terminal determines whether the real-time moving position exists in the position corresponding to the environmental map position, thereby determining whether the environmental parameters of the current position of the electric bicycle have been recorded.

[0051] Step S2011: If it is in compliance, the riding environment parameters are determined according to the relationship between the real-time moving position and the preset position environment.

[0052] Among them, if the processing terminal determines that the real-time moving position exists in the position corresponding to the environmental map position, it means that the environmental parameters of the current position of the electric bicycle have been recorded, so the riding environment parameters are determined according to the relationship between the real-time moving position and the position environment.

[0053] The position-environment relationship refers to the correspondence between the position and the environmental parameters. The operator records the environmental parameters at different positions and forms a mapping table by corresponding the positions to the environmental parameters one by one. The riding environment parameters in this step are consistent with the riding environment parameters in step S101, and are obtained by the processing terminal in the mapping table corresponding to the position-environment relationship according to the position corresponding to the real-time mobile position.

[0054] Step S2012: If not, obtain the moving position image and position fluctuation angle.

[0055] Among them, if the processing terminal determines that the real-time moving position does not exist in the position corresponding to the environmental map position, it means that the environmental parameters of the current position of the electric bicycle have not been recorded. Therefore, real-time detection is required to detect the moving position image and position fluctuation angle to provide data support for the subsequent determination of the riding environment parameters.

[0056] The moving position image refers to the front image of the electric bicycle when it is moving, which is taken by the camera installed on the electric bicycle and sent to the processing terminal. The position fluctuation angle refers to the angle of the road surface when the electric bicycle is moving. The fluctuation angle of the electric bicycle is detected by the inertial measurement unit installed on the electric bicycle, which is the angle of the road surface.

[0057] Step S202: performing image analysis on the moving position image to determine the moving position road condition, and generating riding environment parameters by associating the moving position road condition and the position fluctuation angle.

[0058] The mobile position road condition refers to the road condition at the current position of the electric bicycle, including the road surface material and road surface flatness, which is obtained by the processing terminal inputting the mobile position image into a preset road condition recognition model for recognition. The riding environment parameters in this step are consistent with the riding environment parameters in step S101, and the processing terminal stores the road condition information corresponding to the mobile position road condition and the angle corresponding to the position fluctuation angle in the same data packet.

[0059] Step S203: controlling a preset weight detection device to detect the rider according to the riding environment parameters to generate a real-time bearing weight.

[0060] The real-time load-bearing weight in this step is consistent with the real-time load-bearing weight in step S101. After the processing terminal obtains the riding environment parameters, the processing terminal controls the weight detection device to detect the rider according to the riding environment parameters to obtain the real-time load-bearing weight. For specific methods, refer to Figure 3 The weight detection device refers to a device for detecting the weight of the rider, which can be a force-sensitive sensor installed on the seat of the electric bicycle.

[0061] Reference Figure 3 The steps of controlling a preset weight detection device to detect the rider according to the riding environment parameters to generate a real-time load weight include: Step S300: Control the weight detection device to detect the rider to generate a basic bearing weight.

[0062] Among them, the basic load-bearing weight refers to the weight value directly detected on the rider, which is detected by a weight detection device and sent to a processing terminal.

[0063] Step S301: Analyze riding environment parameters to determine a real-time riding angle.

[0064] The real-time riding angle refers to the ups and downs angle of the electric bicycle, which is identified and called by the processing terminal in the riding environment parameters.

[0065] Step S302: Determine whether the real-time riding angle meets the requirement of the preset zero-force angle.

[0066] Among them, the zero-force angle refers to the angle at which the weight of the rider on the electric bicycle will not be divided, that is, zero degrees. The requirement for the zero-force angle refers to being consistent with the zero-force angle, which is stored in the processing terminal by the operator.

[0067] Whether the real-time riding angle is consistent with the angle without force component is determined by the processing terminal, thereby determining whether the weight detected by the weight detection device is the total weight of the rider.

[0068] Step S3021: If it meets the requirements, the basic bearing weight is defined as the real-time bearing weight.

[0069] Among them, if the processing terminal determines that the real-time riding angle is consistent with the angle without force component, it means that the weight of the rider on the electric bicycle is not divided by force, so the basic bearing weight detected by the weight detection device is the real-time bearing weight.

[0070] Step S3022: If not, the real-time riding angle and basic load-bearing weight are analyzed to determine the real-time load-bearing weight.

[0071] Among them, if the processing terminal determines that the real-time riding angle is inconsistent with the angle without force component, it means that the weight of the rider on the electric bicycle is divided. Therefore, it is necessary to determine the real-time bearing weight after analysis based on the real-time riding angle and the basic bearing weight. The specific analysis method is: the basic bearing weight is actually a right-angled side of the right-angled triangle, the real-time bearing weight is the hypotenuse of the right-angled triangle, and the real-time riding angle is the angle between the hypotenuse and the right-angled side. Therefore, the cosine value of the real-time riding angle is calculated, and then the quotient of the basic bearing weight and the cosine value is calculated to obtain the real-time bearing weight.

[0072] Reference Figure 4 ,The steps of obtaining the real-time moving position of the electric bicycle based on the riding trigger signal include: Step S400: obtaining a basic positioning position of the electric bicycle based on the riding trigger signal.

[0073] Among them, the basic positioning position refers to the position of the electric bicycle, which is located by the positioning system on the electric bicycle and sent to the processing terminal.

[0074] Step S401: Determine whether the basic positioning position meets the requirements of the preset riding overlapping position.

[0075] The riding overlap position refers to a position where roads overlap, and the riding overlap position requirement refers to being consistent with the riding overlap position, both of which are stored in the processing terminal by the operator.

[0076] The processing terminal determines whether the basic positioning position is consistent with the riding overlapping position, thereby determining whether there are multiple overlapping roads at the current position of the electric bicycle.

[0077] Step S4011: If not, the basic positioning position is defined as the real-time moving position.

[0078] Among them, if the processing terminal determines that the basic positioning position is inconsistent with the riding overlapping position, it means that there is only one road at the current position of the electric bicycle, so the basic positioning position can be directly defined as the real-time moving position.

[0079] Step S4012: If it is in compliance, obtain the positioning position image.

[0080] Among them, if the processing terminal determines that the basic positioning position is consistent with the riding overlapping position, it means that there are multiple overlapping roads at the current position of the electric bicycle, such as elevated roads. Therefore, the positioning position image is collected to provide data support for the subsequent determination of the specific position.

[0081] The positioning position image refers to an image of the current position of the electric bicycle, which is taken by a camera installed on the electric bicycle and sent to a processing terminal.

[0082] Step S402: determining a reference position image according to the basic positioning position and a preset position image relationship.

[0083] Among them, the position-image relationship refers to the correspondence between the positioning position and the specific position and the specific position image. The positioning position includes multiple specific positions, such as roads at different heights. The operator collects the corresponding specific position images at multiple specific positions, and then forms a mapping table by corresponding the positioning position to the specific position and the specific position image one by one.

[0084] The reference position image refers to a specific position and a specific position image, which is obtained by searching a mapping table corresponding to the position-image relationship by the processing terminal according to the basic positioning position.

[0085] Step S403: Analyze the positioning position image and the reference position image to determine the real-time moving position.

[0086] Among them, the real-time moving position in this step is consistent with the real-time moving position in step S200, and is determined by the processing terminal after analysis based on the positioning position image and the reference position image. The specific analysis method is: if there are two reference position images, including position A and the corresponding a image, position B and the corresponding b image, if the positioning position image is image a, the determined real-time moving position is position A.

[0087] Reference Figure 5 The steps of analyzing the riding environment parameters and the real-time load weight to determine the actual power assist parameters and the actual flywheel parameters include: Step S500: Determine whether the riding environment parameters meet the requirements of the preset power-assisting environment parameters.

[0088] Among them, the power-assisting environment parameters refer to the road angle that requires power-assisting, that is, the angle from zero degrees corresponding to a flat road to the angles corresponding to different uphill roads. The requirements for the power-assisting environment parameters refer to the angle range corresponding to the power-assisting environment parameters, which are all stored in the processing terminal by the operator.

[0089] The processing terminal determines whether the road angle corresponding to the riding environment parameter is within the angle range corresponding to the power-assisting environment parameter, thereby determining whether the electric bicycle needs power assistance at this time.

[0090] Step S501: If not, define the preset non-assisted parameters as actual assisted parameters, and obtain the first real-time moving speed.

[0091] Among them, if the processing terminal determines that the road angle corresponding to the riding environment parameter is not within the angle range corresponding to the power-assisting environment parameter, it means that the electric bicycle is on a downhill road at this time, so no power-assisting is required. The no-power-assisting parameter is defined as the actual power-assisting parameter, and the first real-time moving speed is detected to provide data support for the subsequent determination of the flywheel parameters.

[0092] The unassisted parameter refers to the assisted parameter with zero output power, which is stored in the processing terminal by the operator. The first real-time moving speed refers to the current moving speed of the electric bicycle, which is detected by the speed sensor installed on the electric bicycle and sent to the processing terminal.

[0093] Step S5011: Analyze the first real-time moving speed and the riding environment parameters to determine the actual flywheel parameters of the preset speed-changing flywheel.

[0094] Among them, the actual flywheel parameters in this step are consistent with the actual flywheel parameters in step S102, and are determined by the processing terminal after analysis based on the first real-time moving speed and riding environment parameters. The specific analysis method is: first determine that the road in the riding environment parameters is a downhill road. When on a downhill road, the safety of the rider is given priority. The relationship between speed and the number of flywheel teeth is that the faster the speed, the more flywheel teeth there are, thereby ensuring that when the rider uses the pedals too quickly, the moving speed of the electric bicycle will not be too fast. The corresponding relationship between the moving speed and the number of flywheel teeth is determined by the operator according to actual conditions to form a mapping table. The processing terminal searches the mapping table for the number of flywheel teeth according to the first real-time moving speed, which is the actual flywheel parameter.

[0095] The variable speed flywheel refers to the variable speed flywheel installed on the rear wheel of the electric bicycle. Figure 8 .

[0096] Step S502: If it meets the requirements, the basic assistance parameters are determined according to the real-time load-bearing weight and the preset weight assistance relationship.

[0097] Among them, if the processing terminal determines that the road angle corresponding to the riding environment parameters is within the angle range corresponding to the power-assisting environment parameters, it indicates that the electric bicycle is on a horizontal or uphill road, so the electric bicycle may need power assistance. Therefore, the basic power-assisting parameters are determined according to the real-time load-bearing weight and weight-assisting relationship to provide data support for the subsequent determination of the actual power-assisting parameters.

[0098] The weight-assistance relationship refers to the correspondence between the load-bearing weight and the range of power-assistance parameters under different environments. Under the same environment, the greater the load-bearing weight, the greater the output power corresponding to the power-assistance parameter. The proportional coefficient between the two is determined by the operator according to the actual situation, and the operator forms a database by matching the load-bearing weight with the range of power-assistance parameters under different environments one by one. The basic power-assistance parameter refers to the parameter range for assisting the current rider, including the power-assistance parameters corresponding to roads with different road conditions. For the same road, the worse the road condition, the greater the power-assistance parameter; for different roads, the greater the undulation angle of the road, the greater the power-assistance parameter. The processing terminal searches in the mapping table corresponding to the weight-assistance relationship according to the real-time load-bearing weight.

[0099] Step S5021: Analyze the basic power-assisting parameters and the riding environment parameters to determine the actual power-assisting parameters and the actual flywheel parameters of the preset speed-changing flywheel.

[0100] The actual power-assistance parameters and actual flywheel parameters in this step are consistent with the actual power-assistance parameters and actual flywheel parameters in step S102, and are determined by the processing terminal after analyzing the basic power-assistance parameters and riding environment parameters. For specific methods, refer to Figure 6 The speed-changing flywheel in this step is the same as the speed-changing flywheel in step S5011, and will not be described in detail here.

[0101] Reference Figure 6 The steps of analyzing the basic power assist parameters and the riding environment parameters to determine the actual power assist parameters and the actual flywheel parameters of the preset speed change flywheel include: Step S600: Acquire real-time meteorological data.

[0102] Among them, the real-time meteorological data refers to the weather at the location of the electric bicycle at the moment, which is searched and called by the processing terminal on the meteorological website according to the positioning location.

[0103] Step S601: Determine whether the real-time meteorological data meets the preset requirements of abnormal meteorological data.

[0104] Among them, abnormal meteorological data refers to weather that will cause changes in the road environment, such as rain and snow, and the requirements for abnormal meteorological data refer to the weather that is consistent with the abnormal meteorological data, which are all stored in the processing terminal by the operator.

[0105] The processing terminal determines whether the weather corresponding to the real-time weather data is consistent with the weather corresponding to the abnormal weather data, thereby determining whether the weather at this time will change the road conditions.

[0106] Step S6011: If it is met, the actual power assist parameters and actual flywheel parameters are determined according to the preset complex road condition trigger signal.

[0107] If the processing terminal determines that the weather corresponding to the real-time weather data is consistent with the weather corresponding to the abnormal weather data, it means that the weather at this time will change the road conditions. Therefore, the actual power assist parameters and actual flywheel parameters are determined according to the complex road condition trigger signal. For specific methods, refer to Figure 7 steps.

[0108] The complex road condition trigger signal refers to a signal used by the control processing terminal to determine the power assist parameters and flywheel parameters through complex road condition analysis, and is stored in the processing terminal by the operator.

[0109] Step S6012: If not, the basic power-assisting parameters and the riding environment parameters are analyzed to determine the actual power-assisting parameters and obtain the second real-time moving speed.

[0110] Among them, if the processing terminal determines that the weather corresponding to the real-time meteorological data is inconsistent with the weather corresponding to the abnormal meteorological data, it means that the weather at this time will not change the road conditions. Therefore, the actual power assist parameters are determined after analyzing the basic power assist parameters and riding environment parameters, and the second real-time moving speed is collected to provide data support for the subsequent determination of the flywheel parameters.

[0111] The actual power-assisting parameters in this step are determined by the processing terminal after analyzing the basic power-assisting parameters and the riding environment parameters. The specific analysis method is: the processing terminal searches for the power-assisting parameters in the basic power-assisting parameters according to the road conditions and road angles corresponding to the riding environment parameters. For example, the basic power-assisting parameters include power-assisting parameters corresponding to roads with different road conditions. For the same road, the worse the road conditions, the greater the power-assisting parameters; for different roads, the greater the undulating angle of the road, the greater the power-assisting parameters. If the riding environment parameters are the flat road surface of a horizontal road, the power-assisting parameters are smaller. If the riding environment parameters are the bumpy road surface of the maximum uphill road, the power-assisting parameters are larger. The second real-time moving speed refers to the moving speed of the electric bicycle, which is detected by the speed sensor installed on the electric bicycle and sent to the processing terminal.

[0112] Step S602: Analyze the second real-time moving speed and riding environment parameters to determine actual flywheel parameters.

[0113] Among them, the actual flywheel parameters in this step are determined by the processing terminal after analysis based on the second real-time moving speed and the riding environment parameters. The specific analysis method is: first determine the road angle in the riding environment parameters. The larger the road angle, the more difficult it is for the electric bicycle to go uphill. At this time, as the angle increases, the number of flywheel teeth increases, thereby reducing the difficulty for the rider to use the pedals; if the road angle is zero degrees, it indicates that the road is a horizontal road. At this time, analysis is performed based on the second real-time moving speed. The smaller the second real-time moving speed, the more the electric bicycle has just started. At this time, the speed is proportional to the number of flywheel teeth, that is, the smaller the speed, the fewer the number of flywheel teeth, ensuring that the electric bicycle starts quickly. The proportional coefficient between the two is determined by the operator according to actual conditions.

[0114] Reference Figure 7 The steps of determining the actual power assist parameters and the actual flywheel parameters according to the preset complex road condition trigger signal include: Step S700: defining a preset maximum number of flywheel teeth as an actual flywheel parameter.

[0115] Among them, the actual flywheel parameter in this step is the maximum number of teeth on the flywheel. Because the weather makes the road conditions more complicated, it is necessary to ensure the safety of the rider. At this time, it is not easy to ride at too fast a speed. Therefore, the maximum number of teeth on the flywheel is used as the actual flywheel parameter to ensure that the speed of the electric bicycle is not too fast.

[0116] Step S701: Analyze riding environment parameters to determine real-time moving road conditions.

[0117] Among them, the real-time mobile road condition refers to the road condition of the electric bicycle's current location, including dirt roads, cement roads, asphalt roads, etc., which is obtained by the processing terminal identifying and calling the riding environment parameters.

[0118] Step S702: Determine the traffic condition change according to the real-time moving traffic condition and the preset traffic condition change relationship.

[0119] The road condition change relationship refers to the correspondence between the original road condition and the changed road condition. For example, if the original road condition is a dirt road, the changed road condition is a muddy road condition. If the original road condition is a cement road or an asphalt road, the changed road condition is a slippery road condition. The operator forms a mapping table by matching the original road condition with the changed road condition one by one. The road condition change situation refers to the road change situation at the current location of the electric bicycle, which is found by the processing terminal in the mapping table corresponding to the road condition change relationship according to the road condition corresponding to the real-time mobile road condition.

[0120] Step S703: determining whether the road condition change is a preset muddy road condition or a preset slippery road condition.

[0121] Among them, the muddy road condition refers to the muddy road condition, and the slippery road condition refers to the slippery road condition, both of which are stored in the processing terminal by the operator.

[0122] The processing terminal determines whether the road condition corresponding to the road condition change is a muddy road condition or a slippery road condition, thereby determining whether the electric bicycle needs power assistance.

[0123] Step S7031: If the road condition is slippery, the preset non-assistance parameters are defined as actual assistance parameters.

[0124] If the processing terminal determines that the road condition corresponding to the road condition change is a road condition corresponding to a slippery road condition, it indicates that the road at the current position of the electric bicycle has become slippery, and the speed is not easy to be too fast at this time, so the unassisted parameter is defined as the actual assisted parameter. The unassisted parameter in this step is consistent with the unassisted parameter in step S501, and will not be repeated here.

[0125] Step S7032: If the road condition is muddy, the additional movement resistance is obtained, and the actual power assistance parameter is determined according to the additional movement resistance.

[0126] Among them, if the processing terminal determines that the road condition corresponding to the road condition change is a muddy road condition, it means that the road on which the electric bicycle is currently traveling has become muddy, and the mud will make it difficult for the electric bicycle to move. Therefore, the additional resistance to movement is detected, and the actual assist parameters are determined based on the additional resistance to movement.

[0127] The additional resistance to movement refers to the additional force required when an electric bicycle moves at the current speed on a muddy road. The processing terminal first determines the normal force value required for a rider of this weight to ride at this speed on a normal road, and then detects the force value required when the electric bicycle moves at the current speed on the muddy road at this time. The difference between the force value at this time and the normal force value is calculated to obtain the additional resistance to movement.

[0128] The actual power assist parameter in this step is determined by the processing terminal based on the analysis of the additional movement resistance. The additional movement resistance is proportional to the actual power assist parameter. The proportional coefficient between the two is determined by the operator based on the actual situation, and the processing terminal calculates the product of the additional movement resistance and the proportional coefficient to obtain the actual power assist parameter.

[0129] Based on the same inventive concept, Figure 8The embodiment of the present application provides a variable speed flywheel, including an outer sleeve 1, a flywheel piece 2 and a locking ring 3. The outer sleeve 1 is arranged in a circular step ladder shape, and the outer sleeve 1 forms three steps for the flywheel piece 2 to be mounted. There are eight flywheel pieces 2, and the flywheel pieces 2 are evenly spaced and mounted on the three steps of the outer sleeve 1. In the present application, the spacing between the flywheel pieces 2 is equal, which can be achieved by installing washers between the flywheel pieces 2 and relying on the deformation and extension of the flywheel piece 2 itself. A limiting block is integrally formed on the inner diameter of the flywheel piece 2, and a limiting groove is provided on the outer sleeve 1. When the flywheel piece 2 is mounted on the outer sleeve 1, the limiting block is inserted into the limiting groove, thereby realizing the circumferential limitation of the flywheel piece 2 and the outer sleeve 1.

[0130] The end of the outer sleeve 1 with the largest step diameter is integrally formed with a limiting ring 12. When the flywheel piece 2 is mounted on the outer sleeve 1, the limiting ring 12 abuts against the flywheel piece 2, thereby limiting the flywheel piece 2 along the installation direction to prevent the flywheel piece 2 from falling off the outer sleeve 1. The locking ring 3 is installed on the end of the outer sleeve 1 with the smallest step diameter. The outer sleeve 1 is provided with a locking opening 11 for the locking ring 3 to be inserted and fixed. After the flywheel piece 2 is completely mounted on the outer sleeve 1, the locking ring 3 is inserted into the locking opening 11, so that the locking ring 3 limits the flywheel piece 2 on the outer sleeve 1. The outer diameter of the flywheel piece 2 gradually increases from the locking ring 3 to the limiting ring 12, and the corresponding number of teeth is set to 10 teeth, 13 teeth, 15 teeth, 17 teeth, 19 teeth, 21 teeth, 24 teeth and 28 teeth respectively.

[0131] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by a variable-speed flywheel-based electric vehicle control method.

[0132] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0133] Based on the same inventive concept, an embodiment of the present application provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes an electric vehicle control method based on a variable speed flywheel.

[0134] Those skilled in the art can clearly 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 assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0135] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A tram control method based on a variable speed flywheel, characterized in that: include: Obtain riding trigger signal of electric bicycle; Acquire riding environment parameters and real-time load weight of the electric bicycle based on the riding trigger signal; Analyze riding environment parameters and real-time load weight to determine actual power assist parameters and actual flywheel parameters; The electric bicycle is regulated and controlled according to the actual power-assistance parameters and the actual flywheel parameters; The steps of obtaining riding environment parameters and real-time load weight of the electric bicycle based on the riding trigger signal include: Acquire the real-time moving position of the electric bicycle based on the riding trigger signal; Determine whether the real-time mobile position meets the requirements of the preset environment map position; If it is in compliance, the riding environment parameters are determined according to the relationship between the real-time mobile position and the preset position environment; If it does not meet the requirements, the moving position image and the position fluctuation angle are obtained; Performing image analysis on the mobile location image to determine the mobile location road condition, and correlating the mobile location road condition and the location undulation angle to generate riding environment parameters; The preset weight detection device is controlled according to the riding environment parameters to detect the rider to generate the real-time bearing weight.

2. The electric vehicle control method based on a variable speed flywheel according to claim 1, characterized in that: The steps of controlling a preset weight detection device to detect the rider according to the riding environment parameters to generate a real-time load weight include: Controlling the weight detection device to detect the rider to generate a basic bearing weight; Analyze riding environment parameters to determine real-time riding angle; Determine whether the real-time riding angle meets the preset zero-force angle requirement; If it meets the requirements, the basic bearing weight is defined as the real-time bearing weight; If not, the real-time riding angle and basic load-bearing weight are analyzed to determine the real-time load-bearing weight.

3. The electric vehicle control method based on a variable speed flywheel according to claim 1, characterized in that: The steps of obtaining the real-time moving position of the electric bicycle based on the riding trigger signal include: Acquire the basic positioning position of the electric bicycle based on the riding trigger signal; Determine whether the basic positioning position meets the requirements of the preset riding overlap position; If it does not match, the basic positioning position is defined as the real-time moving position; If it meets the requirements, the positioning position image is obtained; Determine a reference position image according to a relationship between a basic positioning position and a preset position image; The positioning position image and the reference position image are analyzed to determine the real-time moving position.

4. The electric vehicle control method based on a variable speed flywheel according to claim 1, characterized in that: The steps of analyzing the riding environment parameters and the real-time load weight to determine the actual power assist parameters and the actual flywheel parameters include: Determine whether the riding environment parameters meet the requirements of the preset power-assisting environment parameters; If not, the preset non-assistance parameter is defined as the actual assistance parameter, and the first real-time moving speed is obtained; Analyzing the first real-time moving speed and the riding environment parameters to determine actual flywheel parameters of the preset speed-changing flywheel; If it meets the requirements, the basic power-assistance parameters are determined according to the real-time load-bearing weight and the preset weight-assistance relationship; The basic power assist parameters and riding environment parameters are analyzed to determine the actual power assist parameters and the actual flywheel parameters of the preset speed-changing flywheel.

5. The electric vehicle control method based on a variable speed flywheel according to claim 4, characterized in that: The steps of analyzing the basic power assist parameters and the riding environment parameters to determine the actual power assist parameters and the actual flywheel parameters of the preset speed change flywheel include: Get real-time weather data; Determine whether the real-time meteorological data meets the preset requirements of abnormal meteorological data; If it is in compliance, the actual power-assisting parameters and actual flywheel parameters are determined according to the preset complex road condition trigger signal; If not, the basic power-assistance parameters and riding environment parameters are analyzed to determine the actual power-assistance parameters and obtain the second real-time moving speed; The second real-time moving speed and riding environment parameters are analyzed to determine actual flywheel parameters.

6. The electric vehicle control method based on variable speed flywheel according to claim 5, characterized in that: The steps of determining the actual power assist parameters and the actual flywheel parameters according to the preset complex road condition trigger signal include: Define the preset maximum number of flywheel teeth as the actual flywheel parameter; Analyze riding environment parameters to determine real-time moving road conditions; Determine the change of road condition according to the real-time moving road condition and the preset relationship between road condition changes; Determining whether the road condition change is a preset muddy road condition or a preset slippery road condition; If the road condition is slippery, the preset non-assistance parameter is defined as the actual assistance parameter; If the road condition is muddy, the additional resistance to movement is obtained, and the actual power assistance parameter is determined according to the additional resistance to movement.

7. A variable speed flywheel, applied to the electric vehicle control method based on the variable speed flywheel as claimed in any one of claims 1 to 6, characterized in that: It comprises a jacket (1), a flywheel sheet (2) and a locking ring (3), wherein a plurality of flywheel sheets (2) are provided, and the flywheel sheets (2) are evenly spaced and sleeved on the jacket (1), and the flywheel sheets (2) and the jacket (1) are in contact with each other in the circumferential direction; The locking ring (3) is arranged at one end of the outer sleeve (1); the outer sleeve (1) is provided with a locking opening (11) for the locking ring (3) to be inserted and fixed; the locking ring (3) is inserted into the locking opening (11) and abuts against the flywheel (2); a limiting ring (12) is arranged at one end of the outer sleeve (1) away from the locking ring (3); the limiting ring (12) abuts against the flywheel (2); and the outer diameter of the flywheel (2) gradually increases along the direction from the locking ring (3) to the limiting ring (12).

8. A variable speed flywheel according to claim 7, characterized in that: The flywheel plates (2) are provided with eight teeth, and the number of teeth of the flywheel plates (2) along the direction from the locking ring (3) to the limiting ring (12) is set to 10 teeth, 13 teeth, 15 teeth, 17 teeth, 19 teeth, 21 teeth, 24 teeth and 28 teeth respectively.

9. A computer-readable storage medium, characterized in that: The computer program is stored which can be loaded by a processor and execute the electric vehicle control method based on a variable speed flywheel according to any one of claims 1 to 6.

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