Personalized bicycle auxiliary power providing method

Abstract

The personalized bicycle auxiliary power providing method of the present invention is to establish a user's personalized intelligent auxiliary power control system through riding data collection. The system is used to establish real-time monitoring of the user's personal riding parameters in different riding environments (slope changes), and collect data such as speed and pedaling power output when riding on different terrains, analyze parameters that conform to personal riding habits, and write these personalized parameters into the processing unit to provide the control unit as reference data for intelligent auxiliary control adjustment. The main technical framework includes establishing a personalized riding preference model by collecting user riding data, and establishing intelligent control based on the personalized riding preference model. In this way, the present invention can quickly and accurately obtain an evaluation, improving the problem of slow and inaccurate known evaluations.

Description

[Technical Field]

[0001] This invention relates to auxiliary power technology for bicycles, and more particularly to a personalized method for providing auxiliary power to bicycles. [Previous Technology]

[0002] In recent years, with the rapid growth of the electric-assisted bicycle market, electric-assisted bicycles have gradually become a popular choice for modern urban travel and a trend in daily riding. Although current electric assistance systems have achieved certain results in many aspects, frequent adjustments to the assistance status (e.g., adjusting the assistance level or assistance power parameters) are still required when facing complex terrain or different riding needs. In this case, traditional control systems require riders to spend a lot of effort adjusting the assistance level and it is difficult to obtain the best assistance effect immediately. Such a design often makes it difficult for riders to focus on riding itself, reducing the comfort and enjoyment of the overall riding experience.

[0003] The most relevant patent found so far is the "Assisted Power Control System and Method for Electric Assisted Bicycles" patent from Sinbang Electronics Co., Ltd. The system in this patent includes a sensing device, a mobile computing device, a first controller, and a second controller. The sensing device detects riding torque and riding speed. The mobile computing device uses a first ANN model with personal data (age, weight, height, and gender) and historical riding data (average speed, maximum speed, riding distance, calories burned, average heart rate, maximum heart rate, etc.) as input data. The second ANN model outputs a fine-tuning factor based on the prediction score output by the first ANN model, the personal data, and environmental data (including weather, temperature, time, location, wind speed, etc.). The first controller generates a terminal factor based on the fine-tuning factor, the mode factor, and the gap factor. The second controller generates motor target parameters based on the terminal factor, the riding torque, and the riding speed. It then generates a motor drive current based on the motor target parameters and outputs it to the motor to make it run. However, such systems also face certain challenges, especially in terms of operational flexibility and immediacy. Rider intervention may still be required to some extent, and a completely seamless assistance experience cannot be achieved. [Summary of the Invention]

[0004] The inventor, in view of the fact that the existing bicycles still have many shortcomings in actual use, has made improvements with a tireless spirit and with the help of his rich professional knowledge and many years of practical experience, and has created this invention.

[0005] The purpose of this invention is to provide a personalized bicycle auxiliary power supply method. This invention aims to simplify operation and reduce the number of manual operations to adjust the auxiliary power, so as to provide intelligent auxiliary power control that meets the user's personalized needs, allowing the user to focus on enjoying the riding pleasure.

[0006] To achieve the above objective, the present invention proposes a personalized bicycle power assistance method, comprising the following steps: Step 1: Riding a bicycle, the bicycle including a processing unit, an auxiliary power unit providing power assistance, and a control unit connected to the processing unit and the auxiliary power unit; the processing unit collects various sensing data during riding, including a pedaling power, a gradient, and a speed; Step 2: When one of the pedaling power, the gradient, and the speed changes each time, the processing unit performs a division, accumulating multiple changes to obtain multiple segments; Step 3: ... Step 3: The processing unit records the time length of each segment and presets a sampling time length; Step 4: Segments in which the pedaling power, slope, and speed sensing data remain unchanged for a time length greater than the sampling time length are selected to obtain multiple sampling segments; Step 5: An evaluation model is established by calculating the slope and speed corresponding to each sampling segment and the pedaling power corresponding to each sampling segment, and a majority of evaluation power is estimated based on the evaluation model; Step 6: The control unit controls the auxiliary power unit to provide auxiliary power according to the evaluation power, so that the riding data reaches a target power.

[0007] This invention obtains the sampling segment by selecting segments in which the pedaling power, gradient, and speed remain unchanged for a duration longer than the sampling time, thus quickly and accurately determining the evaluated power. This method provides personalized and efficient auxiliary power support during riding, further enhancing riding comfort and efficiency. The difference between this invention and the previous one is that, based on individual riding history data and changes in the local environment (route gradient), a personalized preference model is analyzed and established, providing intelligent auxiliary power control tailored to different terrain conditions, allowing users to focus on enjoying the riding experience.

[0008] Preferably, the evaluation model in step 5 is calculated using a linear regression equation. This allows for rapid analysis and accurate evaluation.

[0009] Preferably, the calculation of each sampling segment in step 5 is based on the average value of each pedaling power per unit time. This makes the data more accurate.

[0010] Preferably, the calculation of each sampling segment in step 5 is based on the average value of each slope per unit time. This makes the data more accurate.

[0011] Preferably, the calculation of each sampling segment in step 5 is based on the average value of each speed per unit time. This makes the data more accurate.

[0012] The technical content of this invention may include:

[0013] 1. Establish a personalized riding preference model by collecting user riding data:

[0014] One aspect of the present invention is to collect a specific number of riding data from the user through a processing unit, including riding history data (pedal power, speed) and external environment (route gradient changes), and then analyze the rider's preferred pedaling power under different gradients and speed changes in a stable state (maintained for a specific time length) to establish a dynamic personalized riding preference model. The processing unit will continuously update the evaluation model as the number of riding data accumulated is fixed, in order to adapt to changes in the user's riding status.

[0015] 2. Establish intelligent control based on a personalized riding preference model:

[0016] The second embodiment of the present invention is to use a processing unit and a control unit to adjust the controllable components to make the riding data reach the target parameters based on the parameters generated in the personalized preference model by inputting real-time riding data into the processing unit and the control unit.

[0017] The personalized bicycle auxiliary power supply method provided by the present invention will be described in detail in the following embodiments. However, those skilled in the art should understand that such detailed descriptions and the specific embodiments listed for implementing the present invention are for illustrative purposes only and are not intended to limit the scope of the patent application.

Implementation Method

[0019] In order to explain the technical features of the present invention in detail, the following preferred embodiment is described in conjunction with the accompanying drawings.

[0020] Please refer to Figures 1 to 4. The present invention provides a personalized bicycle power assistance method, the steps of which include:

[0021] Step 1: As shown in Figure 1, ride a bicycle. The bicycle includes a processing unit 10, an auxiliary power unit that provides power assistance, and a control unit 20 connected to the processing unit 10 and the auxiliary power unit. The processing unit 10 collects various sensing data during riding, including pedaling power, gradient, and speed.

[0022] wherein, speed is kilometers per hour (km / hr), and pedaling power (watt) is 1 joule per second (1 J / s), which is the output of the rider.

[0023] Step 2: As shown in Figure 2, when any of the sensing data such as pedaling power, slope, or speed changes each time, the processing unit 10 divides the recorded data once, and after accumulating multiple times, obtains multiple segments S. The change in any of the sensing data such as pedaling power, slope, or speed occurs when the change in the sensing data of pedaling power exceeds its preset range, or the change in the sensing data of slope exceeds its preset range, or the change in the sensing data of speed exceeds its preset range.

[0024] Changes in slope, such as continuous uphill climbing exceeding a predetermined value, rather than slight changes, are considered changes, for example, 1%, such as a change from 1.3% to 2.3%. Alternatively, a fixed range can be defined, for example, a change from 0% to 1% to 1% to 2%.

[0025] Ideally, the slope is a range value, wherein the change in slope is divided into intervals of 0.5%, 1% or 2%, that is, a change exceeding a preset range is considered a change.

[0026] The speed change is determined by filtering according to the set range. This method can reflect the user's actual riding state under different road conditions, so as to provide auxiliary power more accurately.

[0027] Step 3: The processing unit 10 records the time length of each segment S and presets a sampling time length. This time length can be set according to actual needs to ensure that the data of each segment can represent the real riding situation.

[0028] Step 4: Filter the segments S of the pedaling power, slope, and speed sensing data that remain unchanged for a duration longer than the sampling time to obtain multiple sampling segments (segments 3, 6, and 7 as shown in Figure 2). This filtering eliminates invalid or unnecessary data fluctuations, improving the accuracy and efficiency of the calculation.

[0029] Step 5: Calculate and establish an evaluation model based on the slope and speed corresponding to each sampling section and the corresponding trampling power to obtain the majority of the evaluation power. The establishment of the evaluation model will directly affect the accuracy of the final output power. As shown in Figure 3, the table lists the preferred trampling power for different slopes and speeds.

[0030] In this embodiment, the calculation of trampling power, speed, and slope in each sampling segment is based on the average value of each, that is, the average trampling power, average speed, and average slope per unit time in each segment. This ensures more accurate data and effectively avoids the impact of sudden changes in data at a single point in time on the results, guaranteeing the stability and accuracy of the data.

[0031] Step 6: The control unit 20 controls the auxiliary power unit to provide an auxiliary power according to the evaluated power, so that the riding data reaches a target power, as shown in Figure 4.

[0032] The calculation formula in this embodiment adopts a linear regression equation. The linear regression formula is y = b0 + b1x1 + b2x2, where y is the evaluated power, x1 is the slope, x2 is the speed, b0 is the intercept of the regression line, and b1 and b2 are the slopes of each regression line. The advantage of this method is its simplicity and ability to fully reflect the influence of slope and speed on pedaling power.

[0033] The actual calculation and establishment of the evaluation model in this embodiment is in the form of a three-dimensional or multi-dimensional model (not shown in the figure). Among them, the multi-dimensional model can more accurately predict the power required under complex road conditions. This formula can calculate the most suitable evaluation power based on the latest data, thereby improving efficiency and comfort during riding.

[0034] This embodiment selects only the data collection segments S from the pedaling power, slope, and speed sensing data that remain unchanged for a duration longer than the data collection time to establish the evaluation model. This effectively reduces the calculation of unnecessary segments S, saves calculation time, and ensures that the calculated items better meet the requirements. Through this embodiment, the present invention can quickly and accurately derive the evaluation power. Ultimately, the filtered data will help accurately calculate the required power, thereby ensuring that the power output provided to the user meets the requirements.

[0035] The personalized bicycle power supply method of the present invention collects relevant riding data only after the user starts riding and updates the power prediction model based on the accumulation of riding time. It is not a specific value or data sheet set in advance by the manufacturer. Therefore, the present invention can adjust the evaluation model more in response to changes in the user's physical condition.

[0036] The personalized bicycle power supply method of the present invention determines the output power value based on the latest power prediction model. Therefore, the present invention can output a more accurate and suitable power value. It can not only better cope with changes in the user's physical condition, but also adjust the power output according to the current riding environment, thereby improving the overall riding comfort and efficiency.

[0037] Furthermore, the present invention is not limited to using only linear regression equations, but can also establish evaluation models for various other regression equations. For example, logistic regression, multinomial regression, stepwise regression, etc., to make it applicable to other needs for speed or accuracy.

[0038] The technical content of the present invention can be further described as follows:

[0039] 1. Establish a personalized riding preference model by collecting user riding data.

[0040] The implementation method involves the user riding in the selected manual mode, and the processing unit 10 collects riding data (including speed and pedaling power) and external environmental information (gradient). Through the personal riding data collected by the system, a dynamic personalized riding preference model is established under different external environments in a stable state (defined as: maintained for a specific time, such as 30 seconds), and the evaluation model is updated on a rolling basis as data accumulates (a specific number of data points, such as 3000 data points).

[0041] Distinguish between automatic and manual modes. Manual mode is for learning; automatic mode is automatically controlled by control unit 20. If manual operation is performed in automatic mode, it will enter manual mode (learning); the logic will be updated after the vehicle is restarted.

[0042] 2. Establish intelligent control based on personalized riding preference model.

[0043] The processing unit 10 and the control unit 20 calculate the parameters generated in the personalized preference model based on the real-time riding data, and perform intelligent riding control when the user selects the automatic mode, so that the riding data reaches the target parameters by adjusting the controllable components.

[0044] In summary, the personalized bicycle power supply method of the present invention can indeed achieve the expected use effect through the above-disclosed embodiments; however, the above-disclosed drawings and descriptions are only preferred embodiments of the present invention, and the methods and constituent elements disclosed in the above-disclosed embodiments are only illustrative examples and are not intended to limit the scope of the present invention. Substitutions or variations of other equivalent elements should also be covered by the patent application scope of the present invention. [Simplified Explanation of the Diagram]

[0018] Figure 1 is a system diagram of a preferred embodiment of the personalized bicycle auxiliary power supply method of the present invention. Figure 2 is a sampling diagram of a preferred embodiment of the personalized bicycle auxiliary power supply method of the present invention. Figure 3 is a model method diagram of a preferred embodiment of the personalized bicycle auxiliary power supply method of the present invention. Figure 4 is an implementation diagram of a preferred embodiment of the personalized bicycle auxiliary power supply method of the present invention.

Claims

1. A personalized bicycle power assistance method, comprising the following steps: Step 1: Riding a bicycle, the bicycle including a processing unit, an auxiliary power unit providing power assistance, and a control unit connected to the processing unit and the auxiliary power unit; the processing unit collects various sensing data during riding, the various sensing data including a pedaling power, a gradient, and a speed; Step 2: When one of the pedaling power, the gradient, and the speed changes each time, the processing unit divides the data once, accumulating multiple segments; Step 3: The processing unit records the time length of each segment and presets a sampling time length; Step 4: Segments in which the pedaling power, the gradient, and the speed sensing data remain unchanged and the time length is greater than the sampling time length are selected to obtain multiple sampling segments; Step 5: An evaluation model is established by calculating the gradient and speed corresponding to each sampling segment and the pedaling power corresponding to each sampling segment, and a majority of evaluation power is estimated based on the evaluation model; Step 6: The control unit controls the auxiliary power unit to provide auxiliary power according to the evaluated power, so that the riding data reaches a target power.

2. The personalized bicycle power assistance method as described in claim 1, wherein the evaluation model in step 5 is obtained by calculation using a linear regression equation.

3. The personalized bicycle power assistance method as described in claim 1, wherein the calculation of each sampling segment in step 5 is based on the average value of each pedaling power per unit time.

4. The personalized bicycle power assistance method as described in claim 1, wherein the calculation of each measurement segment in step 5 is based on the average value of each slope per unit time.

5. The personalized bicycle power supply method as described in claim 1, wherein the calculation of each measurement segment in step 5 is based on the average value of each speed per unit time.

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