TWI635019B

TWI635019B - Bicycle driving device with pedal sensor

Info

Publication number: TWI635019B
Application number: TW106117510A
Authority: TW
Inventors: 陳智勇; 蕭學良; 黃詩婷; 吳昀澤; 錢勃伽; 廖御呈
Original assignee: 樹德科技大學
Priority date: 2017-05-26
Filing date: 2017-05-26
Publication date: 2018-09-11
Also published as: TW201900488A

Abstract

本發明係揭露一種踏板感測式之自行車驅動裝置，其包含：踏板，係可拆卸式設置於自行車之踏桿上，踏板係配置以感測使用者騎乘自行車並踩踏踏板時之踏頻及壓力；以及驅動裝置，係可拆卸式設置於自行車之車輪上，驅動裝置係配置以接收踏頻及壓力並感測車輪之轉速，以對轉速、踏頻及壓力進行運算，進而輸出最適輔助動力來驅動車輪。 The present invention discloses a pedal-sensing bicycle driving device, comprising: a pedal detachably disposed on a pedal of a bicycle, wherein the pedal is configured to sense a cadence of a user riding a bicycle and stepping on the pedal; The pressure device and the driving device are detachably disposed on the wheel of the bicycle. The driving device is configured to receive the cadence and pressure and sense the rotational speed of the wheel to calculate the rotational speed, the cadence and the pressure, and thereby output the optimal auxiliary power. To drive the wheels.

Description

踏板感測式之自行車驅動裝置 Pedal sensing type bicycle driving device

本發明係有關於一種自行車驅動裝置，特別是一種踏板感測式之自行車驅動裝置。 The present invention relates to a bicycle driving device, and more particularly to a pedal sensing type bicycle driving device.

近年來，由於環保意識逐漸受到重視，使得自行車成為現代人所喜愛的交通工具之一。自行車不僅能夠成為上班上課的代步工具，更可以減少二氧化碳的排放量，更能夠達成運動紓壓的效果。然而，現有的自行車因地形、距離或速度等因素，造成騎乘時容易耗費太多體力，雖市面上之電動輔助自行車可透過電能驅動的方式輔助使用者騎乘，但不僅價格昂貴，亦需要專業的自行車維修技術，導致民眾望之卻步。 In recent years, due to the increasing awareness of environmental protection, bicycles have become one of the favorite vehicles for modern people. Bicycles can not only become a means of transportation to work, but also reduce carbon dioxide emissions, and achieve the effect of sports pressure. However, existing bicycles tend to consume too much physical force due to factors such as terrain, distance or speed. Although electric-assisted bicycles on the market can assist users to ride through electric energy, they are not only expensive but also need to be used. Professional bicycle repair technology has caused the public to be discouraged.

鑑於上述習知技藝的問題，本發明之目的就是在提供一種踏板感測式之自行車驅動裝置，不僅令使用者自行將現有的自行車升級為電動自行車，更可精準地控制驅動裝置提供使用者騎乘時的輔助動力。 In view of the above-mentioned problems of the prior art, the object of the present invention is to provide a pedal-sensing bicycle driving device that not only allows the user to upgrade the existing bicycle to an electric bicycle, but also precisely controls the driving device to provide the user to ride. Auxiliary power for multiplication.

本發明之一目的在於提供一種踏板感測式之自行車驅動裝置，其包含：踏板，係可拆卸式設置於自行車之踏桿上，踏板係配置以感測使用者騎乘自行車並踩踏踏板時之踏頻及壓力；以及驅動裝置，係可拆卸式設置於自行車之車輪上，驅動裝置係配置以接收踏頻及壓力並感測車輪之轉速，以對轉速、踏頻及壓力進行運算，進而輸出最適輔助動力來驅動車輪。 An object of the present invention is to provide a pedal-sensing bicycle driving device, comprising: a pedal detachably disposed on a pedal of a bicycle, wherein the pedal is configured to sense a user riding a bicycle and stepping on the pedal The cadence and pressure; and the drive unit are detachable On the wheel of the vehicle, the driving device is configured to receive the cadence and pressure and sense the rotational speed of the wheel to calculate the rotational speed, the cadence and the pressure, and then output the optimum auxiliary power to drive the wheel.

前述之踏板上更可設有第一控制單元及壓力感測單元，壓力感測單元係電性連接第一控制單元，以依據使用者踩踏壓力感測單元時所產生之電阻變化來計算壓力。 The pedal can be further provided with a first control unit and a pressure sensing unit. The pressure sensing unit is electrically connected to the first control unit to calculate the pressure according to the resistance change generated when the user steps on the pressure sensing unit.

前述之踏板上更可設有踏頻感測單元，踏頻感測單元係電性連接第一控制單元，以依據踏桿轉動時所產生之電壓變化次數來計算踏頻。 The pedal is further provided with a cadence sensing unit, and the cadence sensing unit is electrically connected to the first control unit to calculate the cadence according to the number of voltage changes generated when the pedal is rotated.

前述之踏板上更可設有第一無線傳輸單元，第一無線傳輸單元係電性連接第一控制單元，以藉由無線傳輸方式傳送壓力及踏頻至驅動裝置。 The first wireless transmission unit is electrically connected to the first control unit to transmit the pressure and the cadence to the driving device by wireless transmission.

前述之驅動裝置上更可設有第二控制單元及第二無線傳輸單元，第二無線傳輸單元係電性連接第二控制單元，以藉由無線傳輸方式接收壓力及踏頻。 The second driving unit and the second wireless transmission unit are electrically connected to the second control unit to receive the pressure and the cadence by wireless transmission.

前述之驅動裝置上更可設有轉速感測單元，轉速感測單元係電性連接第二控制單元，以依據車輪轉動時所產生之電壓變化來計算轉速。 The driving device may further be provided with a rotation speed sensing unit, and the rotation speed sensing unit is electrically connected to the second control unit to calculate the rotation speed according to the voltage change generated when the wheel rotates.

前述之驅動裝置上更可設有驅動馬達，驅動馬達係電性連接第二控制單元並傳動連接車輪，以依據最適輔助動力驅動車輪轉動。 The driving device may further be provided with a driving motor electrically connected to the second control unit and drivingly connecting the wheels to drive the wheel to rotate according to the optimal auxiliary power.

前述之驅動裝置係將轉速、踏頻及壓力作為感測資料輸入機率神經網路模型進行運算。 The aforementioned driving device calculates the rotational speed, the cadence and the pressure as sensing data input probability neural network models.

前述之機率神經網路模型更依據感測資料與訓練資料之間的相似值高低來判斷並計算最適輔助動力。 The aforementioned probabilistic neural network model judges and calculates the optimal auxiliary power based on the similarity between the sensing data and the training data.

此外，本發明之踏板感測式之自行車驅動裝置更可包含顯示裝置，顯示裝置係以無線傳輸方式從驅動裝置接收並顯示轉速、踏頻及壓力。 In addition, the pedal-sensing bicycle driving device of the present invention may further include a display device that receives and displays the rotational speed, the cadence, and the pressure from the driving device in a wireless transmission manner.

承上所述，本發明之踏板感測式之自行車驅動裝置具有一個或多個下列優點： As described above, the pedal-sensing bicycle drive of the present invention has one or more of the following advantages:

(1)藉由可拆卸式的踏板及驅動裝置，令使用者可輕易地裝設於現有的自行車上，藉此將現有的自行車輕鬆升級為電動自行車。 (1) With the detachable pedal and driving device, the user can easily install it on an existing bicycle, thereby easily upgrading the existing bicycle to an electric bicycle.

(2)藉由機率神經網路模型對輸入的踏頻、壓力及車輪轉速進行演算，可精準地運算出在不同的騎乘狀態下所需之最適輔助動力，讓使用者可輕鬆地騎乘自行車。 (2) Calculating the input cadence, pressure and wheel speed by the probability neural network model, the optimal auxiliary power required in different riding conditions can be accurately calculated, so that the user can easily ride bicycle.

茲為使鈞審對本發明的技術特徵及所能達到之技術功效有更進一步的瞭解與認識，謹佐以較佳的實施例及配合詳細的說明如後。 For a better understanding of the technical features of the present invention and the technical effects that can be achieved, the preferred embodiments and the detailed description are as follows.

10‧‧‧踏板 10‧‧‧ pedal

11‧‧‧第一控制單元 11‧‧‧First Control Unit

12‧‧‧壓力感測單元 12‧‧‧ Pressure sensing unit

13‧‧‧踏頻感測單元 13‧‧‧ cadence sensing unit

14‧‧‧第一無線傳輸單元 14‧‧‧First wireless transmission unit

20‧‧‧驅動裝置 20‧‧‧ drive

21‧‧‧第二控制單元 21‧‧‧Second Control Unit

22‧‧‧轉速感測單元 22‧‧‧Speed sensing unit

23‧‧‧驅動馬達 23‧‧‧Drive motor

24‧‧‧第二無線傳輸單元 24‧‧‧Second wireless transmission unit

30‧‧‧顯示裝置 30‧‧‧Display device

圖1為本發明之踏板感測式之自行車驅動裝置之第一實施例之方塊圖。 1 is a block diagram of a first embodiment of a pedal sensing type bicycle driving device of the present invention.

圖2為本發明之踏板感測式之自行車驅動裝置之機率神經網路模型之架構圖。 2 is a structural diagram of a probability neural network model of a pedal-sensing bicycle driving device of the present invention.

圖3為本發明之踏板感測式之自行車驅動裝置之第二實施例之方塊圖。 3 is a block diagram of a second embodiment of a pedal sensing type bicycle driving device of the present invention.

以下將參照附圖，說明本發明之踏板感測式之自行車驅動裝置之實施例，為使便於理解，下述實施例中的相同元件係以相同的符號標示來說明。 DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the pedal-sensing bicycle driving device of the present invention will be described with reference to the accompanying drawings. For the sake of understanding, the same components in the following embodiments are denoted by the same reference numerals.

請參閱圖1，圖1為本發明之踏板感測式之自行車驅動裝置之第一實施例之方塊圖。 Please refer to FIG. 1. FIG. 1 is a block diagram of a first embodiment of a pedal sensing type bicycle driving device according to the present invention.

本發明之種踏板感測式之自行車驅動裝置至少包含踏板10及驅動裝置20。踏板10係可拆卸式設置於自行車之踏桿上，且踏板10係配置以感測使用者騎乘自行車並踩踏踏板10時之踏頻及壓力。驅動裝置20係可拆卸式設置於自行車之車輪(如後輪)上，驅動裝置20係配置以接收踏頻及壓力並感測車輪之轉速，以對轉速、踏頻及壓力進行運算，進而輸出最適輔助動力來驅動車輪。 The pedal-sensing bicycle driving device of the present invention includes at least a pedal 10 and a driving device 20. The pedal 10 is detachably disposed on the pedal of the bicycle, and the pedal 10 is configured to sense the cadence and pressure when the user rides the bicycle and steps on the pedal 10. The driving device 20 is detachably disposed on a bicycle wheel (such as a rear wheel), and the driving device 20 is configured to receive the cadence and pressure and sense the rotational speed of the wheel to calculate the rotational speed, the cadence and the pressure, and then output Optimal auxiliary power to drive the wheels.

踏板10上更可設有第一控制單元11、壓力感測單元12、踏頻感測單元13及第一無線傳輸單元14，且壓力感測單元12、踏頻感測單元13及第一無線傳輸單元14係分別電性連接第一控制單元11。驅動裝置20上更可設有第二控制單元21、轉速感測單元22、驅動馬達23及第二無線傳輸單元24，且轉速感測單元22、驅動馬達23及第二無線傳輸單元24係分別電性連接第二控制單元21。 The pedal 10 is further provided with a first control unit 11, a pressure sensing unit 12, a cadence sensing unit 13 and a first wireless transmission unit 14, and the pressure sensing unit 12, the cadence sensing unit 13 and the first wireless The transmission unit 14 is electrically connected to the first control unit 11, respectively. The driving device 20 is further provided with a second control unit 21, a rotation speed sensing unit 22, a driving motor 23 and a second wireless transmission unit 24, and the rotation speed sensing unit 22, the driving motor 23 and the second wireless transmission unit 24 are respectively The second control unit 21 is electrically connected.

壓力感測單元12可例如埋設於踏板10中或設置於踏板10之表面，以依據使用者踩踏壓力感測單元12時所產生之電阻變化來計算壓力。舉例來說，壓力感測單元12可例如為壓阻式壓力感測器，因此壓力感測單元12會因使用者踩踏踏板10時所產生的應力變化而造成電阻值改變，藉此計算使用者踩踏踏板10時之壓力。 The pressure sensing unit 12 can be embedded, for example, in the pedal 10 or on the surface of the pedal 10 to calculate the pressure according to the change in resistance generated when the user steps on the pressure sensing unit 12. For example, the pressure sensing unit 12 can be, for example, a piezoresistive pressure sensor. Therefore, the pressure sensing unit 12 changes the resistance value due to a change in stress generated when the user steps on the pedal 10, thereby calculating the user. The pressure when pedal 10 is depressed.

踏頻感測單元13係用以依據踏桿轉動時所產生之電壓變化次數來計算踏頻。舉例來說，踏頻感測單元13可例如包含霍爾元件及磁鐵，其中霍爾元件可例如設置於踏板10之側面，磁鐵可例如環繞於踏桿，因此當使用者在騎乘自行車並踩踏踏板10時，踏桿便會開始轉動，接著霍爾元件便會偵測到磁鐵，以藉由偵測時的電壓變化次數來計算踏頻。 The cadence sensing unit 13 is configured to calculate the cadence according to the number of voltage changes generated when the pedal is rotated. For example, the cadence sensing unit 13 may include, for example, a Hall element and a magnet, wherein the Hall element may be disposed, for example, on the side of the pedal 10, and the magnet may be, for example, wrapped around the pedal, so when the user is riding the bicycle and stepping on the bicycle When the pedal 10 is used, the pedal will start to rotate, and then the Hall element will detect the magnet to calculate the cadence by the number of voltage changes during detection.

踏板10及驅動裝置20係分別透過第一無線傳輸單元14及第二無線傳輸單元24以無線傳輸方式傳送及接收壓力及踏頻。其中，無線傳輸方式可例如為無線網路通信的工業標準(Wireless fidelity，Wi-Fi)、藍芽(Bluetooth)、紅外線(Infrared Radiation，IR)、無線射頻(Radio Frequency，RF)或群蜂技術(Zigbee)，然而本發明不限於此。 The pedal 10 and the driving device 20 transmit and receive pressure and cadence in a wireless transmission manner through the first wireless transmission unit 14 and the second wireless transmission unit 24, respectively. The wireless transmission mode may be, for example, a wireless fidelity (Wi-Fi), a Bluetooth, an Infrared Radiation (IR), a Radio Frequency (RF), or a group bee technology. (Zigbee), however, the invention is not limited thereto.

轉速感測單元22係依據車輪轉動時所產生之電壓變化來計算轉速。舉例來說，轉速感測單元22可例如包含霍爾元件及磁鐵，其中霍爾元件可例如設置於車輪輪軸(如後輪輪軸)之側面，磁鐵可例如設置於車輪之側面(如後輪之幅條上)，因此當使用者在騎乘自行車時，車輪便會開始轉動，接著霍爾元件便會偵測到磁鐵，以藉由偵測時的電壓變化來計算轉速。 The rotational speed sensing unit 22 calculates the rotational speed based on the voltage change generated when the wheel is rotated. For example, the rotation speed sensing unit 22 may include, for example, a Hall element and a magnet, wherein the Hall element may be disposed, for example, on a side of a wheel axle (such as a rear wheel axle), and the magnet may be disposed, for example, on a side of the wheel (such as a rear wheel). On the spoke), when the user is riding the bicycle, the wheel will start to rotate, and then the Hall element will detect the magnet to calculate the rotation speed by detecting the voltage change.

驅動馬達23係傳動連接車輪，以依據最適輔助動力驅動車輪轉動。其中，驅動馬達23可例如為無刷直流馬達，並且可以脈波調變的方式控制無刷直流馬達調整輔助動力，因此不僅可快速地在短時間內完成拆裝，更可在不改裝自行車的情況下相容於市售大部分之車型，且可令使用者在停車時輕易拆卸隨身攜帶，避免遭竊。 The drive motor 23 is configured to drive the wheels to drive the wheels to rotate in accordance with the optimum auxiliary power. The driving motor 23 can be, for example, a brushless DC motor, and can control the brushless DC motor to adjust the auxiliary power in a pulse wave modulation manner, so that the disassembly and assembly can be completed not only in a short time, but also in the bicycle. In case of compatibility with most of the commercially available models, the user can easily disassemble and avoid being stolen while parking.

請配合圖1一併參閱圖2，圖2為本發明之踏板感測式之自行車驅動裝置之機率神經網路模型之架構圖。 Please refer to FIG. 2 together with FIG. 1. FIG. 2 is a structural diagram of a probability neural network model of the pedal sensing type bicycle driving device of the present invention.

驅動裝置20係將轉速、踏頻及壓力作為感測資料輸入機率神經網路模型進行運算，且機率神經網路模型更依據感測資料與訓練資料之間的相似值高低來判斷並計算最適輔助動力。 The driving device 20 calculates the rotational speed, the cadence and the pressure as the sensing data input probability neural network model, and the probability neural network model judges and calculates the optimal auxiliary according to the similarity value between the sensing data and the training data. power.

機率神經網路模型為一種四層神經元結構的網路模型，其包含：輸入層(Input Layer)、類別層(Pattern Layer)、總和層(Summation Layer)及輸出層 (Output Layer)，此模型係屬於前向式神經網路架構的一種。機率式神經網路模型主要的理論基礎係建立在於貝氏決策(Bayes decision)上，其最重要的特色在於網路訓練的即時性。 The probabilistic neural network model is a network model of a four-layer neuron structure, which includes: an input layer, a pattern layer, a summation layer, and an output layer. (Output Layer), this model is a kind of forward neural network architecture. The main theoretical basis of the probabilistic neural network model is based on the Bayes decision. The most important feature is the immediacy of network training.

驅動裝置20之第二控制單元21透過機率神經網路模型對轉速、踏頻及壓力之感測資料進行運算之說明如下： The operation of the second control unit 21 of the driving device 20 to calculate the sensing data of the rotational speed, the cadence frequency and the pressure through the probability neural network model is as follows:

在輸入層中，輸入x為轉速、踏頻及壓力之感測資料：x={g₁,g₂,...,g_m}；其中，m為輸入感測資料的數量，在本發明中即為每一筆的轉速、踏頻及壓力。 In the input layer, input x is the sensing data of the rotational speed, the cadence and the pressure: x = {g ₁ , g ₂ , ..., g _m }; wherein m is the quantity of the input sensing data, in the present invention In the middle is the speed, cadence and pressure of each pen.

在類別層中，假設機率神經網路模型具有類別向量c(即訓練資料，在本發明之實施例中可例如為不同轉速、踏頻及壓力所對應之輔助動力)：c={c ₁,c ₂,...,c _r}及c _i={y_i1,y_i2,...,y_im}；其中，r為類別c的數量，m為每個類別內的資料數量。 In the category layer, it is assumed that the probability neural network model has a category vector c (ie, training data, which may be, for example, auxiliary speeds corresponding to different rotational speeds, cadences, and pressures) in the embodiment of the present invention: c = { c ₁ , c ₂ ,..., c _r } and c _i ={y _i1 ,y _i2 ,...,y _im }; where r is the number of categories c and m is the number of data within each category.

然而，在實際利用貝氏決策解決分類問題時，會發現並無法事先了解資料的機率密度函數。因此，在總和層中，本發明使用一個特徵值估測一個類別，對於訓練資料中的每一樣本建立一個以樣本的特徵值為中心的高斯曲線，接著把所有建立的曲線疊加成一個屬於該類別的機率密度函數。若是要用在任意維度的問題上，則可以將機率密度函數表示成：其中，d為訓練資料向量之維度；σ為高斯函數之平滑係數(Smoothing Parameter)；(g-c_i)^T為(g-c_i)之轉置。 However, when the Bayesian decision is actually used to solve the classification problem, it is found that the probability density function of the data cannot be known in advance. Therefore, in the summation layer, the present invention estimates a category using a feature value, establishes a Gaussian curve centered on the feature value of the sample for each sample in the training data, and then superimposes all the established curves into one belonging to the The probability density function of the category. If you want to use it on any dimension, you can express the probability density function as: Where d is the dimension of the training data vector; σ is the smoothing parameter of the Gaussian function; (gc _i ) ^T is the transposition of (gc _i ).

實作時，部分可視為常數忽略不計，因此在輸出層中，最大值(最接近)輸出結果p表示如下：其中，p為判定驅動裝置20輸出輔助動力(如驅動馬達23之脈波輸出)之參數。當輸入之感測資料與訓練資料之相似值越高時，其機率密度值就越高。接著，當p大於一預設值時，便判定該數值為最適輔助動力。 When it is implemented, Partially visible as a constant ignore, so in the output layer, the maximum (closest) output p is expressed as follows: Here, p is a parameter for determining that the driving device 20 outputs the auxiliary power (such as the pulse wave output of the drive motor 23). When the input sensory data and the training data have higher similarity values, the probability density value is higher. Then, when p is greater than a predetermined value, it is determined that the value is the optimum auxiliary power.

由上述說明可知，本發明透過機率神經網路模型可有效地成為驅動裝置20輸出最適輔助動力之演算模型。再者，機率神經網路模型的學習過程為零，因此可直接從訓練資料中讀取所需數據，而不需要像傳統類神經網路迭代的學習過程，且傳統類神經網路對於記憶體空間需求較大。因此，本發明非常適合將機率神經網路模型實作於微控制器上，且現有微控制器不僅皆可外加大量的快閃記憶體，其成本亦相當低廉。故只需將訓練資料放入快閃記憶體，以空間換取時間，且兼具效能提升與降低成本的雙重優勢。 As can be seen from the above description, the present invention can effectively become a calculation model for outputting an optimum auxiliary power by the drive device 20 through the probability neural network model. Furthermore, the learning process of the probabilistic neural network model is zero, so the required data can be read directly from the training data, without the need for a learning process like the traditional neural network iteration, and the traditional neural network for the memory Space demand is large. Therefore, the present invention is very suitable for implementing a probabilistic neural network model on a microcontroller, and the existing microcontroller can not only add a large amount of flash memory, but also has a relatively low cost. Therefore, it is only necessary to put the training materials into the flash memory, and exchange space for time, and has the dual advantages of performance improvement and cost reduction.

此外，藉由機率神經網路模型的運算，可令自行車加速平順，減少暴衝或轉速不足等不舒適的感覺。 In addition, the calculation of the probabilistic neural network model can make the bicycle accelerate smoothly and reduce the uncomfortable feeling such as overshoot or insufficient speed.

請配合圖1一併參閱圖3，圖3為本發明之踏板感測式之自行車驅動裝置之第二實施例之方塊圖。第二實施例與第一實施例之間的差異僅在於更包含顯示裝置30，因此下文主要針對顯示裝置30的部分進行描述，其餘部分則不再贅述。 Please refer to FIG. 3 together with FIG. 1. FIG. 3 is a block diagram of a second embodiment of the pedal sensing type bicycle driving device of the present invention. The difference between the second embodiment and the first embodiment is only that the display device 30 is further included, so that the description of the portion of the display device 30 will be mainly described below, and the rest will not be described again.

本發明之踏板感測式之自行車驅動裝置更可包含顯示裝置30，顯示裝置30係以無線傳輸方式從驅動裝置20接收並顯示轉速、踏頻及壓力。其中，無線傳輸方式可例如為無線網路通信的工業標準(Wireless fidelity，Wi-Fi)、藍芽(Bluetooth)、紅外線(Infrared Radiation，IR)、無線射頻(Radio Frequency，RF)或群蜂技術(Zigbee)，且顯示裝置30可例如為智慧型手機、智慧型穿戴裝置、顯示螢幕(如LCD)等，令使用者可即時接收並查看轉速、踏頻及壓力，藉此調整使用者騎乘的騎乘方式。 The pedal-sensing bicycle driving device of the present invention may further include a display device 30 that receives and displays the rotational speed, the cadence, and the pressure from the driving device 20 in a wireless transmission manner. among them, The wireless transmission method may be, for example, a wireless fidelity (Wi-Fi), a Bluetooth, an infrared ray (IR), a radio frequency (RF), or a group bee technology (Zigbee). And the display device 30 can be, for example, a smart phone, a smart wearable device, a display screen (such as an LCD), etc., so that the user can instantly receive and view the rotation speed, the cadence and the pressure, thereby adjusting the ride of the user. Multiply the way.

上述所揭露的各個實施例僅為例示性，而非為限制性。任何未背離本發明之精神與範疇，而對本發明所揭露之實施例進行的等效修改或變更，皆應包含於後附之申請專利範圍中。 The various embodiments disclosed above are illustrative only and not limiting. Equivalent modifications or variations of the embodiments of the present invention are intended to be included within the scope of the appended claims.

Claims

一種踏板感測式之自行車驅動裝置，其包含：一踏板，係可拆卸式設置於一自行車之一踏桿上，該踏板係配置以感測一使用者騎乘該自行車並踩踏該踏板時之一踏頻及一壓力；以及一驅動裝置，係可拆卸式設置於該自行車之一車輪上，該驅動裝置係配置以接收該踏頻及該壓力並感測該車輪之一轉速，以對該轉速、該踏頻及該壓力進行運算，進而輸出一最適輔助動力來驅動該車輪，其中該驅動裝置係將該轉速、該踏頻及該壓力作為一感測資料輸入一機率神經網路模型進行運算，該機率神經網路模型係依據該感測資料與一訓練資料之間的相似值高低來判斷並計算該最適輔助動力。 A pedal-sensing bicycle driving device comprising: a pedal detachably disposed on a pedal of a bicycle, the pedal configured to sense a user riding the bicycle and stepping on the pedal a stepping frequency and a pressure; and a driving device detachably disposed on one of the wheels of the bicycle, the driving device configured to receive the cadence and the pressure and sense a rotational speed of the wheel to The rotational speed, the cadence and the pressure are calculated, and an optimal auxiliary power is output to drive the wheel, wherein the driving device inputs the rotational speed, the cadence and the pressure as a sensing data into a probability neural network model. The calculation, the probability neural network model determines and calculates the optimal auxiliary power based on the similarity between the sensing data and a training data.

如申請專利範圍第1項所述之踏板感測式之自行車驅動裝置，其中該踏板上更設有一第一控制單元及一壓力感測單元，該壓力感測單元係電性連接該第一控制單元，以依據該使用者踩踏該壓力感測單元時所產生之一電阻變化來計算該壓力。 The pedal-sensing bicycle driving device according to claim 1, wherein the pedal is further provided with a first control unit and a pressure sensing unit, wherein the pressure sensing unit is electrically connected to the first control The unit calculates the pressure according to a change in resistance generated when the user steps on the pressure sensing unit.

如申請專利範圍第2項所述之踏板感測式之自行車驅動裝置，其中該踏板上更設有一踏頻感測單元，該踏頻感測單元係電性連接該第一控制單元，以依據該踏桿轉動時所產生之一電壓變化次數來計算該踏頻。 The pedal-sensing bicycle driving device according to the second aspect of the invention, wherein the pedal is further provided with a stepping frequency sensing unit electrically connected to the first control unit to The cadence is calculated by the number of voltage changes generated when the pedal is rotated.

如申請專利範圍第3項所述之踏板感測式之自行車驅動裝置，其中該踏板上更設有一第一無線傳輸單元，該第一無線傳輸單元係電性連接該第一控制單元，以藉由一無線傳輸方式傳送該壓力及該踏頻至該驅動裝置。 The pedal-sensing bicycle driving device of claim 3, wherein the pedal is further provided with a first wireless transmission unit, the first wireless transmission unit is electrically connected to the first control unit, The pressure and the cadence are transmitted to the drive device by a wireless transmission.

如申請專利範圍第4項所述之踏板感測式之自行車驅動裝置，其中該驅動裝置上更設有一第二控制單元及一第二無線傳輸單元，該第二無線傳輸單元係電性連接該第二控制單元，以藉由該無線傳輸方式接收該壓力及該踏頻。 The pedal-sensing bicycle driving device of claim 4, wherein the driving device further comprises a second control unit and a second wireless transmission unit, wherein the second wireless transmission unit is electrically connected to the bicycle driving device. The second control unit receives the pressure and the cadence by the wireless transmission mode.

如申請專利範圍第5項所述之踏板感測式之自行車驅動裝置，其中該驅動裝置上更設有一轉速感測單元，該轉速感測單元係電性連接該第二控制單元，以依據該車輪轉動時所產生之一電壓變化來計算該轉速。 The pedal-sensing bicycle driving device according to the fifth aspect of the invention, wherein the driving device is further provided with a rotation speed sensing unit electrically connected to the second control unit to The speed is calculated by a voltage change generated when the wheel rotates.

如申請專利範圍第6項所述之踏板感測式之自行車驅動裝置，其中該驅動裝置上更設有一驅動馬達，該驅動馬達係電性連接該第二控制單元並傳動連接該車輪，以依據該最適輔助動力驅動該車輪轉動。 The pedal-sensing bicycle driving device according to claim 6, wherein the driving device further comprises a driving motor electrically connected to the second control unit and driving the wheel to be The optimum auxiliary power drives the wheel to rotate.

如申請專利範圍第1項所述之踏板感測式之自行車驅動裝置，更包含一顯示裝置，該顯示裝置係以一無線傳輸方式從該驅動裝置接收並顯示該轉速、該踏頻及該壓力。 The pedal-sensing bicycle driving device according to claim 1, further comprising a display device that receives and displays the rotational speed, the cadence and the pressure from the driving device in a wireless transmission manner. .