A method and system for energy management to improve the cycling experience

Abstract

The application discloses an energy management method and system for improving riding experience, which detects the motor output torque of an electric bicycle, the acceleration and angular velocity of the electric bicycle, and the rotation angle of the motor at any moment, calculates the posture of the electric bicycle in a world coordinate system through the acceleration and angular velocity of the electric bicycle in a sensor coordinate system, calculates the load condition of the electric bicycle through the output torque change of a direct-current brushless motor and the acceleration of the electric bicycle in the sensor coordinate system, calculates the friction coefficient between the electric bicycle and the road surface through the acceleration of the electric bicycle in the sensor coordinate system, the posture angle of the electric bicycle in the world coordinate system, the load condition of the electric bicycle, and the output torque of the direct-current brushless motor, and integrates the load condition of the electric bicycle and the friction coefficient between the electric bicycle and the road surface into the state equation of a control scheme, so that the energy management system of the electric bicycle has stronger environmental adaptability, and the riding experience of a rider is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of electric bicycles, and particularly relates to an energy management system for improving riding experience. In particular, it relates to an energy management system that detects and predicts road condition information and load conditions through an inertial measurement unit and a torque sensor, and controls power output based thereon to improve the riding experience of a rider and extend the endurance capability. BACKGROUND

[0002] At present, electric bicycles have become an important tool for people to travel due to their high cost performance, ease of use and convenience. There are generally three riding modes for electric bicycles: electric vehicles, power-assisted bicycles and bicycles. In daily use, the electric vehicle mode is the most common. At present, electric bicycles generally use a direct-current brushless motor as a power source, install a position sensor inside for detecting the rotor position, and use an electronic switching circuit for commutation. Generally, PWM is used for control. When the rider turns the handlebar, the duty cycle of the PWM signal changes, thereby changing the voltage at both ends of the motor armature winding, causing the motor output torque to change, thereby achieving the purpose of speed regulation. However, single PWM control makes it impossible for the electric bicycle to automatically adapt to different road conditions and loads in a timely manner, and the rider needs to manually turn the handlebar to adjust the speed, which not only greatly affects the riding experience of the rider, but also causes power waste to a certain extent due to the frequent changes in speed and mismatched energy input, greatly reducing the endurance capability of the electric bicycle.

[0003] At present, there are schemes that use speed sensors and torque sensors to detect the driving speed of electric bicycles and the load of the motor, and adjust the motor input according to the real-time output power and speed of the motor. However, this method has a certain lag in theory, i.e., after the electric bicycle motor completes the adjustment, the electric bicycle has already driven away from the local section. However, the above motor input adjustment method can adjust the input and improve the riding experience when the road condition is stable. However, under different load and road conditions, the existing control scheme may not achieve the desired effect. The problems that may be encountered by the control method under different load and road conditions are described as follows: The acceleration of the electric bicycle is the resultant force received by the electric bicycle divided by the total mass of the electric bicycle and its load. Changes in the total mass caused by different loads and changes in the force received by the electric bicycle caused by different road conditions will cause inconsistencies in the acceleration of the electric bicycle under the same motor torque output, i.e., the same motor output torque detected by the torque sensor may result in different accelerations of the electric bicycle, which will have a greater impact on the transient response of the motor, reduce the stability and rapidity of the control system, and even make the riding experience of the rider unable to achieve the desired effect. SUMMARY

[0004] The application provides an energy management method and system for improving riding experience, and solves the problem of poor riding experience caused by single PWM control.

[0005] In order to achieve the above-mentioned purpose, the application adopts the following technical solutions:

[0006] An energy management method for improving riding experience, comprising the following steps:

[0007] S1, collecting the acceleration and angular velocity of the electric bicycle in the sensor coordinate system; collecting the motor output torque and the motor output shaft rotation angle;

[0008] S2, calculating the displacement of the electric bicycle in the world coordinate system and the road undulation passed by the bicycle according to the acceleration and angular velocity of the electric bicycle in the sensor coordinate system;

[0009] According to the motor output rotation angle, the driving distance of the electric bicycle is calculated;

[0010] According to the road undulation passed by the bicycle and the driving distance of the electric bicycle, the undulation of the future road is predicted;

[0011] S3, calculating the prediction result confidence coefficient according to the road undulation passed by the bicycle and the undulation of the future road;

[0012] S4, obtaining the motor torque output adjustment scheme according to the prediction result confidence coefficient, the friction coefficient between the electric bicycle and the road, and the total mass of the electric bicycle and its load;

[0013] S5, obtaining the control scheme of the PWM signal duty cycle according to the motor torque output adjustment scheme and the motor input-output characteristic curve.

[0014] Further, in step S2, calculating the displacement of the electric bicycle in the world coordinate system and the road undulation passed by the bicycle according to the acceleration and angular velocity of the electric bicycle in the sensor coordinate system comprises the following steps:

[0015] SA1, calculating the initial pitch angle, initial roll angle and initial yaw angle of the electric bicycle according to the acceleration of the electric bicycle in the sensor coordinate system at the initial time;

[0016] SA2, calculating the attitude angle of the electric bicycle at any time according to the initial pitch angle, initial roll angle and initial yaw angle;

[0017] SA3, calculating the acceleration of the electric bicycle in the z-axis direction of the world coordinate system at any time according to the attitude angle of the electric bicycle at any time ;

[0018] SA4. Calculate the acceleration of the electric bicycle along the z-axis in the world coordinate system at any given moment. The velocity of the electric bicycle along the z-axis in the world coordinate system;

[0019] SA5, based on any time Calculate the velocity of the electric bicycle in the z-axis direction in the world coordinate system and the displacement of the electric bicycle in the z-axis direction in the world coordinate system at time t.

[0020] SA6, based on any time Calculate the displacement of the electric bicycle along the z-axis in the world coordinate system at any given moment and the distance traveled by the electric bicycle. The displacement of the electric bicycle along the z-axis in the world coordinate system; at any time... The displacement of the electric bicycle along the z-axis in the world coordinate system represents the road undulations traversed by the electric bicycle.

[0021] Furthermore, in step S2, predicting the future road undulations based on the road undulations traversed by the bicycle and the distance traveled by the electric bicycle includes the following steps:

[0022] SB1, based on the motor at any given time Calculate the distance traveled by an electric bicycle based on its rotation angle. :

[0023] SB2. Let the latest time of the electric bicycle's movement be... Taking the distance at several time points before the latest time, and using Chebyshev polynomials for optimal squared approximation, the result is:

[0024]

[0025] in, , All are intermediate variables;

[0026] Predicted The following information pertains to the road undulations that the electric bicycle will soon pass through, and the z-axis coordinate of the electric bicycle in the world coordinate system. for: .

[0027] Furthermore, in step S3, the confidence coefficient of the prediction result is... The calculation formula is:

[0028]

[0029] in, As an intermediate variable, for The displacement of the electric bicycle along the z-axis in the world coordinate system at any given time. for The displacement of the electric bicycle along the z-axis in the world coordinate system at any given moment.

[0030] Furthermore, step S4 includes the following steps:

[0031] S4.1 Calculate the two optimal motor torque output schemes using optimal control theory. and ,in The motor torque output scheme is calculated based on the predicted road undulations. The optimal control model for the motor torque output scheme calculated based on the current road undulations is as follows:

[0032] The state equation of the controlled system is:

[0033]

[0034] in, for The distance traveled by the electric bicycle at any given time. This refers to the transmission ratio from the drive wheel of an electric bicycle to the DC brushless motor. The radius of the drive wheel of the electric bicycle. The total mass of the electric bicycle and its load. It is the acceleration due to gravity. For electric bicycles The coefficient of friction at time t, As an intermediate variable, For electric bicycles The pitch angle at any given moment;

[0035] The boundary conditions are:

[0036]

[0037] in, for The distance traveled by the electric bicycle at any given time. for, for The distance traveled by the electric bicycle at any given time. The distance traveled by the electric bicycle at the end of the time. For terminal speed;

[0038] The control constraints are:

[0039]

[0040] in, This is the maximum torque that a brushless DC motor can output.

[0041] The performance indicators are:

[0042] ;

[0043] in, For performance indicators;

[0044] S4.2, Based on the confidence coefficient For the optimal motor torque output scheme and By integrating these components, the final motor torque output adjustment scheme is obtained. :

[0045] .

[0046] Furthermore, in step S4.1, the coefficient of friction f μ ( t Calculated using the following formula:

[0047]

[0048] For electric bicycles The pitch angle at any given moment.

[0049] Furthermore, in step S4.1, the total mass of the electric bicycle and its load... The calculation formula is:

[0050]

[0051] in: This refers to the change in the output torque of the motor in an electric bicycle. This refers to the transmission ratio from the drive wheel of an electric bicycle to the DC brushless motor. The radius of the drive wheel of the electric bicycle. , , These represent the changes in acceleration of the electric bicycle in three directions within the sensor coordinate system.

[0052] Furthermore, in step S5, the control scheme for the PWM signal duty cycle is obtained through the following formula. :

[0053]

[0054] in: The motor output shaft speed is At that time, it is the ratio of the PWM signal duty cycle to the electrode output torque.

[0055] Furthermore, in step S5, the motor input-output characteristic curve used is the modified input-output characteristic curve, which is modified based on the motor output torque, the motor rotation angle at any time, and the PWM signal duty cycle of the brushless DC motor.

[0056] An energy management system for improving the riding experience includes a mass detection button, an inertial measurement unit, a torque sensor, and a signal processing and control module. The output terminals of the electric bicycle handlebars, mass detection button, inertial measurement unit, and torque sensor are all connected to the input terminal of the signal processing and control module, and the output terminal of the signal processing and control module is connected to the input terminal of the motor.

[0057] The electric bicycle handlebars are used to control the speed of the electric bicycle.

[0058] The inertial measurement unit is used to detect the acceleration and angular velocity of an electric bicycle in the sensor coordinate system;

[0059] Torque sensors are used to detect the output torque of a motor at any given time;

[0060] The signal processing and control module is used to process the signals from the inertial measurement unit, torque sensor, and Hall sensor to predict the road conditions and speed of the electric bicycle at any given time. Based on this, the module modifies the duty cycle of the output PWM signal to keep the electric bicycle's speed constant.

[0061] Compared with the prior art, the present invention has at least the following beneficial technical effects:

[0062] 1. This invention detects the output torque, acceleration, and angular velocity of the electric bicycle's motor, as well as the rotation angle of the brushless DC motor at any given time. The bicycle's attitude in the world coordinate system is calculated using its acceleration and angular velocity in the sensor coordinate system. The load condition of the electric bicycle is calculated using the change in the brushless DC motor's output torque and the acceleration in the sensor coordinate system. The friction coefficient between the electric bicycle and the road surface is calculated using the acceleration in the sensor coordinate system, the attitude angle in the world coordinate system, the load condition, and the output torque of the brushless DC motor. These factors are then integrated into the state equations of the control scheme, giving the electric bicycle's energy management system greater environmental adaptability and improving the rider's riding experience.

[0063] 2. This invention detects the acceleration and angular velocity of an electric bicycle and the rotation angle of a brushless DC motor at any given time. It calculates the bicycle's attitude in the world coordinate system using the acceleration and angular velocity in the sensor coordinate system. A modified Hamming prediction-correction formula is used to calculate the bicycle's velocity and displacement in the world coordinate system. The travel distance of the electric bicycle is calculated using the detected rotation angle of the brushless DC motor at any given time. Function optimal approximation is used to fit the bicycle's displacement in the z-direction and the travel distance in the world coordinate system. Interpolation is used to predict future road undulations. The predicted road conditions and the actual road conditions over a recent period are compared to calculate a confidence coefficient, which is then incorporated into the state equation of the control scheme. Because the resulting control scheme considers the predicted future road conditions, it can better and more promptly adapt to the upcoming road conditions, solving the time lag problem of existing technologies.

[0064] Furthermore, by using optimal control theory and incorporating factors such as the load of the electric bicycle, the friction coefficient with the road surface, and future road undulations into the state equation, the optimal motor control scheme is solved, which greatly improves the speed and stability of energy input control during the electric bicycle's operation.

[0065] Furthermore, since the control scheme is highly compatible with the load conditions and road conditions of the electric bicycle during the control process, and the control scheme has extremely high speed and stability, the present invention reduces power waste to a certain extent. Attached Figure Description

[0066] Figure 1 This is a structural block diagram of the present invention.

[0067] Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0068] To make the objectives and technical solutions of this invention clearer and easier to understand, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0069] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more. In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0070] Reference Figure 1 An energy management system for improving the riding experience of electric bicycles mainly includes an electric bicycle handlebar 1, a mass detection button 2, an inertial measurement unit 3, a torque sensor 4, a signal processing and control module 5, and a DC brushless motor 6. The signal processing and control module consists of a handlebar signal processing circuit 51, a mass detection button signal processing circuit 52, a sensor signal processing circuit 53, an AD conversion circuit module 54, a microcontroller 55, and a switching power supply circuit 56. The DC brushless motor 6 has a built-in Hall sensor 61.

[0071] The signal output terminal of the electric bicycle handlebar 1 is connected to the input terminal of the handlebar signal processing circuit 51. The output terminal of the quality detection button 2 is connected to the input terminal of the quality detection button signal processing circuit 52. The signal output terminals of the inertial measurement unit 3, the torque sensor 4, and the Hall sensor 61 are all connected to the input terminal of the sensor signal processing circuit 53. The output terminals of the handlebar signal processing circuit 51, the quality detection button signal processing circuit 52, and the sensor signal processing circuit 53 are connected to the input terminal of the AD conversion circuit module 54. The output terminal of the AD conversion circuit module 54 is connected to the input terminal of the microcontroller 55. The output terminal of the microcontroller 55 is connected to the input terminal of the switching power supply circuit 56. The output terminal of the switching power supply circuit 56 is connected to the input terminal of the DC brushless motor 6.

[0072] The handlebar 1 of the electric bicycle is used to control the speed of the electric bicycle by controlling the output torque of the motor. When the speed reaches a stable value, its size is... The rider manually rotates the electric bicycle handlebars 1 to send a signal to the electric bicycle, thereby controlling the speed of the electric bicycle, and the rotation angle of the electric bicycle handlebars is proportional to the speed of the electric bicycle.

[0073] Optionally, the handlebar 1 of the electric bicycle can be a Hall effect throttle with a built-in magnetic strip and Hall element. When the handlebar 1 of the electric bicycle is rotated, the output voltage of the Hall element increases.

[0074] Inertial Measurement Unit 3 is a six-axis inertial measurement unit, installed and fixed on the electric bicycle. The x-axis of the sensor coordinate system of Inertial Measurement Unit 3 is parallel to the direction of the electric bicycle's linear motion in the world coordinate system, and the z-axis is parallel to the plane containing the rear wheel of the electric bicycle. Inertial Measurement Unit 3 is used to detect the acceleration of the electric bicycle in the sensor coordinate system. , , and angular velocity , , It is used to calculate the attitude of the electric bicycle in the world coordinate system and its displacement in the z-axis direction. The attitude of an electric bicycle in a world coordinate system includes pitch angle. Roll angle and yaw angle The displacement of the electric bicycle along the z-axis in the world coordinate system. It can also represent the road surface undulations traversed by an electric bicycle, where the world coordinate system is a Cartesian left-handed coordinate system, and the z-axis direction is parallel to the local gravitational acceleration. The direction is opposite, the x-axis direction is the same as... The projection directions on the XOY plane are the same. The electric bicycle's attitude and displacement along the z-axis in the world coordinate system. The specific calculation method is as follows:

[0075] The initial acceleration of the electric bicycle in the sensor coordinate system was measured by inertial measurement unit 3. , , Calculate the initial pitch angle of the electric bicycle. Initial roll angle and initial yaw angle :

[0076]

[0077]

[0078]

[0079] Using quaternions The initial pose of the electric bicycle is represented by the following calculation method:

[0080]

[0081] The quaternion representing pose is updated using the first-order Runge-Kutta method:

[0082]

[0083] in: The sampling time of the inertial measurement unit. , , , , All of these are intermediate variables.

[0084] Transform quaternions into arbitrary time intervals attitude angle

[0085]

[0086] According to any time The attitude rotation angle and the inertial measurement unit 3 detected , , Calculate any time The acceleration of the electric bicycle in the z-axis direction in the world coordinate system :

[0087]

[0088] in: This is the acceleration due to gravity.

[0089] Based on the acceleration of the electric bicycle along the z-axis in the world coordinate system at any given moment, the modified Hamming prediction-correction formula is used to calculate the acceleration at any given moment. The velocity of the electric bicycle along the z-axis in the world coordinate system :

[0090]

[0091] in: , , All of these are intermediate variables.

[0092] Based on the velocity of the electric bicycle along the z-axis in the world coordinate system at any given moment, the modified Hamming prediction-correction formula is used to calculate the velocity at any given moment. The displacement of the electric bicycle along the z-axis in the world coordinate system :

[0093]

[0094] Road undulations and the z-axis displacement of the electric bicycle in the world coordinate system same.

[0095] Torque sensor 4 is mounted on the output shaft of brushless DC motor 6 to detect the torque of brushless DC motor 6 at any given time. Output torque Torque sensor 4 is a bridge-type strain torque sensor that outputs a voltage signal.

[0096] The quality detection button 2 is used to send a start signal to detect the total mass of the electric bicycle and its load. When pressed, the signal from the quality detection button 2 is processed by the quality detection button signal processing circuit 52 and the AD conversion circuit 54, and then input to the microcontroller 55. The duty cycle of the PWM signal output by the microcontroller 55 increases slightly momentarily and then returns to normal. The change in torque produced by the DC brushless motor 6 is... The changes in acceleration of the electric bicycle in the three directions in the sensor coordinate system are respectively , , The total mass of the electric bicycle and its load, calculated by the microcontroller 55. for:

[0097]

[0098] in: The transmission ratio from the drive wheel of the electric bicycle to the DC brushless motor 6; This is the radius of the drive wheel of the electric bicycle.

[0099] Hall sensor 61 is used to detect the DC brushless motor 6 at any time. rotation angle The results are then fed back to the signal processing and control module, enabling the 55 microcontroller to output the correct PWM signal.

[0100] The signal processing and control module 5 processes the signals from the inertial measurement unit 3, torque sensor 4, and Hall sensor 61 to calculate and predict the electric bicycle and its load mass, road conditions at any given time, friction coefficient between the electric bicycle and the road, and speed. Based on this, it modifies the duty cycle of the output PWM signal to maintain a constant speed for the electric bicycle, thereby improving the rider's experience. The handlebar signal processing circuit 51 converts the rotation angle of the electric bicycle handlebar 1 into a voltage signal compatible with the input of the AD conversion circuit module 54, and amplifies, reduces, or biases the output voltage signal of the electric bicycle handlebar 1 to the input voltage range of the AD conversion circuit module 54.

[0101] The quality detection button signal processing circuit 52 is used to convert the signal emitted by the quality detection button 2 into a voltage signal compatible with the input of the AD conversion circuit module 54, and to amplify, reduce or bias the signal of the quality detection button 2 to the input voltage range of the AD conversion circuit module 54.

[0102] The sensor signal processing circuit 53 filters and amplifies the output signals of the inertial measurement unit 3, torque sensor 4 and Hall sensor 61, and then converts them into a voltage signal compatible with the input of the AD conversion circuit module 54.

[0103] The AD conversion circuit module 54 processes the signal-processed electric vehicle handlebar output signal 51, quality detection button output signal 52, and sensor signal processing circuit 53 output signal, converting their analog signals into digital signals compatible with the microcontroller 55, and transmitting the digital signals to the input terminal of the microcontroller 55.

[0104] The 55 microcontroller is the core of the entire signal processing and control module. An AVR series microcontroller can be selected, specifically the ATmega8.

[0105] The microcontroller 55 can calculate the electric bicycle's position at any moment in the world coordinate system based on the acceleration and angular velocity signals measured by the inertial measurement unit 3. The attitude and displacement in the z-axis direction The displacement of the electric bicycle along the z-axis at any moment in the world coordinate system. It can also be used to describe the undulations of the road surface that a bicycle travels on.

[0106] The microcontroller 55 can receive the signal from the mass detection button 2 and then process the signals from the inertial measurement unit 3 and the torque sensor 4 to calculate the total mass of the electric bicycle and its load.

[0107] The 55 microcontroller can evaluate the coefficient of friction between the electric bicycle and the road surface. ( t )for:

[0108]

[0109] The 55 microcontroller can make a small-scale prediction of the road undulations of the future based on the calculated road undulations of the electric bicycle, and obtain the confidence coefficient of the prediction result by comparing the results.

[0110] The method for predicting road undulations is as follows:

[0111] According to Hall sensor 61, the DC brushless motor 6 is detected at any time. rotation angle Calculate the distance traveled by the electric bicycle :

[0112]

[0113] The latest time the electric bicycle was in motion is ,Pick , , ... There are 10 points in total. The optimal squared approximation is performed using Chebyshev polynomials, and the result is:

[0114]

[0115] in, , All of these are intermediate variables.

[0116] intermediate variables It satisfies the following recurrence relation:

[0117]

[0118]

[0119]

[0120] Then the prediction The following information pertains to the road undulations that the electric bicycle will soon pass through, and the z-axis coordinate of the electric bicycle in the world coordinate system. for:

[0121]

[0122] The microcontroller 55 compares the predicted road condition information with the actual road undulations in that section and obtains the confidence coefficient of the prediction result for the next time interval. The confidence coefficient ranges from 0 to 1. The closer the confidence coefficient is to 1, the more accurate the prediction and the higher the reliability of the prediction for the next time interval. (Prediction Confidence Coefficient) The calculation formula is:

[0123]

[0124] Based on the calculated current and predicted road undulations, the friction coefficient between the electric bicycle and the road, the output signal of the torque sensor 4, the acceleration signal output by the inertial measurement unit 3, the rotation signal of the electric bicycle handlebar 1, and the input-output characteristic curve of the DC brushless motor 6 stored in the microcontroller, the microcontroller 55 uses optimal control theory to calculate two optimal torque output schemes for the DC brushless motor 6. and ,in The proposed DC brushless motor torque output scheme is calculated based on predicted road undulations. The optimal control model for the 6-torque output scheme of the brushless DC motor, calculated based on the current road undulations, is as follows:

[0125] State equations of the controlled system:

[0126]

[0127] in, This represents the latest time during the riding process of the electric bicycle. Boundary conditions:

[0128]

[0129] in, The start time, size and equal; For terminal time; For terminal speed.

[0130] Control constraints:

[0131]

[0132] in, This is the maximum torque that a brushless DC motor can output.

[0133] Performance metrics:

[0134]

[0135] in, For performance indicators, appropriate ones should be selected. and make Minimum.

[0136] The single-chip microcomputer 55 is based on the confidence coefficient Based on the magnitude of the torque output, the two torque output adjustment schemes for the brushless DC motor mentioned above are integrated to obtain the final torque output adjustment scheme for the brushless DC motor. :

[0137]

[0138] Adjustment scheme for PWM signal duty cycle for:

[0139]

[0140] in: The output shaft speed of the brushless DC motor is 6. At that time, the ratio of the PWM signal duty cycle to the electrode output torque is related to the input-output characteristics of the DC brushless motor 6 itself.

[0141] The microcontroller 55 can determine the position of the brushless DC motor 6 at any time based on the Hall sensor 61. rotation angle Calculate the electric bicycle at any time driving speed :

[0142]

[0143] The 55 microcontroller can implement a final PWM duty cycle adjustment scheme. Three-phase PWM signals are output from the three output ports and transmitted to the switching power supply circuit 56.

[0144] The microcontroller 55 corrects the input-output characteristics of the brushless DC motor 6 based on the output torque of the brushless DC motor 6 detected by the torque sensor 4, the rotation angle of the brushless DC motor 6 at any time detected by the Hall sensor 61, and the duty cycle of the PWM signal output by the microcontroller 55.

[0145] The switching power supply circuit 56 consists of three identical switching power supplies, which boost the PWM signals from the three output ports of the microcontroller 55 to the rated voltage of the brushless DC motor 6, thus supplying power to the brushless DC motor 6.

[0146] The DC brushless motor 6 has a built-in Hall sensor 61 and serves as the power source for the electric bicycle. Its input and output characteristics need to be tested in advance, and the input and output characteristics of the DC brushless motor 6 obtained from the test are stored in the microcontroller 55.

[0147] On the other hand, refer to Figure 2This invention provides an energy management method for improving the riding experience of electric bicycles, comprising the following steps:

[0148] S1. Collect the acceleration and angular velocity of the electric bicycle in the sensor coordinate system; collect the motor output torque and the rotation angle of the motor output shaft;

[0149] S2. Calculate the displacement of the electric bicycle in the world coordinate system and the road undulations traversed by the bicycle based on the acceleration and angular velocity of the electric bicycle in the sensor coordinate system.

[0150] Calculate the distance traveled by the electric bicycle based on the rotation angle output by the motor.

[0151] Predict future road undulations based on the road undulations traversed by bicycles and the distance traveled by electric bicycles.

[0152] S3. Calculate the confidence coefficient of the prediction result based on the road undulations that the bicycle has traveled and the future road undulations.

[0153] S4. Based on the confidence coefficient of the prediction results, the friction coefficient between the electric bicycle and the road surface, and the total mass of the electric bicycle and its load, a motor torque output adjustment scheme is obtained.

[0154] S5. Based on the motor torque output adjustment scheme and the motor input-output characteristic curve, obtain the control scheme for the PWM signal duty cycle.

[0155] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. An energy management method for improving the cycling experience, characterized in that, Includes the following steps: S1. Collect the acceleration and angular velocity of the electric bicycle in the sensor coordinate system; Collect the motor output torque and the motor output shaft rotation angle; S2. Calculate the displacement of the electric bicycle in the world coordinate system and the road undulations traversed by the bicycle based on the acceleration and angular velocity of the electric bicycle in the sensor coordinate system. Calculate the distance traveled by the electric bicycle based on the rotation angle output by the motor. Predict future road undulations based on the road undulations traversed by bicycles and the distance traveled by electric bicycles. S3. Calculate the confidence coefficient of the prediction result based on the road undulations that the bicycle has traveled and the future road undulations. S4. Based on the confidence coefficient of the prediction results, the friction coefficient between the electric bicycle and the road surface, and the total mass of the electric bicycle and its load, a motor torque output adjustment scheme is obtained. S5. Based on the motor torque output adjustment scheme and the motor input-output characteristic curve, obtain the control scheme for the PWM signal duty cycle.

2. The energy management method for improving cycling experience according to claim 1, characterized in that, In step S2, calculating the displacement of the electric bicycle in the world coordinate system and the road undulations traversed by the bicycle based on the acceleration and angular velocity of the electric bicycle in the sensor coordinate system includes the following steps: SA1. Calculate the initial pitch angle, initial roll angle and initial yaw angle of the electric bicycle based on the acceleration of the electric bicycle in the sensor coordinate system at the initial moment. SA2. Calculate the electric bicycle's position at any given moment based on the initial pitch angle, initial roll angle, and initial yaw angle. attitude angle; SA3, based on any time of day of the electric bicycle Attitude angle calculation at any time The acceleration of the electric bicycle along the z-axis in the world coordinate system; SA4. Calculate the acceleration of the electric bicycle along the z-axis in the world coordinate system at any given moment. The velocity of the electric bicycle along the z-axis in the world coordinate system; SA5, based on any time Calculate the velocity of the electric bicycle in the z-axis direction in the world coordinate system and the displacement of the electric bicycle in the z-axis direction in the world coordinate system at time t. SA6, based on any time Calculate the displacement of the electric bicycle along the z-axis in the world coordinate system at any given moment and the distance traveled by the electric bicycle. The displacement of the electric bicycle along the z-axis in the world coordinate system; at any time... The displacement of the electric bicycle along the z-axis in the world coordinate system represents the road undulations traversed by the electric bicycle.

3. The energy management method for improving cycling experience according to claim 1, characterized in that, Step S2, predicting future road undulations based on the road undulations traversed by the bicycle and the distance traveled by the electric bicycle, includes the following steps: SB1, based on the motor at any given time Calculate the distance traveled by an electric bicycle based on its rotation angle. : SB2. Let the latest time of the electric bicycle's movement be... Taking the distance at several time points before the latest time, and using Chebyshev polynomials for optimal squared approximation, the result is: in, , All are intermediate variables; Predicted The following information pertains to the road undulations that the electric bicycle will soon pass through, and the z-axis coordinate of the electric bicycle in the world coordinate system. for: .

4. The energy management method for improving cycling experience according to claim 1, characterized in that, In step S3, the confidence coefficient of the prediction result The calculation formula is: in, As an intermediate variable, for The displacement of the electric bicycle along the z-axis in the world coordinate system at any given time. Let t be the displacement of the electric bicycle along the z-axis in the world coordinate system at time t.

5. The energy management method for improving cycling experience according to claim 1, characterized in that, Step S4 includes the following steps: S4.1 Calculate the two optimal motor torque output schemes using optimal control theory. and ,in The motor torque output scheme is calculated based on the predicted road undulations. The optimal control model for the motor torque output scheme calculated based on the current road undulations is as follows: The state equation of the controlled system is: in, for The distance traveled by the electric bicycle at any given time. This refers to the transmission ratio from the drive wheel of an electric bicycle to the DC brushless motor. The radius of the drive wheel of the electric bicycle. The total mass of the electric bicycle and its load. It is the acceleration due to gravity. For electric bicycles The coefficient of friction at time t, As an intermediate variable, For electric bicycles The pitch angle at any given moment; The boundary conditions are: in, for The distance traveled by the electric bicycle at any given time. for, for The distance traveled by the electric bicycle at any given time. The distance traveled by the electric bicycle at the end of the time. For terminal speed, For terminal time; The control constraints are: in, This is the maximum torque that a brushless DC motor can output. The performance indicators are: ； in, For performance indicators; S4.2, Based on the confidence coefficient For the optimal motor torque output scheme and By integrating these components, the final motor torque output adjustment scheme is obtained. : 。 6. The energy management method for improving cycling experience according to claim 5, characterized in that, In step S4.1, the coefficient of friction f μ ( t Calculated using the following formula: For electric bicycles The pitch angle at any given moment.

7. The energy management method for improving cycling experience according to claim 5, characterized in that, In step S4.1, the total mass of the electric bicycle and its load... The calculation formula is: in: This refers to the change in the output torque of the motor in an electric bicycle. This refers to the transmission ratio from the drive wheel of an electric bicycle to the DC brushless motor. The radius of the drive wheel of the electric bicycle. , , These represent the changes in acceleration of the electric bicycle in three directions within the sensor coordinate system.

8. The energy management method for improving cycling experience according to claim 1, characterized in that, In step S5, the control scheme for the PWM signal duty cycle is obtained using the following formula. : in: The motor output shaft speed is At that time, it is the ratio of the PWM signal duty cycle to the electrode output torque.

9. The energy management method for improving cycling experience according to claim 1, characterized in that, In step S5, the motor input-output characteristic curve used is the corrected input-output characteristic curve, which is corrected based on the motor output torque, the motor rotation angle at any time, and the PWM signal duty cycle.

10. An energy management system for improving the cycling experience, characterized in that, It includes an electric bicycle handlebar (1), a mass detection button (2), an inertial measurement unit (3), a torque sensor (4), and a signal processing and control module (5); the output terminals of the electric bicycle handlebar (1), mass detection button (2), inertial measurement unit (3), and torque sensor (4) are all connected to the input terminal of the signal processing and control module (5), and the output terminal of the signal processing and control module (5) is connected to the input terminal of the motor; The electric bicycle handlebar (1) is used to control the speed of the electric bicycle. The inertial measurement unit (3) is used to detect the acceleration and angular velocity of the electric bicycle in the sensor coordinate system; Torque sensor (4) is used to detect the output torque of the motor at any time; The signal processing and control module (5) is used to process the signals from the inertial measurement unit (3), torque sensor (4) and Hall sensor (61) to predict the road conditions and speed of the electric bicycle at any time, and modify the duty cycle of the output PWM signal based on this to keep the speed of the electric bicycle constant.

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