Electric power-assisted bicycle control method and device and electric power-assisted bicycle

Abstract

The invention discloses an electric power-assisted bicycle control method and device and an electric power-assisted bicycle, and relates to the technical field of electric power-assisted bicycle control. Target parameters and actual armature current are input; calculating a target armature current according to the target parameter; inputting the target armature current and the actual armature current into a # imgabs0 # controller, and outputting a motor control signal; and according to the motor control signal, the power-assisted torque of the electric power-assisted bicycle is adjusted. The # imgabs 1 # controller has the advantage of high response speed of # imgabs 2 # control and the characteristic of high anti-interference capability of # imgabs 3 # control, and can meet the control requirements of high dynamic nature and high robustness of the electric power-assisted bicycle.

Description

Technical Field

[0001] The present invention relates to the technical field of electric assist bicycle control, and particularly to an electric assist bicycle control method, device and electric assist bicycle. Background Art

[0002] Electric assist bicycles (E-bikes) are widely favored by consumers due to their advantages such as reliability, ease of riding, environmental friendliness and affordability. Compared with ordinary bicycles, electric assist bicycles can provide assistance to riders through motors, thereby helping riders overcome the obstacles of hills, slopes and rough terrains and complete more difficult riding challenges.

[0003] See Figure 1 For the torque sensor space vector schematic diagram in, during the riding process of an electric assist bicycle, the torque applied by the rider is not constant, but changes with the pedal position, gravity, inertia and muscle exertion. Since the applied torque is not a constant value, the control method is required to have the ability of fast dynamic response following. However, the existing technology generally controls the assist torque by monitoring the speed. This control method has a slow response speed and cannot stably follow, resulting in a poor assist effect. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide an electric assist bicycle control method, device and electric assist bicycle, which can improve the robustness of the system while quickly following the target armature current and optimize the control effect of the electric assist bicycle.

[0005] To achieve the above purpose, the embodiments of the present invention provide an electric assist bicycle control method, including: Input the target parameters and the actual armature current; Calculate the target armature current according to the target parameters; Input the target armature current and the actual armature current into a controller to output a motor control signal; Adjust the assist torque of the electric assist bicycle according to the motor control signal; Wherein, in the controller, the motor control signal is calculated by the following method: Input the target armature current and the actual armature current into an error amplifier to obtain a current following error; Input the current following error into the controller to obtain an initial reference current; Sum the initial reference current and a ramp compensation signal to obtain a target reference current; Input the target reference current and the actual armature current into a comparator to output a motor control signal.

[0006] As an improvement to the above solution, the target parameters include human factor data, slope, actual wheel speed, actual acceleration, applied torque, and assist torque; then, calculating the target armature current according to the target parameters includes: Calculate the target wheel speed and target acceleration according to the human factor data; According to the applied torque and the assist torque, with the goal of minimizing the human-machine hybrid output power, calculate the human-machine output ratio weight; Based on a hybrid strategy of feedforward and error feedback control, calculate the initial target armature current according to the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope; Multiply the human-machine output ratio weight and the initial target armature current to obtain the target armature current.

[0007] As an improvement to the above solution, the human-machine hybrid output power is calculated by the following formula: Where, represents the human-machine hybrid output power; represents the applied torque; represents the human-machine output ratio weight; represents the human-vehicle transmission speed ratio; represents the wheel damping coefficient; represents the pedal damping coefficient; represents the motor damping coefficient; represents the assist torque; represents the actual wheel speed.

[0008] As an improvement to the above solution, calculating the target wheel speed and target acceleration according to the human factor data includes: Generate an initial value of the wheel speed according to the human factor data; Substitute the initial value of the wheel speed into a preset wheel speed trajectory formula to obtain a target wheel speed trajectory formula for calculating the target wheel speed; Differentiate the target wheel speed trajectory formula to obtain a target acceleration trajectory formula for calculating the target acceleration.

[0009] As an improvement to the above solution, the human factor data includes heart rate, subjective score, fatigue index, and pedal frequency; then, generating the initial value of the wheel speed according to the human factor data includes: Calculate a first initial value of the wheel speed according to the heart rate; wherein, the heart rate and the first initial value of the wheel speed are negatively correlated; Calculate the initial value of the second-round speed according to the subjective score; wherein, the subjective score has a negative correlation with the initial value of the second-round speed; Calculate the initial value of the third-round speed according to the fatigue index; wherein, the fatigue index has a negative correlation with the initial value of the third-round speed; Calculate the initial value of the fourth-round speed according to the pedal frequency; wherein, the pedal frequency has a positive correlation with the initial value of the fourth-round speed; Perform weighted summation on the initial value of the first-round speed, the initial value of the second-round speed, the initial value of the third-round speed and the initial value of the fourth-round speed to obtain the initial value of the wheel speed.

[0010] As an improvement to the above solution, the wheel speed trajectory formula is shown as follows: Wherein, represents the target wheel speed at time represents the initial value of the wheel speed; represents the natural base; represents time; represents the time constant.

[0011] As an improvement to the above solution, for the hybrid strategy based on feedforward and error feedback control, calculate the initial target armature current according to the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration and the slope, including: Multiply the target wheel speed by the wheel speed feedforward control coefficient to obtain the first feedforward control current value; Multiply the target acceleration by the acceleration feedforward control coefficient to obtain the second feedforward control current value; Calculate the slope compensation control current value according to the slope; wherein, the slope compensation control current value has a positive correlation with the sine value of the slope; Calculate the wheel speed error between the target wheel speed and the actual wheel speed, and multiply the wheel speed error by the wheel speed error feedback coefficient to obtain the first error feedback control current value; Calculate the acceleration error between the target acceleration and the actual acceleration, and multiply the acceleration error by the acceleration error feedback coefficient to obtain the second error feedback control current value; Sum the first feedforward control current value, the second feedforward control current value, the slope compensation control current value, the first error feedback control current value and the second error feedback control current value to obtain the initial target armature current.

[0012] As an improvement of the above solution, the target acceleration satisfies the slope filtering and limiting constraint condition, and the target armature current satisfies the preset armature current constraint condition, where the armature current constraint condition includes at least one of an acceleration limiting condition, a motor capacity constraint condition, and an emergency braking interruption constraint condition.

[0013] To achieve the above object, an embodiment of the present invention further provides an electric assist bicycle control device, including: A parameter input module for inputting target parameters and an actual armature current; A target armature current calculation module for calculating a target armature current according to the target parameters; A boost torque calculation module for inputting the target armature current and the actual armature current to a controller to output a motor control signal, A boost torque control module for adjusting the boost torque of the electric assist bicycle according to the motor control signal; wherein, in the controller, the motor control signal is calculated by the following method: Inputting the target armature current and the actual armature current to an error amplifier to obtain a current following error; Inputting the current following error to the controller to obtain an initial reference current; Summing the initial reference current and a ramp compensation signal to obtain a target reference current; Inputting the target reference current and the actual armature current to a comparator to output a motor control signal.

[0014] To achieve the above object, an embodiment of the present invention further provides an electric assist bicycle, including an electric assist bicycle body and the electric assist bicycle control device according to any one of the above embodiments.

[0015] Compared with the prior art, the electric assist bicycle control method, device, and electric assist bicycle provided by the embodiments of the present invention input target parameters and an actual armature current; calculate a target armature current according to the target parameters; input the target armature current and the actual armature current to the controller to output a motor control signal; adjust the boost torque of the electric assist bicycle according to the motor control signal; wherein, in the controller, the motor control signal is calculated by the following method: inputting the target armature current and the actual armature current to an error amplifier to obtain a current following error; inputting the current following error to the The controller obtains an initial reference current; sums the initial reference current and a slope compensation signal to obtain a target reference current; inputs the target reference current and the actual armature current into a comparator, and outputs a motor control signal. In the embodiment of the present invention, the controller has both the advantages of fast control response speed and the characteristics of strong anti-interference ability of control, and can meet the control requirements of high dynamic performance and high robustness of the electric assist bicycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a schematic diagram of the space vector of the torque sensor provided by an embodiment of the present invention Figure 2 is a flowchart of a control method for an electric assist bicycle provided by an embodiment of the present invention; Figure 3 is a schematic diagram of a control system for an electric assist bicycle provided by an embodiment of the present invention; Figure 4 is provided by an embodiment of the present invention a schematic diagram of the controller; Figure 5 is a schematic diagram of slope compensation provided by an embodiment of the present invention; Figure 6 is a schematic diagram of the forces acting on an electric assist bicycle provided by an embodiment of the present invention; Figure 7 is a flowchart of a control method for an electric assist bicycle provided by another embodiment of the present invention; Figure 8 is a schematic diagram of the experimental results without adding an inclination sensor; Figure 9 is a schematic diagram of the experimental results with an inclination sensor added; Figure 10 is a comparison diagram of the armature current tracking effects of different controllers provided by an embodiment of the present invention; Figure 11 is provided by an embodiment of the present invention Nyquist diagram; Figure 12 is a schematic diagram of the structure of a control device for an electric assist bicycle provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present application.

[0019] The terms "first" and "second" are only used for descriptive purposes, and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "plurality" is two or more.

[0020] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "mounted", "connected", and "connected" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific situations.

[0021] See Figure 2 , which is a flowchart of an electric assist bicycle control method provided by an embodiment of the present invention, including steps S1 to S4: S1. Input the target parameters and the actual armature current; S2. Calculate the target armature current according to the target parameters; S3. Input the target armature current and the actual armature current into the controller to output a motor control signal; S4. Adjust the assist torque of the electric assist bicycle according to the motor control signal; wherein, in the controller, the motor control signal is calculated by the following method: Input the target armature current and the actual armature current into an error amplifier to obtain a current following error; Input the current following error into a controller to obtain an initial reference current; Sum the initial reference current and a ramp compensation signal to obtain a target reference current; Input the target reference current and the actual armature current into a comparator to output a motor control signal.

[0022] It should be noted that the electric assist bicycle control method described in the embodiments of the present invention can be implemented by a control device in the electric assist bicycle.

[0023] Exemplarily, the target parameters in step S1 may include human factor data, slope, actual wheel speed, actual acceleration, applied torque, and assist torque. Among them, the applied torque is the torque applied by the rider through the pedals when riding, and the assist torque refers to the output torque of the motor, that is, the electromagnetic torque of the motor. And, for the sake of narrative convenience, in the present invention, the wheel speed acceleration is simply referred to as acceleration. Further, in step S2, convert the target parameters into a target armature current. Among them, the target armature current can be understood as the armature current reference value. Exemplarily, the target wheel speed and target acceleration can be predicted according to the human factor data, and the target armature current can be calculated by combining the error between the target wheel speed and the actual wheel speed, the error between the target acceleration and the actual acceleration, etc., so as to automatically predict the assist demand of the rider and perform control in advance. Further, when calculating the target armature current, a slope compensation control current value calculated according to the slope can also be introduced. Among them, the slope can be understood as the inclination angle of the road surface. By detecting the slope / inclination angle, uphill and downhill can be identified, so that the assist torque can be adjusted quickly in response to environmental changes to improve the response speed, and the stability and safety of riding can also be ensured. Further, in step S3, input the target armature current and the actual armature current into a controller to calculate a motor control signal. It can be understood that, in some embodiments, a control algorithm can also be used to replace the controller to calculate the motor control signal, which is not limited herein.

[0024] Refer to Figure 3 , which is a schematic diagram of an electric assist bicycle control system provided by an embodiment of the present invention. It can be seen from Figure 3 that the electric assist bicycle control system includes a controller, a signal processing unit, a control unit, a human factor data input unit, and a comprehensive sensor. Among them, the comprehensive sensor includes an inclination sensor, a torque sensor, a wheel speed sensor, and an acceleration sensor.

[0025] Specifically, the sensor is connected to the signal processing unit to convert the signal collected by the sensor into an electronic signal through the signal processing unit and transmit it to the control unit; further, the control unit is configured to calculate the target armature current according to the human factor data and the data collected by the sensor, The controller then calculates the motor control signal based on the target armature current and the actual armature current; thereafter, the motor drive device adjusts the armature current of the motor according to the received motor control signal, thereby controlling the motor (electric motor) to output the target assist torque. Exemplarily, the control unit may be a DSP (Digital Signal Processor), and the motor drive device may be a UPE (User Plane Entity, power electronic converter).

[0026] Further, referring to Figure 4 is a schematic diagram of a controller provided by an embodiment of the present invention, where CLK (Clock Signal) is a clock signal, which is generated by It can be seen that Figure 4 the controller includes an error amplifier, a comparator and a controller, and the error amplifier is used to calculate the current following error between the target armature current and the actual armature current and input the current following error into the controller to obtain the initial reference current, and the sum of the initial reference current and the slope compensation signal is used as the target reference current. Further, the target reference current and the actual armature current are input into the comparator and output the motor control signal through an SR latch (Set-Reset Latch), that is, output a PWM waveform.

[0027] Figure 4 Further, referring to the target armature current and the actual armature current enter the error amplifier at the same time, which is the control described in the embodiment of the present invention. This is a hysteresis control. The advantage of the hysteresis control is fast speed, but the anti-interference performance is extremely poor. Therefore, the embodiment of the present invention also introduces a controller, The

[0028] control uses an augmented matrix, considers more interference sources and suppresses them, so as to optimize the robustness while the system responds quickly, and can better balance the dynamic response and anti-interference ability of the control system.It should be noted that since the initial reference current value may jitter, resulting in an inaccurate generated PWM duty cycle. Therefore, to solve this technical problem, in the embodiments of the present invention, a slope compensation signal is further added. Among them, the slope compensation signal can be a ramp signal with a period of , and a negative slope. Further, referring to Figure 5 , it is a schematic diagram of slope compensation provided by an embodiment of the present invention. Among them, in Figure 5 , the first curve is the initial reference current , corresponding to the output signal of the Figure 4 controller in ; the second curve is the waveform after ramp compensation of , that is, the target reference current, corresponding to the input signal of the negative input terminal of the comparator in Figure 4 ; the third curve is the actual armature current ; further, when reaching the rising edge of CLK, or when the actual armature current is equal to the target reference current, the PWM flips, thereby obtaining the fourth curve PWM waveform in Figure 5 , that is, the output of the SR latch. It can also be seen from Figure 5 that the period of the clock signal (CLK) is , and the duty cycle of the PWM waveform is .

[0029] Compared with the prior art, the electric assist bicycle control method provided by the embodiments of the present invention can improve the response speed and high robustness stability of the control system by adopting the controller, and further optimize the assist effect.

[0030] As an optional implementation manner, in step S2, the target parameters include human factor data, slope, actual wheel speed, actual acceleration, applied torque, and assist torque; then, calculating the target armature current according to the target parameters includes: S21. Calculate the target wheel speed and target acceleration according to the human factor data; S22. Calculate the human-machine output power ratio weight with the minimum human-machine mixed output power as the target according to the applied torque and the assist torque; S23. Based on a hybrid strategy of feedforward and error feedback control, calculate the initial target armature current according to the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope; S24. Multiply the human-machine output power ratio weight and the initial target armature current to obtain the target armature current.

[0031] It can be understood that the steps of S21, S22, and S23 can be adjusted accordingly. For example, the human-machine output ratio weight can be calculated first, then the target wheel speed and target acceleration can be calculated, and then the target armature current can be calculated. Or, the target wheel speed and target acceleration can be calculated first, then the target armature current can be calculated, and then the human-machine output ratio weight can be calculated. As long as it is ensured that the target wheel speed and target acceleration are calculated first, and then the initial target armature current is calculated. The execution order of other steps is not limited herein.

[0032] Furthermore, the slope can be collected by an inclination sensor, the actual wheel speed can be collected by a wheel speed sensor, the actual acceleration can be collected by an acceleration sensor, and the applied torque can be collected by a torque sensor. And the applied torque in step S2 should be understood as the actual applied torque, and the assist torque should be understood as the actual assist torque.

[0033] Exemplarily, the wheel speed sensor can be installed at the rear hub of the electric assist bicycle. By measuring the speed of the rear wheel, the effect of electric assist can be intuitively reflected; the inclination sensor can be installed near the center frame of the electric assist bicycle and close to the center of gravity. By measuring the inclination at a position close to the center of mass of the electric assist bicycle, the overall tilting state of the electric assist bicycle can be better reflected, so as to more accurately measure the slope of the current riding section.

[0034] As one optional implementation manner, in step S21, the calculating the target wheel speed and target acceleration according to the human factor data includes: S211. Generating an initial wheel speed value according to the human factor data; S212. Substituting the initial wheel speed value into a preset wheel speed trajectory formula to obtain a target wheel speed trajectory formula for calculating the target wheel speed; S213. Differentiating the target wheel speed trajectory formula to obtain a target acceleration trajectory formula for calculating the target acceleration.

[0035] As one optional implementation manner, the human factor data includes heart rate, subjective score, fatigue index, and pedaling frequency. Then, in step S211, the generating an initial wheel speed value according to the human factor data includes: Calculating a first initial wheel speed value according to the heart rate; wherein, there is a negative correlation between the heart rate and the first initial wheel speed value; Calculating a second initial wheel speed value according to the subjective score; wherein, there is a negative correlation between the subjective score and the second initial wheel speed value; Calculating a third initial wheel speed value according to the fatigue index; wherein, there is a negative correlation between the fatigue index and the third initial wheel speed value; Calculate the initial value of the fourth wheel speed according to the pedal frequency; wherein, there is a positive correlation between the pedal frequency and the initial value of the fourth wheel speed; Perform weighted summation on the initial value of the first wheel speed, the initial value of the second wheel speed, the initial value of the third wheel speed, and the initial value of the fourth wheel speed to obtain the initial value of the wheel speed.

[0036] Among them, the subjective score refers to the degree of fatigue felt by the user and is input by the user (rider); the heart rate can be collected by a heart rate sensor, the pedal frequency can be collected by an acceleration sensor, and the fatigue index can be calculated based on the heart rate. It should be noted that although both the subjective score and the fatigue index are used to quantify the user's fatigue degree, the subjective score is input by the user and represents the user's subjective feeling, while the fatigue index is calculated based on the user's physiological parameter (heart rate) and is an objective measurement. In the embodiments of the present invention, by comprehensively calculating the quantification values of the fatigue degree in two dimensions, subjective and objective, to calculate the target wheel speed, the assistance effect can better meet the actual needs of the user.

[0037] Exemplarily, the initial value of the first wheel speed is calculated by the following formula: (1) wherein, represents the initial value of the first wheel speed; represents the average wheel speed; represents the first fitting constant; represents the target heart rate Furthermore, is calculated by the following formula: (2) wherein, represents; represents the maximum heart rate; represents the resting heart rate.

[0038] That is, by collecting the maximum heart rate during cycling and the resting heart rate at the beginning of cycling to calculate the target heart rate .

[0039] Exemplarily, the initial value of the second wheel speed is calculated by the following formula: (3) wherein, represents the initial value of the second wheel speed; represents the average wheel speed; represents the second fitting constant; represents the per-unit value of the subjective score, , "10" is the upper limit value, representing the subjective score.

[0040] Exemplarily, in the above formula (3), can be fitted by the correlation data samples and subjective scores collected in advance during the motion cycle. Among them, the subjective scores of users can be collected by arranging a scoring interface in the test system, and the value of the subjective score is The correlation data samples include wheel speed and average wheel speed , so as to obtain the sample set , where represents the average wheel speed collected in the th motion cycle, represents the subjective score collected in the th motion cycle, represents the total number of motion cycles; further, the collected wheel speed is used as in the above formula (3), and is used as in the above formula (3), and the collected is used as in the above formula (3), and then the is obtained by fitting.

[0041] Exemplarily, the initial value of the third wheel speed is calculated by the following formula: (4) where represents the initial value of the third wheel speed; represents the maximum normal wheel speed; represents the third fitting constant; represents the fatigue index at the moment of

[0042] Exemplarily, the fatigue index can be calculated by the following formula: (5) where represents the fatigue index at the moment of represents the heart rate at the moment of represents the maximum heart rate; represents the user power accumulation value, where the user power refers to the work done by the user per unit time during cycling; represents the empirical user power value.

[0043] Exemplarily, the initial value of the fourth wheel speed is calculated by the following formula: (6) wherein, represents the initial value of the fourth wheel speed; represents the base wheel speed; represents the fourth fitting constant; represents the cadence; represents the average reference cadence.

[0044] It can be seen from formula (6) that there is a positive correlation between the cadence and the initial value of the fourth wheel speed. This is because the higher the cadence, it means that the cyclist is actively exerting force. At this time, it is determined that the user expects to increase the cycling speed. Therefore, the initial value of the fourth wheel speed is increased to increase the target wheel speed.

[0045] Furthermore, a weighted sum of the initial values of the first wheel speed, the second wheel speed, the third wheel speed, and the fourth wheel speed is performed to obtain the initial value of the wheel speed, as shown in the following formula: (7) wherein, represents the initial value of the wheel speed at time represents the initial value of the first wheel speed; represents the initial value of the second wheel speed; represents the initial value of the third wheel speed; represents the initial value of the fourth wheel speed; represents the first weight; represents the second weight; represents the third weight; represents the fourth weight.

[0046] As an optional implementation manner, in step S212, the wheel speed trajectory formula is as shown in the following formula: (8) wherein, represents the target wheel speed at time represents the initial value of the wheel speed; represents the natural base; represents the time; represents the time constant.

[0047] It should be noted that since the target wheel speed / target acceleration of the user generally does not change significantly within a certain period of time and may also follow a certain change rule, in some embodiments of the present invention, by calculating the initial value of the wheel speed and substituting it into the wheel speed trajectory formula, the target wheel speed trajectory formula is obtained. Then, within a certain period of time, by substituting different moment values into the target wheel speed trajectory formula, the target wheel speed at different moments can be calculated, so that it is not necessary to collect the target parameters and calculate the target wheel speed at each moment, which greatly reduces the calculation amount while improving the calculation accuracy of the target wheel speed, and can also achieve smooth control.

[0048] Exemplarily, in step S213, the derivative of the target wheel speed trajectory formula is obtained to get the target acceleration trajectory formula, as shown in the following formula: (9) Wherein, represents the target acceleration at the moment of; represents the target wheel speed at the moment of; represents the differential symbol; represents the initial value of the wheel speed; represents the natural base; represents time; represents.

[0049] Compared with the prior art, the embodiment of the present invention obtains the target acceleration by calculating the target acceleration trajectory formula, without collecting the target parameters and calculating the target acceleration at each moment, which can greatly reduce the calculation amount while improving the calculation accuracy of the target acceleration, and can also achieve smooth control.

[0050] Further, in some embodiments, the target acceleration should satisfy a preset acceleration limiting condition. Exemplarily, the acceleration limiting condition is shown in the following formula: (10) Wherein, represents the target acceleration; represents the upper limit value of the target acceleration; represents the absolute value operation.

[0051] Exemplarily, can take 2.0 (metre per second squared, meter per second squared).

[0052] Further, since the wheel acceleration is proportional to the pedal acceleration, the target acceleration is also proportional to the target pedal acceleration, as shown in the following formula: (11) Wherein, represents the target pedal angular acceleration; represents the human-machine transmission speed ratio; represents the target acceleration.

[0053] Then, Equation (12) can be obtained from Equation (10) and Equation (11) for limiting the pedal angular acceleration in some embodiments: (12) Wherein, represents the target pedal angular acceleration; represents the human-machine transmission speed ratio; represents the upper limit value of the target acceleration; represents the absolute value operation.

[0054] Compared with the prior art, the embodiment of the present invention calculates the target wheel speed according to the human factor data, which can make the finally output assist torque more in line with the riding needs of humans. Moreover, the embodiment of the present invention can automatically predict the target wheel speed required by the user without the user manually inputting the target wheel speed, and can achieve a more intelligent control of the electric bicycle, improving the riding experience of the user.

[0055] Compared with the prior art, the embodiment of the present invention can generate a target wheel speed and a target acceleration that are more in line with the personalized needs of humans by adopting human factor data and a trajectory formula, which has more practical physical significance.

[0056] As one of the optional embodiments, in step S23, the initial target armature current is calculated based on the hybrid strategy of feedforward and error feedback control according to the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope, including: Multiply the target wheel speed by the wheel speed feedforward control coefficient to obtain a first feedforward control current value; Multiply the target acceleration by the acceleration feedforward control coefficient to obtain a second feedforward control current value; Calculate the slope compensation control current value according to the slope; wherein, the slope compensation control current value is positively correlated with the sine value of the slope; Calculate the wheel speed error between the target wheel speed and the actual wheel speed, and multiply the wheel speed error by the wheel speed error feedback coefficient to obtain a first error feedback control current value; Calculate the acceleration error between the target acceleration and the actual acceleration, and multiply the acceleration error by the acceleration error feedback coefficient to obtain a second error feedback control current value; Sum the first feedforward control current value, the second feedforward control current value, the slope compensation control current value, the first error feedback control current value, and the second error feedback control current value to obtain the initial target armature current.

[0057] Exemplarily, the initial target armature current is calculated by the following formula: (13) where represents the initial target armature current; represents the acceleration feedforward control coefficient, taking the current control moment of inertia; represents the target acceleration; represents the wheel speed feedforward control coefficient, taking the current control damping coefficient; represents the target wheel speed; represents the slope compensation coefficient; represents the slope; represents the wheel speed error feedback coefficient; represents the acceleration error feedback coefficient; represents the second feedforward control current value; represents the first feedforward control current value; represents the slope compensation control current value; represents the first error feedback control current value; represents the second error feedback control current value.

[0058] Furthermore, in some embodiments, the acceleration feedforward control coefficient and the wheel speed feedforward control coefficient can be calculated according to the mechanical motion equation of the electric assist bicycle: Specifically, the mechanical motion equation of the motor is shown as the following formula: (14) where represents the moment of inertia of the motor; represents the angular acceleration of the motor; represents the damping coefficient of the motor; represents the angular velocity of the motor speed; represents the electromagnetic torque; represents the electromagnetic torque constant; represents the armature current.

[0059] Furthermore, the mechanical motion equation of the user is shown as the following formula: (15) where represents the moment of inertia of the pedal; Indicates the stepping angular acceleration; Indicates the pedal damping coefficient; Indicates the stepping angular velocity; Indicates the applied torque; Indicates the resistance torque.

[0060] Furthermore, the motion mechanical equation of the entire electric-assisted bicycle is shown as follows: (16) Wherein, Indicates the moment of inertia of the wheel; Indicates the acceleration; Indicates the wheel damping coefficient; Indicates the wheel speed; Indicates the applied torque; Indicates the electromagnetic torque; Indicates the resistance torque.

[0061] Furthermore, referring to Figure 6 , it is a schematic diagram of the forces acting on the electric-assisted bicycle provided by an embodiment of the present invention. Wherein, Indicates the wind resistance, Indicates the component force of the gravity in the downward direction along the slope, Indicates the rolling resistance, Indicates the component force of the assistance of the motor to the electric-assisted bicycle in the upward direction along the slope, Indicates the component force of the force applied by the user to the electric-assisted bicycle in the upward direction along the slope. Furthermore, the resistance torque Is shown as follows: (17) Wherein, Indicates; Indicates the wheel radius of the electric-assisted bicycle; Indicates the wind resistance; Indicates the component force of the gravity in the downward direction along the slope; Indicates the rolling resistance.

[0062] It can be understood that the wheel speed is in a proportional relationship with the stepping angular velocity, and the stepping angular acceleration and the wheel speed acceleration are in a proportional relationship, as shown in Equations (18) and (19) respectively: (18) Wherein, Indicates the stepping angular velocity; Indicates the ratio of the human-machine transmission speed; Indicates the wheel speed.

[0063] (19) Wherein, Indicates the stepping angular acceleration; Indicates the vehicle - human transmission speed ratio; Indicates the wheel speed acceleration.

[0064] Furthermore, substituting equations (18) and (19) into equation (15), and then subtracting equation (16), the following equation can be obtained: (20) Where, Indicates the wheel moment of inertia; Indicates the vehicle - human transmission speed ratio; Indicates the pedal moment of inertia; Indicates the acceleration; Indicates the wheel damping coefficient; Indicates the pedal damping coefficient; Indicates the wheel speed; Indicates the electromagnetic torque.

[0065] Furthermore, from equations (20) and (14), equations (21) and (22) can be obtained (21) Where, Indicates the acceleration; Indicates the motor angular acceleration; Indicates the motor moment of inertia; Indicates the wheel moment of inertia; Indicates the vehicle - human transmission speed ratio; Indicates the pedal moment of inertia.

[0066] (22) Where, Indicates the wheel speed; Indicates the motor rotational speed angular velocity; Indicates the motor damping coefficient; Indicates the wheel damping coefficient; Indicates the vehicle - human transmission speed ratio; Indicates the pedal damping coefficient.

[0067] Furthermore, the acceleration feed - forward control coefficient and the wheel speed feed - forward control coefficient are respectively shown in equations (23) and (24) as follows: (23) Where, Indicates the acceleration feed - forward control coefficient; Indicates the wheel moment of inertia; Indicates the vehicle - human transmission speed ratio; Indicates the pedal moment of inertia (24) Wherein, Indicates the wheel speed feedforward control coefficient; Indicates the wheel damping coefficient; Indicates the human-vehicle transmission speed ratio; Indicates the pedal damping coefficient Compared with the prior art, after calculating the target acceleration and target wheel speed in the embodiment of the present invention, the target armature current is calculated by introducing a hybrid strategy of feedforward control and feedback control (a hybrid strategy of feedforward and error feedback control), which can, on the basis of retaining the fast response and low latency of feedforward control, combine error feedback to correct errors, so that the target armature current can be calculated quickly and accurately.

[0068] Exemplarily, different control strategies can also be adopted in different riding stages, and the following takes four scenarios of the starting stage, fatigue stage, flat road cruising stage, and climbing stage as examples. In the starting stage of the electric assist bicycle, the user has a low heart rate and a fast cadence. At this time, it is necessary to increase the acceleration and armature current to achieve a fast response; when it is recognized that the user has a relatively fast heart rate and a long riding time, it is determined that the user is in a fatigue state (fatigue stage). At this time, the comfort strategy is turned on to regulate the armature current so that the wheel speed drops or the acceleration is less than or equal to 0; in the flat road cruising state, at this time, the user's cadence and heart rate are stable, then the wheel speed can be kept unchanged, thus giving the user a good and stable riding experience; in the climbing stage, after the slope is recognized by the tilt sensor, the slope compensation assistance is turned on to reduce the user's riding burden.

[0069] As an optional implementation manner, in step S22, the human-machine hybrid output power is calculated by the following formula: (25) Wherein, Indicates the human-machine hybrid output power; Indicates the applied torque; Indicates the human-machine output ratio weight; Indicates the human-vehicle transmission speed ratio; Indicates the wheel damping coefficient; Indicates the pedal damping coefficient; Indicates the motor damping coefficient; Indicates the assistance torque; Indicates the actual wheel speed.

[0070] It should be noted that during cycling, the greater the torque applied by the cyclist, the more strenuous the cycling and the worse the cycling experience. Increasing the assisting torque of the motor (i.e., electromagnetic torque) can reduce the torque applied by the cyclist. However, as the assisting torque increases, the losses suffered by the motor also increase, resulting in a reduction in the service life of the motor. Therefore, in the embodiments of the present invention, an objective function is set to optimize the human-machine output power with the minimum as the goal to allocate the human-machine output ratio, so as to optimize the motor output while achieving assistance, and better balance the user's cycling experience and the service life of the motor.

[0071] Furthermore, the objective function of the embodiments of the present invention is shown as the following formula: (26) Wherein, represents the operation of taking the minimum value; represents the human-machine mixed output power; represents the weight of the human-machine output ratio, and ; represents the applied torque; represents the pedaling angular velocity; represents the electromagnetic torque; represents the angular velocity of the motor speed.

[0072] Furthermore, when solving the above objective function, constraint conditions need to be added, that is, it is also necessary to ensure that the power of the motor and the target armature current do not exceed the upper limit. The specific formula is shown as follows: (27) Wherein, represents the target armature current; represents the operation of taking the absolute value; represents the maximum value of the armature current; represents the power of the motor; represents the electromagnetic torque; represents the angular velocity of the motor speed; represents the upper limit value of the motor power.

[0073] Furthermore, substituting formula (18) and formula (21) into formula (26), another expression of the objective function can be obtained, as shown in the following formula: (28) Wherein, represents the operation of taking the minimum value; represents the human-machine mixed output power; represents the applied torque; represents the weight of the human-machine output ratio; represents the ratio of the human-vehicle transmission speed; represents the wheel damping coefficient; represents the pedal damping coefficient; represents the motor damping coefficient; represents the vehicle's assisted torque, which is the sum of the human and motor torques, i.e., ; represents the wheel speed.

[0074] It should be noted that in formula (28), is collected by the torque sensor, , , and are fixed values. Therefore, by iterating different to solve the objective function, the human-machine output ratio weight under the minimum human-machine combined output power can be obtained .

[0075] Furthermore, in some embodiments, for the convenience of solving, it can be set that , , then the minimum human-machine combined output power can be further written as a function of , as shown in the following formula: (29) When A > B, then increases as increases. At this time, taking the minimum value of , then is the minimum. It should be noted that when takes too small a value, the assistance purpose cannot be achieved. Therefore, in some embodiments, the minimum value of can be set to 0.5, that is, when A > B, take ; Furthermore, when A < B, then decreases as increases. At this time, taking the maximum value of , that is, taking is the minimum; Furthermore, when A = B, is independent of , and the initial armature current is taken as the target armature current.

[0076] Furthermore, in step S24, multiplying the human-machine output ratio weight and the initial target armature current gives the target armature current, as shown in the following formula: (30) Where, represents the target armature current; represents the human-machine output ratio weight; Indicates the initial target armature current.

[0077] As an optional implementation manner, the target acceleration satisfies the slope filtering limit constraint condition, and the target armature current satisfies a preset armature current constraint condition, where the armature current constraint condition includes at least one of a motor capability constraint condition, a slope filtering limit constraint condition, and an emergency brake interruption constraint condition.

[0078] Exemplarily, the motor capability constraint condition is shown as the following formula: (31) Wherein, represents the maximum value of the armature current; represents the target armature current.

[0079] Further, the emergency brake interruption constraint condition means that when it is recognized that the emergency brake device is turned on, the target armature current is set to so as to achieve a quick emergency stop and prevent danger from occurring.

[0080] Further, the slope filtering limit constraint condition means that slope compensation is performed between the set maximum slope and minimum slope, and the slope compensation coefficient is adjusted according to the slope. Exemplarily, the slope filtering limit constraint condition is shown as the following formula: (32) It can be understood that all or part of the processes in the electric assist bicycle control method described in the embodiments of the present invention can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented.

[0081] Further, referring to Figure 7 , it is a flowchart of the electric assist bicycle control method provided by another embodiment of the present invention, which can be sorted into the following steps T1 to T8: Step T1: Initialize the peripheral modules required by the controller, including the INTSYNC (Interrupt Synchronization) module, the GPIO (General Purpose Input Output) module, the ADC (Analog-to-Digital Converter), the EPWM (Enhanced Pulse Width Modulation) module, and the eCAP (Event Capture) module; Step T2: Determine whether the interrupt flag of the eCAP module is triggered. If not, maintain the waiting state (which can be achieved through an empty loop or a no-operation instruction). Step T3: When the interrupt flag of the EPWM module is triggered, enter the data acquisition and control calculation process. Step T4: Read the voltage values of multiple input channels through the ReadADCValues() function and convert them into the current system state parameters, including but not limited to the actual armature current, slope, acceleration, and applied torque, etc. And read the encoder value through the eCAP module to read the wheel speed. It should be noted that various collected parameters also need to be subjected to data normalization, filtering, and data calibration. Step T5: Call the ComputeReferenceCurrent() function to calculate the target armature current of the current control period according to the above collected parameters and the preset physical model (also known as the armature current reference value). It should be noted that when calculating the target armature current , constraint conditions such as slope filtering limit constraints also need to be added. Step T6: Calculate the error value between the actual armature current and the target armature current , and use this error as the input of the controller. Calculate the controller output through the transfer function determined and discretized in advance in MATLAB (Matrix Laboratory), that is, output the PWM duty cycle modulation value. Step T7: Write the duty cycle modulation value into the CMPA (Compare Register A) and CMPB (Compare Register B) of the EPWM module to implement the output PWM control signal to drive the closed-loop control of the motor current. Step T8: Clear the interrupt flag and prepare to enter the next control cycle.

[0082] Step T8: Clear the interrupt flag and prepare to enter the next control cycle.

[0083] It should be noted that this process can be executed periodically to achieve the armature current control based on the real-time state and human intention, thereby improving the response speed of the electric assist bicycle (assist) control system to provide a more comfortable riding experience.

[0084] Furthermore, the following uses some experimental data to illustrate the assist effect of the electric assist bicycle control described in the present invention.

[0085] See Figure 8 and Figure 9, which are schematic diagrams of experimental results with and without an inclination sensor respectively. Among them, speed refers to the speed of the electric assist bicycle, the applied torque refers to the torque applied by the person, and the assist torque refers to the output torque of the motor, that is, the electromagnetic torque. And in both experiments, the electric assist bicycle rides onto a slope with an inclination of 30 degrees at t = 1s.

[0086] It can be seen from Figure 8 that starting from t = 1s, the inclination gradually increases from 0° to 30°, and the resistance received by the electric assist bicycle gradually increases during the uphill process; moreover, since the inclination sensor is not added and the uphill cannot be recognized, therefore, the assist torque cannot be increased at the beginning of going uphill, resulting in a decrease in speed after the person feels the resistance; further, as the speed difference changes, the assist torque also increases subsequently with the increase of the speed difference, and at the same time the torque applied by the person also increases. Finally, the torque applied by the person is equal to the assist torque of the motor, and the speed first decreases and then overshoots, and finally reaches the original speed. It can be seen from Figure 8 that due to the lack of an inclination sensor, there is a certain delay in the adjustment of the assist torque.

[0087] Furthermore, it can be seen from Figure 9 that starting from t = 1s, the inclination gradually increases from 0° to 30°, and the resistance received by the electric assist bicycle gradually increases during the uphill process; at this time, since the inclination sensor is added, the uphill can be recognized. In the embodiment of the present invention, the slope compensation coefficient is taken as 1, the electric assist bicycle operates in the climbing state, and the target armature current is generated according to human factor data, etc. and the target armature current is tracked. It can be seen from Figure 9 that compared with not adding an inclination sensor and controlling based on the speed difference, the embodiment of the present invention can increase the assist torque more timely, improve the response speed and provide a more comfortable riding experience.

[0088] Furthermore, referring to Figure 10 , it is a comparison diagram of the armature current tracking effects of different controllers provided by an embodiment of the present invention under a sudden speed increase. Among them, the horizontal axis represents time (t), the unit is s (second), and the vertical axis represents the armature current, the unit is A (ampere). The green dashed line (Id reference) represents the armature current reference value (target armature current), and the magenta solid line (PI control) represents the actual armature current under the traditional PI (Proportional – Integral) controller. The orange solid line ( control) represents the actual armature current under the traditional controller, and the blue solid line ( control) represents The actual armature current under the controller is Figure 10 It can be seen that the controller provided by the embodiment of the present invention has better robustness and accuracy in a multi-disturbance environment, and can well complete the assistance task under non-ideal working conditions.

[0089] It can be understood that the process of designing the controller includes, on the basis of determining the linear mathematical model of the controlled system , obtaining the augmented matrix P(s) by selecting the weight function W(s), and then obtaining the transfer function of the H∞ controller in the MATLAB robust toolbox .

[0090] Furthermore, in the embodiment of the present invention, the controlled system is the aforementioned control link, which is modeled as a G(s) controlled system, and its transfer function is as follows: (33) Wherein, K represents the gain of the controlled system; T represents the delay time constant; represents the damping coefficient of the controlled system; represents a complex variable.

[0091] Exemplarily, in combination with the circuit parameters of the embodiment of the present invention, the weight function of the embodiment of the present invention is shown in the following formula: ; (34) Wherein, represents the first weight function; represents the second weight function; represents the third weight function; represents a complex variable.

[0092] Furthermore, by using the hinfsyn function in the MATLAB robust control toolbox, according to the obtained controlled system and weight function, the transfer function of the H∞ controller can be obtained as shown in the following formula: (35) Wherein, represents the transfer function of the H∞ controller; represents a complex variable.

[0093] Furthermore, referring to Figure 11 , it is the Nyquist diagram of provided by an embodiment of the present invention, which shows the Nyquist curve of "H∞ controller + controlled object G(s)". It can be seen from the figure that all the roots of the system are in the left half plane and there are no unstable roots. Therefore, the closed-loop system of the embodiment of the present invention is stable.

[0094] See Figure 12 , an embodiment of the present invention further provides an electric assist bicycle control device 10, including: A parameter input module 11 for inputting target parameters and actual armature current; A target armature current calculation module 12 for calculating a target armature current according to the target parameters; An assist torque calculation module 13 for inputting the target armature current and the actual armature current into a controller to output a motor control signal, An assist torque control module 14 for adjusting the assist torque of the electric assist bicycle according to the motor control signal; wherein, in the controller, the motor control signal is calculated in the following manner: Input the target armature current and the actual armature current into an error amplifier to obtain a current following error; Input the current following error into the controller to obtain an initial reference current; Sum the initial reference current and a ramp compensation signal to obtain a target reference current; Input the target reference current and the actual armature current into a comparator to output a motor control signal.

[0095] The electric assist bicycle control device provided by the embodiment of the present invention can implement all the process steps of the electric assist bicycle control method described in the above embodiment. The functions and achieved technical effects of each module and unit in the device respectively correspond to those of the electric assist bicycle control method described in the above embodiment, and the specific implementation manners are not elaborated herein.

[0096] To achieve the above object, an embodiment of the present invention further provides an electric assist bicycle, including an electric assist bicycle body and the electric assist bicycle control device as described in any one of the above embodiments.

[0097] Compared with the prior art, the electric assist bicycle control method, device and electric assist bicycle provided by the embodiment of the present invention input target parameters and actual armature current; calculate a target armature current according to the target parameters; input the target armature current and the actual armature current into the controller to output a motor control signal; adjust the assist torque of the electric assist bicycle according to the motor control signal; wherein, in the controller, the motor control signal is calculated in the following manner: input the target armature current and the actual armature current into an error amplifier to obtain a current following error; input the current following error into The controller obtains an initial reference current; sums the initial reference current and a ramp compensation signal to obtain a target reference current; and inputs the target reference current and the actual armature current into a comparator to output a motor control signal. In the embodiment of the present invention, the controller combines both the advantages of fast control response speed and the characteristics of strong control anti-interference ability, and can meet the control requirements of high dynamic performance and high robustness of the electric assist bicycle.

[0098] The above is the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. An electric assist bicycle control method, characterized in that, Including: Inputting target parameters and actual armature current; Calculating the target armature current according to the said target parameters; Input the target armature current and the actual armature current into a controller to output a motor control signal; Adjusting the assisting torque of the electric assist bicycle according to the said motor control signal; Among them, in the said controller, the motor control signal is calculated in the following manner: Inputting the said target armature current and the said actual armature current into an error amplifier to obtain a current following error; Input the current following error into a controller to obtain an initial reference current; Summing the said initial reference current and the ramp compensation signal to obtain a target reference current; Inputting the said target reference current and the said actual armature current into a comparator to output a motor control signal.

2. The electric assist bicycle control method according to claim 1, wherein The said target parameters include human factor data, slope, actual wheel speed, actual acceleration, applied torque and assisting torque; then, calculating the target armature current according to the said target parameters includes: Calculating a target wheel speed and a target acceleration according to the said human factor data; Calculating a human-machine output power ratio weight with the minimum human-machine hybrid output power as the target according to the said applied torque and the actual assisting torque; Calculating an initial target armature current based on a hybrid strategy of feedforward and error feedback control according to the said target wheel speed, the said actual wheel speed, the said target acceleration, the said actual acceleration and the said slope; Multiplying the said human-machine output power ratio weight and the said initial target armature current to obtain the target armature current.

3. The electric-assisted bicycle control method according to claim 2, wherein The said human-machine hybrid output power is calculated by the following formula: Among them, represents the human-machine hybrid output power; represents the applied torque; represents the human-machine output ratio weight; represents the vehicle-person transmission speed ratio; represents the wheel damping coefficient; represents the pedal damping coefficient; represents the motor damping coefficient; represents the assisting torque; represents the actual wheel speed.

4. The electric assist bicycle control method according to claim 2, characterized in that, Calculating the target wheel speed and the target acceleration according to the said human factor data includes: Generating an initial value of the wheel speed according to the said human factor data; Substituting the said initial value of the wheel speed into a preset wheel speed trajectory formula to obtain a target wheel speed trajectory formula for calculating the target wheel speed; Differentiating the said target wheel speed trajectory formula to obtain a target acceleration trajectory formula for calculating the target acceleration.

5. The electric assist bicycle control method according to claim 4, wherein, The said human factor data includes heart rate, subjective score, fatigue index and cadence; then, generating the initial value of the wheel speed according to the said human factor data includes: Calculating a first initial value of the wheel speed according to the said heart rate; wherein, there is a negative correlation between the heart rate and the first initial value of the wheel speed; Calculating a second initial value of the wheel speed according to the said subjective score; wherein, there is a negative correlation between the subjective score and the second initial value of the wheel speed; Calculating a third initial value of the wheel speed according to the said fatigue index; wherein, there is a negative correlation between the fatigue index and the third initial value of the wheel speed; Calculating a fourth initial value of the wheel speed according to the said cadence; wherein, there is a positive correlation between the cadence and the fourth initial value of the wheel speed; Performing weighted summation on the said first initial value of the wheel speed, the said second initial value of the wheel speed, the said third initial value of the wheel speed and the said fourth initial value of the wheel speed to obtain the initial value of the wheel speed.

6. The electric assist bicycle control method according to claim 4, characterized in that, The said wheel speed trajectory formula is shown as follows: Among them, represents the target wheel speed at a moment; represents the initial value of the wheel speed; represents the natural base; represents time; represents the time constant.

7. The electric assist bicycle control method according to claim 2, characterized in that, Based on the hybrid strategy of feedforward and error feedback control, calculating the initial target armature current according to the said target wheel speed, the said actual wheel speed, the said target acceleration, the said actual acceleration and the said slope includes: Multiplying the said target wheel speed by a wheel speed feedforward control coefficient to obtain a first feedforward control current value; Multiplying the said target acceleration by an acceleration feedforward control coefficient to obtain a second feedforward control current value; Calculating a slope compensation control current value according to the said slope; wherein, there is a positive correlation between the slope compensation control current value and the sine value of the slope; Calculate the wheel speed error between the target wheel speed and the actual wheel speed, and multiply the wheel speed error by a wheel speed error feedback coefficient to obtain a first error feedback control current value; Calculate the acceleration error between the target acceleration and the actual acceleration, and multiply the acceleration error by an acceleration error feedback coefficient to obtain a second error feedback control current value; Sum the first feedforward control current value, the second feedforward control current value, the slope compensation control current value, the first error feedback control current value, and the second error feedback control current value to obtain an initial target armature current.

8. The electric assist bicycle control method according to claim 2, wherein, The target acceleration satisfies a slope filtering limit constraint condition, and the target armature current satisfies a preset armature current constraint condition, where the armature current constraint condition includes at least one of an acceleration limit condition, a motor capacity constraint condition, and an emergency brake interruption constraint condition.

9. An electric assist bicycle control device, characterized in that, It includes: A parameter input module for inputting target parameters and the actual armature current; A target armature current calculation module for calculating a target armature current according to the target parameters; The assisting torque calculation module is configured to input the target armature current and the actual armature current to the controller and output a motor control signal. An assist torque control module for adjusting the assist torque of the electric assist bicycle according to the motor control signal; Among them, in the controller, the motor control signal is calculated in the following manner: Input the target armature current and the actual armature current into an error amplifier to obtain a current following error; Input the current following error into a controller to obtain an initial reference current; Sum the initial reference current and the ramp compensation signal to obtain a target reference current; Input the target reference current and the actual armature current into a comparator to output a motor control signal.

10. An electric assist bicycle, characterized in that, It includes an electric assist bicycle body and the electric assist bicycle control device as claimed in claim 9.

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