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

Abstract

The present invention discloses a control method and device for an electric-assisted bicycle, and the electric-assisted bicycle. These methods relate to the technical field of electric-assisted bicycle control. The method comprises inputting a target parameter and an actual armature current; calculating a target armature current based on the target parameter; inputting the target and actual armature currents into an imgabs0# controller, which outputs a motor control signal; and adjusting the assist torque of the electric-assisted bicycle based on the motor control signal. The imgabs1# controller of the present invention combines the advantages of fast response speed of imgabs2# control with the strong anti-interference capability of imgabs3# control, meeting the high dynamic and robust control requirements of electric-assisted bicycles.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power-assisted bicycle control, and in particular to an electric power-assisted bicycle control method and device, and an electric power-assisted bicycle. Background Art

[0002] Electric bikes (E-bikes) are widely popular among consumers due to their reliability, ease of riding, environmental friendliness, and affordability. Compared to conventional bicycles, E-bikes utilize an electric motor to provide power to the rider, enabling riders to overcome hills, slopes, and rough terrain, allowing them to complete more challenging cycling challenges.

[0003] See also Figure 1 Schematic diagram of the torque sensor space vector. During riding an electric-assisted bicycle, the rider's applied torque is not constant but changes with pedal position, gravity, inertia, and muscle force. Because the applied torque is not constant, the control method must have fast dynamic response and tracking capabilities. However, existing technologies generally use speed monitoring to control the power-assisting torque. This control method has a slow response speed and lacks stable tracking, resulting in poor power-assisting effect. Summary of the Invention

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

[0005] To achieve the above objectives, an embodiment of the present invention provides an electric-assisted bicycle control method, comprising:

[0006] Input target parameters and actual armature current;

[0007] calculating a target armature current according to the target parameter;

[0008] The target armature current and the actual armature current are input into A controller that outputs motor control signals;

[0009] adjusting the power-assisting torque of the electric-assisted bicycle according to the motor control signal;

[0010] Among them, in the In the controller, the motor control signal is calculated in the following way:

[0011] Inputting the target armature current and the actual armature current into an error amplifier to obtain a current following error;

[0012] The current following error input The controller obtains the initial reference current;

[0013] Summing the initial reference current and the slope compensation signal to obtain a target reference current;

[0014] The target reference current and the actual armature current are input into a comparator, and a motor control signal is output.

[0015] 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 based on the target parameters includes:

[0016] calculating a target wheel speed and a target acceleration based on the human factors data;

[0017] Calculating the human-machine output ratio weight based on the applied torque and the assist torque with the goal of minimizing the human-machine hybrid output power;

[0018] Calculating an initial target armature current based on the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope based on a feedforward and error feedback control hybrid strategy;

[0019] The human-machine output ratio weight is multiplied by the initial target armature current to obtain the target armature current.

[0020] As an improvement to the above solution, the human-machine hybrid output power is calculated by the following formula:

[0021]

[0022] in, Indicates the human-machine mixed output power; represents the applied torque; Indicates the weight of the human-machine output ratio; Indicates the transmission speed ratio between man and vehicle; represents the wheel damping coefficient; represents the pedal damping coefficient; Indicates the motor damping coefficient; represents the assist torque; Indicates actual wheel speed.

[0023] As an improvement to the above solution, the calculation of the target wheel speed and target acceleration based on the human factors data includes:

[0024] generating an initial wheel speed value according to the human factor data;

[0025] 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;

[0026] The target wheel speed trajectory formula is derived to obtain a target acceleration trajectory formula for calculating the target acceleration.

[0027] As an improvement to the above solution, the human factor data includes heart rate, subjective score, fatigue index and cadence; then, generating the initial wheel speed value based on the human factor data includes:

[0028] Calculating a first wheel speed initial value based on the heart rate; wherein the heart rate and the first wheel speed initial value are negatively correlated;

[0029] Calculating a second wheel speed initial value based on the subjective score; wherein the subjective score and the second wheel speed initial value are negatively correlated;

[0030] Calculating an initial value of a third wheel speed according to the fatigue index; wherein the fatigue index and the initial value of the third wheel speed are negatively correlated;

[0031] Calculating a fourth wheel speed initial value according to the cadence; wherein the cadence and the fourth wheel speed initial value are positively correlated;

[0032] A weighted sum is performed on the first wheel speed initial value, the second wheel speed initial value, the third wheel speed initial value, and the fourth wheel speed initial value to obtain a wheel speed initial value.

[0033] As an improvement to the above solution, the wheel speed trajectory formula is as follows:

[0034]

[0035] in, express Target wheel speed at the moment; Indicates the initial value of wheel speed; Indicates the natural base; Indicates time; Represents the time constant.

[0036] As an improvement to the above solution, the hybrid strategy based on feedforward and error feedback control calculates 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:

[0037] multiplying the target wheel speed and the wheel speed feedforward control coefficient to obtain a first feedforward control current value;

[0038] Multiplying the target acceleration and the acceleration feedforward control coefficient to obtain a second feedforward control current value;

[0039] Calculating a slope compensation control current value according to the slope; wherein the slope compensation control current value and the sine value of the slope are positively correlated;

[0040] calculating a wheel speed error between the target wheel speed and the actual wheel speed, and multiplying the wheel speed error by a wheel speed error feedback coefficient to obtain a first error feedback control current value;

[0041] calculating an acceleration error between the target acceleration and the actual acceleration, and multiplying the acceleration error by an acceleration error feedback coefficient to obtain a second error feedback control current value;

[0042] 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 are summed to obtain an initial target armature current.

[0043] As an improvement of the above scheme, the target acceleration satisfies the slope filtering and limiting constraint condition, and the target armature current satisfies the preset armature current constraint condition, wherein the armature current constraint condition includes at least one of the acceleration limiting condition, the motor capacity constraint condition and the emergency brake interruption constraint condition.

[0044] To achieve the above objectives, an embodiment of the present invention further provides an electric power-assisted bicycle control device, comprising:

[0045] Parameter input module, used to input target parameters and actual armature current;

[0046] a target armature current calculation module, configured to calculate the target armature current according to the target parameters;

[0047] The power torque calculation module is used to input the target armature current and the actual armature current into the Controller, output motor control signal,

[0048] An assist torque control module, configured to adjust the assist torque of the electric-assisted bicycle according to the motor control signal;

[0049] Among them, in the In the controller, the motor control signal is calculated in the following way:

[0050] Inputting the target armature current and the actual armature current into an error amplifier to obtain a current following error;

[0051] The current following error input The controller obtains the initial reference current;

[0052] Summing the initial reference current and the slope compensation signal to obtain a target reference current;

[0053] The target reference current and the actual armature current are input into a comparator, and a motor control signal is output.

[0054] To achieve the above objectives, an embodiment of the present invention further provides an electric-assisted bicycle, comprising an electric-assisted bicycle body and an electric-assisted bicycle control device as described in any of the above embodiments.

[0055] Compared with the prior art, the electric power bicycle control method, device and electric power bicycle provided by the embodiment of the present invention input the target parameter and the actual armature current; calculate the target armature current according to the target parameter; input the target armature current and the actual armature current into the control method, device and electric power bicycle provided by the embodiment of the present invention; The controller outputs a motor control signal; adjusts the power torque of the electric power-assisted bicycle according to the motor control signal; wherein, In the controller, the motor control signal is calculated by: inputting the target armature current and the actual armature current into the error amplifier to obtain the current following error; inputting the current following error into the error amplifier The controller obtains an initial reference current; sums the initial reference current and the 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. Controller with both Advantages of fast control response and The control has strong anti-interference ability and can meet the high dynamic and high robustness control requirements of electric assisted bicycles. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 Schematic diagram of the space vector of the torque sensor provided by one embodiment of the present invention

[0057] Figure 2 This is a flow chart of a method for controlling an electric-assisted bicycle provided by one embodiment of the present invention;

[0058] Figure 3 1 is a schematic diagram of a control system for an electric-assisted bicycle provided by one embodiment of the present invention;

[0059] Figure 4 An embodiment of the present invention provides Schematic diagram of the controller;

[0060] Figure 5 is a schematic diagram of slope compensation provided by an embodiment of the present invention;

[0061] Figure 6 This is a schematic diagram of the forces acting on an electric-assisted bicycle provided by one embodiment of the present invention;

[0062] Figure 7 is a flow chart of a method for controlling an electric-assisted bicycle provided by another embodiment of the present invention;

[0063] Figure 8 This is a schematic diagram of the experimental results without adding the tilt sensor;

[0064] Figure 9 This is a schematic diagram of the experimental results when the tilt sensor is added;

[0065] Figure 10 This is a comparison diagram of armature current tracking effects of different controllers provided by one embodiment of the present invention;

[0066] Figure 11 An embodiment of the present invention provides Nyquist plot of

[0067] Figure 12 The figure is a schematic structural diagram of an electric power-assisted bicycle control device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0069] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0070] 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 the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0071] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0072] See also Figure 2 , is a flow chart of an electric-assisted bicycle control method provided by an embodiment of the present invention, comprising steps S1 to S4:

[0073] S1. Input target parameters and actual armature current;

[0074] S2. Calculating a target armature current according to the target parameter;

[0075] S3, input the target armature current and the actual armature current into A controller that outputs motor control signals;

[0076] S4. adjusting the power-assisting torque of the electric power-assisted bicycle according to the motor control signal;

[0077] Among them, in the In the controller, the motor control signal is calculated in the following way:

[0078] Inputting the target armature current and the actual armature current into an error amplifier to obtain a current following error;

[0079] The current following error input The controller obtains the initial reference current;

[0080] Summing the initial reference current and the slope compensation signal to obtain a target reference current;

[0081] The target reference current and the actual armature current are input into a comparator, and a motor control signal is output.

[0082] It is worth noting that the electric-assisted bicycle control method described in the embodiment of the present invention can be executed and implemented by a control device in the electric-assisted bicycle.

[0083] Exemplarily, the target parameters in step S1 may include human factor data, slope, actual wheel speed, actual acceleration, applied torque and assist torque, wherein 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. In addition, for the sake of convenience, in the present invention, the wheel speed acceleration is referred to as acceleration. Further, in step S2, the target parameter is converted into a target armature current, wherein the target armature current can be understood as an armature current reference value. For example, the target wheel speed and target acceleration can be predicted based on human factors data, and the target armature current can be calculated in combination with 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 rider's power assistance needs and control them in advance. Further, when calculating the target armature current, a slope compensation control current value calculated based on the slope can be introduced, wherein the slope can be understood as the inclination of the road surface. By detecting the slope / inclination, uphill and downhill can be identified, so that the power assistance torque can be adjusted quickly in response to environmental changes to improve the response speed and ensure the stability and safety of riding. Further, in step S3, the target armature current and the actual armature current are input into The controller is used to calculate the motor control signal. It is understood that in some embodiments, it can also be used Control algorithm replacement The controller calculates the motor control signal, which is not limited here.

[0084] See also Figure 3 , is a schematic diagram of an electric-assisted bicycle control system provided by an embodiment of the present invention, Figure 3 It can be seen that the electric bicycle control system includes A controller, a signal processing unit, a control unit, a human factors data input unit and a comprehensive sensor, wherein the comprehensive sensor includes a tilt sensor, a torque sensor, a wheel speed sensor and an acceleration sensor.

[0085] Specifically, the sensor is connected to the signal processing unit so that the signal collected by the sensor is converted into an electronic signal through the signal processing unit and transmitted to the control unit; further, the control unit is used to calculate the target armature current based on the human factor data and the data collected by the sensor. The controller calculates a motor control signal based on the target armature current and the actual armature current. The motor drive then adjusts the motor's armature current according to the received motor control signal, thereby controlling the motor (electric motor) to output the target assist torque. For example, the control unit can be a DSP (Digital Signal Processor), and the motor drive can be a UPE (User Plane Entity).

[0086] Further, see Figure 4 , is provided by an embodiment of the present invention Schematic diagram of the controller, where CLK (Clock Signal) is the clock signal, which is composed of Figure 4 It can be seen The controller includes an error amplifier, a comparator and controller, and uses an error amplifier to calculate the target armature current and the actual armature current The current following error is input into The controller obtains an initial reference current and uses the sum of the initial reference current and the slope compensation signal as the target reference current. Furthermore, the target reference current and the actual armature current are input into the comparator, and the motor control signal is output through the SR latch (Set-Reset Latch), that is, the output PWM waveform.

[0087] Further, see Figure 4 , target armature current The actual armature current At the same time, the error amplifier is entered, which is the embodiment of the present invention. This is a hysteresis control. The advantage of hysteresis control is fast speed, but the anti-interference performance is very poor. Therefore, the embodiment of the present invention also introduces controller, The control utilizes an augmented matrix to consider more interference sources and suppress them, thereby optimizing robustness while ensuring rapid system response, and better balancing the dynamic response and anti-interference capabilities of the control system.

[0088] It is worth noting that since the initial reference current value may jitter, resulting in an inaccurate PWM duty cycle, in order to solve this technical problem, a slope compensation signal is also added in the embodiment of the present invention, wherein the slope compensation signal can be a period of , a ramp signal with a negative slope. Further, see Figure 5 , is a schematic diagram of slope compensation provided by an embodiment of the present invention, wherein Figure 5 The first curve is the initial reference current ,correspond Figure 4 middle The output signal of the controller; the second curve is The waveform after slope compensation, that is, the target reference current, corresponds to Figure 4 The input signal of the negative input terminal of the comparator; the third curve is the actual armature current ; Further, when the rising edge of CLK is reached, or when the actual armature current When the target reference current is equal to the target reference current, the PWM is reversed, so that Figure 5 The fourth curve PWM waveform in the figure is the output of the SR latch, which is given by Figure 5 It can also be seen that the period of the clock signal (CLK) is , the duty cycle of the PWM waveform is .

[0089] Compared with the prior art, the electric power bicycle control method provided by the embodiment of the present invention adopts The controller can improve the response speed and robust stability of the control system, and further optimize the power assist effect.

[0090] 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:

[0091] S21. Calculating a target wheel speed and a target acceleration based on the human factor data;

[0092] S22. Calculating a human-machine output ratio weight based on the applied torque and the assist torque, with the goal of minimizing the human-machine hybrid output power;

[0093] S23, calculating an initial target armature current based on the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope based on a feedforward and error feedback control hybrid strategy;

[0094] S24: Multiply the human-machine output ratio weight by the initial target armature current to obtain a target armature current.

[0095] It can be understood that steps S21, S22 and S23 can be adjusted accordingly. For example, the human-machine output ratio weight can be calculated first, and then the target wheel speed and target acceleration are calculated, and then the target armature current is calculated. Alternatively, the target wheel speed and target acceleration can be calculated first, and then the target armature current is calculated, and then the human-machine output ratio weight is calculated. It is only necessary to ensure that the target wheel speed and target acceleration are calculated first, and then the target armature current is initially calculated. The execution order of other steps is not limited here.

[0096] Furthermore, the slope can be collected by the inclination sensor, the actual wheel speed can be collected by the wheel speed sensor, the actual acceleration can be collected by the acceleration sensor, and the applied torque can be collected by the torque sensor. In addition, 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.

[0097] For example, the wheel speed sensor can be installed at the rear wheel hub of the electric assisted bicycle. By measuring the speed on the rear wheel, the effect of the electric assist can be intuitively reflected. The inclination sensor can be installed near the center frame of the electric assisted bicycle and close to the center of gravity. By measuring the inclination at a position close to the center of mass of the electric assisted bicycle, it can better reflect the overall inclination state of the electric assisted bicycle, thereby more accurately measuring the slope of the current riding section.

[0098] As an optional implementation manner, in step S21, calculating the target wheel speed and target acceleration according to the human factor data includes:

[0099] S211. Generate an initial wheel speed value based on the human factor data;

[0100] S212, substituting the initial wheel speed value into a preset wheel speed trajectory formula to obtain a target wheel speed trajectory formula for calculating a target wheel speed;

[0101] S213 . Derivative the target wheel speed trajectory formula to obtain a target acceleration trajectory formula for calculating the target acceleration.

[0102] As an optional implementation manner, the human factor data includes heart rate, subjective score, fatigue index and cadence; then, in step S211, generating the initial wheel speed value based on the human factor data includes:

[0103] Calculating a first wheel speed initial value based on the heart rate; wherein the heart rate and the first wheel speed initial value are negatively correlated;

[0104] Calculating a second wheel speed initial value based on the subjective score; wherein the subjective score and the second wheel speed initial value are negatively correlated;

[0105] Calculating an initial value of a third wheel speed according to the fatigue index; wherein the fatigue index and the initial value of the third wheel speed are negatively correlated;

[0106] Calculating a fourth wheel speed initial value according to the cadence; wherein the cadence and the fourth wheel speed initial value are positively correlated;

[0107] A weighted sum is performed on the first wheel speed initial value, the second wheel speed initial value, the third wheel speed initial value, and the fourth wheel speed initial value to obtain a wheel speed initial value.

[0108] The subjective score refers to the user's perceived fatigue level and is input by the user (cyclist). Heart rate can be collected by a heart rate sensor, cadence can be collected by an accelerometer, and the fatigue index can be calculated based on heart rate. It's worth noting that while both the subjective score and the fatigue index are used to quantify the user's fatigue level, the subjective score is input by the user and represents their subjective feelings, while the fatigue index is calculated based on the user's physiological parameters (heart rate) and is an objective measurement. This embodiment of the present invention calculates the target wheel speed by combining the quantified fatigue values ​​from both subjective and objective dimensions, enabling the power assistance effect to better meet the user's actual needs.

[0109] For example, the first wheel speed initial value Calculated by the following formula:

[0110] (1)

[0111] in, Indicates the initial value of the first wheel speed; Indicates the average wheel speed; represents the first fitting constant; Indicates target heart rate

[0112] Furthermore, Calculated by the following formula:

[0113] (2)

[0114] in, express; Indicates maximum heart rate; Indicates resting heart rate.

[0115] That is, by collecting the maximum heart rate during cycling and your resting heart rate when you first start riding , to calculate the target heart rate .

[0116] For example, the second wheel speed initial value Calculated by the following formula:

[0117] (3)

[0118] in, Indicates the initial value of the second wheel speed; Indicates the average wheel speed; represents the second fitting constant; represents the per-unit value of subjective rating, , "10" is The upper limit value of Indicates a subjective rating.

[0119] For example, the above formula (3) The fitting can be performed by using the associated data samples and subjective scores collected in advance during the exercise cycle, wherein the user's subjective score can be collected by arranging a scoring interface in the test system, and the value of the subjective score is The associated data samples include wheel speed and average wheel speed , so we get the sample set ,in, Indicates the The average wheel speed collected during the movement cycle, Shidi The subjective scores collected during the exercise cycle, Indicates the total number of motion cycles; further, the collected wheel speed As the above formula (3) ,Will As the above formula (3) , the collected As the above formula (3) , and then fitted to get .

[0120] For example, the third wheel speed initial value Calculated by the following formula:

[0121] (4)

[0122] in, Indicates the initial value of the third wheel speed; Indicates the normal maximum wheel speed; represents the third fitting constant; express Fatigue indicator at all times.

[0123] Exemplary fatigue indicators It can be calculated by the following formula:

[0124] (5)

[0125] in, express Fatigue indicators at all times; express Heart rate at all times; Indicates maximum heart rate; Indicates the accumulated user power, where user power refers to the work done by the user per unit time during cycling; Indicates the empirical user power value.

[0126] For example, the fourth wheel speed initial value Calculated by the following formula:

[0127] (6)

[0128] in, Indicates the initial value of the fourth wheel speed; Indicates basic wheel speed; represents the fourth fitting constant; Indicates cadence; Indicates average baseline cadence.

[0129] It can be seen from formula (6) that the cadence and the initial value of the fourth wheel speed are positively correlated. This is because the higher the cadence, the more active the rider is exerting force. At this time, it is determined that the user wants to increase the riding speed, so the initial value of the fourth wheel speed is increased to increase the target wheel speed.

[0130] Furthermore, a weighted sum is performed on the first wheel speed initial value, the second wheel speed initial value, the third wheel speed initial value, and the fourth wheel speed initial value to obtain the wheel speed initial value, as shown in the following formula:

[0131] (7)

[0132] in, express Initial value of wheel speed at time t; Indicates the initial value of the first wheel speed; Indicates the initial value of the second wheel speed; Indicates the initial value of the third wheel speed; Indicates the initial value of the fourth wheel speed; represents the first weight; represents the second weight; represents the third weight; Represents the fourth weight.

[0133] As an optional implementation, in step S212, the wheel speed trajectory formula is as follows:

[0134] (8)

[0135] in, express Target wheel speed at the moment; Indicates the initial value of wheel speed; Indicates the natural base; Indicates time; Represents the time constant.

[0136] It is worth noting that, since the user's target wheel speed / target acceleration often does not change significantly within a certain period of time and may also follow a certain change pattern, in some embodiments of the present invention, the target wheel speed trajectory formula is obtained by calculating the initial wheel speed value and substituting it into the wheel speed trajectory formula. Thereafter, over a period of time, the target wheel speed at different moments can be calculated by substituting different moment values ​​into the target wheel speed trajectory formula. This eliminates the need to collect target parameters and calculate the target wheel speed at each moment, thereby significantly reducing the amount of calculation while improving the accuracy of the target wheel speed calculation and achieving smooth control.

[0137] Exemplarily, in step S213, the target wheel speed trajectory formula is derived to obtain the target acceleration trajectory formula, as shown in the following formula:

[0138] (9)

[0139] in, express Target acceleration at the moment; express Target wheel speed at the moment; represents the differential symbol; Indicates the initial value of wheel speed; Indicates the natural base; Indicates time; express.

[0140] Compared with the prior art, the embodiment of the present invention obtains the target acceleration by calculating the target acceleration trajectory formula. There is no need to collect target parameters and calculate the target acceleration at every moment. This can significantly reduce the amount of calculation while improving the accuracy of target acceleration calculation, and can also achieve smooth control.

[0141] Furthermore, in some embodiments, the target acceleration should satisfy a preset acceleration limit condition. For example, the acceleration limit condition is as follows:

[0142] (10)

[0143] in, represents the target acceleration; Indicates the upper limit of target acceleration; Indicates the absolute value operation.

[0144] For example, You can take 2.0 (metre per second squared, meter per second squared).

[0145] Furthermore, since the wheel acceleration is proportional to the pedaling angular acceleration, the target acceleration is also proportional to the target pedaling angular acceleration, as shown in the following formula:

[0146] (11)

[0147] in, represents the target pedaling angular acceleration; Indicates the transmission speed ratio between man and vehicle; Indicates the target acceleration.

[0148] Then, equation (12) can be obtained from equation (10) and equation (11), which is used to limit the pedaling angular acceleration in some embodiments:

[0149] (12)

[0150] in, represents the target pedaling angular acceleration; Indicates the transmission speed ratio between man and vehicle; Indicates the upper limit of target acceleration; Indicates the absolute value operation.

[0151] Compared with the existing technology, the embodiment of the present invention calculates the target wheel speed based on human factors data, so that the final output power torque is more in line with human riding needs. In addition, the embodiment of the present invention can automatically predict the target wheel speed required by the user without the need for the user to manually input the target wheel speed, thereby achieving more intelligent electric bicycle control and improving the user's riding experience.

[0152] Compared with the prior art, the embodiments of the present invention, by adopting human factor data and trajectory formulas, can generate target wheel speeds and target accelerations that are more in line with human personalized needs and have more realistic physical meaning.

[0153] As one optional implementation manner, in step S23, the calculation of the initial target armature current based on the feedforward and error feedback control hybrid strategy according to the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope includes:

[0154] multiplying the target wheel speed and the wheel speed feedforward control coefficient to obtain a first feedforward control current value;

[0155] Multiplying the target acceleration and the acceleration feedforward control coefficient to obtain a second feedforward control current value;

[0156] Calculating a slope compensation control current value according to the slope; wherein the slope compensation control current value and the sine value of the slope are positively correlated;

[0157] calculating a wheel speed error between the target wheel speed and the actual wheel speed, and multiplying the wheel speed error by a wheel speed error feedback coefficient to obtain a first error feedback control current value;

[0158] calculating an acceleration error between the target acceleration and the actual acceleration, and multiplying the acceleration error by an acceleration error feedback coefficient to obtain a second error feedback control current value;

[0159] 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 are summed to obtain an initial target armature current.

[0160] For example, the initial target armature current Calculated by the following formula:

[0161] (13)

[0162] in, represents the initial target armature current; It represents the acceleration feedforward control coefficient, and the current is used to control the moment of inertia; represents the target acceleration; It represents the wheel speed feedforward control coefficient, which is the current control damping coefficient; Indicates the target rotation degree; Indicates the slope compensation coefficient; Indicates 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; Indicates the slope compensation control current value; represents the first error feedback control current value; Indicates the second error feedback control current value.

[0163] Furthermore, in some embodiments, the acceleration feedforward control coefficient can be calculated based on the mechanical motion equation of the electric power-assisted bicycle. and wheel speed feedforward control coefficient :

[0164] Specifically, the mechanical motion equation of the motor is shown as follows:

[0165] (14)

[0166] in, Indicates the motor's moment of inertia; Indicates the motor angular acceleration; Indicates the motor damping coefficient; Indicates the angular velocity of the motor; represents electromagnetic torque; represents the electromagnetic torque constant; Indicates the armature current.

[0167] Furthermore, the user's mechanical equation of motion is as follows:

[0168] (15)

[0169] in, represents the pedal moment of inertia; represents the pedaling angular acceleration; represents the pedal damping coefficient; represents the pedaling angular velocity; represents the applied torque; Represents the resistance torque.

[0170] Furthermore, the kinematic mechanical equation of the electric-assisted bicycle is as follows:

[0171] (16)

[0172] in, represents the moment of inertia of the wheel; represents acceleration; represents the wheel damping coefficient; Indicates wheel speed; represents the applied torque; represents electromagnetic torque; Represents the resistance torque.

[0173] Further, see Figure 6 , is a force diagram of an electric-assisted bicycle provided by an embodiment of the present invention, wherein, represents wind resistance, represents the component of gravity along the slope downward, represents rolling resistance, It represents the force component of the motor on the electric power-assisted bicycle that assists the bicycle upward along the slope. It represents the upward component of the force applied by the user to the electric bicycle along the slope. As shown in the following formula:

[0174] (17)

[0175] in, express; Indicates the wheel radius of an electric-assisted bicycle; Indicates wind resistance; It represents the component of gravity along the slope downward; Indicates rolling resistance.

[0176] It can be understood that the wheel speed is proportional to the pedaling angular velocity, and the pedaling angular acceleration is proportional to the wheel speed acceleration, as shown in Equations (18) and (19), respectively:

[0177] (18)

[0178] in, represents the pedaling angular velocity; Indicates the transmission speed ratio between man and vehicle; Indicates wheel speed.

[0179] (19)

[0180] in, represents the pedaling angular acceleration; Indicates the transmission speed ratio between man and vehicle; Indicates wheel speed acceleration.

[0181] Furthermore, by substituting formulas (18) and (19) into formula (15) and then subtracting them from formula (16), we can obtain the following formula:

[0182] (20)

[0183] in, represents the moment of inertia of the wheel; Indicates the transmission speed ratio between man and vehicle; represents the pedal moment of inertia; represents acceleration; represents the wheel damping coefficient; represents the pedal damping coefficient; Indicates wheel speed; Represents electromagnetic torque.

[0184] Furthermore, from formula (20) and formula (14), we can get formula (21) and (22)

[0185] (twenty one)

[0186] in, represents acceleration; Indicates the motor angular acceleration; Indicates the motor's moment of inertia; represents the moment of inertia of the wheel; Indicates the transmission speed ratio between man and vehicle; Indicates the pedal moment of inertia.

[0187] (twenty two)

[0188] in, Indicates wheel speed; Indicates the angular velocity of the motor; Indicates the motor damping coefficient; represents the wheel damping coefficient; Indicates the transmission speed ratio between man and vehicle; Indicates the pedal damping coefficient.

[0189] Furthermore, the acceleration feedforward control coefficient can be obtained and wheel speed feedforward control coefficient As shown in formula (23) and formula (24) respectively:

[0190] (twenty three)

[0191] in, represents the acceleration feedforward control coefficient; represents the moment of inertia of the wheel; Indicates the transmission speed ratio between man and vehicle; Indicates the pedal moment of inertia

[0192] (twenty four)

[0193] in, represents the wheel speed feedforward control coefficient; represents the wheel damping coefficient; Indicates the transmission speed ratio between man and vehicle; Indicates the pedal damping coefficient

[0194] Compared with the prior art, after calculating the target acceleration and target wheel speed, the embodiment of the present invention calculates the target armature current by introducing a hybrid strategy of feedforward control and feedback control (a hybrid strategy of feedforward and error feedback control). This can correct the error by combining error feedback while retaining the fast response and low latency of feedforward control, thereby enabling the target armature current to be calculated quickly and accurately.

[0195] For example, different control strategies can be used in different riding stages. The following examples are based on the starting stage, fatigue stage, cruising stage, and climbing stage. During the starting stage of an electric-assisted bicycle, the user's heart rate is low and the cadence is fast. At this time, the acceleration and armature current need to be increased to achieve a quick response. When the user's heart rate is fast and the riding time is long, it is determined that the user is in a fatigue state (fatigue stage). At this time, the comfort strategy is activated to regulate the armature current to reduce the wheel speed or reduce the acceleration to less than or equal to 0. In the cruising state, when the user's cadence and heart rate are stable, the wheel speed can be maintained unchanged, giving the user a good and stable riding experience. During the climbing stage, after the slope is detected by the inclination sensor, the slope compensation power assist is activated to reduce the user's riding burden.

[0196] As an optional implementation, in step S22, the human-machine hybrid output power is calculated using the following formula:

[0197] (25)

[0198] in, Indicates the human-machine mixed output power; represents the applied torque; Indicates the weight of the human-machine output ratio; Indicates the transmission speed ratio between man and vehicle; represents the wheel damping coefficient; represents the pedal damping coefficient; Indicates the motor damping coefficient; represents the assist torque; Indicates actual wheel speed.

[0199] It is worth noting that during riding, the greater the torque applied by the rider, the harder it is to ride and the worse the riding experience. Increasing the assist torque (i.e., electromagnetic torque) of the motor can reduce the torque applied by the rider. However, as the assist torque increases, the loss of the motor will also increase, resulting in a reduction in the service life of the motor. Therefore, in the embodiment of the present invention, an objective function is set to achieve the hybrid output power of the human-machine. The human-machine output ratio is allocated with the minimum as the goal, so as to optimize the motor output while achieving power assistance, and better balance the user's riding experience and the motor's service life.

[0200] Furthermore, the objective function of the embodiment of the present invention is shown as follows:

[0201] (26)

[0202] in, Indicates the minimum value operation; Indicates 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 electromagnetic torque; Indicates the motor speed angular velocity.

[0203] Furthermore, constraints need to be added when solving the above objective function, that is, it is also necessary to ensure that the motor power and target armature current do not exceed the upper limit. The specific formula is as follows:

[0204] (27)

[0205] in, represents the target armature current; Indicates the absolute value operation; Indicates the maximum value of armature current; Indicates motor power; represents electromagnetic torque; Indicates the angular velocity of the motor; Indicates the upper limit of motor power.

[0206] Furthermore, by substituting formula (18) and formula (21) into formula (26), another expression of the objective function can be obtained, as shown below:

[0207] (28)

[0208] in, Indicates the minimum value operation; Indicates the human-machine mixed output power; represents the applied torque; Indicates the weight of the human-machine output ratio; Indicates the transmission speed ratio between man and vehicle; represents the wheel damping coefficient; represents the pedal damping coefficient; Indicates the motor damping coefficient; It represents the power-assisting torque of the whole vehicle, which is the sum of the torque of the human and the motor, that is, ; Indicates wheel speed.

[0209] It is worth noting that in formula (28), The torque sensor collects 、 、 and is a fixed value, so by iterating different Solve the objective function to obtain the human-machine output ratio weight under the minimum human-machine mixed output power .

[0210] Furthermore, in some embodiments, for the convenience of solving, it is possible to , , then the minimum human-machine hybrid output power It can be further written about The function is as follows:

[0211] (29)

[0212] When A>B, then along with increases with the increase of The minimum value of Minimum, worth mentioning, when If the value of is too small, the purpose of assisting cannot be achieved. Therefore, in some embodiments, The minimum value can be set to 0.5, that is, when A>B, take ; Further, when A<B, then along with The increase of The maximum value of ,but minimum; further, when A=B, and If it is irrelevant, the initial armature current is taken as the target armature current.

[0213] Furthermore, in step S24, the human-machine output ratio weight is multiplied by the initial target armature current to obtain the target armature current, as shown in the following formula:

[0214] (30)

[0215] in, represents the target armature current; Indicates the weight of the human-machine output ratio; Indicates the initial target armature current.

[0216] As one of the optional implementations, the target acceleration satisfies the slope filtering and limiting constraint condition, and the target armature current satisfies the preset armature current constraint condition, wherein the armature current constraint condition includes at least one of the motor capacity constraint condition, the slope filtering and limiting constraint condition, and the emergency brake interruption constraint condition.

[0217] For example, the motor capacity constraint condition is as follows:

[0218] (31)

[0219] in, Indicates the maximum value of armature current; Indicates the target armature current.

[0220] Furthermore, the emergency brake interruption constraint condition means that when the emergency brake device is identified to be turned on, the target armature current Set to , thereby achieving a quick emergency stop and preventing danger from occurring.

[0221] Furthermore, the slope filter limit constraint condition refers to performing slope compensation between the set maximum slope and minimum slope, and adjusting the slope compensation coefficient according to the slope , exemplary, slope filtering and limiting constraints are as follows:

[0222] (32)

[0223] It can be understood that all or part of the processes in the electric assisted bicycle control method described in the embodiment of the present invention can be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned method embodiments.

[0224] Further, see Figure 7 , is a flow chart of an electric-assisted bicycle control method provided by another embodiment of the present invention, which can be organized into the following steps T1 to T8:

[0225] Step T1: Initialize the peripheral modules required by the controller, including the INTSYNC (Interrupt Synchronization) module, GPIO (General Purpose Input Output) module, ADC (Analog-to-Digital Converter), EPWM (Enhanced Pulse Width Modulation) module, and eCAP (Event Capture) module.

[0226] Step T2: Determine whether the interrupt flag of the eCAP module is triggered. If not, remain in the waiting state (which can be achieved through an empty loop or a no-operation instruction);

[0227] Step T3: When the interrupt flag of the EPWM module is triggered, the data acquisition and control calculation process begins;

[0228] Step T4: Use the ReadADCValues() function to read the voltage values ​​of multiple input channels and convert them into current system state parameters, including but not limited to actual armature current, slope, acceleration, and applied torque. The encoder values ​​are then read through the eCAP module to obtain wheel speed. It is worth noting that the various collected parameters also require data normalization, filtering, and calibration.

[0229] Step T5: Call the ComputeReferenceCurrent() function to calculate the target armature current of the current control cycle based on the above-collected parameters and the preset physical model (Also called armature current reference value); It is worth noting that when calculating the target armature current When , it is also necessary to add constraints such as slope filtering and limiting constraints;

[0230] Step T6: Calculate the error between the actual armature current and the target armature current , and use the error as the input of the controller, which is determined and discretized in MATLAB (Matrix Laboratory) in advance. The transfer function calculates the controller output, which is the output PWM duty cycle modulation value;

[0231] Step T7: Write the duty cycle modulation value into CMPA (Compare Register A) and CMPB (Compare Register B) of the EPWM module to output a PWM control signal to drive the motor current closed-loop control.

[0232] Step T8: Clear the interrupt flag and prepare to enter the next control cycle.

[0233] It is worth noting that this process can be executed periodically to achieve armature current control based on real-time status and human intention, thereby improving the response speed of the electric power-assisted bicycle (power-assisted) control system to provide a more comfortable riding experience.

[0234] Furthermore, the power-assisting effect of the electric power-assisted bicycle control of the present invention is illustrated below through some experimental data.

[0235] See also Figure 8 and Figure 9, are schematic diagrams of the experimental results without and with the inclination sensor, respectively. Speed ​​refers to the speed of the electric-assisted bicycle, applied torque refers to the torque applied by the person, and assist torque refers to the output torque of the motor, also known as the electromagnetic torque. In both experiments, the electric-assisted bicycle was ridden on a slope with an inclination of 30 degrees at t=1s.

[0236] Depend on Figure 8 As can be seen, starting at t = 1s, the inclination angle gradually increases from 0° to 30°, and the resistance experienced by the e-bike during the uphill climb gradually increases. Furthermore, since the inclination sensor is not included and cannot identify the uphill slope, the assist torque cannot be increased at the beginning of the uphill climb, resulting in a decrease in speed after the rider feels the resistance. Furthermore, as the speed difference changes, the assist torque increases as the speed difference increases, and the rider's applied torque also increases. Ultimately, the rider's applied torque and the motor's assist torque become equal, while the speed first decreases, then overshoots, and finally returns to the original speed. As shown in Figure 8, the lack of an inclination sensor results in a certain delay in adjusting the assist torque.

[0237] Further, by Figure 9 It can be seen that starting from t=1s, the inclination angle gradually increases from 0° to 30°, and the resistance encountered by the electric bicycle gradually increases during the uphill process; at this time, due to the addition of the inclination sensor, the uphill can be identified. In the embodiment of the present invention, the slope compensation coefficient Take 1, the electric bicycle is running in the climbing state, and the target armature current is generated and tracked according to human factors data, etc. Figure 9 It can be seen that compared with the control based on speed difference without adding the inclination sensor, the embodiment of the present invention can increase the power-assist torque more timely, improve the response speed and provide a more comfortable riding experience.

[0238] Further, see Figure 10 , is a comparison diagram of the armature current tracking effects of different controllers under sudden speed increase provided by an embodiment of the present invention, wherein the horizontal axis represents time (t) in seconds (seconds), the vertical axis represents the armature current in amperes (amperes), the green dotted line (Id reference) represents the armature current reference value (target armature current), the purple solid line (PI control) represents the actual armature current under the traditional PI (Proportional – Integral) controller, and the orange solid line ( control) indicates tradition The actual armature current under the controller, the blue solid line ( control) The actual armature current under the controller is given by Figure 10 It can be seen that the embodiment of the present invention provides The controller has better robustness and accuracy in a multi-disturbance environment and can well complete the power assistance task under non-ideal working conditions.

[0239] Understandably, the design The controller process involves determining the linear mathematical model of the controlled system Based on the weight function W(s), the augmented matrix P(s) is obtained by selecting the weight function W(s), and then the transfer function of the H∞ controller is obtained in the MATLAB robust toolbox. .

[0240] Furthermore, in the embodiment of the present invention, the controlled system is the aforementioned The control link is modeled as a G(s) controlled system, and its transfer function is as follows:

[0241] (33)

[0242] Where K represents the controlled system gain; T represents the delay time constant; represents the damping coefficient of the controlled system; represents a complex variable.

[0243] 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 as follows:

[0244] ; (34)

[0245] in, represents the first weight function; represents the second weight function; represents the third weight function; represents a complex variable.

[0246] Furthermore, using the hinfsyn function in the MATLAB robust control toolbox, according to the controlled system and weight function, the transfer function of the H∞ controller can be obtained as shown below:

[0247] (35)

[0248] in, represents the transfer function of the H∞ controller; represents a complex variable.

[0249] Further, see Figure 11 , is provided by an embodiment of the present invention The Nyquist diagram of FIG1 shows the Nyquist curve of “H∞ controller + controlled object G(s)”. As can be seen from the diagram, all roots of the system are on the left half plane and there are no unstable roots. Therefore, the closed-loop system of the embodiment of the present invention is stable.

[0250] See also Figure 12 The embodiment of the present invention further provides an electric-assisted bicycle control device 10, comprising:

[0251] Parameter input module 11, used for inputting target parameters and actual armature current;

[0252] a target armature current calculation module 12, configured to calculate the target armature current according to the target parameters;

[0253] The assist torque calculation module 13 is used to input the target armature current and the actual armature current into Controller, output motor control signal,

[0254] The power-assist torque control module 14 is used to adjust the power-assist torque of the electric power-assist bicycle according to the motor control signal;

[0255] Among them, in the In the controller, the motor control signal is calculated in the following way:

[0256] Inputting the target armature current and the actual armature current into an error amplifier to obtain a current following error;

[0257] The current following error input The controller obtains the initial reference current;

[0258] Summing the initial reference current and the slope compensation signal to obtain a target reference current;

[0259] The target reference current and the actual armature current are input into a comparator, and a motor control signal is output.

[0260] The electric-assisted bicycle control device provided in an embodiment of the present invention can implement all the process steps of the electric-assisted bicycle control method described in the above embodiment. The functions and technical effects achieved by each module and unit in the device are respectively the same as the functions and technical effects achieved by the electric-assisted bicycle control method described in the above embodiment. The specific implementation method will not be repeated here.

[0261] To achieve the above objectives, an embodiment of the present invention further provides an electric-assisted bicycle, comprising an electric-assisted bicycle body and an electric-assisted bicycle control device as described in any of the above embodiments.

[0262] Compared with the prior art, the electric power bicycle control method, device and electric power bicycle provided by the embodiment of the present invention input the target parameter and the actual armature current; calculate the target armature current according to the target parameter; input the target armature current and the actual armature current into the control method, device and electric power bicycle provided by the embodiment of the present invention; The controller outputs a motor control signal; adjusts the power torque of the electric power-assisted bicycle according to the motor control signal; wherein, In the controller, the motor control signal is calculated by: inputting the target armature current and the actual armature current into the error amplifier to obtain the current following error; inputting the current following error into the error amplifier The controller obtains an initial reference current; sums the initial reference current and the 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. Controller with both Advantages of fast control response and The control has strong anti-interference ability and can meet the high dynamic and high robustness control requirements of electric assisted bicycles.

[0263] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for controlling an electric power-assisted bicycle, characterized in that: include: Input target parameters and actual armature current; calculating a target armature current according to the target parameter; The target armature current and the actual armature current are input into A controller that outputs motor control signals; adjusting the power-assisting torque of the electric-assisted bicycle according to the motor control signal; Among them, in the In the controller, the motor control signal is calculated in the following way: Inputting the target armature current and the actual armature current into an error amplifier to obtain a current following error; The current following error input The controller obtains the initial reference current; Summing the initial reference current and the slope compensation signal to obtain a target reference current; Inputting the target reference current and the actual armature current into a comparator and outputting a motor control signal; 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: calculating a target wheel speed and a target acceleration based on the human factors data; According to the applied torque and the actual assist torque, the human-machine output ratio weight is calculated with the goal of minimizing the human-machine hybrid output power; Calculating an initial target armature current based on the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration, and the slope based on a feedforward and error feedback control hybrid strategy; Multiplying the human-machine output ratio weight by the initial target armature current to obtain a target armature current; The human-machine hybrid output power is calculated by the following formula: in, Indicates the human-machine mixed output power; represents the applied torque; Indicates the weight of the human-machine output ratio; Indicates the transmission speed ratio between man and vehicle; represents the wheel damping coefficient; represents the pedal damping coefficient; Indicates the motor damping coefficient; represents the assist torque; Indicates actual wheel speed.

2. The electric-assisted bicycle control method according to claim 1, wherein: Calculating the target wheel speed and target acceleration according to the human factor data includes: generating an initial wheel speed value according to the human factor data; 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; The target wheel speed trajectory formula is derived to obtain a target acceleration trajectory formula for calculating the target acceleration.

3. The electric-assisted bicycle control method according to claim 2, wherein: The human factor data includes heart rate, subjective score, fatigue index and cadence; then, generating the initial wheel speed value based on the human factor data includes: Calculating a first wheel speed initial value based on the heart rate; wherein the heart rate and the first wheel speed initial value are negatively correlated; Calculating a second wheel speed initial value based on the subjective score; wherein the subjective score and the second wheel speed initial value are negatively correlated; Calculating an initial value of a third wheel speed according to the fatigue index; wherein the fatigue index and the initial value of the third wheel speed are negatively correlated; Calculating a fourth wheel speed initial value according to the cadence; wherein the cadence and the fourth wheel speed initial value are positively correlated; A weighted sum is performed on the first wheel speed initial value, the second wheel speed initial value, the third wheel speed initial value, and the fourth wheel speed initial value to obtain a wheel speed initial value.

4. The electric-assisted bicycle control method according to claim 2, wherein: The wheel speed trajectory formula is shown below: in, express Target wheel speed at the moment; Indicates the initial value of wheel speed; Indicates the natural base; Indicates time; Represents the time constant.

5. The electric-assisted bicycle control method according to claim 1, wherein: The feedforward and error feedback control hybrid strategy is based on the target wheel speed, the actual wheel speed, the target acceleration, the actual acceleration and the slope, and calculates the initial target armature current, including: multiplying the target wheel speed and the wheel speed feedforward control coefficient to obtain a first feedforward control current value; Multiplying the target acceleration and the acceleration feedforward control coefficient to obtain a second feedforward control current value; Calculating a slope compensation control current value according to the slope; wherein the slope compensation control current value and the sine value of the slope are positively correlated; calculating a wheel speed error between the target wheel speed and the actual wheel speed, and multiplying the wheel speed error by a wheel speed error feedback coefficient to obtain a first error feedback control current value; calculating an acceleration error between the target acceleration and the actual acceleration, and multiplying the acceleration error by an acceleration error feedback coefficient to obtain a second error feedback control current value; 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 are summed to obtain an initial target armature current.

6. The electric-assisted bicycle control method according to claim 1, wherein: The target acceleration satisfies a slope filtering and limiting constraint condition, and the target armature current satisfies a preset armature current constraint condition, wherein the armature current constraint condition includes at least one of an acceleration limiting condition, a motor capacity constraint condition, and an emergency brake interruption constraint condition.

7. An electric power-assisted bicycle control device, characterized in that: The electric-assisted bicycle control device is applied to the electric-assisted bicycle control method according to claim 1, and the electric-assisted bicycle control device includes: Parameter input module, used to input target parameters and actual armature current; a target armature current calculation module, configured to calculate the target armature current according to the target parameters; The power torque calculation module is used to input the target armature current and the actual armature current into the Controller, output motor control signal, An assist torque control module, configured to adjust the assist torque of the electric-assisted bicycle according to the motor control signal; Among them, in the In the controller, the motor control signal is calculated in the following way: Inputting the target armature current and the actual armature current into an error amplifier to obtain a current following error; The current following error input The controller obtains the initial reference current; Summing the initial reference current and the slope compensation signal to obtain a target reference current; The target reference current and the actual armature current are input into a comparator, and a motor control signal is output.

8. An electric power-assisted bicycle, characterized in that: The invention comprises an electric-assisted bicycle body and the electric-assisted bicycle control device as claimed in claim 7 .

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