Direct drive type intelligent cycling platform, inertia simulation system and method thereof, and storage medium

Abstract

The application discloses a kind of inertia simulation systems of direct drive type intelligent riding platform, including simulation inertia control system, inverter and motor;Simulation inertia control system, based on the dynamic compensation torque signal generated by motor acceleration change, for compensating the torque error generated by the difference between the rotational inertia of motor output and target rotational inertia under the same driving torque, it converts the dynamic compensation torque signal into the control signal of inverter, controls the voltage signal of inverter to motor, so that the torque generated by motor and target torque error tend to 0.The application also provides a kind of inertia simulation method of direct drive type intelligent riding platform.The application replaces the mechanical flywheel and transmission structure design necessary in traditional method, so that the mechanical structure of riding platform is simplified, so as to improve the operation reliability of riding platform, save hardware cost, and reduce the overall weight of riding platform system.

Description

TECHNICAL FIELD

[0001] The present application relates to a riding platform, in particular to a direct drive type intelligent riding platform and an inertia simulation system and method thereof, and a storage medium. BACKGROUND

[0002] As an environmentally friendly and healthy way of travel, bicycles have become the choice of more and more people. However, bad weather, congested traffic and complex road conditions often affect people's cycling plans. Therefore, indoor cycling platforms have emerged to make cycling no longer affected by objective factors and safer.

[0003] Currently, the implementation schemes of the cycling platforms on the market are mainly drum-type cycling platforms, fixed friction-type cycling platforms and belt drive-type cycling platforms.

[0004] The drum-type cycling platform utilizes the differential speed between the drum and the front and rear wheels to generate friction and thus apply cycling resistance to the wheels. Although this scheme has a simple structure, the pure mechanical structure cannot adjust the resistance and cannot simulate the cycling inertia.

[0005] The fixed friction-type cycling platform connects the bicycle rear hook claw with the cycling platform in a fixed manner, and the rolling shaft of the cycling platform is in frictional contact with the bicycle rear wheel. The rolling shaft is reversed to generate friction with the bicycle rear wheel through the self-liquid resistance structure of the rolling shaft or the control motor to simulate the cycling inertia. The structure of the fixed friction-type cycling platform determines that the rolling shaft and the wheel cannot achieve ideal state without sliding friction. The loss caused by the sliding between the rolling shaft and the wheel makes this type of cycling platform only simulate the trend of cycling inertia.

[0006] The belt drive-type cycling platform connects the bicycle rear wheel shaft with the solid flywheel of the cycling platform, and simulates the phenomenon of continuous driving of the bicycle caused by the kinetic energy of the mass inertia of the flywheel. In addition to the solid flywheel, the belt drive-type cycling platform also configures a motor connected with the solid flywheel through a belt. The rotation direction and torque of the motor are controlled to transmit the motor torque to the solid flywheel through the belt to simulate the cycling inertia. Although the cooperation of the solid flywheel and the motor can achieve the simulation of the cycling inertia, and the transmission belt can solve the problem of sliding to a certain extent, the complex mechanical structure and the use of vulnerable and consumable parts such as the belt in the key transmission part reduce the reliability of the cycling platform; the power loss caused by the transmission structure, the transmission ratio conversion; the increase of the elastic deformation of the belt due to the increase of the temperature of the belt after the cycling platform runs for a long time, resulting in inaccurate simulation load; the complex and difficult-to-implement calibration algorithm; and the difficulty in realizing stepless inertia simulation due to the weight limitation of the flywheel, are still problems that cannot be ignored for the belt drive-type cycling platform. At the same time, the motor needs to cooperate with the heavy mechanical flywheel, which greatly increases the weight of the cycling platform system, making the storage and use of the cycling platform very inconvenient. SUMMARY

[0007] The application provides a direct-drive intelligent riding platform, an inertia simulation system and method thereof and a storage medium to solve the technical problems in the prior art.

[0008] The technical scheme adopted by the application to solve the technical problems in the prior art is as follows: an inertia simulation system of a direct-drive intelligent riding platform, comprising a simulation inertia control system, an inverter and a motor; the simulation inertia control system generates a dynamic compensation torque signal based on motor acceleration variation, is used for compensating torque error generated by the difference between the rotational inertia of the motor and target rotational inertia under the same driving torque, converts the dynamic compensation torque signal into a control signal of the inverter, controls the inverter to output a voltage signal to the motor, and makes the torque generated by the motor tend to 0.

[0009] Further, the system further comprises a signal detection system, which is used for detecting motor stator winding current, motor speed and phase.

[0010] Further, the simulation inertia control system comprises: an inertia simulation unit for simulating dynamic rotational inertia in a riding process, first to third PI regulators, a Clark converter, a Park converter, a Park inverse converter and a space vector pulse width modulator; the Clark converter inputs detected motor three-phase winding current signals and converts them into current signals in an α, β coordinate system and outputs them to the Park converter; the Park converter converts the current signals in the α, β coordinate system into current signals in a d, q coordinate system and outputs them as current feedback signals; the inertia simulation unit inputs detected motor speed signals, generates dynamic rotational inertia, converts the dynamic rotational inertia into a speed signal and outputs the speed signal as a motor speed reference signal; the first PI regulator inputs the difference between the motor speed reference signal and the detected motor speed signal, generates a reference current signal; the second PI regulator inputs the difference between the reference current signal and the q-axis current signal from the Park converter, generates a q-axis voltage control signal; the third PI regulator inputs the difference between a set d-axis current reference signal and the d-axis current signal from the Park converter, generates a d-axis voltage control signal; the Park inverse converter inputs the voltage control signals in the d, q coordinate system from the second and third PI regulators, converts them into voltage control signals in the α, β coordinate system and outputs them to the space vector pulse width modulator; the space vector pulse width modulator outputs a pulse signal to the inverter; and the inverter outputs a voltage signal to the motor.

[0011] Further, the mathematical model expression of the inertia simulation unit is as follows:

[0012]

[0013] J s =J f -JM ;

[0014] J M is the motor rotational inertia;

[0015] J f is the simulated flywheel rotational inertia;

[0016] J s is the difference between the simulated flywheel rotational inertia and the motor rotational inertia;

[0017] ω ref is the reference angular velocity;

[0018] ω fed is the feedback angular velocity, which is converted from the detected motor rotational speed signal;

[0019] K q is the electromagnetic torque coefficient;

[0020] i q is the motor stator q-axis current;

[0021] K ω is the simulated speed-dependent load torque compensation coefficient during cycling;

[0022] T b is the base load torque during simulated cycling;

[0023] T s is the dynamic compensation torque signal based on the motor acceleration change;

[0024] ω min is the minimum compensation speed;

[0025] m is the total weight of the human and the direct-drive intelligent cycling platform;

[0026] r is the radius of the wheel;

[0027] t is time;

[0028] i is the transmission ratio, representing the gear ratio of the gear connected to the pedal to the gear connected to the wheel.

[0029] The application also provides a direct-drive intelligent cycling platform, which comprises the inertia simulation system of the direct-drive intelligent cycling platform.

[0030] The application further provides an inertia simulation method of a direct-drive intelligent riding platform, which comprises an inertia simulation control system, an inverter and a motor.

[0031] Further, a signal detection system is arranged, which is used for detecting motor stator winding current, motor rotating speed and phase.

[0032] Further, the inertia simulation control system comprises an inertia simulation unit for simulating dynamic rotating inertia in the riding process, first to third PI regulators, a Clark converter, a Park converter, a Park inverse converter and a space vector pulse width modulator; the Clark converter inputs detected motor three-phase winding current signals and converts them into current signals in an α, β coordinate system and outputs them to the Park converter; the Park converter converts the current signals in the α, β coordinate system into current signals in a d, q coordinate system and outputs them as current feedback signals; the inertia simulation unit inputs detected motor rotating speed signals, generates dynamic rotating inertia, converts the dynamic rotating inertia into speed signals and outputs them as motor speed reference signals; the first PI regulator inputs the difference between the motor speed reference signals and the detected motor rotating speed signals, generates reference current signals; the second PI regulator inputs the difference between the reference current signals and the q-axis current signals from the Park converter, generates q-axis voltage control signals; the third PI regulator inputs the difference between the set d-axis current reference signals and the d-axis current signals from the Park converter, generates d-axis voltage control signals; the Park inverse converter inputs the voltage control signals in the d, q coordinate system from the second and third PI regulators, converts them into voltage control signals in the α, β coordinate system and outputs them to the space vector pulse width modulator; the space vector pulse width modulator outputs pulse signals to the inverter; and the inverter outputs voltage signals to the motor.

[0033] Further, the inertia simulation unit is constructed by using the following mathematical model:

[0034]

[0035] J s =J f -J M ;

[0036] J M is the motor rotating inertia;

[0037] J f is the simulated flywheel rotating inertia;

[0038] J s is the difference between the flywheel moment of inertia and the motor moment of inertia;

[0039] ω ref is the reference angular velocity;

[0040] ω fed is the feedback angular velocity, which is converted from the detected motor speed signal;

[0041] K q is the electromagnetic torque coefficient;

[0042] i q is the motor stator q-axis current;

[0043] K ω is the speed-dependent load torque compensation coefficient during the simulation of cycling;

[0044] T b is the basic load torque during the simulation of cycling;

[0045] T s is the dynamic compensation torque signal based on the motor acceleration change;

[0046] ω min is the minimum compensation speed;

[0047] m is the total weight of the person and the whole direct-drive intelligent cycling platform;

[0048] r is the radius of the wheel;

[0049] t is time;

[0050] i is the transmission ratio, representing the gear ratio of the gear connected to the pedal and the gear connected to the wheel.

[0051] The application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the inertia simulation method steps of the direct-drive intelligent cycling platform.

[0052] The present application has the advantages and positive effects that: for a given riding platform self weight, user weight, mechanical structure and sensed motor speed, the system compensation inertia is coupled to the dynamic compensation torque by combining the dynamic equation. The dynamic equation is combined with the inertia simulation equation, the dynamic compensation torque is converted into a speed control quantity, and the speed control quantity is applied to the control system of the inverter to realize inertia simulation. The present application solves the problems of uneven output simulation riding load, feeling of stepping out, etc. caused by the weight of the mechanical flywheel in the traditional mechanical inertia and speed tracking scheme, realizes the non-polarized simulation of riding resistance and inertia under different users and different road conditions, solves the problems of power loss and transmission ratio conversion of the transmission structure caused by the belt transmission in the traditional scheme, and the increase of the elastic deformation of the belt due to the temperature rise of the belt after the long-time running of the riding platform, and the inaccurate simulation load caused by the complex calibration algorithm, optimizes the simulation performance of the riding platform, replaces the mechanical flywheel and transmission structure design necessary in the traditional method, simplifies the mechanical structure of the riding platform, improves the operation reliability of the riding platform, saves the hardware cost, and reduces the overall weight of the riding platform system. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 is a direct drive type intelligent riding platform structure schematic diagram of the present application.

[0054] Figure 2 is a direct drive type intelligent riding platform inertia simulation system working process schematic diagram of the present application.

[0055] Figure 3 is a direct drive type intelligent riding platform inertia simulation system working principle diagram of the present application.

[0056] Figure 4 is a target speed and actual speed simulation result of the motor under the traditional mechanical inertia and speed tracking control.

[0057] Figure 5 is a target speed and actual speed simulation result of the motor using the direct drive type intelligent riding platform inertia simulation system of the present application.

[0058] IN THE DRAWINGS:

[0059] PI1 is a first PI regulator, PI2 is a second PI regulator, and PI3 is a third PI regulator.

[0060] Inv Park represents a Park inverse transformer.

[0061] Park represents a Park transformer.

[0062] Clark represents a Clark transformer.

[0063] SVPWM is a space vector pulse width modulator.

[0064] θ is the motor phase angle.

[0065] z is a z factor.

[0066] i abc is the motor stator winding current variable in the three-phase stationary, 120°-phase-difference abc coordinate system.

[0067] i a , i b , i c is the a-phase current, b-phase current, and c-phase current in the abc coordinate system.

[0068] i α is the motor stator α-axis current. β is the motor stator β-axis current.

[0069] i d is the motor stator d-axis current. q is the motor stator q-axis current.

[0070] v α is the motor stator α-axis voltage. β is the motor stator β-axis voltage.

[0071] v d is the motor stator d-axis voltage. q is the motor stator q-axis voltage.

[0072] i dfed is the motor stator d-axis feedback current.

[0073] i qfed is the motor stator q-axis feedback current.

[0074] J M is the motor moment of inertia.

[0075] J0 is the self-weight inertia during the simulation of the cycling process.

[0076] ω ref is the reference angular velocity.

[0077] ω fed is the feedback angular velocity, which is converted from the detected motor speed signal.

[0078] K q is the electromagnetic torque coefficient.

[0079] K ω is the speed-dependent load torque compensation coefficient during the simulation of the cycling process.

[0080] T bTo simulate the base load torque in the process of riding.

[0081] ω min For the minimum compensation speed. DETAILED DESCRIPTION

[0082] To further understand the invention content, features and effects of the present application, the following examples are listed, and the detailed description is as follows:

[0083] Please see Figures 1 to 5 The inertia simulation system of the direct-drive intelligent riding platform comprises a simulation inertia control system, an inverter and a motor. The simulation inertia control system generates a dynamic compensation torque signal based on the acceleration change of the motor, and is used to compensate the torque error generated by the difference between the rotational inertia of the motor and the target rotational inertia under the same driving torque. The simulation inertia control system converts the dynamic compensation torque signal into a control signal of the inverter, controls the output voltage signal of the inverter to the motor, and makes the torque generated by the motor tend to 0.

[0084] Preferably, the inertia simulation system of the direct-drive intelligent riding platform further comprises a signal detection system for detecting the motor stator winding current, the motor speed and the phase. The signal detection system can detect the motor stator winding current, the motor speed and the phase by using the sensors in the prior art and the calculation software in the prior art. The signal detection system can output the motor three-phase stator winding current signal, the motor speed feedback signal and the motor phase signal.

[0085] Preferably, the simulation inertia control system can comprise: an inertia simulation unit for simulating dynamic moment of inertia in the process of riding, first to third PI regulators, a Clark converter, a Park converter, a Park inverse converter and a space vector pulse width modulator; the Clark converter inputs detected motor three-phase stator winding current signals and converts them into current signals in the α, β coordinate system and outputs them to the Park converter; the Park converter converts the current signals in the α, β coordinate system into current signals in the d, q coordinate system and outputs them as current feedback signals; the inertia simulation unit can input detected motor speed signals and generate dynamic moment of inertia, which can be converted into speed signals and output as motor speed reference signals; the first PI regulator can input the difference between the motor speed reference signals and the detected motor speed signals and generate reference current signals; the second PI regulator can input the difference between the reference current signals and the q-axis current signals from the Park converter and generate q-axis voltage control signals; the third PI regulator can input the difference between the set d-axis current reference signals and the d-axis current signals from the Park converter and generate d-axis voltage control signals; the Park inverse converter can input the voltage control signals in the d, q coordinate system from the second and third PI regulators, convert them into voltage control signals in the α, β coordinate system and output them to the space vector pulse width modulator; the space vector pulse width modulator outputs pulse signals to the inverter; and the inverter outputs voltage signals to the motor. The d-axis current reference signals can be set to 0.

[0086] Preferably, the mathematical model expression of the inertia simulation unit can be as follows:

[0087]

[0088] J s = J f - J M ;

[0089] J M is the motor moment of inertia;

[0090] J f is the simulated flywheel moment of inertia;

[0091] J s is the difference between the simulated flywheel moment of inertia and the motor moment of inertia;

[0092] ω ref is the reference angular velocity;

[0093] ω fed is the feedback angular velocity, which is converted from the detected motor speed signals;

[0094] K q is the electromagnetic torque coefficient;

[0095] i q is the q-axis current of the motor stator;

[0096] K ω is the speed-related load torque compensation coefficient during the simulation of riding process;

[0097] T b is the basic load torque during the simulation of riding process;

[0098] T s is the dynamic compensation torque signal generated based on the acceleration change of the motor;

[0099] ω min is the minimum compensation speed;

[0100] m is the total weight of the human and the whole direct-drive intelligent riding platform;

[0101] r is the radius of the wheel;

[0102] t is time;

[0103] i is the transmission ratio, representing the ratio of the number of teeth of the gear connected to the pedal to the number of teeth of the gear connected to the wheel.

[0104] The application also provides a direct-drive intelligent riding platform embodiment, which comprises the inertia simulation system of the direct-drive intelligent riding platform described above. The direct-drive intelligent riding platform can further comprise a communication module, which can wirelessly or wirelessly establish a connection, interaction and communication between the simulation inertia control system and a user terminal. The user terminal can be a computer, a tablet computer, a mobile phone or the like.

[0105] The application also provides an inertia simulation method embodiment of a direct-drive intelligent riding platform, which sets an simulation inertia control system, an inverter and a motor. The simulation inertia control system generates a dynamic compensation torque signal based on the acceleration change of the motor, which is used to compensate the torque error generated by the difference between the rotational inertia of the motor and the target rotational inertia under the same driving torque. The simulation inertia control system converts the dynamic compensation torque signal into a control signal of the inverter, controls the inverter to output a voltage signal to the motor, and makes the torque generated by the motor tend to 0.

[0106] Preferably, the inertia simulation method of the direct-drive intelligent riding platform can further set a signal detection system, which can be used to detect the motor stator winding current, the rotational speed and the phase of the motor.

[0107] Preferably, the simulation inertia control system can be provided with: an inertia simulation unit for simulating dynamic rotational inertia in the process of riding, first to third PI regulators, a Clark converter, a Park converter, a Park inverse converter and a space vector pulse width modulator; the Clark converter inputs the motor three-phase winding current signal detected and converts the same into an α, β coordinate system current signal output to the Park converter; the Park converter converts the α, β coordinate system current signal into a d, q coordinate system current signal as an output of current feedback signal; the inertia simulation unit inputs the motor speed signal detected and generates dynamic rotational inertia, which converts the dynamic rotational inertia into a speed signal as an output of motor speed reference signal; the first PI regulator inputs the difference between the motor speed reference signal and the motor speed signal detected and generates a reference current signal; the second PI regulator inputs the difference between the reference current signal and the q-axis current signal from the Park converter and generates a q-axis voltage control signal; the third PI regulator inputs the difference between the set d-axis current reference signal and the d-axis current signal from the Park converter and generates a d-axis voltage control signal; the Park inverse converter inputs the d, q coordinate system voltage control signals from the second and third PI regulators and converts the same into an α, β coordinate system voltage control signal output to the space vector pulse width modulator; the space vector pulse width modulator outputs a pulse signal to the inverter; and the inverter outputs a voltage signal to the motor.

[0108] Preferably, the inertia simulation unit can be constructed by using the following mathematical model:

[0109]

[0110] J s = J f - J M ;

[0111] J M is the motor rotational inertia;

[0112] J f is the simulated flywheel rotational inertia;

[0113] J s is the difference between the simulated flywheel rotational inertia and the motor rotational inertia;

[0114] ω ref is the reference angular velocity;

[0115] ω fed is the feedback angular velocity, which is converted from the motor speed signal detected;

[0116] K q is the electromagnetic torque coefficient;

[0117] i q is the motor stator q-axis current;

[0118] K ω is a speed-related load torque compensation coefficient for simulating the riding process;

[0119] T b is a basic load torque for simulating the riding process;

[0120] T s is a dynamic compensation torque signal generated based on the motor acceleration change;

[0121] ω min is a minimum compensation speed;

[0122] m is the total weight of the person and the whole direct-drive intelligent riding platform;

[0123] r is the radius of the wheel;

[0124] t is time;

[0125] i is a transmission ratio, representing the gear ratio of the gear connected to the pedal and the gear connected to the wheel.

[0126] The application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the inertia simulation method steps of the direct-drive intelligent riding platform.

[0127] The readable storage medium, communication module, first to third PI regulators, Clark converter, Park converter, Park inverse converter, space vector pulse width modulator, communication module, inverter, motor and other devices and components in the above can adopt the components, equipment applicable in the prior art, or be composed of components and equipment in the prior art, or be constructed by software and electronic components in the prior art.

[0128] The inertia simulation unit and signal detection system in the above can be composed of components in the prior art, or be constructed by software and electronic components in the prior art.

[0129] The working principle of the application is as follows:

[0130] The Clark converter inputs the motor three-phase stator winding current signal from the signal detection system, that is, inputs the current variable in the three-phase stationary and 120°-offset abc coordinate system, and converts it into the current variable in the two-phase stationary and 90°-offset αβ coordinate system.

[0131] Park converter converts stationary α,β coordinate system signal to rotating d,q coordinate system signal; since the tracking effect of PID controller to direct current reference signal is better, stationary α,β coordinate system needs to be converted to rotating d,q coordinate system (Park conversion is also called 2s / 2r conversion) after Clark conversion.

[0132] Park inverse converter converts rotating d,q coordinate system signal to stationary α,β coordinate system signal.

[0133] The implementation of SVPWM algorithm uses stationary coordinate system α,β, so i d / v d ,i q / v q After PI or PID operation, Park inverse conversion is needed to convert to α,β coordinate system.

[0134] The traditional mechanical inertia method is to connect the rear wheel shaft of the bicycle with the mechanical flywheel, and to simulate the kinetic energy caused by the bicycle continuous driving phenomenon by the mass inertia of the mechanical flywheel itself. In addition to the mechanical flywheel or the configuration of the motor connected with it through the belt, the motor torque is transmitted to the mechanical flywheel through the control of the motor rotation direction and rotation torque through the belt drive to generate the simulated riding inertia.

[0135] Ignoring the influence of mechanical friction, the dynamic equation of the cycling platform using the traditional mechanical inertia method is:

[0136]

[0137] In the formula: T p is the driving torque; T L is the load torque; J f is the flywheel moment of inertia; ω is the angular velocity.

[0138] Ignoring the influence of mechanical friction, the dynamic equation of the load simulation motor using the flywheel-free design is:

[0139]

[0140] In the formula: T p is the driving torque; T L is the load torque; J M is the motor moment of inertia; ω is the angular velocity.

[0141] Under the action of the same driving torque T p and load torque T L , if the motor angular velocity change is consistent, the motor needs to simulate the moment of inertia J s is:

[0142] Js = J f - J M . (3)

[0143] Substitute formula (3) into formula (1) to get:

[0144]

[0145] In the above formula, record:

[0146]

[0147] Compare formula (2), formula (4), T s That is, the dynamic compensation torque generated by the motor according to its acceleration change is simulated by the inertia. dω can be taken as dω fed .

[0148] Considering the influence of the self-weight of the cycling platform, the weight of the user and the mechanical structure on the inertia, the self-weight inertia in the cycling process is simulated as:

[0149]

[0150] In the formula, m is the total weight of the person and the direct-drive intelligent cycling platform complete machine; r is the radius of the wheel; i is the transmission ratio.

[0151] The load torque T L of the cycling platform can be obtained by the following formula:

[0152] T L = (T ω + T b ) K a (7)

[0153] T ω = K ω ω fed (8)

[0154]

[0155] In the formula, T ω is the speed-related load torque in the simulated cycling process; T b is the basic load torque in the simulated cycling process, which is selected according to the simulated cycling slope and road conditions, and the basic load torque T B is known; K a is the speed compensation coefficient of the load in the simulated cycling process; ω min is the minimum compensation speed; ω fed is the detected motor speed, K ω is the speed-related load torque compensation coefficient in the simulated cycling process. Except ω fed , other parameters can be set as constants.

[0156] Moreover, in steady state, it is known that the driving torque T p is equal to the electromagnetic torque T e The interaction force and the reaction force:

[0157] T p = -T e ; (10)

[0158] From the model of permanent magnet synchronous motor, the following torque equation is obtained:

[0159] (11)

[0161] In the speed tracking control, to achieve the maximum efficiency of the motor, usually make i d = 0, we can get:

[0162]

[0163] In the formula: n p is the number of motor pole pairs; ψ f is the flux generated by the rotor permanent magnet. i d is the motor stator d-axis current; i q is the motor stator q-axis current. L d is the equivalent inductance component of permanent magnet synchronous motor on the d-axis; L q is the equivalent inductance component of permanent magnet synchronous motor on the q-axis.

[0164] If the motor is constant, n p , ψ f is constant. Therefore, set K q as the electromagnetic torque coefficient, and record:

[0165]

[0166] Then formula (12) can be recorded as:

[0167] T e = K q i q ; (14)

[0168] Solving formula (4), formula (5), formula (6), formula (7), formula (8), formula (9), formula (10), formula (14), we can get the riding platform motion equation:

[0169]

[0170] So far, from the above derivation, it is known that the speed change will produce a dynamic torque T s , when accelerating At this time ω ref > ω fed, according to the inertia simulation method will produce a torque T s , so T s is the resistance torque; when decelerating At this time ω ref <ω fed , according to the inertia simulation method will produce a torque T s , so T s is the assistance torque.

[0171] From the simulation results of Figure 4 and Figure 5 , it can be seen that when the speed suddenly changes, the traditional mechanical inertia combined with the speed tracking scheme cannot quickly converge to the target speed due to the influence of the weight of the mechanical flywheel itself, and the actual speed of the riding platform oscillates at the initial stage of operation. This "instantaneous" oscillation leads to uneven output simulation of the riding load, resulting in a strong feeling of stepping out of the air. The inertia simulation method described in the present application does not require the use of a mechanical flywheel, and the speed convergence time of the same load inertia under the same working condition is shortened by 77% compared with the traditional mechanical inertia combined with the speed tracking method, solving the problem of uneven output simulation of the riding load and the feeling of stepping out of the air caused by the weight of the flywheel itself when the traditional riding platform is accelerated instantaneously.

[0172] The above-described embodiments are only used to illustrate the technical ideas and characteristics of the present application, and the purpose is to enable those skilled in the art to understand the content of the present application and to implement it, and cannot be limited to the patent scope of the present application only by the present embodiment, i.e. any equivalent changes or modifications made in the spirit disclosed by the present application still fall within the patent scope of the present application.

Claims

1. An inertia simulation system of a direct drive intelligent cycling platform, characterized in that, The simulation inertia control system, the inverter and the motor; the simulation inertia control system generates a dynamic compensation torque signal based on the acceleration change of the motor, and is used to compensate the torque error generated by the difference between the rotational inertia of the motor and the target rotational inertia under the same driving torque; the simulation inertia control system converts the dynamic compensation torque signal into a control signal of the inverter, controls the inverter to output a voltage signal to the motor, and makes the torque generated by the motor tend to 0; The simulation inertia control system includes an inertia simulation unit for simulating the dynamic rotational inertia in the riding process. The mathematical model expression of the inertia simulation unit is as follows: J s = J f - J M ; J M J for the moment of inertia of the motor J f To simulate the flywheel moment of inertia; J s To simulate the difference between the flywheel moment of inertia and the motor moment of inertia; ω ref is the reference angular velocity; ω fed ω is the feedback angular velocity, which is converted from the detected motor speed signal; K q is the electromagnetic torque coefficient; i q q-axis current for the motor stator; K ω Speed-dependent load torque compensation factor for simulating cycling; T b To simulate the base load torque during cycling; T s is a dynamic compensation torque signal generated based on a change in motor acceleration; ω min Vmin is the minimum compensation speed; M is the total weight of the person and the whole machine of the direct-drive intelligent riding platform; R is the radius of the wheel; T is time; I is the transmission ratio, which represents the ratio of the gear connected to the pedal to the gear connected to the wheel.

2. The inertia simulation system of the direct drive smart cycling platform according to claim 1, wherein, The signal detection system is also included, which is used to detect the motor stator winding current, the motor speed and the phase.

3. The inertia simulation system of the direct drive smart cycling platform of claim 1, wherein, The simulation inertia control system includes: an inertia simulation unit for simulating the dynamic rotational inertia in the riding process, first to third PI regulators, a Clark converter, a Park converter, a Park inverse converter and a space vector pulse width modulator; the Clark converter inputs the detected motor three-phase winding current signal and converts it into an α, β coordinate system current signal output to the Park converter; the Park converter converts the α, β coordinate system current signal into a d, q coordinate system current signal as a current feedback signal output; the inertia simulation unit inputs the detected motor speed signal and generates a dynamic compensation torque, which converts the dynamic compensation torque into a speed signal as a motor speed reference signal output; the first PI regulator inputs the difference between the motor speed reference signal and the detected motor speed signal to generate a reference current signal; the second PI regulator inputs the difference between the reference current signal and the q-axis current signal from the Park converter to generate a q-axis voltage control signal; the third PI regulator inputs the difference between the set d-axis current reference signal and the d-axis current signal from the Park converter to generate a d-axis voltage control signal; the Park inverse converter inputs the d, q coordinate system voltage control signals from the second and third PI regulators, converts them into α, β coordinate system voltage control signals and outputs them to the space vector pulse width modulator; the space vector pulse width modulator outputs a pulse signal to the inverter; and the inverter outputs a voltage signal to the motor.

4. A direct drive smart cycling platform characterized by, The inertia simulation system of the direct-drive intelligent riding platform of any one of claims 1 to 3.

5. An inertia simulation method of a direct drive intelligent cycling platform, characterized in that, The simulation inertia control system, the inverter and the motor; the simulation inertia control system generates a dynamic compensation torque signal based on the acceleration change of the motor, and is used to compensate the torque error generated by the difference between the rotational inertia of the motor and the target rotational inertia under the same driving torque; the simulation inertia control system converts the dynamic compensation torque signal into a control signal of the inverter, controls the inverter to output a voltage signal to the motor, and makes the torque generated by the motor tend to 0; The simulation inertia control system includes an inertia simulation unit for simulating the dynamic rotational inertia in the riding process. The mathematical model expression of the inertia simulation unit is as follows: J s = J f - J M ; J M J is the moment of inertia of the motor; J f To simulate the flywheel moment of inertia; J s to simulate the difference between the flywheel moment of inertia and the motor moment of inertia; ω ref is the reference angular velocity; ω fed is the feedback angular velocity, which is converted from the detected motor speed signal; K q is the electromagnetic torque coefficient; i q q-axis current for the motor stator; K ω Speed-dependent load torque compensation factor for simulating cycling; T b To simulate the base load torque during cycling; T s is a dynamic compensation torque signal generated based on a change in motor acceleration; ω min Vmin is the minimum compensation speed; m is the total weight of the human and the direct drive intelligent cycling platform complete machine; r is the radius of the wheel; t is time; i is the transmission ratio, representing the ratio of the number of teeth of the gear connected to the pedal and the gear connected to the wheel.

6. The inertia simulation method of the direct drive intelligent cycling platform according to claim 5, wherein, A signal detection system is also provided, which is used to detect the motor stator winding current, the motor speed and phase.

7. The inertia simulation method of the direct drive intelligent cycling platform according to claim 5, wherein, The simulation inertia control system is provided with an inertia simulation unit for simulating the dynamic rotational inertia in the cycling process, first to third PI regulators, a Clark converter, a Park converter, a Park inverse converter and a space vector pulse width modulator; the Clark converter inputs the detected motor three-phase winding current signal and converts it into an α, β coordinate system current signal output to the Park converter; the Park converter converts the α, β coordinate system current signal into a d, q coordinate system current signal as an output of the current feedback signal; the inertia simulation unit inputs the detected motor speed signal and generates a dynamic compensation torque, which converts the dynamic compensation torque into a speed signal as an output of the motor speed reference signal; the first PI regulator inputs the difference between the motor speed reference signal and the detected motor speed signal to generate a reference current signal; the second PI regulator inputs the difference between the reference current signal and the q-axis current signal from the Park converter to generate a q-axis voltage control signal; the third PI regulator inputs the difference between the set d-axis current reference signal and the d-axis current signal from the Park converter to generate a d-axis voltage control signal; the Park inverse converter inputs the d, q coordinate system voltage control signals from the second and third PI regulators and converts them into α, β coordinate system voltage control signals output to the space vector pulse width modulator; the space vector pulse width modulator outputs a pulse signal to the inverter; and the inverter outputs a voltage signal to the motor.

8. A computer readable storage medium storing a computer program, characterized in that: The computer program is executed by the processor to realize the inertia simulation method steps of the direct drive intelligent cycling platform as claimed in any one of claims 5 to 7.

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