CN112874315B - Motion control method, device and equipment of balance car and storage medium - Google Patents

Abstract

The invention discloses a motion control method, a motion control device, equipment and a storage medium of a balance car, wherein the method comprises the following steps: acquiring current attitude information of the balance car under a preset road condition, and determining a first wheel balance parameter and a second wheel balance parameter of the balance car according to the current attitude information; fusing the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter; and driving a motor of the balance car according to the target balance parameters to realize motion control. Compared with the prior art, the left-right balance of the balance car needs to be realized by depending on the control of a body, the acquired first wheel balance parameter and the acquired second wheel balance parameter are subjected to fusion processing to obtain the target balance parameter, and then the motor of the balance car is driven according to the target balance parameter, so that the stable and accurate steering control of the balance car is realized, and the riding experience of a user is further improved.

Description

Motion control method, device, device and storage medium of balance car

technical field

The present invention relates to the technical field of self-balancing vehicles, in particular to a motion control method, device, equipment and storage medium of a self-balancing vehicle.

Background technique

Motion control is the key technology in the research content of the self-balancing car. The movement of the existing self-balancing car products is mainly realized through the control of its carrier (human), and the operator leans forward or backward to change the entire self-balancing car. The distribution of the center of gravity of the self-balancing car realizes the movement, resulting in the inability of the existing self-balancing car to control the steering smoothly and accurately.

The above content is only used to assist in understanding the technical solution of the present invention, and does not mean that the above content is admitted as prior art.

Contents of the invention

The main purpose of the present invention is to provide a motion control method, device, equipment and storage medium of a self-balancing car, aiming at solving the technical problem of how to realize the stable and precise steering control of the self-balancing car.

In order to achieve the above object, the present invention provides a motion control method of a self-balancing car, which includes:

Obtaining current posture information of the self-balancing vehicle under preset road conditions, and determining a first wheel balance parameter and a second wheel balance parameter of the self-balancing vehicle according to the current posture information;

performing fusion processing on the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter;

Driving the motor of the balance car according to the target balance parameters to realize motion control.

Optionally, the step of obtaining the current posture information of the self-balancing vehicle under preset road conditions includes:

Obtain the first data of the acceleration sensor in the balance vehicle and the second data of the gyroscope under preset road conditions;

obtaining a real-time angular velocity value according to the first data, and obtaining an angle value according to the second data;

The current posture information of the balance car is determined according to the real-time angular velocity value and the angle value.

Optionally, before the step of obtaining the real-time angular velocity value according to the first data, it also includes:

Obtain a first data type corresponding to the first data;

judging whether the first data type satisfies a preset angular velocity type condition;

When the first data type satisfies the preset angular velocity type condition, the step of obtaining a real-time angular velocity value according to the first data is performed.

Optionally, before the step of obtaining the first data type corresponding to the first data, it also includes:

Acquiring a first data storage amount corresponding to the first data;

judging whether the first data storage capacity satisfies a preset data storage condition;

When the first data storage amount satisfies the preset data storage condition, the step of acquiring the first data type corresponding to the first data is performed.

Optionally, before the step of obtaining an angle value according to the second data, it also includes:

Obtain a second data type corresponding to the second data;

judging whether the second data type satisfies a preset angle type condition;

When the second data type satisfies the preset angle type condition, the step of obtaining an angle value according to the second data is executed.

Optionally, before the step of obtaining the second data type corresponding to the second data, it may further include:

Acquiring a second data storage amount corresponding to the second data;

judging whether the second data storage capacity satisfies a preset data storage condition;

When the second data storage amount satisfies the preset data storage condition, the step of acquiring a second data type corresponding to the second data is performed.

Optionally, the step of obtaining a real-time angular velocity value according to the first data includes:

determining the angular velocity of the balance car according to the first data;

Integrating the angular velocity to obtain output attitude inclination, attitude inclination deviation and noise value;

A real-time angular velocity value is determined according to the output attitude inclination, the attitude inclination deviation and the noise value.

Optionally, the step of determining the real-time angular velocity value according to the output attitude inclination, the attitude inclination deviation and the noise value includes:

calculating a real-time angular velocity value through a preset angular velocity formula according to the output attitude inclination, the attitude inclination deviation, and the noise value;

The preset angular velocity formula is:

In the formula, Y ₁ (t) is the output attitude inclination, Y ₂ (t) is the attitude inclination deviation, w(t) is the noise value, y ₁ (t) is the estimated value of the Kalman filter, y ₂ (t) is the deviation value of the Kalman filter, and u _gyro (t) is the real-time angular velocity value.

Optionally, acquiring a measurement noise value according to the second data;

calculating an angle value through a preset angle formula according to the measurement noise value, the estimated value of the Kalman filter, and the deviation value of the Kalman filter;

The preset angle formula is:

In the formula, v(t) measures the noise value, and z(t) is the angle value.

Optionally, the step of determining the first wheel balance parameter and the second wheel balance parameter of the self-balancing car according to the current attitude information includes:

Analyzing the current attitude information to obtain the driving state of the self-balancing vehicle;

A first wheel balance parameter and a second wheel balance parameter of the self-balancing vehicle are determined according to the driving state.

Optionally, the step of determining the first wheel balance parameter and the second wheel balance parameter of the self-balancing car according to the driving state includes:

Searching for corresponding sample wheel balance parameters from a preset driving state mapping relationship table according to the driving state;

determining a first sample wheel balance parameter and a second sample wheel balance parameter according to the sample wheel balance parameter;

The preset driving state mapping relationship table includes the corresponding relationship between the driving state and the sample wheel balance parameters.

Optionally, the step of performing fusion processing on the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter includes:

determining a first motor output value according to the first wheel balance parameter, and determining a second motor output value according to the first motor output value and the second wheel balance parameter;

Perform fusion processing on the first motor output value and the second motor output value to obtain target balance parameters.

In addition, in order to achieve the above purpose, the present invention also proposes a motion control device for a self-balancing vehicle, which includes:

An acquisition module, configured to acquire current attitude information of the self-balancing car under preset road conditions, and determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing car according to the current attitude information;

A processing module, configured to perform fusion processing on the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter;

The control module is used to drive the motor of the balance car according to the target balance parameters, so as to realize motion control.

Optionally, the obtaining module is also used to obtain the first data of the acceleration sensor in the balance vehicle and the second data of the gyroscope under preset road conditions;

The obtaining module is also used to obtain a real-time angular velocity value according to the first data, and obtain an angle value according to the second data;

The acquiring module is further configured to determine the current attitude information of the balance car according to the real-time angular velocity value and the angle value.

Optionally, the acquisition module is further configured to determine the angular velocity of the self-balancing vehicle according to the first data;

The acquisition module is also used to perform integral processing on the angular velocity to obtain the output attitude inclination, attitude inclination deviation and noise value;

The acquiring module is further configured to determine a real-time angular velocity value according to the output attitude inclination, the attitude inclination deviation and the noise value.

Optionally, the acquisition module is also configured to analyze the current posture information to obtain the driving state of the self-balancing vehicle;

The obtaining module is further configured to determine a first wheel balance parameter and a second wheel balance parameter of the self-balancing vehicle according to the driving state.

Optionally, the obtaining module is further configured to search for corresponding sample wheel balance parameters from a preset driving state mapping table according to the driving state;

The obtaining module is further configured to determine a first sample wheel balance parameter and a second sample wheel balance parameter according to the sample wheel balance parameter;

The acquiring module is further configured to include the corresponding relationship between the driving state and the sample wheel balance parameters in the preset driving state mapping relationship table.

Optionally, the processing module is further configured to determine a first motor output value according to the first wheel balance parameter, and determine a second motor output value according to the first motor output value and the second wheel balance parameter ;

The processing module is further configured to perform fusion processing on the first motor output value and the second motor output value to obtain target balance parameters.

In addition, in order to achieve the above object, the present invention also proposes a motion control device for a self-balancing car, which includes: a memory, a processor, and a motion control system of the self-balancing car that is stored in the memory and can run on the processor. A control program, the motion control program of the self-balancing car is configured to implement the steps of the method for controlling the motion of the self-balancing car as described above.

In addition, in order to achieve the above object, the present invention also proposes a storage medium, on which the motion control program of the self-balancing car is stored, and when the motion control program of the self-balancing car is executed by the processor, the above-mentioned balance is realized. Steps of a method for controlling motion of a car.

The present invention first obtains the current posture information of the self-balancing vehicle under the preset road conditions, and determines the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the current posture information, and then performs a process on the first wheel balance parameter and the second wheel balance parameter Fusion processing to obtain the target balance parameters, and then drive the motor of the balance car according to the target balance parameters to achieve motion control. Compared with the existing technology, it is necessary to rely on the control of the body to realize the left and right balance of the self-balancing car. However, the present invention fuses the obtained first wheel balance parameters and the second wheel balance parameters to obtain the target balance parameters, and then according to the target balance The parameters drive the motor of the self-balancing car to achieve stable and precise steering control of the self-balancing car, thereby improving the user's riding experience.

Description of drawings

Fig. 1 is a schematic structural diagram of a motion control device of a balance car in a hardware operating environment related to the solution of an embodiment of the present invention;

Fig. 2 is a schematic flow chart of the first embodiment of the motion control method of the balance car of the present invention;

Fig. 3 is a schematic flow chart of the second embodiment of the motion control method of the balance car of the present invention;

Fig. 4 is a schematic flow chart of the third embodiment of the motion control method of the balance car of the present invention;

Fig. 5 is a structural block diagram of the first embodiment of the motion control device of the balance car of the present invention.

The realization of the purpose of the present invention, functional characteristics and advantages will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

Referring to FIG. 1 , FIG. 1 is a schematic structural diagram of a motion control device of a balance car in a hardware operating environment related to an embodiment of the present invention.

As shown in FIG. 1 , the motion control device of the balance car may include: a processor 1001 , such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002 , a user interface 1003 , a network interface 1004 , and a memory 1005 . Wherein, the communication bus 1002 is used to realize connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) memory, or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001 .

Those skilled in the art can understand that the structure shown in Figure 1 does not constitute a limitation on the motion control device of the balance car, and may include more or less components than shown in the figure, or combine some components, or different components layout.

As shown in FIG. 1 , the memory 1005 as a storage medium may include an operating system, a data storage module, a network communication module, a user interface module and a motion control program of the self-balancing vehicle.

In the motion control device of the balance car shown in Figure 1, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processing in the motion control device of the balance car of the present invention The controller 1001 and the memory 1005 can be set in the motion control device of the self-balancing car. The motion control device of the self-balancing car calls the motion control program of the self-balancing car stored in the memory 1005 through the processor 1001, and executes the balancing car provided by the embodiment of the present invention. Vehicle motion control method.

An embodiment of the present invention provides a motion control method for a self-balancing vehicle. Referring to FIG. 2 , FIG. 2 is a schematic flowchart of a first embodiment of the method for controlling the motion of a self-balancing vehicle according to the present invention.

In this embodiment, the motion control method of the balance car includes the following steps:

Step S10: Obtain the current posture information of the self-balancing vehicle under preset road conditions, and determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the current posture information.

It is easy to understand that the execution subject of this embodiment may be a motion control device of a self-balancing vehicle with functions such as data processing, network communication, and program operation, or other computer equipment with similar functions. limit.

The preset road conditions may be various road surfaces on which the user rides the self-balancing vehicle, such as uphill road conditions, downhill road conditions, etc., which are not limited in this embodiment.

It can be understood that the current attitude information of the self-balancing car can be the real-time angular velocity value and angle value of the self-balancing car, and the step of obtaining the current attitude information of the self-balancing car under the preset road conditions can be: obtaining the acceleration sensor inside the self-balancing car under the preset road conditions The first data of the gyroscope and the second data of the gyroscope, the real-time angular velocity value is obtained according to the first data, and the angle value is obtained according to the second data, and the current attitude information of the self-balancing vehicle is determined according to the real-time angular velocity value and the angle value.

It should be noted that this embodiment uses its internal gyroscope and acceleration sensor to detect changes in the posture of the car body, that is to say, the control system on both sides of the two wheels of the self-balancing vehicle collects respective posture information through a high-precision 6-axis posture sensor, And use the servo control system to accurately drive the motor to make corresponding adjustments to maintain the balance of the system.

The first data can be a single angular velocity or multiple angular velocities collected by the acceleration sensor in the balance car, and the second data can be a single angle value or multiple angle values collected by the gyroscope in the balance car. This embodiment does not add limit.

In order to obtain accurate first data, before the step of obtaining the real-time angular velocity value according to the first data, it is necessary to obtain the first data type corresponding to the first data, and then determine whether the first data type satisfies the preset angular velocity type condition. When a data type satisfies the preset angular velocity type condition, a real-time angular velocity value and the like are obtained according to the first data.

The first data type may be understood as a type corresponding to an angular velocity value, etc., and the preset angular velocity type condition may be a type corresponding to an angular velocity, etc., which are not limited in this embodiment.

Assume that the first data type corresponding to the acquired first data is type A, and the preset angular velocity type condition is also type A, and then judge whether the first data type A type is consistent with the preset angular velocity A type, and whether the first data type A type is consistent with the preset angular velocity type A When the types of the preset angular velocity A are consistent, the real-time angular velocity value and the like are obtained according to the first data.

Before the step of obtaining the first data type corresponding to the first data, it is also necessary to obtain the first data storage volume corresponding to the first data, and determine whether the first data storage volume meets the preset data storage conditions. When data storage conditions are set, the first data type corresponding to the first data is obtained.

The first data storage capacity can be understood as the storage size corresponding to a single angular velocity or multiple angular velocities, etc. The preset data storage conditions can be user-defined settings, which can be 5kb, or 5M, etc., which are not limited in this embodiment .

Assuming that the first data storage capacity corresponding to the first data acquisition is 5kb, and the preset data storage condition is 5kb, then it is judged whether the first data storage capacity is consistent with the preset data storage threshold. When the thresholds are consistent, the first data type corresponding to the first data and the like are acquired.

Furthermore, in order to accurately obtain the angle value, before the step of obtaining the angle value according to the second data, it is necessary to obtain the second data type corresponding to the second data, and then determine whether the second data type satisfies the preset angle type condition. When the second data type satisfies the preset angle type condition, the angle value and the like are obtained according to the second data.

The second data type may be understood as a type corresponding to an angle value, etc., and the preset angular velocity type condition may be a type corresponding to an angle, etc., which are not limited in this embodiment.

Assume that the second data type corresponding to the acquired second data is type B, and the preset angle type condition is also type B, and then judge whether the second data type B type is consistent with the preset angle B type, and whether the second data type B type is consistent with the preset angle type B When the types of the preset angle B are consistent, the angle value and the like are obtained according to the second data.

Before the step of obtaining the second data type corresponding to the second data, it is also necessary to obtain the second data storage amount corresponding to the second data, and judge whether the second data storage amount satisfies the preset data storage condition. When the data storage condition is set, the second data type corresponding to the second data is obtained.

The second data storage capacity can be understood as the storage size corresponding to a single angle value or multiple angle values, etc. The preset data storage conditions can be user-defined settings, which can be 8kb or 6M, etc. This embodiment does not be restricted.

Assuming that the second data storage amount corresponding to the second data acquisition is 6M, and the preset data storage condition is 6M, then it is judged whether the second data storage amount is consistent with the preset data storage threshold, and when the second data storage amount and the preset data storage When the thresholds are consistent, the second data type corresponding to the second data and the like are acquired.

The step of obtaining the real-time angular velocity value according to the first data can be as follows: determine the angular velocity of the self-balancing car according to the first data, and then perform integral processing on the angular velocity to obtain the output attitude inclination angle, attitude inclination angle deviation and noise value, and finally according to the output attitude inclination angle, attitude inclination angle The deviation and noise values determine the real-time angular velocity value.

The method of determining the real-time angular velocity value according to the output attitude inclination, attitude inclination deviation and noise value may be, according to the output attitude inclination, attitude inclination deviation and noise value, calculate the real-time angular velocity value through the preset angular velocity formula;

The preset angular velocity formula is:

In the formula, Y ₁ (t) is the output attitude inclination, Y ₂ (t) is the attitude inclination deviation, w(t) is the noise value, y ₁ (t) is the estimated value of the Kalman filter, y ₂ (t) is the deviation value of the Kalman filter, and u _gyro (t) is the real-time angular velocity value.

The preset angular velocity formula can be used to integrate the output angular velocity when using the acceleration sensor to solve the attitude angle. The state formula in the Kalman filter can be constructed according to this characteristic of the acceleration sensor.

The method of obtaining the angle value according to the second data may be to obtain the measurement noise value according to the second data, and then calculate the angle through the preset angle formula according to the measurement noise value, the estimated value of the Kalman filter and the deviation value of the Kalman filter value;

The preset angle formula is:

In the formula, v(t) measures the noise value, and z(t) is the angle value.

The accelerometer can detect the acceleration components on each axis of the space Cartesian coordinate system during motion, that is, the space vector of the current motion can be obtained, and the current attitude angle of the direction can be obtained by calculating the angle between any axis and the space vector.

The step of determining the first wheel balance parameter and the second wheel balance parameter of the self-balancing car according to the current attitude information may be: analyzing the current attitude information to obtain the driving state of the self-balancing car, and then determining the first wheel balance of the self-balancing car according to the driving state parameters and the second wheel balance parameters, etc.

The method of determining the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the driving state may be to search the corresponding sample wheel balance parameters from the preset driving state mapping relationship table according to the driving state, and then determine according to the sample wheel balance parameters The first sample wheel balance parameter and the second sample wheel balance parameter, and then the preset driving state mapping relationship table includes the corresponding relationship between the driving state and the sample wheel balance parameters, and there are multiple driving states in the preset driving state mapping relationship table. state and multiple sample wheel balance parameters etc.

The first wheel balance parameter may be a parameter required to maintain balance of the left wheel of the balance car, etc., and the second wheel balance parameter may be a parameter required to maintain balance of the right wheel of the balance car, etc., which are not limited in this embodiment.

The driving state may be an acceleration state, a pause state, a steering state, etc., which are not limited in this embodiment.

Step S20: performing fusion processing on the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter.

The first wheel balance parameter and the second wheel balance parameter are fused together to obtain the target balance parameter by determining the output value of the first motor according to the first wheel balance parameter, and determining the output value of the first motor according to the output value of the first motor and the second wheel balance parameter. The parameters determine the output value of the second motor, and then perform fusion processing on the output value of the first motor and the output value of the second motor to obtain target balance parameters and the like.

The way to determine the first motor output value according to the first wheel balance parameter can be to convert the first wheel balance parameter to obtain the corresponding first motor output value, or to calculate the first motor output value required by each balance through the balance control algorithm. Motor output value, etc.

The step of obtaining the output value of the second motor may be that the control systems on both sides communicate and exchange data at a high frequency of 500HZ to obtain the output value of the second motor required by the control calculation of the other party, or it may be based on the output value of the first motor and the second The wheel balance parameters determine the output value of the second motor, etc., which are not limited in this embodiment.

In a specific implementation, it is necessary to fuse the output value of the first motor and the output value of the second motor through an adaptive algorithm to obtain the final output motor value, that is, the target balance parameter and the like.

It should be noted that the balance car control algorithm is more intelligent than the existing technology. The parameters are optimized and matched for different loads, different riding road surfaces, and riding at different speeds. Real-time collection of parameters such as angle, angular velocity, driving speed, current current, voltage, etc. Through multi-sensor data fusion, it can intelligently identify the current riding state and calculate the optimal parameters to achieve a better riding experience.

Step S30: Drive the motor of the self-balancing car according to the target balance parameters to realize motion control.

It should be understood that the obtained target balance parameters are used to drive the motor of the self-balancing car to achieve motion control. In addition, for the self-balancing car, the steering damping control algorithm can also be customized to achieve smooth and precise steering control. Make the balance bike riding more stable and smooth. Under different loads and different speeds, the steering damping algorithm calculates the current most suitable compensation coefficient according to the real-time dynamic voltage, current and speed, and then obtains the steering control output on both sides through the damping filter calculation, and then drives the balance car according to the steering control output on both sides motors for motion control etc.

In this embodiment, first obtain the current posture information of the self-balancing vehicle under preset road conditions, and determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the current posture information, and then perform the first wheel balance parameter and the second wheel balance parameter The wheel balance parameters are fused to obtain the target balance parameters, and then the motors of the self-balancing car are driven according to the target balance parameters to achieve motion control. Compared with the existing technology, it is necessary to rely on the control of the body to realize the left and right balance of the self-balancing car. However, in this embodiment, the obtained first wheel balance parameter and the second wheel balance parameter are fused to obtain the target balance parameter, and then according to the target The balance parameters drive the motor of the self-balancing car, which realizes the stable and precise steering control of the self-balancing car, thereby improving the riding experience of the user.

Referring to FIG. 3 , FIG. 3 is a schematic flowchart of a second embodiment of a motion control method of a self-balancing vehicle according to the present invention.

Based on the first embodiment above, in this embodiment, the step S10 further includes:

Step S101: Obtain the first data of the gyroscope in the balance car and the second data of the acceleration sensor under a preset road condition.

The preset road conditions may be various road surfaces on which the user rides the self-balancing vehicle, such as uphill road conditions, downhill road conditions, etc., which are not limited in this embodiment.

It can be understood that the current attitude information of the self-balancing car can be the real-time angular velocity value and angle value of the self-balancing car, and the step of obtaining the current attitude information of the self-balancing car under the preset road conditions can be: obtaining the acceleration sensor inside the self-balancing car under the preset road conditions The first data of the gyroscope and the second data of the gyroscope, the real-time angular velocity value is obtained according to the first data, and the angle value is obtained according to the second data, and the current attitude information of the self-balancing vehicle is determined according to the real-time angular velocity value and the angle value.

It should be noted that this embodiment uses its internal gyroscope and acceleration sensor to detect changes in the posture of the car body, that is to say, the control system on both sides of the two wheels of the self-balancing vehicle collects respective posture information through a high-precision 6-axis posture sensor, And use the servo control system to accurately drive the motor to make corresponding adjustments to maintain the balance of the system.

The first data can be a single angular velocity or multiple angular velocities collected by the acceleration sensor in the balance car, and the second data can be a single angle value or multiple angle values collected by the gyroscope in the balance car. This embodiment does not add limit.

Step S102: Obtain a real-time angular velocity value according to the first data, and obtain an angle value according to the second data.

In order to obtain accurate first data, before the step of obtaining the real-time angular velocity value according to the first data, it is necessary to obtain the first data type corresponding to the first data, and then determine whether the first data type satisfies the preset angular velocity type condition. When a data type satisfies the preset angular velocity type condition, a real-time angular velocity value and the like are obtained according to the first data.

The first data type may be understood as a type corresponding to an angular velocity value, etc., and the preset angular velocity type condition may be a type corresponding to an angular velocity, etc., which are not limited in this embodiment.

Assume that the first data type corresponding to the acquired first data is type A, and the preset angular velocity type condition is also type A, and then judge whether the first data type A type is consistent with the preset angular velocity A type, and whether the first data type A type is consistent with the preset angular velocity type A When the types of the preset angular velocity A are consistent, the real-time angular velocity value and the like are obtained according to the first data.

Before the step of obtaining the first data type corresponding to the first data, it is also necessary to obtain the first data storage volume corresponding to the first data, and determine whether the first data storage volume meets the preset data storage conditions. When data storage conditions are set, the first data type corresponding to the first data is obtained.

The first data storage capacity can be understood as the storage size corresponding to a single angular velocity or multiple angular velocities, etc. The preset data storage conditions can be user-defined settings, which can be 5kb, or 5M, etc., which are not limited in this embodiment .

Assuming that the first data storage capacity corresponding to the first data acquisition is 5kb, and the preset data storage condition is 5kb, then it is judged whether the first data storage capacity is consistent with the preset data storage threshold. When the thresholds are consistent, the first data type corresponding to the first data and the like are acquired.

Furthermore, in order to accurately obtain the angle value, before the step of obtaining the angle value according to the second data, it is necessary to obtain the second data type corresponding to the second data, and then determine whether the second data type satisfies the preset angle type condition. When the second data type satisfies the preset angle type condition, the angle value and the like are obtained according to the second data.

The second data type may be understood as a type corresponding to an angle value, etc., and the preset angular velocity type condition may be a type corresponding to an angle, etc., which are not limited in this embodiment.

Assume that the second data type corresponding to the acquired second data is type B, and the preset angle type condition is also type B, and then judge whether the second data type B type is consistent with the preset angle B type, and whether the second data type B type is consistent with the preset angle type B When the types of the preset angle B are consistent, the angle value and the like are obtained according to the second data.

Before the step of obtaining the second data type corresponding to the second data, it is also necessary to obtain the second data storage amount corresponding to the second data, and judge whether the second data storage amount satisfies the preset data storage condition. When the data storage condition is set, the second data type corresponding to the second data is obtained.

The second data storage capacity can be understood as the storage size corresponding to a single angle value or multiple angle values, etc. The preset data storage conditions can be user-defined settings, which can be 8kb or 6M, etc. This embodiment does not be restricted.

Assuming that the second data storage amount corresponding to the second data acquisition is 6M, and the preset data storage condition is 6M, then it is judged whether the second data storage amount is consistent with the preset data storage threshold, and when the second data storage amount and the preset data storage When the thresholds are consistent, the second data type corresponding to the second data and the like are acquired.

The step of obtaining the real-time angular velocity value according to the first data can be as follows: determine the angular velocity of the self-balancing car according to the first data, and then perform integral processing on the angular velocity to obtain the output attitude inclination angle, attitude inclination angle deviation and noise value, and finally according to the output attitude inclination angle, attitude inclination angle The deviation and noise values determine the real-time angular velocity value.

The method of determining the real-time angular velocity value according to the output attitude inclination, attitude inclination deviation and noise value may be, according to the output attitude inclination, attitude inclination deviation and noise value, calculate the real-time angular velocity value through a preset angular velocity formula.

The preset angular velocity formula can be used to integrate the output angular velocity when using the acceleration sensor to solve the attitude angle. The state formula in the Kalman filter can be constructed according to this characteristic of the acceleration sensor.

The method of obtaining the angle value according to the second data may be to obtain the measurement noise value according to the second data, and then calculate the angle through the preset angle formula according to the measurement noise value, the estimated value of the Kalman filter and the deviation value of the Kalman filter value.

The accelerometer can detect the acceleration components on each axis of the space Cartesian coordinate system during motion, that is, the space vector of the current motion can be obtained, and the current attitude angle of the direction can be obtained by calculating the angle between any axis and the space vector.

Step S103: Determine the current attitude information of the self-balancing car according to the real-time angular velocity value and the angle value, and determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing car according to the current attitude information.

The step of determining the first wheel balance parameter and the second wheel balance parameter of the self-balancing car according to the current attitude information may be: analyzing the current attitude information to obtain the driving state of the self-balancing car, and then determining the first wheel balance of the self-balancing car according to the driving state parameters and the second wheel balance parameters, etc.

The method of determining the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the driving state may be to search the corresponding sample wheel balance parameters from the preset driving state mapping relationship table according to the driving state, and then determine according to the sample wheel balance parameters The first sample wheel balance parameter and the second sample wheel balance parameter, and then the preset driving state mapping relationship table includes the corresponding relationship between the driving state and the sample wheel balance parameters, and there are multiple driving states in the preset driving state mapping relationship table. state and multiple sample wheel balance parameters etc.

The first wheel balance parameter may be a parameter required to maintain balance of the left wheel of the balance car, etc., and the second wheel balance parameter may be a parameter required to maintain balance of the right wheel of the balance car, etc., which are not limited in this embodiment.

The driving state may be an acceleration state, a pause state, a steering state, etc., which are not limited in this embodiment.

In this implementation, first obtain the first data of the acceleration sensor in the balance car and the second data of the gyroscope under the preset road conditions, then obtain the real-time angular velocity value according to the first data, obtain the angle value according to the second data, and finally obtain the real-time The angular velocity value and the angle value determine the current attitude information of the self-balancing car, and then obtain accurate attitude information of the self-balancing car.

Referring to FIG. 4 , FIG. 4 is a schematic flowchart of a third embodiment of a motion control method of a self-balancing vehicle according to the present invention.

Based on the first embodiment above, in this embodiment, the step S20 further includes:

Step S201: Determine a first motor output value according to the first wheel balance parameter, and determine a second motor output value according to the first motor output value and the second wheel balance parameter.

The way to determine the first motor output value according to the first wheel balance parameter can be to convert the first wheel balance parameter to obtain the corresponding first motor output value, or to calculate the first motor output value required by each balance through the balance control algorithm. Motor output value, etc.

The step of obtaining the output value of the second motor may be that the control systems on both sides communicate and exchange data at a high frequency of 500HZ to obtain the output value of the second motor required by the control calculation of the other party, or it may be based on the output value of the first motor and the second The wheel balance parameters determine the output value of the second motor, etc., which are not limited in this embodiment.

Step S202: Perform fusion processing on the first motor output value and the second motor output value to obtain target balance parameters.

In a specific implementation, it is necessary to fuse the output value of the first motor and the output value of the second motor through an adaptive algorithm to obtain the final output motor value, that is, the target balance parameter and the like.

It should be noted that the balance car control algorithm is more intelligent than the existing technology. The parameters are optimized and matched for different loads, different riding road surfaces, and riding at different speeds. Real-time collection of parameters such as angle, angular velocity, driving speed, current current, voltage, etc. Through multi-sensor data fusion, it can intelligently identify the current riding state and calculate the optimal parameters to achieve a better riding experience.

In this embodiment, the first motor output value is determined according to the first wheel balance parameter, and the second motor output value is determined according to the first motor output value and the second wheel balance parameter, and then the first motor output value and the second The output value of the motor is fused to obtain the target balance parameters, and then the accurate target balance parameters are obtained to realize the stable and precise steering control of the self-balancing car.

Referring to FIG. 5 , FIG. 5 is a structural block diagram of the first embodiment of the motion control device of the self-balancing vehicle of the present invention.

As shown in Figure 5, the motion control device of the balance car proposed by the embodiment of the present invention includes:

An acquisition module 5001, configured to acquire the current posture information of the self-balancing vehicle under preset road conditions, and determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the current posture information;

A processing module 5002, configured to perform fusion processing on the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter;

The control module 5003 is used to drive the motor of the balance car according to the target balance parameters, so as to realize motion control.

In this embodiment, first obtain the current posture information of the self-balancing vehicle under preset road conditions, and determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the current posture information, and then perform the first wheel balance parameter and the second wheel balance parameter The wheel balance parameters are fused to obtain the target balance parameters, and then the motors of the self-balancing car are driven according to the target balance parameters to achieve motion control. Compared with the existing technology, it is necessary to rely on the control of the body to realize the left and right balance of the self-balancing car. However, in this embodiment, the obtained first wheel balance parameter and the second wheel balance parameter are fused to obtain the target balance parameter, and then according to the target The balance parameters drive the motor of the self-balancing car, which realizes the stable and precise steering control of the self-balancing car, thereby improving the riding experience of the user.

Further, the obtaining module 5001 is also used to obtain the first data of the acceleration sensor in the balance vehicle and the second data of the gyroscope under preset road conditions;

The obtaining module 5001 is also used to obtain a real-time angular velocity value according to the first data, and obtain an angle value according to the second data;

The acquisition module 5001 is further configured to determine the current attitude information of the balance car according to the real-time angular velocity value and the angle value.

Further, the acquiring module 5001 is further configured to acquire the first data type corresponding to the first data;

The acquiring module 5001 is also used to judge whether the first data type satisfies the preset angular velocity type condition;

The obtaining module 5001 is further configured to execute the operation of obtaining a real-time angular velocity value according to the first data when the first data type satisfies the preset angular velocity type condition.

Further, the acquiring module 5001 is also configured to acquire a first data storage amount corresponding to the first data;

The acquiring module 5001 is further configured to judge whether the first data storage amount satisfies a preset data storage condition;

The obtaining module 5001 is further configured to perform the operation of obtaining the first data type corresponding to the first data when the first data storage amount satisfies the preset data storage condition.

Further, the acquiring module 5001 is further configured to acquire a second data type corresponding to the second data;

The obtaining module 5001 is also used to judge whether the second data type satisfies the preset angle type condition;

The acquiring module 5001 is further configured to execute the operation of acquiring an angle value according to the second data when the second data type satisfies the preset angle type condition.

Further, the acquiring module 5001 is also configured to acquire a second data storage amount corresponding to the second data;

The acquiring module 5001 is further configured to judge whether the second data storage amount satisfies a preset data storage condition;

The acquiring module 5001 is further configured to execute the operation of acquiring the second data type corresponding to the second data when the second data storage amount satisfies the preset data storage condition.

Further, the obtaining module 5001 is also used to determine the angular velocity of the self-balancing vehicle according to the first data;

The acquisition module 5001 is also used to perform integral processing on the angular velocity to obtain the output attitude inclination, attitude inclination deviation and noise value;

The obtaining module 5001 is further configured to determine a real-time angular velocity value according to the output attitude inclination, the attitude inclination deviation and the noise value.

Further, the acquisition module 5001 is also used to calculate a real-time angular velocity value through a preset angular velocity formula according to the output attitude inclination, the attitude inclination deviation and the noise value;

The preset angular velocity formula is:

In the formula, Y ₁ (t) is the output attitude inclination, Y ₂ (t) is the attitude inclination deviation, w(t) is the noise value, y ₁ (t) is the estimated value of the Kalman filter, y ₂ (t) is the deviation value of the Kalman filter, and u _gyro (t) is the real-time angular velocity value.

Further, the acquiring module 5001 is also configured to acquire a measurement noise value according to the second data;

The acquisition module 5001 is further configured to calculate an angle value through a preset angle formula according to the measurement noise value, the estimated value of the Kalman filter, and the deviation value of the Kalman filter;

The preset angle formula is:

In the formula, v(t) measures the noise value, and z(t) is the angle value.

Further, the acquisition module 5001 is also used to analyze the current posture information to obtain the driving state of the self-balancing vehicle;

The obtaining module 5001 is further configured to determine the first wheel balance parameter and the second wheel balance parameter of the self-balancing vehicle according to the driving state.

Further, the acquisition module 5001 is also used to search the corresponding sample wheel balance parameters from the preset driving state mapping relationship table according to the driving state;

The obtaining module 5001 is further configured to determine a first sample wheel balance parameter and a second sample wheel balance parameter according to the sample wheel balance parameter;

The acquiring module 5001 is further configured to include the corresponding relationship between the driving state and the sample wheel balance parameters in the preset driving state mapping relationship table.

Further, the processing module 5002 is further configured to determine a first motor output value according to the first wheel balance parameter, and determine a second motor output value according to the first motor output value and the second wheel balance parameter ;

The processing module 5002 is further configured to perform fusion processing on the first motor output value and the second motor output value to obtain target balance parameters.

For other embodiments or specific implementations of the motion control device of the self-balancing vehicle of the present invention, reference may be made to the above-mentioned method embodiments, which will not be repeated here.

It should be noted that, as used herein, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or system comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or system. Without further limitations, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, article or system comprising that element.

The serial numbers of the above embodiments of the present invention are for description only, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solution of the present invention can be embodied in the form of software products in essence or in other words, the part that contributes to the prior art, and the computer software products are stored in a storage medium (such as read-only memory/random access memory, magnetic disk, optical disk), including several instructions to make a terminal device (which can be a mobile phone, computer, server, air conditioner, or network equipment, etc.) execute the methods described in various embodiments of the present invention.

The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the description of the present invention and the contents of the accompanying drawings, or directly or indirectly used in other related technical fields , are all included in the scope of patent protection of the present invention in the same way.

Claims (16)

1. A motion control method of a balance car is characterized by comprising the following steps:

acquiring first data and second data of a balance car under a preset road condition, determining current attitude information according to data storage amounts and data types corresponding to the first data and the second data, and determining a first wheel balance parameter and a second wheel balance parameter of the balance car according to the current attitude information;

fusing the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter;

driving a motor of the balance car according to the target balance parameter to realize motion control;

the step of obtaining first data and second data of the balance car under the preset road condition and determining current attitude information according to data storage amount and data type corresponding to the first data and the second data comprises the following steps:

acquiring first data of an acceleration sensor in a balance car and second data of a gyroscope under a preset road condition;

acquiring a first data storage capacity corresponding to the first data;

judging whether the first data storage quantity meets a preset data storage condition or not;

when the first data storage capacity meets the preset data storage condition, acquiring a first data type corresponding to the first data;

judging whether the first data type meets a preset angular velocity type condition or not;

when the first data type meets the preset angular velocity type condition, obtaining a real-time angular velocity value according to the first data, and obtaining an angular value according to the second data;

and determining the current attitude information of the balance car according to the real-time angular velocity value and the angle value.

2. The method of claim 1, wherein the step of obtaining an angle value from the second data is preceded by:

acquiring a second data type corresponding to the second data;

judging whether the second data type meets a preset angle type condition or not;

and when the second data type meets the preset angle type condition, executing the step of obtaining the angle value according to the second data.

3. The method of claim 2, wherein the step of obtaining the second data type corresponding to the second data is preceded by the step of:

acquiring a second data storage capacity corresponding to the second data;

judging whether the second data storage quantity meets a preset data storage condition or not;

and when the second data storage quantity meets the preset data storage condition, executing the step of acquiring a second data type corresponding to the second data.

4. A method according to claim 2 or 3, wherein the step of obtaining a real-time angular velocity value from the first data comprises:

determining the angular speed of the balance car according to the first data;

performing integral processing on the angular velocity to obtain an output attitude dip angle, an attitude dip angle deviation and a noise value;

and determining a real-time angular velocity value according to the output attitude inclination angle, the attitude inclination angle deviation and the noise value.

5. The method of claim 4, wherein said step of determining a real-time angular velocity value based on said output attitude dip, said attitude dip offset and said noise value comprises:

calculating a real-time angular velocity value through a preset angular velocity formula according to the output attitude inclination angle, the attitude inclination angle deviation and the noise value;

the preset angular velocity formula is as follows:

in the formula, Y ₁ (t) is the output attitude dip, Y ₂ (t) is attitude dip angle deviation, w (t) is noise value, y ₁ (t) is an estimate of the Kalman filter, y ₂ (t) is the deviation value of the Kalman filter, u _gyro And (t) is a real-time angular velocity value.

6. The method of claim 5, wherein said step of obtaining an angle value based on said second data comprises:

acquiring a measurement noise value according to the second data;

calculating an angle value through a preset angle formula according to the measurement noise value, the estimated value of the Kalman filter and the deviation value of the Kalman filter;

the preset angle formula is as follows:

where v (t) measures the noise value and z (t) is the angle value.

7. The method of claim 1, wherein the step of determining a first wheel balancing parameter and a second wheel balancing parameter of the balancing vehicle based on the current attitude information comprises:

analyzing the current attitude information to obtain the driving state of the balance car;

and determining a first wheel balance parameter and a second wheel balance parameter of the balance vehicle according to the running state.

8. The method of claim 7, wherein the step of determining a first wheel balancing parameter and a second wheel balancing parameter of the balancing vehicle based on the driving condition comprises:

searching a corresponding sample wheel balance parameter from a preset driving state mapping relation table according to the driving state;

determining a first sample wheel balance parameter and a second sample wheel balance parameter according to the sample wheel balance parameters;

the preset driving state mapping relation table comprises a corresponding relation between a driving state and a sample wheel balance parameter.

9. The method of claim 1, wherein the step of fusing the first wheel balancing parameter and the second wheel balancing parameter to obtain a target balancing parameter comprises:

determining a first motor output value according to the first wheel balance parameter, and determining a second motor output value according to the first motor output value and the second wheel balance parameter;

and carrying out fusion processing on the first motor output value and the second motor output value to obtain a target balance parameter.

10. A motion control device of a balance car, characterized by comprising:

the acquisition module is used for acquiring first data and second data of the balance car under a preset road condition, determining current attitude information according to data storage amounts and data types corresponding to the first data and the second data, and determining first wheel balance parameters and second wheel balance parameters of the balance car according to the current attitude information;

the processing module is used for carrying out fusion processing on the first wheel balance parameter and the second wheel balance parameter to obtain a target balance parameter;

the control module is used for driving a motor of the balance car according to the target balance parameters so as to realize motion control;

the acquisition module is also used for acquiring first data of an acceleration sensor in the balance car and second data of a gyroscope under a preset road condition; acquiring a first data storage capacity corresponding to the first data; judging whether the first data storage quantity meets a preset data storage condition or not; when the first data storage capacity meets the preset data storage condition, acquiring a first data type corresponding to the first data; judging whether the first data type meets a preset angular velocity type condition or not; when the first data type meets the preset angular velocity type condition, obtaining a real-time angular velocity value according to the first data, and obtaining an angular value according to the second data; and determining the current attitude information of the balance car according to the real-time angular velocity value and the angular value.

11. The apparatus of claim 10, wherein the acquisition module is further configured to determine an angular velocity of the balance car based on the first data;

the acquisition module is further used for performing integral processing on the angular velocity to obtain an output attitude inclination angle, an attitude inclination angle deviation and a noise value;

the acquisition module is further used for determining a real-time angular velocity value according to the output attitude inclination angle, the attitude inclination angle deviation and the noise value.

12. The device of claim 10, wherein the obtaining module is further configured to analyze the current posture information to obtain a driving state of the balance car;

the acquisition module is further used for determining a first wheel balance parameter and a second wheel balance parameter of the balance vehicle according to the running state.

13. The apparatus according to claim 12, wherein the obtaining module is further configured to look up corresponding sample wheel balance parameters from a preset driving state mapping table according to the driving state;

the acquisition module is further used for determining a first sample wheel balance parameter and a second sample wheel balance parameter according to the sample wheel balance parameter;

the obtaining module is further configured to obtain a corresponding relationship between a driving state and a sample wheel balance parameter in the preset driving state mapping relationship table.

14. The apparatus of claim 10, wherein the processing module is further configured to determine a first motor output value based on the first wheel balancing parameter and a second motor output value based on the first motor output value and the second wheel balancing parameter;

and the processing module is also used for carrying out fusion processing on the first motor output value and the second motor output value to obtain a target balance parameter.

15. A motion control apparatus of a balance car, characterized in that the apparatus comprises: a memory, a processor and a motion control program of a balancing vehicle stored on the memory and executable on the processor, the motion control program of the balancing vehicle being configured to implement the steps of the motion control method of the balancing vehicle as claimed in any one of claims 1 to 9.

16. A storage medium, characterized in that the storage medium stores thereon a motion control program of a balance car, which when executed by a processor implements the steps of the motion control method of a balance car according to any one of claims 1 to 9.

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