A thrust auxiliary control method, device, system and medium of an electric wheelchair

Abstract

The application provides a thrust auxiliary control method, device and system of an electric wheelchair and a medium, and relates to the technical field of electric wheelchair control. The method aims to solve the problems of motion unevenness, travel yaw and insufficient safety caused by simple control strategy in the prior art. The method comprises: performing low-pass filtering processing on the original input signal received from the rear handle control rod; performing gear switching by using hysteresis logic based on the filtered linear velocity component; introducing a yaw compensation mechanism to differentially adjust the target speed of the left and right drive wheels to compensate for travel yaw; applying an angular acceleration slope limit to the angular velocity component to smooth the steering process; and monitoring the continuity of the original input signal, and triggering a safety parking strategy when a signal interruption timeout is detected. The application can significantly improve the smoothness, accuracy and safety of the thrust auxiliary control of the electric wheelchair through multi-strategy fusion.

Description

Technical Field

[0001] This invention relates to the field of electric wheelchair control technology, and more specifically, to a multi-strategy fusion method for thrust-assisted control of electric wheelchairs. Background Technology

[0002] The rear-handle push-assist function of electric wheelchairs is designed to allow caregivers to easily control the wheelchair's movement via a rear-mounted control device, reducing the burden of pushing it. However, existing control methods still have many shortcomings.

[0003] First, many control schemes employ a simple linear mapping method, directly converting the displacement of the joystick into drive commands for the motor. This method is highly sensitive to the inherent high-frequency noise in the joystick signal and unconscious hand tremors from the caregiver, easily causing unnecessary minor accelerations, decelerations, and swaying during wheelchair movement. Simultaneously, when the caregiver performs rapid steering maneuvers, the wheelchair often exhibits abrupt steering acceleration, causing discomfort and safety hazards for the occupant. Regarding steering stability, existing technologies, such as Chinese patent application number CN202011127811.X, disclose an electric wheelchair driving control method and system. This method calculates the target yaw rate by detecting the vehicle speed and the intention of the joystick, and automatically adjusts the speed of the left and right drive wheel motors when the yaw rate exceeds a preset value to ensure it remains within the allowable range. While such methods improve steering safety to some extent, the overall smoothness of operation still needs optimization in more complex driving environments and under varying operational demands.

[0004] Secondly, in order to achieve multi-speed control, some solutions have set different speed levels. However, the switching logic of these levels is usually based on a single speed threshold. When the wheelchair speed fluctuates slightly around this threshold, it will cause frequent back-and-forth changes in the speed, resulting in a jerky feeling during the movement.

[0005] Furthermore, due to mechanical wear and tear, uneven aging of the left and right tires, or driving on surfaces with different coefficients of friction on both sides during long-term use, wheelchairs may experience uneven output torque or adhesion between the left and right drive wheels. Traditional control methods typically assume perfect symmetry between the left and right drive systems, failing to adequately consider the impact of this asymmetry. This causes the wheelchair to gradually yaw when intended to travel in a straight line, increasing the burden of manual corrections for caregivers.

[0006] Finally, existing thrust assist systems, especially those using wireless communication, are highly dependent on signal integrity. In the event of a communication anomaly such as signal interruption or data error, without an effective safety monitoring mechanism, the wheelchair may execute incorrect commands or produce unpredictable actions, posing a risk of loss of control.

[0007] Therefore, how to comprehensively solve the above-mentioned problems such as motion vibration, frequent gear shifting, yaw, abrupt steering, and communication failure, and provide a smoother, more accurate, and safer thrust assist control method is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0008] In view of the deficiencies in the prior art, the purpose of this invention is to provide a thrust-assisted control method for an electric wheelchair.

[0009] According to a first aspect of the present invention, a thrust-assisted control method for an electric wheelchair is applied to an electric wheelchair system including a controller and left and right drive wheels. The method includes: performing low-pass filtering on an original input signal representing a desired speed received from a rear-grip joystick to generate a filtered speed command; performing gear shifting based on the linear velocity component in the filtered speed command using hysteresis logic, the hysteresis logic including setting an upshift threshold higher than its corresponding downshift threshold for at least one gear; introducing a yaw compensation mechanism to differentially adjust the target speeds of the left and right drive wheels based on the filtered speed command to compensate for the yaw of the electric wheelchair; applying an angular acceleration ramp limit to the angular velocity component in the filtered speed command to smooth the steering process; and monitoring the continuity of the original input signal, and triggering a safe stopping strategy to stop the electric wheelchair when an interruption in the original input signal is detected to reach a preset timeout threshold.

[0010] Optionally, the yaw compensation mechanism is a dual yaw following gain compensation mechanism, which includes introducing a static yaw correction and a dynamic yaw following gain to adjust the target speed of the left and right drive wheels.

[0011] Optionally, the step of monitoring the continuity of the original input signal includes: comparing whether the difference between the current time and the timestamp of the latest received original input signal exceeds the preset timeout threshold.

[0012] Optionally, the step of applying an angular acceleration ramp limit to the angular velocity component includes: limiting the change in the angular velocity component within each control cycle to a preset product of the maximum angular acceleration and the control cycle.

[0013] Optionally, the method further includes: switching between a preset normal mode and a slow mode in response to user input, wherein the slow mode has at least one of the following characteristics: a lower gear speed threshold, a lower maximum speed limit, or a smaller maximum angular acceleration limit.

[0014] Optionally, the method further includes: identifying the user's manipulation intention by calculating the rate of change of the original input signal, wherein when the rate of change of the original input signal exceeds a first threshold, it is identified as an emergency manipulation intention, and when the rate of change is lower than a second threshold, it is identified as a gentle manipulation intention; and adaptively adjusting at least one of the following based on the identified manipulation intention: the control parameters of the low-pass filtering process and the control parameters of the angular acceleration ramp limit.

[0015] Optionally, the yaw compensation mechanism is a closed-loop compensation control, and the method further includes: taking the angular velocity component in the filtered speed command as the target angular velocity; obtaining the actual angular velocity from the inertial measurement unit; and generating a yaw correction amount to adjust the target speed of the left and right drive wheels based on the error between the actual angular velocity and the target angular velocity.

[0016] This application also provides a control device for an electric wheelchair, comprising: a processor; and a memory storing computer instructions thereon, which, when executed by the processor, cause the processor to perform the method as described in any of the preceding claims.

[0017] This application also provides an electric wheelchair system, including left and right drive wheels, a rear handlebar, and a control device as described above.

[0018] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the preceding claims.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. Improved stability and comfort during movement: By using low-pass filtering on the input signal, hand tremors and electrical noise are effectively suppressed, making the wheelchair movement smoother; at the same time, the use of hysteresis gear switching logic avoids frequent gear jumps at speed critical points, eliminating the feeling of jerking.

[0021] 2. Improve straight-line driving accuracy. By introducing a yaw compensation mechanism, it can effectively compensate for the asymmetry of the driving force of the left and right wheels caused by mechanical errors or uneven road surfaces, ensuring the straight-line driving stability of the wheelchair and reducing the correction burden on caregivers.

[0022] 3. Enhanced steering safety and smoothness: By applying an angular acceleration ramp limit to the angular velocity, the wheelchair's angular velocity can smoothly increase or decrease even when the caregiver operates the steering wheel quickly, avoiding sudden steering impact and ensuring steering safety.

[0023] 4. Ensure absolute safety in case of system malfunctions. Through a data timeout safety detection mechanism, the communication status of the joystick can be monitored in real time. Once an anomaly such as signal loss or interruption occurs, the system can automatically execute a safe stopping strategy, fundamentally avoiding the risk of loss of control due to communication anomalies.

[0024] 5. Enhanced scene adaptability: By integrating normal and slow modes and configuring different control parameters for different modes, the wheelchair can flexibly adapt to different usage scenarios, improving the convenience and safety of operation. Attached Figure Description

[0025] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 A logic flowchart of a multi-strategy fusion electric wheelchair thrust assist control method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the gear shifting hysteresis logic provided in the embodiments of this application; Figure 3 The waveform diagrams showing the comparison of low-pass filtering effects provided in the embodiments of this application are as follows; Figure 4 An illustration of the effect of angular acceleration ramp limitation provided in the embodiments of this application; Figure 5 This is a block diagram of the modular architecture of the system provided in the embodiments of this application; Figure 6 A kinematic model diagram of dual yaw follower gain compensation provided in the embodiments of this application; Figure 7 A comparison diagram of actual test trajectories with and without yaw compensation provided for embodiments of this application; Figure 8 This application provides a system state machine transition diagram for its embodiments. Figure 9 This is a block diagram of closed-loop yaw compensation control provided in an embodiment of this application. Detailed Implementation

[0026] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0027] This application provides a multi-strategy fusion-based electric wheelchair thrust assistance control method, applied to an electric wheelchair system. This system typically includes a control device, two independently driven left and right wheels located on the wheelchair chassis, and a rear-grip joystick for the caregiver to control the wheelchair's movement from behind. The control device is the core execution unit of this method; it can be one or more processors, such as a microcontroller, digital signal processor, field-programmable gate array, or a general-purpose processor-based embedded system, and is equipped with memory for storing program instructions and related parameters. The rear-grip joystick is used to acquire the caregiver's control intentions and convert these intentions into raw input signals representing the desired speed, which are then transmitted to the control device via wired or wireless means.

[0028] Example 1 In one embodiment of this application, a thrust-assisted control method for electric wheelchairs integrating five core strategies—signal filtering, hysteresis gear management, yaw compensation, steering smoothing, and safety monitoring—is described in detail. This embodiment aims to provide a basic control scheme that balances ride comfort, responsiveness, and safety, and fully supports the independent claims of this application.

[0029] Figure 5 A possible modular system architecture block diagram for implementing the method of this application is shown. Logically, the entire control system can be divided into an input layer, a core control module, and an execution and output module. The input layer is responsible for receiving raw input signals from the rear-grip joystick. The execution and output module is responsible for sending the finally calculated control commands to the motor drivers of the left and right drive wheels. The core control module is the key to this solution, and it integrates multiple functional sub-modules, including a signal filtering module, a gear management module, a yaw compensation module, a smooth control module, and a safety detection module. These modules work together to implement the control method described in this application.

[0030] Figure 1 This is a logic flowchart of a multi-strategy fusion electric wheelchair thrust assist control method provided in an embodiment of this application. The following will be combined with... Figure 1 The specific steps of this embodiment will be described in detail with reference to the accompanying drawings and other figures.

[0031] During system startup or operation, the control device initializes and loads a series of preset control parameters. Specifically, in this embodiment, typical values ​​for these parameters may include: the control period dt is set to 0.02 seconds, i.e., the controller's operating frequency is 50 Hz; the first-order low-pass filter time constant tau for signal filtering is set to 0.08 seconds; and a threshold array for gear speed division in normal mode. The maximum speed is set to [0.3, 0.4, 0.5] m / s, corresponding to the first, second, and third gears respectively; the hysteresis for gear shifting is set to 0.02 m / s; and the maximum angular acceleration limit for smooth steering control is set. Set to 0.3 radians / second²; static yaw correction for yaw compensation. and dynamic yaw follower gain Settings are configured based on offline calibration results for a specific wheelchair; and data timeout thresholds are used for safety monitoring. Set to 0.3 seconds.

[0032] The control process first receives and parses the raw input signal from the rear-grip joystick. This signal typically contains the wheelchair movement information desired by the caregiver, which can be parsed into the desired linear velocity component. and the expected angular velocity component Each received signal packet is accompanied by a timestamp for subsequent communication status monitoring.

[0033] Subsequently, the system performs a crucial safety check step: monitoring the continuity of the original input signal. This step corresponds to... Figure 1 The "signal validity / timeout detection" step involves the control device continuously comparing the current system time with the timestamp of the most recently received signal. If the difference between the two exceeds a preset data timeout threshold... If the communication timeout is 0.3 seconds (in this embodiment), it is considered a communication timeout. It is understood that communication timeouts can be caused by various reasons, such as lost wireless signal, power failure of the joystick, or communication link failure. Once a communication timeout is detected, the system will immediately trigger a safe stopping strategy. That is, the control device will bypass all conventional motion control calculations, directly forcibly set the target speed command output to the left and right drive wheels to zero, and send it to the motor driver through the execution and output module, causing the wheelchair to brake quickly and safely and stop moving. This mechanism ensures that in any communication anomaly, the wheelchair will not lose control due to executing outdated commands or exhibiting unpredictable behavior, thus providing fundamental safety assurance. Experiments show that when simulating a communication interruption, the wheelchair can completely stop within a very short time (e.g., within 0.3 to 0.5 seconds) after the 0.3-second timeout threshold set in this embodiment is triggered. Figure 8 The system state machine transition diagram shown depicts the transition logic between different states of the system. The transition from the normal operation state to the emergency stop state is triggered by the data timeout event, which reflects the highest priority of this safety mechanism.

[0034] After confirming the signal is valid, the control process enters the normal motion command processing stage.

[0035] The first step in the processing stage is for the signal filtering module to perform low-pass filtering on the raw input signal. It should be noted that unintentional hand tremors by the caregiver or electrical noise from the joystick sensor itself can affect the original speed command. and The signal contains a large amount of high-frequency disturbances. Directly using these noisy signals for control would cause unnecessary minor accelerations, decelerations, and swaying in the wheelchair, affecting passenger comfort. Therefore, this embodiment employs a first-order low-pass filter to smooth the original signal. The filtering process can be described by the following formula:

[0036] in, and These are the raw linear velocity and angular velocity commands received in the current cycle. and It is the output value after filtering in the previous control cycle, dt is the control cycle (0.02 seconds), and τ is the filtering time constant (0.08 seconds); For linear velocity commands, This is the angular velocity command. The time constant determines the filter's cutoff frequency, which in this embodiment is approximately 2 Hz, effectively filtering out most hand tremors (typically above 2 Hz) while preserving the user's true control intentions (usually low-frequency signals). Combined with... Figure 3 The waveform comparison of the low-pass filtering effect is shown in the figure. The original joystick signal (gray curve) fluctuates wildly, while the signal after low-pass filtering (blue curve) becomes very smooth, providing a stable and clean input basis for subsequent control calculations. Experimental data shows that after adopting this filtering strategy, the standard deviation of acceleration during wheelchair movement can be reduced by about 60%, significantly improving the smoothness of motion.

[0037] After filtering, the process enters the gear management module, based on the filtered linear velocity command. The system employs hysteresis logic for gear selection and switching. Existing gear-shifting methods based on a single speed threshold are prone to frequent gear jumps and jerking when the wheelchair speed fluctuates around the threshold. This embodiment addresses this issue by setting an upshift speed threshold and a downshift speed threshold for each gear, with the upshift threshold being higher than the downshift threshold. Figure 2 This is a schematic diagram of the gear shift hysteresis logic. Taking shifting from first to second gear as an example, assuming the maximum speed in first gear is 0.3 m / s and the maximum speed in second gear is 0.4 m / s, the hysteresis is 0.02 m / s. Correspondingly, the upshift threshold... The speed will be set to 0.3 + 0.02 = 0.32 m / s, and the downshift threshold from second to first gear will be... Then it is 0.3 m / s. Only when Upshifting occurs only when the speed travels upwards at 0.32 m / s; downshifting occurs only when the speed travels downwards at 0.3 m / s. Within this hysteresis range of 0.3 m / s to 0.32 m / s, the gear remains constant regardless of speed fluctuations. This mechanism significantly enhances the stability of gear shifting. Experimental results show that, using hysteresis logic, unnecessary gear shifts can be reduced by approximately 70% in typical deployment scenarios. After determining the gear, the system will adjust the linear speed command based on the current gear. Limit the speed to ensure it does not exceed the maximum speed of the current gear, thus generating the limited linear velocity. .

[0038] To address the issue of wheelchair veering off course when traveling straight, the system further incorporates a yaw compensation module. It is understood that yaw is typically caused by factors such as mechanical asymmetry between the left and right drive wheels (e.g., uneven tire wear), differences in motor performance, or uneven road surface friction coefficients. This embodiment employs a dual yaw following gain compensation mechanism to differentiate the calculated target speeds of the left and right wheels. Figure 6 The kinematic model of yaw compensation is presented. This mechanism introduces two core parameters: static yaw correction. and dynamic yaw follower gain .in, It is a fixed angular offset used to compensate for the inherent yaw tendency of wheelchairs, which exists when stationary or moving straight. This value is obtained through offline calibration. This is a dynamic gain used to adjust for the difference in response between the left and right wheels during steering. The compensated target speeds of the left and right wheels... and Calculated using the following formula:

[0039] in, This refers to the wheel spacing between the left and right drive wheels. In this way, the control system can actively generate a corrective torque that is opposite to the yaw disturbance torque, thereby ensuring the straight-line stability of the wheelchair. Figure 7 The image shows a comparison of actual test trajectories with and without yaw compensation. It clearly shows that the wheelchair trajectory using the method described in this application (solid blue line) is very close to the ideal straight line, while the trajectory using the traditional method (dashed red line) shows a significant lateral deviation. Experimental data confirms that after compensation, the yaw angle of the wheelchair within a 10-meter straight-line distance can be precisely controlled within 1 degree, improving straight-line accuracy by approximately 80%.

[0040] Finally, to improve comfort and safety during steering, the smooth control module applies an angular acceleration ramp limit to angular velocity commands. When a caregiver quickly operates the joystick to steer, the unprocessed angular velocity command... A step change can occur, causing the wheelchair to suddenly veer, resulting in a swaying sensation and a sense of insecurity for the occupant. This embodiment smooths this process by limiting the maximum change in angular velocity within each control cycle. Specifically, the final output angular velocity command... Not directly equal to Instead, it started from the previous cycle. Value direction The value is approximated with a limited step size. Within each control cycle dt, the change in angular velocity is limited to [-]. × dt, The range is [l × dt]. In this embodiment, that is, [-0.3 × 0.02, 0.3 × 0.02], which is [-0.006, 0.006] radians / second. Figure 4 This diagram illustrates the effect of angular acceleration ramp limiting. When the target angular velocity (dashed line) experiences a step change, the actual output angular velocity (solid line) increases linearly with a constant slope until it reaches the target value. The corresponding actual angular acceleration (chart below) remains at a constant maximum value during the change, rather than a theoretically infinite impact. This treatment makes steering smoother and more predictable; experiments show that the maximum angular acceleration during steering can be reduced by approximately 75%.

[0041] Finally, after all the above processing steps, the resulting compensated and smooth left and right wheel speed commands are obtained. and The data is sent to the execution and output module to drive the wheelchair to move smoothly, precisely, and safely.

[0042] Example 2 As an optional implementation, this embodiment proposes a variant based on Embodiment 1, introducing an adaptive control strategy based on user manipulation intent recognition to support further technical features of this application. This scheme aims to enable the wheelchair control system to intelligently balance "smoothness" and "responsiveness" to adapt to different operating scenarios.

[0043] The overall control flow in this embodiment is similar to that in Embodiment 1, but an "intention recognition module" is added after the signal filtering process. The core function of this module is to analyze the caregiver's behavior in real time and determine whether they want a smooth, routine push or an emergency obstacle avoidance maneuver.

[0044] The recognition of control intent is based on the calculation of the dynamic characteristics of the original input signal. Specifically, this module calculates the rate of change of displacement of the joystick input, denoted as Δu. For example, it can calculate the original angular velocity command over a recent short time period (e.g., 100 milliseconds). or linear velocity command The maximum change.

[0045] The system presets two thresholds: a higher emergency threshold and a lower easing threshold. The judgment logic is as follows: If Δu rises rapidly within a short period of time and exceeds the preset emergency threshold, the system determines that the user's control intention is an "emergency control intention," such as suddenly turning or pushing the joystick to avoid a suddenly appearing obstacle.

[0046] If Δu remains at a low level, meaning the input signal changes smoothly, the system determines that the user's intention is a "smooth operation intention," such as pushing a wheelchair smoothly in an open corridor.

[0047] Based on the identified different manipulation intentions, the control system will adaptively adjust the control parameters of the subsequent processing modules to achieve different control effects: When an "emergency maneuvering intent" is detected, the system switches to high-response mode. Specifically, the controller automatically reduces the time constant tau of the first-order low-pass filter, for example, from 0.08 seconds in Example 1 to 0.04 seconds. A smaller tau means a wider filter passband, allowing the system to follow the input signal more quickly. Simultaneously, the controller increases the maximum angular acceleration limited by the angular acceleration ramp. For example, increasing l from 0.3 radians / second² to 0.6 radians / second² allows the wheelchair to turn with faster angular acceleration. These parameter adjustments collectively make the wheelchair more responsive, meeting the demands for rapid reaction during emergency obstacle avoidance.

[0048] When a "smooth maneuvering intention" is detected, the system operates in the normal smooth mode. In this mode, the controller uses the default parameter values ​​defined in Example 1, i.e., tau is 0.08 seconds. l is 0.3 radians / second². These parameters are designed to maximize noise filtering and smooth motion, providing passengers with the most comfortable and stable experience.

[0049] In this way, the control method provided in this embodiment is no longer fixed, but dynamically changing. When the caregiver is leisurely pushing the wheelchair in the park, the system prioritizes comfort; while when an emergency turn is needed to avoid pedestrians, the system can immediately provide the necessary agile maneuverability. This intelligent adaptive capability greatly enhances the scenario adaptability and user experience of the electric wheelchair.

[0050] Example 3 This embodiment proposes a further improvement to the yaw compensation mechanism, upgrading it from the open-loop compensation in Embodiment 1 to a closed-loop adaptive compensation system. This scheme, by introducing sensor feedback, achieves real-time, dynamic suppression of yaw disturbances, supporting the closed-loop compensation technical features described in this application.

[0051] To achieve closed-loop control, an inertial measurement unit (IMU) is additionally installed on the chassis of the electric wheelchair in this embodiment. This IMU can measure the three-axis angular velocities and accelerations of the wheelchair body in real time with high precision. In this scheme, the angular velocity about the vertical axis, i.e., the actual yaw rate of the wheelchair, is mainly utilized. .

[0052] Figure 9 This is a block diagram of the closed-loop yaw compensation control provided in this embodiment. The diagram clearly shows the structure and data flow of the closed-loop feedback system. Its control flow is as follows: The system's target angular velocity... (Right now Figure 9 The target angular velocity command (in the context of driving) is generated by the upstream smoothing control module. During straight-line driving, The value is zero. An inertial measurement unit (IMU) sensor mounted on the wheelchair measures the actual motion of the wheelchair's dynamic model (i.e., the actual wheelchair) in real time and outputs the actual angular velocity. This signal serves as feedback of the actual angular velocity. At the comparison point of the controller, the target angular velocity is... Feedback with actual angular velocity Compare and calculate the angular velocity error. = - The error signal is fed into a PID controller (or a simplified PI or P controller depending on system requirements), which calculates a real-time yaw correction angular velocity based on the current error, the accumulated error, and the rate of change of the error. For example, in a simplified proportional controller, = Kp × Where Kp is the proportional gain. This yaw correction is generated by the closed-loop feedback. , and the original target angular velocity They were fed into the differential kinematics model together. Within the model, the angular velocity command ultimately used to calculate the differential speed between the left and right wheels was updated to... = + Subsequently, the differential kinematics model was used. l and linear velocity after limiting It calculates the final left and right wheel speed commands and sends them to the motor driver.

[0053] A specific scenario can better illustrate its working process: Suppose a wheelchair is traveling on a road surface slightly tilted to the right, and the caregiver intends to keep it in a straight line. At this moment, the target angular velocity... The actual angular velocity is 0. However, because the component of gravity on the slope generates a torque that causes the wheelchair to yaw to the right, the wheelchair produces a small, non-zero actual angular velocity. The inertial measurement unit sensor detected this. Therefore, a negative error is generated at the comparison point. The PID controller outputs a positive correction angular velocity based on this error. .this This is incorporated into the differential kinematics model, causing the system to allocate a slightly higher speed to the left wheel and a slightly lower speed to the right wheel, thus generating a counteracting torque to the left. This counteracting torque precisely balances the yaw torque to the right caused by the road surface inclination, ultimately resulting in a lower actual angular velocity of the wheelchair. It returns to 0, thus dynamically maintaining straight-line travel.

[0054] Compared to the open-loop compensation in Example 1, the closed-loop scheme in this embodiment has significant advantages. It no longer relies solely on offline calibrated static parameters, but can proactively and in real-time combat various unknown, time-varying disturbances, such as crosswinds, dynamically changing load unevenness (e.g., occupant body movement), and various complex road conditions. This greatly improves the robustness and accuracy of yaw compensation, maintaining excellent straight-line driving performance in various complex environments.

[0055] Example 4 This embodiment details the deep integration and switching mechanism of multi-mode parameter sets, serving as a deepening and concretization of the multi-mode concept in Embodiment 1, and aims to support the technical features of multi-mode control in this application. This solution provides a highly scenario-based control experience by pre-setting complete parameter sets for different scenarios and achieving one-click atomic switching.

[0056] In this embodiment, the control system presets at least two complete parameter sets: one for "normal mode" and the other for "slow mode". Each parameter set contains a series of core control parameters that affect the dynamic behavior of the wheelchair.

[0057] (Normal Mode Parameter Set) is designed for open outdoor environments, prioritizing traffic efficiency and general comfort. Typical parameter configurations may include: Gear speed threshold : [0.3, 0.4, 0.5] m / s.

[0058] Maximum angular acceleration limit : 0.3 radians / second².

[0059] linear velocity decay coefficient during steering 0.4. This is a new parameter used to attenuate the linear velocity to a certain extent during turning, based on the magnitude of the angular velocity, in order to improve stability during turning. The smaller the value, the less noticeable the attenuation.

[0060] The (slow mode parameter set) is specifically designed for complex environments such as indoors, narrow spaces, or crowded areas, prioritizing safety and operational precision. Typical parameter configurations may include: Gear speed threshold [0.15, 0.2, 0.25] meters per second. The overall speed level is significantly reduced, and the gear divisions are more refined, making fine adjustments easier.

[0061] Maximum angular acceleration limit 0.15 radians / second². Steering will become smoother.

[0062] linear velocity decay coefficient during steering A higher value (0.8) means that the wheelchair's forward speed will decrease more significantly when turning, thereby greatly reducing the turning radius and improving safety and controllability in confined spaces.

[0063] Mode switching can be triggered in several ways, such as via a dedicated physical button on the rear grip joystick or via a service call sent from an upper-level application (such as a mobile app) connected to the wheelchair control system. When the control device receives a command to switch modes, such as from "Normal Mode" to "Slow Mode," it performs an atomic operation: immediate loading. All parameters are replaced, and the set of active parameters currently in memory is replaced with them. This overall replacement ensures that all relevant dynamic characteristics of the system change synchronously and in a coordinated manner.

[0064] Take a real-world application scenario as an example: A caregiver pushes a wheelchair from an outdoor plaza, preparing to enter a small, crowded elevator. Before entering the elevator, the caregiver presses the mode switch button on the control lever to switch the system to "slow mode." Instantly, the wheelchair's maximum speed limit drops from 0.5 m / s to 0.25 m / s. When the caregiver makes a turning maneuver, they will find the wheelchair's turning motion much smoother than before, and the wheelchair's forward speed automatically and significantly decreases while turning. This allows the caregiver to perform very precise and safe fine-tuning operations inside the elevator, such as turning in place or making small movements, without worrying about hitting others or the elevator walls due to excessive speed or sharp turns. Experimental data shows that in simulated narrow passage tests, using slow mode can increase the success rate from 60% to 95%.

[0065] Through this deeply integrated multi-mode design, the control method provided in this application is no longer singular, but can present completely different control characteristics according to user needs and environmental changes, greatly enhancing the product's practicality, safety and user-friendliness.

[0066] The present invention also provides a multi-strategy fusion electric wheelchair thrust assist control system. The multi-strategy fusion electric wheelchair thrust assist control system can be implemented by executing the process steps of the multi-strategy fusion electric wheelchair thrust assist control method. That is, those skilled in the art can understand the multi-strategy fusion electric wheelchair thrust assist control method as a preferred embodiment of the multi-strategy fusion electric wheelchair thrust assist control system.

[0067] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0068] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A thrust-assisted control method for an electric wheelchair, applied to an electric wheelchair system including a controller and left and right drive wheels, characterized in that, Includes the following steps: The raw input signal representing the desired speed, received from the rear-grip joystick, is low-pass filtered to generate a filtered speed command. Based on the linear velocity component in the filtered speed command, hysteresis logic is used for gear switching. The hysteresis logic includes setting an upshift threshold higher than its corresponding downshift threshold for at least one gear. A yaw compensation mechanism is introduced, which adjusts the target speed of the left and right drive wheels differently based on the filtered speed command in order to compensate for the yaw of the electric wheelchair. An angular acceleration ramp limit is applied to the angular velocity component in the filtered velocity command to smooth the steering process; as well as The continuity of the original input signal is monitored, and when the interruption of the original input signal reaches a preset timeout threshold, a safe parking strategy is triggered to stop the electric wheelchair from moving.

2. The method according to claim 1, characterized in that, The yaw compensation mechanism is a dual yaw following gain compensation mechanism, which includes introducing a static yaw correction and a dynamic yaw following gain to adjust the target speed of the left and right drive wheels.

3. The method according to claim 1, characterized in that, The step of monitoring the continuity of the original input signal includes: Compare whether the difference between the current time and the timestamp of the latest received original input signal exceeds the preset timeout threshold.

4. The method according to any one of claims 1, 2, or 3, characterized in that, The step of applying angular acceleration ramp limiting to the angular velocity components includes: The change in the angular velocity component within each control cycle is limited to the product of the preset maximum angular acceleration and the control cycle.

5. The method according to any one of claims 1, 2, or 3, characterized in that, The method further includes: In response to user input, the system switches between a preset normal mode and a slow mode, wherein the slow mode has at least one of the following characteristics: a lower gear speed threshold, a lower maximum speed limit, and a smaller maximum angular acceleration limit.

6. The method according to any one of claims 1, 2, or 3, characterized in that, The method further includes: The user's control intention is identified by calculating the rate of change of the original input signal, wherein when the rate of change of the original input signal exceeds a first threshold, it is identified as an urgent control intention, and when the rate of change is below a second threshold, it is identified as a gentle control intention; and Based on the identified manipulation intent, at least one of the following should be adaptively adjusted: the control parameters of the low-pass filtering process and the control parameters of the angular acceleration ramp limit.

7. The method according to claim 1 or 3, characterized in that, The yaw compensation mechanism is a closed-loop compensation control, and the method further includes: The angular velocity component in the filtered velocity command is taken as the target angular velocity. Obtain the actual angular velocity from the inertial measurement unit; and Based on the error between the actual angular velocity and the target angular velocity, a yaw correction is generated to adjust the target speed of the left and right drive wheels.

8. A control device for an electric wheelchair, comprising: processor; as well as A memory having stored thereon computer instructions that, when executed by the processor, cause the processor to perform the method as described in any one of claims 1, 2, or 3.

9. An electric wheelchair system, comprising left and right drive wheels, a rear grip lever, and a control device as described in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of claims 1, 2, or 3.

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