Foamed material electric bicycle automatic turnover seat intelligent control method and system

Abstract

This invention relates to the field of electric bicycle technology, specifically to an intelligent control method and system for an automatic flip seat on an electric bicycle made of foam material. The method first collects real-time vehicle status information such as side stand position, seat position, seat flip angle, and motor operating current. Upon receiving a seat flip command, it performs a safety verification. If the verification is successful, it drives the motor to flip the seat using an S-curve acceleration / deceleration algorithm, and includes real-time anti-pinch checks during the flip. The method also adds a seat system self-check and health assessment step. When parking conditions are met, the seat is flipped at low speed, the motor current curve is collected and recorded, and feature values ​​are extracted and compared with benchmark values ​​to assess the system's health status. It also supports feature value trend analysis and forced locking during driving, adapting to the physical characteristics of foam seats, improving operational convenience and system safety, enabling predictive maintenance of the seat system, and extending its service life.

Description

Technical Field

[0001] This invention relates to the field of electric bicycle technology, and more specifically, to a smart control method and system for an electric bicycle with an automatically flipping seat made of foam material. Background Technology

[0002] Currently, most two-wheeled electric bicycles use a manually flip-up seat design. The seat is made of foam material and is connected to the frame via a mechanical latch. Users need to manually operate the seat to open the storage compartment to access their items. Manual flipping usually requires the user to bend over and use one hand to operate the latch and lift the seat. This is extremely inconvenient when the user is carrying heavy items (such as shopping bags or helmets), as they often need to put the items down before opening the storage compartment. Summary of the Invention

[0003] In view of this, the present invention aims to solve the aforementioned problems existing in the prior art, and provides a method and system for intelligent control of an automatic flip-over seat for an electric bicycle made of foam material. This system enables automatic seat flipping, ensures safety through multiple safety verification mechanisms, protects the foam material through flexible motion control, and achieves intelligent monitoring and predictive maintenance of the seat's health status through self-diagnostic functions.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for intelligent control of an electric bicycle with an automatically flipping seat made of foam material includes the following steps: Real-time collection of vehicle status information, including side stand status, rider seating status, seat tilt angle, and drive motor operating current; When a seat open or close command is received, a safety verification is performed; When the safety verification is passed, the control drive motor drives the seat to flip according to the preset S-curve acceleration and deceleration algorithm; During the seat rotation process, an anti-pinch detection is performed to stop the rotation if an object is caught.

[0006] Preferably, the safety verification includes: verifying that the side support is in the lowered state, verifying that the seat cushion is in a pressure-free state, and verifying that the vehicle is stationary.

[0007] Preferably, the anti-pinch judgment includes: real-time monitoring of the motor operating current; when the instantaneous current value exceeds the preset anti-pinch threshold and the duration exceeds the preset time threshold, it is determined that the anti-pinch is triggered; when the anti-pinch is triggered, the power supply to the drive motor is cut off and the motor is controlled to rotate in the opposite direction by a preset angle and then stop.

[0008] Preferably, the method further includes a self-diagnostic step: a self-test is performed each time the vehicle is powered on and the preset safety conditions are met. The self-test steps include: controlling the drive motor to drive the seat to flip at a speed lower than the normal operating speed according to a preset S-curve acceleration and deceleration algorithm; recording the current curve of the drive motor operating current changing over time at a preset sampling frequency; extracting at least one feature value from the current curve; comparing the extracted feature value with a preset benchmark feature value, and evaluating the health status of the seat system based on the comparison result.

[0009] Preferably, the characteristic value includes at least one of peak current, average current, travel time, and current fluctuation rate; wherein, the peak current is the maximum instantaneous current value in the current curve, reflecting the point of maximum resistance during seat flipping; the average current is the arithmetic mean of the current values ​​at each sampling point in the current curve, reflecting the overall resistance level; the travel time is the time from the start of the drive motor to the time the seat reaches the target position, reflecting the smoothness of movement; and the current fluctuation rate is the ratio of the standard deviation of the current curve to the average current, reflecting the stability of movement.

[0010] Preferably, comparing the extracted feature values ​​with preset benchmark feature values ​​and evaluating the health status of the seat system based on the comparison results includes: calculating the percentage deviation between the real-time feature values ​​and the benchmark feature values; comparing the percentage deviation with at least one preset threshold; outputting maintenance reminder information when the percentage deviation exceeds a first preset threshold; and outputting fault alarm information and disabling the automatic flip function when the percentage deviation exceeds a second preset threshold, wherein the second preset threshold is greater than the first preset threshold.

[0011] Preferably, the method further includes a trend analysis step: storing the feature values ​​extracted from each self-diagnosis step into a historical database, and establishing a trend curve of the feature values ​​changing with usage time; when the trend curve shows that the feature values ​​are monotonically increasing and approaching a preset threshold, a predictive maintenance prompt is output in advance.

[0012] Preferably, the method further includes: when the vehicle is detected to be in motion, cutting off the drive circuit of the drive motor and short-circuiting the motor windings to generate braking torque, while locking the electromagnetic locking mechanism.

[0013] An intelligent control system for an electric bicycle with an automatically flipping seat made of foam material, for performing the method described in any of the above-mentioned methods, comprising: The sensing module includes a side stand position sensor for detecting the side stand status, a seat pressure sensor array for detecting the rider's seated status, a seat position sensor for detecting the seat tilt angle, and a current detection module for sampling the operating current of the drive motor. The decision controller is electrically connected to each sensor of the perception module and is configured to generate motion control commands based on the vehicle status information and user commands collected by the perception module, and execute the method described in any of the above-mentioned steps. The execution module, electrically connected to the decision controller, includes a drive motor for driving the seat to flip and an electromagnetic locking mechanism for locking the seat position.

[0014] Preferably, the seat cushion pressure sensor array is a thin-film pressure sensor array, which is laid under the high-density transition layer between the foam material and the seat base.

[0015] Preferably, the seat position sensor includes a linear Hall element for continuously detecting the seat tilt angle and a micro-limit switch for redundancy confirmation of the seat position.

[0016] Compared with the prior art, the present invention has the following beneficial effects: First, it significantly improves ease of use. Users can open or close the water seat with a single button press or by sending a command via a mobile app, without having to bend over or free their hands. This is especially suitable for scenarios where both hands are carrying items.

[0017] Secondly, comprehensive safety is ensured. Through a three-level safety verification mechanism, the seat is only allowed to flip when the side support is down, the seat cushion is unpressured, and the vehicle is stationary. At the same time, a forced locking mode is set up, which generates braking torque by short-circuiting the windings and locks the electromagnetic lock when the vehicle is in motion, reducing the safety hazard of the seat opening accidentally.

[0018] Third, it effectively protects the foam material and extends the seat's lifespan. An S-curve acceleration / deceleration algorithm is used to achieve smooth start-stop, avoiding damage to the foam material from impact loads; the seat actively decelerates and buffers as it approaches its end point, reducing impact wear between the foam and the seat cushion edge.

[0019] Fourth, it enables intelligent predictive maintenance. Through self-diagnostic functions, it automatically collects the motor current curve each time power is applied, extracting four characteristic values: peak current, average current, travel time, and current fluctuation rate. These are compared with benchmark values ​​to accurately assess the seat's health status. When the deviation of these characteristic values ​​exceeds a threshold, it outputs tiered maintenance reminders or fault alarms. Through historical data trend analysis, it can provide early warnings before faults occur, transforming reactive repair into proactive maintenance.

[0020] Fifth, it provides comprehensive personal safety protection. Through the anti-pinch protection function, the motor current is monitored in real time, and when a foreign object is detected being clamped, it immediately reverses, effectively preventing pinching accidents. Attached Figure Description

[0021] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0022] Figure 1 This is a flowchart illustrating an embodiment of the intelligent control method for automatically flipping the seat of an electric bicycle made of foam material provided in this application. Figure 2 This is a schematic diagram of the structure of an intelligent control system for an electric bicycle with an automatic flip seat made of foam material, provided in one embodiment of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Figure 1 This is a flowchart illustrating an embodiment of the intelligent control method for an automatic flip-up seat on an electric bicycle made of foam material. The intelligent control method for an automatic flip-up seat on an electric bicycle made of foam material is applied to an intelligent control system for an automatic flip-up seat on an electric bicycle made of foam material, such as... Figure 1 As shown, the method includes the following:

[0025] Step S110: Real-time collection of vehicle status information, including side stand status, rider seating status, seat tilt angle, and drive motor operating current. In practical applications, the system is always in a real-time sensing state, continuously collecting multiple core vehicle status information, including the side stand position detected by the side stand position sensor to indicate whether the side stand is folded up or down, the rider's seated status fed back by the seat pressure sensor array, the real-time seat flip angle collected by the seat position sensor, and the drive motor operating current sampled by the current detection module. This information is synchronously transmitted to the decision controller, providing accurate and real-time status basis for subsequent control operations.

[0026] It should be noted that in some situations, the system can enter a low-power standby mode. In this mode, real-time acquisition of seat tilt angle and drive motor operating current will cease, and only low-power monitoring of side stand status and rider seating status will be maintained. For example, when the vehicle is in normal riding mode, to avoid energy loss due to invalid signal acquisition and to prevent accidental triggering operations in non-parked states, the system will automatically switch to this standby mode. Similarly, if no operation commands are detected after the vehicle is powered on and it remains in a parked, inactive state for a preset duration, the system will also proactively enter standby mode to reduce energy consumption and improve the vehicle's range. Only when changes in side stand status and rider seating status that meet the wake-up conditions are detected will the system exit standby mode, resume real-time acquisition of all vehicle status information, and enter a ready-to-work state.

[0027] Step S120: When a seat opening or closing command is received, perform a safety verification. Specifically, when the decision controller receives a seat opening or closing command from the user via a legitimate input method such as the car key button or a mobile Bluetooth app, it will not directly trigger the seat to flip. Instead, it will immediately initiate a safety verification process to comprehensively verify the current actual state of the vehicle. By retrieving previously collected real-time vehicle status information, it will determine whether various safety conditions are met. Only after all safety verification items have been verified and the operating conditions are confirmed to be safe will the subsequent seat flip control stage begin. If any verification item is not met, the flip command will be directly refused to be executed, thus avoiding operational risks under unsafe conditions from the source.

[0028] Step S130: When the safety verification is passed, control the drive motor to drive the seat to flip according to the preset S-curve acceleration and deceleration algorithm; Specifically, if all safety verification conditions are passed, the decision controller will immediately send a drive control command to the execution module, controlling the drive motor to operate according to the S-curve acceleration and deceleration algorithm preset by the system. This algorithm precisely controls the speed change of the motor, driving the seat to smoothly complete the corresponding opening or closing and flipping actions, adapting to the damping and flexible physical characteristics of the foam material seat, and avoiding wear of the foam seat or impact on the mechanism due to sudden speed changes.

[0029] During the seat rotation process, an anti-pinch detection is performed to stop the rotation if an object is caught.

[0030] In other words, the system continuously performs anti-pinch checks during the entire seat rotation process. By monitoring the changes in the operating current of the drive motor in real time, it determines whether a foreign object is caught during the seat rotation. Once an abnormal situation that meets the anti-pinch trigger conditions is detected, the anti-pinch protection mechanism will be triggered immediately to stop the seat rotation and avoid damage to foreign objects, damage to the foam seat, or failure of the motor mechanism.

[0031] In some embodiments, the safety verification includes: verifying that the side stand is in the down position, verifying that the seat cushion is in a pressure-free position, and verifying that the vehicle is stationary.

[0032] The aforementioned safety verification process employs a three-level verification method, specifically including three core verification items. All three verifications must be passed to be considered a successful safety verification: First, the side stand status is verified by retrieving real-time data from the side stand position sensor to confirm that the side stand is in a parked position, preventing the risk of tipping over when the vehicle is not parked and the seat is flipped. Second, the seat pressure status is verified by using feedback signals from the seat pressure sensor array to verify that the seat is in a pressure-free state, ensuring that no rider is seated at this time, thus avoiding operational hazards from a personnel safety perspective. Finally, the vehicle's operating status is verified by using signals from the motor Hall sensor or vehicle data read from the vehicle's CAN bus to verify that the vehicle is in a stationary, non-moving state, preventing accidental seat tipping over during vehicle operation.

[0033] In some embodiments, the anti-pinch determination includes: real-time monitoring of the motor operating current; when the instantaneous current value exceeds a preset anti-pinch threshold and the duration exceeds a preset time threshold, it is determined that the anti-pinch is triggered; when the anti-pinch is triggered, the power supply to the drive motor is cut off and the motor is controlled to rotate in the opposite direction by a preset angle and then stop.

[0034] Specifically, the anti-pinch detection during the seat flipping process relies on real-time monitoring and intelligent judgment of the motor's operating current. This is a key protective measure to ensure the safety of the seat flipping operation, prevent the foam seat from being crushed and damaged, and avoid overload of the transmission mechanism. The specific execution process is as follows: The first step is the real-time monitoring of the motor's operating current. Throughout the entire process of the drive motor being driven by a command to open or close the foam seat, the current detection module connected in series with the motor's power supply circuit continuously monitors the motor's operating current using high-frequency sampling. The collected real-time current data is then transmitted synchronously and accurately to the decision controller, ensuring that the controller can dynamically grasp the motor's current change status and provide continuous and reliable current data for subsequent anti-pinch judgment.

[0035] Secondly, there is the anti-pinch trigger determination stage. The decision controller continuously compares the received real-time motor current value with the pre-calibrated anti-pinch current threshold of the system, and simultaneously judges the state of current exceeding the threshold by timing. Only when the instantaneous value of the motor current is detected to exceed the preset anti-pinch threshold, and the duration of the abnormal state exceeding the threshold reaches the time threshold set by the system, will the decision controller officially determine that the anti-pinch has been triggered, confirming that the seat has caught a foreign object during the flipping process, avoiding false triggering of the anti-pinch mechanism due to instantaneous current fluctuations, and ensuring the accuracy of the control logic.

[0036] Finally, there's the execution phase after the anti-pinch mechanism is triggered. Once the decision controller determines that the anti-pinch mechanism has been triggered, it will immediately issue an emergency protection control command, cutting off the power supply to the drive motor to prevent it from continuing to rotate in the original direction. This avoids the foreign object being continuously squeezed, and prevents the foam seat from denting or breaking due to excessive localized force. It also prevents the motor from burning out its windings due to overload. While cutting off the power, the controller will simultaneously control the motor to rotate in the opposite direction by a preset angle, causing the seat to retract slightly, effectively releasing the trapped foreign object. After the motor completes the preset angle of reverse rotation, the controller will issue another command to stop all motor operations until the user removes the foreign object and issues a new operation command. The entire process forms a complete anti-pinch protection closed loop.

[0037] In some embodiments, this intelligent control method further includes a health status assessment step for the seat system, namely: when preset conditions are met, a self-test is performed. The self-test steps include: controlling the drive motor to drive the seat to flip at a speed lower than normal operating speed according to a preset S-curve acceleration and deceleration algorithm; recording the current curve of the drive motor's operating current changing over time at a preset sampling frequency; extracting at least one feature value from the current curve; comparing the extracted feature value with a preset benchmark feature value; and assessing the health status of the seat system based on the comparison result.

[0038] Specifically, this step is conducted as a system self-check, which is initiated only when preset safe parking conditions are met. This achieves status detection of the seat system while avoiding interference with normal user operation. Furthermore, the self-check process is adapted to the physical characteristics of the foam seat material throughout, preventing wear and tear on the seat due to the testing actions. The specific self-check execution steps are as follows: First, the system determines whether the current vehicle meets the preset self-check conditions, namely, the vehicle is powered on, the side stand is down, the seat cushion is unpressurized, and the wheels are stationary. Only when all conditions are met will the self-check process be initiated. After the self-check is initiated, the decision controller sends control commands to the drive motor, controlling the drive motor to follow the preset S... The algorithm operates on a curve-based acceleration / deceleration mechanism, with the motor running at a speed lower than the normal seat rotation speed (e.g., 50% of normal speed). This low-speed rotation effectively reduces the impact on the foam seat during self-testing, minimizing wear on the mechanical components and balancing testing requirements with the durability of the seat system. Throughout the self-testing process of the motor-driven seat rotation, the current detection module continuously collects and records the motor's operating current at a preset high-frequency sampling rate, creating a complete current curve showing the motor's operating current over time. This provides continuous and accurate current data support for subsequent status analysis. Once the seat has completed its rotation... After the action and current curves are collected, the system will extract at least one feature value from the current curves recorded during the self-test process that can reflect the seat's tilting resistance and the operating status of the mechanism. This feature value will serve as the core indicator for assessing the health status of the seat system. Finally, the system will comprehensively compare the real-time feature value extracted during this self-test with the pre-calibrated benchmark feature value stored in the storage unit. Based on the deviation between the two, the system will comprehensively judge the aging degree of the foam seat, the operating accuracy of the transmission mechanism, and the coordination status of each component. Ultimately, the system will complete an accurate assessment of the overall health status of the seat system, providing reliable data for subsequent maintenance reminders, fault alarms, and predictive maintenance.The extracted feature values ​​specifically include at least one of peak current, average current, travel time, and current fluctuation rate. Each feature value has a clear physical meaning and corresponds to different operating states of the seat system: Peak current is the maximum instantaneous current value in the entire current curve. The change in this value can directly reflect the maximum resistance point that needs to be overcome during the seat flipping process, and can accurately determine whether there are problems such as local jamming or local aging and hardening of foam; Average current is the arithmetic mean of the current values ​​of all sampling points in the current curve. This value can reflect the overall resistance level of the entire seat flipping process. Issues such as uniform aging of foam and poor lubrication of the transmission mechanism will be directly reflected in the change of average current; Travel time is the total time from the start of the drive motor to the smooth flipping of the seat to the target position. This indicator can intuitively reflect the smoothness of the seat flipping movement. Problems such as increased resistance and inflexible operation of the mechanism will lead to a longer travel time; Current fluctuation rate is the ratio of the standard deviation of the current curve to the average current. This indicator is used to measure the stability of the motor's operating current. The larger the current fluctuation rate, the more violent the current fluctuation during the seat flipping process, which can indirectly reflect whether the mechanism operates smoothly and whether there are periodic jamming or local unevenness on the surface of the foam seat.

[0039] After feature value extraction is completed, the system will compare the real-time feature values ​​obtained from this collection and calculation with the pre-calibrated and stored benchmark feature values ​​one by one. The benchmark feature values ​​are reference values ​​calibrated under standard operating conditions when the seat system is in a brand-new state, which can represent the benchmark of various indicators when the seat system is operating normally. By calculating the deviation between the real-time feature values ​​and the benchmark feature values, and combining the physical meaning of each feature value, the system comprehensively judges the aging state of the foam seat, the operating accuracy of the transmission mechanism, the coordination of various components, etc., and finally comprehensively evaluates the overall health status of the seat system, providing accurate data judgment basis for subsequent maintenance reminders and fault alarms.

[0040] Furthermore, when comparing the extracted real-time feature values ​​with preset benchmark feature values ​​to assess the health status of the seat system, a tiered threshold judgment method is used to achieve precise status warnings and fault control. The specific operation process is as follows: First, the system calculates the percentage deviation of each real-time feature value relative to the corresponding benchmark feature value according to the preset calculation logic. The quantified numerical deviation intuitively reflects the degree of difference between the current operating indicators of the seat system and the standard state, providing a quantitative basis for subsequent status judgment. Next, the calculated percentage deviation of each feature value is compared and analyzed one by one with at least one threshold preset by the system. This threshold is calibrated through a large number of tests based on the aging characteristics of the foam material and the operating limits of the mechanical mechanism of the seat system, and different levels of judgment standards are set, including a first preset threshold and a second preset threshold. The value of the second preset threshold is greater than the first preset threshold, corresponding to the minor abnormality and serious abnormality state of the seat system, respectively.

[0041] After comparing the deviation percentage with the threshold, the system will execute corresponding status prompts and function control operations based on the comparison results: If the deviation percentage of any characteristic value exceeds the first preset threshold, it indicates that the seat system has a minor abnormality, such as initial aging of the foam, slight lubrication failure of the transmission mechanism, or a slight increase in local resistance. At this time, the system will immediately output maintenance reminder information, reminding the user to check and maintain the seat system through text display on the dashboard, indicator lights, or buzzers, so as to eliminate potential minor problems in time and prevent the fault from developing further. If the deviation percentage of any characteristic value exceeds the second preset threshold, it indicates that the seat system has a serious abnormality, such as foam aging and cracking, mechanical mechanism jamming, or severe wear of transmission components. Continuing to use the automatic flip function may cause the motor to burn out, the foam seat to break, or the flip mechanism to malfunction. At this time, the system will immediately output fault alarm information and directly disable the automatic flip function of the seat, only retaining the permission for manual emergency operation, thus avoiding the risk of the fault escalating from the hardware function. The automatic flip function will only be disabled after the user completes professional inspection and troubleshooting of the seat system and the system confirms that the indicators have returned to normal through self-testing.

[0042] In some embodiments, this intelligent control method further includes a trend analysis step for the seat system. By tracking and analyzing the changing patterns of historical feature values ​​over a long period, it enables early prediction and preventative maintenance of the seat system's status. Compared to a single health status assessment, this further enhances the foresight and scientific rigor of system maintenance. The specific execution process is as follows: After each health assessment of the seat system, extraction, and calculation of real-time feature values, the system stores the feature value data, the corresponding detection time, and environmental operating condition information in a preset historical database. This enables long-term retention and systematic management of feature value data. The database can continuously store multiple sets of feature value data from previous detections, providing sufficient sample support for trend analysis. Subsequently, based on all feature value data stored in the historical database, the system performs data sorting and fitting according to the timeline, automatically establishing trend curves for each feature value as a function of vehicle usage time. This visually presents the long-term changing patterns of various operating indicators of the seat system, clearly reflecting the gradual process of foam material aging and mechanical wear.

[0043] After establishing the characteristic value change trend curve, the system continuously monitors and analyzes the curve's trend, focusing on the overall change direction of the characteristic values. When the trend curve shows that any characteristic value is continuously and monotonically increasing, and the current value of that characteristic value is gradually approaching the preset first threshold, it indicates that the operating status of the seat system is developing abnormally. Foam aging or mechanical wear has entered a stage requiring early intervention. At this time, the system will proactively output predictive maintenance prompts, reminding users to check and maintain the seat system in advance through interactive methods such as text and indicator lights on the dashboard. This predictive maintenance prompt is issued earlier than regular maintenance prompts, allowing users to take timely maintenance measures before obvious abnormalities appear in the seat system. This effectively slows down the rate of foam aging and mechanical wear, preventing small problems from developing into serious malfunctions from the source, further extending the overall service life of the seat system. It also allows users to schedule maintenance time more rationally, improving the user experience.

[0044] In some embodiments, to fundamentally avoid the safety hazards caused by the accidental flipping of the seat during vehicle operation, this intelligent control method also sets up a forced seat locking mechanism while the vehicle is in motion, forming multiple safety protections. The system continuously relies on the vehicle status information collected by the sensing module to comprehensively determine whether the vehicle is in motion. Specifically, it detects whether the wheels are rotating through the motor Hall sensor, or combines the pressure signal from the seat pressure sensor array with the retraction signal from the side support position sensor for joint judgment. As long as the determination conditions for the motion state are met, the system will immediately trigger the forced locking operation: First, it quickly cuts off the drive circuit of the drive motor to prevent the motor from receiving any flipping drive command. At the same time, it short-circuits the motor windings, using the electromagnetic characteristics of the motor to generate braking torque, keeping the motor rotor in a locked state, unable to be driven to rotate by external force, thus completely restricting the seat flipping action from the drive end. Simultaneously, the system sends a locking command to the electromagnetic locking mechanism, causing the electromagnetic locking mechanism to fully close and lock, firmly fixing the seat to the frame, thus achieving rigid locking of the seat from the mechanical structure end. With a triple protection system of drive circuit cut-off, motor winding short-circuit braking, and electromagnetic locking mechanism, the seat remains firmly closed during vehicle operation. Regardless of any misoperation commands or minor external interference, the seat will not flip over, maximizing riding safety during vehicle operation.

[0045] Reference Figure 2This application also provides an intelligent control system for an electric bicycle with an automatic flip seat made of foam material, used to execute the aforementioned intelligent control method for an electric bicycle with an automatic flip seat made of foam material. The intelligent control system includes: a sensing module 1, comprising a side stand position sensor for detecting the side stand's state, a seat pressure sensor array for detecting the rider's seated state, a seat position sensor for detecting the seat flip angle, and a current detection module for sampling the operating current of the drive motor; a decision controller 2, electrically connected to each sensor of the sensing module, configured to generate motion control commands based on vehicle status information and user commands collected by the sensing module, and execute the aforementioned method; and an execution module 3, electrically connected to the decision controller, comprising a drive motor for driving the seat flip and an electromagnetic locking mechanism for locking the seat position. Specifically, the seat pressure sensor array is a thin-film pressure sensor array, laid under a high-density transition layer between the foam material and the seat base; the seat position sensor includes a linear Hall element for continuously detecting the seat flip angle and a micro-motion limit switch for redundancy confirmation of the seat position.

[0046] It should be noted that this solution is designed for traditional foam seats, featuring an automatic flipping control system centered on a microcontroller, integrating multi-sensor fusion, intelligent control algorithms, and self-diagnostic functions. While enabling convenient automatic opening / closing of the seat bucket, the system fully considers the physical properties of the foam material, ensuring seat comfort, reliability, and durability through optimized control strategies and mechanical interface design. A self-check function is specifically introduced at startup, monitoring the current curve during the flipping process to assess foam aging and mechanical condition in real time, providing early warnings of maintenance needs, enabling predictive maintenance, and extending the seat's lifespan.

[0047] The following describes the solution provided in this application in further detail, combining the method and system: The system provided in this application mainly includes the following structure: perception layer (i.e., perception module), decision layer (i.e., decision controller), execution layer (i.e., execution module), interaction layer, and power layer. The perception layer (i.e., the perception module) includes: Side support position sensor: a contact switch that detects the side support's retracted / lowered state. Seat pressure sensor: A thin-film pressure sensor array, laid under a high-density transition layer between the foam and the base plate, detects the rider's seating position. Vehicle tilt sensor: MEMS gyroscope, monitors the vehicle's tilt angle for tipping prediction. Motor Hall sensor: Built into DC geared motor, providing rotor position and speed feedback. Seat position sensor: A linear Hall element is installed at the pivot to detect the seat tilt angle; a micro-limit switch is installed at the base plate as a redundancy confirmation of the seat in position. Current detection module: Samples the motor's operating current for anti-pinch detection and resistance characteristic analysis. The decision-making body includes: Main control chip (MCU): Automotive-grade 32-bit MCU, integrating power management, motor drive PWM, CAN communication, and fault diagnosis modules. Storage unit: EEPROM / Flash, storing self-test history data, current reference curve, fault codes, etc. Algorithm modules: S-curve acceleration / deceleration control, PID closed-loop regulation, anti-pinch logic, self-test analysis algorithm. The execution layer includes: DC geared motor: equipped with Hall sensor, driven by worm gear, and has self-locking characteristics. Electromagnetic locking mechanism: Used to lock the seat after it is fully open / closed to prevent accidental operation. Manual emergency release cable: Mechanical unlocking device, allows manual release of the seat in case of power failure. The interaction layer includes: Input methods: keypad button, mobile app (Bluetooth), optional voice control module Outputs: Instrument panel status indicator lights, buzzer, text prompts (e.g., "Please maintain your seats") The power layer includes: Vehicle power supply: The DC-DC converter draws power from the vehicle battery, providing 12V / 5V power with overvoltage and overcurrent protection. Backup battery: Optional, to maintain real-time clock and fault memory. The system working method provided in this application is as follows: In normal working mode: 1. Standby: After the system is powered on, it performs a hardware initialization self-test and then enters a low-power standby mode, monitoring only the side support sensor and the seat pressure sensor.

[0048] 2. Wake-up: When the side stand is down and there is no pressure signal from the seat for more than 3 seconds, the system determines that the vehicle is in a safe parking state, wakes up the main control chip, and enters the standby state.

[0049] 3. Command Verification: The user issues an open or close command via key / APP, and the decision controller performs three levels of safety verification: Is the side stand down? Is there no pressure on the seat? Are the wheels stationary (read via motor Hall effect sensor or CAN bus)? If all conditions are met, the electromagnetic lock will unlock and the motor will start according to the preset S-curve; if any condition is not met, the operation will be refused and an alarm will sound.

[0050] Specifically, during motion control, the motor is driven by an S-curve acceleration and deceleration algorithm. The opening process is as follows: low-speed start (overcoming static friction) → medium-to-high-speed operation → deceleration and buffering near the end point; the closing process is at low speed throughout, and the last 5 degrees is closed at a crawling speed to avoid impact.

[0051] Real-time monitoring of motor current and position: If the current exceeds the set threshold and continues for 50ms, the anti-pinch function is triggered, the motor reverses for 200ms and then stops and an alarm is triggered.

[0052] After reaching the target position (double confirmation by position sensor and limit switch), the motor power is cut off, the electromagnetic lock is activated, and the instrument status is updated.

[0053] Forced locking: When the vehicle is in motion (when the wheels are rotating or the seat cushion is under pressure and the side support is retracted), the controller short-circuits the motor windings to generate braking torque and locks the electromagnetic lock to ensure that the seat cannot be opened accidentally.

[0054] Furthermore, the solution provided in this application also includes: initiating a self-test mode: Each time the vehicle is powered on (i.e., under the preset trigger conditions) or when the user manually triggers a self-check via the app, the system first checks whether the safety conditions are met: the side stand is down, the seat is unpressured, and the wheels are stationary. If these conditions are met, the self-check process is automatically initiated; if not (e.g., the vehicle is being ridden), the self-check is skipped, and the failure to execute is recorded until the conditions are met again.

[0055] Opening phase: The system controls the motor at 50% normal speed (to reduce impact) to slowly open the seat from the closed position to the fully open position, while recording the motor current curve Iopen(t) at a sampling rate of 1kHz.

[0056] Feature extraction: Four feature values ​​were extracted from the recorded turn-on current curve: Peak current Ip: The maximum instantaneous current value during the start-up process, reflecting the point of maximum resistance.

[0057] Average current Iavg: The arithmetic mean of the current during the start-up process, reflecting the overall resistance level.

[0058] Travel time T: The time from when the motor starts to when the seat reaches the open position, reflecting the smoothness of movement.

[0059] 2.2 Comparative Analysis: During the startup process, the extracted real-time feature values ​​are compared with the reference feature values ​​(factory calibration) stored in the EEPROM, and the percentage deviation of each feature value is calculated: Peak current deviation:

[0060] Ip,real: The peak current collected in real time, i.e., the maximum instantaneous value of the motor current during this self-test activation (unit: Ampere A). It reflects the maximum resistance point that the mechanism needs to overcome in the current state. For example, this value will increase when foam aging causes local jamming or increased friction.

[0061] Ip,base: Reference peak current, a standard value (unit: A) stored in the controller. This value is usually calibrated when the seat is brand new and represents the maximum resistance under normal conditions.

[0062] | Ip, real Ip,base|: The absolute difference between the real-time peak value and the reference peak value. The absolute value is used to eliminate the influence of direction. Only the magnitude of the deviation is considered (whether it is too large or too small, it is considered abnormal, but aging usually increases the current).

[0063] If ΔIp>20%, it indicates that the point of maximum resistance has increased significantly, which may indicate severe local wear or foreign object jamming.

[0064] Average current deviation:

[0065] Iavg,real: Real-time average current, which is the arithmetic mean of the current at all sampling points during this self-test activation process (unit: A). , where N is the number of sampling points. It reflects the overall resistance level; uneven aging of the foam or poor lubrication can lead to an increase in the average current.

[0066] Iavg,base: Baseline average current (unit: A), the average current value under normal conditions.

[0067] If ΔIavg > 15% (for example), it indicates an increase in overall friction, which may be caused by foam aging, mechanical wear, or lubrication failure.

[0068] Trip time deviation:

[0069] Treal: Real-time travel time, which is the time elapsed from the start of the motor to the seat reaching the fully open position during this self-test (unit: seconds). It is affected by motion resistance and motor load; increased resistance will lead to a decrease in speed and an increase in time.

[0070] Tbase: Baseline travel time (unit: seconds), the time required to complete the start-up process under normal conditions.

[0071] If ΔT>10% (for example), it indicates that the opening speed has slowed down, which may be caused by a general increase in resistance or a drop in power supply voltage (but the self-test is performed under the same voltage conditions, mainly due to mechanical resistance).

[0072] Current fluctuation deviation:

[0073] σreal: Real-time current fluctuation rate

[0074] The standard deviation of the current divided by the average current is used to measure the stability of the current. The greater the volatility, the more drastic the current fluctuations, which may reflect unstable operation of the mechanism, periodic jamming, or local unevenness in the foam.

[0075] σbase: Base current volatility, volatility under normal conditions.

[0076] The deviation in current fluctuation rate reflects changes in motion stability. If Δσ > 30% (for example), it indicates a significant increase in current fluctuation, which may suggest mechanical wear, intermittent interference from foreign objects, or damage to the foam surface.

[0077] In case of an abnormality, the dashboard will display "Seat Maintenance Reminder" or "System Fault, Please Check" and store the fault code; if normal, the temporary fault code will be cleared and the system will return to standby.

[0078] After reaching the open position, pause for 2 seconds, then close the seat at the same speed. The closing current curve can be recorded and feature values ​​extracted for auxiliary judgment, but for simplicity, the system can primarily judge based on the opening process. The closing process is still protected by the anti-pinch protection.

[0079] If seat pressure is suddenly detected during the self-test (when the user gets in the vehicle) or the side stand retracts, the self-test will immediately stop, the motor will stop and lock, ensuring safety. Reference curve management: The system can store the results of the last 10 self-tests for after-sales diagnostics. The reference curve can be recalibrated by pressing and holding a specific button combination to enter "learning mode" (e.g., after replacing a new seat).

[0080] The self-test is performed automatically only when the vehicle is started and unattended, without interfering with normal user operation. The self-test results are used for early warning and do not affect the basic functions of the system; however, if a serious abnormality is detected (such as excessive current that may damage the mechanism), the system will disable automatic tilting, prompting the user to operate manually and send the vehicle for repair.

[0081] Specifically, in practical applications, when the vehicle is parked, the system enters a low-power standby mode, monitoring only the side stand position sensor and the seat pressure sensor array. When the side stand position sensor detects that the side stand is down and the seat pressure sensor array detects no pressure signal for more than three seconds, the system determines that the vehicle is in a safe parking state, and the decision controller wakes up and enters a standby state. At this time, if the user issues a seat opening command via the car key button or mobile APP, the decision controller first performs a three-level safety verification: confirming that the side stand position sensor is down, confirming that the seat pressure sensor array has no pressure signal, and reading the motor Hall sensor via the CAN bus to confirm that the wheels are stationary. If all three conditions are met, the decision controller sends an unlock command to the electromagnetic lock, and then sends a forward rotation command to the motor drive module; if any condition is not met, the system refuses to execute and issues a warning sound via a buzzer, and the instrument panel displays a prohibition on operation prompt. After the motor starts, the decision controller monitors the motor speed and position in real time through the built-in Hall sensor, and reads the actual seat tilt angle through the linear Hall position sensor, using an S-curve acceleration and deceleration algorithm to control the motor operation, achieving smooth start and stop. During the flipping process, the decision controller continuously monitors the motor's operating current and compares it with a preset standard current curve. This standard current curve is recorded during the system's factory calibration phase and stored in the decision controller's non-volatile memory. When the instantaneous current value exceeds the set threshold and lasts for more than 50 milliseconds, it is determined to be an anti-pinch trigger. The decision controller immediately cuts off the motor power and controls the motor to rotate in the opposite direction for 200 milliseconds, causing the seat to retract and release the obstacle. It then stops and issues a fault warning. When the linear Hall position sensor detects that the seat has reached the fully open position and the micro-limit switch is triggered, the decision controller cuts off the motor power and activates the electromagnetic lock to lock the seat in the open state. The seat closing process is similar. After receiving the closing command, the decision controller performs a safety verification again. After successful verification, the electromagnetic lock is released, the motor rotates in the opposite direction to drive the seat back down. When it approaches the fully closed position, the decision controller actively reduces the motor speed to achieve a buffered closure. When the micro-limit switch is triggered and the linear Hall position sensor reports a zero position, the decision controller stops the motor and relocks the electromagnetic lock. When the vehicle enters riding mode, i.e., the motor Hall sensor detects wheel rotation or the seat pressure sensor array detects pressure and the side stand is retracted, the decision controller immediately enters the forced locking mode, cuts off the motor drive circuit and short-circuits the motor windings, and locks the electromagnetic lock to ensure that the seat cannot be opened accidentally under any circumstances.

[0082] Each time the vehicle is powered on and started, if the decision controller detects that the vehicle is in a parked state and the seat pressure sensor array confirms that no one is sitting, the system automatically executes a self-test flipping procedure.

[0083] The self-test flipping procedure includes the following steps: First, the decision controller records the current ambient temperature, as the damping characteristics of the foam material are temperature sensitive; second, the decision controller controls the motor to drive the seat to flip from a fully closed position to a fully open position, and then back to a fully closed position, completing a full cycle; during this process, the decision controller records the change curve of the motor operating current over time at a millisecond sampling frequency, and compares and analyzes this real-time current curve with the reference current curve stored in the controller. The reference current curve is the calibration curve measured by the system under standard ambient temperature before the vehicle leaves the factory; the decision controller extracts the feature values ​​of the real-time current curve, including peak current, average current, and stroke. The system measures time and current fluctuations; it compares the characteristic values ​​with the corresponding characteristic values ​​of the baseline curve and calculates the percentage deviation. If the percentage deviation exceeds the first set threshold of 15%, it is determined to be a slight abnormality in foam resistance, and the system prompts the user on the dashboard, "Increased seat resistance, maintenance recommended." If the percentage deviation exceeds the second set threshold of 20%, it is determined to be a severe abnormality in foam resistance, which may indicate foam aging and cracking, foreign object jamming, or mechanical failure. The system displays "Seat system failure, please repair immediately" on the dashboard and disables the automatic flipping function, allowing only manual operation. If the percentage deviation is within the normal range, the self-test passes, the dashboard does not prompt, and the system records the self-test data for subsequent trend analysis. In addition, the decision controller stores the characteristic values ​​of each self-test in the historical database to establish a trend curve of foam resistance change. When the trend curve shows that the resistance value increases monotonically with usage time and approaches the first set threshold, the system issues an early warning prompt to achieve predictive maintenance.

[0084] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0085] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for intelligent control of an electric bicycle with an automatically flipping seat made of foam material, characterized in that, Includes the following steps: Real-time collection of vehicle status information, including side stand status, rider seating status, seat tilt angle, and drive motor operating current; When a seat open or close command is received, a safety verification is performed; When the safety verification is passed, the control drive motor drives the seat to flip according to the preset S-curve acceleration and deceleration algorithm; During the seat rotation process, an anti-pinch detection is performed to stop the rotation if an object is caught.

2. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 1, characterized in that, The safety verification includes: verifying that the side support is in the lowered state, verifying that the seat cushion is in a pressure-free state, and verifying that the vehicle is stationary.

3. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 1, characterized in that, The anti-pinch judgment includes: Real-time monitoring of motor operating current; When the instantaneous current value exceeds the preset anti-pinch threshold and the duration exceeds the preset time threshold, it is determined that the anti-pinch is triggered. When the anti-pinch function is triggered, the power supply to the drive motor is cut off and the motor is controlled to rotate in the opposite direction by a preset angle before stopping.

4. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 1, characterized in that, Also includes: When preset conditions are met, a self-check is performed: The self-test steps include: The drive motor is controlled to rotate the seat at a speed lower than normal operating speed, following a preset S-curve acceleration and deceleration algorithm. Record the current curve of the drive motor operating current changing over time at a preset sampling frequency; Extract at least one feature value from the current curve; The extracted feature values ​​are compared with preset benchmark feature values, and the health status of the seat system is evaluated based on the comparison results.

5. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 4, characterized in that, The characteristic value includes at least one of peak current, average current, travel time, and current fluctuation rate; The peak current is the maximum instantaneous current value in the current curve, reflecting the point of maximum resistance during the seat flipping process; The average current is the arithmetic mean of the current values ​​at each sampling point in the current curve, reflecting the overall resistance level; The travel time is the time from the start of the drive motor to the time the seat reaches the target position, reflecting the smoothness of the movement; The current fluctuation rate is the ratio of the standard deviation of the current curve to the average current, reflecting the smoothness of the motion.

6. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 5, characterized in that, The step of comparing the extracted feature values ​​with preset benchmark feature values ​​and evaluating the health status of the seat system based on the comparison results includes: Calculate the percentage deviation between the real-time feature value and the benchmark feature value; The deviation percentage is compared with at least one preset threshold; When the deviation percentage exceeds the first preset threshold, a maintenance reminder message is output; When the deviation percentage exceeds the second preset threshold, a fault alarm message is output and the automatic flip function is disabled, wherein the second preset threshold is greater than the first preset threshold.

7. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 5, characterized in that, It also includes trend analysis steps: Store the extracted feature values ​​in a historical database and establish a trend curve of feature values ​​changing over time. When the trend curve shows that the feature value is monotonically increasing and approaching the preset threshold, a predictive maintenance prompt is output in advance.

8. The intelligent control method for automatic seat flipping of an electric bicycle made of foam material according to claim 1, characterized in that, Also includes: When the vehicle is detected to be in motion, the drive circuit of the drive motor is cut off and the motor windings are short-circuited to generate braking torque, while the electromagnetic locking mechanism is locked.

9. A smart control system for an electric bicycle with an automatically flipping seat made of foam material, characterized in that, include: The sensing module includes a side stand position sensor for detecting the side stand status, a seat pressure sensor array for detecting the rider's seated status, a seat position sensor for detecting the seat tilt angle, and a current detection module for sampling the operating current of the drive motor. The decision controller is electrically connected to each sensor of the perception module, and is configured to generate motion control commands based on the vehicle status information and user commands collected by the perception module, and execute the method described in any one of claims 1 to 8. The execution module, electrically connected to the decision controller, includes a drive motor for driving the seat to flip and an electromagnetic locking mechanism for locking the seat position.

10. The intelligent control system for automatic flipping seat of an electric bicycle made of foam material according to claim 9, characterized in that, The seat cushion pressure sensor array is a thin-film pressure sensor array, which is laid under the high-density transition layer between the foam material and the seat base. The seat position sensor includes a linear Hall element for continuously detecting the seat tilt angle and a micro-limit switch for redundancy confirmation of the seat position.

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