Adaptive riding mode switching method and system for electric two-wheeler

Abstract

The embodiment of the application discloses a kind of electric two-wheeled vehicle adaptive riding mode switching method and system, it is related to electric two-wheeled vehicle control technical field, the method includes: obtaining the multidimensional input information of electric two-wheeled vehicle, current riding state is identified based on the multidimensional input information, and the riding state is mapped as candidate target riding mode;According to the preset gating condition, it is judged whether to allow switching to the candidate target riding mode;If switching is allowed and after confirmation by the anti-shake retention mechanism, mode switching is executed and control parameters are output shaped to smooth transition;After switching is completed, the effect verification is carried out to vehicle dynamic response, if it is detected that dynamic response is abnormal, then trigger safety rollback;Through the complete closed-loop control, while improving the automation level of electric two-wheeled vehicle riding mode adaptive switching, the riding safety and comfort are also considered.

Description

Technical Field

[0001] This invention relates to the field of electric two-wheeled vehicle control technology, and in particular to an adaptive riding mode switching method and system for electric two-wheeled vehicles. Background Technology

[0002] Electric two-wheelers, as a convenient and environmentally friendly personal transportation tool, have been widely used in various scenarios such as daily commuting, short-distance logistics, and leisure riding. To adapt to different riding conditions and user preferences, electric two-wheelers are usually equipped with multiple riding modes, such as economy mode, standard mode, and sport mode, to adjust control strategies such as power output characteristics, energy recovery intensity, and throttle response sensitivity.

[0003] Currently, switching riding modes mainly relies on active user operation, such as manual selection via physical buttons, instrument menus, or mobile applications. Some solutions also propose automatic switching mechanisms, such as triggering automatic mode transitions based on changes in a single parameter like battery state of charge, vehicle speed, or throttle opening.

[0004] However, in actual riding, electric two-wheelers face complex and varied road conditions, including but not limited to frequent starts and stops on urban roads, hill climbs, slippery surfaces, and cornering. Under these conditions, the vehicle requires a high degree of stability in power output and timely response. How to achieve a reasonable match between riding modes under different conditions, and to smoothly transition between modes while ensuring safety and comfort, remains a problem to be solved in this field. Summary of the Invention

[0005] The main objective of this invention is to provide an adaptive riding mode switching method and system for electric two-wheeled vehicles, aiming to solve the problems of unsafe timing and uneven process when switching riding modes in electric two-wheeled vehicles.

[0006] To achieve the above objectives, the first aspect of this application provides a method for adaptive riding mode switching of an electric two-wheeled vehicle, comprising: The multidimensional input information of the electric two-wheeler is obtained, including at least vehicle dynamics information, rider operation information, load information, road surface and environment information, and energy status information. The current riding state is identified based on the multidimensional input information, and the riding state is mapped to a candidate target riding mode. Determine whether to allow switching to the candidate target riding mode based on preset gating conditions; If switching is permitted and confirmed by the anti-shake holding mechanism, the mode switch is executed and the control parameters are output shaped for a smooth transition. After the switch is completed, the vehicle's dynamic response is verified. If an abnormal dynamic response is detected, a safety rollback is triggered, restoring the riding mode before the switch or the default safety mode.

[0007] A second aspect of this application provides an adaptive riding mode switching system for an electric two-wheeled vehicle, comprising: The status acquisition module is used to acquire multi-dimensional input information of the electric two-wheeler. The multi-dimensional input information includes at least vehicle dynamics information, rider operation information, load information, road surface and environment information, and energy status information. The state recognition module is used to identify the current riding state based on the multi-dimensional input information and map the riding state to a candidate target riding mode; The switching gating module is used to determine whether to allow switching to the candidate target riding mode based on preset gating conditions; The mode switching execution module is used to perform mode switching if switching is allowed and confirmed by the anti-jitter holding mechanism; the output shaping module is used to shape the control parameters for a smooth transition. The effect verification module is used to verify the effect of the vehicle's dynamic response after the switch is completed; The safety rollback module is used to trigger a safety rollback and restore the riding mode to the previous mode or the default safety mode if the effect verification module detects an abnormal dynamic response.

[0008] A third aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the first aspects.

[0009] This application has at least the following beneficial effects: After identifying candidate target patterns, a safety check is first performed using preset gating conditions. Switching is only allowed when the safety conditions are met, which avoids sudden mode changes in dangerous conditions such as turning, low-adhesion road surfaces, and braking transients, and significantly reduces the risk of vehicle instability caused by sudden power changes.

[0010] During mode switching, an output shaping mechanism is introduced to gradually process the target torque of the motor, the energy recovery intensity, and the throttle response curve. This eliminates the physical shock caused by the instantaneous change of parameters in traditional solutions, allowing for a nearly imperceptible mode transition and improving riding comfort.

[0011] After the switch is completed, an effect verification window is set up to monitor the vehicle's dynamic response in real time. Once an abnormality is detected, a safety rollback is automatically triggered to restore the vehicle to the mode before the switch or the default safety mode, providing the system with automatic error correction and degradation protection capabilities.

[0012] By identifying the current riding status through multi-dimensional input information, and then mapping the status to the target riding mode, the mode switching is more in line with the actual riding scenario. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] in: Figure 1 This is a schematic diagram of the structure of an adaptive riding mode switching method for an electric two-wheeled vehicle provided in an embodiment of this application; Figure 2 This is a schematic diagram of a cycling state recognition process provided in an embodiment of this application; Figure 3 This is a schematic diagram of a switching gating and anti-shake hold process provided in an embodiment of this application; Figure 4 This application provides a schematic diagram of an execution and output shaping process. Figure 5 A schematic diagram of an effect verification and security rollback process provided for an embodiment of this application; Figure 6 A schematic diagram of the overall system architecture provided in this application embodiment; Figure 7 This is a schematic diagram of the structure of an adaptive riding mode switching system for an electric two-wheeled vehicle provided in an embodiment of this application. Detailed Implementation

[0015] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0016] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0017] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0018] The embodiments of this application are described below with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart illustrating an adaptive riding mode switching method for an electric two-wheeled vehicle, as provided in an embodiment of this application. Figure 1 As shown, the method includes: 101. Obtain multi-dimensional input information of the electric two-wheeler. The multi-dimensional input information includes at least vehicle dynamics information, rider operation information, load information, road surface and environment information, and energy status information.

[0020] The method in this application embodiment can be implemented based on a vehicle controller, specifically an on-board control unit running on an electric two-wheeler or a decision / execution entity in a control architecture.

[0021] In one alternative implementation, the aforementioned vehicle dynamics information includes vehicle speed, longitudinal acceleration, yaw rate, body roll angle, current drive torque, and motor speed. The rider operation information mentioned above includes throttle opening, throttle change rate, brake input, recent operation frequency, and number of rapid accelerations / decelerations. The above load information includes the estimated gross vehicle weight, load rating, or rear seat additional load status; the above road and environmental information includes slope, adhesion estimate, road surface smoothness, temperature, and wet skid risk signs. The aforementioned energy status information includes battery state of charge (SOC), battery temperature, motor temperature, and thermal protection status.

[0022] The aforementioned information can be acquired in real time through onboard sensors (such as Hall effect sensors and current sensors), inertial measurement units (IMUs), battery management systems (BMS), and the CAN bus. After acquisition, preprocessing operations such as filtering, de-jittering, and time alignment can be performed on the raw data to improve the accuracy of subsequent identification.

[0023] The inertial measurement unit (IMU) in this embodiment is mainly used to acquire information on vehicle acceleration, angular velocity, and attitude changes.

[0024] 102. Based on the above multi-dimensional input information, identify the current riding state and map the above riding state to candidate target riding modes.

[0025] The riding states mentioned in this application mainly refer to the state labels obtained by comprehensively identifying the current operating conditions of the vehicle, the rider's operating characteristics, and the road environment. They are a classification description of the current operating conditions of the vehicle. The riding states involved in this application include at least the smooth start state, stable cruising state, dynamic response state, climbing load state, and low adhesion risk state, etc., and are not limited here.

[0026] The riding modes mentioned in the embodiments of this application refer to a set of vehicle control strategies for electric two-wheeled vehicles in terms of power output, energy recovery, torque response, and speed response. The riding modes involved in this application include at least economy mode, standard mode, sport mode, and conservative mode, but are not limited to these.

[0027] Specifically, the aforementioned smooth start-up state in this application refers to the low-speed initial driving phase during which the vehicle accelerates from a standstill to a stable speed. The aforementioned stable cruise state refers to the straight-line driving phase in which the vehicle travels at a relatively constant speed and maintains a stable attitude; The aforementioned dynamic response state refers to the stage of intense vehicle handling, such as high yaw rate, large angle turning, or rapid acceleration and deceleration. The aforementioned hill-climbing load state refers to the stage where the vehicle is traveling on a sloped road and under a large load; The aforementioned low-adhesion-risk state refers to a driving stage where the road surface adhesion coefficient is lower than a preset threshold, posing a risk of slippage.

[0028] The aforementioned energy-saving driving range refers to the energy-saving phase when the battery's state of charge is below a preset threshold and the vehicle is traveling at a constant speed.

[0029] Accordingly, the aforementioned economic mode in this application refers to a riding mode with the primary goal of reducing energy consumption, which typically limits maximum torque output and increases energy recovery intensity; The aforementioned standard mode refers to the default riding mode that strikes a balance between power performance and energy consumption; The aforementioned sport modes refer to riding modes that primarily aim to improve power response, typically increasing the upper limit of torque and reducing the intensity of energy recovery; The aforementioned conservative mode refers to a safe riding mode used in low-adhesion or high-risk conditions, which typically limits the rate of torque change and employs a gentle power response characteristic.

[0030] Figure 2 This is a schematic diagram of a cycling state recognition process provided in an embodiment of this application. Figure 2 As shown, the domain controller first acquires IMU data and CAN bus data, and preprocesses the acquired data through filtering, debouncing, and time alignment. Then, based on the preprocessed data, it constructs state features, which include at least vehicle speed features, lean angle features, yaw rate features, drive torque features, braking state features, road slope estimation features, and historical riding style features. Based on these state features, the domain controller identifies the current riding state of the vehicle through a rule engine, scoring model, or classification model. These riding states include at least a smooth start state, a stable cruise state, a dynamic response state, a climbing load state, and a low adhesion risk state. After state identification, the domain controller generates candidate target riding modes based on the current riding state, providing input for subsequent switching gating and mode switching execution.

[0031] Specifically, firstly, based on the acquired multidimensional input information, a feature vector for state recognition can be constructed. This feature vector includes at least vehicle speed features, tilt angle features, yaw rate features, driving torque features, braking state features, throttle opening rate of change features, road slope estimation features, and historical riding style features.

[0032] Based on the aforementioned feature vectors, the current riding state of the vehicle is identified using a pre-defined recognition model. This model can be a rule engine, a weighted scoring model, a decision tree model, a neural network classification model, or any combination thereof. The recognition result not only outputs the current riding state label but also simultaneously outputs the pattern confidence level corresponding to that state, which is used as a reference for subsequent switching decisions.

[0033] The pattern confidence level mentioned in the embodiments of this application refers to the degree of credibility of the current recognition result corresponding to a certain riding state or riding mode, which is used to participate in the switching determination and is usually expressed in numerical form.

[0034] After identifying the current riding state, it can be converted into a candidate target riding mode according to a preset mapping relationship. This mapping relationship can be set and adjusted as needed. In one implementation, the above mapping relationship is as follows: When a smooth start-up state is identified, it is preferentially mapped to either the standard mode or the conservative mode. When the mode is identified as stable cruise mode or energy-saving mode, it is preferentially mapped to economic mode. When identified as a dynamic response state, it is preferentially mapped to a motion pattern; When identified as a ramp load state, it is preferentially mapped to a high torque mode or a motion mode limited sub-mode; When identified as a low-attachment-risk state, it is preferentially mapped to a conservative mode.

[0035] By adopting the strategy of first identifying the state and then mapping it to the mode, we can effectively avoid the misjudgment problem caused by directly switching modes based on a single parameter, and improve the accuracy and interpretability of mode switching judgment.

[0036] 103. Determine whether to allow switching to the above candidate target riding modes based on preset gating conditions.

[0037] In this embodiment of the application, after obtaining the candidate target riding mode, the switching is not performed immediately, but a switching gating determination is performed first.

[0038] The switching gating mentioned in this application refers to a constraint mechanism that allows riding mode switching only when preset safety conditions are met. The preset gating conditions in this application refer to one or more sets of safety judgment rules pre-set by the system to determine whether "the current moment is suitable for executing riding mode switching." These conditions are mainly designed around the driving stability, posture safety, and control continuity of the electric two-wheeler at the moment of switching, and are not limited here.

[0039] In one alternative implementation, the gating conditions include at least one or more of the following: vehicle speed range, torque change rate, safe range of yaw rate and vehicle tilt angle, braking transient, road adhesion risk, and the shortest holding time of the current mode, and switching is allowed only when the above gating conditions are continuously met for a preset period.

[0040] Further optionally, the aforementioned road surface adhesion risk is estimated based on a comprehensive assessment of road surface smoothness, temperature, and slipperiness risk indicators; and / or, the aforementioned vehicle tilt angle and yaw rate are obtained through a six-axis inertial measurement unit (IMU).

[0041] For example, the specific criteria for judgment include: Is the current vehicle speed within the preset allowed switching range? Is the current longitudinal torque change rate less than a preset threshold? Are the yaw rate and vehicle tilt angle within the preset safety range? Is the vehicle in a braking transient or a rapid acceleration transient? Is the risk of road surface adhesion higher than the set threshold? Does it meet the minimum hold time for the current mode?

[0042] If any gating condition is not met, the system will not perform a mode switch, will maintain the current riding mode, and will enter a waiting or observation state. Only when all gating conditions are met, and a preset number of sampling periods are satisfied consecutively, will subsequent mode switching procedures be allowed. This gating mechanism effectively prevents sudden mode changes under dangerous conditions such as turning, low-traction surfaces, and excessive braking, ensuring riding safety.

[0043] 104. If switching is allowed and confirmed by the anti-jitter holding mechanism, perform mode switching and output shaping of control parameters for a smooth transition.

[0044] After the gating determination in step 103 allows the switching, the system further performs a confirmation of the anti-shake holding mechanism. In one specific implementation, the above-mentioned anti-shake holding mechanism includes: Each riding mode has a minimum holding time T_hold, during which switching is prohibited; Different thresholds are set for entering and exiting the target mode to form a hysteresis interval; The actual switching is only allowed when the state recognition result continuously meets the target mode condition for a preset number of sampling periods; When the state recognition result meets the switching condition only once, the system only updates the candidate mode and does not perform an actual switch.

[0045] This application, through the aforementioned anti-shake holding mechanism, can effectively suppress mode switching caused by short-term road condition disturbances, short-term throttle fluctuations, or slight attitude changes.

[0046] The anti-shake hold time involved in the embodiments of this application refers to the time window during which switching modes is prohibited again in the shortest possible time after switching modes, which is used to suppress frequent mode jumps under boundary conditions.

[0047] The hysteresis threshold in this application embodiment refers to the range formed by different judgment thresholds set for entering the target mode and exiting the target mode, which is used to reduce the back-and-forth switching of modes caused by critical fluctuations.

[0048] Figure 3 This is a schematic diagram of a switching gating and anti-shake holding process provided in an embodiment of this application.

[0049] like Figure 3The diagram illustrates the gating and anti-shake hold process for cycling mode switching. Specifically, it includes: inputting the current cycling state and candidate target modes, and checking the switching gating conditions accordingly. These conditions include at least the speed range, braking state, lean angle threshold, gradient threshold, speed limit threshold, low traction risk, and minimum hold time. If the gating conditions are not met, the current mode is maintained; if the gating conditions are met, the anti-shake hold determination phase begins, timing the duration of continuously meeting the switching conditions. When the duration of continuously meeting the switching conditions reaches a preset time window, mode switching is allowed; if the time window is not reached, the process remains in the anti-shake hold determination phase until the timing is met. This process, through a dual mechanism of gating screening and anti-shake timing, ensures the safety and stability of mode switching.

[0050] After the anti-shake holding mechanism confirms that the switching is allowed, the system can perform the riding mode switch, and the output shaping module will smooth the switching process.

[0051] Output shaping in this embodiment refers to the process of gradually transitioning control quantities such as motor target torque, energy recovery intensity, and throttle response slope after mode switching occurs, including smooth changes within a time window according to a preset slope, piecewise function, or lookup table method.

[0052] In one alternative implementation, the output shaping includes gradually varying at least one of the motor target torque, energy recovery intensity, and throttle response curves according to a preset slope or time window, and limiting their maximum rate of change.

[0053] For example, when switching from Eco mode to Sport mode, the vehicle does not immediately switch to a high-response curve. Instead, it gradually increases the torque response coefficient over a preset time window (e.g., 1.2 seconds) while gradually decreasing the energy recovery intensity over another time window (e.g., 0.8 seconds) to avoid the rider experiencing abrupt power jumps or drag. After the mode transition is complete, the instrument panel or HMI updates the current mode display.

[0054] Figure 4 This is a schematic diagram illustrating an execution and output shaping process provided in an embodiment of this application. Figure 4 As shown, once mode switching is permitted, the domain controller generates a parameter set corresponding to the target mode, including the target torque limit, target energy recovery intensity, target throttle response curve, and target power output constraint, and sends this set to the vehicle controller via the CAN bus. The vehicle controller performs output shaping based on these target parameters, that is, it gradually adjusts the drive torque, energy recovery intensity, and response curve according to a preset slope, thereby avoiding abrupt power jumps or drag during mode switching. After the mode transition is complete, the instrument cluster or HMI updates the current mode display.

[0055] 105. After the switch is completed, verify the effect of the vehicle's dynamic response. If an abnormal dynamic response is detected, trigger a safety rollback and restore the riding mode before the switch or the default safety mode.

[0056] Specifically, after the mode switch is completed, the system enters the effect verification phase. In particular, within the preset effect verification window, the system can continuously collect dynamic data of the vehicle after the switch. The dynamic data can include at least changes in vehicle speed, yaw rate, tilt angle, drive torque response, and braking and energy recovery response.

[0057] Based on the aforementioned dynamic data, the switching effect index is calculated and compared with preset safety thresholds. These safety thresholds may include at least yaw rate thresholds, tilt angle thresholds, and torque response deviation thresholds. If the vehicle's dynamic response after switching meets stability and safety requirements, the target riding mode remains unchanged; if it does not meet the preset requirements, a safety revert logic is triggered.

[0058] Optionally, the above-mentioned security rollback can revert to the previous mode, the default mode, or a dedicated degradation mode for different anomaly types.

[0059] In one optional implementation, the above-mentioned security rollback adopts a tiered strategy, specifically including: If the verification fails once in the verification window after switching, it will revert to the riding mode before switching. If the verification fails twice in a row, the system will enter the default security mode. If a low adhesion risk signal or sensor malfunction is detected, a forced switch to conservative mode will be initiated.

[0060] In one optional implementation, the above-mentioned effect verification includes collecting at least one of the following verification indicators within a preset verification window: The rate of change of longitudinal acceleration or the amplitude of longitudinal acceleration fluctuation; the change in yaw rate or the change in tilt angle; the deviation between the rider's throttle input and the output torque response or the response delay time; the trigger status of traction control, overcurrent protection, or thermal protection; the rate of change of energy consumption per unit time or the time required for the torque response to reach the target value.

[0061] Specifically, the effect verification in this application embodiment includes collecting at least one of the following verification indicators within a preset verification window and comparing them with their respective preset thresholds: If the rate of change of longitudinal acceleration is greater than the preset rate of change threshold, or the amplitude of longitudinal acceleration fluctuation is greater than the preset fluctuation threshold, the vehicle dynamic response after switching is determined to be abnormal. If the change in yaw rate is greater than the preset yaw rate threshold, or the change in tilt angle is greater than the preset tilt angle threshold, the vehicle dynamic response after switching is determined to be abnormal. If the deviation between the throttle input and the output torque response is greater than a preset deviation threshold, or the delay time of the torque response relative to the throttle input is greater than a preset delay threshold, then the vehicle dynamic response after switching is determined to be abnormal. If the traction control system, overcurrent protection mechanism, or thermal protection mechanism is triggered after switching, the vehicle's dynamic response is determined to be abnormal after switching. If the rate of change of energy consumption per unit time is greater than the preset energy consumption change rate threshold, or the time required for the torque response to reach the target value is greater than the preset response time threshold, then the vehicle dynamic response after switching is determined to be abnormal.

[0062] Optionally, the above verification indicators can be used individually or in combination. When multiple verification methods are used, a weighted scoring or logical AND / OR method is employed for comprehensive judgment, and this application embodiment does not impose any restrictions on this.

[0063] Figure 5 This is a schematic diagram illustrating an effect verification and security rollback process provided for an embodiment of this application. For example... Figure 5 As shown, after the mode switch is completed, the domain controller enters the effect verification window, continuously collecting the vehicle's dynamic data after the switch, including changes in vehicle speed, yaw rate, tilt angle, drive torque response, and braking and energy recovery response, and calculates the switching effect index accordingly. If the vehicle's dynamic response after the switch meets the stability and safety requirements, the target mode is maintained; if it does not meet the preset requirements, the safety rollback logic is triggered, restoring the previous stable mode, and entering the conservative mode if necessary to ensure that the vehicle is always under control.

[0064] The method in this embodiment of the application performs layered identification of vehicle operating conditions, rider operating habits and road conditions. After identifying a suitable riding state, it does not immediately switch modes, but first performs a switching gating judgment. The mode switch is only executed when the gating conditions are met, and the torque output and energy recovery are shaped during the switching process. After the switch is completed, the effect is further verified through dynamic response characteristics. If an unexpected response is detected, a safety backoff mechanism is triggered, thereby improving the level of automation while taking into account riding safety and comfort.

[0065] To further illustrate the implementation process of this application, a specific working example is provided below. The specific numerical values ​​involved do not constitute a limitation on the scope of protection of this application.

[0066] Assume the vehicle is currently traveling at a stable speed of 35 km / h, with a body tilt angle of 2.5° and a yaw rate of 0.08 rad / s. It is not currently braking, and the road surface has a certain gradient. Based on the multi-dimensional input information obtained in step 101, the domain controller identifies in step 102 that the vehicle is currently in a climbing load state, the current mode is standard mode, and the candidate target mode is sport mode.

[0067] In step 103, the domain controller checks the gating conditions: the current vehicle speed is within the permissible switching range, the torque change rate is less than the threshold, the yaw rate and tilt angle are within the safe range, the vehicle is not in a braking transient, the road adhesion risk is below the threshold, and the minimum hold time of 10 seconds since the last mode switch has been exceeded. All gating conditions are met.

[0068] In step 104, the hill-climbing load state is maintained continuously for 3 seconds to meet the continuous sampling period requirement of the anti-shake holding mechanism. The domain controller sends the target mode identifier and parameter set to the vehicle controller via the CAN bus. The vehicle controller completes the gradual change of the upper limit of drive torque from 55 N·m to 68 N·m within 1.2 seconds, and the gradual change of energy recovery intensity from 18% to 10% within 0.8 seconds.

[0069] In step 105, after the mode switch is completed, the domain controller enters a 2-second effect verification window. If, during this window, the yaw rate suddenly increases beyond a preset yaw rate threshold, or the tilt angle exceeds a preset tilt angle threshold, the domain controller determines that the current mode switch does not meet safety requirements and triggers a rollback logic to restore the vehicle from Sport mode to Standard mode. If a low-adhesion risk signal is detected at the same time, the controller further switches to Conservative mode to ensure that the vehicle remains under control.

[0070] The method in this application embodiment improves the accuracy and interpretability of mode switching determination by first identifying the riding state and then performing mode mapping and switching gating, compared to directly switching the riding mode based on a single condition.

[0071] The method in this application embodiment, by switching gating, anti-shake holding and hysteresis mechanisms, avoids the two-wheeled vehicle from frequently switching riding modes under boundary conditions, thereby improving the overall vehicle control stability and riding comfort.

[0072] The method in this embodiment reduces torque abrupt changes and tactile shock during mode switching through an output shaping mechanism, which helps to ensure the smoothness of the mode switching process.

[0073] The method in this application embodiment constructs a complete closed loop of "identification-gating-switching-verification-rollback" through effect verification and safety rollback mechanism after switching, so that adaptive mode switching has safety redundancy capability.

[0074] The method in this application fully considers the specific characteristics of two-wheeled vehicles in scenarios such as tilt angle, yaw, load, and low adhesion. It differs from the conventional mode recommendation logic for four-wheeled vehicles or general motor equipment and is more suitable for electric two-wheeled vehicle scenarios.

[0075] To more clearly illustrate the implementation of the method in the embodiments of this application, the following description is provided in conjunction with the system architecture and sub-step flowchart.

[0076] Figure 6 This is a schematic diagram of the overall system architecture provided in an embodiment of this application.

[0077] like Figure 6 As shown, the system includes multiple input sources, a core processing module, and execution and feedback terminals. Input sources include a six-axis inertial measurement unit (IMU) providing three-axis acceleration and three-axis angular velocity data; a CAN bus that aggregates operational data (such as vehicle speed, drive / braking status, battery status, and motor status); user input of intent via an interactive interface (such as comfort / sport / personalization preferences); and historical operational data (such as throttle changes, braking frequency, and long-term operating conditions) also serving as auxiliary input.

[0078] The core processing module is the domain controller, whose functions include state recognition, handover gating, anti-shake maintenance, target pattern generation, and effect verification. The domain controller receives the above multi-source inputs, makes a comprehensive judgment, and outputs a decision command.

[0079] The above output terminals interact with the vehicle controller, which then distributes instructions to each execution unit: the motor controller is responsible for power output adjustment; the energy recovery strategy adjustment module controls the intensity of braking energy recovery; the instrument / HMI is responsible for displaying the current mode; and the drive torque execution module and the energy recovery strategy execution module respectively implement the power and energy management strategies.

[0080] Specifically, the adaptive riding mode switching system in this application uses a domain controller as the upper-level decision-making unit. The domain controller receives three-axis acceleration and three-axis angular velocity information output by the six-axis inertial measurement unit (IMU), and simultaneously reads vehicle operating data such as vehicle speed, drive torque, braking status, battery status, and motor status via the CAN bus. It then combines user input and historical riding data to complete riding state recognition, switching gating, anti-shake holding, target mode generation, and effect verification. After generating the target mode, the domain controller sends a mode switching request or target parameters to the vehicle controller via the CAN bus. The vehicle controller further coordinates the motor controller and energy recovery control logic to execute gradual changes in drive torque and energy recovery intensity, and sends the execution feedback data back to the domain controller, forming a complete closed-loop control architecture.

[0081] Based on the aforementioned method embodiments, this application also provides an adaptive riding mode switching system for electric two-wheeled vehicles.

[0082] Figure 7 This is a schematic diagram of the structure of an adaptive riding mode switching system for an electric two-wheeled vehicle provided in an embodiment of this application. Figure 7 As shown, the electric two-wheeler adaptive riding mode switching system 700 includes: The status acquisition module 710 is used to acquire multi-dimensional input information of the electric two-wheeler. The multi-dimensional input information includes at least vehicle dynamics information, rider operation information, load information, road surface and environment information, and energy status information. The state recognition module 720 is used to recognize the current riding state based on the multi-dimensional input information and map the riding state to a candidate target riding mode; The switching gating module 730 is used to determine whether switching to the candidate target riding mode is allowed based on preset gating conditions; The mode switching execution module 740 is used to perform mode switching if switching is allowed and confirmed by the anti-jitter holding mechanism; the output shaping module is used to shape the control parameters for a smooth transition. The effect verification module 750 is used to verify the effect of the vehicle's dynamic response after the switch is completed; The safety rollback module 760 is used to trigger a safety rollback and restore the riding mode or default safety mode before switching if the effect verification module 750 detects an abnormal dynamic response.

[0083] In this application, an adaptive riding mode switching method for an electric two-wheeled vehicle can be provided by... Figure 7 The execution of each module of the system in the illustrated embodiment will not be described in detail here.

[0084] Based on the foregoing method embodiments, this application also provides a computer-readable storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the steps of any of the adaptive riding mode switching methods for electric two-wheeled vehicles of this application, which will not be repeated here.

[0085] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

Claims

1. A method for adaptive riding mode switching of an electric two-wheeled vehicle, characterized in that, The method includes: The multidimensional input information of the electric two-wheeler is obtained, including at least vehicle dynamics information, rider operation information, load information, road surface and environment information, and energy status information. The current riding state is identified based on the multidimensional input information, and the riding state is mapped to a candidate target riding mode. Determine whether to allow switching to the candidate target riding mode based on preset gating conditions; If switching is permitted and confirmed by the anti-shake holding mechanism, the mode switch is executed and the control parameters are output shaped for a smooth transition. After the switch is completed, the vehicle's dynamic response is verified. If an abnormal dynamic response is detected, a safety rollback is triggered, restoring the riding mode before the switch or the default safety mode.

2. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The gating conditions include at least one or more of the following: vehicle speed range, torque change rate, safe range of yaw rate and vehicle tilt angle, braking transient, road adhesion risk, and the shortest holding time of the current mode, and switching is allowed only when the gating conditions are continuously met for a preset period.

3. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The output shaping includes gradually changing at least one of the motor target torque, energy recovery intensity, and throttle response curve according to a preset slope or time window, and limiting its maximum rate of change.

4. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The security rollback adopts a tiered strategy, specifically including: If the verification fails once in the verification window after switching, it will revert to the riding mode before switching. If the verification fails twice in a row, the system will enter the default security mode. If a low adhesion risk signal or sensor malfunction is detected, a forced switch to conservative mode will be initiated.

5. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The method further includes: When identifying the current riding state, the riding state is further divided into at least the starting state, steady-state cruise state, aggressive driving state, heavy-load climbing state, low-adhesion-risk state, and energy-saving range state, and the corresponding mode confidence is output.

6. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The anti-shake holding mechanism includes setting a minimum holding time for each riding mode, and / or setting different recognition thresholds for entering and exiting the target mode to form a hysteresis interval.

7. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The vehicle dynamics information includes vehicle speed, longitudinal acceleration, yaw rate, body roll angle, current drive torque, and motor speed; The rider's operation information includes throttle opening, throttle change rate, braking input, recent operation frequency, and number of rapid accelerations / decelerations. The load information includes the estimated total mass of the vehicle, load rating, or rear seat additional load status; the road surface and environmental information includes slope, adhesion estimate, road surface smoothness, temperature, and slippery risk signs; The energy status information includes battery state of charge (SOC), battery temperature, motor temperature, and thermal protection status.

8. The adaptive riding mode switching method for an electric two-wheeled vehicle according to claim 1, characterized in that, The effect verification includes collecting at least one of the following verification indicators within a preset verification window: The rate of change of longitudinal acceleration or the amplitude of longitudinal acceleration fluctuation; the change in yaw rate or the change in tilt angle; the deviation between the rider's throttle input and the output torque response or the response delay time; the trigger status of traction control, overcurrent protection, or thermal protection; the rate of change of energy consumption per unit time or the time required for the torque response to reach the target value.

9. An adaptive riding mode switching system for an electric two-wheeled vehicle, characterized in that, include: The status acquisition module is used to acquire multi-dimensional input information of the electric two-wheeler. The multi-dimensional input information includes at least vehicle dynamics information, rider operation information, load information, road surface and environment information, and energy status information. The state recognition module is used to identify the current riding state based on the multi-dimensional input information and map the riding state to a candidate target riding mode; The switching gating module is used to determine whether to allow switching to the candidate target riding mode based on preset gating conditions; The mode switching execution module is used to perform mode switching if switching is allowed and confirmed by the debouncing retention mechanism. The output shaping module is used to shape the control parameters for a smooth transition. The effect verification module is used to verify the effect of the vehicle's dynamic response after the switch is completed; The safety rollback module is used to trigger a safety rollback and restore the riding mode to the previous mode or the default safety mode if the effect verification module detects an abnormal dynamic response.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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