Electric two-wheeled vehicle and electric two-wheeled vehicle control method and device

Abstract

The embodiment of the invention provides an electric two-wheeled vehicle and an electric two-wheeled vehicle control method and device.The electric two-wheeled vehicle comprises a collecting component and a controller, the collecting component is used for responding to the situation that the vehicle meets the energy recovery condition, obtaining a driving intention signal and battery state parameters of the vehicle, avoiding energy recovery under the improper condition, and improving the energy recovery efficiency. The controller is used for determining the corresponding basic energy recovery torque of the vehicle in the current driving state according to the driving intention signal so that the energy recovery force can be matched with the real-time intention of a driver, and determining the maximum allowable recovery torque of the vehicle in the current driving state according to the battery state parameters so that the recoverable energy can be utilized to the maximum extent. The energy recovery efficiency is improved; and the target recovery torque is determined according to the basic energy recovery torque and the maximum allowable recovery torque, braking energy recovery is carried out according to the target recovery torque, and in the current driving state, braking energy recovery can achieve maximization of the energy recovery efficiency.

Description

Technical Field

[0001] This application relates to the field of energy recovery technology, and more specifically, to an electric two-wheeled vehicle, an electric two-wheeled vehicle control method, and an apparatus. Background Technology

[0002] Most regenerative kinetic energy recovery systems employ a fixed-level energy recovery strategy, such as electric two-wheelers offering fixed levels of energy recovery intensity ("strong," "medium," "weak") for the driver to choose from. The drawback of this approach is its inability to dynamically adjust based on real-time operating conditions, resulting in insufficient recovery of usable kinetic energy under many circumstances and consequently, low overall energy recovery efficiency. Summary of the Invention

[0003] This application provides an electric two-wheeled vehicle, an electric two-wheeled vehicle control method, and an apparatus to at least solve the technical problem of low energy recovery efficiency of electric two-wheeled vehicles in the related art.

[0004] According to one aspect of the embodiments of this application, an electric two-wheeled vehicle is provided, comprising: a data acquisition component, configured to acquire a driving intention signal and battery state parameters of the vehicle in response to the vehicle meeting energy recovery conditions; the driving intention signal refers to a real-time intention generated by the driver's interaction with the vehicle, reflecting the driver's intention to accelerate or decelerate the vehicle; the battery state parameters refer to parameters reflecting the health and operating state of the vehicle's battery; and a controller, configured to determine a base energy recovery torque corresponding to the vehicle in the current driving state based on the driving intention signal; determine a maximum permissible recovery torque corresponding to the vehicle in the current driving state based on the battery state parameters; determine a target recovery torque based on the base energy recovery torque and the maximum permissible recovery torque; and perform braking energy recovery based on the target recovery torque.

[0005] According to another aspect of the embodiments of this application, an electric two-wheeled vehicle control method is also provided, comprising: in response to the vehicle meeting energy recovery conditions, acquiring a driving intention signal and battery state parameters of the vehicle; the driving intention signal refers to a real-time intention generated by the interaction between the driver and the vehicle, used to reflect the acceleration or deceleration of the vehicle; the battery state parameters refer to parameters reflecting the health and working state of the vehicle's battery; determining a basic energy recovery torque corresponding to the vehicle in the current driving state based on the driving intention signal; determining a maximum permissible recovery torque corresponding to the vehicle in the current driving state based on the battery state parameters; determining a target recovery torque based on the basic energy recovery torque and the maximum permissible recovery torque, and performing braking energy recovery based on the target recovery torque.

[0006] According to another aspect of the embodiments of this application, an electric two-wheeled vehicle control device is also provided, comprising: an acquisition unit, configured to acquire a driving intention signal and battery state parameters of the vehicle in response to the vehicle meeting energy recovery conditions; the driving intention signal refers to a real-time intention generated by the interaction between the driver and the vehicle, used to reflect the acceleration or deceleration of the vehicle; the battery state parameters refer to parameters reflecting the health and working state of the vehicle's battery; a determination unit, configured to determine a basic energy recovery torque corresponding to the vehicle in the current driving state based on the driving intention signal; and to determine a maximum permissible recovery torque corresponding to the vehicle in the current driving state based on the battery state parameters; and a recovery unit, configured to determine a target recovery torque based on the basic energy recovery torque and the maximum permissible recovery torque, and to perform braking energy recovery based on the target recovery torque.

[0007] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed by a processor.

[0008] According to another aspect of the embodiments of this application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform the steps in any of the method embodiments described above.

[0009] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to perform the steps of any of the above method embodiments through the computer program.

[0010] According to this application, an electric two-wheeler includes a data acquisition component and a controller. The data acquisition component acquires the vehicle's driving intention signal and battery state parameters in response to the vehicle meeting energy recovery conditions, thus avoiding energy recovery under inappropriate conditions. The controller determines the basic energy recovery torque corresponding to the vehicle's current driving state based on the driving intention signal, ensuring that the energy recovery intensity matches the driver's real-time intention to accelerate or decelerate the vehicle, avoiding energy waste or a poor experience due to excessive or insufficient recovery torque. Furthermore, based on the battery state parameters, it determines the maximum permissible recovery torque of the vehicle under the current driving state, not only avoiding potential damage to the battery from high-intensity recovery under adverse conditions, but also... When the battery condition allows, the recoverable energy is utilized to the maximum extent, thereby significantly improving energy recovery efficiency while ensuring battery safety. Based on the basic energy recovery torque and the maximum allowable recovery torque, a target recovery torque is determined. The target recovery torque not only meets the driver's braking intention but also strictly adheres to the battery's safe operating range. Braking energy recovery is performed according to the target recovery torque, ensuring that braking energy recovery reaches maximum efficiency under the current driving condition without exceeding the battery's capacity. This maximizes energy recovery efficiency while ensuring battery safety and vehicle driving comfort. Therefore, it can solve the technical problem of low energy recovery efficiency in related technologies for electric two-wheelers. Attached Figure Description

[0011] Figure 1 This is a structural schematic diagram of an electric two-wheeled vehicle according to an embodiment of this application;

[0012] Figure 2 This is a flowchart of an optional braking energy recovery method according to an embodiment of this application;

[0013] Figure 3 This is a flowchart illustrating an optional electric two-wheeled vehicle control method according to an embodiment of this application;

[0014] Figure 4 This is a structural block diagram of an optional electric two-wheeled vehicle control device according to 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 should fall within the scope of protection of the present application.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. 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 comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] According to one aspect of the embodiments of this application, such as Figure 1 As shown, an electric two-wheeled vehicle 102 is provided, including a braking component 1021, a data acquisition component 1022, a controller 1023, a motor 1024, a battery management system (BMS) 1025, and a hydraulic braking system 1026. The controller 1023 can be connected to the data acquisition component 1022, the motor 1024, the battery management system (BMS), and the hydraulic braking system 1026. The data acquisition component 1022 can be connected to the braking component 1021, wherein the braking component 1021 can be a pedal or a brake handle.

[0018] The acquisition unit 1022 is used to acquire the vehicle's driving intention signal and battery status parameters in response to the vehicle meeting the energy recovery conditions; the driving intention signal refers to the real-time intention of the driver to accelerate or decelerate the vehicle generated by the interaction between the driver and the vehicle; the battery status parameters refer to the parameters reflecting the health and working status of the vehicle's battery.

[0019] The controller 1023 is used to determine the basic energy recovery torque corresponding to the current driving state of the vehicle based on the driving intention signal; determine the maximum allowable recovery torque corresponding to the current driving state of the vehicle based on the battery state parameters; determine the target recovery torque based on the basic energy recovery torque and the maximum allowable recovery torque, and perform braking energy recovery based on the target recovery torque.

[0020] The electric two-wheeled vehicle 102 in this embodiment can be, but is not limited to, an electric motorcycle, an electric bicycle, or an electric scooter, and can be applied to the field of energy recovery technology, specifically to scenarios where electric two-wheeled vehicles perform braking energy recovery. For example, in congested urban environments, vehicles frequently start and stop, allowing for the recovery of braking energy; or, when driving down a long downhill section, the driver needs to continuously lightly press the brake pedal or continuously press the brake lever to control speed, allowing for the recovery of braking energy and effectively recovering kinetic energy during the downhill process.

[0021] In related technologies, regenerative braking energy recovery systems for electric two-wheelers generally employ relatively simple and fixed energy recovery strategies. Common strategies include: 1. Using a fixed-gear mode, the vehicle provides fixed levels of energy recovery intensity such as "strong," "medium," and "weak" for the driver to choose from. The disadvantage of this mode is that it cannot dynamically adjust according to real-time operating conditions, resulting in failure to maximize the recovery of usable kinetic energy in many situations, leading to low overall energy recovery efficiency. For example, selecting "strong" recovery when the battery is fully charged may lead to the risk of battery overcharging or uneven braking; a sudden strong recovery during high-speed cruising can cause a noticeable dragging sensation, affecting comfort. 2. Taking electric bicycles as an example, a simple strategy linked to the brake lever is used. Some systems only intervene in energy recovery when the brake lever is lightly squeezed, relying mainly on mechanical braking when squeezed heavily. This strategy does not fully consider factors such as vehicle speed and battery status, leaving room for optimization in recovery efficiency, and the braking feel is not easily linearized, affecting the driving experience. 3. Machine learning algorithms learn the driver's habits and gradually fix the recovery style.

[0022] However, the aforementioned technologies cannot achieve a dynamic balance between efficiency, comfort, and safety. The fixed energy recovery strategies are difficult to adapt to ever-changing driving scenarios (such as traffic jams, highways, and downhill driving), and they do not provide sufficient protection for the battery. If strong energy recovery is still performed when the battery charge is high or the temperature is too low, it may damage the battery life or pose a safety risk. Due to the lack of intelligent adjustment, the aforementioned technologies fail to recover the available kinetic energy to the maximum extent under many operating conditions, and the energy recovery efficiency is not optimal. Learning the driver's habits through machine learning algorithms and gradually fixing the recovery style is a complex, costly, and time-consuming method, and it is slow to respond when faced with sudden road conditions or sudden changes in battery state.

[0023] To at least partially address the aforementioned technical problems, this embodiment provides an intelligent regenerative energy recovery control strategy. Its core objective is to dynamically and smoothly adjust the intensity of energy recovery by real-time sensing and comprehensive analysis of multiple key parameters such as vehicle speed, braking force, battery charge (SOC), and battery temperature. This maximizes energy recovery efficiency while ensuring safety and driving comfort, achieving an optimal balance among the three. The recovery strategy dynamically changes based on real-time sensed key data, automatically adapting to complex road conditions such as urban congestion, highway cruising, and long downhill slopes without driver intervention. Compared to fixed recovery strategies in related technologies, this dynamic recovery strategy achieves maximum energy recovery efficiency under different operating conditions while realizing seamless intelligent optimization, improving driving convenience and user experience. Furthermore, it adjusts the target recovery torque in real-time and dynamically based on real-time sensed key data, eliminating the need for lengthy learning periods and enabling real-time and rapid response. This avoids the problems of complex implementation, high cost, long learning cycles, and delayed response to sudden road conditions or battery state changes associated with technologies that rely on machine learning algorithms to learn driver habits.

[0024] In this embodiment, the electric two-wheeler includes a data acquisition component and a controller. The data acquisition component acquires the vehicle's driving intention signal and battery state parameters in response to the vehicle meeting energy recovery conditions, avoiding energy recovery under inappropriate conditions. The controller determines the basic energy recovery torque corresponding to the vehicle's current driving state based on the driving intention signal, ensuring that the energy recovery intensity matches the driver's real-time intention to accelerate or decelerate the vehicle, avoiding energy waste or a poor experience due to excessive or insufficient recovery torque. Furthermore, based on the battery state parameters, it determines the maximum allowable recovery torque for the vehicle's current driving state, not only avoiding potential damage to the battery from high-intensity recovery under adverse conditions, but also... When the battery condition allows, the recoverable energy is utilized to the maximum extent, thereby significantly improving energy recovery efficiency while ensuring battery safety. Based on the basic energy recovery torque and the maximum permissible recovery torque, a target recovery torque is determined. The target recovery torque not only meets the driver's braking intention but also strictly adheres to the battery's safe operating range. Braking energy recovery is performed according to the target recovery torque, ensuring that braking energy recovery reaches maximum efficiency under the current driving condition without exceeding the battery's capacity. This maximizes energy recovery efficiency while ensuring battery safety and vehicle driving comfort. Therefore, it can solve the technical problem of low energy recovery efficiency in related technologies for electric two-wheelers.

[0025] In this embodiment, the energy recovery condition refers to the specified conditions under which the vehicle can recover energy. For example, whether the vehicle meets the energy recovery condition can be determined based on the following: whether the vehicle is in motion, the motor controller fault flag, the BMS fault flag (such as overvoltage, undervoltage, overtemperature), and the communication timeout or invalid data flag of key sensors (e.g., inertial sensor IMU, handle sensor). That is, the vehicle can meet the energy recovery condition when it is in motion (e.g., V>5km / h) and there is no fault. If any key fault is detected, energy recovery is prohibited. Optionally, energy recovery can be performed when the vehicle's speed exceeds a specified threshold or when the vehicle's battery charge is below a specified level.

[0026] Driving intention signals refer to signals generated by the driver's interaction with the vehicle, used to express the driver's real-time intention to accelerate or decelerate the vehicle. Optionally, driving intention signals can be applied via the brake pedal or brake lever to express the real-time intention to accelerate or decelerate the vehicle, and the intensity and duration of the driving intention signal can reflect the degree and urgency of the driver's desired acceleration or deceleration. For example, driving intention signals may include the depth of the brake lever (D_brake) and the throttle opening (D_acc).

[0027] Battery state parameters refer to parameters reflecting the health and operating status of a vehicle's battery. Optionally, battery state parameters may include battery state of charge (SOC), battery voltage, and battery temperature. The maximum permissible regenerative torque is an upper limit set to ensure battery safety and health, preventing overcharging or high-intensity energy recovery under extreme temperature conditions. This upper limit takes into account the battery's remaining capacity and temperature to avoid subjecting the battery to excessive charging stress under unsuitable conditions, thereby protecting the battery from damage and ensuring the safety and effectiveness of the regenerative braking process.

[0028] For example, in related technologies, simple linear control is performed based solely on brake pedal signals or vehicle speed, neglecting fine-tuning of battery state. However, this reduces recycling efficiency (it cannot recycle at high SOC) and poses battery safety risks. Its overall performance is far inferior to this embodiment. Furthermore, fixing the recycling intensity through GPS navigation information or driving mode selection (such as "Energy Saving" or "Sport") is unreliable, unable to respond to real-time changes in battery state and subtle driving intentions, lacking sufficient intelligence and precision. This embodiment considers determining the maximum permissible recyclable torque corresponding to the vehicle's current driving state based on battery state parameters, avoiding the simplified single-factor or two-factor control methods used in the aforementioned related technologies. This fundamentally prevents strong energy recovery under adverse conditions such as overcharging and low temperatures, prioritizing battery life and overall vehicle safety.

[0029] In an optional embodiment, the system is powered on and initialized, the controller performs a self-test, and establishes communication with each sensor and BMS; real-time data acquisition is performed, and the vehicle speed V, brake lever depth D_brake, throttle opening D_acc, battery SOC, and temperature T_bat are read cyclically.

[0030] Baseline energy recovery torque refers to the recovery torque determined by the driving intention signal under the current driving conditions of the vehicle.

[0031] Optionally, an inertial measurement unit (IMU) or other acceleration sensor is provided to detect the acceleration or deceleration trend of the vehicle. The IMU can provide information such as vehicle acceleration, deceleration, and tilt angle. Based on the vehicle's current speed V and the detected acceleration a in the current driving state, the dynamic characteristics of the vehicle are analyzed to obtain the vehicle's acceleration change value, such as whether the vehicle is in a rapid deceleration state or a smooth deceleration state. Rapid deceleration can use a higher energy recovery torque to match the braking demand, while smooth deceleration can use a lower recovery torque to maintain driving comfort. The travel depth of the brake lever in the current driving state is obtained, and the travel depth of the brake lever is weighted and summed with the acceleration change value to determine the base energy recovery torque.

[0032] Alternatively, vehicle operation data can be continuously collected, including but not limited to vehicle speed, braking frequency, braking force, road environment (such as road surface friction coefficient), battery status, etc. The collected data can be used to train a machine learning model (such as neural network, support vector machine or decision tree) so that the machine learning model can learn to predict the corresponding basic energy recovery torque under a given driving state. After obtaining the vehicle's driving intention signal, the vehicle's driving intention signal is input into the machine learning model to obtain the corresponding basic energy recovery torque.

[0033] The maximum permissible regenerative torque refers to the regenerative torque determined based on battery state parameters under the current driving conditions of the vehicle.

[0034] Optionally, a battery health status monitoring module can be set up in the vehicle's battery management system to continuously assess the battery's health status. The battery's health status reflects the ratio of its actual capacity to its rated capacity in its brand-new state, and can be an important indicator of battery aging. The lower the battery's health status, the worse its ability to withstand high-current charging and discharging. A mapping rule between battery health status and the maximum allowable regenerative torque can be established. For example, when the battery health status is below a preset threshold (e.g., 80%), the maximum allowable regenerative torque should decrease proportionally. The mapping rule can be a function expression or a preset lookup table. After obtaining the battery's health status parameters, the corresponding maximum allowable regenerative torque is obtained using the mapping rule based on these parameters.

[0035] Alternatively, the number of charge-discharge cycles of the battery can be obtained, and a cycle number threshold and a correction coefficient can be set. When the number of charge-discharge cycles of the battery is less than the cycle number threshold, the correction coefficient is 1. When the number of charge-discharge cycles of the battery is greater than or equal to the cycle number threshold, the correction coefficient decreases exponentially or linearly according to the degree of exceeding the cycle number, until the specified correction threshold is reached. Then, the maximum allowable recoverable torque can be calculated based on the battery's charge level, battery temperature, and number of charge-discharge cycles. For example, the maximum allowable recoverable torque can be equal to the theoretical maximum generating torque of the motor and controller at the current speed, multiplied by the minimum value among the battery's charge level, battery temperature, and number of charge-discharge cycles multiplied by the correction factor.

[0036] The target recovery torque refers to the actual torque used to recover energy. For example, the target recovery torque T_regen can be a multi-input, single-output dynamic mapping function: T_regen = f(V, D_brake, SOC, T_bat).

[0037] Optionally, the minimum of the baseline energy recovery torque and the maximum permissible recovery torque can be determined as the target recovery torque; alternatively, a weighted sum of the baseline energy recovery torque and the maximum permissible recovery torque can be used to determine the target recovery torque; or, the battery's health status can be assessed in real time by monitoring the battery's charge and temperature. For example, a battery health factor can be defined, which decreases as the battery's charge increases and the temperature deviates from the ideal range. The baseline energy recovery torque can be corrected based on the battery's health factor. If the battery's health is high, the corrected torque will be close to the original baseline recovery torque; if the health is low, the corrected torque will be limited to a lower value to reduce stress on the battery. The corrected baseline recovery torque is then compared with the maximum permissible recovery torque. If the corrected baseline energy recovery torque is less than or equal to the maximum permissible recovery torque, then the corrected baseline recovery torque is the target recovery torque; if the corrected baseline recovery torque is greater than the maximum permissible recovery torque, then the maximum permissible recovery torque is taken as the target recovery torque.

[0038] Alternatively, the baseline energy recovery torque and the maximum permissible recovery torque can be converted into fuzzy sets, for example, defining three fuzzy sets: "low," "medium," and "high." A set of fuzzy logic rules is then established to determine the fuzzy level of the target recovery torque based on the fuzzy membership degrees of the baseline energy recovery torque and the maximum permissible recovery torque. For example, "if the baseline energy recovery torque is high and the maximum permissible recovery torque is medium, then the target recovery torque should be high"; if the baseline energy recovery torque is low and the maximum permissible recovery torque is high, then the target recovery torque is medium. Using fuzzy logic reasoning, the fuzzy level of the target recovery torque is inferred from the rule base based on the current baseline energy recovery torque and the maximum permissible recovery torque. Defuzzification methods (such as centroid method, maximum membership degree method, etc.) are then applied to convert the fuzzy level into a specific numerical value, which is used as the target recovery torque.

[0039] After obtaining the target recovery torque, the controller performs regenerative braking based on it. Essentially, the system can control the vehicle's drive motor to enter a generator state, producing corresponding braking torque to convert the vehicle's kinetic energy into electrical energy, which is then stored in the battery. This process is not static; the target recovery torque can be adjusted according to changes in the vehicle's operating environment and state (such as changes in driving intention signals or battery status parameters) to ensure that each regenerative braking operation achieves the optimal balance between efficiency, comfort, and safety.

[0040] In an optional embodiment, an intelligent regenerative braking energy recovery system can be configured. This system may include a sensing unit, a vehicle speed sensor, a brake stroke sensor, a throttle opening processor, a battery management system (BMS), a decision-making unit, and an execution unit. The sensing unit collects real-time vehicle operating status data. The vehicle speed sensor is mounted on the wheels or transmission system to detect vehicle speed (V) in real time. The brake stroke sensor is integrated into the brake lever assembly to detect the depth (D_brake) of the driver's squeeze of the brake lever. The throttle opening sensor detects the throttle opening (D_acc); when D_acc=0, it can be determined that the driver intends to coast. The BMS provides real-time key status parameters of the battery pack, including the battery state of charge (SOC) and battery temperature (T_bat). The decision-making unit includes a motor controller and a drive motor. The motor controller precisely controls the drive motor to operate in a generator state, producing the required braking torque. The drive motor, as an actuator, converts the vehicle's kinetic energy into electrical energy.

[0041] It should be noted that the core algorithm of the control strategy in this embodiment can also be transferred from the vehicle controller (VCU) to the battery management system (BMS) or the motor controller. Although the hardware carriers are different, the core idea and method of dynamic adjustment based on multiple factors (vehicle speed, braking, battery status) are essentially the same.

[0042] According to the embodiments provided in this application, the electric two-wheeler includes a data acquisition component and a controller. The data acquisition component is used to acquire the vehicle's driving intention signal and battery state parameters in response to the vehicle meeting energy recovery conditions, thus avoiding energy recovery under inappropriate conditions. The controller is used to determine the basic energy recovery torque corresponding to the vehicle's current driving state based on the driving intention signal, ensuring that the intensity of energy recovery matches the driver's real-time intention to accelerate or decelerate the vehicle, avoiding energy waste or a poor experience due to excessive or insufficient recovery torque; and based on the battery state parameters, it determines the maximum allowable recovery torque of the vehicle under the current driving state, not only avoiding potential damage to the battery caused by high-intensity recovery under adverse conditions, but also... Furthermore, when the battery condition allows, it maximizes the utilization of recyclable energy, thereby significantly improving energy recovery efficiency while ensuring battery safety. Based on the basic energy recovery torque and the maximum permissible recovery torque, a target recovery torque is determined. The target recovery torque not only meets the driver's braking intention but also strictly adheres to the battery's safe operating range. Braking energy recovery is performed according to the target recovery torque, ensuring that braking energy recovery reaches maximum efficiency under the current driving conditions without exceeding the battery's capacity. This maximizes energy recovery efficiency while ensuring battery safety and vehicle driving comfort. Therefore, it can solve the technical problem of low energy recovery efficiency in related technologies for electric two-wheelers.

[0043] In an exemplary embodiment, the driving intention signal includes brake lever travel and throttle opening; the controller is further configured to: determine that the vehicle is in coasting recovery mode in response to the brake lever travel indicating no braking input and the throttle opening indicating no throttle input, and acquire the real-time vehicle speed, and determine the basic energy recovery torque corresponding to the vehicle in the current driving state based on a first mapping relationship and the real-time vehicle speed; the first mapping relationship represents the correlation between the vehicle speed and the recovery torque.

[0044] In this embodiment, the brake lever travel refers to the physical displacement (or angular displacement) of the brake lever when the driver operates the brake lever of the electric two-wheeler, from the initial fully released position (i.e., no braking) to the final limit position when pressed or pinched. Optionally, the brake lever travel can be measured in millimeters (mm) or degrees (°), and the brake lever travel can be measured by a sensor and converted into an electrical signal. The throttle opening refers to the angle or position of the throttle handle in the electric two-wheeler, which can be used to reflect the intensity of the driver's acceleration request. Optionally, the throttle opening can be expressed as a percentage (%), typically ranging from 0% to 100%.

[0045] Coasting recovery mode refers to a mode where there is no braking input during the brake lever travel and no throttle input during the throttle opening. For example, coasting recovery mode can be a mode where the vehicle neither accelerates nor brakes (it coasts only by inertia). In this coasting recovery mode, the vehicle's motor switches to generator mode, converting the excess kinetic energy during the vehicle's coasting process into electrical energy, which is then stored in the battery.

[0046] For example, when the throttle opening D_acc=0 and the brake lever depth (i.e., brake lever travel) D_brake=0, the vehicle enters coasting recovery mode.

[0047] Optionally, in coasting recovery mode, the base energy recovery torque T_base can be mapped according to the vehicle speed V (for example, the higher the vehicle speed, the more the base energy recovery torque can be, but smoothness must be ensured).

[0048] Real-time vehicle speed is the current speed of a vehicle. Optionally, real-time vehicle speed can be obtained by monitoring vehicle speed sensors.

[0049] The first mapping relationship characterizes the correlation between vehicle speed and regenerative torque. Optionally, the first mapping relationship can characterize the correlation between vehicle speed and base energy recovery torque. A vehicle speed range can map a base energy recovery torque value. For example, the first mapping relationship can be that the base energy recovery torque increases positively with increasing vehicle speed.

[0050] Optionally, historical data, including actual values ​​of vehicle speed and corresponding baseline energy recovery torque, as well as other possible influencing factors such as road type, vehicle load, and ambient temperature, are collected and used as training samples. A Support Vector Machine (SVM) regression algorithm is used to learn from these training samples (i.e., historical data) to establish a predictive model from vehicle speed to baseline energy recovery torque. When the system receives real-time vehicle speed, it inputs the real-time speed into the trained SVM model, and the model outputs the predicted baseline energy recovery torque. Furthermore, the predicted baseline energy recovery torque can be combined with other real-time parameters (such as battery SOC and temperature) and further optimized through weighted summation to obtain the final baseline energy recovery torque.

[0051] In this embodiment, in response to the brake lever travel indicating no braking input and the throttle opening indicating no throttle input, the vehicle is determined to be in coasting recovery mode. The basic energy recovery torque is determined based on real-time vehicle speed dynamics and a first mapping relationship, avoiding the defects caused by the energy recovery force being fixed at any vehicle speed. This effectively balances energy recovery efficiency and driving comfort. Furthermore, during the coasting phase, the vehicle can smoothly recover energy, reducing energy waste and extending the driving range of electric vehicles. At the same time, it ensures that the driver can obtain a consistent and comfortable driving experience under different driving conditions, and intelligent adjustment can be completed without manual intervention.

[0052] In one exemplary embodiment, the driving intention signal includes brake lever travel; the controller is further configured to: determine that the vehicle is in regenerative braking mode in response to the brake lever travel indicating the presence of braking input, and determine the total braking torque desired by the driver based on the brake lever travel; determine the maximum regenerative torque corresponding to the vehicle's motor at the current speed, and determine the minimum of the total braking torque and the maximum regenerative torque as the base energy recovery torque corresponding to the vehicle in the current driving state.

[0053] In this embodiment, braking input refers to the input that controls the vehicle to decelerate or stop through the travel of the brake lever. For example, braking input can be generated by the driver pressing the brake pedal, pulling the brake lever, or by operating the control buttons on the steering wheel. These physical operations are detected by the vehicle's sensors and converted into electronic signals.

[0054] Regenerative braking mode refers to the driver applying braking intent through the brake lever, causing the vehicle to enter an energy recovery control mode.

[0055] Optionally, when the system detects that the driver operates the brake lever, i.e., the brake lever travel changes, the system immediately recognizes this signal as the trigger condition for the braking command. This means that the driver intends to slow down or stop the vehicle, and the vehicle needs to enter the regenerative braking mode.

[0056] For example, when the depth of the brake lever D_brake > 0 (i.e., the brake lever travel is greater than 0), the regenerative braking mode is entered.

[0057] The total braking torque expected by the driver refers to the total deceleration torque expected to be generated by all braking systems (including electric braking and mechanical braking) through braking operation, which can reflect the driver's need for the degree of deceleration.

[0058] Optionally, a pressure sensor is installed inside the brake lever or on its contact surface to detect the pressure applied by the driver when operating the brake lever; a pressure-torque mapping table is set up to convert the detected pressure value into the corresponding braking torque value, thereby determining the total braking torque desired by the driver.

[0059] Alternatively, an inertial measurement unit can be set up to collect data such as the vehicle's acceleration, angular velocity, and direction information during braking. A model can be trained based on the collected data, taking parameters such as brake lever travel, vehicle speed, acceleration change, load, and road conditions as inputs, and calculating the predicted total braking torque expected by the driver through the model.

[0060] Maximum regenerative torque refers to the maximum torque value at which the motor can convert kinetic energy into electrical energy and store it in the battery under the current vehicle operating conditions (such as motor speed). Here, the obtained total braking torque can be compared with the maximum regenerative torque, and the smaller of the total braking torque and the maximum regenerative torque can be determined as the basic energy recovery torque. That is, if the total braking torque is greater than the maximum regenerative torque, the maximum regenerative torque can be determined as the basic energy recovery torque; if the total braking torque is less than or equal to the maximum regenerative torque, the total braking torque can be determined as the basic energy recovery torque.

[0061] Optionally, the maximum regenerative torque characteristic curve of the motor at various speeds is obtained. When the vehicle receives a braking command, the motor speed is monitored in real time, and the maximum regenerative torque that the motor can provide at that speed is found in the characteristic curve database according to the speed. The maximum regenerative torque found is compared with the total braking torque expected by the driver, and the smaller value between the maximum regenerative torque and the total braking torque expected by the driver is taken as the basic energy recovery torque.

[0062] In an optional embodiment, when the vehicle is in regenerative braking mode, the base energy recovery torque T_base is allocated based on the total braking demand (i.e., total braking force) (determined by the total braking torque D_brake and V of the brake lever travel) and a pre-set "electric braking priority" principle. Based on the brake lever travel D_brake, the driver's desired total deceleration or total braking torque T_total = f(D_brake) is mapped. This mapping relationship needs to be calibrated as a linear or slightly sensitive curve with a smoother transition at the beginning to optimize the feel. Typically, when the total braking force demand is small, it is primarily handled by electric motor braking. In this embodiment, the base energy recovery torque T_base can be expressed as T_base = min(T_total, T_motor_max), where T_motor_max is the maximum recovery torque that the motor can provide at the current speed. That is, as long as the motor capacity is sufficient, all braking is done using the electric motor.

[0063] This improves driving comfort, with smooth changes in regenerative braking force that meet driving expectations. It intelligently adjusts according to vehicle speed and braking requests, effectively avoiding low-speed jerking and excessive drag at high speeds.

[0064] In this embodiment, in response to the presence of braking input indicated by the brake lever travel, the vehicle is determined to be in regenerative braking mode. By dynamically matching the brake lever travel, the total braking torque is determined, as well as the maximum regenerative torque that the motor can achieve at the current speed. The smaller of the two values ​​can be selected as the basic energy recovery torque command. This avoids situations where the motor is overloaded or the regenerative torque exceeds the driver's actual needs, achieving real-time optimization of braking energy recovery. This not only enhances the responsiveness and controllability of the vehicle's braking system but also significantly improves the effectiveness of energy recovery and the smoothness of the driving experience.

[0065] In an exemplary embodiment, the battery state parameters include multiple battery parameters; the controller is further configured to: determine a limiting coefficient corresponding to each of the multiple battery parameters, and determine the smallest limiting coefficient among the multiple battery parameters as a target limiting coefficient; the limiting coefficient corresponding to each battery parameter is used to adjust the regeneration intensity of the vehicle; the limiting coefficient corresponding to each battery parameter is less than or equal to 1; determine the maximum generating torque corresponding to the vehicle in the current driving state, and determine the product between the target limiting coefficient and the maximum generating torque as the maximum permissible regeneration torque corresponding to the vehicle in the current driving state.

[0066] In this embodiment, battery parameters refer to various quantitative indicators of battery state, performance and characteristics. Optionally, battery parameters may include battery state of charge (i.e. battery capacity), battery temperature, voltage, current and battery health status, etc.

[0067] The limiting coefficient for each of the multiple battery parameters refers to the coefficient used to adjust the vehicle's recycling intensity. Each battery parameter corresponds to a unique limiting coefficient, which is less than or equal to 1. For example, the limiting coefficient for each battery parameter could be 0.6 or 0.9, etc., and can be set according to actual conditions; no specific restrictions are imposed here. The target limiting coefficient refers to the smallest limiting coefficient among the multiple battery parameters.

[0068] In some embodiments, the limiting coefficient corresponding to each battery parameter can be multiplied by the maximum generated torque corresponding to the vehicle under the current driving state to obtain the adjusted maximum generated torque corresponding to each battery parameter. The adjusted maximum generated torque corresponding to each battery parameter can then be weighted and summed to obtain the maximum permissible regenerative torque corresponding to the vehicle under the current driving state. Alternatively, the limiting coefficients corresponding to each battery parameter can be fused to obtain the target limiting coefficient. However, the above weighted summation process requires setting reasonable weights for each parameter. The selection and adjustment of these weights may require extensive testing and calibration, increasing complexity. Furthermore, the above fusion process involves comprehensive calculations of multiple parameters, which may require longer data collection and processing time to obtain results, resulting in slow response times. Therefore, the data obtained from the above weighted summation and fusion processes cannot reflect the true state of the battery, and thus cannot obtain a limiting coefficient that matches the battery state, leading to an inaccurate determination of the maximum permissible regenerative torque corresponding to the current driving state.

[0069] To address the problems associated with the weighted summation and fusion method described above, this embodiment selects the minimum limiting coefficient as the target limiting coefficient. This target limiting coefficient is then multiplied by the maximum generating torque corresponding to the current driving state to determine the maximum permissible regenerative torque of the vehicle under the current condition. This avoids complex weighted or fusion calculations, simplifies the control logic, ensures rapid response to rapidly changing battery states, and uses the minimum limiting coefficient as the target limiting coefficient. This means the system will follow the strictest battery protection measures, ensuring the battery is not subjected to excessive charging stress, thus protecting its health and safety. The maximum permissible regenerative torque obtained by multiplying the target limiting coefficient by the maximum generating torque more directly reflects the most pressing battery state limitations, ensuring that the regenerative torque is neither too high, causing battery overload, nor too conservative, wasting regenerative opportunities. Therefore, by using the minimum limiting coefficient to determine the maximum permissible regenerative torque, this embodiment can achieve precise electric braking energy recovery control under complex and changing driving and battery conditions, improving energy recovery efficiency while also considering battery safety and driving comfort.

[0070] Optionally, the battery's health status is obtained, and a battery health status threshold is set. For example, when the battery health status is below 80%, a limiting coefficient is introduced, and the limiting coefficient gradually decreases as the state of health (SOH) decreases. A limiting function is then set based on the battery health status, battery capacity, and battery temperature. This function maps the values ​​corresponding to the battery health status, battery capacity, and battery temperature to the corresponding limiting coefficients, resulting in multiple limiting coefficients. The smallest limiting coefficient among these is selected as the target limiting coefficient.

[0071] Maximum generating torque refers to the maximum generating torque produced by the motor at the current speed. Optionally, the maximum generating torque can be the upper limit of the motor's capacity in generating mode.

[0072] Optionally, the operating status of the motor can be monitored in real time, including parameters such as motor temperature, speed, current and voltage. The current efficiency and remaining power of the motor can be evaluated based on the above parameters. Through the vehicle dynamics model, and in combination with factors such as current vehicle speed, vehicle load and road slope, the maximum torque required for the vehicle to decelerate to zero or reach the target deceleration under the current operating conditions can be calculated.

[0073] Alternatively, an inverse mathematical model of the motor can be constructed. This inverse mathematical model of the motor correlates the physical characteristics of the motor (such as motor type, size, number of magnetic poles, winding design, etc.) with the performance parameters of the motor under different operating conditions (such as speed, current, voltage, temperature) to predict the maximum generating torque of the motor under any given condition. The current driving state parameters (such as vehicle speed, battery temperature, etc.) are input into the inverse model of the motor, and the theoretical maximum generating torque of the motor under the current operating condition is obtained based on the calculation results of the model.

[0074] The target limiting coefficient and the maximum generated torque are multiplied together, and the product is determined as the maximum allowable regenerative torque of the vehicle under the current driving condition.

[0075] For example, when multiple battery parameters, including the SOC coefficient and the battery temperature coefficient, are considered, the maximum permissible recyclable torque T_max can be calculated according to the following formula (1):

[0076] T_max = T_max_theoretical × min(SOC coefficient, temperature coefficient) (1)

[0077] Where T_max_theoretical is the maximum generating torque that the motor and controller can provide at the current speed.

[0078] This embodiment dynamically evaluates the limiting effect of multiple battery parameters on energy recovery, thereby adjusting the intensity of energy recovery without compromising battery safety and lifespan. The selection of the target limiting coefficient ensures that the entire system operates under the constraints of battery parameters, while the determination of the maximum allowable recovery torque ensures that the energy recovery intensity can fully utilize the generator's power generation capacity while strictly adhering to the battery's health and safety standards under current operating conditions. This not only improves the efficiency of regenerative braking energy recovery but also greatly enhances the reliability of the entire system.

[0079] In an exemplary embodiment, the controller is further configured to: perform the following operations on each battery parameter as the current battery parameter to obtain a limiting coefficient corresponding to each battery parameter: determine the target preset parameter range in which the current battery parameter is located from a plurality of preset parameter ranges; each preset parameter range in the plurality of preset parameter ranges corresponds to a second mapping relationship; the second mapping relationship corresponding to each preset parameter range characterizes the mapping relationship between the battery parameter and the limiting coefficient in each preset parameter range; and determine the limiting coefficient corresponding to the current battery parameter according to the second mapping relationship corresponding to the target preset parameter range.

[0080] In this embodiment, the preset parameter range refers to the preset range of battery parameters. For example, when the battery parameter is SOC, SOC can be divided into multiple preset parameter ranges such as 0%-10%, 10%-20%, 20%-90%, 90%-95%, and 95%-100%. When the battery parameter is battery temperature, battery temperature can be divided into preset parameter ranges such as -20°C to 0°C, 0°C to 40°C, and 40°C to 60°C.

[0081] The target preset parameter range refers to the specific preset range corresponding to the actual value of a battery parameter obtained at the current moment. For example, if the current battery charge is 85%, the target preset parameter range can be determined from multiple preset parameter ranges, i.e., from the above multiple preset parameter ranges, the target preset parameter range can be 20%-90%.

[0082] Among them, each preset parameter range in the multiple preset parameter ranges corresponds to a second mapping relationship. The second mapping relationship for each preset parameter range refers to the mapping relationship between the battery parameter and the limiting coefficient in each preset parameter range. One battery parameter in a preset parameter range can be mapped to one limiting coefficient. That is, the limiting coefficient corresponding to each battery parameter can be obtained by looking up the second mapping relationship corresponding to each battery parameter in the preset parameter range where each battery parameter is located.

[0083] In an optional embodiment, Table 1 illustrates the relationship between several preset parameter ranges of SOC and the maximum permissible regenerative torque T_max, and Table 2 illustrates the relationship between several preset parameter ranges of battery temperature and the maximum permissible regenerative torque T_max, as shown in Tables 1 and 2. Torque limitation can be based on battery state; a maximum permissible regenerative torque upper limit T_max can be obtained by looking up the tables according to SOC and T_bat.

[0084] Table 1

[0085]

[0086] Table 2

[0087]

[0088] By consulting Tables 1 and 2 above, the second mapping relationship corresponding to the target preset parameter range can be obtained, thus yielding the current battery's limiting coefficient. In this way, by using battery parameter states (SOC, temperature) as the core decision-making basis, strong energy recovery under adverse conditions such as overcharging and low temperatures is fundamentally prevented, prioritizing battery life and vehicle safety.

[0089] In this embodiment, by dividing the battery parameters into multiple preset parameter ranges and setting a corresponding second mapping relationship for each preset parameter range, energy recovery can be adjusted in a timely manner under extreme conditions (such as near full charge or abnormal battery temperature) to protect the battery from damage. At the same time, based on the second mapping relationship corresponding to the target preset parameter range, the limiting coefficient corresponding to the current battery parameters is determined. By dynamically optimizing the energy recovery intensity in real time, the system can always recover energy with the highest possible efficiency within the acceptable range of the battery, significantly improving the vehicle's driving range and demonstrating high efficiency.

[0090] In one exemplary embodiment, the controller is further configured to: determine the target recovery torque as the minimum of the base energy recovery torque and the maximum permissible recovery torque.

[0091] In some embodiments, the target recovery torque can be obtained by weighted summation of the base recovery torque and the maximum permissible recovery torque, or by fusion of the base recovery torque and the maximum permissible recovery torque. However, the weighted summation process described above requires setting appropriate weights for each parameter. Improper weight settings may favor one side, resulting in poor overall performance. Furthermore, the weighted summation and fusion process may require more complex algorithms and longer computation time, which is an unnecessary burden in regenerative braking control that requires immediate response. Complex processing may lead to decision delays, reduce the system's response speed to driving demands and changes in battery state, and affect the overall braking effect and safety.

[0092] To address the issues associated with the weighted summation and fusion processing described above, this embodiment determines the target recovery torque as the minimum of the base energy recovery torque and the maximum permissible recovery torque. This ensures that each braking energy recovery operation occurs within the battery's safe range, responds instantly to changes in battery status, protects battery health and vehicle safety, and maximizes energy recovery efficiency without sacrificing safety. This helps improve the electric vehicle's range and energy utilization efficiency. The recovery torque can be smoothly and dynamically adjusted, avoiding unnecessary jerking caused by complex interactions between parameters, and providing a comfortable and stable driving experience.

[0093] Optionally, the base torque T_base and the maximum allowable upper limit T_max (i.e., the maximum allowable recovery torque) are compared, and the smaller one is taken as the final command torque (i.e., the target recovery torque). The target recovery torque can be obtained by the following formula (2):

[0094] T_regen=min(T_base,T_max)(2)

[0095] The target recovery torque is obtained by formula (2) above, which ensures that the recovery intensity is always within the battery safety range.

[0096] In this embodiment, by determining the minimum of the basic energy recovery torque and the maximum permissible recovery torque as the target recovery torque, it is ensured that the energy recovery torque does not exceed the boundary of safe battery operation, while meeting the basic braking requirements as much as possible, thus achieving a balance between energy recovery efficiency, driving comfort and battery safety.

[0097] In one exemplary embodiment, the driving intention signal includes brake lever travel; the controller is further configured to: recover electric braking energy via the vehicle's motor in response to a target recovery torque being greater than the total braking torque; recover electric braking energy via the vehicle's motor based on the target recovery torque in response to a target recovery torque being less than or equal to the total braking torque; determine a torque difference between the target recovery torque and the total braking torque; and perform mechanical braking via the vehicle's hydraulic system according to the torque difference.

[0098] In this embodiment, the process of determining the driver's desired total braking torque based on the brake handle travel can be referred to in the above embodiment, and will not be repeated here.

[0099] Electric braking energy recovery refers to the process of converting the vehicle's kinetic energy into electrical energy by operating the vehicle's drive motor during braking, thereby achieving energy recovery. When the target recovery torque is greater than the total braking torque, electric braking energy recovery can be achieved through the vehicle's motor.

[0100] A hydraulic system is an engineering system that uses liquid (usually hydraulic oil) as a working medium to transmit power and control motion. Mechanical braking refers to the use of the vehicle's hydraulic braking system to supplement the remaining braking force when the electric braking force is insufficient, so as to ensure that the overall braking force reaches the total braking torque expected by the driver.

[0101] For example, the hydraulic braking system (used for coordinated control) is triggered by the ABS controller to supplement the total braking force when the energy recovery torque is insufficient or the battery cannot accept more energy, ensuring braking safety and linear feel.

[0102] When the target recovery torque is less than or equal to the total braking torque, the vehicle's motor can perform electric braking energy recovery based on the target recovery torque, and the vehicle's hydraulic system can perform mechanical braking based on the torque difference between the target recovery torque and the total braking torque.

[0103] Optionally, the torque difference ΔT = T_total - T_regen between the target recovery torque T_regen and the driver's desired total braking torque T_total is calculated in real time. This torque difference ΔT is then input into the PID controller. Based on the parameters (Kp, Ki, Kd) of the PID algorithm and the rate of change of the torque difference, the PID controller can calculate a suitable control quantity. This control quantity directly reflects the required intensity of hydraulic braking. The calculated control quantity is then converted into a command for the hydraulic braking system, ensuring that the hydraulic braking system generates the corresponding braking torque according to the command to compensate for the insufficiency of electric braking recovery.

[0104] For example, when the total braking torque T_total > the target recovery torque T_regen, electric braking energy recovery is performed based on the target recovery torque T_regen. The insufficient portion (T_total - T_motor_max) is supplemented by the hydraulic braking system. The controller calculates the difference between the total braking force requirement and T_regen. If hydraulic braking compensation is needed, a request is sent to the ABS controller. By outputting commands and coordinating braking, seamless coordination between electric and hydraulic braking is achieved, ensuring consistent braking feel. In this way, by prioritizing the use of the motor to recover braking force, the reliance on the mechanical braking system is reduced, thereby reducing the wear of mechanical braking components and extending their service life.

[0105] In some embodiments, Figure 3 This is a flowchart of an optional regenerative braking process according to an embodiment of this application, such as... Figure 2 As shown, real-time vehicle operating status data (including vehicle speed, brake lever depth, throttle opening, battery charge status, and battery temperature) is acquired to determine whether the vehicle meets the energy recovery conditions. If the vehicle does not meet the energy recovery conditions, energy recovery is prohibited, and the energy recovery process ends directly. If the vehicle meets the energy recovery conditions, the vehicle's braking mode is determined, and the basic energy recovery torque, maximum allowable recovery torque, and total braking torque are determined. Based on the basic energy recovery torque and maximum allowable recovery torque, the target recovery torque is determined, and it is determined whether the target recovery torque is greater than the total braking torque. If the target recovery torque is greater than the total braking torque, electric braking energy recovery is performed through the vehicle's motor according to the target recovery torque. If the target recovery torque is less than or equal to the total braking torque, electric braking energy recovery is performed through the vehicle's motor according to the target recovery torque, and mechanical braking is performed through the vehicle's hydraulic system according to the torque difference between the target recovery torque and the total braking torque.

[0106] In this embodiment, the total braking torque desired by the driver is determined by the brake lever travel, which improves the accuracy and reliability of braking operation. Furthermore, by comparing the target recovery torque with the total braking torque desired by the driver, the system intelligently decides whether to use electric braking or introduce hydraulic braking to supplement the braking force, achieving a seamless switch between energy recovery and traditional braking, thus improving the system's intelligence level. Through smooth torque distribution, the system enhances vehicle stability and driving comfort during braking.

[0107] In an optional embodiment, the system executes the above embodiment cyclically at millisecond intervals (e.g., 10ms) to achieve dynamic real-time adjustment.

[0108] In an optional embodiment, the controller is further configured to: perform smoothing filtering on the target recovery torque and perform braking energy recovery based on the processed target recovery torque.

[0109] In this embodiment, smoothing filtering refers to the controller performing time-domain smoothing on the obtained target regenerative torque (T_regen), which can suppress its instantaneous jumps or step changes, so that the regenerative braking torque output by the motor responds in a continuous and gradual manner, thereby avoiding vehicle jerking, shaking or discomfort for passengers, and improving the smoothness and comfort of the braking process.

[0110] In some embodiments, abrupt changes in recovery force can cause vehicle jerking, which can easily cause discomfort to vehicle occupants and a poor driving experience. To solve this problem, in this application embodiment, the controller can be used to perform torque smoothing filtering on the target recovery torque. That is, in order to avoid jerking caused by abrupt changes in the target recovery torque T_regen, the final command (i.e., the target recovery torque) is smoothed by filtering (such as using a first-order low-pass filter or a rate limiter) to make its changes more gradual and improve comfort.

[0111] In this embodiment, by introducing smoothing filtering at the target recovery torque output end, the torque step and high-frequency jitter caused by instantaneous fluctuations in control parameters during regenerative braking are effectively suppressed, achieving continuous, gradual, and abrupt output of regenerative braking force. This significantly improves the braking smoothness, ride comfort, electric drive system stability, and braking consistency of electric two-wheelers during energy recovery.

[0112] According to another aspect of the embodiments of this application, a control method for an electric two-wheeled vehicle is also provided. In this embodiment, the electric two-wheeled vehicle control method can be applied to... Figure 1 In the hardware environment described in this application, the electric two-wheeler control method can be executed by the electric two-wheeler 102.

[0113] Taking the electric two-wheeler control method in this embodiment as an example, Figure 3 This is a schematic flowchart of an optional electric two-wheeled vehicle control method according to an embodiment of this application, as shown below. Figure 3 As shown, the process of this method may include the following steps S302 to S306.

[0114] Step S302: In response to the vehicle meeting the energy recovery conditions, the driving intention signal and battery status parameters of the vehicle are acquired; the driving intention signal refers to the real-time intention of the driver to accelerate or decelerate the vehicle generated by the interaction between the driver and the vehicle; the battery status parameters refer to the parameters reflecting the health status and working status of the vehicle's battery.

[0115] Step S304: Based on the driving intention signal, determine the basic energy recovery torque corresponding to the current driving state of the vehicle; based on the battery state parameters, determine the maximum allowable recovery torque corresponding to the current driving state of the vehicle.

[0116] Step S306: Determine the target recovery torque based on the basic energy recovery torque and the maximum allowable recovery torque, and perform braking energy recovery based on the target recovery torque.

[0117] It should be noted that, for the sake of simplicity, the foregoing embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0118] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / random access memory (RAM), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0119] According to another aspect of the embodiments of this application, an electric two-wheeled vehicle control device is also provided. This electric two-wheeled vehicle control device can be used to implement the braking energy recovery method provided in the above embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0120] Figure 4 This is a structural block diagram of an optional electric two-wheeled vehicle control device according to an embodiment of this application, such as... Figure 4 As shown, the electric two-wheeler control device includes:

[0121] The acquisition unit 402 is used to acquire the vehicle's driving intention signal and battery status parameters in response to the vehicle meeting the energy recovery conditions; the driving intention signal refers to the real-time intention of the driver to accelerate or decelerate the vehicle generated by the interaction between the driver and the vehicle; the battery status parameters refer to parameters that reflect the health and working status of the vehicle's battery.

[0122] The determining unit 404 is used to determine the basic energy recovery torque corresponding to the current driving state of the vehicle based on the driving intention signal; and to determine the maximum allowable recovery torque corresponding to the current driving state of the vehicle based on the battery state parameters.

[0123] The recovery unit 406 is used to determine the target recovery torque based on the basic energy recovery torque and the maximum permissible recovery torque, and to perform braking energy recovery based on the target recovery torque.

[0124] It should be noted that the acquisition unit 402 in this embodiment can be used to execute the above step S302, the determination unit 404 in this embodiment can be used to execute the above step S304, and the recycling unit 406 in this embodiment can be used to execute the above step S306.

[0125] The embodiments provided in this application, in response to the vehicle meeting energy recovery conditions, acquire the vehicle's driving intention signal and battery state parameters, avoiding energy recovery under inappropriate conditions. Based on the driving intention signal, determine the basic energy recovery torque corresponding to the vehicle's current driving state, ensuring that the energy recovery intensity matches the driver's real-time intention to accelerate or decelerate the vehicle, avoiding energy waste or poor experience due to excessive or insufficient recovery torque; and based on the battery state parameters, determine the maximum permissible recovery torque of the vehicle under the current driving state, not only avoiding potential damage to the battery from high-intensity recovery under adverse conditions, but also ensuring that the battery state allows for... Under these conditions, the recoverable energy is utilized to the maximum extent, thereby significantly improving energy recovery efficiency while ensuring battery safety. Based on the basic energy recovery torque and the maximum allowable recovery torque, the target recovery torque is determined. The target recovery torque not only meets the driver's braking intention but also strictly adheres to the battery's safe operating range. Braking energy recovery is performed according to the target recovery torque, ensuring that braking energy recovery reaches maximum efficiency under the current driving conditions without exceeding the battery's carrying capacity. This maximizes energy recovery efficiency while ensuring battery safety and vehicle driving comfort. Therefore, it can solve the technical problem of low energy recovery efficiency in related technologies.

[0126] In an exemplary embodiment, the driving intention signal includes the brake lever travel and the throttle opening. The determining unit 404 is configured to determine that the vehicle is in coasting recovery mode in response to the brake lever travel indicating no braking input and the throttle opening indicating no throttle input, and to acquire the real-time vehicle speed. Based on a first mapping relationship and the real-time vehicle speed, the determining unit 404 determines the basic energy recovery torque corresponding to the vehicle in the current driving state. The first mapping relationship represents the correlation between the vehicle speed and the recovery torque.

[0127] In an exemplary embodiment, the driving intention signal includes the brake lever travel; the determining unit 404 is configured to determine that the vehicle is in a regenerative braking mode in response to the brake lever travel indicating the presence of a braking input, and to determine the total braking torque desired by the driver based on the brake lever travel; to determine the maximum regenerative torque corresponding to the vehicle's motor at the current speed, and to determine the minimum of the total braking torque and the maximum regenerative torque as the basic energy recovery torque corresponding to the vehicle in the current driving state.

[0128] In an exemplary embodiment, the battery state parameters include multiple battery parameters; the determining unit 404 is configured to determine a limiting coefficient corresponding to each of the multiple battery parameters, and determine the smallest limiting coefficient among the multiple battery parameters as the target limiting coefficient; the limiting coefficient corresponding to each battery parameter is used to adjust the regeneration intensity of the vehicle; the limiting coefficient corresponding to each battery parameter is less than or equal to 1; determine the maximum generating torque corresponding to the vehicle in the current driving state, and determine the product between the target limiting coefficient and the maximum generating torque as the maximum permissible regeneration torque corresponding to the vehicle in the current driving state.

[0129] In an exemplary embodiment, the determining unit 404 is configured to perform the following operations on each battery parameter as the current battery parameter to obtain the limiting coefficient corresponding to each battery parameter: determining the target preset parameter range in which the current battery parameter is located from a plurality of preset parameter ranges; each preset parameter range in the plurality of preset parameter ranges corresponds to a second mapping relationship; the second mapping relationship corresponding to each preset parameter range characterizes the mapping relationship between the battery parameter and the limiting coefficient in each preset parameter range; and determining the limiting coefficient corresponding to the current battery parameter according to the second mapping relationship corresponding to the target preset parameter range.

[0130] In one exemplary embodiment, the recovery unit 406 is configured to determine the target recovery torque as the minimum of the base energy recovery torque and the maximum permissible recovery torque.

[0131] In one exemplary embodiment, the driving intention signal includes the brake lever travel; a recovery unit 406 is configured to determine the total braking torque desired by the driver based on the brake lever travel; in response to a target recovery torque being greater than the total braking torque, perform electric braking energy recovery via the vehicle's motor; in response to a target recovery torque being less than or equal to the total braking torque, perform electric braking energy recovery via the vehicle's motor based on the target recovery torque, determine the torque difference between the target recovery torque and the total braking torque, and perform mechanical braking via the vehicle's hydraulic system according to the torque difference.

[0132] In an exemplary embodiment, the recovery unit 406 is further configured to perform smoothing filtering on the target recovery torque and to perform braking energy recovery based on the processed target recovery torque.

[0133] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0134] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0135] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. An electric two-wheeled vehicle, characterized in that, include: The data acquisition unit is used to acquire the vehicle's driving intention signal and battery status parameters in response to the vehicle meeting the energy recovery conditions. The driving intention signal refers to the real-time intention generated by the driver's interaction with the vehicle, which reflects the driver's intention to accelerate or decelerate the vehicle. The battery status parameters refer to parameters that reflect the health and operating status of the vehicle's battery. The controller is configured to determine the base energy recovery torque corresponding to the vehicle in the current driving state based on the driving intention signal; determine the maximum permissible recovery torque corresponding to the vehicle in the current driving state based on the battery state parameters; determine the target recovery torque based on the base energy recovery torque and the maximum permissible recovery torque; and perform braking energy recovery based on the target recovery torque.

2. The electric two-wheeled vehicle according to claim 1, characterized in that, The driving intention signal includes the brake lever travel and the throttle opening; the controller is further configured to: in response to the brake lever travel indicating no braking input and the throttle opening indicating no throttle input, determine that the vehicle is in coasting recovery mode, and acquire the real-time vehicle speed, and determine the basic energy recovery torque corresponding to the vehicle in the current driving state according to a first mapping relationship and the real-time vehicle speed; the first mapping relationship represents the correlation between the vehicle speed and the recovery torque.

3. The electric two-wheeled vehicle according to claim 1, characterized in that, The driving intention signal includes the brake lever travel; the controller is further configured to: in response to the brake lever travel indicating the presence of braking input, determine that the vehicle is in regenerative braking mode, and determine the total braking torque desired by the driver based on the brake lever travel; determine the maximum regenerative torque corresponding to the vehicle's motor at the current speed, and determine the minimum of the total braking torque and the maximum regenerative torque as the basic energy recovery torque corresponding to the vehicle in the current driving state.

4. The electric two-wheeled vehicle according to claim 1, characterized in that, The battery state parameters include multiple battery parameters; the controller is further configured to: determine the limiting coefficient corresponding to each of the multiple battery parameters, and determine the smallest limiting coefficient among the multiple battery parameters as the target limiting coefficient; the limiting coefficient corresponding to each battery parameter is used to adjust the recovery intensity of the vehicle; the limiting coefficient corresponding to each battery parameter is less than or equal to 1; The maximum power generation torque corresponding to the vehicle in the current driving state is determined, and the product between the target limiting coefficient and the maximum power generation torque is determined as the maximum allowable regenerative torque corresponding to the vehicle in the current driving state.

5. The electric two-wheeled vehicle according to claim 4, characterized in that, The controller is further configured to: use each battery parameter as the current battery parameter to perform the following operations to obtain the limiting coefficient corresponding to each battery parameter: determine the target preset parameter range in which the current battery parameter is located from a plurality of preset parameter ranges; each preset parameter range in the plurality of preset parameter ranges corresponds to a second mapping relationship; the second mapping relationship corresponding to each preset parameter range characterizes the mapping relationship between the battery parameter and the limiting coefficient in each preset parameter range; Based on the second mapping relationship corresponding to the target preset parameter range, the limiting coefficient corresponding to the current battery parameters is determined.

6. The electric two-wheeled vehicle according to claim 1, characterized in that, The controller is further configured to: determine the minimum of the base energy recovery torque and the maximum permissible recovery torque as the target recovery torque.

7. The electric two-wheeled vehicle according to claim 1, characterized in that, The driving intention signal includes the brake lever travel; the controller is further configured to: determine the total braking torque desired by the driver based on the brake lever travel; recover electric braking energy via the vehicle's motor in response to the target recovery torque being greater than the total braking torque; recover electric braking energy via the vehicle's motor based on the target recovery torque in response to the target recovery torque being less than or equal to the total braking torque; determine the torque difference between the target recovery torque and the total braking torque; and perform mechanical braking via the vehicle's hydraulic system according to the torque difference.

8. The electric two-wheeled vehicle according to claim 1, characterized in that, The controller is also configured to: perform smooth filtering on the target recovery torque, and perform braking energy recovery based on the processed target recovery torque.

9. A control method for an electric two-wheeled vehicle, characterized in that, include: In response to the vehicle meeting the energy recovery conditions, the system acquires the vehicle's driving intention signals and battery status parameters. The driving intention signal refers to the real-time intention generated by the driver's interaction with the vehicle, which reflects the driver's intention to accelerate or decelerate the vehicle. The battery status parameters refer to parameters that reflect the health and operating status of the vehicle's battery. Based on the driving intention signal, determine the basic energy recovery torque corresponding to the vehicle in the current driving state; based on the battery state parameters, determine the maximum allowable recovery torque corresponding to the vehicle in the current driving state. Based on the basic energy recovery torque and the maximum permissible recovery torque, the target recovery torque is determined, and braking energy recovery is performed based on the target recovery torque.

10. A control device for an electric two-wheeled vehicle, characterized in that, include: The acquisition unit is used to acquire the vehicle's driving intention signal and battery state parameters in response to the vehicle meeting the energy recovery conditions. The driving intention signal refers to the real-time intention generated by the driver's interaction with the vehicle, which reflects the driver's intention to accelerate or decelerate the vehicle. The battery status parameters refer to parameters that reflect the health and operating status of the vehicle's battery. The determining unit is configured to determine the basic energy recovery torque corresponding to the vehicle in the current driving state based on the driving intention signal; and to determine the maximum allowable recovery torque corresponding to the vehicle in the current driving state based on the battery state parameters. The recovery unit is used to determine the target recovery torque based on the basic energy recovery torque and the maximum allowable recovery torque, and to perform braking energy recovery based on the target recovery torque.

Images