CN-122009374-A - Energy recovery and assistance cooperative control method for electric two-wheeled vehicle

CN122009374ACN 122009374 ACN122009374 ACN 122009374ACN-122009374-A

Abstract

The invention discloses an energy recovery and power assisting cooperative control method for an electric two-wheeled vehicle, which belongs to the technical field of electric vehicle control and comprises the steps of generating load prediction characteristics and intention confidence vectors by acquiring vehicle operation data, fusing master-slave constraint data with phase differences, dynamically cutting and compensating and distributing energy recovery and electric power assisting demands according to the load prediction characteristics and the intention confidence vectors, generating a dynamic torque distribution diagram, generating a motor smooth control instruction by combining a smooth mapping function simulating human body operation physiological characteristics, and executing feedback to correct parameters. The control strategy of smooth mapping and closed-loop feedback correction for simulating the physiological characteristics of a human body is combined, so that control conflict between assistance and recovery can be solved, and control smoothness, safety and energy efficiency of a vehicle under complex working conditions are improved.

Inventors

LIU YILIN
ZHANG GUANGHUI
CHEN GANG

Assignees

天津豪爵阳光电动车有限公司

Dates

Publication Date: 20260512
Application Date: 20260312

Claims (10)

1. The method for cooperatively controlling the energy recovery and the assistance of the electric two-wheeled vehicle is characterized by comprising the following steps of: acquiring and processing vehicle operation data to generate load prediction features and intention confidence vectors; fusing the load prediction features and the intention confidence vectors, and performing constraint construction to generate master-slave constraint data with phase differences; Dynamic clipping and compensation distribution are carried out on the energy recovery requirement and the electric power assisting requirement based on the master-slave constraint data, and a dynamic torque distribution diagram is generated; carrying out smooth and safe mapping according to the dynamic torque distribution diagram and a preset mapping function simulating the motion physiological characteristics of the human body operation part, and generating a motor smooth control instruction; And executing the motor smoothing control instruction, collecting vehicle state data and energy data after executing the motor smoothing control instruction, and correcting the master-slave constraint data and the parameters of the mapping function.
2. The cooperative control method for energy recovery and assistance of an electric two-wheeled vehicle according to claim 1, wherein the steps of acquiring and processing vehicle operation data and generating a load prediction feature and an intention confidence vector include: acquiring a pedal frequency parameter and a pedal force parameter of a vehicle, and carrying out load disturbance observation based on the change rate of the pedal frequency parameter and the pedal force parameter to generate a short-term load disturbance characteristic; Acquiring a braking operation parameter and a vehicle body inclination angle parameter of a vehicle, and carrying out intention trend analysis on the change gradient and the angular speed of the braking operation parameter and the vehicle body inclination angle parameter to generate an intention strength and definition characteristic; And correcting the intention strength and the definition characteristic by the short-term load disturbance characteristic, and carrying out load disturbance analysis by the corrected intention strength and the corrected definition characteristic to generate a load prediction characteristic and an intention confidence vector.
3. The cooperative control method for energy recovery and assistance of an electric two-wheeled vehicle according to claim 2, wherein the fusing the load prediction feature and the intention confidence vector and performing constraint construction, generating master-slave constraint data with phase differences comprises: Taking the intention confidence vector as a dominant and fusing the load prediction features to generate an active phase constraint subset defining the power output response speed and the torque smoothness; Taking the load prediction feature as a dominant and fusing the intention confidence vector to generate a recovery phase constraint subset which defines energy recovery intensity and disturbance rejection stability; And calculating a master control phase according to the intention confidence vector and the load prediction characteristic, determining a phase difference relation between the time sequence and the weight of the active phase constraint subset and the recovery phase constraint subset based on the master control phase, and generating master-slave constraint data.
4. A cooperative control method for energy recovery and assistance in an electric two-wheeled vehicle according to claim 3, wherein the generating a recovery phase constraint subset defining energy recovery strength and immunity stability comprises: acquiring an attachment risk prediction grade from the load prediction features; Generating an influence range and a constraint strength based on the intent confidence vector and the attachment risk prediction grade; generating an initial constraint subset by utilizing the influence range and the constraint intensity; acquiring real-time load estimation parameters of a vehicle, and calculating to obtain a basic recovery boundary; And fusing the initial constraint subset with the basic recovery boundary to obtain a recovery phase constraint subset defining energy recovery intensity and disturbance rejection stability.
5. The cooperative control method for energy recovery and assistance of an electric two-wheeled vehicle according to claim 3, wherein the generating a dynamic torque distribution map includes: identifying an overlapping conflict area of the energy recovery requirement and the electric power assistance requirement in a time domain or a torque domain at the current moment; determining a demand party according to the master control phase in the master-slave constraint data and the overlapping conflict area, and cutting to generate cut demand characteristics; And generating a compensation torque command based on the cut demand characteristics, and fusing the compensation torque command with the uncut demand characteristics to generate a dynamic torque distribution diagram.
6. The cooperative control method for energy recovery and assistance of an electric two-wheeled vehicle according to claim 5, wherein the generating the compensation torque command based on the cut demand feature comprises: identifying a demand type corresponding to the cut demand characteristics, and if the demand type is the energy recovery demand, generating a reinforced recovery pulse as a compensation torque instruction; If the electric power assisting requirement is met, generating additional smooth power assisting torque as a compensation torque command; wherein the magnitude and duration of the compensation torque command are defined within dynamic safety boundaries of the master-slave constraint data.
7. The cooperative control method for energy recovery and power assistance of an electric two-wheeled vehicle according to claim 5, wherein the generating the motor smoothing control command includes: mapping an original torque instruction in the dynamic torque distribution diagram through a preset mapping function simulating the motion physiological characteristics of the human body operation part to generate a comfortable torque curve; Acquiring wheel speed difference parameters and road surface roughness parameters of a vehicle, and converting the wheel speed difference parameters and the road surface roughness parameters into rigidity adjusting factors; Dynamically adjusting the response stiffness of the mapping function with the stiffness adjustment factor to modify the comfort torque curve; and generating a motor smooth control command by using the corrected comfortable torque curve.
8. The cooperative control method for energy recovery and power assistance of an electric two-wheeled vehicle according to claim 7, wherein the step of obtaining the wheel speed difference parameter and the road surface roughness parameter of the vehicle and converting the wheel speed difference parameter and the road surface roughness parameter into the rigidity adjustment factor comprises the steps of: acquiring wheel speed difference parameters and road surface roughness parameters of a vehicle; calculating a real-time slip trend index based on the wheel speed difference parameter; Calculating the current road surface peak attachment coefficient based on the mapping relation between the road surface roughness parameter and the preset attachment coefficient; and fusing the real-time slip trend index with the current road surface peak attachment coefficient, and calculating to obtain the rigidity regulating factor.
9. The cooperative control method for energy recovery and assistance of an electric two-wheeled vehicle according to claim 7, wherein the correcting the parameters of the master-slave constraint data and the mapping function includes: collecting the actual energy recovery amount and consumption amount after executing the motor smoothing control instruction, and comparing the actual energy recovery amount and consumption amount with a preset theoretical value set to generate an energy efficiency deviation characteristic; collecting the pedal frequency parameter and pedal force parameter after executing the motor smooth control instruction, analyzing convergence stability, and generating experience evaluation characteristics; And correcting the parameter configuration related to the energy boundary in the master-slave constraint data according to the energy efficiency deviation characteristic, and correcting the parameter configuration related to smoothness in the mapping function according to the experience evaluation characteristic.
10. An electric two-wheeled vehicle energy recovery and assistance cooperative control system, characterized in that the system comprises: the sensing module is used for acquiring and processing vehicle operation data and generating load prediction characteristics and an intention confidence vector; the constraint generation module is used for fusing the load prediction features and the intention confidence vectors and carrying out constraint construction to generate master-slave constraint data with phase differences; the double-ring sensing module is used for dynamically cutting and compensating distribution of the energy recovery requirement and the electric power assisting requirement based on the master-slave constraint data to generate a dynamic torque distribution diagram; The safety control module is used for carrying out smooth safety mapping according to the dynamic torque distribution diagram and a preset mapping function simulating the motion physiological characteristics of the human body operation part, and generating a motor smooth control instruction; And the execution and feedback module is used for executing the motor smoothing control instruction, collecting vehicle state data and energy data after the motor smoothing control instruction is executed, and correcting the master-slave constraint data and the parameters of the mapping function.

Description

Energy recovery and assistance cooperative control method for electric two-wheeled vehicle Technical Field The invention relates to the technical field of electric vehicle control, in particular to an energy recovery and assistance cooperative control method for an electric two-wheel vehicle. Background An electric two-wheel vehicle is used as an environment-friendly and convenient personal transportation tool, and one of the core technologies is a control strategy of an electric driving system. The electric drive system not only includes an electric assist function for powering riding, but also increasingly integrates an energy recovery function, i.e., converting kinetic energy or potential energy of the vehicle into electric energy for storage back to the battery during braking or coasting, to extend the range. Energy recovery and electric assistance are two core functions of an electric drive system, and effective cooperative control of the two functions directly affects energy efficiency, running safety and riding comfort of a vehicle. In the prior art, relatively independent control logic is generally adopted for controlling the energy recovery and the electric power assistance of the electric two-wheel vehicle. The activation and assistance of the electric assistance system are usually output by a preset assistance level curve according to signals of a pedal frequency sensor or a torque sensor. While the energy recovery system is mostly triggered by an independent brake signal, such as holding a brake handle or stopping stepping in a specific mode, its recovery intensity is often also fixed in several gear positions or simply related to the vehicle speed. The two functions are regarded as separate modules at the control level, working independently according to different triggering conditions. However, during actual riding, the operation intention of the rider is complex and variable with the running state of the vehicle, and there often occurs a case where two function triggering conditions overlap, such as the rider brakes slightly while descending a slope, while remaining stepped on to maintain the speed. Under such a compound condition, the above-described independently controlled strategy exposes defects. The control logic of the system may conflict, so that the motor is quickly switched between the power assisting state and the braking state, obvious jerk feeling is generated, and riding comfort is affected. Meanwhile, the simple control strategy is difficult to adapt to complex road conditions such as wet road surfaces, the recovery strength cannot be adjusted according to real-time adhesive force conditions, and certain potential safety hazards exist. Disclosure of Invention In order to solve the problems, the invention provides an energy recovery and assistance cooperative control method for an electric two-wheeled vehicle, which adopts master-slave constraint data with phase difference to dynamically cut and compensate and distribute the energy recovery and electric assistance demands, combines a control strategy of smooth mapping and closed-loop feedback correction for simulating the physiological characteristics of a human body, can solve control conflict between assistance and recovery, and improves the control smoothness, safety and energy efficiency of the vehicle under complex working conditions. The above object can be achieved by the following scheme: A cooperative control method for energy recovery and assistance of an electric two-wheeled vehicle comprises the steps of obtaining vehicle operation data and processing the vehicle operation data to generate a load prediction feature and an intention confidence vector, fusing the load prediction feature and the intention confidence vector, conducting constraint construction to generate master-slave constraint data with phase differences, conducting dynamic clipping and compensation distribution on energy recovery requirements and electric assistance requirements based on the master-slave constraint data to generate a dynamic torque distribution diagram, conducting smooth safety mapping according to the dynamic torque distribution diagram and a preset mapping function simulating motion physiological characteristics of a human body operation part to generate a motor smooth control instruction, executing the motor smooth control instruction, collecting vehicle state data and energy data after executing the motor smooth control instruction, and correcting parameters of the master-slave constraint data and the mapping function. The method comprises the steps of obtaining vehicle running data and processing the vehicle running data, obtaining a pedal frequency parameter and a pedal force parameter of a vehicle, carrying out load disturbance observation based on the change rate of the pedal frequency parameter and the pedal force parameter to generate a short-term load disturbance characteristic, obtaining a brake operation parameter and a ve