CN114103661A - Recovery method of braking energy recovery strategy of distributed driving electric automobile - Google Patents
Recovery method of braking energy recovery strategy of distributed driving electric automobile Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
- B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
- B60L15/2009—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed for braking
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L7/00—Electrodynamic brake systems for vehicles in general
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- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/42—Drive Train control parameters related to electric machines
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60L2240/00—Control parameters of input or output; Target parameters
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- Y02T10/72—Electric energy management in electromobility
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Abstract
The invention discloses a method for recovering braking energy of a distributed driving electric automobile, which is characterized by comprising the following steps of: the recovery method comprises the steps of obtaining the optimal braking demand torque of each actuator through an upper layer controller, deciding the weight of the optimal motor braking torque of each actuator according to vehicle state parameters, and guaranteeing the maximum braking energy recovery in real time through the weight. By adopting the recovery method, aiming at the structural characteristics of the distributed driving electric automobile, the optimal braking demand torque of each actuator is obtained through the upper-layer controller according to the driving habits of drivers and the running state parameters of the automobile, so that the recovery efficiency of the braking energy of the automobile is improved, the optimal braking torque of the driving motor is ensured, the cruising mileage of the automobile is increased, and the method has popularization and application values.
Description
Technical Field
The invention relates to the technical field of electric automobile braking energy recovery, in particular to a method for recovering a braking energy recovery strategy of a distributed driving electric automobile.
Background
Compared with an internal combustion engine automobile, the electric automobile has certain advantages in the aspects of environmental protection, vibration, noise and the like. The distributed driving electric automobile becomes the development direction of the future electric automobile due to the unique chassis structure and the advantages of the distributed driving electric automobile. With the increasing popularization of electric automobiles, the endurance mileage of the electric automobiles is more and more concerned by people, and the endurance capacity of the electric automobiles is always a research hotspot in the field of new energy automobiles. Because the energy of the current vehicle-mounted power battery is limited, in order to increase the driving mileage of the automobile, part of braking energy needs to be recovered into the power battery through the motor in the braking process so as to drive the automobile.
The electric automobile adopts the power battery as the vehicle-mounted energy, the motor-driven vehicle runs, and for the distributed driving electric automobile, the distributed driving system adopts flexible connection to replace part of mechanical transmission parts, so that the structure is compact, the driving efficiency and the space utilization rate of the vehicle are improved, the electronic differential speed is realized by independently adjusting the torque of the driving wheel, the electronization degree of the vehicle is enhanced, the better active control is realized, and the electric automobile driving system becomes a research hotspot of the electric automobile driving technology. The basic principle of the regenerative braking of the electric automobile is as follows: the conversion of the kinetic energy and the electric energy of the electric automobile is realized by the motor/generator with reversible action. Most of the current researches are mainly based on centralized driving, and only energy recovery is carried out on driving wheels, which results in low recovery effect of braking energy. Therefore, how to effectively improve the recovery efficiency of the braking energy is a key for improving the dynamic property and the energy economy of the distributed driving electric automobile.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a recovery method which is convenient to operate, in particular to a recovery method of a braking energy recovery strategy of a distributed driving electric automobile, aiming at the problems in the background technology and the structural characteristics of the distributed driving electric automobile, and according to the driving habits of a driver and the running state parameters of the automobile, the recovery efficiency of the braking energy of the automobile is improved, and the endurance mileage of the automobile is increased.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a recovery method of a braking energy recovery strategy of a distributed driving electric automobile is characterized in that the recovery method obtains the optimal braking demand torque of each actuator through an upper layer controller, the weight of the optimal motor braking torque of each actuator is decided according to vehicle state parameters, and the maximization of the braking energy recovery is ensured in real time through the weight; the method specifically comprises the following steps:
s1, acquiring input parameters of a driver, and acquiring braking intention of the driver according to driving habits of the driver, wherein the braking intention is according to the driving habits, namely force applied to a brake pedal, so that the stroke generated by a pedal sensor and the change rate of the stroke are enabled;
s2, identifying the intention of the driver, making a braking coefficient according to a corresponding rule by taking the stroke and the change rate thereof generated by the force applied to the brake pedal by the driver as input according to the braking intention of the driver, and deciding the braking torque required by the whole vehicle according to the braking coefficient;
s3, torque optimal distribution is carried out, an upper layer controller determines the torque optimal distribution according to a braking coefficient, wherein the torque optimal distribution is that the optimal required braking torque of each actuator is decided according to vehicle state parameters;
s4, making a braking torque weight decision of each actuator, wherein according to the torque weight decision, each actuator energy recovery weight module selects a corresponding braking energy recovery control strategy according to the characteristic value and the BMS system, an upper-layer controller adopts an advanced optimization algorithm to determine a braking torque weight coefficient of each actuator, and a corresponding weight value is distributed through the braking torque weight decision of each actuator;
and S5, recovering the braking energy, wherein the braking energy recovery module distributes braking torque according to the determined weight value of the recovery of the braking energy of each actuator, and then applies the braking torque to the driving motor through corresponding braking torque, so that the driving motor serves as a generator to charge the battery, and the maximum recovery of the braking energy is realized.
Further, in the method for recovering braking energy of a distributed-type driving electric vehicle, in the step S2, the braking coefficient is mainly used for identifying a braking mode, wherein the braking mode includes a light braking mode, a medium braking mode and an emergency braking mode, and a braking torque required by the whole vehicle is determined according to different braking modes.
Further, in the method for recovering braking energy of a distributed-type driving electric vehicle according to the present invention, in step S3, the moment optimal allocation is to optimally allocate braking torque required by the entire vehicle by each actuator according to state parameters of the vehicle, such as vehicle speed, tire slip rate, yaw rate, centroid slip angle, and the like.
Further, in the step S4, the characteristic values include a road adhesion utilization module, a tire slip rate control module, a driving motor peak moment module, a driving motor failure module, and a yaw stability control module, and each actuator energy recovery weight module selects a corresponding braking energy recovery control strategy according to the road adhesion utilization module, the tire slip rate control module, the driving motor peak moment module, the driving motor failure module, and the yaw stability control module, and allocates the weight value of the braking energy of each actuator;
the road surface adhesion utilization rate module is characterized in that the road surface adhesion utilization rate is correspondingly different due to the fact that road surface adhesion conditions are complex and changeable and road surface adhesion coefficients are different, and influences on lateral and longitudinal dynamics control of a vehicle are large; the maximum road adhesion force which can be provided for wheels by the ground is directly represented through the high and low conditions of the road adhesion utilization rate;
the tire slip rate control module acquires the tire dynamics state in real time, controls the slip rate in a linear stable region in real time, enables the tire to be close to the optimal slip rate, fully utilizes the road adhesion condition, and realizes the optimal control of the tire dynamics and the whole vehicle dynamics;
the driving motor peak torque module is used for monitoring the running state of the driving motor in real time, deciding the maximum torque which can be provided by the driving motor according to the driving motor peak torque state and playing a role in protecting the service life of the driving motor and controlling the control performance of the whole vehicle;
the driving motor failure module monitors the operation parameters of the driving motor in real time, and the driving motor has a complex structure and a complex and changeable use environment, so that the failure factor of each driving motor is uncertain, the failure of the driving motor directly influences the dynamic control stability control of the whole vehicle, the life and property safety of drivers and passengers is threatened, once the driving motor fails, the corresponding parameters are fed back to an upper controller, the optimal moment of the failed wheel is decided, the generation of an unexpected yaw moment of the vehicle is reduced, and the stability control and dynamic control range of the vehicle is increased;
the yaw stability control module is used for performing deviation correction control on the vehicle in real time according to the control input of the vehicle state parameter mass center side slip angle and the yaw angular speed, so that the driving safety is ensured, and the control of the vehicle dynamics manipulation stability is improved.
Further, in the method for recovering braking energy of a distributed-type-driven electric vehicle, in step S4, the BMS is a battery management system configured to monitor a battery operating state in real time, where the battery operating state includes battery remaining life prediction, battery temperature monitoring and control, and battery state of charge prediction.
Further, in the method for recovering braking energy of a distributed driving electric vehicle according to the present invention, in step S4, the weight coefficient of braking torque of each actuator means that the maximum expected braking torque that can be received by the driving motor occupies the weight of the expected braking torque of each actuator determined by the upper decision layer, and the weight coefficient is a determining factor for maximizing the recovery of braking energy; the actuators refer to braking torque of a driving motor and braking torque of a hydraulic brake.
Further, in the method for recovering the braking energy recovery strategy of the distributed driving electric vehicle, in step S5, the braking energy recovery module applies the braking torque of the driving motor to the driving motor according to the determined weight values of the braking energy recovery of each actuator, where different weight values have different energy recovery rates, and the braking torque of the driving motor is ensured to be optimal in real time, so that the driving motor reversely rotates to charge the battery.
Compared with the prior art, the recovery method of the braking energy recovery strategy of the distributed driving electric automobile has the beneficial effects that: the method comprises the steps of setting the braking intention of a driver according to the driving habit of the driver, formulating a braking coefficient according to the braking intention, determining torque optimal distribution according to the braking coefficient, selecting a corresponding braking energy recovery control strategy by each actuator energy recovery weight module according to a characteristic value and a BMS system, and applying corresponding braking torque to a driving motor to enable the driving motor to serve as a generator to charge a battery, so that the energy recovery utilization rate is improved to the maximum extent. By adopting the recovery method, aiming at the structural characteristics of the distributed driving electric automobile, the optimal braking demand torque of each actuator is obtained through the upper-layer controller according to the driving habits of drivers and the running state parameters of the automobile, so that the recovery efficiency of the braking energy of the automobile is improved, the optimal braking torque of the driving motor is ensured, the cruising mileage of the automobile is increased, and the method has popularization and application values.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings.
FIG. 1 is a flow architecture diagram of the invention;
fig. 2 is a schematic diagram of a braking torque weight decision framework according to the present invention.
Detailed Description
To further illustrate the concepts of the present invention, embodiments of the present invention will be further described with reference to the accompanying drawings in which:
as shown in fig. 1, in the recovery method of the braking energy recovery strategy of the distributed driving electric vehicle, the recovery method obtains the optimal braking demand torque of each actuator through an upper controller, decides the weight of the optimal motor braking torque of each actuator according to vehicle state parameters, and ensures the maximum braking energy recovery in real time through the weight; the method specifically comprises the following steps:
s1, acquiring input parameters of a driver, and acquiring braking intention of the driver according to driving habits of the driver, wherein the braking intention is according to the driving habits, namely force applied to a brake pedal, so that the stroke generated by a pedal sensor and the change rate of the stroke are enabled;
s2, identifying the intention of the driver, making a braking coefficient according to a corresponding rule by taking the stroke and the change rate thereof generated by the force applied to the brake pedal by the driver as input according to the braking intention of the driver, and deciding the braking torque required by the whole vehicle according to the braking coefficient;
s3, torque optimal distribution is carried out, an upper layer controller determines the torque optimal distribution according to a braking coefficient, wherein the torque optimal distribution is that the optimal required braking torque of each actuator is decided according to vehicle state parameters;
s4, making a braking torque weight decision of each actuator, wherein according to the torque weight decision, each actuator energy recovery weight module selects a corresponding braking energy recovery control strategy according to the characteristic value and the BMS system, an upper-layer controller adopts an advanced optimization algorithm to determine a braking torque weight coefficient of each actuator, and a corresponding weight value is distributed through the braking torque weight decision of each actuator; the characteristic values comprise a road adhesion utilization rate module, a tire slip rate control module, a driving motor peak moment module, a driving motor failure module and a yaw stability control module, and the energy recovery control strategies of the actuators are selected by the energy recovery weight modules according to the road adhesion utilization rate module, the tire slip rate control module, the driving motor peak moment module, the driving motor failure module and the yaw stability control module to distribute the weight values of the braking energy of the actuators; the road surface adhesion utilization rate module is characterized in that the road surface adhesion utilization rate is correspondingly different due to the fact that road surface adhesion conditions are complex and changeable and road surface adhesion coefficients are different, and the influence on the lateral and longitudinal dynamics control of a vehicle is large; the maximum road adhesion force which can be provided for wheels by the ground is directly represented through the high and low conditions of the road adhesion utilization rate; the tire slip rate control module acquires the tire dynamics state in real time, controls the slip rate in a linear stable region in real time, enables the tire to be close to the optimal slip rate, fully utilizes the road adhesion condition, and realizes the optimal control of the tire dynamics and the whole vehicle dynamics; the driving motor peak torque module is used for monitoring the running state of the driving motor in real time, deciding the maximum torque which can be provided by the driving motor according to the driving motor peak torque state and playing a role in protecting the service life of the driving motor and controlling the control performance of the whole vehicle; the driving motor failure module monitors the operation parameters of the driving motor in real time, and the driving motor has a complex structure and a complex and changeable use environment, so that the failure factor of each driving motor is uncertain, the failure of the driving motor directly influences the dynamic control stability control of the whole vehicle, the life and property safety of drivers and passengers is threatened, once the driving motor fails, the corresponding parameters are fed back to an upper controller, the optimal moment for changing the failed wheel is decided, the undesirable yaw moment generated by the vehicle is reduced, and the stability control and dynamic control range of the vehicle is increased; the yaw stability control module is used for performing deviation correction control on the vehicle in real time according to the control input of the vehicle state parameter mass center side slip angle and the yaw angular speed, so that the driving safety is ensured, and the control of the vehicle dynamics manipulation stability is improved.
The BMS is a battery management system and is used for monitoring the running state of the battery in real time, wherein the running state of the battery comprises the prediction of the residual service life of the battery, the monitoring and control of the temperature of the battery and the prediction of the state of charge of the battery.
And S5, recovering the braking energy, wherein the braking energy recovery module distributes braking torque according to the determined weight value of the recovery of the braking energy of each actuator, and then applies the braking torque to the driving motor through corresponding braking torque, so that the driving motor serves as a generator to charge the battery, and the maximum recovery of the braking energy is realized.
In the step S2, the braking coefficient is mainly used for identifying a braking mode, wherein the braking mode includes a light braking mode, a medium braking mode and an emergency braking mode, and the braking torque required by the whole vehicle is determined according to different braking modes; in step S3, the moment optimal allocation is determined by determining each actuator to optimally allocate the braking moment required by the whole vehicle according to the vehicle speed, the tire slip rate, the yaw rate, and the state parameters of the centroid slip angle of the vehicle; in step S4, the weight coefficient of the braking torque of each actuator means that the maximum expected braking torque that can be received by the drive motor occupies the weight in the expected braking torque of each actuator determined by the upper decision-making layer, and the weight coefficient is a determining factor for maximizing the recovery of braking energy; wherein each actuator refers to a driving motor braking torque and a hydraulic brake braking torque; in step S5, the braking energy recovery module applies the braking torque of the driving motor to the driving motor according to the determined weight values of the braking energy recovery of each actuator, where different weight values have different energy recovery rates, and the braking torque of the driving motor is guaranteed to be optimal in real time, so that the driving motor is reversely rotated to charge the battery.
The invention relates to a recovery method of a braking energy recovery strategy of a distributed driving electric automobile, which comprises a driver input module 100, a driver intention identification module 200, a torque optimization distribution module 300, a braking torque weight decision module 400 of each actuator and a braking energy recovery module 500; the driver input module 100 is mainly used for acquiring driver intention information, namely force applied to a brake pedal, and stroke and change rate thereof generated by a pedal sensor; the driver driving module 100 is used as a driver intention identification module 200 to provide input parameters, so that the driver intention identification module 200 can decide the braking torque required by the whole vehicle according to the pedal stroke and the change rate thereof; the driver intention identification module 200 is used as the input of the torque optimization distribution module 300, and the torque optimization distribution module 300 optimally distributes the braking torque required by the whole vehicle according to vehicle state parameters such as vehicle speed, tire slip rate, yaw angular velocity, mass center slip angle and the like, so that the optimized braking torque is the expected braking torque of each actuator; the moment optimization distribution module 300 is used as the input of the braking moment weight decision module 400 of each actuator, the braking moment weight decision module 400 of each actuator takes the extracted characteristic values and the battery life, temperature, battery charge state and the like predicted by the BMS system as the basis to decide the braking moment weight coefficient of each actuator, wherein the characteristic values comprise a road adhesion utilization rate module, a tire slip rate control module, a driving motor peak moment module, a driving motor failure module and a yaw stability control module, the braking moment weight coefficient of each actuator refers to the weight of the maximum expected braking moment which can be received by the driving motor in the upper decision layer to decide the expected braking moment of each actuator, and the weight coefficient is the decision factor for maximizing the recovery of the braking energy; the braking torque weight decision module 400 of each actuator is used as the input of the braking energy recovery module 500, so that the braking energy recovery module 500 applies the braking torque of the driving motor to the driving motor according to the weight coefficient, and the driving motor reversely rotates to charge the battery.
The following describes in detail the recovery method of the braking energy recovery strategy of the distributed drive electric vehicle according to the present invention by making a decision on the braking torque weight of each actuator, with reference to fig. 2:
the method comprises the following steps that brake torque weight decisions of each actuator are made, each actuator energy recovery weight module S403 selects a corresponding brake energy recovery control strategy according to a characteristic value S401 and a BMS system S402, an upper-layer controller adopts an advanced optimization algorithm to determine brake torque weight coefficients of each actuator, and corresponding weight values are distributed through the brake torque weight decisions of each actuator, and the method specifically comprises the following steps:
eigenvalue S401: the characteristic value mainly comprises a road surface adhesion utilization rate module, a tire slip rate control module, a driving motor peak moment module, a driving motor failure module and a yaw stability control module.
(1) The road surface attachment utilization rate module: the road surface adhesion utilization rate module aims to obtain the road surface adhesion coefficient utilization rate, the road surface adhesion conditions are complex and changeable, the road surface adhesion coefficients are different, the road surface adhesion utilization rate has certain difference, the road surface adhesion utilization rate directly represents the maximum road surface adhesion force which can be provided for wheels by the ground, and the influence on the transverse and longitudinal dynamics control of the vehicle is large.
(2) A tire slip ratio control module: the tire slip rate control aims to control the slip rate in a linear stable region in real time, so that the tire is positioned near the optimal slip rate, the road adhesion condition is fully utilized, the optimal control of tire dynamics and vehicle dynamics is realized, and the tire dynamics state is obtained in real time.
(3) Drive motor peak torque module: the peak torque of the driving motor is used for monitoring the running state of the driving motor in real time, and the maximum torque which can be provided by the driving motor is determined by combining the states, so that the effects of protecting the service life of the driving motor and controlling the control performance of the whole vehicle are achieved.
(4) The driving motor failure module: due to the fact that the structure of the driving motor is complex, the using environment is complex and changeable, and therefore the failure factor of each driving motor is uncertain. The failure of the driving motor directly influences the control of the dynamic control stability of the whole vehicle and threatens the life and property safety of drivers and passengers. Therefore, the failure factor of the driving motor must be considered, the operation parameters of the driving motor are monitored in real time, and once the failure happens, the corresponding parameters are fed back to an upper controller to decide the optimal moment of the failed wheel, reduce the undesirable yaw moment generated by the vehicle and increase the stability control and dynamic control range of the vehicle.
(5) A yaw stability control module: the yaw stability control is mainly based on the control input of the vehicle state parameters, namely the mass center side slip angle and the yaw velocity, and the deviation rectification control is carried out on the vehicle in real time, so that the driving safety is ensured, and the control of the dynamic control stability of the vehicle is improved.
BMS system S402: the Battery Management System is a Battery Management System (BMS System for short) and is used for monitoring the Battery running state in real time, wherein the Battery running state mainly comprises Battery residual life prediction, Battery temperature monitoring and control and Battery state of charge estimation.
And (3) performing weight decision on the braking torque of each actuator, wherein an energy recovery weight module S403 of each actuator takes the characteristic value S401 and the BMS system S402 as input, and performs optimization decision on the weight of each actuator through an advanced algorithm, wherein each actuator refers to the braking torque of a driving motor and the braking torque of a hydraulic brake. And the upper-layer controller decides and distributes corresponding weight values through the brake torque weight of each actuator according to various decision factors (characteristic values and parameters in the BMS system), and realizes the maximum recovery of brake energy by ensuring the brake torque of the driving motor to be in the optimal state in real time.
According to the method for recovering the braking energy recovery strategy of the distributed driving electric automobile, the braking intention of a driver is set according to the driving habit of the driver, the braking coefficient is made according to the braking intention, the moment optimal distribution is determined according to the braking coefficient, the corresponding braking energy recovery control strategy is selected by the energy recovery weight modules of the actuators according to the characteristic values and the BMS system, and finally the corresponding braking torque is applied to the driving motor to enable the driving motor to serve as a generator to charge the battery, so that the energy recovery utilization rate is improved to the maximum extent.
In conclusion, by adopting the recovery method, aiming at the structural characteristics of the distributed driving electric automobile, the optimal braking demand torque of each actuator is obtained through the upper controller according to the driving habits of the driver and the running state parameters of the automobile, so that the recovery efficiency of the braking energy of the automobile is improved, the optimal braking torque of the driving motor is ensured, the cruising mileage of the automobile is increased, and the method has popularization and application values.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art, and any modifications, equivalents, improvements, etc. made by using the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A method for recovering braking energy of a distributed driving electric automobile is characterized by comprising the following steps: the recovery method comprises the steps that the optimal braking demand torque of each actuator is obtained through an upper layer controller, the weight of the optimal motor braking torque of each actuator is decided according to vehicle state parameters, and the maximum braking energy recovery is guaranteed in real time through the weight; the method specifically comprises the following steps:
s1, acquiring input parameters of a driver, and acquiring braking intention of the driver according to driving habits of the driver, wherein the braking intention is according to the driving habits, namely force applied to a brake pedal, so that the stroke generated by a pedal sensor and the change rate of the stroke are enabled;
s2, identifying the intention of the driver, making a braking coefficient according to a corresponding rule by taking the stroke and the change rate thereof generated by the force applied to the brake pedal by the driver as input according to the braking intention of the driver, and deciding the braking torque required by the whole vehicle according to the braking coefficient;
s3, torque optimal distribution is carried out, an upper layer controller determines the torque optimal distribution according to a braking coefficient, wherein the torque optimal distribution is that the optimal required braking torque of each actuator is decided according to vehicle state parameters;
s4, making a braking torque weight decision of each actuator, wherein according to the torque weight decision, each actuator energy recovery weight module selects a corresponding braking energy recovery control strategy according to the characteristic value and the BMS system, an upper-layer controller adopts an advanced optimization algorithm to determine a braking torque weight coefficient of each actuator, and a corresponding weight value is distributed through the braking torque weight decision of each actuator;
and S5, recovering the braking energy, wherein the braking energy recovery module distributes braking torque according to the determined weight value of the recovery of the braking energy of each actuator, and then applies the braking torque to the driving motor through corresponding braking torque, so that the driving motor serves as a generator to charge the battery, and the maximum recovery of the braking energy is realized.
2. The method for recovering the braking energy of the distributed driving electric vehicle according to claim 1, characterized in that: in the step S2, the braking coefficient is mainly used for identifying a braking mode, where the braking mode includes a light braking mode, a medium braking mode and an emergency braking mode, and the braking torque required by the entire vehicle is determined according to different braking modes.
3. The method for recovering the braking energy of the distributed driving electric vehicle according to claim 1, characterized in that: in step S3, the moment optimal distribution is determined by each actuator to optimally distribute the braking moment required by the whole vehicle according to the vehicle speed, the tire slip rate, the yaw rate, the centroid slip angle, and other state parameters of the vehicle.
4. The method for recovering the braking energy of the distributed driving electric vehicle according to claim 1, characterized in that: in step S4, the characteristic values include a road adhesion utilization module, a tire slip rate control module, a driving motor peak moment module, a driving motor failure module, and a yaw stability control module, and each of the actuator energy recovery weight modules selects a corresponding braking energy recovery control strategy according to the road adhesion utilization module, the tire slip rate control module, the driving motor peak moment module, the driving motor failure module, and the yaw stability control module, and allocates a weight value of the braking energy of each of the actuators;
the road surface adhesion utilization rate module is characterized in that the road surface adhesion utilization rate is correspondingly different due to the fact that road surface adhesion conditions are complex and changeable and road surface adhesion coefficients are different, and influences on lateral and longitudinal dynamics control of a vehicle are large; the maximum road adhesion force which can be provided for wheels by the ground is directly represented through the high and low conditions of the road adhesion utilization rate;
the tire slip rate control module acquires the tire dynamics state in real time, controls the slip rate in a linear stable region in real time, enables the tire to be close to the optimal slip rate, fully utilizes the road adhesion condition, and realizes the optimal control of the tire dynamics and the whole vehicle dynamics;
the driving motor peak torque module is used for monitoring the running state of the driving motor in real time, deciding the maximum torque which can be provided by the driving motor according to the driving motor peak torque state and playing a role in protecting the service life of the driving motor and controlling the control performance of the whole vehicle;
the driving motor failure module monitors the operation parameters of the driving motor in real time, and the driving motor has a complex structure and a complex and changeable use environment, so that the failure factor of each driving motor is uncertain, the failure of the driving motor directly influences the dynamic control stability control of the whole vehicle, the life and property safety of drivers and passengers is threatened, once the driving motor fails, the corresponding parameters are fed back to an upper controller, the optimal moment of the failed wheel is decided, the generation of an unexpected yaw moment of the vehicle is reduced, and the stability control and dynamic control range of the vehicle is increased;
the yaw stability control module is used for performing deviation correction control on the vehicle in real time according to the control input of the vehicle state parameter mass center side slip angle and the yaw angular speed, so that the driving safety is ensured, and the control of the vehicle dynamics manipulation stability is improved.
5. The method for recovering the braking energy of the distributed driving electric vehicle according to claim 1, characterized in that: in step S4, the BMS is a battery management system configured to monitor a battery operating state in real time, where the battery operating state includes battery remaining life prediction, battery temperature monitoring and control, and battery state of charge prediction.
6. The method for recovering the braking energy of the distributed driving electric vehicle according to claim 1, characterized in that: in step S4, the weight coefficient of the braking torque of each actuator means that the maximum expected braking torque that can be received by the drive motor occupies the weight in the expected braking torque of each actuator determined by the upper decision-making layer, and the weight coefficient is a determining factor for maximizing the recovery of braking energy; the actuators refer to braking torque of a driving motor and braking torque of a hydraulic brake.
7. The method for recovering the braking energy of the distributed driving electric vehicle according to claim 1, characterized in that: in step S5, the braking energy recovery module applies the braking torque of the driving motor to the driving motor according to the determined weight values of the braking energy recovery of each actuator, where different weight values have different energy recovery rates, so as to ensure that the braking torque of the driving motor is optimal in real time, and the driving motor is rotated reversely to charge the battery.
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