CN112606707A - Hydrogen fuel cell four-wheel hub motor driving plug-in controller and control method - Google Patents
Hydrogen fuel cell four-wheel hub motor driving plug-in controller and control method Download PDFInfo
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- 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
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- 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
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- 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
- B60L15/32—Control or regulation of multiple-unit electrically-propelled vehicles
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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
- B60L7/10—Dynamic electric regenerative 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
- B60L2220/00—Electrical machine types; Structures or applications thereof
- B60L2220/40—Electrical machine applications
- B60L2220/44—Wheel Hub motors, i.e. integrated in the wheel hub
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/10—Vehicle control parameters
- B60L2240/12—Speed
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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
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/10—Vehicle control parameters
- B60L2240/14—Acceleration
- B60L2240/16—Acceleration longitudinal
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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
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/10—Vehicle control parameters
- B60L2240/14—Acceleration
- B60L2240/18—Acceleration lateral
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention discloses a hydrogen fuel cell four-wheel hub motor driving plug-in controller, which comprises a processor, an angular velocity measuring module, a three-axial acceleration measuring module, a digital signal input module, an analog signal input module and a digital high-side output module, wherein the function separation of a hub motor differential torque control TVCU from a vehicle control unit VCU is realized, the requirement on the consumption of computing resources of a controller chip is reduced, and the cost of the differential torque controller is saved; the functions of the controllers are separated, and the risk of load unbalance on the CAN network is reduced; the control comprising two control functions is not required to be re-developed, so that the development period is saved; the control function of seamless integration of the differential torque control and the vehicle control unit of the hydrogen fuel cell full-power four-wheel hub motor driven vehicle is realized for the first time.
Description
Technical Field
The invention relates to the technical field of hub motors, in particular to a hydrogen fuel cell four-wheel hub motor driving plug-in controller and a control method.
Background
At present, a design mode of redevelopment of a whole Vehicle controller and embedding of distributed driving torque vector control of a hub motor is adopted for a hydrogen fuel cell full-power hub motor distributed driving new energy Vehicle, in the design mode, the distributed driving torque vector control of the hub motor relates to whole Vehicle multi-body dynamics analysis and complex algorithm development and calculation, a large amount of controller chip resources are consumed, and the cost of the whole Vehicle controller is required to be increased in order to improve the chip computing capability of a VCU (Vehicle control unit) of the whole Vehicle; and the functions of the whole vehicle Controller and the torque vector Controller are integrated in one Controller, so that the load pressure on a Controller Area Network (CAN) Network is increased, and the load imbalance is easy to generate. In addition, compared with a traditional pure electric vehicle, the hydrogen fuel cell extended-range power structure increases an interaction signal with a VCU of the whole vehicle, communication pressure on a CAN network is increased, and meanwhile, functions of the hub motor distributed driving torque vector controller TVCU and the VCU of the whole vehicle controller are combined and redeveloped, so that the development difficulty of controller software is increased, and the development period is prolonged.
The braking energy recovery and the drive anti-skid logic of the four-wheel hub motor-driven passenger car are in the theoretical research stage, and no mature and reliable scheme exists, so that the current four-wheel hub motor-driven passenger car does not have the functions of braking energy recovery and drive anti-skid.
Disclosure of Invention
The invention aims to provide a hydrogen fuel cell four-wheel hub motor driving plug-in controller and a control method, which realize the distributed driving control function of a hub motor, improve the maneuverability and stability of a finished automobile and simultaneously realize the personalized definition of the dynamic property and the economical efficiency of the finished automobile.
In order to achieve the purpose, the external hanging controller for driving the four-wheel hub motor of the hydrogen fuel cell comprises a processor, an angular velocity measuring module, a three-axial acceleration measuring module, a digital signal input module, an analog signal input module and a digital high-side output module, wherein the angular velocity measuring module is used for measuring the real-time yaw angular velocity, pitch angular velocity and roll angular velocity of a vehicle, the three-axial acceleration measuring module is used for measuring the real-time lateral acceleration, longitudinal acceleration and vertical acceleration of the vehicle, the digital signal input module is used for transmitting a digital signal of the running state of the vehicle to the processor, the analog signal input module is used for transmitting an analog signal of the running state of the vehicle to the processor, and the digital high-side output module is used for outputting hard wire enabling signals of the front axle hub motor and the rear axle hub motor under the control of the processor, the processor is used for acquiring driving intention information from the vehicle control unit;
the processor is used for carrying out braking energy recovery and driving antiskid control according to real-time yaw angular velocity, pitch angular velocity, rolling angular velocity, transverse acceleration, longitudinal acceleration, vertical acceleration, vehicle running state digital signals, vehicle running state analog signals and driving intention information of the vehicle to generate corresponding braking energy recovery control signals and driving antiskid control signals, the processor controls the front shaft hub motor controller and the rear shaft hub motor controller according to the braking energy recovery control signals to realize the whole vehicle braking energy recovery control function, and the processor controls the front shaft hub motor controller and the rear shaft hub motor controller according to the driving antiskid control signals to realize the whole vehicle driving antiskid control function.
A hydrogen fuel cell four-wheel hub motor driving torque vector control method comprises the following steps:
step 1: acquiring an ideal yaw rate of the vehicle by combining a two-degree-of-freedom model of the vehicle through basic parameters of the overall dimension of the vehicle and the mass of the whole vehicle, vehicle attitude data and road surface state data, wherein the ideal yaw rate of the vehicle is used as a real-time yaw rate following control target;
step 2: the angular velocity measuring module sends real-time yaw angular velocity, pitch angular velocity and roll angular velocity of the vehicle to the processor, the triaxial acceleration measuring module sends real-time transverse acceleration, longitudinal acceleration and vertical acceleration of the vehicle to the processor, the processor obtains real-time vehicle speed information of the vehicle according to the real-time yaw angular velocity, pitch angular velocity and roll angular velocity of the vehicle and the real-time transverse acceleration, longitudinal acceleration and vertical acceleration of the vehicle, the processor obtains driving intention information from the whole vehicle controller, and the processor obtains initial control moment of the four-wheel hub motor according to the driving intention information and the real-time vehicle speed information of the vehicle;
and step 3: designing a self-adaptive combined second-order sliding mode control model taking the real-time vehicle yaw angular velocity and the vehicle mass center side slip angle as control variables, and controlling a front axle hub motor controller and a rear axle hub motor controller by a processor through the self-adaptive combined second-order sliding mode control model to realize that an additional yaw moment is applied to the instability state of the whole vehicle and compensate the additional yaw moment on the initial control moment of a four-wheel hub motor;
and 4, step 4: the processor judges the vehicle running condition according to the vehicle running state digital signal transmitted by the digital signal input module and the vehicle running state analog signal transmitted by the analog signal input module, under the braking condition, the processor acquires ideal longitudinal acceleration according to a brake pedal stroke signal in the vehicle running state analog signal, the ideal longitudinal acceleration integrates time to acquire ideal longitudinal vehicle speed, the processor takes the vehicle longitudinal speed in the vehicle real-time vehicle speed information as actual longitudinal vehicle speed, and the processor controls the braking torque and braking energy recovery of the front axle hub motor controller and the rear axle hub motor controller through a sliding mode variable structure control model taking the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed as control variables, so that four-wheel compensation braking torque control under the vehicle energy recovery state is realized.
According to the invention, the functions of the hub motor torque vector control TVCU and the VCU of the vehicle control unit are separated, so that the requirement on the consumption of computing resources of a controller chip is reduced, and the cost of the differential torque controller is saved; the functions of the controllers are separated, and the risk of load unbalance on the CAN network is reduced; the control comprising two control functions is not required to be re-developed, so that the development period is saved; the control function of seamless integration of torque vector control and a vehicle controller of a hydrogen fuel cell full-power four-wheel hub motor driven vehicle is realized for the first time.
According to the invention, the VCU and the TVCU are separately designed, so that the requirements on respective hardware microprocessors are reduced, the load balancing problem is effectively improved, intermediate variable messages in the control process are reduced, the control logic is clearer, the TVCU is equivalent to the centralized calculation of differential torque compensation, and the calculation efficiency is improved.
The braking energy recovery function of the invention is used for being assembled on a four-wheel hub motor-driven passenger car, the battery of the four-wheel hub motor-driven passenger car consists of a hydrogen fuel cell and a pure power battery pack, and the energy storage of the pure power battery pack is far less than that of the pure electric car, so that the braking energy recovery of the whole car is precious.
The anti-skid driving function is used for being assembled on a four-wheel hub motor driven passenger car, the driving anti-skid function under the low-speed working condition can keep the dynamic property of the car, and the operating performance and the stability of the car can be improved under the high-speed working condition.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a schematic structural diagram of the present invention in use.
The system comprises a processor 1, an angular velocity measuring module 2, a triaxial acceleration measuring module 3, a CAN communication interface module 4, a digital signal input module 5, an analog signal input module 6, a vehicle control unit 7, a digital high-side output module 8, a digital bottom side output module 9, a front axle hub motor controller 10, a rear axle hub motor controller 11, an internal voltage monitoring module 12 and an electrifying enable and autonomous power-off module 13.
Detailed Description
The invention is described in further detail below with reference to the following figures and specific examples:
as shown in fig. 1 and 2, the hydrogen fuel cell four-wheel hub motor driving plug-in controller comprises a processor 1, an angular velocity measuring module 2, a three-axial acceleration measuring module 3, a digital signal input module 5, an analog signal input module 6 and a digital high-side output module 8, wherein the processor 1 can automatically perform self-check of a CPU unit, a clock unit and a storage unit, when a fault occurs, a response interrupt is generated to inform an application program to process, the angular velocity measuring module 2 is used for measuring the real-time yaw angular velocity, pitch angular velocity and roll angular velocity of a vehicle, the three-axial acceleration measuring module 3 is used for measuring the real-time lateral acceleration, longitudinal acceleration and vertical acceleration of the vehicle, the digital signal input module 5 is used for transmitting a vehicle running state digital signal to the processor 1, the analog signal input module 6 is used for transmitting a vehicle running state analog signal to the processor 1, the digital high-side output module 8 is used for outputting hard-line enabling signals (hard-line enabling signals of two hub motors of a rear shaft with a driving voltage of 12V and a driving current of 200mA and hard-line enabling signals of two hub motors of a front shaft) of the hub motor of the front shaft and the hub motor of the rear shaft under the control of the processor 1, and the processor 1 is used for acquiring driving intention information from the vehicle control unit 7;
the processor 1 is used for recovering braking energy and driving antiskid control according to real-time yaw angular velocity, pitch angular velocity, roll angular velocity, transverse acceleration, longitudinal acceleration, vertical acceleration, vehicle running state digital signals, vehicle running state analog signals and driving intention information of a vehicle to generate corresponding braking energy recovery control signals and driving antiskid control signals, the processor 1 controls the front axle hub motor controller 10 and the rear axle hub motor controller 11 to realize the whole vehicle braking energy recovery control function according to the braking energy recovery control signals, the processor 1 controls the front axle hub motor controller 10 and the rear axle hub motor controller 11 to realize the whole vehicle driving antiskid control function according to the driving antiskid control signals, and the CAN communication interface circuit module mainly comprises a CAN receiver and a CAN receiver which support four-way CAN communication to realize the assembly and disassembly of messages, filtering and checking of received information, etc.
In the above technical solution, the vehicle running state digital signals include two-way dual redundancy (one active high and one active low) signals of a brake pedal, three-way high level digital signals of a combination shifter shift logic, key ACC/START/ON electrical active digital signals, ESC high level digital signals, and the like;
the vehicle running state analog signal comprises a voltage signal of the oil pressure of a brake master cylinder, two redundant voltage signals of a driver stepping on an accelerator pedal, a voltage signal value representing the air pressure of a vacuum booster pump and the like.
In the above technical scheme, the vehicle-mounted controller further comprises a CAN communication interface module 4, and the processor 1 is used for respectively connecting the front axle hub motor controller 10, the rear axle hub motor controller 11 and the vehicle control unit 7 through the CAN communication interface module 4. The processor 1 is used as an external controller of the vehicle control unit 7 and is externally connected to a private CAN bus of the vehicle control unit 7, and the two front axle hub motors and the corresponding two hub motor controllers form a CAN signal path with the processor 1 independently; the two rear axle hub motors and the corresponding two hub motor controllers and the processor 1 independently form another CAN signal path.
In the above technical solution, the processor further includes an internal voltage monitoring module 12, where the internal voltage monitoring module 12 is configured to monitor an internal voltage of the processor 1, and ensure that the voltage is in a normal range.
In the above technical solution, the power-on enabling and autonomous power-off module 13 is further included, where the power-on enabling and autonomous power-off module 13 is configured to initialize the processor 1 when the processor 1 is powered on, and control the processor 1 to power off autonomously when the processor 1 is powered off. The controller has extremely low static power consumption, and when the ignition switch is turned off, the current in the controller does not exceed 1 mA. The power supply enabling function is benefited, only the power supply enabling circuit is in a working state under a static state, and the electric quantity of the storage battery can be effectively prevented from being excessively consumed under a parking state.
In the above technical solution, it further includes a digital bottom edge output module 9, where the digital bottom edge output module 9 is configured to output a cooling water pump driving signal and a vacuum pump relay driving signal (for supplying voltage 12V, current 200mA, suspended in default, a low-side driving digital output signal for lighting a backlight of an ESC switch, for supplying voltage 12V, current 200mA, suspended in default, a low-side driving digital output signal for closing the vacuum pump relay, for supplying voltage 12V, current 200mA, suspended in default).
In the technical scheme, the four-wheel hub motor drives the plug-in controller to receive power supply of a storage battery (12V) through a key switch; transmitting a high-voltage power-on request signal to wake up the controller through a CAN of the whole vehicle controller 7; the power-off request signal forwarded by the CAN of the vehicle control unit 7 and the motor direct-current bus voltage value forwarded to the controller under the control of the hub motor are used for judging whether the controller is in dormancy in accordance with the power-off condition, wherein the power-off condition is as follows: one is a power-off request signal (keyoff 1) forwarded by the vehicle controller 7 through the CAN network, and the other is whether a motor direct-current bus voltage value forwarded by the motor controller MCU through the CAN network is lower than a threshold value of 36V, because the cleaning work of the cell stack is performed before the hydrogen fuel cell is powered off for about five minutes, after the power-off instruction keyoff 1 is received by the power-off controller of the four-wheel in-wheel motor drive, it is necessary to wait for about 5 minutes of power-off of the battery pack, the voltage of the motor direct-current bus is reduced to below 36V by the battery pack, and when both conditions are satisfied, the four-wheel in-wheel motor drive external controller starts to execute power-off logic.
In the technical scheme, the processor 1 judges the vehicle running condition according to the vehicle running state digital signal transmitted by the digital signal input module 5 and the vehicle running state analog signal transmitted by the analog signal input module 6, under the braking condition, the processor 1 acquires ideal longitudinal acceleration according to a brake pedal travel signal in a vehicle running state simulation signal, the ideal longitudinal acceleration integrates time to acquire ideal longitudinal vehicle speed, the processor 1 takes the vehicle longitudinal speed in the vehicle real-time vehicle speed information as actual longitudinal vehicle speed, and the processor 1 controls the braking torque and braking energy recovery of the front axle hub motor controller 10 and the rear axle hub motor controller 11 through a sliding mode variable structure control model taking the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed as control variables to realize four-wheel compensation braking torque control under the vehicle braking energy recovery state.
In the technical scheme, the processor 1 judges the vehicle running condition according to the vehicle running condition digital signal transmitted by the digital signal input module 5 and the vehicle running condition analog signal transmitted by the analog signal input module 6, under the driving antiskid condition, the processor 1 adopts a standard tire and road surface Burckhardt model and fuzzy logic reasoning and correction to obtain an ideal road surface slip ratio, and obtains an actual road surface slip ratio through the wheel rotating speed, the wheel radius and the wheel longitudinal speed;
the ideal road surface slip rate and the actual road surface slip rate are used as the input of PID (proportion-integral-derivative control) control in the processor 1, the total wheel slip torque capable of adjusting the actual slip rate to the ideal road surface slip rate is decided through a PID feedback control model of the road surface slip rate, proportional, integral and derivative parameters (a PID control algorithm, which is a linear control model and does not contain a vehicle dynamics model and can not reflect the characteristics of a vehicle in the running state) during PID feedback control are corrected through fuzzy self-setting in the PID feedback control process, and once the three parameters of the PID are given, the three parameters of the PID do not change, and the driving anti-slip working condition is controlled by a pure PID linear algorithm between linear and nonlinear, so that the on-line setting of the three parameters of P, I, D is provided, that is, under the moving state of the vehicle, the P, I, D parameter is changed to adapt to the dynamic condition of the vehicle driving the antiskid. On-line, namely under the vehicle motion state, the more ideal feedback effect of PID is achieved by automatically adjusting P, I, D three parameters), and meanwhile, the problem of overshoot control of the slip rate during PID feedback control of the road slip rate is solved through PID feedforward control; the processor 1 compensates the wheel slip total torque to four wheels by controlling the front axle hub motor controller 10 and the rear axle hub motor controller 11, so as to realize the anti-slip control of the vehicle driving.
In the above technical scheme, the judgment standard of the driving antiskid working condition is as follows: the slip rate is greater than the maximum slip rate S of the conventional runningmax(most road surface optimum slip rates are 0.05-0.25) and the driver demand torque is greater than 0 (no intervention is detected when the driver releases the pedal completely, the status signal is simulated) while the key signal is in the ON gear (digital status signal).
A hydrogen fuel cell four-wheel hub motor driving torque vector control method is characterized by comprising the following steps:
step 1: acquiring an ideal yaw rate of the vehicle by combining a two-degree-of-freedom model of the vehicle through basic parameters of the overall dimension of the vehicle and the mass of the whole vehicle, vehicle attitude data and road surface state data, wherein the ideal yaw rate of the vehicle is used as a real-time yaw rate following control target;
step 2: the angular velocity measuring module 2 sends real-time yaw angular velocity, pitch angular velocity and roll angular velocity of the vehicle to the processor 1, the triaxial acceleration measuring module 3 sends real-time lateral acceleration, longitudinal acceleration and vertical acceleration of the vehicle to the processor 1, the processor 1 obtains real-time vehicle speed information of the vehicle according to the real-time yaw angular velocity, longitudinal acceleration and roll angular velocity of the vehicle and the real-time lateral acceleration, longitudinal acceleration and vertical acceleration of the vehicle, the processor 1 obtains driving intention information from the whole vehicle controller 7, and the processor 1 obtains initial control moment of the four-wheel hub motor through the driving intention information and the real-time vehicle speed information of the vehicle (the initial control moment is respectively superposed on four wheels through distribution principle moments of a control distribution module (CA);
and step 3: designing a self-adaptive combined second-order sliding mode control model taking a real-time vehicle yaw angular velocity and a vehicle mass center side slip angle (an included angle between a vehicle mass center velocity direction and a vehicle head direction) as control variables, and controlling a front axle hub motor controller 10 and a rear axle hub motor controller 11 by a processor 1 through the self-adaptive combined second-order sliding mode control model to realize that an additional yaw moment is applied to the instability state of the whole vehicle and compensate the additional yaw moment on an initial control moment of a four-wheel hub motor;
and 4, step 4: the processor 1 judges the vehicle running condition according to the vehicle running state digital signal transmitted by the digital signal input module 5 and the vehicle running state analog signal transmitted by the analog signal input module 6, under the braking condition, the processor 1 acquires ideal longitudinal acceleration according to a brake pedal travel signal in a vehicle running state simulation signal, the ideal longitudinal acceleration integrates time to acquire ideal longitudinal vehicle speed, the processor 1 takes the vehicle longitudinal speed in the vehicle real-time vehicle speed information as actual longitudinal vehicle speed, and the processor 1 controls the braking torque and braking energy recovery of the front axle hub motor controller 10 and the rear axle hub motor controller 11 through a sliding mode variable structure control model taking the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed as control variables to realize four-wheel compensation braking torque control under the vehicle braking energy recovery state (the four-wheel compensation braking torque is respectively superposed on four wheels through the distribution principle torque of a control distribution module (CA);
and 5: the processor 1 judges the vehicle running condition according to the vehicle running condition digital signal transmitted by the digital signal input module 5 and the vehicle running condition analog signal transmitted by the analog signal input module 6, under the driving antiskid condition, the processor 1 adopts a standard tire and road surface Burckhardt model and fuzzy logic reasoning correction to obtain an ideal road surface slip ratio (the corresponding optimal slip ratio of a peak value adhesion coefficient can be determined according to the relationship between the slip ratio and the road surface adhesion coefficient, and a standard tire-road surface Burckhardt model is established), and the actual road surface slip ratio is obtained through the wheel rotating speed, the wheel radius and the wheel longitudinal speed;
the ideal road surface slip rate and the actual road surface slip rate are used as the input of PID control in the processor 1, the total wheel slip torque which can adjust the actual slip rate to the ideal road surface slip rate is decided through a PID feedback control model of the road surface slip rate, the proportional, integral and differential parameters during PID feedback control are corrected through fuzzy self-setting in the PID feedback control process, and meanwhile, the problem of overshoot of slip rate control during PID feedback control of the road surface slip rate is solved through PID feedforward control; the processor 1 compensates the wheel slip total torque to four wheels by controlling the front axle hub motor controller 10 and the rear axle hub motor controller 11, so as to realize the anti-slip control of the vehicle driving.
In step 4 of the above technical scheme, the construction mode of the sliding mode variable structure with the ideal longitudinal speed and the actual vehicle longitudinal speed as control variables is as follows:
defining a sliding mode surface through the error between the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed, and designing a sliding mode approaching rule to approach the sliding mode surface by adopting an arc tangent function; obtaining the total ideal moment of the four wheels through the whole vehicle dynamic relation between the sliding mode surface and the whole vehicle rotational inertia; according to the fact that the braking torque of the front wheel and the braking torque of the rear wheel are in direct proportion to the normal force, the friction force of each wheel is utilized to the maximum extent, and the recovery rate of braking energy is improved; the relation between the braking efficiency and the braking torque is expressed by using a first-order cubic polynomial, the nonlinear non-convex band constraint optimization problem is solved through a Lagrange equation, so that a proper weight factor of the front axle braking energy conversion efficiency, a proper weight factor of the rear axle braking energy conversion efficiency and a value of the steady-state oscillation amplitude of the sliding mode motion are determined, a first-order Taylor formula is applied, a starting point approaching the sliding mode surface iteration is obtained, and a sliding mode surface coefficient is determined. The defect jitter problem of the sliding mode is realized by replacing sign(s) with 2/pi arctan (lambda · s), wherein lambda is a buffeting attenuation coefficient, sign(s) is a sign function in sliding mode control, s represents an approaching speed reaching a sliding mode surface, in the sliding mode control, due to the existence of the sign function sign(s), the system has the characteristic of discontinuous switch, the buffeting is easy to generate, the boundedness and the parity of a hyperbolic tangent function tanh (x) in a saturation function sat (x) are adopted, x represents the approaching speed of the system to the sliding mode surface and is equal to s, the graph is sandwiched between a horizontal straight line Y-1 and Y-1, Y is equal to sign(s), and represents a function value with s as an independent variable, and when the absolute value of x is large, its pattern is close to the straight line y-1 in the first quadrant and close to the straight line y-1 in the third quadrant. The hyperbolic tangent function tanh (x) replaces the sign function sgn (x) to design an approach law, so that buffeting generated in limited areas on two sides of the system when the system state approaches a switching surface and passes through the switching surface back and forth is inhibited, and smooth continuity of control input near the switching surface is ensured.
In the technical scheme, in order to obtain a smoother control variable curve, the interference and noise are filtered through the dynamically adjustable first-order inertia filtering, namely, random interference signals of ideal vehicle speed and distributed to wheel braking torque are filtered, and the smoothness degree of output signals and singular point filtering are facilitated to be improved. In the first-order inertia filtering aiming at the ideal vehicle speed, the input of the first-order inertia filtering is the ideal vehicle speed in a sampling period, the ideal vehicle speed in the last sampling period, a preset filtering coefficient, a time constant and the time of each period, and an ideal vehicle speed interference signal and a singular point are respectively filtered according to a first-order inertia filtering algorithm; in the first-order inertia filtering aiming at the real-time brake moment, the input of the inertia filtering is the brake moment in a sampling period, the brake moment in the last sampling period, a preset filtering coefficient, a time constant and the time of each period, and the brake moment interference signals and singular points are respectively filtered according to a dynamically adjustable first-order inertia filtering algorithm. Because the first-order inertial filtering algorithm cannot perfectly take sensitivity and stability into account, the technical scheme introduces an error threshold value, realizes dynamic adjustment of filtering amplitude, and finds a balance point between the sensitivity and the stability.
In step 1 of the above technical scheme, a complete vehicle two-degree-of-freedom model describing the motion characteristics of a vehicle is established, and the transfer function form of the yaw rate of the two-degree-of-freedom linear vehicle model to the front wheel steering angle response is as follows:
wherein:
wherein, K is the stability factor of the automobile (the unit is s2/m2, which is an important parameter for representing the steady-state response of the automobile), taurAs the response time constant, omega, of the vehiclenThe natural circular frequency of the system, zeta is the damping ratio of the automobile, KfIs the front axle equivalent yaw stiffness, KrEquivalent cornering stiffness, I, for the rear axlezIs the rotational inertia, omega, of the automobilerIdeal yaw rate, L wheel base, VxFor the longitudinal speed, K, of the vehiclefEquivalent cornering stiffness, K, for the front wheelrEquivalent cornering stiffness of the rear wheel, m is the vehicle mass, a is the distance from the center of mass to the front axle, b is the distance from the center of mass to the rear axle, GrThe vehicle stability gain is, delta is the front wheel rotation angle, and s is the independent variable of the transfer function; the response time constant is 1/e, and e represents the actual growth rate of continuous growth when the nominal base growth rate is 1; the damping ratio is a unitless dimension and represents the damped form of the structure vibrating after being excited. The damping ratio can be divided into 4 types of damping ratios which are equal to 1, equal to 0, more than 1 and between 0 and 1, namely the damping system is not considered, and the damping ratio which is common in the structure is between 0 and 1; 1. the damping ratio ξ ═ 0, called undamped; 2. damping ratio of 0<ξ<1, known as underdamping; 3. the damping ratio ξ ═ 1, called critical damping; 4. damping ratio xi>1, called over-damping.
The yaw rate response process can be completely expressed as follows:
as can be seen from the formula, the reference yaw rate includes both transient and steady-state components. Setting ideal damping ratio xi to 0.707; in order to improve the steering characteristic of the automobile to approach neutral steering, a reference model K is reduced on the basis of the original automobile; in order to improve the response speed of the vehicle, the natural frequency of the reference model is improved on the basis of the original vehicle. Precisely because of the yaw rate of the vehicle and the k, omeganAnd xi have the relationship, so the ideal characteristics of the vehicle can be designed through three parameters, the deviation between the ideal yaw rate and the actual yaw rate calculated according to the automobile reference model is used as a feedback quantity to carry out yaw moment decision, and the decided additional yaw moment is superposed and acted on each wheel through moment distribution, thereby realizing moment vector control and improving the automobile maneuverability.
The front-rear axis equivalent cornering stiffness Kf and Kr are key parameters in a two-degree-of-freedom model, and are obtained through angle pulse tests at different vehicle speeds and calculated by an ARMAX equivalent cornering stiffness distinguishing module. Through angle pulse tests under different vehicle speeds (40km/h, 50km/h, 60km/h, 70km/h and 80km/h), the equivalent lateral deflection rigidity of the front and rear shafts under different vehicle speeds is identified. On the premise of obtaining front and rear axle equivalent yaw stiffness corresponding to different vehicle speeds, the front and rear axle equivalent yaw stiffness between the two vehicle speeds is obtained through a linear interpolation method, and finally a two-dimensional truth table of the vehicle speed and the front and rear axle equivalent yaw stiffness is obtained.
A Torque Vector Controller (TVCU), namely a processor 1 obtains acceleration signals from an angular velocity measuring module 2 (a gyroscope) and a triaxial acceleration measuring module 3 (an accelerometer) through CAN signals, and obtains the longitudinal speed of the whole vehicle finally through time integration to serve as the actual speed of the whole vehicle; acceleration analyzed by the travel of the brake pedal acquired by the driving intention recognition module is used as the ideal speed of the whole vehicle, and the expected speed of the driver is obtained by integrating time.
In step 3 of the above technical scheme, the yaw rate and the centroid slip angle are two most basic reference characteristic quantities reflecting the driving stability of the automobile, the former mainly emphasizes the basic characteristic quantity of the stability problem of the automobile, reflects the speed of the change of the course angle in the driving process of the automobile, and determines the steering characteristic of the automobile; the latter emphasizes the basic characteristic quantity of the automobile track keeping problem and reflects the deviation degree of the automobile from the preset track in the steering process. The sliding mode control is based on two control variables of yaw velocity and mass center side slip angle, the ideal yaw velocity of the vehicle is obtained on the basis of a linear two-degree-of-freedom model of the whole vehicle, the ideal yaw velocity is used as a vehicle control following target to obtain a compensation yaw moment, an additional yaw moment is applied to the instability state of the whole vehicle, the compensation yaw moment is compensated on the initial control moment of four wheels of a hub, and the stability of the whole vehicle is further improved. The control strategy for compensating the additional yaw moment, which is decided by a torque vector distribution strategy module (TVC) module, is disclosed in the invention patent CN201910814242.7 'Combined second-order sliding mode control method for moment compensation of four-wheel hub motor-driven vehicles'.
In step 5 of the above technical scheme, according to the relationship between the slip ratio and the road adhesion coefficient, the optimal slip ratio corresponding to the peak adhesion coefficient of the ground can be determined. Obtaining ideal optimal road surface slip by adopting a standard tire-road surface Burckhardt model and fuzzy logic reasoning correctionRate; driving an anti-skid PID control algorithm, taking the optimal slip rate and the error between the optimal slip rate and the actual slip rate as the input of a PID controller, and adjusting the actual slip rate to be close to the optimal slip rate through a PID control model; in order to correct the overshoot problem of slip rate control during PID feedback, the judgment of the optimal slip rate change rate (the second derivative of the optimal slip rate) and PID feedforward torque compensation are added; k for reflecting control law by traditional PID controlp、Ki、KdOnce the three parameters are fixed, the three parameters cannot be adjusted online, P, I, D parameter self-adjusting logic based on fuzzy control is added to ensure the robustness of PID control, the application robustness of PID in a nonlinear state is increased by online adjusting of P, I, D parameters, and a driving anti-skid P, I, D parameter fuzzy online self-adjusting control method of an incremental adjusting structure is adopted.
And (3) determining a dynamic compensation principle of the slip torque: the power performance is guaranteed by the slip and rotation during low-speed running, the transverse stability is guaranteed during high-speed running, and both conditions are usually met; compensation logic for different slip conditions: single-wheel slip, same-side slip, coaxial slip and multi-wheel slip. For single-wheel slip, firstly, the principle of dynamic property and transverse stability is simultaneously satisfied, torque compensation is carried out on the other wheels on the same side, when the condition is not satisfied, a vehicle speed threshold value of slip torque compensation is set, the vehicle speed threshold value is lower than the vehicle speed threshold value and mainly satisfies the dynamic property, and the vehicle speed threshold value is higher than the vehicle speed threshold value and satisfies the requirement of yaw stability; the wheels on the same side rotate in a sliding mode, and when the speed is higher than a speed threshold value, the moment of the wheels on the non-sliding side is reduced to be equal to that of the wheels on the sliding side; when the vehicle speed is lower than the vehicle speed threshold value, the reduced driving torque of the slip side is transferred to the corresponding wheel on the same side; the coaxial wheels are in slip rotation, and when the speed of the vehicle is lower than a vehicle speed threshold value, the moment reduced by the front wheels due to the driving anti-slip control is transferred to the corresponding rear axle wheels; when the vehicle speed is higher than the vehicle speed threshold value, setting an unbalanced torque threshold Tden. The moment difference of the left wheel and the right wheel is less than TdenThe moment difference of the left wheel and the right wheel of the current axle is larger than T without moment transferdenThe unbalanced moment is transferred to rear axle wheels to offset the differential torque yaw moment generated by the front axle due to anti-skid control, so as to prevent the generation of the unexpected yaw moment during high-speed driving; multi-wheel vehicle wheel slipWhen the vehicle speed is higher than the vehicle speed threshold value, the torque control is based on a low selection principle, and the four wheel torques are equal to the minimum wheel torque at the same time; when the vehicle speed is lower than the vehicle speed threshold value, the three wheels slip, and the torque reduced by the slip is transferred to the wheels which do not slip; and if the four wheels all rotate in a sliding mode, the moment dynamic compensation is not carried out.
Details not described in this specification are within the skill of the art that are well known to those skilled in the art.
Claims (10)
1. The utility model provides a hydrogen fuel cell four-wheel in-wheel motor drive joins externally controller which characterized in that: the device comprises a processor (1), an angular velocity measuring module (2), a triaxial acceleration measuring module (3), a digital signal input module (5), an analog signal input module (6) and a digital high-side output module (8), wherein the angular velocity measuring module (2) is used for measuring the real-time yaw angular velocity, pitch angular velocity and roll angular velocity of a vehicle, the triaxial acceleration measuring module (3) is used for measuring the real-time lateral acceleration, longitudinal acceleration and vertical acceleration of the vehicle, the digital signal input module (5) is used for transmitting a vehicle running state digital signal to the processor (1), the analog signal input module (6) is used for transmitting a vehicle running state analog signal to the processor (1), the digital high-side output module (8) is used for outputting hard wire enabling signals of a front axle hub motor and a rear axle hub motor under the control of the processor (1), the processor (1) is used for acquiring driving intention information from the vehicle control unit (7);
the processor (1) is used for carrying out braking energy recovery and driving antiskid control according to real-time yaw angular velocity, pitch angular velocity, roll angular velocity, transverse acceleration, longitudinal acceleration, vertical acceleration, vehicle running state digital signals, vehicle running state analog signals and driving intention information of a vehicle to generate corresponding braking energy recovery control signals and driving antiskid control signals, the processor (1) controls the front shaft hub motor controller (10) and the rear shaft hub motor controller (11) according to the braking energy recovery control signals to realize the whole vehicle braking energy recovery control function, and the processor (1) controls the front shaft hub motor controller (10) and the rear shaft hub motor controller (11) according to the driving antiskid control signals to realize the whole vehicle driving antiskid control function.
2. The hydrogen fuel cell four-wheel in-wheel motor drive externally hung controller according to claim 1, characterized in that: the vehicle-mounted controller is characterized by further comprising a CAN communication interface module (4), wherein the processor (1) is used for being respectively connected with a front axle hub motor controller (10), a rear axle hub motor controller (11) and a vehicle control unit (7) through the CAN communication interface module (4).
3. The hydrogen fuel cell four-wheel in-wheel motor drive externally hung controller according to claim 1, characterized in that: it further comprises an internal voltage monitoring module (12), said internal voltage monitoring module (12) being adapted to monitor an internal voltage of the processor (1).
4. The hydrogen fuel cell four-wheel in-wheel motor drive externally hung controller according to claim 1, characterized in that: the power-on and power-off control system further comprises a power-on enabling and power-off module (13), wherein the power-on enabling and power-off module (13) is used for initializing the processor (1) when the processor (1) is powered on and controlling the processor (1) to power off autonomously when the processor (1) is powered off.
5. The hydrogen fuel cell four-wheel in-wheel motor drive externally hung controller according to claim 1, characterized in that: the device also comprises a digital bottom edge output module (9), wherein the digital bottom edge output module (9) is used for outputting a cooling water pump driving signal and a vacuum pump relay driving signal under the control of the processor (1).
6. The hydrogen fuel cell four-wheel in-wheel motor drive externally hung controller according to claim 1, characterized in that: the processor (1) judges the vehicle running condition according to the vehicle running state digital signal transmitted by the digital signal input module (5) and the vehicle running state analog signal transmitted by the analog signal input module (6), under the braking condition, the processor (1) acquires ideal longitudinal acceleration according to a brake pedal travel signal in a vehicle running state analog signal, the ideal longitudinal acceleration integrates time to acquire ideal longitudinal vehicle speed, the processor (1) takes the vehicle longitudinal speed in vehicle real-time vehicle speed information as actual longitudinal vehicle speed, and the processor (1) controls the braking torque and braking energy recovery of the front axle hub motor controller (10) and the rear axle hub motor controller (11) through a sliding mode variable structure control model taking the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed as control variables, so that four-wheel compensation braking torque control under the vehicle braking energy recovery state is realized.
7. The hydrogen fuel cell four-wheel in-wheel motor drive externally hung controller according to claim 1, characterized in that: the processor (1) judges the vehicle running condition according to the vehicle running condition digital signal transmitted by the digital signal input module (5) and the vehicle running condition analog signal transmitted by the analog signal input module (6), under the driving antiskid condition, the processor (1) adopts a standard tire and road surface Burckhardt model and fuzzy logic reasoning and correction to obtain an ideal road surface slip rate, and obtains an actual road surface slip rate through the wheel rotating speed, the wheel radius and the wheel longitudinal speed;
the ideal road surface slip rate and the actual road surface slip rate are used as the input of PID control in a processor (1), the total wheel slip torque which can adjust the actual slip rate to the ideal road surface slip rate is decided through a PID feedback control model of the road surface slip rate, the proportional, integral and differential parameters during PID feedback control are corrected through fuzzy self-setting in the PID feedback control process, and meanwhile, the problem of overshoot of slip rate control during PID feedback control of the road surface slip rate is solved through PID feedforward control; the processor (1) compensates the wheel slip total moment to four wheels by controlling the front axle hub motor controller (10) and the rear axle hub motor controller (11), so as to realize the anti-slip control of the vehicle driving.
8. A hydrogen fuel cell four-wheel hub motor driving torque vector control method is characterized by comprising the following steps:
step 1: acquiring an ideal yaw rate of the vehicle by combining a two-degree-of-freedom model of the vehicle through basic parameters of the overall dimension of the vehicle and the mass of the whole vehicle, vehicle attitude data and road surface state data, wherein the ideal yaw rate of the vehicle is used as a real-time yaw rate following control target;
step 2: the method comprises the following steps that an angular velocity measuring module (2) sends real-time yaw angular velocity, pitch angular velocity and roll angular velocity of a vehicle to a processor (1), a triaxial acceleration measuring module (3) sends real-time transverse acceleration, longitudinal acceleration and vertical acceleration of the vehicle to the processor (1), the processor (1) obtains real-time vehicle speed information of the vehicle according to the real-time yaw angular velocity, pitch angular velocity and roll angular velocity of the vehicle and the real-time transverse acceleration, longitudinal acceleration and vertical acceleration of the vehicle, the processor (1) obtains driving intention information from a whole vehicle controller (7), and the processor (1) obtains initial control moment of a four-wheel hub motor through the driving intention information and the real-time vehicle speed information of the vehicle;
and step 3: designing a self-adaptive combined second-order sliding mode control model taking the real-time vehicle yaw angular velocity and the vehicle mass center side slip angle as control variables, and controlling a front axle hub motor controller (10) and a rear axle hub motor controller (11) by a processor (1) through the self-adaptive combined second-order sliding mode control model to realize the application of an additional yaw moment to the instability state of the whole vehicle and compensate the additional yaw moment on the initial control moment of a four-wheel hub motor;
and 4, step 4: the processor (1) judges the vehicle running condition according to the vehicle running state digital signal transmitted by the digital signal input module (5) and the vehicle running state analog signal transmitted by the analog signal input module (6), under the braking condition, the processor (1) acquires ideal longitudinal acceleration according to a brake pedal travel signal in a vehicle running state analog signal, the ideal longitudinal acceleration integrates time to acquire ideal longitudinal vehicle speed, the processor (1) takes the vehicle longitudinal speed in vehicle real-time vehicle speed information as actual longitudinal vehicle speed, and the processor (1) controls the braking torque and braking energy recovery of the front axle hub motor controller (10) and the rear axle hub motor controller (11) through a sliding mode variable structure control model taking the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed as control variables, so that four-wheel compensation braking torque control under the vehicle braking energy recovery state is realized.
9. The hydrogen fuel cell four-wheel in-wheel motor drive torque vectoring method as claimed in claim 8, wherein: step 4 is followed by step 5: the processor (1) judges the vehicle running condition according to the vehicle running condition digital signal transmitted by the digital signal input module (5) and the vehicle running condition analog signal transmitted by the analog signal input module (6), under the driving antiskid condition, the processor (1) adopts a standard tire and road surface Burckhardt model and fuzzy logic reasoning and correction to obtain an ideal road surface slip rate, and obtains an actual road surface slip rate through the wheel rotating speed, the wheel radius and the wheel longitudinal speed;
the ideal road surface slip rate and the actual road surface slip rate are used as the input of PID control in a processor (1), the total wheel slip torque which can adjust the actual slip rate to the ideal road surface slip rate is decided through a PID feedback control model of the road surface slip rate, the proportional, integral and differential parameters during PID feedback control are corrected through fuzzy self-setting in the PID feedback control process, and meanwhile, the problem of overshoot of slip rate control during PID feedback control of the road surface slip rate is solved through PID feedforward control; the processor (1) compensates the wheel slip total moment to four wheels by controlling the front axle hub motor controller (10) and the rear axle hub motor controller (11), so as to realize the anti-slip control of the vehicle driving.
10. The hydrogen fuel cell four-wheel in-wheel motor drive torque vectoring method as claimed in claim 8, wherein: in the step 4, the construction mode of the sliding mode variable structure with the ideal longitudinal speed and the actual vehicle longitudinal speed as control variables is as follows:
defining a sliding mode surface through the error between the ideal longitudinal vehicle speed and the actual longitudinal vehicle speed, and designing a sliding mode approaching rule to approach the sliding mode surface by adopting an arc tangent function; obtaining the total ideal moment of the four wheels through the whole vehicle dynamic relation between the sliding mode surface and the whole vehicle rotational inertia; according to the fact that the braking torque of the front wheel and the braking torque of the rear wheel are in direct proportion to the normal force, the friction force of each wheel is utilized to the maximum extent, and the recovery rate of braking energy is improved; the relation between the braking efficiency and the braking torque is expressed by using a first-order cubic polynomial, the nonlinear non-convex band constraint optimization problem is solved through a Lagrange equation, so that a proper weight factor of the front axle braking energy conversion efficiency, a proper weight factor of the rear axle braking energy conversion efficiency and a value of the steady-state oscillation amplitude of the sliding mode motion are determined, a first-order Taylor formula is applied, a starting point approaching the sliding mode surface iteration is obtained, and a sliding mode surface coefficient is determined.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105501078A (en) * | 2015-11-26 | 2016-04-20 | 湖南大学 | Cooperative control method of four-wheel independent-drive electric car |
| CN108001294A (en) * | 2017-11-20 | 2018-05-08 | 清华大学 | A kind of network topology structure of electric wheel truck vector control system |
| CN109795338A (en) * | 2018-12-20 | 2019-05-24 | 清华大学 | A kind of vector control method for electric wheel truck |
| CN110341497A (en) * | 2019-07-17 | 2019-10-18 | 东风汽车集团有限公司 | System and method for promoting four-wheel In-wheel motor driving control stability |
| CN110466359A (en) * | 2019-08-05 | 2019-11-19 | 东风汽车集团有限公司 | Wheel hub 4 wheel driven pure electric automobile torque vector control system and control method |
| CN110466361A (en) * | 2019-08-14 | 2019-11-19 | 东风汽车集团有限公司 | Two-wheeled In-wheel motor driving pure electric vehicle controller and control method |
| CN110481343A (en) * | 2019-08-30 | 2019-11-22 | 东风汽车集团有限公司 | The combination Second Order Sliding Mode Control method of four-wheel In-wheel motor driving automobile torque compensation |
-
2020
- 2020-12-23 CN CN202011541121.9A patent/CN112606707B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105501078A (en) * | 2015-11-26 | 2016-04-20 | 湖南大学 | Cooperative control method of four-wheel independent-drive electric car |
| CN108001294A (en) * | 2017-11-20 | 2018-05-08 | 清华大学 | A kind of network topology structure of electric wheel truck vector control system |
| CN109795338A (en) * | 2018-12-20 | 2019-05-24 | 清华大学 | A kind of vector control method for electric wheel truck |
| CN110341497A (en) * | 2019-07-17 | 2019-10-18 | 东风汽车集团有限公司 | System and method for promoting four-wheel In-wheel motor driving control stability |
| CN110466359A (en) * | 2019-08-05 | 2019-11-19 | 东风汽车集团有限公司 | Wheel hub 4 wheel driven pure electric automobile torque vector control system and control method |
| CN110466361A (en) * | 2019-08-14 | 2019-11-19 | 东风汽车集团有限公司 | Two-wheeled In-wheel motor driving pure electric vehicle controller and control method |
| CN110481343A (en) * | 2019-08-30 | 2019-11-22 | 东风汽车集团有限公司 | The combination Second Order Sliding Mode Control method of four-wheel In-wheel motor driving automobile torque compensation |
Non-Patent Citations (1)
| Title |
|---|
| 李刚: "线控四轮独立驱动轮毂电机电动汽车稳定性与节能控制研究", 《吉林大学博士学位论文》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113177267A (en) * | 2021-05-26 | 2021-07-27 | 浙江大学 | Full-process multidisciplinary modeling method based on improved fuzzy PID |
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