CN109555849B - Gear shifting strategy optimization and accurate tracking control method for electric vehicle - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000005457 optimization Methods 0.000 title claims description 6
- 239000011159 matrix material Substances 0.000 claims description 21
- 230000005540 biological transmission Effects 0.000 claims description 7
- 238000013016 damping Methods 0.000 claims description 6
- 238000005096 rolling process Methods 0.000 claims description 6
- 239000003638 chemical reducing agent Substances 0.000 claims description 4
- 230000001133 acceleration Effects 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000005299 abrasion Methods 0.000 abstract description 4
- 238000011084 recovery Methods 0.000 abstract description 3
- 230000002035 prolonged effect Effects 0.000 abstract description 2
- 238000011217 control strategy Methods 0.000 description 8
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H61/04—Smoothing ratio shift
- F16H61/0437—Smoothing ratio shift by using electrical signals
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H61/02—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used
- F16H61/0202—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric
- F16H61/0204—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal
- F16H61/0213—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal characterised by the method for generating shift signals
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
- F16H2061/0093—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method using models to estimate the state of the controlled object
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H61/02—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used
- F16H61/0202—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric
- F16H61/0204—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal
- F16H61/0213—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal characterised by the method for generating shift signals
- F16H2061/0223—Generating of new shift maps, i.e. methods for determining shift points for a schedule by taking into account driveline and vehicle conditions
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- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Hydraulic Clutches, Magnetic Clutches, Fluid Clutches, And Fluid Joints (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a method for optimizing and accurately tracking and controlling a gear shifting strategy of an electric vehicle, which comprises the following steps: aiming at specific objects, determining an optimized control target of the gear shifting process of the electric automobile: step two: establishing a gear shifting process physical model; step three: and designing a model predictive control algorithm, improving the robustness of the system and accurately tracking the optimal control track. Compared with the prior art, the invention can comprehensively consider the aims of the duration of the gear shifting process, the gear shifting impact degree, the sliding abrasion power and the like, and is suitable for the gear shifting process of multiple gears. The cooperative control of the driving motor and the clutch can be realized, and the recovery process of the motor torque is completed while the gear shifting quality is ensured. The robustness of tracking the established gear shifting strategy is high, the gear shifting quality is stable, and the service life of the clutch is prolonged.
Description
Technical Field
The invention relates to the technical field of electric automobiles, in particular to a gear shifting strategy optimization and accurate tracking control method for an electric automobile.
Background
The gear shifting control strategy is one of the core contents of automobile control, and has decisive influence on the dynamic property, the economical efficiency and the gear shifting smoothness of the whole automobile. For a pure electric automobile provided with a multi-gear mechanical transmission, an electric motor converts electric energy into mechanical energy to drive the automobile to run, and the gear shifting process of the pure electric automobile has power interruption.
The main control strategies in the field of automobiles at present are as follows:
1) summarizing excellent driver experience, establishing a fuzzy rule base, judging the intention of a driver by acquiring the rotation speed of an engine, the opening degree of an accelerator and the current gear information, and determining the combination amount of a clutch by fuzzy control.
2) And (4) considering the vehicle impact degree and the sliding abrasion power, and deducing the optimal combination track of the clutch based on the minimum value and the linear quadratic optimal control theory.
3) And determining a target engine speed change rate according to the current gear and the accelerator pedal opening, and then controlling the engine speed change rate to be kept near the target value through closed-loop control, wherein the control quantity is the clutch position.
4) And planning a clutch rotation speed difference track through the accelerator opening and the engine rotation speed.
5) The increment of the clutch control pressure is obtained by acquiring the difference and the change between the actual rotating speed of the engine and the target rotating speed of the engine, or the difference and the change between the output torque of the transmission and the target torque.
6) The strategy is only suitable for a pure electric vehicle provided with a two-gear transmission, and power uninterrupted gear shifting is realized by optimizing the overall structure of a transmission-clutch system and utilizing smooth transition of torques of a synchronizer and a clutch.
Existing shift control strategies have some significant drawbacks, mainly: the gear shifting process is not planned, the combination quantity of the clutch is determined only through the collected automobile running state and the output signal of the driver, and the goals of the gear shifting process such as duration, gear shifting impact degree and sliding abrasion power are not comprehensively considered; because the output torque of the engine is difficult to control, a control strategy is only established aiming at the combination control of the clutch; the gear shifting strategy for realizing uninterrupted power through structural optimization is only suitable for back-and-forth switching between two gears and cannot be suitable for a multi-gear shifting process.
The existing control strategy of pure electric is greatly different from that of the traditional fuel automobile, the torque of the driving motor can be controlled, the key point of the gear shifting strategy is the cooperative control of the driving motor and the clutch, and the recovery process of the motor torque is required to be completed while the gear shifting quality is ensured.
The accurate realization of the established gear shifting strategy is another difficulty of the gear shifting process, the established gear shifting strategy is tracked by a control mode combining PID, PID and fuzzy control, the robustness is poor, if external interference exists in the control process, control signals can vibrate, the gear shifting quality is seriously influenced, and the service life of a clutch can be lost even in serious conditions.
Disclosure of Invention
The invention mainly aims to provide a method for optimizing and accurately tracking and controlling a gear shifting strategy of an electric vehicle, so as to solve the problem that the gear shifting control strategy of the vehicle in the prior art is poor and medium.
In order to achieve the purpose, the electric vehicle gear shifting strategy optimization and accurate tracking control method comprises the following steps:
the method comprises the following steps: aiming at specific objects, determining an optimized control target of the gear shifting process of the electric automobile:
1) determining a target impact degree limit value in the gear shifting process;
2) determining a target range for a shift event duration;
3) the transmission torque change in the whole process is ensured to be stable; one important measurement index is the gear shifting end time, the torque of the driving motor should be equal to the friction torque of the clutch, and the smooth transition of the torque is ensured
4) Determining a target torque needing to be recovered by the motor according to the opening ratio of 0-1 of the current power pedal, wherein the target torque is To＝αTm_maxWherein T isoIs a target torque, alpha is a power pedal opening, Tm_maxThe maximum output torque of the motor;
5) the difference between the rotating speeds of the driving part and the driven part of the clutch is zero at the moment of gear shifting ending;
step two: establishing a physical model of a gear shifting process:
the specific values of the following parameters of each gear are obtained through experiments, sensor measurement and data query: the equivalent rotary inertia of a clutch driving part, the equivalent rotary inertia of a clutch driven part, the rotary inertia of a clutch input shaft, the rotary inertia of a driving motor, the rotary inertia of a clutch output shaft, the rotary inertia of wheels, the equivalent damping coefficient of the clutch driving part, the equivalent damping coefficient of the clutch driven part, the torque of the driving motor, the friction torque of the clutch, the speed ratio of a speed changer, the speed ratio of a main reducer, the rolling radius of the wheels, the mass of an automobile, the gravity acceleration, the rolling friction coefficient, the road gradient, the air resistance coefficient, the windward area, the speed of the automobile, the rotating speed of the clutch driving part, the rotating speed of the clutch driven part, the rotating speed difference of the clutch, and the driving resistance torque,
a system state differential equation is constructed and written in the form of a state space equation:
y(t)＝Cx(t)
selecting a system state quantity:
x＝[x1,x2,x3,x4,x5,x6]Τ＝[ωm,Δω,Tm-To,Tc-To,To,Tf]Τ；
selecting a system control quantity:
selecting system output quantity: y ═ ωm,ωc,Tm,Tc]Τ；
ωmRepresenting motor speed, ωcIndicating the motor control speed, TmRepresenting motor output torque, TcWhich represents the motor control torque and is,
representing the derivative of the drive motor torque with respect to time,
expressed as the derivative of clutch friction torque with time, TfRepresenting vehicle running resistance torque;
step three: designing a model predictive control algorithm, improving the robustness of the system and accurately tracking an optimal control track;
discretizing the system state space equation into the form
Performance index function J punishs and predicts controlled output and reference track yrefThe deviation between (k + j | k) is defined as follows:
where N denotes the length of the prediction time domain, NcRepresenting the length of the control time domain, Q (j) is a state quantity symmetric weight matrix used for predicting y (k + j | k) -y in the time domainrefPunishment is carried out on the point (k + j | k), R (j) is a control quantity symmetric weight matrix which is used for punishment on the change of the control time domain state quantity,
according to the actual condition of the system, determining the specific values of the sampling time and the weight matrix of a control time domain, a prediction time domain and a model prediction control algorithm;
a sufficient requirement for the system output to be fully controllable is the matrix [ CB CAB CA2B…CAn-1B]The rank of (2) is equal to the dimension of the output matrix y, the output controllability of the system is judged according to the output complete controllable matrix,
the predicted state quantities of the model can be expressed in a matrix manner as:
the constraints of the model predictive controller are:
ωm∈[-nm_maxπ/30,nm_maxπ/30](rad/s)
ωc∈[-nm_maxπ/30,nm_maxπ/30](rad/s)
Tm∈[-Tm_max,Tm_max](Nm)
Tc∈[-Tm_max,Tm_max](Nm)
wherein n ism_maxThe maximum rotation speed of the driving motor.
The inputs to the model predictive controller are:
1) the optimal control tracks of the torque of the driving motor, the friction torque of the clutch, the rotating speed of a driving part of the clutch and the rotating speed of a driven part of the clutch are obtained based on a linear quadratic optimal control theory;
2) the system is subjected to external disturbance, including measurable disturbance and immeasurable disturbance, and possible sources of the disturbance include uneven ground, disturbed sensor signals, automobile resistance moment change in the gear shifting process and state quantity disturbance signals caused by reasons;
3) the actual state values of the gear shifting system comprise the torque of a driving motor, the friction torque of a clutch, the rotating speed of a driving part of the clutch and the rotating speed of a driven part of the clutch under the actual condition;
the output of the model predictive controller is: a signal of a control quantity solved by the model predictive controller;
solving a quadratic programming problem which takes the acquisition of each step of control signals of model predictive control as a standard, and obtaining an optimal control solution delta u by solving the minimum value of each step of performance functionopt(k) Based on the control signal u (k-1) of the previous step, the predicted control signal u (k) of each step can be obtained.
Compared with the existing gear shifting control strategy, the gear shifting control strategy can comprehensively consider the aims of the duration of the gear shifting process, the gear shifting impact degree, the sliding abrasion power and the like, and is suitable for the gear shifting process of multiple gears. The cooperative control of the driving motor and the clutch can be realized, and the recovery process of the motor torque is completed while the gear shifting quality is ensured. The robustness of tracking the established gear shifting strategy is high, the gear shifting quality is stable, and the service life of the clutch is prolonged.
The present invention will be further described with reference to the following embodiments. Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
FIG. 1 shows a power transmission path in an electric vehicle according to the present invention.
Detailed Description
The invention discloses a method for optimizing and accurately tracking and controlling a gear shifting strategy of an electric vehicle, which comprises the following steps of:
the method comprises the following steps: aiming at specific objects, determining an optimized control target of the gear shifting process of the electric automobile:
1) determining a target impact degree limit value in the gear shifting process;
2) determining a target range for a shift event duration;
3) the transmission torque change in the whole process is ensured to be stable; one important measurement index is the gear shifting end time, the torque of the driving motor should be equal to the friction torque of the clutch, and the smooth transition of the torque is ensured
4) Determining a target torque needing to be recovered by the motor according to the opening ratio of 0-1 of the current power pedal, wherein the target torque is To＝αTm_maxWherein T isoIs a target torque, alpha is a power pedal opening, Tm_maxThe maximum output torque of the motor;
5) the difference between the rotating speeds of the driving part and the driven part of the clutch is zero at the moment of gear shifting ending;
step two: establishing a physical model of a gear shifting process:
the specific values of the following parameters of each gear are obtained through experiments, sensor measurement and data query: the equivalent rotary inertia of a clutch driving part, the equivalent rotary inertia of a clutch driven part, the rotary inertia of a clutch input shaft, the rotary inertia of a driving motor, the rotary inertia of a clutch output shaft, the rotary inertia of wheels, the equivalent damping coefficient of the clutch driving part, the equivalent damping coefficient of the clutch driven part, the torque of the driving motor, the friction torque of the clutch, the speed ratio of a speed changer, the speed ratio of a main reducer, the rolling radius of the wheels, the mass of an automobile, the gravity acceleration, the rolling friction coefficient, the road gradient, the air resistance coefficient, the windward area, the speed of the automobile, the rotating speed of the clutch driving part, the rotating speed of the clutch driven part, the rotating speed difference of the clutch, and the driving resistance torque,
as shown in fig. 1, the power transmission path in the electric vehicle is: the driving method comprises the following steps that (1) a driving motor, 2-a clutch, 3-an AMT (automated mechanical transmission), 4-a main speed reducer and 5-wheels;
a system state differential equation is constructed and written in the form of a state space equation:
y(t)＝Cx(t)
selecting a system state quantity:
x＝[x1,x2,x3,x4,x5,x6]Τ＝[ωm,Δω,Tm-To,Tc-To,To,Tf]Τ；
selecting a system control quantity:
selecting system output quantity: y ═ ωm,ωc,Tm,Tc]Τ；
ωmRepresenting motor speed, ωcIndicating the motor control speed, TmRepresenting motor output torque, TcWhich represents the motor control torque and is,
representing the derivative of the drive motor torque with respect to time,
expressed as the derivative of clutch friction torque with time, TfRepresenting vehicle running resistance torque;
step three: designing a model predictive control algorithm, improving the robustness of the system and accurately tracking an optimal control track;
discretizing the system state space equation into the form
Performance index function J punishs and predicts controlled output and reference track yrefThe deviation between (k + j | k) is defined as follows:
where N denotes the length of the prediction time domain, NcRepresenting the length of the control time domain, Q (j) is a state quantity symmetric weight matrix used for predicting y (k + j | k) -y in the time domainrefPunishment is carried out on the point (k + j | k), R (j) is a control quantity symmetric weight matrix which is used for punishment on the change of the control time domain state quantity,
according to the actual condition of the system, determining the specific values of the sampling time and the weight matrix of a control time domain, a prediction time domain and a model prediction control algorithm;
a sufficient requirement for the system output to be fully controllable is the matrix [ CB CAB CA2B…CAn-1B]The rank of (2) is equal to the dimension of the output matrix y, the output controllability of the system is judged according to the output complete controllable matrix,
the predicted state quantities of the model can be expressed in a matrix manner as:
the constraints of the model predictive controller are:
ωm∈[-nm_maxπ/30,nm_maxπ/30](rad/s)
ωc∈[-nm_maxπ/30,nm_maxπ/30](rad/s)
Tm∈[-Tm_max,Tm_max](Nm)
Tc∈[-Tm_max,Tm_max](Nm)
wherein n ism_maxThe maximum rotation speed of the driving motor.
The inputs to the model predictive controller are:
1) the optimal control tracks of the torque of the driving motor, the friction torque of the clutch, the rotating speed of a driving part of the clutch and the rotating speed of a driven part of the clutch are obtained based on a linear quadratic optimal control theory;
2) the system is subjected to external disturbance, including measurable disturbance and immeasurable disturbance, and possible sources of the disturbance include uneven ground, disturbed sensor signals, automobile resistance moment change in the gear shifting process and state quantity disturbance signals caused by reasons;
3) the actual state values of the gear shifting system comprise the torque of a driving motor, the friction torque of a clutch, the rotating speed of a driving part of the clutch and the rotating speed of a driven part of the clutch under the actual condition;
the output of the model predictive controller is: a signal of a control quantity solved by the model predictive controller;
solving a quadratic programming problem which takes the acquisition of each step of control signals of model predictive control as a standard, and obtaining an optimal control solution delta u by solving the minimum value of each step of performance functionopt(k) Based on the control signal u (k-1) of the previous step, the predicted control signal u (k) of each step can be obtained.
The contents of the present invention have been explained above. Those skilled in the art will be able to implement the invention based on these teachings. All other embodiments, which can be derived by a person skilled in the art from the above description without inventive step, shall fall within the scope of protection of the present invention.
Claims (1)
1. The electric vehicle gear shifting strategy optimization and accurate tracking control method is characterized by comprising the following steps of:
the method comprises the following steps: aiming at specific objects, determining an optimized control target of the electric automobile gear shifting process:
1) determining a target impact degree limit value in the gear shifting process;
2) determining a target range for a shift event duration;
3) the transmission torque change in the whole process is ensured to be stable;
4) determining a target torque needing to be recovered by the motor according to the opening ratio of 0-1 of the current power pedal, wherein the target torque is To＝αTm_maxWherein T isoIs a target torque, alpha is a power pedal opening, Tm_maxThe maximum output torque of the motor;
5) the difference between the rotating speeds of the driving part and the driven part of the clutch is zero at the moment of gear shifting ending;
step two: establishing a physical model of a gear shifting process:
specific values of the following parameters of each gear are obtained: the equivalent rotary inertia of a clutch driving part, the equivalent rotary inertia of a clutch driven part, the rotary inertia of a clutch input shaft, the rotary inertia of a driving motor, the rotary inertia of a clutch output shaft, the rotary inertia of wheels, the equivalent damping coefficient of the clutch driving part, the equivalent damping coefficient of the clutch driven part, the torque of the driving motor, the friction torque of the clutch, the speed ratio of a speed changer, the speed ratio of a main reducer, the rolling radius of the wheels, the mass of an automobile, the gravity acceleration, the rolling friction coefficient, the road gradient, the air resistance coefficient, the windward area, the speed of the automobile, the rotating speed of the clutch driving part, the rotating speed of the clutch driven part, the rotating speed difference of the clutch, and the driving resistance torque,
constructing a system state differential equation, and writing the system state differential equation into a state space equation form:
y(t)＝Cx(t)
selecting a system state quantity:
x＝[x1,x2,x3,x4,x5,x6]Τ＝[ωm,Δω,Tm-To,Tc-To,To,Tf]Τ；
selecting a system control quantity:
selecting system output quantity: y ═ ωm,ωc,Tm,Tc]Τ；
ωmRepresenting motor speed, ωcIndicating the motor control speed, TmRepresenting motor output torque, TcWhich represents the motor control torque and is,
representing the derivative of the drive motor torque with respect to time,
expressed as the derivative of clutch friction torque with time, TfRepresenting vehicle running resistance torque;
step three: designing a model predictive control algorithm, improving the robustness of the system and accurately tracking an optimal control track;
discretizing the system state space equation into the form
Performance index function J punishs and predicts controlled output and reference track yrefThe deviation between (k + j | k) is defined as follows:
where N denotes the length of the prediction time domain, NcRepresenting the length of the control time domain, Q (j) is a state quantity symmetric weight matrix used for predicting y (k + j | k) -y in the time domainrefPunishment is carried out on the point (k + j | k), R (j) is a control quantity symmetric weight matrix which is used for punishment on the change of the control time domain state quantity,
according to the actual condition of the system, determining the specific values of the sampling time and the weight matrix of a control time domain, a prediction time domain and a model prediction control algorithm;
a sufficient requirement for the system output to be fully controllable is the matrix [ CB CAB CA2B…CAn-1B]The rank of (2) is equal to the dimension of the output matrix y, the output controllability of the system is judged according to the output complete controllable matrix,
the predicted state quantities of the model can be expressed in a matrix manner as:
the constraints of the model predictive controller are:
ωm∈[-nm_maxπ/30,nm_maxπ/30](rad/s)
ωc∈[-nm_maxπ/30,nm_maxπ/30](rad/s)
Tm∈[-Tm_max,Tm_max](Nm)
Tc∈[-Tm_max,Tm_max](Nm)
wherein n ism_maxThe maximum rotating speed of the driving motor;
the inputs to the model predictive controller are:
1) the optimal control tracks of the torque of the driving motor, the friction torque of the clutch, the rotating speed of a driving part of the clutch and the rotating speed of a driven part of the clutch are obtained based on a linear quadratic optimal control theory;
2) the system is subjected to external disturbance, including measurable disturbance and immeasurable disturbance, and possible sources of the disturbance include uneven ground, disturbed sensor signals, automobile resistance moment change in the gear shifting process and state quantity disturbance signals caused by reasons;
3) the actual state values of the gear shifting system comprise the torque of a driving motor, the friction torque of a clutch, the rotating speed of a driving part of the clutch and the rotating speed of a driven part of the clutch under the actual condition;
the output of the model predictive controller is: a signal of a control quantity solved by the model predictive controller;
solving a quadratic programming problem which takes the acquisition of each step of control signals of model predictive control as a standard, and obtaining an optimal control solution Vu by solving the minimum value of each step of performance functionopt(k) Based on the control signal u (k-1) of the previous step, the predicted control signal u (k) of each step can be obtained.
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| CN110667395B (en) * | 2019-09-30 | 2021-03-19 | 重庆大学 | Multi-target optimization method for gear shifting rule of pure electric vehicle of two-gear automatic gearbox based on braking working condition |
| CN110778670B (en) * | 2019-11-01 | 2021-09-17 | 长春工业大学 | Comprehensive optimization control strategy for continuously variable transmission based on model predictive control |
| CN112081912B (en) * | 2020-09-25 | 2021-09-28 | 一汽解放汽车有限公司 | Static gear shifting control method and static gear shifting control system |
| CN113007238B (en) * | 2021-04-28 | 2022-08-05 | 一汽解放汽车有限公司 | Starting control method and system of engine constant-speed clutch based on target impact degree |
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| US7912683B2 (en) * | 2006-03-31 | 2011-03-22 | The Yokohama Rubber Co., Ltd. | Tire transient response data calculating method, data processing method, tire designing method, vehicle motion predicting method, and tire cornering characteristic evaluation method and evaluation device therefor |
| US9052013B2 (en) * | 2012-12-14 | 2015-06-09 | Caterpillar Inc. | Grade and payload based transmission gear selection strategy |
| CN106080584A (en) * | 2016-06-21 | 2016-11-09 | 江苏大学 | A kind of hybrid vehicle pattern based on Model Predictive Control Algorithm switching control method for coordinating |
| CN107813814A (en) * | 2016-09-12 | 2018-03-20 | 法乐第(北京)网络科技有限公司 | Energy hole track optimizing method, hybrid vehicle for hybrid vehicle |
| US10125712B2 (en) * | 2017-02-17 | 2018-11-13 | GM Global Technology Operations LLC | Torque security of MPC-based powertrain control |
| CN107719355B (en) * | 2017-10-10 | 2020-07-24 | 苏州大学 | Gear shifting strategy optimization and tracking control method and system for hybrid electric vehicle |
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