CN109555849B - Gear shifting strategy optimization and accurate tracking control method for electric vehicle - Google Patents

Gear shifting strategy optimization and accurate tracking control method for electric vehicle Download PDF

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CN109555849B
CN109555849B CN201811162349.XA CN201811162349A CN109555849B CN 109555849 B CN109555849 B CN 109555849B CN 201811162349 A CN201811162349 A CN 201811162349A CN 109555849 B CN109555849 B CN 109555849B
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clutch
control
torque
gear shifting
max
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CN109555849A (en
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胡广地
罗鹏
郭峰
胡坚耀
叶梦琪
刘伟群
李雨生
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Southwest Jiaotong University
China Electronic Product Reliability and Environmental Testing Research Institute
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Southwest Jiaotong University
China Electronic Product Reliability and Environmental Testing Research Institute
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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
    • 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
    • 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
    • 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

Gear shifting strategy optimization and accurate tracking control method for electric vehicle
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:
Figure GDA0003277022530000021
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:
Figure GDA0003277022530000022
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,
Figure GDA0003277022530000023
representing the derivative of the drive motor torque with respect to time,
Figure GDA0003277022530000024
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
Figure GDA0003277022530000031
Performance index function J punishs and predicts controlled output and reference track yrefThe deviation between (k + j | k) is defined as follows:
Figure GDA0003277022530000032
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:
Figure GDA0003277022530000033
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)
Figure GDA0003277022530000041
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:
Figure GDA0003277022530000051
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:
Figure GDA0003277022530000052
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,
Figure GDA0003277022530000053
representing the derivative of the drive motor torque with respect to time,
Figure GDA0003277022530000054
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
Figure GDA0003277022530000055
Performance index function J punishs and predicts controlled output and reference track yrefThe deviation between (k + j | k) is defined as follows:
Figure GDA0003277022530000056
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:
Figure GDA0003277022530000061
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)
Figure GDA0003277022530000062
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.电动汽车换挡策略优化及精确跟踪控制方法，其特征在于，包括以下步骤：1. Electric vehicle shifting strategy optimization and precise tracking control method, is characterized in that, comprises the following steps: 步骤一：针对具体对象，确定电动汽车换挡过程的优化控制目标：Step 1: For specific objects, determine the optimal control objective of the electric vehicle shifting process: 1)确定换挡过程目标冲击度限值；1) Determine the target impact degree limit of the shifting process; 2)确定换挡过程持续时间的目标范围；2) Determine the target range for the duration of the shifting process; 3)保证整个过程传输转矩变化平稳；3) Ensure that the transmission torque changes smoothly throughout the process; 4)按照当前动力踏板的开度比0～1，确定电机需要恢复的目标转矩，其大小为To＝αTm_max，其中To为目标转矩，α为动力踏板开度，Tm_max为电机最大输出转矩；4) According to the opening ratio of the current power pedal from 0 to 1, determine the target torque that the motor needs to recover, and its magnitude is T o =αT m_max , where T o is the target torque, α is the power pedal opening, and T m_max is The maximum output torque of the motor; 5)换挡结束时刻离合器主动部分和从动部分转速差为零；5) The speed difference between the active part and the driven part of the clutch at the end of the shift is zero; 步骤二：建立换挡过程物理模型：Step 2: Establish a physical model of the shifting process: 获得每个档位以下参数的具体取值：离合器主动部分等效转动惯量、离合器从动部分等效转动惯量、离合器输入轴转动惯量、驱动电机转动惯量、离合器输出轴转动惯量、车轮转动惯量、离合器主动部分等效阻尼系数、离合器从动部分等效阻尼系数、驱动电机转矩、离合器摩擦力矩、变速器速比、主减速器速比、车轮滚动半径、汽车质量、重力加速度、滚动摩擦系数、道路坡度、空气阻力系数、迎风面积，汽车车速、离合器主动部分转速、离合器从动部分转速、离合器转速差、行驶阻力矩，Obtain the specific values of the following parameters for each gear: the equivalent moment of inertia of the active part of the clutch, the equivalent moment of inertia of the driven part of the clutch, the moment of inertia of the clutch input shaft, the moment of inertia of the drive motor, the moment of inertia of the clutch output shaft, the moment of inertia of the wheel, The equivalent damping coefficient of the active part of the clutch, the equivalent damping coefficient of the driven part of the clutch, the torque of the drive motor, the friction torque of the clutch, the speed ratio of the transmission, the speed ratio of the main reducer, the rolling radius of the wheel, the mass of the car, the acceleration of gravity, the rolling friction coefficient, Road slope, air resistance coefficient, windward area, vehicle speed, rotational speed of the active part of the clutch, rotational speed of the driven part of the clutch, difference in clutch rotational speed, driving resistance torque, 构建系统状态微分方程，并该系统状态微分方程书写为状态空间方程的形式：Construct the system state differential equation and write the system state differential equation in the form of state space equation:
Figure FDA0003269449260000011
Figure FDA0003269449260000011
 y(t)＝Cx(t)y(t)=Cx(t) 选择系统状态量：Select the system state quantity: x＝[x1,x2,x3,x4,x5,x6]Τ＝[ωm,Δω,Tm-To,Tc-To,To,Tf]Τ；x = [x 1 , x 2 , x 3 , x 4 , x 5 , x 6 ] Τ = [ω m , Δω, T m -T o , T c -T o , T o , T f ] Τ ; 选择系统控制量：
Figure FDA0003269449260000012
Select the system control amount:
Figure FDA0003269449260000012
 选择系统输出量：y＝[ωm,ωc,Tm,Tc]Τ；Select system output: y=[ω m , ω c , T m , T c ] Τ ; ωm表示电机转速，ωc表示电机控制转速，Tm表示电机输出转矩，Tc表示电机控制转矩，
Figure FDA0003269449260000013
表示驱动电机转矩对时间的导数，
Figure FDA0003269449260000014
表示为离合器摩擦力矩对时间的导数，Tf表示车辆行驶阻力矩；ω m represents the motor speed, ω c represents the motor control speed, T m represents the motor output torque, T c represents the motor control torque,
Figure FDA0003269449260000013
represents the derivative of the drive motor torque with respect to time,
Figure FDA0003269449260000014
It is expressed as the derivative of the clutch friction torque with respect to time, and T f is the driving resistance torque of the vehicle; 步骤三：设计模型预测控制算法，提高系统鲁棒性，精确跟踪最优控制轨迹；Step 3: Design a model predictive control algorithm to improve the robustness of the system and accurately track the optimal control trajectory; 将系统状态空间方程离散化表示为如下形式The discretization of the system state space equation is expressed as the following form
Figure FDA0003269449260000015
Figure FDA0003269449260000015
 性能指标函数J惩罚预测被控输出与参考轨迹yref(k+j|k)之间的偏差，定义如下：The performance index function J penalizes the deviation between the predicted controlled output and the reference trajectory y ref (k+j|k), which is defined as follows:
Figure FDA0003269449260000016
Figure FDA0003269449260000016
 其中，N表示预测时域的长度，Nc表示控制时域的长度，Q(j)为状态量对称权重矩阵，用于对预测时域中y(k+j|k)-yref(k+j|k)的点进行惩罚，R(j)为控制量对称权重矩阵，用于对控制时域状态量的变化进行惩罚，Among them, N represents the length of the prediction time domain, N c represents the length of the control time domain, and Q(j) is the state quantity symmetric weight matrix, which is used for y(k+j|k)-y ref (k +j|k) points are penalized, R(j) is the symmetric weight matrix of the control quantity, which is used to penalize the change of the state quantity in the control time domain, 根据系统的实际情况，确定控制时域、预测时域、模型预测控制算法的采样时间和权重矩阵的具体取值；According to the actual situation of the system, determine the control time domain, prediction time domain, the sampling time of the model predictive control algorithm and the specific value of the weight matrix; 系统输出完全能控的充分必要条件是矩阵[CB CAB CA2B…CAn-1B]的秩等于输出矩阵y的维数，按输出完全能控制矩阵对系统的输出能控性进行判断，The necessary and sufficient condition for the system output to be fully controllable is that the rank of the matrix [CB CAB CA 2 B…CA n-1 B] is equal to the dimension of the output matrix y, and the output controllability of the system is judged according to the output fully controllable matrix. 模型的预测状态量以矩阵的方式可以表示为：The predicted state quantity of the model can be expressed as a matrix in the form of:
Figure FDA0003269449260000021
Figure FDA0003269449260000021
 模型预测控制器的约束为：The constraints of the model predictive controller are: ωm∈[-nm_maxπ/30,nm_maxπ/30](rad/s)ω m ∈[-n m_max π/30,n m_max π/30](rad/s) ωc∈[-nm_maxπ/30,nm_maxπ/30](rad/s)ω c ∈[-n m_max π/30,n m_max π/30](rad/s) Tm∈[-Tm_max,Tm_max](Nm)T m ∈[-T m_max ,T m_max ](Nm) Tc∈[-Tm_max,Tm_max](Nm)T c ∈[-T m_max ,T m_max ](Nm)
Figure FDA0003269449260000022
Figure FDA0003269449260000022
 其中，nm_max为驱动电机最大转速；Among them, n m_max is the maximum speed of the drive motor; 模型预测控制器的输入为：The inputs to the model predictive controller are: 1)基于线性二次型最优控制理论所获得的驱动电机转矩、离合器摩擦力矩、离合器主动部分转速、离合器从动部分转速的最优控制轨迹；1) Based on the linear quadratic optimal control theory, the optimal control trajectories of drive motor torque, clutch friction torque, rotational speed of the active part of the clutch, and rotational speed of the driven part of the clutch are obtained; 2)系统所受到的外界扰动，包括可测扰动和不可测扰动，其可能的来源为地面不平整、传感器信号被干扰、换挡过程汽车阻力矩变化以及原因引起的状态量扰动的信号；2) External disturbances to the system, including measurable disturbances and unmeasurable disturbances, the possible sources of which are uneven ground, disturbance of sensor signals, changes in vehicle resistance torque during gear shifting, and signals of state quantity disturbances caused by causes; 3)换挡系统的实际状态值，包括实际情况下的驱动电机转矩、离合器摩擦力矩、离合器主动部分转速、离合器从动部分转速；3) The actual state value of the shifting system, including the driving motor torque, clutch friction torque, rotational speed of the active part of the clutch, and rotational speed of the driven part of the clutch under actual conditions; 模型预测控制器的输出为：模型预测控制器所解得的控制量的信号；The output of the model predictive controller is: the signal of the control quantity obtained by the model predictive controller; 模型预测控制的每一步控制信号的获得为标准的二次规划问题求解，通过求解每一步性能函数的最小值，得到最优控制解Vuopt(k)，根据上一步的控制信号u(k-1)，可以求取预测所得的每一步控制信号u(k)。The acquisition of the control signal of each step of the model predictive control is a standard quadratic programming problem. By solving the minimum value of the performance function of each step, the optimal control solution Vu opt (k) is obtained. According to the control signal u (k- 1), the predicted control signal u(k) of each step can be obtained.
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