CN112685838B - Functional-based step transmission speed ratio optimization method and system - Google Patents
Functional-based step transmission speed ratio optimization method and system Download PDFInfo
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Abstract
The invention relates to a functional-based step transmission speed ratio optimization method and system, relating to the technical field of propulsion system parameter optimization, wherein the method comprises the steps of determining a constraint condition of an acceleration time performance functional according to acquired vehicle dynamics parameters; performing dynamic weighting on the acceleration time performance functional according to the acquired acceleration performance index and the dynamic weighting coefficient set to obtain an acceleration comprehensive objective function; taking the minimum value of the comprehensive objective function of acceleration as a target, taking the constraint condition of the acceleration time performance functional as the constraint condition of the comprehensive objective of acceleration, and adopting a genetic algorithm to carry out optimization solution on each comprehensive objective function of acceleration so as to obtain the stepped transmission speed ratios under different dynamic weighting coefficient sets; the invention can optimize the parameters of the propulsion system in the dynamic acceleration process.
Description
Technical Field
The invention relates to the technical field of propulsion system parameter optimization, in particular to a functional-based step transmission speed ratio optimization method and system.
Background
The research on the optimization matching method of the propulsion system parameter design with universality has important theoretical significance for fully improving the vehicle mobility. At present, an empirical formula is adopted in the acceleration process and then an optimization method is adopted, static characteristics are mostly adopted in parameter design as references for front-back comparison, and the influence of the dynamic acceleration process is ignored. At present, the research on the acceleration performance of the propulsion system is mature, but the transmission efficiency is mostly regarded as a fixed value as a basic premise, the transmission characteristic of the efficiency is not concerned much, and the influence mechanism on the constraint condition is not studied deeply.
Disclosure of Invention
The invention aims to provide a functional-based method and a functional-based system for optimizing a stepped transmission speed ratio, which are used for optimizing parameters of a propulsion system in a dynamic acceleration process.
In order to achieve the purpose, the invention provides the following scheme:
a functional-based step transmission speed ratio optimization method comprises the following steps:
acquiring vehicle dynamics parameters and acceleration performance indexes of an optimized vehicle;
determining a constraint condition of an acceleration time performance functional according to the vehicle dynamics parameters; the acceleration time performance functional is a performance functional which takes the vehicle speed as an independent variable, takes the acceleration time as a functional quantity and takes the expected vehicle speed as the upper limit and the lower limit of the independent variable; the constraint conditions comprise dynamic conditions, road adhesion conditions, gear difference conditions, speed ratio gradual reduction conditions and speed ratio upper and lower boundary conditions;
performing dynamic weighting on the acceleration time performance functional according to the acceleration performance index and the dynamic weighting coefficient set to obtain an acceleration comprehensive objective function; the number of the accelerating comprehensive objective functions is the same as that of the dynamic weighting coefficient set; different dynamic weighting coefficients exist in different dynamic weighting coefficient sets, and the number of the dynamic weighting coefficients in each dynamic weighting coefficient set is the same; the number of dynamic weighting coefficients in the dynamic weighting coefficient set is the same as the number of the acceleration performance indexes;
and taking the minimum value of the comprehensive objective function of the acceleration as a target, taking the constraint condition of the acceleration time performance functional as the constraint condition of the comprehensive objective of the acceleration, and adopting a genetic algorithm to carry out optimization solution on each comprehensive objective function of the acceleration so as to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets.
Optionally, the vehicle dynamics parameters include vehicle mass, wheel radius, side transmission ratio, windward area, rolling resistance coefficient, road adhesion coefficient, main deceleration efficiency, transmission efficiency, gravitational acceleration, maximum climbing gradient, maximum vehicle speed, shift time, maximum rotating speed of the power device, and maximum torque of the power device;
the acceleration performance indexes comprise 0-32km/h starting acceleration time and 40-60km/h overtaking acceleration time.
Optionally, the step-by-step transmission speed ratio under different dynamic weighting coefficient sets is obtained by using the minimum value of the comprehensive accelerated objective function as a target, using the constraint condition of the accelerated time performance functional as the constraint condition of the comprehensive accelerated objective function, and using a genetic algorithm to perform optimal solution on each comprehensive accelerated objective function, and specifically includes:
compiling the accelerated comprehensive objective function and the constraint conditions of the accelerated comprehensive objective function into an M file by utilizing an Optimol tool kit of Matlab; the number of the M files is the same as that of the accelerated comprehensive objective functions;
and processing each M file by using a GAS + fmincon hybrid genetic algorithm to obtain the step transmission speed ratio under different dynamic weighting coefficient sets.
Optionally, the expression of the acceleration time performance functional is as follows:
wherein ay is the whole acceleration process; i ═ i 0 i g ，i g For step-variable transmission ratio, i 0 Is a main reduction ratio; u is the vehicle speed; ge is the total number of gears; u. of j1 ，u j2 Initial vehicle speed and final vehicle speed during acceleration in the jth gear;
m is the mass of the vehicle, I W Is the rotational inertia of the wheel, and r is the radius of the driving wheel;
I f rotational inertia of a rotating part of the engine; lambda [ alpha ] 3 Fmg, f is the rolling resistance coefficient, g is the gravity acceleration;
a is the frontal area, C D Is an air resistance system; i.e. i j The gear ratio of the j gear is; eta T To turbine efficiency; eta TB For the impeller efficiency; t is a unit of dl Outputting torque for a power source; τ is the shift time.
Optionally, the expression of the accelerated synthetic objective function is:
F(i)＝ζ 1 f 0-32 (i)+ζ 2 f 40-60 (i)
wherein F (i) is a target value of an accelerated synthesis objective function; f. of 0-32 (i) An acceleration time of 0 to 32 km/h; f. of 40-60 (i) An acceleration time of 40 to 60 km/h; zeta 1 、ζ 2 Is a dynamic weighting coefficient, and 1 +ζ 2 ＝1。
optionally, the dynamic condition is: f t (u,i)-F f (u,i)-F w (u,i)≥0；
The pavement adhesion conditions are as follows:
the gear difference conditions are as follows:
the condition that the speed ratio is gradually decreased is as follows: i.e. i j ＞i j+1 ；
The speed ratio upper and lower boundary conditions are as follows:
wherein, F t Is a driving force; f f Is rolling resistance; f w Is the air resistance;
is the road surface adhesion coefficient; beta is a max The maximum climbing gradient is obtained; ttmax is the power source maximum drive torque; i.e. i 0 Is a main reduction ratio; eta T To turbine efficiency; eta TB For the pump impeller efficiency; n is the normal acting force of the road surface; v. of max The maximum speed index of the designed vehicle is obtained; n is EP The rotating speed is output for the maximum power of the power source.
A functional-based stepped transmission ratio optimization system, comprising:
the data acquisition module is used for acquiring vehicle dynamics parameters and acceleration performance indexes of the optimized vehicle;
the constraint condition determining module is used for determining the constraint condition of the acceleration time performance functional according to the vehicle dynamics parameters; the acceleration time performance functional is a performance functional which takes the vehicle speed as an independent variable, takes the acceleration time as a functional quantity and takes the expected vehicle speed as the upper limit and the lower limit of the independent variable; the constraint conditions comprise dynamic conditions, road surface attachment conditions, gear step difference conditions, speed ratio gradual decrease conditions and speed ratio upper and lower boundary conditions;
the acceleration comprehensive objective function determining module is used for dynamically weighting the acceleration time performance functional according to the acceleration performance index and the dynamic weighting coefficient set to obtain an acceleration comprehensive objective function; the number of the accelerating comprehensive objective functions is the same as that of the dynamic weighting coefficient sets; different dynamic weighting coefficients exist in different dynamic weighting coefficient sets, and the number of the dynamic weighting coefficients in each dynamic weighting coefficient set is the same; the number of the dynamic weighting coefficients in the dynamic weighting coefficient set is the same as that of the acceleration performance indexes;
and the optimization solving module is used for taking the minimum value of the comprehensive objective function of the acceleration as a target, taking the constraint condition of the acceleration time performance functional as the constraint condition of the comprehensive objective of the acceleration and adopting a genetic algorithm to carry out optimization solving on each comprehensive objective function of the acceleration so as to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets.
Optionally, the vehicle dynamics parameters in the data acquisition module include vehicle mass, wheel radius, side transmission ratio, windward area, rolling resistance coefficient, road adhesion coefficient, main deceleration efficiency, transmission efficiency, gravitational acceleration, maximum climbing slope, maximum vehicle speed, shift time, maximum rotational speed of the power device, and maximum torque of the power device;
the acceleration performance indexes in the data acquisition module comprise 0-32km/h starting acceleration time and 40-60km/h overtaking acceleration time.
Optionally, the optimization solving module specifically includes:
the compiling unit is used for compiling the accelerated comprehensive objective function and the constraint conditions of the accelerated comprehensive objective function into an M file by utilizing an Optimol tool box of Matlab; the number of the M files is the same as that of the accelerated comprehensive objective functions;
and the optimization solving unit is used for processing each M file by using a GAs + fmincon hybrid genetic algorithm to obtain the stepped transmission speed ratios under different dynamic weighting coefficient sets.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
aiming at the characteristics that the acceleration capability difference of a propulsion system of a tracked vehicle is obvious under different road environments and the parameters of the acceleration process are complex and changeable, the invention provides a functional-based step transmission speed ratio optimization method and system, firstly, the propulsion system of the acceleration process is taken as a research object, the optimal acceleration capability is taken as a design target, a target functional of the shortest acceleration time is obtained, and a prerequisite condition is provided for the development of the optimal acceleration capability parameter design and matching of the propulsion system; and secondly, introducing a variational method idea, regarding the power output characteristic and the energy transfer efficiency characteristic of the propulsion system as parameter equations, performing numerical iterative computation on performance functional of different forms by using a genetic algorithm, and interpolating to obtain an approximate solution fitting curve. It is evident that the invention enables optimization of propulsion system parameters during dynamic acceleration.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a functional-based step-drive speed ratio optimization method of the present invention;
FIG. 2 is a schematic structural diagram of a functional-based step-drive ratio optimization system of the present invention;
FIG. 3 is a schematic representation of a vehicle speed-gear curve of the present invention;
FIG. 4 is a graph of comparative analysis of acceleration before and after optimization in accordance with the present invention; FIG. 4(a) comparative acceleration analysis plots before and after 0-100s optimization; FIG. 4(b) comparative acceleration analysis plots before and after 0-10s optimization;
FIG. 5 is a comparison graph of gear curves of the acceleration process before and after optimization according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a functional-based step transmission speed ratio optimization method and system, which are used for optimizing parameters of a propulsion system in a dynamic acceleration process.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention provides a functional-based step transmission speed ratio optimization method, which can establish a performance functional representing the longitudinal acceleration performance of a vehicle by utilizing functional analysis and a variational method principle and acquire an extreme value of the performance functional by utilizing a genetic algorithm.
The parameters involved in the speed ratio optimization design process are shown in table 1:
TABLE 1 parameters involved in the optimization procedure
Establishing a longitudinal dynamic model of a vehicle
1. The rotational speed relationship between the wheel rotational speed and the engine rotational speed is:
r is the radius of the drive wheel.
And (3) carrying out derivation on two sides of the rotating speed relation:
2. as shown in FIG. 3, during acceleration of the vehicle, the vehicle speed u continuously increases monotonically with time t, and the vehicle transmission gear ratio i g Decreases in segments as time t increases; each vehicle speed only corresponds to one transmission ratio, and the piecewise function taking the vehicle speed as an independent variable and the transmission ratio as a dependent variable is as follows: i.e. i g (u(t))。
3. The driving wheel torque considering the efficiency is:
driving wheel without friction resistanceThe moments are:
the actual frictional drag torque equivalent to at the drive wheel is:
4. and (3) variable substitution: i ═ i 0 i g The frictional resistance is then:
the friction dissipation power is
5. The power balance is:
(II) constructing an acceleration time performance functional
1. The simplest functional is in the mathematical form of
Wherein x is a performance functional independent variable(ii) a y is the functional volume of the performance functional; x is a radical of a fluorine atom 0 、x 1 The upper and lower limits of the independent variable.
2. Speed u of vehicle 0 Accelerate to u 1 The time T required can be regarded as the acceleration a v Integral of the reciprocal of (c) with the vehicle speed u, i.e.
And (3) variable substitution:
λ 3 ＝fmg，
simplifying the performance functional to:
the gear j is not continuous at one moment of gear shifting, and the acceleration i' does not exist; i is constant in the rest of time, i' is 0, the acceleration time performance functional is simplified as follows:
Considering shift time τ, the final acceleration time performance functional is:
extremum solution of (III) functional
The speed ratio of the step-variable vehicle is a constant value with limited discontinuity, so that a functional extremum curve cannot be obtained. In order to obtain the global optimal solution as much as possible, the genetic algorithm is used for iterative calculation.
1. Constraint conditions are as follows:
the dynamic conditions are as follows: gamma ray 1 (u,i)＝F t (u,i)-F f (u,i)-F w (u,i)≥0。
The road surface adhesion conditions are as follows:
the gear difference conditions are as follows:
the condition that the speed ratio is gradually reduced is as follows: gamma ray 4 (i j )＝i j ＞i j+1 。
The upper and lower boundary requirements are:
2. the transmission efficiency of different gears is as follows: eta T (i)＝0.87+0.02×ge。
3. The road surface resistance coefficient of the vehicle is as follows: f. of r (v)＝0.0076+0.00056×v。
4. The comprehensive objective function of acceleration is F (i) ═ ζ 1 f 0-32 (i)+ζ 2 f 40-60 (i) In that respect Wherein F (i) refers to an accelerating integrated objective function; fu 0 -u 1 As the speed u of the vehicle 0 To the speed u of the vehicle 1 Acceleration time of (d); zeta 1 And ζ 2 For an accelerating weighting factor (or an accelerating weighting system), ζ 1 +ζ 2 1. And performing speed ratio optimization design on the model under different weight coefficients.
Based on the above, the present embodiment provides a functional-based step-gear ratio optimization method as shown in fig. 1, comprising the following steps:
step 101: acquiring the whole vehicle dynamics parameters and the acceleration performance indexes of the optimized vehicle; the whole vehicle dynamic parameters comprise the whole vehicle mass, the wheel radius, the side transmission ratio, the windward area, the rolling resistance coefficient, the road adhesion coefficient, the main deceleration efficiency, the transmission efficiency, the gravity acceleration, the maximum climbing gradient, the highest vehicle speed, the gear shifting time, the maximum rotating speed of the power device and the maximum torque of the power device; the acceleration performance indexes comprise 0-32km/h starting acceleration time and 40-60km/h overtaking acceleration time.
Step 102: determining a constraint condition of an acceleration time performance functional according to the vehicle dynamics parameters; the acceleration time performance functional is a performance functional which takes the vehicle speed as an independent variable, takes the acceleration time as a functional quantity and takes the expected vehicle speed as the upper limit and the lower limit of the independent variable; the constraint conditions comprise dynamic conditions, road surface attachment conditions, gear step difference conditions, speed ratio gradual decrease conditions and speed ratio upper and lower boundary conditions; wherein the expression of the acceleration time performance functional is as follows:
wherein ay is the whole acceleration process; i ═ i 0 i g ，i g For step-variable transmission ratio, i 0 Is a main reduction ratio; u is the vehicle speed; ge is the total number of gears; u. of j1 ，u j2 Initial vehicle speed and final vehicle speed during acceleration in the jth gear;
m is the vehicle mass, I W Is the rotational inertia of the wheel, and r is the radius of the driving wheel;
I f rotational inertia of a rotating part of the engine; lambda 3 Fmg, f is the rolling resistance coefficient, g is the gravitational acceleration;
a is the frontal area, C D Is an air resistance system; i.e. i j The gear ratio of the j gear is; eta T To the turbine efficiency; eta TB For the impeller efficiency; t is dl Outputting torque for a power source; τ is the shift time.
The dynamic stripThe parts are as follows: f t (u,i)-F f (u,i)-F w (u,i)≥0；
The pavement adhesion conditions are as follows:
the gear step difference condition is as follows:
the condition that the speed ratio is gradually decreased is as follows: i.e. i j ＞i j+1 ；
The speed ratio upper and lower boundary conditions are as follows:
wherein, F t Is a driving force; f f Is rolling resistance; f w Is the air resistance;
is the road adhesion coefficient; beta is a max The maximum climbing gradient is obtained; ttmax is the power source maximum drive torque; i.e. i 0 Is a main reduction ratio; eta T To turbine efficiency; eta TB For the pump impeller efficiency; n is the normal acting force of the road surface; v. of max The maximum speed index of the designed vehicle is obtained; n is EP The rotating speed is output for the maximum power of the power source.
Step 103: performing dynamic weighting on the acceleration time performance functional according to the acceleration performance index and the dynamic weighting coefficient set to obtain an acceleration comprehensive objective function; the number of the accelerating comprehensive objective functions is the same as that of the dynamic weighting coefficient set; different dynamic weighting coefficients exist in different dynamic weighting coefficient sets, and the number of the dynamic weighting coefficients in each dynamic weighting coefficient set is the same; the number of dynamic weighting coefficients in the dynamic weighting coefficient set is the same as the number of the acceleration performance indexes; the expression of the accelerated synthesis objective function is:
F(i)＝ζ 1 f 0-32 (i)+ζ 2 f 40-60 (i)
wherein F (i) is a target value of an accelerated synthesis objective function; f. of 0-32 (i) An acceleration time of 0 to 32 km/h; f. of 40-60 (i) An acceleration time of 40 to 60 km/h; zeta 1 、ζ 2 Is a dynamic weighting coefficient, and ζ 1 +ζ 2 ＝1。
Step 104: taking the minimum value of the comprehensive objective function of acceleration as a target, taking the constraint condition of the acceleration time performance functional as the constraint condition of the comprehensive objective of acceleration, and adopting a genetic algorithm to carry out optimization solution on each comprehensive objective function of acceleration so as to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets; the method specifically comprises the following steps:
compiling the accelerated comprehensive objective function and the constraint conditions of the accelerated comprehensive objective function into an M file by utilizing an Optimol tool kit of Matlab; and the number of the M files is the same as that of the accelerated comprehensive objective functions.
And processing each M file by using a GAS + fmincon hybrid genetic algorithm to obtain the step transmission speed ratio under different dynamic weighting coefficient sets.
Example two
As shown in fig. 2, the present embodiment provides a functional-based step-gear ratio optimization system, comprising:
and the data acquisition module 201 is used for acquiring the vehicle dynamics parameters and the acceleration performance indexes of the optimized vehicle.
A constraint condition determining module 202, configured to determine a constraint condition of an acceleration time performance functional according to the vehicle dynamics parameter; the acceleration time performance functional is a performance functional which takes the vehicle speed as an independent variable, takes the acceleration time as a functional quantity and takes the expected vehicle speed as the upper limit and the lower limit of the independent variable; the constraint conditions comprise dynamic conditions, road surface adhesion conditions, gear step difference conditions, speed ratio gradual decrease conditions and speed ratio upper and lower boundary conditions.
An accelerated comprehensive objective function determining module 203, configured to perform dynamic weighting on the acceleration time performance functional according to the acceleration performance index and the dynamic weighting coefficient set, so as to obtain an accelerated comprehensive objective function; the number of the accelerating comprehensive objective functions is the same as that of the dynamic weighting coefficient sets; different dynamic weighting coefficients exist in different dynamic weighting coefficient sets, and the number of the dynamic weighting coefficients in each dynamic weighting coefficient set is the same; the number of dynamic weighting coefficients in the dynamic weighting coefficient set is the same as the number of acceleration performance indexes.
And the optimization solving module 204 is configured to optimally solve each accelerated comprehensive objective function by using a genetic algorithm with the minimum value of the accelerated comprehensive objective function as a target and the constraint condition of the accelerated time performance functional as a constraint condition of the accelerated comprehensive objective function, so as to obtain a stepped transmission speed ratio under different dynamic weighting coefficient sets.
The vehicle dynamics parameters in the data acquisition module 201 include vehicle mass, wheel radius, side transmission ratio, windward area, rolling resistance coefficient, road adhesion coefficient, main deceleration efficiency, transmission efficiency, gravitational acceleration, maximum climbing slope, maximum vehicle speed, gear shifting time, maximum rotating speed of the power device and maximum torque of the power device;
the acceleration performance indexes in the data acquisition module comprise 0-32km/h starting acceleration time and 40-60km/h overtaking acceleration time.
The expression of the acceleration time performance functional in the constraint condition determination module 202 is:
wherein ay is the whole acceleration process; i ═ i 0 i g ，i g For step-variable transmission ratio, i 0 Is a main reduction ratio; u is the vehicle speed; ge is the total number of gears; u. of j1 ，u j2 To accelerate in the jth gearInitial vehicle speed and final vehicle speed;
m is the vehicle mass, I W Is the rotational inertia of the wheel, and r is the radius of the driving wheel;
I f rotational inertia of a rotating part of the engine; lambda 3 Fmg, f is the rolling resistance coefficient, g is the gravitational acceleration;
a is the frontal area, C D Is an air resistance system; i.e. i j The gear ratio of the j gear is; eta T To turbine efficiency; eta TB For the pump impeller efficiency; t is dl Outputting torque for a power source; τ is the shift time.
The dynamics conditions in the constraint determination module 202 are:
F t (u,i)-F f (u,i)-F w (u,i)≥0；
the pavement adhesion conditions are as follows:
the gear difference conditions are as follows:
the condition that the speed ratio is gradually decreased is as follows: i.e. i j ＞i j+1 ；
The upper and lower boundary conditions of the speed ratio are as follows:
wherein, F t Is a driving force; f f Is rolling resistance; f w Is the air resistance;
is the road surface adhesion coefficient; beta is a max The maximum climbing gradient; ttmax is the power source maximum drive torque; i.e. i 0 Is a main reduction ratio; eta T To turbine efficiency; eta TB For the impeller efficiency; n is the normal acting force of the road surface; v. of max The maximum speed index of the designed vehicle is obtained; n is EP The rotating speed is output for the maximum power of the power source.
The expression of the accelerating integrated objective function in the accelerating integrated objective function determining module 203 is:
F(i)＝ζ 1 f 0-32 (i)+ζ 2 f 40-60 (i)
wherein F (i) is a target value of an accelerated synthesis objective function; f. of 0-32 (i) An acceleration time of 0 to 32 km/h; f. of 40-60 (i) An acceleration time of 40 to 60 km/h; zeta 1 、ζ 2 Is a dynamic weighting coefficient, and 1 +ζ 2 ＝1。
the optimization solving module 204 specifically includes:
the compiling unit is used for compiling the accelerated comprehensive objective function and the constraint conditions of the accelerated comprehensive objective function into an M file by utilizing an Optimol tool box of Matlab; the number of the M files is the same as that of the accelerated comprehensive objective functions;
and the optimization solving unit is used for processing each M file by using a GAS + fmincon hybrid genetic algorithm to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets.
EXAMPLE III
The vehicle dynamics parameter values of a vehicle are shown in table 2.
TABLE 2 complete vehicle dynamics parameter table
The functional-based step transmission speed ratio optimization method disclosed by the embodiment specifically comprises the following implementation steps:
the method comprises the following steps: determining the upper and lower boundaries i of the transmission ratio according to the dynamic parameters and design indexes of the whole vehicle max And i min . Upper boundary i max Simultaneously, the climbing condition and the road surface adhesive force condition are met, the lower boundary meets the requirement of the highest vehicle speed, and the formula (1) is as follows:
ttmax — power source maximum drive torque;
i 0 -a main gear ratio;
η T -turbine efficiency;
η TB -pump impeller efficiency;
f-rolling resistance coefficient;
r z -capstan radius;
n is the normal acting force of the road surface;
v max -a designed vehicle maximum speed indicator;
n EP -maximum power output speed of the power source.
Solved to obtain i of more than or equal to 3.91 max ≤6.73，i min ≤1.07。
Other constraints are then determined, see example one.
Step two: and (3) establishing an acceleration time performance functional taking the vehicle speed as an independent variable, the acceleration time as a functional quantity and the expected vehicle speed as upper and lower limits of the independent variable, as shown in a formula (2).
In the formula, ge represents a gear;
u j1 ，u j2 vehicle with initial and final accelerationSpeed;
η T -turbine efficiency;
η TB -pump impeller efficiency;
η CVT -efficiency;
T dl -power source output torque;
f, rolling resistance coefficient;
r-the radius of the driving wheel;
τ — shift time.
Taking the starting acceleration time of 0-32km/h and the overtaking acceleration time of 40-60km/h as two acceleration performance indexes, and carrying out dynamic weighting by using a weight method to obtain an acceleration comprehensive objective function, wherein the formula is shown in a formula (3).
F(i)＝ζ 1 f 0-32 (i)+ζ 2 f 40-60 (i) (3)
Wherein F (i) -an accelerating complex objective function;
f 0-32 ，f 40-60 -acceleration times ranging from 0 to 32km/h and from 40 to 60 km/h;
ζ 1 ，ζ 2 -an acceleration weight coefficient, ζ 1 +ζ 2 ＝1。
Compiling constraint conditions and an acceleration comprehensive objective function of a power transmission system into an M file, and designing speed ratios under different acceleration weight coefficients by utilizing an Optimol tool kit of Matlab and a GAS + fmincon hybrid genetic algorithm, wherein the speed ratios comprise zeta 1 ＝1.0,ζ 2 Acceleration performance at 0-32km/h, ζ 1 ＝0.8,ζ 2 Overall acceleration performance and zeta at 0.2 1 ＝1,ζ 2 The overtaking acceleration performance of 40-60km/h when the speed is 0. The functional quantities under different dynamic weighting coefficients are obtained by calculation, as shown in tables 3-5.
TABLE 3 ζ 1 ＝1.0，ζ 2 Table of engine input ratio optimum (t-4.451 s) at 0
| Optimized rear speed ratio | I gear | II gear | III gear | IV gear | V gear | VI gear |
| Numerical value | 9.040 | 5.919 | 3.830 | 2.404 | 1.592 | 1.125 |
TABLE 4 ζ 1 ＝0.8,ζ 2 Table of engine input speed ratio optimum (t-4.662 s) at 0.2
| Optimized rear speed ratio | I gear | II gear | III gear | IV gear | V gear | VI gear |
| Numerical value | 8.939 | 5.716 | 3.761 | 2.665 | 1.852 | 1.200 |
TABLE 5 ζ 1 ＝1,ζ 2 Table of engine input ratio optimum (t-5.390 s) at 0
| Optimized rear speed ratio | I gear | II gear | III gear | IV gear | V gear | VI gear |
| Numerical value | 9.069 | 6.583 | 4.379 | 2.895 | 1.900 | 1.192 |
Analysis can be carried out, when the optimization target is 40-60km/h overtaking acceleration time, the IV gear, the V gear and the VI gear tend to be enlarged, and larger driving force can be provided; when the optimization target is 0-32km/h starting acceleration time, gears I, II and III tend to be maximum values under the constraints of level difference and the like.
According to the comparative analysis graph of the acceleration performance before and after optimization of fig. 4 and the comparative graph of the gear curve during the acceleration process before and after optimization of fig. 5, it can be seen that the acceleration time of 0-32km/h after optimization is shortened to 5.84s from the original 6.34s, the acceleration time is shortened to 7.89%, the rule that the gear shifting time is advanced as the gear is higher is embodied, and the optimization design of the starting acceleration time performance functional of the tracked vehicle is feasible.
Gear utilization table for 60-32 km/h acceleration time
| Gear position | I gear | II gear | III gear | IV gear | Acceleration time [ s ]] |
| Before optimization | 24.78％ | 18.55％ | 30.03％ | 26.58％ | 6.34s |
| After optimization | 24.12％ | 15.77％ | 24.72％ | 35.39％ | 5.84s |
As can be seen from table 6, after optimization, the utilization rate of the I, II gear is not obviously changed, the acceleration utilization rate of the III gear is reduced, and the acceleration utilization rate of the IV gear is obviously increased, which indicates that the functional optimization increases the speed ratio of two adjacent gears stopping the vehicle speed, so that the acceleration performance of the vehicle is improved, and further indicates that the transmission ratio optimized by the embodiment is feasible for improving the dynamic performance of the vehicle.
The method comprises the steps of carrying out modeling analysis on main factors influencing the vehicle acceleration capacity, establishing a performance functional representing the longitudinal acceleration performance of the vehicle by taking a step-variable vehicle as a research object, obtaining an extreme value of the performance functional by utilizing a numerical solving algorithm, obtaining a propulsion system parameter matching design method based on the optimal acceleration performance of the tracked vehicle, carrying out dynamic optimization by utilizing Simulink on the basis, comparing results before and after the optimization, and verifying the effectiveness of the method and the model.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A functional-based step transmission speed ratio optimization method is characterized by comprising the following steps:
acquiring vehicle dynamics parameters and acceleration performance indexes of an optimized vehicle;
determining a constraint condition of an acceleration time performance functional according to the vehicle dynamics parameters; the acceleration time performance functional is a performance functional which takes the vehicle speed as an independent variable, takes the acceleration time as a functional quantity and takes the expected vehicle speed as the upper limit and the lower limit of the independent variable; the constraint conditions comprise dynamic conditions, road surface attachment conditions, gear step difference conditions, speed ratio gradual decrease conditions and speed ratio upper and lower boundary conditions;
performing dynamic weighting on the acceleration time performance functional according to the acceleration performance index and the dynamic weighting coefficient set to obtain an acceleration comprehensive objective function; the number of the accelerating comprehensive objective functions is the same as that of the dynamic weighting coefficient sets; different dynamic weighting coefficients exist in different dynamic weighting coefficient sets, and the number of the dynamic weighting coefficients in each dynamic weighting coefficient set is the same; the number of dynamic weighting coefficients in the dynamic weighting coefficient set is the same as the number of the acceleration performance indexes;
taking the minimum value of the comprehensive objective function of acceleration as a target, taking the constraint condition of the acceleration time performance functional as the constraint condition of the comprehensive objective of acceleration, and adopting a genetic algorithm to carry out optimization solution on each comprehensive objective function of acceleration so as to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets;
the expression of the acceleration time performance functional is as follows:
wherein ay is the whole acceleration process; i ═ i 0 i g ，i g For step-variable transmission ratio, i 0 Is a final reduction ratio; u is the vehicle speed; ge is the total number of gears; u. of j1 ，u j2 Initial vehicle speed and final vehicle speed during acceleration in the jth gear;
m is the vehicle mass, I W Is the rotational inertia of the wheel, and r is the radius of the driving wheel;
I f rotational inertia of a rotating part of the engine; lambda [ alpha ] 3 Fmg, f is the rolling resistance coefficient, g is the gravity acceleration;
a is the windward area, C D Is an air resistance system; i.e. i j The gear ratio of the j gear; eta T To turbine efficiency; eta TB For the pump impeller efficiency; t is dl Outputting torque for a power source; τ is the shift time.
2. The method according to claim 1, wherein the vehicle dynamics parameters include vehicle mass, wheel radius, lateral gear ratio, windward area, rolling resistance coefficient, road adhesion coefficient, main deceleration efficiency, transmission efficiency, gravitational acceleration, maximum climbing slope, maximum vehicle speed, shift time, maximum power device rotational speed, and maximum power device torque;
the acceleration performance indexes comprise 0-32km/h starting acceleration time and 40-60km/h overtaking acceleration time.
3. The functional-based stepped transmission speed ratio optimization method according to claim 1, wherein the step of performing optimization solution on each accelerated synthetic objective function by using a genetic algorithm with a minimum value of the accelerated synthetic objective function as a target and a constraint condition of the accelerated time performance functional as a constraint condition of the accelerated synthetic objective to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets specifically comprises:
compiling the accelerated comprehensive objective function and the constraint conditions of the accelerated comprehensive objective function into an M file by utilizing an Optimol tool kit of Matlab; the number of the M files is the same as that of the accelerated comprehensive objective functions;
and processing each M file by using a GAS + fmincon hybrid genetic algorithm to obtain the step transmission speed ratio under different dynamic weighting coefficient sets.
4. A functional-based method of optimizing a ratio of a stepped transmission according to claim 2, wherein said accelerative objective function is expressed as:
F(i)＝ζ 1 f 0-32 (i)+ζ 2 f 40-60 (i)
wherein F (i) is a target value of an accelerated synthesis objective function; f. of 0-32 (i) An acceleration time of 0 to 32 km/h; f. of 40-60 (i) An acceleration time of 40 to 60 km/h; zeta 1 、ζ 2 Is a dynamic weighting coefficient, and 1 +ζ 2 ＝1。
5. the method of functional-based step-gear ratio optimization according to claim 2,
the dynamic conditions are as follows: f t (u,i)-F f (u,i)-F w (u,i)≥0；
The pavement adhesion conditions are as follows:
the gear step difference condition is as follows:
the condition that the speed ratio is gradually decreased is as follows: i.e. i j ＞i j+1 ；
The speed ratio upper and lower boundary conditions are as follows:
wherein, F t Is a driving force; f f Is rolling resistance; f w Is the air resistance;
is the road surface adhesion coefficient; beta is a max The maximum climbing gradient is obtained; ttmax is the power source maximum drive torque; i.e. i 0 Is a main reduction ratio; eta T To turbine efficiency; eta TB For the pump impeller efficiency; n is the normal acting force of the road surface; v. of max The maximum speed index of the designed vehicle is obtained; n is EP The rotating speed is output for the maximum power of the power source.
6. A functional-based step-drive ratio optimization system, comprising:
the data acquisition module is used for acquiring vehicle dynamics parameters and acceleration performance indexes of the optimized vehicle;
the constraint condition determining module is used for determining the constraint condition of the acceleration time performance functional according to the vehicle dynamics parameters; the acceleration time performance functional is a performance functional which takes the vehicle speed as an independent variable, takes the acceleration time as a functional quantity and takes the expected vehicle speed as the upper limit and the lower limit of the independent variable; the constraint conditions comprise dynamic conditions, road surface attachment conditions, gear step difference conditions, speed ratio gradual decrease conditions and speed ratio upper and lower boundary conditions;
the acceleration comprehensive objective function determining module is used for dynamically weighting the acceleration time performance functional according to the acceleration performance index and the dynamic weighting coefficient set to obtain an acceleration comprehensive objective function; the number of the accelerating comprehensive objective functions is the same as that of the dynamic weighting coefficient set; different dynamic weighting coefficients exist in different dynamic weighting coefficient sets, and the number of the dynamic weighting coefficients in each dynamic weighting coefficient set is the same; the number of dynamic weighting coefficients in the dynamic weighting coefficient set is the same as the number of the acceleration performance indexes;
the optimization solving module is used for taking the minimum value of the comprehensive objective function of acceleration as a target, taking the constraint condition of the acceleration time performance functional as the constraint condition of the comprehensive objective of acceleration, and adopting a genetic algorithm to carry out optimization solving on each comprehensive objective function of acceleration so as to obtain a stepped transmission speed ratio under different dynamic weighting coefficient sets;
the expression of the acceleration time performance functional is as follows:
wherein ay is the whole acceleration process; i ═ i 0 i g ，i g For step-variable transmission ratio, i 0 Is a final reduction ratio; u is the vehicle speed; ge is the total number of gears; u. u j1 ，u j2 Initial vehicle speed and final vehicle speed during acceleration in the jth gear;
m is the vehicle mass, I W Is the rotational inertia of the wheel, and r is the radius of the driving wheel;
I f rotational inertia of a rotating part of the engine; lambda [ alpha ] 3 Fmg, f is the rolling resistance coefficient, g is the gravity acceleration;
7. The functional-based stepped transmission speed ratio optimization system according to claim 6, wherein the vehicle dynamics parameters in the data acquisition module include vehicle mass, wheel radius, side transmission ratio, windward area, rolling resistance coefficient, road adhesion coefficient, main deceleration efficiency, transmission efficiency, gravitational acceleration, maximum climbing slope, maximum vehicle speed, shift time, maximum power device rotational speed, and maximum power device torque;
the acceleration performance indexes in the data acquisition module comprise 0-32km/h starting acceleration time and 40-60km/h overtaking acceleration time.
8. The functional-based stepped transmission speed ratio optimization system according to claim 6, wherein the optimization solution module specifically comprises:
the compiling unit is used for compiling the accelerated comprehensive objective function and the constraint conditions of the accelerated comprehensive objective function into an M file by utilizing an Optimol tool box of Matlab; the number of the M files is the same as that of the accelerated comprehensive objective functions;
and the optimization solving unit is used for processing each M file by using a GAS + fmincon hybrid genetic algorithm to obtain the stepped transmission speed ratio under different dynamic weighting coefficient sets.
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