CN113135127A - Method for planning posture collaborative motion path of automobile electric seat - Google Patents

Method for planning posture collaborative motion path of automobile electric seat Download PDF

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Publication number
CN113135127A
CN113135127A CN202110589014.1A CN202110589014A CN113135127A CN 113135127 A CN113135127 A CN 113135127A CN 202110589014 A CN202110589014 A CN 202110589014A CN 113135127 A CN113135127 A CN 113135127A
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seat
posture
path
freedom
movement
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孟德建
张立军
高赟海
李文博
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Nanchang Intelligent New Energy Vehicle Research Institute
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Nanchang Intelligent New Energy Vehicle Research Institute
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/0224—Non-manual adjustments, e.g. with electrical operation
    • B60N2/02246—Electric motors therefor
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/0224—Non-manual adjustments, e.g. with electrical operation
    • B60N2/0244—Non-manual adjustments, e.g. with electrical operation with logic circuits
    • B60N2/0252—Non-manual adjustments, e.g. with electrical operation with logic circuits with relations between different adjustments, e.g. height of headrest following longitudinal position of seat
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/04—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable the whole seat being movable
    • B60N2/06—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable the whole seat being movable slidable
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/04—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable the whole seat being movable
    • B60N2/16—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable the whole seat being movable height-adjustable
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/22—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable the back-rest being adjustable

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  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Seats For Vehicles (AREA)

Abstract

The invention relates to a method for planning a collaborative motion path of the posture of an electric seat of an automobile, which comprises the following steps: step 1: setting the path points of the seat for back and forth movement, up and down height and backrest angle; step 2: setting an initial time interval sequence of the seat posture movement; and step 3: calculating the total energy consumption of the motion path based on the MATLAB three-degree-of-freedom seat model; and 4, step 4: solving the optimal energy-saving path motion time interval based on a particle swarm algorithm; and 5: and obtaining an optimized seat back and forth movement displacement-time curve, an upper and lower height displacement-time curve and a backrest angle inclination angle-time curve. Compared with the prior art, the invention takes the energy consumption saving into consideration, and optimizes the path-time curve of the posture motion of the electric seat.

Description

Method for planning posture collaborative motion path of automobile electric seat
Technical Field
The invention relates to the field of attitude control of electric seats, in particular to a method for planning a collaborative motion path of the attitude of an automobile electric seat.
Background
The manual mode of regulation of traditional car seat needs the passenger to relax the locking mechanism of seat through the handle earlier, later drives the seat through the sitting posture and the position that change the health and removes, loosens locking mechanism's handle at last, fixes the seat in the position of selecting. Along with the acceleration of automobile electromotion, intelligent process, partial automobile has installed the motor in the seat skeleton and carries out the electric control of gesture, compares traditional car seat gesture and adjusts more portably swiftly.
However, the posture adjustment of the conventional electric seat is oriented to one-way adjustment, cooperative posture control is not considered, and energy consumption in the seat posture movement process is not taken into consideration.
Disclosure of Invention
The invention provides a method for planning a collaborative motion path of the posture of an automobile electric seat, aiming at realizing collaborative motion of the front and back positions, the up and down heights and the angle of a backrest of the automobile electric seat. The method simultaneously considers the energy consumption in the motion process to obtain an energy-saving seat three-degree-of-freedom motion path-time curve, and the energy-saving seat three-degree-of-freedom motion path-time curve can be used as an output target curve of each motor of the electric seat to realize the cooperative electric control of the seat posture.
The purpose of the invention can be realized by the following technical scheme:
a method for planning the posture coordinated motion path of an electric seat of an automobile comprises the following steps:
step 1, setting path points of back-and-forth movement, up-and-down height and backrest angle:
the seat is moved from an initial fore-aft position x0Move to the front and back positions x of the targetpIn the process of (2), the seat is horizontally displaced by xp-x0The seat back and forth posture movement path points are 10 in total. Each fore-aft position waypoint may be represented as:
Figure BDA0003088776110000011
from the initial height h of the seat0Move to the target height h9In the process of (a), the seat is vertically displaced by h9-h0The average is divided into 9 sections, the end point of each section is set as a path point, and 10 seat up-down posture movement path points are set in total. Each heightDegree path points may be represented as:
Figure BDA0003088776110000021
seat tilt angle theta from initial back rest0Move to target backrest inclination angle theta9In the process of (2), the inclination angle of the seat back is changed by an amount theta9-θ0The seat back posture movement path points are set to 10 total seat back posture movement path points. Each backrest tilt path point can be expressed as:
Figure BDA0003088776110000022
step 2, setting an initial time interval sequence of the seat posture movement:
seat from initial moment T0Movement to the end time T9In the course of (1), the total time interval is tmThe three seat attitude degrees of freedom are coordinated to move, and the time when the ith (i is 0,1,2, …,9) path point of the three attitude degrees of freedom passes is defined as TiThe time interval from the movement of the ith-1 st waypoint to the movement of the ith waypoint is Deltati(i＝1,2,…,9)，tmAnd Δ tiIs expressed as
Δti＝Ti-Ti-1(i＝1,2,…,9)
Figure BDA0003088776110000023
Determining a desired total time interval t from the initial pose and the target posemWith the initial sequence of time intervals t0＝[Δt1，Δt2，…，Δt9]。
And 3, calculating the total energy consumption of the three-degree-of-freedom motion path of the seat:
establishing a three-degree-of-freedom seat model in MATLAB/Simulink software and inputting the mass, the inertia parameters and the mass center position of a seat cushion and a backrestAnd the like. Based on the seat model, according to the set path point x of the front and rear positions of the seati(i ═ 0,1,2, …,9), seat height Path Point hi(i ═ 0,1,2, …,9), seat back tilt angle waypoint θi(i-0, 1,2, …,9) and an initial sequence of time intervals t0＝[Δt1，Δt2，…，Δt9]And calculating the energy consumption E in the process that the seat moves to the target posture from the current posture in three degrees of freedom simultaneously.
Step 4, energy-saving path planning based on particle swarm optimization:
according to the energy consumption saving requirement in the seat posture movement, the energy-saving path planning optimization model can be expressed as follows:
minE(t)
find:t＝[Δt1,Δt2,…,Δt9]
Figure BDA0003088776110000031
where e (t) is total energy consumption in moving the seat from the initial posture to the target posture, and t ═ Δ t1，Δt2，…，Δt9]Is a sequence of time intervals, j is the degree of freedom of movement of the seat, djIs the displacement or inclination of the motion of the jth degree of freedom of the seat, djminIs the minimum allowable displacement or minimum allowable inclination angle of the motion of the jth degree of freedom of the seat, djmaxIs the maximum allowable displacement or maximum allowable inclination angle, v, of the motion of the jth degree of freedom of the seatjIs the speed, v, of the motion of the jth degree of freedom of the seatjmaxIs the maximum allowable speed, F, for the motion of the jth degree of freedom of the seatjIs the generalized force F received by the seat in the motion process of the jth degree of freedomjmaxIs the maximum driving force provided by the motor corresponding to the jth degree of freedom of the seat, tmaxIs the maximum allowed adjustment time.
The particle swarm optimization is essentially a random search algorithm, and has higher calculation speed and better global search capability compared with the traditional optimization algorithm. The particle swarm algorithm comprises the following steps:
(1) first stageA population of initialising particles, comprising a population size N, a position X of each particleiAnd velocity ViThe expression is as follows:
Xi＝(xi1,xi2,…,xiD),i＝1,2,…,N
Vi＝(vi1,vi2,…,viD),i＝1,2,…,N
in the formula, XiAnd ViD-dimensional vectors, D is the degree of freedom of the seat posture motion, and N is the number of particles.
(2) The fitness value, i.e. the energy E, is calculated for each particle.
(3) Calculating an individual optimum value P for each particlebestAnd is recorded as:
Pbest＝(pi1,pi2,…,piD),i＝1,2,…,N
(4) calculating global optimum g of the whole populationbestAnd is recorded as:
gbest＝(g1,g2,…,gD)
(5) iteratively updating the velocity V of the particleiAnd position XiThe expression of the evolution process is as follows:
vij(t+1)＝w·vij(t)+c1r1(t)[pij(t)-xij(t)]+c2r2(t)[gj(t)-xij(t)]
xij(t+1)＝xij(t)+vij(t+1)
wherein w is the inertial weight, c1And c2Is an acceleration constant, r1And r2Is [0,1 ]]A uniform random number within the range.
(6) And carrying out boundary condition processing.
(7) Judging whether the algorithm termination condition is met, if so, ending the algorithm and outputting an optimal time interval sequence;
otherwise, returning to the step (2).
Step 5, obtaining an optimized seat fore-and-aft movement displacement-time curve, an up-and-down height displacement-time curve and a backrest angle inclination angle-time curve:
the cubic spline interpolation is to divide the whole interval into a plurality of small intervals, perform cubic interpolation in each small interval, and finally splice the interpolation functions of each small interval together to be used as the interpolation function in the whole interpolation interval. Cubic spline interpolation ensures that the function values between two adjacent cells are continuous, the first derivative is continuous, and the second derivative is continuous, so that the interpolation function has certain smoothness, and the expression and the interpolation condition can be expressed as follows:
Figure BDA0003088776110000041
sk(tk-1)＝yk-1,sk(tk)＝yk,k＝1,2,…,n
Figure BDA0003088776110000042
at each time interval tj-1,tj]The interpolation function on (j ═ 1,2, …,9) can be expressed as:
Figure BDA0003088776110000043
in the formula, M0＝M9＝0，Mj＝s”(tj) (j ═ 1,2, …,8), determined by the following matrix:
Figure BDA0003088776110000044
Figure BDA0003088776110000045
positioning the front and rear positions of the seat at a path point xi(i ═ 0,1,2, …,9), seat height Path Point hi(i ═ 0,1,2, …,9), seat back tilt angle waypoint θi(i＝0,1,2,…,9) respectively with an optimum time interval t ═ Δ t1，Δt2，…，Δt9]And (4) carrying out cubic spline interpolation to obtain an optimized seat forward and backward movement displacement-time curve x (t), an optimized seat up and down height displacement-time curve h (t) and an optimized backrest angle inclination angle-time curve theta (t).
Drawings
Fig. 1 is an overall flowchart of a method for planning a posture-coordinated movement path of an electric seat of an automobile.
FIG. 2 is a three-degree-of-freedom seat model built in MATLAB/simulink.
Fig. 3 is a graph of the movement path versus time for the optimized seat fore-aft position.
Fig. 4 is an optimized displacement-time curve for the up-down height motion of the seat.
FIG. 5 is an optimized seat back angular movement inclination versus time curve.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Examples
A method for planning a collaborative motion path of an automobile electric seat posture is shown in a general flow chart in fig. 1, and comprises the following steps:
step 1: and setting path points of back-and-forth movement, up-and-down height and backrest angle.
Get the initial front and back position x of the seat 00, target fore-aft position x90.2m, initial height h 00, target height h90.1m, initial backrest inclination angle theta0Target backrest inclination angle θ is 09The seat horizontal displacement, the vertical displacement and the backrest inclination angle variation are respectively averagely divided into 9 sections, the end point of each section is set as a path point, and 10 seat posture movement path points are respectively set in total, namely:
Figure BDA0003088776110000051
Figure BDA0003088776110000052
θi＝[0,5,10,15,20,25,30,35,40,45](°)
step 2: setting an initial time interval sequence of the seat posture movement.
Take initial time T 00, the maximum operation adjustment time is tmaxSetting the initial adjustment time to t 10sm10s and take equal time intervals at 10 points of the path of the seat attitude motion. I.e. the initial sequence of time intervals deltatiAnd the time T of passing each path pointiIs taken as
Figure BDA0003088776110000053
Figure BDA0003088776110000054
And step 3: and (4) calculating the total energy consumption of the three-degree-of-freedom motion path of the seat.
A three-degree-of-freedom seat model is established in MATLAB/Simulink software, and parameters such as the mass, the inertia parameter, the mass center position and the like of a seat cushion and a backrest are input, as shown in FIG. 2. Based on the seat model, according to the set path point x of the front and rear positions of the seatiSeat height path point hiSeat back tilt angle path point θiAnd an initial sequence of time intervals Δ tiAnd calculating the energy consumption E in the process that the seat moves to the target posture from the current posture in three degrees of freedom simultaneously.
And 4, step 4: and planning an energy-saving path based on a particle swarm algorithm.
According to the energy consumption saving requirement in the seat posture movement, the energy-saving path planning optimization model can be expressed as follows:
minE(t)
find:Δti＝[Δt1,Δt2,…,Δt9]
Figure BDA0003088776110000061
the particle swarm optimization is essentially a random search algorithm, and has higher calculation speed and better global search capability compared with the traditional optimization algorithm. The particle swarm algorithm comprises the following steps:
(1) setting the population size N to 10, initializing a population of particles, including the position X of each particleiAnd velocity ViThe expression is as follows:
Xi＝(xi1,xi2,…,xiD),i＝1,2,…,N
Vi＝(vi1,vi2,…,viD),i＝1,2,…,N
in the formula, XiAnd ViAll are D-dimensional vectors, and D is the degree of freedom 3 of the seat posture movement.
(2) The fitness value, i.e. the energy E, is calculated for each particle.
(3) Calculating an individual optimum value P for each particlebestAnd is recorded as:
Pbest＝(pi1,pi2,…,piD),i＝1,2,…,N
(4) calculating global optimum g of the whole populationbestAnd is recorded as:
gbest＝(g1,g2,…,gD)
(5) iteratively updating the velocity V of the particleiAnd position XiThe expression of the evolution process is as follows:
vij(t+1)＝w·vij(t)+c1r1(t)[pij(t)-xij(t)]+c2r2(t)[gj(t)-xij(t)]
xij(t+1)＝xij(t)+vij(t+1)
in the formula, the inertia weight w is set to 0.8, and the acceleration constant c is set to1And c2Is set to 1.5, r1And r2Is [0,1 ]]A uniform random number within the range.
(6) And carrying out boundary condition processing.
(7) Judging whether the algorithm termination condition is met, if so, ending the algorithm and outputting an optimal time interval sequence; otherwise, returning to the step (2).
Obtaining an optimized time interval sequence delta t after being processed by a particle swarm algorithmiAnd the time T of passing each path pointi。
And 5: and obtaining an optimized seat back-and-forth movement displacement-time curve, an upper-and-lower height displacement-time curve and a backrest angle inclination angle-time curve through cubic spline interpolation, as shown in figures 3-5.
The cubic spline interpolation is to divide the whole interval into a plurality of small intervals, perform cubic interpolation in each small interval, and finally splice the interpolation functions of each small interval together to be used as the interpolation function in the whole interpolation interval. Cubic spline interpolation ensures that the function values between two adjacent cells are continuous, the first derivative is continuous, and the second derivative is continuous, so that the interpolation function has certain smoothness, and the expression and the interpolation condition can be expressed as follows:
Figure BDA0003088776110000071
sk(tk-1)＝yk-1,sk(tk)＝yk,k＝1,2,…,n
Figure BDA0003088776110000072
at each time interval tj-1,tj]The interpolation function on (j ═ 1,2, …,10) can be expressed as:
Figure BDA0003088776110000073
in the formula, M0＝M9＝0，Mj＝s”(tj) (j ═ 1,2, …,8), determined by the following matrix:
Figure BDA0003088776110000074
Figure BDA0003088776110000075
positioning the front and rear positions of the seat at a path point xiSeat height path point hiSeat back tilt angle path point θiRespectively with the time T of passing each path pointiAnd (4) carrying out cubic spline interpolation to obtain an optimized seat forward and backward movement displacement-time curve x (t), an optimized seat up and down height displacement-time curve h (t) and an optimized backrest angle inclination angle-time curve theta (t).

Claims (6)

1. A method for planning a collaborative motion path of the posture of an electric seat of an automobile is characterized by comprising the following steps:
step 1: setting the path points of the seat for back and forth movement, up and down height and backrest angle;
step 2: setting an initial time interval sequence of the seat posture movement;
and step 3: calculating the total energy consumption of the motion path based on the MATLAB three-degree-of-freedom seat model;
and 4, step 4: solving the optimal energy-saving path motion time interval based on a particle swarm algorithm;
and 5: and obtaining an optimized seat back and forth movement displacement-time curve, an upper and lower height displacement-time curve and a backrest angle inclination angle-time curve.
2. The method for planning the posture-coordinated movement path of the electric seat of the automobile according to claim 1, wherein the step 1 specifically comprises:
the seat is moved from an initial fore-aft position x0Move to the front and back positions x of the target9In the process of (2), the seat is horizontally displaced by x9-x0The seat back and forth posture movement path points are 10 in total. Each of the front and rear position waypoints may be represented as：
Figure FDA0003088776100000011
From the initial height h of the seat0Move to the target height h9In the process of (a), the seat is vertically displaced by h9-h0The chair is divided into 9 sections on average, the end point of each section is set as a path point, and 10 chair up-down posture movement path points are set in total; each height path point can be represented as:
Figure FDA0003088776100000012
seat tilt angle theta from initial back rest0Move to target backrest inclination angle theta9In the process of (2), the inclination angle of the seat back is changed by an amount theta9-θ0The seat back posture movement path points are set to be 10 total, and each back inclination angle path point can be expressed as:
Figure FDA0003088776100000013
3. the method for planning the posture-coordinated movement path of the electric seat of the automobile according to claim 1, wherein the step 2 specifically comprises:
seat from initial moment T0Movement to the end time T9In the course of (1), the total time interval is tmThe three seat attitude degrees of freedom are coordinated to move, and the time when the ith (i is 0,1,2, …,9) path point of the three attitude degrees of freedom passes is defined as TiThe time interval from the movement of the ith-1 st waypoint to the movement of the ith waypoint is Deltati(i＝1,2,…,9)，tmAnd Δ tiThe expression of (a) is:
Δti＝Ti-Ti-1(i＝1,2,…,9)
Figure FDA0003088776100000021
determining a desired total time interval t from the initial pose and the target posemWith the initial sequence of time intervals t0＝[Δt1，Δt2，…，Δt9]；
4. The method for planning the posture-coordinated movement path of the electric seat of the automobile according to claim 1, wherein the step 3 specifically comprises:
establishing a three-degree-of-freedom seat model in MATLAB/Simulink software and inputting parameters such as the mass, the inertia parameter, the mass center position and the like of a seat cushion and a backrest; based on the seat model, according to the set path point x of the front and rear positions of the seati(i ═ 0,1,2, …,9), seat height Path Point hi(i ═ 0,1,2, …,9), seat back tilt angle waypoint θi(i-0, 1,2, …,9) and an initial sequence of time intervals t0＝[Δt1，Δt2，…，Δt9]Calculating energy consumption E of the seat in the process of simultaneously moving from the current posture to the target posture in three degrees of freedom;
5. the method for planning the posture-coordinated movement path of the electric seat of the automobile according to claim 1, wherein the step 4 specifically comprises:
according to the energy consumption saving requirement in the seat posture movement, the energy-saving path planning optimization model can be expressed as follows:
min E(t)
find:t＝[Δt1,Δt2,…,Δt9]
Figure FDA0003088776100000022
where e (t) is total energy consumption in moving the seat from the initial posture to the target posture, and t ═ Δ t1，Δt2，…，Δt9]Is a sequence of time intervals, j is the degree of freedom of movement of the seat, djIs the displacement or inclination of the motion of the jth degree of freedom of the seat, djminIs the minimum allowable displacement or minimum allowable inclination angle of the motion of the jth degree of freedom of the seat, djmaxIs the maximum allowable displacement or maximum allowable inclination angle, v, of the motion of the jth degree of freedom of the seatjIs the speed, v, of the motion of the jth degree of freedom of the seatjmaxIs the maximum allowable speed, F, for the motion of the jth degree of freedom of the seatjIs the generalized force F received by the seat in the motion process of the jth degree of freedomjmaxIs the maximum driving force provided by the motor corresponding to the jth degree of freedom of the seat, tmaxIs the maximum allowed adjustment time;
the particle swarm optimization is essentially a random search algorithm, and compared with the traditional optimization algorithm, the particle swarm optimization has higher calculation speed and better global search capability, and the steps of the particle swarm optimization can be divided into:
(1) initializing a population of particles, including a population size N, a position X of each particleiAnd velocity ViThe expression is as follows:
Xi＝(xi1,xi2,…,xiD),i＝1,2,…,N
Vi＝(vi1,vi2,…,viD),i＝1,2,…,N
in the formula, XiAnd ViD-dimensional vectors, D is the degree of freedom of the seat posture movement, and N is the number of particles;
(2) calculating the fitness value, namely the energy E, of each particle;
(3) calculating an individual optimum value P for each particlebestAnd is recorded as:
Pbest＝(pi1,pi2,…,piD),i＝1,2,…,N
(4) calculating global optimum g of the whole populationbestAnd is recorded as:
gbest＝(g1,g2,…,gD)
(5) iteratively updating the velocity V of the particleiAnd position XiThe expression of the evolution process is as follows:
vij(t+1)＝w·vij(t)+c1r1(t)[pij(t)-xij(t)]+c2r2(t)[gj(t)-xij(t)]
xij(t+1)＝xij(t)+vij(t+1)
wherein w is the inertial weight, c1And c2Is an acceleration constant, r1And r2Is [0,1 ]]A uniform random number within a range;
(6) carrying out boundary condition processing;
(7) judging whether the algorithm termination condition is met, if so, ending the algorithm and outputting an optimal time interval sequence;
otherwise, returning to the step (2);
6. the method for planning the posture-coordinated movement path of the electric seat of the automobile according to claim 1, wherein the step 5 specifically comprises:
the cubic spline interpolation is to divide the whole interval into a plurality of small intervals, carry out cubic interpolation in each small interval, and finally splice the interpolation functions of each small interval together to be used as the interpolation function on the whole interpolation interval; cubic spline interpolation ensures that the function values between two adjacent cells are continuous, the first derivative is continuous, and the second derivative is continuous, so that the interpolation function has certain smoothness, and the expression and the interpolation condition can be expressed as follows:
Figure FDA0003088776100000041
sk(tk-1)＝yk-1,sk(tk)＝yk,k＝1,2,…,n
Figure FDA0003088776100000042
at each time interval tj-1,tj](j ═ 1,2, …,9)The interpolation function of (a) can be expressed as:
Figure FDA0003088776100000043
in the formula, M0＝M9＝0，Mj＝s”(tj) (j ═ 1,2, …,8), determined by the following matrix:
Figure FDA0003088776100000044
Figure FDA0003088776100000045
positioning the front and rear positions of the seat at a path point xi(i ═ 0,1,2, …,9), seat height Path Point hi(i ═ 0,1,2, …,9), seat back tilt angle waypoint θi(i-0, 1,2, …,9) is separated from the optimum time interval t [ Δ t ]1，Δt2，…，Δt9]And (4) carrying out cubic spline interpolation to obtain an optimized seat forward and backward movement displacement-time curve x (t), an optimized seat up and down height displacement-time curve h (t) and an optimized backrest angle inclination angle-time curve theta (t).
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Application publication date: 20210720