www.gusucode.com > mbcdemos 工具箱 matlab 源码程序 > mbcdemos/mbcPointByPointCmdLine.m
%% Point-by-point Modeling for a Diesel Engine
%
% This example shows how to use the Model-Based Calibration Toolbox(TM)
% command-line functionality for point-by-point engine modeling projects.
%
% Multiple injection diesel engines and gasoline direct-injection engines
% can often only be modeled with point-by-point models. You can use
% point-by-point models to build a model at each operating point of an
% engine with the necessary accuracy to produce an optimal calibration.
% Point-by-point command-line functionality is necessary to handle the
% complexity of developing designs for each operating point.
%
% Why are point-by-point models necessary? Engine actuators and sensors are
% continually being added to Engine Management Systems (EMS) in response to
% ever-increasing engine emissions, fuel economy, and performance
% requirements. In some cases, optimal engine calibration development
% processes that rely on two-stage modeling may no longer be able to model
% engine performance responses with sufficient accuracy across the engine
% operating range. Point-by-point models can provide the necessary model
% accuracy at measured operating points. However, point-by-point models
% do not provide estimated responses at other operating points.
%
% This example uses the two-stage models generated in the diesel case
% study as a surrogate for an engine dynamometer or CAE engine model, in
% order to generate the point-by-point data for this example. The
% example shows you how to:
%
% * Generate local designs at each operating point. If insufficient
% design points can be collected, you can augment the local design
% using Sobol sequences.
% * Create local *_multiple models_* to model each of the responses at each
% operating point.
% * Build a point-by-point boundary model to define the data
% boundary at each operating point for later use in calibration
% optimization.
%
% Finally, you must visually inspect the fitted models to verify that the
% model quality is acceptable. You usually need to identify and remove
% outliers. You can use the command-line to plot diagnostics and remove
% outliers, but it is easier to use the graphical and statistical tools in
% the Model Browser (mbcmodel) provided in the Model-Based Calibration
% Toolbox.
% Copyright 2009-2015 The MathWorks, Inc.
%% Load Models from Diesel Project
% This example uses engine data generated from the models in the
% diesel case study.
%
% The inputs are MAINSOI, SPEED, BASEFUELMASS, FUELPRESS, VGTPOS, EGRPOS
DieselProject = mbcmodel.LoadProject(fullfile(mbcpath,'mbctraining','Diesel_project.mat'));
% Store the models in a structure for convenience
DieselResponses = DieselProject.Testplans.Responses;
Models.BTQ = DieselResponses(1);
Models.VGTSPEED = DieselResponses(2);
Models.EQREXH = DieselResponses(3);
Models.PEAKPRESS = DieselResponses(4);
Models.NOX = DieselResponses(6);
Models.EGRMF = DieselResponses(7);
%% Define Inputs for Point-by-Point Models and Create Local Model
%
% * The operating point variables are speed (SPEED) and brake torque
% (BTQ).
% * The local inputs are main start of injection (MAINSOI), fuel
% pressure (FUELPRESS), variable gate turbo position (VGTPOS), and
% exhaust gas recirculation position (EGRPOS).
OperatingPointInputs = mbcmodel.modelinput('Symbol',{'SPEED','BTQ'},...
'Name',{'SPEED','BTQ'},...
'Units',{'rpm','Nm'},...
'Range',{[1600 2200],[0 1600]});
LocalInputs = mbcmodel.modelinput('Symbol',{'MAINSOI','FUELPRESS','VGTPOS','EGRPOS'},...
'Name',{'MAINSOI','FUELPRESS','VGTPOS','EGRPOS'},...
'Units',{'deg','MPa','ratio','mm'},...
'Range',{[-9 3],[90 160],[0.2 0.9],[0.5 5]});
% Create a local multiple model
L = mbcmodel.CreateModel('Point-by-Point',LocalInputs);
% Select the best model using the PRESS RMSE statistic.
L.Properties.SelectionStatistic = 'PRESS RMSE';
%% Define Engine Operating Points
% The design for the operating points is a 7 point drive cycle.
Xg = [2200.0 1263.0
2200.0 947.0
2200.0 632.0
2200.0 126.0
1600.0 1550.0
1600.0 1163.0
1600.0 775.0];
OperatingPointDesign = CreateDesign(OperatingPointInputs);
OperatingPointDesign.Points = Xg;
OperatingPointDesign.Name = 'Drive cycle';
%% Create a Local Design for Each Operating Point
% For each operating point, adjust limits for main injection, fuel pressure
% and VGTPOS, and generate a 128 point Sobol design.
localDesign = CreateDesign(LocalInputs,'Type','Sobol Sequence');
localDesignGenerator = localDesign.Generator;
NumLocalPoints = 128;
localDesignGenerator.NumberOfPoints = NumLocalPoints;
DList = mbcdoe.design.empty( 0, 1);
data = [];
for i = 1:OperatingPointDesign.NumberOfPoints;
OperatingPoint = OperatingPointDesign.Points(i,:);
speed = OperatingPoint(1);
TQDemand = OperatingPoint(2);
%% Name the Local Design by Operating Point
localDesign.Name = sprintf('Test %2d (%s=%4.0f,%s=%3.0f)', i,...
OperatingPointInputs(1).Symbol,OperatingPoint(1),....
OperatingPointInputs(2).Symbol,OperatingPoint(2));
%% Set Up Limits Depending on Speed for Local Inputs
% When you use the Limits property to specify the input
% range, you generate a Sobol design with exactly NumLocalPoints points.
f = (speed-1600)/(2200-1600);
% The main soi range varies from [-3,3] at 1600 rpm to
% [-9,-3] at 2200 rpm.
localDesignGenerator.Limits(1,:) = (1-f)*[-3,3] + f*[-9,-3];
% The fuel pressure range varies from [90,130] at 1600 rpm to
% [120,160] at 2200 rpm.
localDesignGenerator.Limits(2,:) = (1-f)*[90 120] + f*[110,160];
% The VGTPOS range varies from [0.2,0.4] at 1600 rpm to
% [0.6,0.9] at 2200 rpm.
localDesignGenerator.Limits(3,:) = (1-f)*[0.2 0.4] + f*[0.6 0.9];
% set design properties and generate local design
localDesign.Generator = localDesignGenerator;
%% Collect Engine Data for Local Design
% Find the fuel required to obtain the demanded torque for each point in
% the local design
[Xlocal,XTS] = mbcSolveTQ(Models,localDesign.Points,speed,TQDemand);
%% Augment Designs if Necessary
% Check that enough points have been collected after running the 128
% point DOE (design of experiment). Collect extra points by augmenting
% the Sobol Sequence with the next N points in the sequence if
% necessary.
N = NumLocalPoints;
count = 1;
while size(Xlocal,1) < NumLocalPoints*0.75 && count<10
localDesign = Generate(localDesign,...
'Skip',N,...
'NumberOfPoints',N);
N = N*2;
% Find the fuel required to obtain the demanded torque for each point in
% the augmented local design
[Xlocalaug,XTSaug] = mbcSolveTQ(Models,localDesign.Points,speed,TQDemand);
Xlocal = [Xlocal; Xlocalaug]; %#ok<AGROW>
XTS = [XTS; XTSaug]; %#ok<AGROW>
end
% Update points in the local design
localDesign.Points = Xlocal;
fprintf('%s: %d points\n',localDesign.Name,localDesign.NumberOfPoints);
%% Collect Response Data
% Calculate response data from the diesel case study models
BTQ = TQDemand*ones(size(Xlocal,1),1);
AFR = 14.46./Models.EQREXH.PredictedValue(XTS);
EGRMF = Models.EGRMF.PredictedValue(XTS);
BSNOX = 3600*Models.NOX.PredictedValue(XTS)/159.5573;
PEAKPRESS = Models.PEAKPRESS.PredictedValue(XTS)/1e6;
VGTSPEED = Models.VGTSPEED.PredictedValue(XTS);
BSFC = 5400.*XTS(:,3)./(BTQ*pi);
%% Check Fit for BSFC
% Check RMSE < 2
[stats,Lbsfc] = Fit(L,Xlocal,BSFC);
if stats(5)>2
fprintf('Poor fit for test %d.\n',i)
end
%% Accumulate Data and Local Designs
% You can ensure tests are automatically defined by defining a variable
% 'logno'.
data = [data ; Xlocal XTS(:,2:3) BTQ BSFC AFR EGRMF BSNOX PEAKPRESS VGTSPEED i*ones(size(Xlocal,1),1)]; %#ok<AGROW>
DList(i) = localDesign;
end
%% Create Project and Test Plan
% Create an mbcmodel project and build models
project = mbcmodel.CreateProject('DieselPointByPoint');
% Create test plan
TP = CreateTestplan( project, {LocalInputs,OperatingPointInputs} );
TP.Name = 'Point-by-point';
% Assign list of local designs to test plan
TP.Designs{1} = DList;
% Set as best design in test plan
TP.BestDesign{2} = OperatingPointDesign;
%% Make and Import Data Structure
D = project.CreateData();
s = D.ExportToMBCDataStructure;
s.varNames = {LocalInputs.Name 'SPEED', 'MAINFUEL','BTQ' 'BSFC' 'AFR' 'EGRMF' 'BSNOX' 'PEAKPRESS' 'VGTSPEED','logno'};
s.varUnits = {'deg','MPa','mm','ratio','rpm','mg/stroke','Nm','g/kWhr','ratio','ratio','g/kWhr','MPa','rpm',''};
s.data = data;
D.BeginEdit;
D.ImportFromMBCDataStructure(s);
D.CommitEdit;
TP.AttachData(D);
%% Build Point-by-Point Boundary Model
% Use a convex hull for local boundaries.
B = TP.Boundary.Local.CreateBoundary('Point-by-Point');
B.LocalModel = CreateBoundary(B.LocalModel,'Convex hull');
% Add point-by-point boundary model to project.
TP.Boundary.Local.Add(B);
%% Build Response Models
% Use a local multiple model and no global model.
Responses = {'BSFC','BSNOX','AFR','EGRMF','PEAKPRESS','VGTSPEED','MAINFUEL'};
for i = 1:length(Responses)
TP.CreateResponse(Responses{i},L,[]);
end
%% Inspect and Refine Models
% Finally, you must visually inspect the fitted models to verify that the
% model quality is acceptable. You usually need to identify and remove
% outliers. You can use the command-line to plot diagnostics and remove
% outliers, but it is easier to use the graphical and statistical tools in
% the Model Browser (mbcmodel) provided in the Model-Based Calibration
% Toolbox.
%
% You must save the project to a file before loading it into the Model
% Browser.
%
% project.Save('DieselPointByPoint.mat');
%
% mbcmodel('DieselPointByPoint.mat')
displayEndOfDemoMessage(mfilename)