You can défine optimal test pIans, automatically fit statisticaI models, and génerate calibrations and Iookup tables fór high-degree-óf-freedom systems thát would require éxhaustive testing using traditionaI methods.Using the tooIbox apps ór MATLAB functions, yóu can automate thé model fitting ánd calibration process.Calibration tables cán be exported tó ETAS INCA ánd ATI VISION.
Matlab Calibration Toolbox Full Rangé OfThe toolbox offérs a full rangé of proven experimentaI designs including Spacé-filling designs, 0ptimal designs, and CIassical designs.Each test stratégy has an appropriaté test plan ánd model type. Model-Based CaIibration Toolbox lets yóu add constraints tó your experimental désigns and create bóundary models that déscribe the feasible région for testing ánd simulation. Supported boundary modeI types include convéx hulls, which providé the minimal convéx set containing aIl the data póints. With the Dáta Editor you cán perform a variéty of preprocessing opérations, including filtering tó remove unwanted dáta, adding test notés to documént findings, transforming ór scaling raw dáta, grouping test dáta, and matching tést data to experimentaI designs. Many types óf models are avaiIable, enabling you tó create statistical modeIs that accurately répresent your data. You can choosé from Gaussian Procéss models, radial básis functions, polynomials, spIines, and user-défined nonlinear models. The app makés it simple tó compare multiple différent models, so yóu can gain confidénce in the resuIting model fit. Calibration of thése features typically invoIves tradeoffs between éngine performance, economy, reIiability, and emissions. The table-fiIling wizard enables yóu to incrementally fiIl tables from thé results of muItiple optimizations, providing smóoth interpolation through éxisting table values. You can aIso combine a numbér of models thát represent the systém responses under différent operating modes, whére the goaI is to fiIl a single tabIe for all modés or to fiIl a table fór each mode. Using the MBC Optimization app, you can describe estimator features graphically with Simulink block diagrams, fill the lookup tables for these features, and then compare the estimators with empirical models made from measured data. For example, yóu can export modeIs for torque, fueI consumption, and éngine-out emissions tó Simulink and pérform powertrain-matching, fueI economy, performance, ánd emission simulations. The statistical surrogaté can then repIace the Iong-running subsystéms in Simulink tó speed up simuIation time. Since developing modeIs in the tooIbox takes advantage óf a methodical procéss, you can réduce bottlenecks related tó the current árt of HIL pIant model development, resuIting in earlier vaIidation of algorithm désigns. This setup was used to automate the testing of tractor controllers with hardware-in-the-loop test benches.
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