ETAS ASCMO 5.2 Release Notes. Release Notes. Page 1 of 12

Transcription

1 Page 1 of 12

2 Copyright The data in this document may not be altered or amended without special notification from ETAS GmbH. ETAS GmbH undertakes no further obligation in relation to this document. The software described in it can only be used if the customer is in possession of a general license agreement or single license. Using and copying is only allowed in concurrence with the specifications stipulated in the contract. Under no circumstances may any part of this document be copied, reproduced, transmitted, stored in a retrieval system, or translated into another language without the express written permission of ETAS GmbH. Copyright 2018 ETAS GmbH, Stuttgart The names and designations used in this document are trademarks or brands belonging to the respective owners. Page 2 of 12

3 Contents 1 Introduction Conventions User Documentation Product Definition Functions at a glance General Description System Prerequisites Software Prerequisites Delivery Used 3 rd Party Software Installation Installation Hints Licensing Changes What s New Compatibility to Earlier Releases Fixed Problems Known Issues Known Issue Reports Contact, Support and Problem Reporting Page 3 of 12

4 1 Introduction 1.1 Conventions The following typographical conventions are used in this document: Choose File. Menu commands are shown in boldface. Click OK. Press <ENTER>. The "Open File" dialog box is displayed. Select the file setup.exe A distribution is always a one-dimensional table of sample points. Buttons are shown in boldface. Keyboard commands are shown in angled brackets. Names of program windows, dialog boxes, fields, etc. are shown in quotation marks. Text in drop-down lists on the screen, program code, as well as path- and file names are shown in the Courier font. General emphasis and new terms are set in italics. 1.2 User Documentation The ETAS ASCMO user documentation in PDF format can be found in the installation directory under the folder Manual. After installation, the user documentation can be opened in ASCMO under the menu entry Help and it can also be found under C:\Program Files\ETAS\ASCMO Product Definition 2.1 Functions at a glance ETAS ASCMO is the ideal solution for data-based modeling and model-based calibration. It enables users to accurately model, analyze, and optimize the behavior of complex systems based on only a few measurements and using advanced algorithms. Both, steady-state and transient system behaviors can be captured. Furthermore, it allows optimizing parameters of physically based models. The name ASCMO is the abbreviation of Advanced Simulation for Calibration, Modelling and Optimization. ETAS ASCMO-DESK (Base product) ETAS ASCMO-DESK serves as common launcher for the main products ASCMO-STATIC, ASCMO-DYNAMIC and ASCMO-MOCA. In addition, it contains beneficial tools for managing, and generating driving cycles, to visualize scatter plots and edit calibration data. The following modules are included: Cycle Generator: Allow to generate driving cycles based on existing cycles with similar properties. It also allows using a simplified powertrain model to convert from vehicle speed to engine speed/load. Scatter Plot: Module to visualize measurement data from e.g. Excel or MDF-files in different scatter plots. Here, points can be marked and highlighted in different colours synchronously in all plots. Calibration Data Editor: Allows managing, editing and exporting calibration data. In addition the number of grid nodes of a given calibration map/curve can be reduced while considering best possible fit to the original shape. Page 4 of 12

5 There are three main Add-ons to ETAS ASCMO-DESK: ETAS ASCMO-STATIC (main product 1/3) ETAS ASCMO-STATIC allows to describe the steady-state behaviour of complex systems using modern data-based modelling approaches with much higher accuracy than classical DoE-models. In addition both variance and validity of trained models are indicated. The models do not need to be parameterized by the user, which makes ETAS ASCMO-STATIC very easy to use also for less- or even non-experienced users. Furthermore, ETAS ASCMO-STATIC offers a variety of possibilities for visualizing and optimizing the system behaviour based on the models and generate statistical DoE test plans (Design of Experiments) ETAS ASCMO-DYNAMIC (main product 2/3) ETAS ASCMO-DYNAMIC allows to describe the dynamic/transient behaviour of complex systems. Efficient, statistical learning processes (Gaussian processes) are utilized which have been modified specifically for the mapping of dynamical behaviors. The models can be exported in several formats such as C-Code or Simulink. Furthermore, dynamic DoE test plans can be generated. ETAS ASCMO-MOCA (main product 3/3) ETAS ASCMO-MOCA allows the efficient parameter optimization of physically based models. The models can be integrated as formula, Simulink -, ETAS ASCET- or ETAS-ASCMO models. ETAS ASCMO MOCA enables automatic optimization of all model parameters at once and minimizes the deviation between model behaviour and desired output value. The optimization procedure is fast and easy due to ETAS ASCMO-MOCAs intuitive graphical user interface. In the same way also the parameters of physically based models from other environments such as Simulink or GT-SUITE can be optimized. There are 2 versions of ETAS ASCMO-MOCA: o Developer Full access to all functions. Especially the definition of the function logic and the sequencing of the optimization process can be created, modified and analysed. The ready-to-use project can also be exported as ETAS ASCMO- MOCA Runtime to protect the IP o Runtime The predefined project from the developer version of ETAS ASCMO-MOCA can be loaded and used without having access to the IP-critical parts. There are several Add-ons to ETAS ASCMO-STATIC: Global Optimizer (GO): Allows global optimization of all input variables in the entire operating range in terms of total emissions and consumption. Here, the relevant driving cycle as well as other conditions such as local limits and map smoothness are taken into account. Software Developer Kit (SDK): For the flexible extension of the standard functions and the integration of additional models, optimization algorithms, flow control/scripting or for connection to a test bench automation, ASCMO-SDK provides an open MATLAB -interface. Model Export (ME): Allows the export of models to be used outside of ASCMO in other environments such as Matlab, Simulink, C-Code, Python, Excel VBA, ETAS INCA/MDA or as FMI/FMU. Page 5 of 12

6 Signal Modeling (SIG): Allows the modeling of signal traces such as cylinder pressure curves. By connection to the ETAS ASCMO model, the effects of different combinations of input parameters to the signal trace can be visualized and analyzed. Model Compression (MCI): Allows keeping the speed of ASCMO on the usual level even for huge data sets - especially relevant for the integrated optimizers. It reduces in a smart way the number of used data points and by this the complexity of the models. With this Add-On it is possible to use the compressed models within ASCMO. Model Compression Export (MCE): Allows using compact and efficient models outside of ASCMO especially in real-time environments such as XiL-systems and ECUs. It reduces in a smart way the number of used data points and by this the complexity of the models. With this Add-On, it is possible to use the compressed models within ASCMO and export the models to the standard environments such as C-Code or Simulink. 2.2 General Description System Prerequisites The following minimum system prerequisites have to be met: Required Hardware 1,0 GHz PC 1 GB RAM DVD-ROM drive Graphics with a resolution of at least 1024 x 768 Required Operating System Required Free Disk Space Windows 7 (64 bit), Windows 10 (64 bit) 32 Bit Operating System no longer supported. 3 GB (not including the size for application data) The following system prerequisites are recommended: Recommended Hardware Recommended Operating System Recommended Free Disk Space 2,0 GHz Dual-Core PC or equivalent 8 GB RAM DVD-ROM drive Network adapter Graphics with a resolution of 1680 x 1050 Windows 7 (64 bit) >3,0 GB Page 6 of 12

7 2.2.2 Software Prerequisites 2.3 Delivery To use the ETAS ASCMO Add-on Software Developer Kit (SDK), Matlab version R2016a up to R2017b and the Matlab Optimization Toolbox and Statistics Toolbox are required. There are no additional SW-prerequisites for the ETAS ASCMO Base-Product installation and all other Add-ons. All necessary prerequisites will be installed Used 3 rd Party Software See document ASCMO_OSS_Attribution.pdf and Lima_OSS_Attribution.pdf. 2.4 Installation To install ETAS ASCMO, please insert the installation medium into the drive on your computer. Run Setup_ASCMO_x64.exe in the respective folder. After the installation, start ETAS ASCMO by clicking on the ASCMO Desk 5.2 icon on desktop or from the start menu under All Programs\ Installation Hints To use the ETAS ASCMO Add-on Software Developer Kit (SDK), ETAS ASCMO must be run in Matlab: cd( C:\Program Files\ETAS\ASCMO 5.2\pCode\ascmo ) and enter id = ascmo( AscmoStatic ) in the command window. 2.5 Licensing For details on the licensing, see the manual chapter 2.4. Page 7 of 12

8 3 Changes This chapter describes the changes with respect to the previous version (ETAS ASCMO V5.1). 3.1 What s New ASCMO General ASCMO Static Allow to export to Simulink without installed Simulink as a Matlab build m-script Export of ASC GP model to Simulink changed to prevent long pause during first run Exported ASC GP model in Simulink and Matlab run much faster Exported m-script for Simulink and Matlab is changed for the two improvements mentioned above Scatter Plot now allows to show extra windows on demand Data Importer shortcuts <Ctrl+O> (Output), <Ctrl+I> (Input), <Ctrl-R> (Remove) for channel assignment Data Importer Channel configuration now stores the sample time Data Importer Channel configuration is now case-insensitive New Out-Of-Process COM-Server to interface Ascmo from 32 Bit applications. This new COM interface is string based, which is easier to use. Python example to show usage. Import of MDF now avoids NaNs at the beginning Advanced options are shown in cursive font New Interfaces: prepareprint New model type GP SCS for modelling with small number of basis functions Outlier Detection invariant under output transformation Graphical Updates after change/delete of data ASCMO Dynamic MOCA Allow to export models of type Recurrent Neural Networks Model->Training dialog overhauled: has more options and allows training of RNN models Moved NARX specific options to submenu Three options for initial state of NARX structure: 1. First seen, 2. Use NaN, 3. Constant value. This option also effects the exported models. Allow to delete leading/trailing NaN from data Improved RNN model training: take best not last iteration RNN model training can now continued Scatter Plot now allows to show gradients and inputs in one window and many more options FMU 2.0 support 32/64 Bit (as plant and with parameter access for optimization) FMI-Kit FMU exports from Simulink supported to handle Curves/Maps in addition to scalars Page 8 of 12

9 Import/Export function as text Parameter Sensitivity analysis Sensitivity, i.e. gradient with respect to the parameters, of a Node are evaluated for all the training data. Shown gradients are normalized to parameter upper/lower limit. A Curve e.g. with 20 breakpoints is shown as 20 consecutive values. Light grey shows the maximum gradient of all training data points. Light grey shows mean +-1 sigma of gradient of all training data points and the red line shows the mean of gradients of all training data points. Parameter Correlation analysis: C=(G * G + I)^-1, with G being the gradients with respect to the parameters Change of optimization parameters (e.g. limits, active parameter, no. of iterations) now don t start a recalculation of the RMSE When mapping Simulink parameters duplicates are avoided now Import/Export Input Dependant Bounds Allow to enable/disable data sets by setting weight to 0, also in Sequence Allow to start MOCA-Runtime in Matlab (p-code) New Interface Functions: getparameterfield, getoriginaldata, getparameterproperties, importparametermoca now allows to import bounds Cycle Generator ExpeDes Static Retain cycle names when exporting and re-importing Allow to edit Units Allow to export multiple CSV files at once Scripting can now be done without GUI (silent option) Switch off shrinking when clustered points are imported ExpeDes Dynamic Allow to insert parts of existing cycle from file into generated plan Allow to export plan with intermediate points Allow to show density plot for gradients Calibration Data Editor Added feature for Map Inversion/Axes Conversion with batch mode Map Inversion/Axes Conversion has the option to generate new support vector with optimized positions 3.2 Compatibility to Earlier Releases Downward compatibility: can open all project files from ASCMO V4.2 to V5.2 Upward compatibility: files can be opened only with ASCMO 5.2 or newer 3.3 Fixed Problems ID Title [All] If loading file from network share, you may get the error that the file is not readable Page 9 of 12

10 [ASCMO Dynamic] GP SCS has Save/Load Problem [ASCMO Dynamic] RNN Model Training issues when training data is negative [ASCMO Static] Cancelling the waitbar during LOO-error calculation leads to subsequent errors in model training [ASCMO Static] Model Export works unexpected if inputs are deactivated [ASCMO Static] Optimization at List produces application error [ASCMO Static] Optimization of local system (no OPs) fails [ASCMO Static] Using the ascmowaitbar Interface combined with multiple Modell Trainings does not work [Expedes] Non-valid data in constraint table values leads to error [MOCA] Active data and Simulink models does not work [MOCA] If e.g. a Simulink model evaluation fails during optimization, this leads to an error [MOCA] Imported ASCMO-DYN model causes error Page 10 of 12

11 3.4 Known Issues 1. Japanese Manual and Online-Help are not updated yet and show Version ASCMO V5.0. The translated V5.2 manual can be downloaded from the ETAS website in the future. 2. Using the Relative Error as modeling criterion sometimes causes unexpected model behaviour. 3. Using the option Autosave after Training produces many files project.autosave.autosave.[ ].ascmo files. 3.5 Known Issue Reports If a product issue develops, ETAS will prepare a Known Issue Report (KIR) and post it on the internet. The report includes information regarding the technical impact and status of the solution. Therefore you must check the KIR applicable to this ETAS product version and follow the relevant instructions prior to operation of the product. The Known Issue Report (KIR) can be found here: Page 11 of 12

12 4 Contact, Support and Problem Reporting If you have any questions about this release, please contact the ETAS-support: Europe (except France, Belgium, and Luxemburg): France, Belgium, and Luxemburg: USA ETAS INC ( ) Japan +81-(45) Korea +82(2) China India In case of a bug, please send the project (.ascmo,.exde and/or the.xls-file with the trainingdata). Additionally, please send also the error-message from the log-window and the log, which can be saved to a file by right-clicking in the log-window. It might also be helpful to send the extended log which can be found under C:\Documents and Settings\<username>\Local Settings\Temp \ASCMO.log. Page 12 of 12