Autonomie R12 New Features

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New Processes (Test cases)

Several new processes have been added & enhanced, including: European certification cycle with imposed gear & inertia weight European PHEV procedure Japan PHEV procedure BEV procedure MD & HD GEM procedure Redesigned parametric study process Redesigned performance process New static gradeability process

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New BEV & PHEV procedures - grouped together for ease of use

Go to ”Insert (View) | Header and Footer" to add your organization, sponsor, meeting name here; then, click "Apply to All"

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Display name changes can be considered.

BEV procedure J1634 shortcut

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agopal Copyr

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

x 104

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time_simu

drv_lin_spd_dmd_simu [mile/h] x 1chas_plant_lin_spd_out_simu [mile/h] x

BEV procedures (EU, Japan, US)

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Different cycles & end of test criteria

PHEV test procedures

Go to ”Insert (View) | Header and Footer" to add your organization, sponsor, meeting name here; then, click "Apply to All"

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Japan EU

Parametric Study

Now works for vehicle mass Usability enhancements: display description, default value, unit, etc. Range checking on inputs to ensure consistent results

Performance

Allow users to calculate performance characteristics of the vehicle, such as:

– 0 to 60 time – Distance it takes to

reach 60 mph – Quarter mile time – Speed reached in a

quarter mile – Speed reached in 10

seconds – Distance reached in 10

seconds

Completely flexible, users can now specify as many calculations as they want

User Modified Process

Users can drag-and-drop additional steps to existing processes (i.e. execute a user-defined .m file at the end of the process)

Steps can be re-ordered, saved, or the entire process can be saved as a new process

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Movable Modifiers

It is now possible for a user to add Movable Modifiers in a processes.

If a step is “movable” it will have a “M” on the icon and can be re-ordered, saved, re-named, or removed from the process.

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When a Movable item is selected, the arrows to the right of the Simulation Steps become enabled and allow the user to move the step. Depending on where the step is moved it can be a pre-process or post- process steps. The color of the icon will reflect which.

Work in Simulink

Add support for developers working directly in Simulink

Fast-track user interface to setup and initialize Matlab to prepare it for development work

Autonomie can open the appropriate version of Matlab, setup the path, open a model, initialize it, prepare the workspace, and run additional setup scripts

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Data Analysis Enhancements – Advanced Plotting

New plot types, like pie, column, and distribution

New signals computed directly on the plot

Additional matlab plots, such as signal derivation, signal integration, signal distribution, and non-zero signal distribution

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Data Analysis Enhancements – Advanced Plotting

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Right click on signal name in legend to access new functions Signal Analysis Functions:

You can enter any Matlab equation, using any signal/parameter from the same data set than the original signal

Data Analysis Enhancements – Advanced Plotting

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1. Click Distribution Plot icon

2. Drag and Drop Signal to plot

Signal Distribution Plot:

Column Plot for

Parameters 1. Click Column Plot icon

2. Drag and Drop Parameter to plot from the “All Data” tree to see its spread across all dataset, or one at a time from each individual dataset

Data Analysis Enhancements – Advanced Plotting

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Pie Plot for Parameters

Advanced Plot for Parameters

1. Click Pie Plot icon

2. Drag and Drop Parameter to plot from the “All Data” tree to see its spread across all dataset, or one at a time from each individual dataset

Data Analysis Enhancements – Comparing Data Sets

Available off a double click

Compare test to test, test to simulation, or simulation to simulation

Signal comparison, correlation, and map comparison

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Data Analysis Enhancements – Comparing Data Sets

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• Analyze summary values graphically by right clicking on the corresponding line and plotting their values, ratio, % change or scatter (vs another value)

• Compare or correlate 2 signals by plotting them and then right clicking in the graph, selecting the Plot submenu

Data Analysis Enhancements – Comparing Data Sets

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• When 2 datasets are loaded with different engine hot maps, you can plot the diff of the maps by double clicking on the Compare Eng eff hot trq map analysis function under Engine plant

• When loading more than 2 datasets at a time, the function will first display a GUI to select which set/inputs to use

There’s also a function to plot the matching _simu on top of it

Select Data source

Select Signal / Parameter

Data Analysis Enhancements – User Defined Plots

New system for user defined “Analysis Functions” (not limited to plots)

1. Write any .m file 2. Run the Autonomie Import Wizard 3. Associate your file to an existing file (model, initialization,

process, etc.) 4. An icon is created to launch your file, so it is available for

quick-launch whenever the associated file is used

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Data Analysis Enhancements – Windowing

Zoom in on a specific window for data analysis Re-run post-processing for the selected time interval Focus on specific areas of interest, such as transient conditions, steady-

state or “hills” of a drive cycle

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Additional Post-processing Calculations

SAE J2951 metric to evaluate the driver's performance over a cycle

Calculate percentage of energy spent by idling during the cycle

Percentage of energy used for the cycle that comes from regen

GUI Misc.

Many additional changes, including: Enforce min/max values of parameters (requirement from

numerous users) Faster load times (at start time and for the post-processing)

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Fuel cut off implemented for gasoline and diesel engines through analysis of test data

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Ford Fusion, UDDS data from APRF

Engine fuel is cut off under the following conditions:

– Vehicle is actively braking, for a certain minimum time.

– Engine speed is above a minimum threshold ( e.g. 1000 RPM).

AUTONOMIE simulation with fuel off

Large negative torque when fuel is off

Engine control and plant blocks re-organized for idle fuel rate and fuel off conditions

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Additional logic for fuel off condition in engine /control/transient

Engine torque at fuel off added to Engine plant/trq calculations*

Fuel off condition implemented in the Engine plant/fuel subsystem*

*Placeholders, the block is going to be completely reorganized.

New Driver Models

Look ahead driver and shifting algorithm – Previously, PI controller computed pedal position based on difference

between actual and target speeds – Problem with steep grades and sharp accelerations – New models “look ahead” at cycle to compute pedal position (and gear for

manual transmissions) Distance based driver

– Previously, drive cycles were time-based (i.e. run this cycle for 505 seconds) – Some applications are distanced-based rather than time-based (i.e. the cycle

is over when the semi reaches the destination, regardless of how long that takes)

– Autonomie now includes a default driver model as well as default cycles that are distance-based rather than time-based

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Model Advisor Rules

MathWorks’ Model Advisor is used to check that models are compatible with Autonomie

Rules for model format and structure can be created and easily extended

Models are checked when imported into Autonomie via the Import Model Wizard

Two rules are currently in place – A model shall contain only one block at the top level – The name of the model block shall be the same as the model name

If a model advisor check fails, the user is informed why

New Low Level Controls

Improve component synchronization during transients Easier to design, understand and modify: Stateflow instead of Simulink Central controller (gearbox) switches component modes

Example of gearbox controller

Updated Default Vehicles

All the 40+ vehicles are being updated to represent current technologies. For example, one of the change includes the use of 6 speed transmissions rather than 5 speed

A couple of additional configurations have also been added in the list of default vehicles (i.e., micro HEV)

Import Test Data

Main features: • Rename signal names, convert units, calculate missing variables, etc. • Save templates for future conversions • Allow to use your own data adaptor, or use one of the provided ones (.mat, .csv,

.xls, .xlsx, .txt) • Use Autonomie’s calculation functions for analysis like fuel economy • Examples will be provided in the next release using D3 test data Three use cases supported: 1. Import Raw Data – quick import to use Autonomie’s data analysis, i.e. first-cut

quality check on raw test data 2. Test Analysis – Select/exclude/rename signals, convert units, calculate missing

variables, automated post-processing etc. 3. Model Validation – All of the above as well as comparison and correlation to an

Autonomie vehicle model

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Import Test Data

Add Data Files and Select Data Adaptor – Users generate their own data adaptor.

Run user-defined post-processes – Calculate missing signals – Calculate fuel economy or other resutls

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Main steps for the process

Change Names and Convert Units – Once saved, the template can be reused.

Vehicle and Component Cost + Levelized Cost of Driving Assumptions and Values

Levelized Cost of Driving GUI

Example of single plant validation – Engine validation using transient engine data

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Model generated using steady state data

Conventional midsize powertrain without engine

ENGINE IN THE LOOP

Torque command

Torque feedback

Torque measurement

Speed measurement

Fuel rate measurement

Measured Torque

Measured speed Fuel rate simulation

Compare

Steps for validation of engine model using engine only configuration.

Import test data using the ‘import test data’ process. – Modify the torque signal to remove heavy oscillations at idle. – Calculate the idle fuel rate and idle torque using a postproc file.

Use engine test bench configuration for validation of engine model – Source provides engine torque command to the engine controller and plant. – Sink provides engine speed (flow) input to the engine plant. – Modify default values for engine idle fuel rate and idle torque.

New Vehicle Configurations and Controls

Vehicle configuration and transmission model for GM Voltec powertrain

Gear System

PG_system

CL1

Planetary Gear (Single Planet)

CL2

BK1

A. Compute and interpret driver demand

B. Compute mixed constraints

C. Compute series constraints

D. Request engine start and stop

F. Compute gearbox mode demand

H. Calculate MG/MG2 torque (braking) G. Compute ICE/MG/MG2 torque (propelling)

E. Manage battery SOC

I. Generate ICE/MG/MG2 torque demands

Supervisory controller

Optimization

Addition of the DIRECT optimization algorithm along with a GUI that allow users to select the input parameters and the optimization criteria

Addition of the POUNDER optimization algorithm along with a GUI that allow users to select the input parameters and the optimization criteria

Accelerate Simulation Time

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Multi-core => MPI (Message Passing Interface) (1) allows Autonomie to launch multiple instances of Matlab, one for each processor core, and run a vehicle simulation on each core

Multi-computer => Run simulations using Matlab’s Distributed Computing Toolbox(1). It allows the user to run a separate vehicle simulation on each worker node.

Multi-solver => CosiMate(2) : co-simulation framework providing communication protocols to dynamically interact between various simulation environments

(1) Already developed outside GUI - Will be integrated into next release (2) Linkage with CosiMate is being currently developed

Distributed Computing

CosiMate NetList

Integrated RTW

Compile your models for hardware using Mathworks’ Real Time Workshop directly from Autonomie

Modify any process for hardware with a simple drag-and-drop

Automates manual steps to save time and prevent mistakes

Software-in-the-Loop (SIL) Capability Autonomie supports SIL as shown in the following example Engine controller is structured with RTOS, SIL, Algo blocks

– RTOS block controls scheduling of functions in the SIL block – SIL block contains compiled production control software – Algo block contains model under development

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Software-in-the-Loop (SIL) Capability SIL block contains compiled C code subsystems Signals from the Algo model can bypass compiled functions

in the SIL block

SIL block

Algo block

Component in the loop example – Engine in the loop Default engine configuration is replaced by the engine in the loop configuration

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Default AUTONOMIE configuration of the engine system for a conventional powertrain

Engine in the loop configuration of the engine system for a conventional powertrain

Controller Plant

Experiment Controller

Plant Experiment Sensor

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Component in the Loop for engine (Engine_system_CIL) can be dragged and dropped from the Systems menu.

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Define Trip Export Trip to

CSV file Define Vehicle and Select CSV file with

Trip Data

Run Vehicle Simulation and Analyze Results

ADAS RP ADAS RP plug-in

Autonomie Autonomie

User Action

Tool

Link with ADAS-RP

(1) ADAS RP - Advanced Driver Assistance Systems Research Platform

A Process in Autonomie Was Created to Generate a Trip from User Inputs on a Map