Physical Modeling with SimScape - bits-chips.nl. Van den Brand, Mday 29-4-2011 2 Bio •Adriaan van...

A. Van den Brand, Mday 29-4-2011 1

Physical Modeling

with SimScape

Adriaan van den Brand

Mday 29-4-2011

Saving energy with Physical Modeling

V1.4


Bio

• Adriaan van den Brand

• System architect Sogeti High Tech

• Embedded systems experience:− Embedded Software

− Software architecture, system architecture

− 7 years automotive (Ford, BMW, Visteon, NXP)

• Current role− System architect at Philips Innovation Services

− Hybrid drive trains for commercial vehicles

[email protected]


Recognizable?

3

Smart phone : 300 hour standby-tijd or 1 day usage?

Car: 3.9 l/100km in brochure 5.8 l/100km in real life?

How long does your energy supply really last?


Agenda

• Title & Bio

• Agenda

• Project

• Model− Common vs. physical modeling

− abstract to reality

− Wat, how & why

• Experiences & Conclusions

• Q&A


Project

Goals

Challenges

Role

Titel & Bio

Agenda

Project

Model

Conclusions

Q&A


Project background

• Hybrid drive train commercial vehicles

• Requirements (!)− Maximum CO2 reduction

− Maximum fuel savings

− Realistic estimations fuel usage

Info: [email protected]


Goal : Model

• Model is used to determine− Energy saving potential (and CO2, ….)

− Optimum system architecture

− Component selection

− Strategies (regeneration)

• Understand before building− Validation based on existing vehicles and setups


Challenge 1

• What is maximum?

• Which „knobs‟ to turn?

• What to model ?

• Modeling energy streams− Chemical (Internal combustion engine)

− Electrical (Battery)

− Mechanical (Rotation)

− Mechanical(Translation)

− Physical Modeling (Matlab/Simulink+SimScape)


Understanding energy flows

• Saving starts with understanding energy flows

Aux

Air Resistance

Vehicle Inertia

Regenerative Breaking

Brakes (Hydraulic/Pneumatic)

HVAC

Rolling resistance

Battery Losses

Waste Heat

Cooling

Mechanic losses vehicle

Mechanic losses body


Challenge 2 : Multi-disciplinary model

• Disciplines− Electric, Mechanics, Pneumatics, Hydraulics, Software

• Interfaces?

• Environment?

• Re-use of existing Simulink models?

• How to fill the missing pieces?


Project : model centric

Key Performance IndicatorsReal world data System model

control &

softwareElectric

Mechanics


Steps

• 1. Understanding energy in basic function− Traction, air drag, rolling resistance, electric system

Domains:

◦ Mechanical (Newton’s laws)

◦ Electrical (iso-efficiency curves)

• 2. Understanding real use− Observing the users, harvesting data from measurements

• 3. Understanding energy in ALL other functions− Air-conditioning, power steering, braking, ….

− Domains: mechanic, electric, hydraulic, pneumatic, thermal

• 4. Refinement & control model− Dynamics

4

1

2

3


Design Space Exploration (project)

• Analysis of optimal system− Top down analysis

− Application domain

• Model refinement− Energy conservation

• Component-choices

1

4

Design Space

F=M*aP=½mv2

Application

Available technology

E-Motor-x

Hybrid mode

series parallel

E-Motor-y

Users


• 1st model: simplicity “brick on wheels”

• 2nd iteration

− Model with detailed subsystems

◦ Motor-behavior, gear boxes, battery models etc.

• Finally

− Virtual prototype with the same interfaces as the real product

− Model with scaleable simulation times

Model in project

Simple, cheap

Determine ideal results

“Best case prediction”


Models

Reference process

Physical modeling

Titel & Bio

Agenda

Project

Model

Conclusions

Q&A


Models :

Backward facing (reference)

1

7

Reference

EnvironmentModel Result

Standard drive cycle

speed = f(t)

Backward

facing model


Models:

Backward facing (common) (2)

• Vehicle„pulls‟ at the wheels

• Wheels turn the gears

• Gears „turn‟ the motor

• Calculate required energy extraction from battery

• reverse world…. Model != reality− doesn’t fit expectations

1

8

gearωwheel

vvehicle

Froll+Fdrag

1T

ωmotor

Τmotor

Pmech ηwheel ηgear ηmotor ηbattery

M+

Ubatt

ibatt

= Pelectric/ / / /


Realistic model (forward facing/physical)

• Action = - Reaction

• Model reflects reality

1

9

ControlsDriverRoute Traffic

G

AlternatorEngine Vehicle

1T

Tyre

Model

Gear&diff

M+

Battery E-motor


Physical Modeling

• Physical signals− Voltage and currents (electric domain)

− Torque and ω (mechanic domain)

− Flow and pressure (and temperature) (pneumatic domain)

− interface independent of implementation!

− Energy in Watt

• Preservation of energy− Energy preserving ports (bi-directional)

− Direction of signals is determined by solver

◦ Action = - reaction

− Energy can be translated to other domains

− Waste energy (heat) is also energy

2

0


Physical Modeling : Electric Motor

2

1

Result: torque

Cause: current

• Electric motor : current rotationCurrent

source M

i

ground

Mechanic reference

(chassis)

U

rotatie


Physical Modeling : Electric Motor (2)

2

2

100 Nm

Cause: torqueResult: current/voltage

• Regenerative braking

• Kinetic energy of vehicle is converted in electricity

• Motor as alternator

M

i

ground

Mechanic reference

(chassis)

U rotation


Physical Modeling : inside E-motor

• Motor is also a model

• Parameters

• Electric substitution

• Non ideal attributes

i

ground

rotation

U

R

L

friction

inertia

Electric

Interface

(Rotating)

Mechanic

interface

Τ:=K*i

U:=K*ω

(K=constant of

proportionality V/

(rad/s) )


Physical interfaces Simulink

• Normal Simulink model:

• Physical model

Fewer connections

Better maintainability

Physical model

Standardization of interfaces


M

i

ground

Mechanic reference

(chassis)

U

rotatie

2

Physical Modeling : Top Down

1

3

G

AlternatorEngine Vehicle

1T

Tyre

Model

Gear&diff

M+

Battery E-motor

i

ground

rotation

U

R

L

friction

inertia

Electric

Interface

(Rotating)

Mechanic

interface

Τ:=K*i

U:=K*ω

(K=constant of

proportionality V/

(rad/s) )


Physical Modeling: energy centric

Energy is important: in all domains

-Concepts comparable- (resistance, load, buffer)

-Coupling domains using converters

- Motor = converter (electric rotering mechanic) Energy

◦ Losses (heat) = thermal energy

◦ Piston (Pneumatic/hydraulic)

◦ Pump ….

2

6


Same interfaces, different models

• Interfaces are stabile− Components exchangeable using variants

◦ Runtime configurable variants

− Scalable simulation accuracy

◦ System level: >>2x real time

› Lookup tables (datasheet info); straightforward

◦ Mean level : 1-2x real time

› i.e. E-motor model reveals 3-phase control

◦ Detailed level:10-20x slower than real time

› i.e. PWM modulation of E-motor inverter

− Current focus: mean level. Good results, reasonable time

27


Model features

• Variation of − Driving cycles

− Components & Component parameters

− Topology

− Driver behaviour

− Environmental conditions (i.e. weather)


Conclusions

Experiences

Conclusions Project

Conclusions Method

Titel & Bio

Agenda

Project

Model

Conclusions

Q&A


Project: scaleable model

• Evolutionary model (grows with project)− Top down

◦ (system) to detailed level

◦ Further refinement possible

◦ No surprises in model validation

◦ Maximum energy saving

− Multi-disciplinairy

◦ Energy centric

• Interfaces stabile− Physical interfaces = reality

• Tooling− Matlab/Simulink

− Extra SimScape/SimDriveline(physical modeling)

3

0

Design Space

F=M*aP=½mv2

Application

Available technology

E-Motor-x

Hybrid mode

series parallel

E-Motor-y

Users


Experiences

• Learning time− Physical model != average Simulink model

− Idealized models don’t work (physically impossible)

− Limited knowledge in industry

− Modeling is learning about the domain

• Tool− SimScape family is very powerful

◦ Little need to dive into bondgraphs and diff. equations

− SimDriveline: powerful interfaces, (too) simple components

− SimElectronics, SimMechanics: interesting toolboxes


Experiences: tool improvements

• Room for improvements in tools:− Hard-to-find Solver issues

− Infinite logging to HD

◦ Much time is lost into squeezing logging into <2GB

− Sampled logging

◦ No interest in femto-second events

◦ decimation doesn’t scale with large step size

− Diff/Merge support

• Wish list for our model− Nightly builds/runs

32


Conclusions

• “Physical modeling”

Excellent for mechatronic models

Modeler is forced into realistic designs

(Extremely) scaleable model

Ideal for for energy saving

Good interfaces

Fewer interfaces, with higher quality

Re-useable components

− Disadvantages

◦ Learning time from simulink (different way of thinking)

◦ Solver limitations for control & plant


Judgement

Physical Modeling is a powerful tool

- to save energy (by modeling)

- To save energy (making the model)


Physical Modeling

with SimScape

Questions?

[email protected]

Titel & Bio

Agenda

Project

Model

Conclusions

Q&A


Interface types

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