Towards a better battery model for INET Laura Marie Feeney (Uppsala - - PowerPoint PPT Presentation

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Towards a better battery model for INET Laura Marie Feeney (Uppsala - - PowerPoint PPT Presentation

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Towards a better battery model for INET Laura Marie Feeney (Uppsala University) lmfeeney@it.uu.se OMNeT++ Community Summit 15 Sep 2016 Outline batteries are complex electro-chemical systems simulating power consumption simulating

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OMNeT++ Community Summit – 15 Sep 2016

Towards a better battery model for INET

Laura Marie Feeney (Uppsala University) lmfeeney@it.uu.se

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Outline

  • batteries are complex electro-chemical systems
  • simulating power consumption
  • simulating batteries in INET using the KiBaM model
  • validating KiBaM in a testbed
  • why do we care about batteries?
  • caveats and to-do's
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OMNeT++ Community Summit – 15 Sep 2016

batteries are complicated

  • complex electro-chemical system
  • depends heavily on battery chemisty and structure

– even manufacturer specific

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Li-coin cell

  • primary (non-rechargeable) Li-coin cell

– Li anode oxidized: Li → Li+ + e- – MnO2 cathode reduced: MnO2 + Li+ + e- → Li Mn(III)O2

Li+ e- i

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  • utput voltage under load
  • load = I(t)

time

c u r r e n t 1 m A 6.2ms

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  • utput voltage under load
  • output = V(t)

voltage time

10mA, 6.2ms

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non-linear characteristics

  • rate-capacity effect

– lower current discharges the battery more efficiently – doubling the current decreases the lifetime by more than half

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non-linear characteristics

  • charge recovery

– intermittent loads discharge the battery more efficiently – 50% duty cycle more than doubles the lifetime

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non-linear characteristics

  • manufacturing variation

– batteries vary – hardware varies

  • temperature

– colder temperatures decrease the battery lifetime

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non-linear characteristics

  • device failure

– battery cannot maintain output voltage under load – depends on cut-off voltage for device electronics

failure

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non-linearities

  • experimental results suggest that non-linearities matter
  • mA-h model

– relative lifetimes vary ~15-20% among loads with the same time-

average current, but different load patterns

– absolute estimates lifetimes vary 2-3x from linear models

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modeling batteries

  • empirical models
  • electro-chemical models

– battery as chemical system (very slow, very complex) – existing models may not be well suited for fine-grain loads

  • analytic models

– V(t) = F ( I(t) )

  • equivalent circuit models

– battery as electical system (RC or RLC circuit)

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KiBaM: kinetic battery model

  • analytic model for state-of-charge

– battery fails when available charge is empty – system of differential equations

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hybrid-KiBaM: kinetic battery model

  • <math deleted >
  • simple closed forms

(fast to compute)

  • parameterization is

complex

– measurements under

highly controlled loads

– battery specific

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hybrid-KiBaM: kinetic battery model

  • equivalent circuit model for output voltage

– KiBaM state-of-charge input voltage – equivalent circuit model for output voltage

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hybrid-KiBaM: kinetic battery model

  • <math deleted >
  • simple closed forms

(fast to compute)

  • parameterization is

complex

– measurements under

highly controlled loads

– battery specific

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simulating battery powered devices

  • device activity
  • load on battery
  • battery state-of-

charge

  • battery status

affects device

battery device

status load

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device activity

  • model protocol or application
  • lowest level element that models device operation

– host can have multiple devices

device battery

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load

battery device

load

  • translate device activity into load on battery

– values based on datasheets or measurement

consumer time current TX (power) sleep

state

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load

battery device

load

  • support diverse representations of loads
  • combine loads from mulitple devices/activities

consumer

state

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battery state: mA-h battery model

  • charge = integral of current over time

– piecewise sum

  • nominal battery capacity = C mA-h
  • state: C = C – i*t

current time battery

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battery status

  • battery is depleted when C == 0
  • shut down the device

– all modules need to know (e.g. stop

generating statistics)

– INET lifeCycleManager

  • on-device battery state-of-charge

estimation

– residual capacity

battery device

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INET power consumption model

  • radio signals all state changes
  • consumer reports relevant changes to the source

– values from lookup table

KiBaM

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INET implementation issue

  • contract
  • energyStorageBase (bookeeping interface)

virtual void setPowerConsumption(int energyConsumerId, consumedPower) = 0

virtual W getPowerConsumption(int energyConsumerId) const = 0; virtual J getNominalCapacity() = 0; virtual J getResidualCapacity() = 0; EnergyConsumerEntry(const IEnergyConsumer *energyConsumer, W consumedPower) : energyConsumer(energyConsumer), consumedPower(consumedPower) {}

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INET implementation issue

  • Watts (consumption) + Joules (capacity)

– P = I * V – constant voltage sources (mains power, simple battery models) – lifetime depends on capacity

  • Amps (consumption) + Amp-h (capacity)

– I = dQ/dt – output voltage varies – lifetime depends on output voltage

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testbed

  • custon harware – large-scale low-cost testbed
  • measure controlled discharge of CR 2032 batteries
  • simple resistive loads and timing patterns
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testbed

  • INET IEEE 802.15.4 MAC layer + hybrid KiBaM battery

model

  • mimic same load in testbed
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testbed

  • INET IEEE 802.15.4 MAC layer + hybrid KiBaM battery

model

  • mimic same load in testbed
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why do we care about simulating batteries?

  • performance evaluation and dimensioning

– load has to be simulated with comparable accuracy!

  • modeling on-device state-of-charge estimation

– load/lifetime balancing – how accurate is the estimate?

  • voltage modeling

– voltage regulation – interface between the battery and the device

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thanks!

  • Christian Rohner, Uppsala University
  • UU Computer Networking Project Course

– Felix Farjsjo, Andreas Gawerth, Jonas Nilson, Eric Stenberg

  • OMNeT++ team, especially Levente
  • the audience :-)
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power consumption in networks

  • ICT infrastructure

– data centers, ISPs, etc. – energy efficiency, reduce

cost

  • battery-powered wireless

devices

– mobiles, sensor networks, IoT – maximize device or network

lifetime