ARLPenn State

The Next Step

Battery Prognostics for Enhanced

Combat Vehicle Readiness and

Reduction of Total Ownership Costs

Dr. James Kozlowski

Complex Systems MonitoringThe Pennsylvania State UniversityApplied Research Laboratory

(814) 863-3849 jdk173@psu.edu

NDIA Tri-Service Expo on Power Management 15 July, 2003 Norfolk, Va.

USMC Light Armored Vehicle LAV-25

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Presentation Outline

• Needs for Battery Monitoring

• Available Technology Comparison

• Model-Based Battery Prognostics

• Operational Implementation

• Operational Risk Management

• Impact to Life Cycle Costs

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New Capability Availableto the Warfighter

• Will the battery crank the engine? How

Many more times?

• Before I shutdown, is the battery ok?

• I’m on silent watch, how much longer

can I go and be sure I can restart?

• This battery has been in storage, is it

still good and charged?

• What’s the electrical problem- the

alternator or battery? Which battery?

Prognostics Information to:

•Operator

•Maintainer

•Log/supply

•PM

•Command/Ctrl

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Battery Health Monitoring

• Carry backup or reserve batteries

• Over-design batteries to reduce use and time between failures

• Heavy, costly

Present Solutions:

New AlternativeUse an online battery monitoring system to detect and predict impending faults and assess available power and usage time

Serviceability11%

Damaged2%

Open Circuit12%

Short Circuit27%

Corrosion32%

Wear Out16%

Failure Modes as a Percentage of Total Automotive Battery Failures

“Batteries for Automotive Use”, P. Reasbeck and J.G. Smith

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Why not just use off-the-shelf battery monitoring products?

• Open-Circuit Voltage : accuracy

• Discharge Test : time and equipment

• Coulomb Counting: need full discharge

• Temperature: harsh environment

• Specific Gravity: SOC only, sealed?

ARLPenn State Technology Comparison

Standard Technologies:Commercial State of Charge (SOC) technologies

use a very simple measurements of voltage, current, temperature and internal impedance.

• Voltage Monitoring: Compares voltage to SOC table.

– Measurements must be made off-line and drop off voltages are difficult to measure accurately.

• Coulomb Counter: Measures total amount of current in/out of battery.

– Low accuracy due to battery self-discharge and temperature variations.

• Internal Impedance: Measurements are based on impedance values at a few frequencies.

– Models are highly frequency dependant so SOC estimates have 10% – 20% error.

• Limited State of Health (SOH) and State of Life (SOL) information available with these methods.

Impedance Interrogation Technology:Uses patented complex impedance measurement to

estimate SOC, SOH and SOL on-line.

• Impedance measurement covers broad range of frequencies.

– High resolution impedance image creates accurate model for analysis.

– SOC prediction: 1% to 2% error• Fuzzy Logic, Neural Network and ARMA

models with decision fusion algorithm.– Multiple predictions provides a higher

level of performance and increased confidence.

• SOH provides classification of the failure mode.

– Improves prognostic capability• SOL - remaining useful cycles prediction is

dependant upon accurate failure mode identification.

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Impedance Interrogation

Excitation IN Response OUT

Characteristics of Internal Condition and Activity

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Isn’t impedance-based technology available in off-the-shelf products?

There is a lack in performance for both

measurement techniques and

processing of the information

Yes, but…

And therefore…

There is a perception that impedance-based technology cannot effectively assess the condition and health of a battery

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Neural Network

Fuzzy Logic

ARMA

User Interface

ImpedanceProcessing Electrochemical Model

Identification

SOC, SOH, and SOL Estimators

Ex,Sn

Feature VectorFiles

SOC, SOH, SOLEstimation FIles

Data Fusion Workbench

User InfoFile

HistoryKnowledge

Decision Fusion

HistoryKnowledge

if,...then

Battery Prognostic Processing Architecture

LAV Installation

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Test ARMA N.N. Fuzzyerror error error

No Load 7.08% 3.41% 7.90%

ISOC 3.07% 3.15% 3.52%

CSOC 1.52% 2.96% 2%

Example from SOC Testing Results20% Train / 80% Test

Training and Testing Results from SLI Lead-Acid Battery Set (-10 to 50 degrees C)

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Tactical Use of Battery Prognostics

• Fast, reliable predictions of State-of-Charge, State-of-Health and State-of-Life with performance errors <5%

• A low power system (<1/2 watt) that is co-located with battery

•Gives broadest range of tactical information before, during and after mission:-State of charge: ready to start

-State of life: condition during use-State of Health: readiness for future mission(s)

•Applies to huge range of battery types, sizes and uses•Example of True Prognostics Capability

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MANAGING OPERATIONAL RISK WITH BATTERY PROGNOSTICS

User interface describing state of battery health, life and charge to the operator.

Information presented before operation (availability) and during operation (maintaining op tempo and managing operational risk)

Fault failure information provided to maintainer

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Location• Vehicle identification• Location (GPS)• Time-of-day

Location• Vehicle identification• Location (GPS)• Time-of-day

Condition MonitoringIntelligent Nodes

Wired, wireless or SneakerNet

Diagnostic Monitoring Unit /Info

Server

Asset Visibility Intelligent Node

ReadinessIntelligent Node

Tactical Combat VehicleSystem Layout

Condition/Health• Battery Health and

State of Charge• Engine Health

Information• Power Train Health

Information

Condition/Health• Battery Health and

State of Charge• Engine Health

Information• Power Train Health

Information

Performance/Status• Warnings• Advisories• Status, levels

Performance/Status• Warnings• Advisories• Status, levels

Smart Maintainter

Vehicle Data Bus/Networking

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Platform Status Information Exchange ………

SME

Supply

SmartMaintainer

TransferDevice

CMMS

LCMSPM

MC

What is the status of all my platform Cs?

What is broken or about to break on this vehicle?

I want to report a problem in to CMMS.

Give battery health data for all of

platform type As?

What is going to break on any of

platform Bs?

OPSLogistician

Planner

Do I have assets for the upcoming mission?

When do I need to buy material for systems that are predicted to

fail?

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 2

VehicleType ABlock 2

VehicleType ABlock 2

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType BBlock 2

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 1

VehicleType ABlock 2

VehicleType ABlock 2

VehicleType CBlock 2

VehicleType BBlock 1

VehicleType CBlock 1

Condition Interface Engine: We need to define the requirements for

the interface between vehicles and corporate systems and select

information standards to implement.

Operator

CMMS = Computerized Maintenance Management SystemGCSS = Global Combat Support SystemISEA = In-Service Engineering AgentLCMS = Life-Cycle Management SystemMC = Maintenance ControllerOPS = OperationsPM = Program ManagerSME = Subject Matter Expert

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Benefits of Battery Prognostics

Benefit Category Impact of Battery Prognostics Benefits to All Vehicles Using 6TL Battery Types (P/A)

Operational Availability

-Eliminates unanticipated failures-to-start

-Enables management of battery power during silent watch

-confirms state-of-charge and state-of-health prior to attempted start

-provides state-of-charge and remaining useful life during silent watch

513,488 lost hours (out-of- service time)

Maintenance

- Isolates fault to a specific battery

-Confirms good condition of battery (visa electrical system problem)

-Stops unintended replacement of good batteries

-Stops the practice of replacing battery farm when only one is bad

-Prevents unnecessary battery removal as part of electrical system diagnosis

-Identifies battery mode of failure and indicates cause

$2.698M per year

Log/Supply

-Reduces number of batteries in inventory

-Provides anticipatory needs for battery replacement

-Extended life of batteries

-A priori determination of need for battery replacement

$5.565M

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Prognostics/CBM Effect on LCC

$400,000,000

$500,000,000

$600,000,000

$700,000,000

$800,000,000

$900,000,000

$1,000,000,000

$1,100,000,000

$1,200,000,000

$1,300,000,000

$1,400,000,000

5 7.5 10 12.5 15 17.5 20 22.5

Length of Estimate (Years)

To

tal

Lif

e C

ycle

Co

st

Adjusted Prognostics

LCC Without Prognostics

LCC With Prognostics

Cost/Benefits Top Level-AAV RAM/RS Studies

Benefits increase as

service life is extended

3-4 yr. payback

“s” shape effect due to deferred depot overhauls

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AAV RAM/RS Data (Hours) W/O Prog W/ProgMean Time Between Failures 64 73.6Mean Time To Repair 0.87 0.87Mean Logistics Delay Time 5.4 2.7675

AAV RAM/RS Calculations W/O Prog W/ProgForecasted Op Availability 91.08% 95.29%Increase in Op Avail w/Prog 4.21%Increased AAVs Mission Capable w/Prog 29Total LCC Costs per AAV w/Prog $973,504Operational AvailabilityOpportunity Benefit of Prognostics $27,890,754

Top Level- EFV (AAAV) Increased Operational Availability

Benefits can either be: increased Ao; decreased life cycle cost or reduced number of assets for same total operational availability

Increase in Operational

Availability As a result of CBM+

ARLPenn State

Applied Research Laboratory

PennState University

ARL Penn StateP.O. Box 30

State College, Pennsylvania 16804www.arl.psu.edu(814) 865-6343

SUMMARY

• Battery Prognostics is Real

• High accuracy over present techniques

• High value added to the warfighter

• Enabling capability to manage operational risk, increase operational readiness and reduce life cycle costs

This work was supported by the Office of Naval Research and Dr. Philip Abraham, Code 331, under ONR Grant N00014-98-1-0795.