arl penn state the next step battery prognostics for enhanced combat vehicle readiness and reduction...
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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 [email protected]
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.