A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Wiesbaden
Springer Fachmedien Wiesbaden GmbH
2023
Springer Vieweg 2023 |
| Edition: | 1st edition 2024 |
| Series: | AutoUni – Schriftenreihe
|
| Subjects: | |
| Online Access: | Inhaltstext Auszug Inhaltsverzeichnis |
| Physical Description: | Approx. 300 p. 21 cm x 14.8 cm |
| ISBN: | 9783658431877 3658431873 |
Staff View
MARC
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| 100 | 1 | |a von Bülow, Friedrich |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries |c Friedrich von Bülow |
| 250 | |a 1st edition 2024 | ||
| 263 | |a 202312 | ||
| 264 | 1 | |a Wiesbaden |b Springer Fachmedien Wiesbaden GmbH |c 2023 | |
| 264 | 1 | |b Springer Vieweg |c 2023 | |
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| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a AutoUni – Schriftenreihe | |
| 650 | 0 | 7 | |a Lithium-Ionen-Akkumulator |0 (DE-588)7681721-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Structural Health Monitoring |0 (DE-588)1088793878 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Batteriefahrzeug |0 (DE-588)4144126-6 |2 gnd |9 rswk-swf |
| 653 | |a Lithium-ion battery | ||
| 653 | |a state of health | ||
| 653 | |a battery aging | ||
| 653 | |a transfer learning | ||
| 653 | |a machine learning | ||
| 653 | |a forecasting | ||
| 653 | |a battery electric vehicles | ||
| 655 | 7 | |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
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| 689 | 0 | 1 | |a Lithium-Ionen-Akkumulator |0 (DE-588)7681721-0 |D s |
| 689 | 0 | 2 | |a Structural Health Monitoring |0 (DE-588)1088793878 |D s |
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Record in the Search Index
| _version_ | 1808587436515655680 |
|---|---|
| adam_text |
CONTENTS
1
INTRODUCTION
.
1
1.1
MOTIVATION
.
1
1.2
RESEARCH
QUESTIONS
.
4
1.3
STRUCTURE
OF
THIS
THESIS
.
6
2
THEORETICAL
BACKGROUND
.
9
2.1
LITHIUM-ION
BATTERIES
.
10
2.1.1
OPERATING
PRINCIPLE
AND
COMPONENTS
OF
LITHIUM-ION
BATTERY
CELLS
.
10
2.1.2
PARAMETERS
FOR
CHARACTERIZATION
AND
OPERATION
OF
BATTERIES
.
12
2.1.3
STATE
OF
HEALTH
AND
REMAINING
USEFUL
LIFETIME
.
15
2.1.4
FUNDAMENTALS
OF
LITHIUM-ION
BATTERY
CELL
AGING
.
19
2.1.5
BATTERY
PACKS
.
23
2.1.6
BATTERY
OPERATION
.
28
2.2
SUPERVISED
MACHINE
LEARNING
FOR
REGRESSION
PROBLEMS
.
35
2.2.1
ARTIFICIAL
NEURAL
NETWORKS
.
35
2.2.2
FEATURE
SCALING
.
39
2.2.3
HYPERPARAMETER
TUNING
.
40
2.2.4
METRICS
FOR
REGRESSION
PROBLEMS
.
41
2.2.5
TRANSFER
LEARNING
.
42
3
TOWARDS
STATE
OF
HEALTH
FORECASTING
OF
LITHIUM-ION
BATTERIES
.
45
3.1
STATE
OF
HEALTH
ESTIMATION,
PREDICTION,
AND
FORECASTING
.
45
3.2
STATE
OF
HEALTH
FORECASTING
VS.
REMAINING
USEFUL
LIFE
PREDICTION
48
3.3
SCENARIOS
IN
STATE
OF
HEALTH
FORECASTING
.50
XVI
CONTENTS
3.4
BATTERY
MODEL
TRANSFER
.
52
3.5
MODEL
KEY
CRITERIA
.
53
4
RELATED
WORK
.
57
4.1
SCREENING
METHOD
.
58
4.2
STATE
OF
HEALTH
FORECASTING
MODELS
.
61
4.2.1
MODELS
WITHOUT
INFORMATION
ABOUT
FUTURE
LOAD
.
68
4.2.2
MODELS
WITH
INFORMATION
ABOUT
FUTURE
LOAD
.
69
4.3
TRANSFER
LEARNING
FOR
BATTERY
MODELS
.
75
4.4
GAPS
OF
RELATED
WORK
.
76
5
DATA
.
79
5.1
LABORATORY
BATTERY
CELL
DATA
SETS
.
80
5.1.1
STANFORD
BATTERY
DATA
SETS
.
80
5.1.2
RWTH
AACHEN
ISEA
CYCLIC
AGING
DATA
SET
.
84
5.1.3
NASA
RANDOMIZED
BATTERY
USAGE
DATA
SET
.
84
5.1.4
OXFORD
DEGRADATION
DATA
SET
.
85
5.2
REAL-WORLD
BATTERY
ELECTRIC
VEHICLE
SYSTEM
DATA
SET
.
86
6
BATTERY
CELL
STATE
OF
HEALTH
FORECASTING
.
91
6.1
METHOD
.
91
6.1.1
STRESSOR
EXTRACTION
.92
6.1.2
DECISION
ON
SIGNAL
SELECTION
.
96
6.1.3
MACHINE
LEARNING
REGRESSION
MODEL
.
97
6.2
DESIGN
OF
EXPERIMENTS
.
97
6.3
RESULTS
.
101
6.4
SUMMARY
AND
CONTRIBUTION
TO
THE
RESEARCH
QUESTIONS
.
106
7
TRANSFER
OF
BATTERY
CELL
STATE
OF
HEALTH
FORECASTING
.
109
7.1
METHOD
.
109
7.1.1
HOW
TO
TRANSFER:
LAYERWISE
FREEZING
.
110
7.1.2
WHEN
TO
TRANSFER:
DATA
AVAILABILITY
.
111
7.1.3
BENCHMARKS
.
113
7.1.4
DATA
.
114
7.2
DESIGN
OF
EXPERIMENTS
.
114
7.3
RESULTS
.
117
7.4
SUMMARY
AND
CONTRIBUTION
TO
THE
RESEARCH
QUESTIONS
.
122
CONTENTS
XVII
8
BATTERY
SYSTEM
STATE
OF
HEALTH
FORECASTING
.
125
8.1
METHOD
.
125
8.1.1
STATE
OF
HEALTH
FORECASTING
.
126
8.1.2
STRESSOR
DATA
.
126
8.2
DESIGN
OF
EXPERIMENTS
.
129
8.2.1
HISTOGRAM-BASED
FEATURES
.
129
8.2.2
ACCESSIBLE
FEATURES
.
131
8.2.3
GENERAL
SETTINGS
.
131
8.3
RESULTS
.
134
8.3.1
HISTOGRAM-BASED
FEATURES
.
135
8.3.2
ACCESSIBLE
FEATURES
.
143
8.4
USE
CASES
.
147
8.5
SUMMARY
AND
CONTRIBUTION
TO
THE
RESEARCH
QUESTIONS
.
150
9
CONCEPT
FOR
A
TECHNICAL
IMPLEMENTATION
.
153
9.1
BATTERY
ELECTRIC
VEHICLE
FLEETS
.
154
9.2
STAKEHOLDER
ROLES
OF
FLEETS
.
154
9.3
STATE
OF
THE
ART:
FLEET
MANAGEMENT
.
155
9.4
FLEET
MANAGEMENT
CONCEPT
FOR
MANUFACTURERS
.
156
9.4.1
MACHINE
LAYER
.
158
9.4.2
FLEET
OPERATOR
LAYER
.
159
9.4.3
MANUFACTURER
LAYER
.
160
9.4.4
DATA
STORAGE
AND
MACHINE
LEARNING
MODEL
TRAINING
.
160
10
LIMITATIONS
&
OUTLOOK
.
163
10.1
METHOD
.
164
10.2
FUTURE
DATA
.
166
10.3
BATTERY
SYSTEMS
.
170
10.4
FURTHER
LEARNING
PARADIGMS
.
171
11
CONCLUSION
.
175
BIBLIOGRAPHY
.
179 |
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| author | von Bülow, Friedrich |
| author_facet | von Bülow, Friedrich |
| author_role | aut |
| author_sort | von Bülow, Friedrich |
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| building | Verbundindex |
| bvnumber | BV049674730 |
| ctrlnum | (DE-599)DNB1303217430 |
| edition | 1st edition 2024 |
| format | Book |
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| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV049674730 |
| illustrated | Not Illustrated |
| indexdate | 2024-08-28T00:03:06Z |
| institution | BVB |
| institution_GND | (DE-588)1043386068 |
| isbn | 9783658431877 3658431873 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035017671 |
| open_access_boolean | |
| owner | DE-83 |
| owner_facet | DE-83 |
| physical | Approx. 300 p. 21 cm x 14.8 cm |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer Fachmedien Wiesbaden GmbH Springer Vieweg |
| record_format | marc |
| series2 | AutoUni – Schriftenreihe |
| spelling | von Bülow, Friedrich Verfasser aut A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries Friedrich von Bülow 1st edition 2024 202312 Wiesbaden Springer Fachmedien Wiesbaden GmbH 2023 Springer Vieweg 2023 Approx. 300 p. 21 cm x 14.8 cm txt rdacontent n rdamedia nc rdacarrier AutoUni – Schriftenreihe Lithium-Ionen-Akkumulator (DE-588)7681721-0 gnd rswk-swf Structural Health Monitoring (DE-588)1088793878 gnd rswk-swf Batteriefahrzeug (DE-588)4144126-6 gnd rswk-swf Lithium-ion battery state of health battery aging transfer learning machine learning forecasting battery electric vehicles (DE-588)4113937-9 Hochschulschrift gnd-content Batteriefahrzeug (DE-588)4144126-6 s Lithium-Ionen-Akkumulator (DE-588)7681721-0 s Structural Health Monitoring (DE-588)1088793878 s DE-604 Springer Fachmedien Wiesbaden (DE-588)1043386068 pbl Erscheint auch als Online-Ausgabe 9783658431884 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=5cc20230372b44dc82a951fe3d88ab08&prov=M&dok_var=1&dok_ext=htm Inhaltstext X:MVB https://link.springer.com/978-3-658-43187-7 Auszug DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035017671&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p vlb 20230921 DE-101 https://d-nb.info/provenance/plan#vlb |
| spellingShingle | von Bülow, Friedrich A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries Lithium-Ionen-Akkumulator (DE-588)7681721-0 gnd Structural Health Monitoring (DE-588)1088793878 gnd Batteriefahrzeug (DE-588)4144126-6 gnd |
| subject_GND | (DE-588)7681721-0 (DE-588)1088793878 (DE-588)4144126-6 (DE-588)4113937-9 |
| title | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries |
| title_auth | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries |
| title_exact_search | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries |
| title_full | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries Friedrich von Bülow |
| title_fullStr | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries Friedrich von Bülow |
| title_full_unstemmed | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries Friedrich von Bülow |
| title_short | A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries |
| title_sort | a data driven fleet service state of health forecasting of lithium ion batteries |
| topic | Lithium-Ionen-Akkumulator (DE-588)7681721-0 gnd Structural Health Monitoring (DE-588)1088793878 gnd Batteriefahrzeug (DE-588)4144126-6 gnd |
| topic_facet | Lithium-Ionen-Akkumulator Structural Health Monitoring Batteriefahrzeug Hochschulschrift |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=5cc20230372b44dc82a951fe3d88ab08&prov=M&dok_var=1&dok_ext=htm https://link.springer.com/978-3-658-43187-7 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035017671&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT vonbulowfriedrich adatadrivenfleetservicestateofhealthforecastingoflithiumionbatteries AT springerfachmedienwiesbaden adatadrivenfleetservicestateofhealthforecastingoflithiumionbatteries |