Home ›
Entities
› academia
› Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries
Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries
Research article (Journal of Energy Storage, 2022) · cited 73× · AI/ML
Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries
Summary
Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries is a scholarly article[1].
Key Facts
Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries. Retrieved May 24, 2026, from https://4ort.xyz/entity/comprehensive-review-of-battery-state-estimation-strategies-using-machine-learning-for-battery-management-systems-of-air
MLA“Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/comprehensive-review-of-battery-state-estimation-strategies-using-machine-learning-for-battery-management-systems-of-air.
BibTeX@misc{4ortxyz_comprehensive-review-of-battery-state-estimation-strategies-using-machine-learning-for-battery-management-systems-of-air_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries}}, year = {2026}, url = {https://4ort.xyz/entity/comprehensive-review-of-battery-state-estimation-strategies-using-machine-learning-for-battery-management-systems-of-air}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Comprehensive review of battery state estimation strategies using machine learning for battery Management Systems of Aircraft Propulsion Batteries — https://4ort.xyz/entity/comprehensive-review-of-battery-state-estimation-strategies-using-machine-learning-for-battery-management-systems-of-air (retrieved 2026-05-24)