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A new type battery management system for Li-ion cell packs

https://doi.org/10.1080/09720502.2017.1382151
0 signed · 9 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-662-45286-8_4openalex-snapshot
Li-Ion Battery Management System for Electric Vehicles - A Practical Guide
inferredcites →https://doi.org/10.1016/j.aej.2015.11.002openalex-snapshot
On the performance of accelerated particle swarm optimization for charging plug-in hybrid electric vehicles
inferredcites →https://doi.org/10.1080/09720502.2016.1191177openalex-snapshot
On connectedmmultiply 2 dimensions hyperplane complete residual graph
inferredcites →https://doi.org/10.1080/09720510.2016.1224470openalex-snapshot
Lie algebra solution of Lie-Markov model: Application of freshness K-value
inferredcites →https://doi.org/10.1155/4185openalex-snapshot
Journal of Applied Mathematics

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3416669openalex-extracted
Review Paper on Electric Vehicle Charging and Battery Management System
inferred← citeshttps://doi.org/10.1080/15325008.2022.2145389openalex-snapshot
A Data-Driven Comparative Analysis of Lithium-Ion Battery State of Health and Capacity Estimation
inferred← citeshttps://doi.org/10.1109/icpeca56706.2023.10075738openalex-snapshot
Forecast of State of Charge and Adaptive Voltage for Lithium-ion Batteries Using Artificial Neural Network
inferred← citeshttps://doi.org/10.1515/ijeeps-2019-0227openalex-snapshot
A cost effective accumulator management system for electric vehicles
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