Daniel-Ioan Stroe
Automotive Engineering · 2014–2021
A researcher in the Science corpus: 7 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Automotive Engineering — 122 citations into it
- Electrical and Electronic Engineering — 119 citations into it
Whom Daniel-Ioan Stroe trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Daniel-Ioan Stroe's perspective
Ordered by how strongly the researchers Daniel-Ioan Stroe trusts endorse each paper. Same corpus, a different order for every researcher.
- A review on the key issues for lithium-ion battery management in electric vehicles
- A comparative study of equivalent circuit models for Li-ion batteries
- The State of Charge Estimation of Lithium-Ion Batteries Based on a Proportional-Integral Observer (IEEE Transactions on Vehicular Technology)
- Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles
- State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF (IEEE transactions on industrial electronics (1982. Print))
- An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks
- Performance analysis and SOH (state of health) evaluation of lithium polymer batteries through electrochemical impedance spectroscopy
- Lithium batteries: Status, prospects and future
- A systematic review of lumped-parameter equivalent circuit models for real-time estimation of lithium-ion battery states
- An overview of generic battery models (IEEE Power & Energy Society General Meeting)
Their papers
- An Overview and Comparison of Online Implementable SOC Estimation Methods for Lithium-Ion Battery (2018) — 335 citations
- Battery second life: Hype, hope or reality? A critical review of the state of the art (2018) — 367 citations
- Overview of Lithium-Ion battery modeling methods for state-of-charge estimation in electrical vehicles (2018) — 330 citations
- A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery (2021) — 355 citations
- Battery state-of-health modelling by multiple linear regression (2021) — 88 citations
- Lithium-Ion Battery Operation, Degradation, and Aging Mechanism in Electric Vehicles: An Overview (2021) — 139 citations
- Lithium ion battery chemistries from renewable energy storage to automotive and back-up power applications — An overview (2014) — 155 citations