Towards safer and smarter design for lithium-ion-battery-powered electric vehicles: A comprehensive review on control strategy architecture of battery management …
As the battery provides the entire propulsion power in electric vehicles (EVs), the utmost
importance should be ascribed to the battery management system (BMS) which controls all …
importance should be ascribed to the battery management system (BMS) which controls all …
Machine learning-based lithium-ion battery capacity estimation exploiting multi-channel charging profiles
Prognostics and health management is a promising methodology to cope with the risks of
failure in advance and has been implemented in many well-known applications including …
failure in advance and has been implemented in many well-known applications including …
Deep learning networks for capacity estimation for monitoring SOH of Li‐ion batteries for electric vehicles
Data‐driven modeling using measurable battery signals tends to provide robust battery
capacity estimation without delving deep into electrochemical phenomenon inside the …
capacity estimation without delving deep into electrochemical phenomenon inside the …
Batteries state of health estimation via efficient neural networks with multiple channel charging profiles
The prognostics and health management (PHM) plays the main role to handle the risk of
failure before its occurrence. Next, it has a broad spectrum of applications including utility …
failure before its occurrence. Next, it has a broad spectrum of applications including utility …
Massively distributed bayesian analysis of electric aircraft battery degradation
Electric vertical takeoff and landing (EVTOL) aircraft have high power and energy
requirements that must be understood throughout their batteries' life. Using a fast …
requirements that must be understood throughout their batteries' life. Using a fast …
AI‐Driven Digital Twin Model for Reliable Lithium‐Ion Battery Discharge Capacity Predictions
The present study proposes a novel method for predicting the discharge capabilities of
lithium‐ion (Li‐ion) batteries using a digital twin model in practice. By combining cutting …
lithium‐ion (Li‐ion) batteries using a digital twin model in practice. By combining cutting …
Universal battery performance and degradation model for electric aircraft
Development of Urban Air Mobility (UAM) concepts has been primarily focused on electric
vertical takeoff and landing aircraft (eVTOLs), small aircraft which can land and takeoff …
vertical takeoff and landing aircraft (eVTOLs), small aircraft which can land and takeoff …
[HTML][HTML] Ageing-aware battery discharge prediction with deep learning
Electrochemical batteries are ubiquitous devices in our society. When employed in mission-
critical applications, the ability to precisely predict their end-of-discharge under highly …
critical applications, the ability to precisely predict their end-of-discharge under highly …
Dynaformer: A deep learning model for ageing-aware battery discharge prediction
Electrochemical batteries are ubiquitous devices in our society. When they are employed in
mission-critical applications, the ability to precisely predict the end of discharge under highly …
mission-critical applications, the ability to precisely predict the end of discharge under highly …
A rest-time-based prognostic model for remaining useful life prediction of lithium-ion battery
This paper proposes a novel empirical model for the remaining useful life prediction of
lithium-ion battery. The proposed model is capable of modeling both the global degradation …
lithium-ion battery. The proposed model is capable of modeling both the global degradation …