Forecasting the lifetime of Li-ion batteries is a critical challenge that limits the integration of battery electric vehicles (BEVs) into the automotive market. Cycle-life performance of Li-ion batteries is intrinsically linked to the fundamental understanding of ageing mechanisms. In contrast to most previous studies which utilise empirical trends (low real-time information) or rough simplifications on mathematical models to predict the lifetime of a Li-ion battery, we deployed a novel ageing formulation that includes heterogeneous dual-layer solid electrolyte interphase (SEI) and lithium-plating ageing mechanisms with porosity evaluation. The proposed model is parameterized and optimized for mass transport and ageing parameters based on f...
Ageing diagnosis in Lithium-ion batteries is essential to ensure their reliability and optimum perfo...
Hybrid and electric vehicles are becoming increasingly popular due to their benefits in lowering emi...
In this paper, we utilize a Doyle-Fuller-Newman (DFN) model including capacity-loss side reactions t...
Accurately predicting aging of lithium-ion batteries would help to prolong their lifespan, but remai...
Prediction of ageing for lithium-ion cell is essential. However this is a complicated area with few ...
Electric vehicles (EVs) have become the most reliable option to replace the current automotive fleet...
This paper explores how to understand and use knowledge of cell ageing in automotive conditions. The...
Lithium-ion batteries are extensively used in electric vehicles, however, their significant degradat...
Lithium-ion batteries are a key technology for current and future energy storage in mobile and stati...
Significant research efforts are being made to understand, and ultimately mitigate, thedegradation o...
Lithium ion batteries undergo complex electrochemical and mechanical degradation. This complexity is...
A hybrid vehicle battery spends around 70% of its time in storage at different temperatures compared...
Ageing prediction is often complicated due to the interdependency of ageing mechanisms. Research has...
Lithium-ion (Li-ion) batteries undergo complex electrochemical and mechanical degradation. This comp...
Lithium-ion batteries are ubiquitous in modern society. The high power and energy density of lithiu...
Ageing diagnosis in Lithium-ion batteries is essential to ensure their reliability and optimum perfo...
Hybrid and electric vehicles are becoming increasingly popular due to their benefits in lowering emi...
In this paper, we utilize a Doyle-Fuller-Newman (DFN) model including capacity-loss side reactions t...
Accurately predicting aging of lithium-ion batteries would help to prolong their lifespan, but remai...
Prediction of ageing for lithium-ion cell is essential. However this is a complicated area with few ...
Electric vehicles (EVs) have become the most reliable option to replace the current automotive fleet...
This paper explores how to understand and use knowledge of cell ageing in automotive conditions. The...
Lithium-ion batteries are extensively used in electric vehicles, however, their significant degradat...
Lithium-ion batteries are a key technology for current and future energy storage in mobile and stati...
Significant research efforts are being made to understand, and ultimately mitigate, thedegradation o...
Lithium ion batteries undergo complex electrochemical and mechanical degradation. This complexity is...
A hybrid vehicle battery spends around 70% of its time in storage at different temperatures compared...
Ageing prediction is often complicated due to the interdependency of ageing mechanisms. Research has...
Lithium-ion (Li-ion) batteries undergo complex electrochemical and mechanical degradation. This comp...
Lithium-ion batteries are ubiquitous in modern society. The high power and energy density of lithiu...
Ageing diagnosis in Lithium-ion batteries is essential to ensure their reliability and optimum perfo...
Hybrid and electric vehicles are becoming increasingly popular due to their benefits in lowering emi...
In this paper, we utilize a Doyle-Fuller-Newman (DFN) model including capacity-loss side reactions t...