相关论文: Parameter identification of lithium-ion batteries:…

Longevity and safety of lithium-ion batteries are facilitated by efficient monitoring and adjustment of the battery operating conditions. Hence, it is crucial to implement fast and accurate algorithms for State of Health (SoH) monitoring on…

The performance of battery materials is determined by their composition and the processing conditions employed during commercial-scale fabrication, where raw materials undergo complex processing steps with various additives to yield final…

Accurately predicting the state of health for sodium-ion batteries is crucial for managing battery modules, playing a vital role in ensuring operational safety. However, highly accurate models available thus far are rare due to a lack of…

Parameterisation of coupled degradation mechanisms in lithium-ion batteries is a major challenge. Interactions between the mechanisms depend on usage conditions: C-rate, rest state-of-charge (SoC), depth-of-discharge (DoD) and temperature.…

Hybrid electric vehicles (HEVs) have an over-actuated system by including two power sources, a battery pack and an internal combustion engine. This feature of HEV is exploited in this paper to simultaneously achieve accurate identification…

A data-driven solution is provided for the fast-charging problem of lithium-ion batteries with multiple safety and aging constraints. The proposed method optimizes the charging current based on the observed history of measurable battery…

Battery Life Prediction (BLP), which relies on time series data produced by battery degradation tests, is crucial for battery utilization, optimization, and production. Despite impressive advancements, this research area faces three key…

Adaptive finite element methods are a powerful tool to obtain numerical simulation results in a reasonable time. Due to complex chemical and mechanical couplings in lithium-ion batteries, numerical simulations are very helpful to…

Accurate and reliable state of charge (SoC) estimation becomes increasingly important to provide a stable and efficient environment for Lithium-ion batteries (LiBs) powered devices. Most data-driven SoC models are built for a fixed ambient…

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter…

Accurate assessment of lithium-ion battery ageing is challenged by cell-to-cell variability, heterogeneous cycling protocols, and limited transferability of data-driven models across datasets. In particular, robust identification of…

Fault diagnosis is extremely important to the safe operation of Lithium-ion batteries. To avoid severe safety issues (e.g., thermal runaway), initial faults should be timely detected and resolved. In this paper, we consider…

Accurate tracking of the internal electrochemical states of lithium-ion battery during cycling enables advanced battery management systems to operate the battery safely and maintain high performance while minimizing battery degradation. To…

Three non-equilibrium photoionisation algorithms for hydrodynamical grid-based simulation codes are compared in terms of accuracy, timestepping criteria, and parallel scaling. Explicit methods with first-order time accuracy for photon…

Advanced battery management is to lithium-ion battery systems as the brain is to the human body. Its performance rests on the use of battery models that are both fast and accurate. However, mainstream equivalent circuit models and…

Equivalent Circuit Model(ECM)has been widelyused in battery modeling and state estimation because of itssimplicity, stability and interpretability.However, ECM maygenerate large estimation errors in extreme working conditionssuch as…

Health evaluation for lithium-ion batteries (LIBs) typically relies on constant charging/discharging protocols, often neglecting scenarios involving dynamic current profiles prevalent in electric vehicles. Conventional health indicators for…

Modeling lithium-ion battery (LIB) degradation offers significant cost savings and enhances the safety and reliability of electric vehicles (EVs) and battery energy storage systems (BESS). Whilst data-driven methods have received great…

Next-generation lithium-ion batteries with silicon anodes have positive characteristics due to higher energy densities compared to state-of-the-art graphite anodes. However, the large volume expansion of silicon anodes can cause high…

Lithium-ion batteries degrade due to usage and exposure to environmental conditions, which affects their capability to store energy and supply power. Accurately predicting the capacity and power fade of lithium-ion battery cells is…