☆ 4.7 Article

A novel based-performance degradation Wiener process model for real-time reliability evaluation of lithium-ion battery

JOURNAL OF ENERGY STORAGE (2022)

Related references

Note: Only part of the references are listed.

Article Thermodynamics

State of health prognostics for series battery packs: A universal deep learning method

Yunhong Che et al.

Summary: This paper proposed a strategy for generating universal health indicators and model fusion method, which can be adapted for various battery packs regardless of the types, connected cell numbers, and aging statuses. The prognostic performance is improved by model migration and fusion, extending the application area to predict the state of health for different battery packs and/or under different working conditions.

ENERGY (2022)

Add to Collection

Article Thermodynamics

Remaining useful life prediction of lithium battery based on capacity regeneration point detection

Qiuhui Ma et al.

Summary: This study combines particle filter and Mann-Whitney U test to detect the capacity regeneration point of lithium batteries, using autoregressive model and PF algorithm for RUL prediction. The method is validated through experiments, showing improved prediction accuracy and reduced error rate.

ENERGY (2021)

Add to Collection

Article Chemistry, Physical

Data driven analysis of lithium-ion battery internal resistance towards reliable state of health prediction

Mohammad A. Hoque et al.

Summary: The paper uses a public dataset to characterize battery internal resistance behavior; develops battery health prediction models for different operating conditions based on internal resistance dynamics; and demonstrates that instantaneous voltage drops due to multiple pulse discharge loads can characterize battery heterogeneity.

JOURNAL OF POWER SOURCES (2021)

Add to Collection

Article Engineering, Industrial

Remaining useful life prediction for multi-phase deteriorating process based on Wiener process

Guobo Liao et al.

Summary: The paper presents a multi-phase degradation model based on Wiener process and uses a Bayesian approach to integrate historical and real-time data for remaining useful life prediction. By estimating hyperparameters using the expectation maximization algorithm, model parameters can be effectively updated to account for multiple random change points.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Add to Collection

Article Energy & Fuels

Life-cycle assessment of the environmental impact of the batteries used in pure electric passenger cars

Xiong Shu et al.

Summary: The use of electric vehicles aims to reduce carbon emissions and environmental pollution caused by transportation. However, the production and application of electric vehicle batteries also contribute to environmental pollution. Research shows that LiFePO4 batteries are more environmentally friendly in the production phase, while Li(NiCoMn)O-2 batteries are more eco-friendly in the application and transportation phases. Despite this, LiFePO4 batteries are generally more environmentally friendly than Li(NiCoMn)O-2 batteries over their entire life cycle.

ENERGY REPORTS (2021)

Add to Collection

Review Energy & Fuels

A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries

Shunli Wang et al.

Summary: This article examines the application of deep learning algorithms in predicting the remaining useful life of lithium-ion batteries, proposing a high-accuracy deep learning algorithm to improve prediction accuracy and reduce feature testing time through analysis and comparison of different mathematical models.

ENERGY REPORTS (2021)

Add to Collection

Article Energy & Fuels

A data-driven accurate battery model to use in probabilistic analyses of power systems

Md Kamruzzaman et al.

Summary: The paper proposes a neural network-based approach to develop a battery model that captures non-linear interactions between charging/discharging power and battery state of charge. By training neural networks and combining them with mixed integer linear programming, an accurate and computationally efficient battery model is developed and successfully applied in power system reliability evaluation to determine optimal battery locations.

JOURNAL OF ENERGY STORAGE (2021)

Add to Collection

Article Energy & Fuels

A comprehensive equivalent circuit model for lithium-ion batteries, incorporating the effects of state of health, state of charge, and temperature on model parameters

Manh-Kien Tran et al.

Summary: The research found that state of health (SOH) has an impact on Thevenin ECM parameters, and it is recommended to use a new empirical model to represent this impact to improve parameter identification accuracy, with experimental validation yielding favorable results.

JOURNAL OF ENERGY STORAGE (2021)

Add to Collection

Article Chemistry, Physical

Recent advances in lithium-ion battery separators with reversible/irreversible thermal shutdown capability

Jiayi Li et al.

Summary: Advancements in separator technology for lithium-ion batteries have been developed to ensure safety, service life, and user experience. The focus is on incorporating thermal shutdown functions to prevent safety issues caused by elevated temperatures. Growing demand for recycling and sustainability has led to the development of functional separators with irreversible or reversible thermal shutdown ability for future utility and manufacture.

ENERGY STORAGE MATERIALS (2021)

Add to Collection

Article Engineering, Mechanical

Two-stage physics-based Wiener process models for online RUL prediction in field vibration data

Bingxin Yan et al.

Summary: This study proposes a two-stage physics-based Wiener process model that integrates fatigue crack mechanisms, crack growth laws, and other minor factors, achieving high accuracy in remaining useful life (RUL) prediction. By jointly employing online change point detection, parameter estimation, and RUL prediction, a general prognostic framework is formulated with good statistical inference and applicability in general nonlinear systems. The joint implementation of an offline two-step parameter estimation method and online Bayesian update method allows for high precision RUL prediction.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

Add to Collection

Article Green & Sustainable Science & Technology

Review on state-of-health of lithium-ion batteries: Characterizations, estimations and applications

Sijia Yang et al.

Summary: This paper reviews existing characteristic parameters in defining battery SOH, proposes suggestions, and discusses the impact of external factors on battery degradation. SOH monitoring goals and applications are summarized based on parameters such as capacity, impedance, and aging mechanisms.

JOURNAL OF CLEANER PRODUCTION (2021)

Add to Collection

Article Energy & Fuels

Lithium-ion battery state of health estimation using the incremental capacity and wavelet neural networks with genetic algorithm

Chun Chang et al.

Summary: This paper proposes an online method based on incremental capacity and wavelet neural networks, which can estimate the health status of the battery under current discharge. By extracting important variables from IC curves and optimizing the WNN model parameters using genetic algorithm, the SOH of the battery is successfully estimated with an error of less than 3%.

JOURNAL OF ENERGY STORAGE (2021)

Add to Collection

Review Engineering, Mechanical

A Critical Review of Online Battery Remaining Useful Lifetime Prediction Methods

Shunli Wang et al.

Summary: This article reviews methods for predicting the remaining service life of lithium-ion batteries, including machine learning, adaptive filtering, and random processes. By comparing and evaluating these methods, machine learning shows higher average accuracy and shorter prediction cycles compared to the other two methods.

FRONTIERS IN MECHANICAL ENGINEERING-SWITZERLAND (2021)

Add to Collection

Review Energy & Fuels

A review of energy storage types, applications and recent developments

S. Koohi-Fayegh et al.

JOURNAL OF ENERGY STORAGE (2020)

Add to Collection

Article Energy & Fuels

A novel safety assurance method based on the compound equivalent modeling and iterate reduce particle-adaptive Kalman filtering for the unmanned aerial vehicle lithium ion batteries

Shunli Wang et al.

ENERGY SCIENCE & ENGINEERING (2020)

Add to Collection

Article Automation & Control Systems

Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries

Kailong Liu et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)

Add to Collection

Article Energy & Fuels

Digital twin for battery systems: Cloud battery management system with online state-of-charge and state-of-health estimation

Weihan Li et al.

JOURNAL OF ENERGY STORAGE (2020)

Add to Collection

Article Green & Sustainable Science & Technology

Multiphysical modeling for life analysis of lithium-ion battery pack in electric vehicles

Quan Xia et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)

Add to Collection

Article Chemistry, Physical

A data-driven remaining capacity estimation approach for lithium-ion batteries based on charging health feature extraction

Peiyao Guo et al.

JOURNAL OF POWER SOURCES (2019)

Add to Collection

Article Chemistry, Physical

A modified reliability model for lithium-ion battery packs based on the stochastic capacity degradation and dynamic response impedance

Quan Xia et al.

JOURNAL OF POWER SOURCES (2019)

Add to Collection

Article Energy & Fuels

A novel adaptive state of charge estimation method of full life cycling lithium-ion batteries based on the multiple parameter optimization

Wen Cao et al.

ENERGY SCIENCE & ENGINEERING (2019)

Add to Collection

Article Chemistry, Physical

An adaptive working state iterative calculation method of the power battery by using the improved Kalman filtering algorithm and considering the relaxation effect

Shun-Li Wang et al.

JOURNAL OF POWER SOURCES (2019)

Add to Collection

Article Energy & Fuels

Intelligent data-driven prognostic methodologies for the real-time remaining useful life until the end-of-discharge estimation of the Lithium-Polymer batteries of unmanned aerial vehicles with uncertainty quantification

Nick Eleftheroglou et al.

APPLIED ENERGY (2019)

Add to Collection

Review Green & Sustainable Science & Technology

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

Yi Li et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)

Add to Collection

Article Engineering, Electrical & Electronic

Modified Gaussian Process Regression Models for Cyclic Capacity Prediction of Lithium-Ion Batteries

Kailong Liu et al.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2019)

Add to Collection

Article Energy & Fuels

Remaining useful life prediction for lithium-ion batteries based on a hybrid model combining the long short-term memory and Elman neural networks

Xiaoyu Li et al.

JOURNAL OF ENERGY STORAGE (2019)

Add to Collection

Review Computer Science, Information Systems

State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review

Dickson N. T. How et al.

IEEE ACCESS (2019)

Add to Collection

Article Energy & Fuels

Comparative study of reduced order equivalent circuit models for on-board state-of-available-power prediction of lithium-ion batteries in electric vehicles

Alexander Farmann et al.

APPLIED ENERGY (2018)

Add to Collection

Article Engineering, Electrical & Electronic

Real-Time Model-Based Estimation of SOC and SOH for Energy Storage Systems

Mario Cacciato et al.

IEEE TRANSACTIONS ON POWER ELECTRONICS (2017)

Add to Collection

Article Energy & Fuels

A dynamic capacity degradation model and its applications considering varying load for a large format Li-ion battery

Minggao Ouyang et al.

APPLIED ENERGY (2016)

Add to Collection

Article Computer Science, Hardware & Architecture

A Hierarchical Model for Lithium-Ion Battery Degradation Prediction

Xin Xu et al.

IEEE TRANSACTIONS ON RELIABILITY (2016)

Add to Collection

Review Chemistry, Physical

A comprehensive review of on-board State-of-Available-Power prediction techniques for lithium-ion batteries in electric vehicles

Alexander Farmann et al.

JOURNAL OF POWER SOURCES (2016)

Add to Collection

Article Computer Science, Information Systems

Reliability assessment and failure analysis of lithium iron phosphate batteries

Li Ran et al.

INFORMATION SCIENCES (2014)

Add to Collection

Article Automation & Control Systems

Estimation of Battery State of Health Using Probabilistic Neural Network

Ho-Ta Lin et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2013)

Add to Collection

Article Automation & Control Systems

State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF

Mohammad Charkhgard et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2010)

Add to Collection

© Peeref 2019-2024. All rights reserved.