4.5 Article

Joint estimation of state-of-charge and state-of-health for all cells in the battery pack using leader-followerstrategy

Related references

Note: Only part of the references are listed.
Article Energy & Fuels

Hierarchical soft measurement of load current and state of charge for future smart lithium-ion batteries

Zhongbao Wei et al.

Summary: This paper proposes a hierarchical soft measurement framework for accurate estimation of SOC and load current in electric vehicles, even without using current measurements. Simulation and experimental results show that the framework can achieve high-fidelity co-estimation even in scenarios of noise corruption and current sensor malfunction.

APPLIED ENERGY (2022)

Article Energy & Fuels

Transfer learning based multi-layer extreme learning machine for probabilistic wind power forecasting

Yanli Liu et al.

Summary: This paper proposes a transfer learning-based method for probabilistic wind power forecasting. It utilizes model-based transfer learning to construct a multilayer extreme learning machine, optimizes the output mapping factors using particle swarm optimization, and updates the weights through joint distribution adaptation. The method achieves more accurate quantile forecasting results and better nonlinear fitting ability compared to other methods.

APPLIED ENERGY (2022)

Article Energy & Fuels

Low temperature preheating techniques for Lithium-ion batteries: Recent advances and future challenges

Yujie Wang et al.

Summary: This paper provides a systematic review, comparison, and discussion of low temperature preheating techniques for lithium-ion batteries. The basic principles, advantages, and disadvantages of each technique are analyzed and compared in five dimensions. The future development directions and challenges of low temperature preheating techniques for lithium-ion batteries are also discussed.

APPLIED ENERGY (2022)

Article Automation & Control Systems

Co-Estimation of State-of-Charge and State-of- Health for Lithium-Ion Batteries Using an Enhanced Electrochemical Model

Yizhao Gao et al.

Summary: This article presents a scheme using a simplified reduced-order electrochemical model and dual nonlinear filters for the reliable co-estimations of cell state-of-charge (SOC) and state-of-health (SOH). By accessing unmeasurable physical variables such as surface and bulk solid-phase concentration, the feasibility and performance of SOC estimator are revealed. Aging factors including loss of lithium ions, loss of active materials, and resistance increment are identified to improve the precision of SOC estimation for aged cells.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2022)

Article Engineering, Electrical & Electronic

Multistage State of Health Estimation of Lithium-Ion Battery With High Tolerance to Heavily Partial Charging

Zhongbao Wei et al.

Summary: This study proposes a multistage SOH estimation method that can accurately estimate the health status of LIBs even under partial charging conditions. By extracting different sets of health indicators and using artificial neural networks for fusion, the accuracy and robustness of the estimates are improved.

IEEE TRANSACTIONS ON POWER ELECTRONICS (2022)

Article Energy & Fuels

Estimation and balancing of multi-state differences between lithium-ion cells within a battery pack

Donald J. Docimo

Summary: This article develops a combined estimation and control strategy for balancing cell-to-cell differences in lithium-ion battery packs. The strategy uses a generalized approach based on a linear time-varying model to model state heterogeneity. The strategy offers benefits such as explicit expression of heterogeneity, applicability for different heterogeneity types and cell models, and reduction in computing costs.

JOURNAL OF ENERGY STORAGE (2022)

Article Automation & Control Systems

A Balancing Current Ratio Based State-of-Health Estimation Solution for Lithium-Ion Battery Pack

Xiaopeng Tang et al.

Summary: This article proposes a solution based on balancing current ratio to estimate the state-of-health (SoH) of all cells within a battery pack. By incorporating voltage-based active balancing, the proposed solution achieves lower estimation error and improved robustness.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2022)

Review Energy & Fuels

Battery management strategies: An essential review for battery state of health monitoring techniques

Sunil K. Pradhan et al.

Summary: This study provides a coherent literature review on battery health estimation techniques, offering valuable information and classification for the research community. It discusses the advantages and limitations of various techniques and their applications, as well as the potential for future research efforts.

JOURNAL OF ENERGY STORAGE (2022)

Review Energy & Fuels

A review of lithium-ion battery state of charge estimation based on deep learning: Directions for improvement and future trends

Yuefeng Liu et al.

Summary: With the rapid growth in productivity, the demand for fossil fuels has increased, leading to research and development of new energy sources. Electric vehicles powered by lithium-ion batteries have become the mainstream in the automotive industry. Battery management systems are important for ensuring the safety and reliability of electric vehicle operation. Deep neural networks have been widely used in the field of battery state estimation, and this review classifies recent estimation methods based on deep learning and discusses future directions.

JOURNAL OF ENERGY STORAGE (2022)

Article Thermodynamics

State-of-charge estimation for lithium-ion battery during constant current charging process based on model parameters updated periodically

Shuzhi Zhang et al.

Summary: This paper proposes a SOC estimation method during CC charging process by combining a global optimization algorithm and Kalman filter. By periodically updating model parameters and utilizing extended Kalman filter, the method accurately tracks battery state of charge. Experimental results demonstrate its superior accuracy compared to existing methods.

ENERGY (2022)

Article Thermodynamics

Real-time state of charge estimation for electric vehicle power batteries using optimized filter

A. Maheshwari et al.

Summary: This paper focuses on the estimation of the battery's State of Charge (SOC) in a battery management system, proposing an optimization algorithm based on EKF and SFO to improve estimation accuracy and convergence speed.

ENERGY (2022)

Article Energy & Fuels

Multiple time scale state-of-charge and capacity-based equalisation strategy for lithium-ion battery pack with passive equaliser

Fei Feng et al.

Summary: In this study, a multiple time scale SOC and capacity-based equalisation strategy for lithium-ion battery packs with passive equalisers was proposed. By establishing a minimum-capacity differential model and using a dual extended Kalman filter for SOC and capacity estimation, a SOC-and-capacity-based equalisation strategy was designed. The experimental results show that the proposed method can efficiently and accurately estimate the SOC and capacity of batteries, achieving high-efficiency energy balancing throughout the entire life cycle.

JOURNAL OF ENERGY STORAGE (2022)

Proceedings Paper Materials Science, Multidisciplinary

Numerical investigation on thermal management system for lithium ion battery using phase change material

Aditya R. Bais et al.

Summary: Lithium ion batteries were developed to overcome the inherent problems of lead acid batteries. However, these batteries exhibit a high rate of temperature increment under higher discharge rates, which can lead to degradation of battery capacity or even fire. Battery Thermal Management System (BTMS), particularly phase change cooling utilizing Phase Change Material (PCM), is used to maintain battery temperature and improve battery performance. The current study analyzed a passive BTMS using RT-42 as PCM and concluded that a minimum thickness of 4 mm is necessary for effective temperature control of the battery cell.

MATERIALS TODAY-PROCEEDINGS (2022)

Article Energy & Fuels

Compressing and reconstructing the voltage data for lithium-ion batteries using model migration and un-equidistant sampling techniques

Xiaopeng Tang et al.

Summary: The long-term storage of battery operating data is crucial for tracking and analyzing historical usage. The vast amount of raw data generated daily poses a challenge, requiring an efficient data compression method. This paper proposes a method that records the entire current trajectory while only capturing partial voltage data, achieving accurate data reconstruction through the establishment of a battery model and the use of a corrector.

ETRANSPORTATION (2022)

Review Energy & Fuels

Critical review of life cycle assessment of lithium-ion batteries for electric vehicles: A lifespan perspective

Xin Lai et al.

Summary: This study reviews the framework and methods of life cycle assessment (LCA) and evaluates the entire lifespan of lithium-ion batteries (LIBs). The results show that battery production significantly impacts the environment and resources, while battery materials recycling and remanufacturing have considerable environmental and economic values. Moreover, greening of electricity is critical to reducing carbon emissions during the battery life cycle.

ETRANSPORTATION (2022)

Article Energy & Fuels

Challenges and development of lithium-ion batteries for low temperature environments

Nan Piao et al.

Summary: In low-temperature environments, lithium-ion batteries face various challenges and limitations, which need to be addressed by increasing the inherent reactivity of the battery and improving the external reaction temperature to enhance reaction kinetics, as well as by implementing real-time temperature monitoring, optimizing charging protocols, and online lithium-plating monitoring for battery management. A systematic review of low-temperature LIBs is conducted to provide references for future research.

ETRANSPORTATION (2022)

Review Energy & Fuels

A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery

Xin Sui et al.

Summary: This paper systematically reviews the five most studied types of machine learning algorithms for battery state of health estimation, comparing their advantages and applicability. Support vector machine and artificial neural network algorithms are still research hotspots, while deep learning shows great potential in estimating battery SOH under complex aging conditions with big data. Ensemble learning provides an emerging alternative in balancing data size and accuracy.

APPLIED ENERGY (2021)

Review Green & Sustainable Science & Technology

Review of energy storage systems for vehicles based on technology, environmental impacts, and costs

Yasaman Balali et al.

Summary: As the global push to reduce fossil fuel dependency grows, the substitution of traditional internal combustion vehicles with electric and hybrid vehicles is a crucial solution to lower greenhouse gas emissions. However, challenges like reducing recharge times and manufacturing costs need to be addressed before fully replacing ICE vehicles.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

Article Computer Science, Interdisciplinary Applications

A modified batch intrinsic plasticity method for pre-training the random coefficients of extreme learning machines

Suchuan Dong et al.

Summary: The modified batch intrinsic plasticity (modBIP) method is proposed for pre-training random coefficients in ELM neural networks. It differs from the batch intrinsic plasticity (BIP) method by not involving the activation function and generating target samples on random intervals with a minimum size. The combined ELM/modBIP method outperforms ELM/BIP in terms of accuracy in numerical simulations.

JOURNAL OF COMPUTATIONAL PHYSICS (2021)

Article Thermodynamics

Capacity estimation of lithium-ion cells by combining model-based and data-driven methods based on a sequential extended Kalman filter

Xin Lai et al.

Summary: This paper proposes a novel capacity estimation method by combining model-based and data-driven methods based on SEKF to improve accuracy and reliability. Through cycle aging tests and dynamic data, it successfully estimates the state-of-charge and capacity of the batteries, while addressing a parameter mismatch problem.

ENERGY (2021)

Article Thermodynamics

A method to estimate battery SOH indicators based on vehicle operating data only

L. Vichard et al.

Summary: Batteries are complex systems that are affected by variable ambient operating conditions, and understanding their dynamic behavior and degradation laws under actual conditions is essential for durability improvement. This study proposes a method to model batteries based on experimental data from postal vehicles, which shows promising results in estimating state of health indicators linked to internal resistance and available capacity. The proposed model aims to provide accurate state of charge estimation onboard and contribute to a better understanding of battery degradation laws.

ENERGY (2021)

Article Green & Sustainable Science & Technology

Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends

Haifeng Dai et al.

Summary: This study reviews the development of battery management systems and introduces a multilayer design architecture for advanced battery management. Future trends in research and development focus on achieving better safety, performance, and interconnectivity in next-generation battery management.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

Article Energy & Fuels

Joint estimation of state of charge and state of health for lithium-ion battery based on dual adaptive extended Kalman filter

Jiabo Li et al.

Summary: This paper proposes a novel dual Kalman filter method to achieve simultaneous SOC and SOH estimation and improves the estimation accuracy of SOC and SOH from aspects such as model establishment, parameter identification, error model proposal, and algorithm improvement. The experimental results show that the proposed model can control the estimation error of SOC and SOH within 1%.

INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2021)

Article Energy & Fuels

A novel method for state of energy estimation of lithium-ion batteries using particle filter and extended Kalman filter

Xin Lai et al.

Summary: A novel SOE estimation method using PF and EKF algorithms is proposed in this study, which is able to improve accuracy and robustness by identifying battery model parameters at different temperatures. Experimental results show that the maximum error of the proposed algorithm is less than 3% under dynamic conditions and can quickly converge to its reference trajectory even with large initial errors in SOE and total available energy.

JOURNAL OF ENERGY STORAGE (2021)

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)

Article Chemistry, Physical

State of health estimation of lithium-ion battery based on an adaptive tunable hybrid radial basis function network

Mingqiang Lin et al.

Summary: This study proposes a novel adaptive hybrid radial basis function network for accurate and robust estimation of the state of health of lithium-ion batteries. The model extracts dynamic and static characteristics, builds a hybrid network state-space model to simulate aging mechanism, and utilizes Brownian motion modeling and particle filter for adaptive parameter modulation. The experimental results demonstrate high prediction accuracy and reliability of the proposed model under various conditions.

JOURNAL OF POWER SOURCES (2021)

Article Multidisciplinary Sciences

Reconstruction of the incremental capacity trajectories from current-varying profiles for lithium-ion batteries

Xiaopeng Tang et al.

Summary: A model-free fitting process is introduced to reconstruct IC analysis trajectories in noisy or current-varying profiles, resulting in peak position errors within 0.25%. Health indicators extracted from the reconstructed IC trajectories can determine battery health status with less than 1% estimation error. Enabling IC-based methods under complex load profiles enhances health assessment and promotes more sustainable society.

ISCIENCE (2021)

Article Energy & Fuels

Cycle life prediction of lithium-ion batteries based on data-driven methods

Laisuo Su et al.

Summary: This study demonstrates the capability of machine learning techniques to accurately predict the cycle life of lithium-ion batteries by capturing hidden features in complex, nonlinear systems.

ETRANSPORTATION (2021)

Article Energy & Fuels

Quantifiability of inherent cell-to-cell variations of commercial lithium-ion batteries

Leo Wildfeuer et al.

Summary: Parameter variations of lithium-ion batteries can reduce battery pack performance, with impedance changes potentially linked to imperfect measurement setup. Experimental findings suggest that parameter variations are greatly influenced by temporal and spatial temperature inhomogeneities, and compensating for these effects can significantly reduce resistance variation.

ETRANSPORTATION (2021)

Article Computer Science, Artificial Intelligence

Recovering large-scale battery aging dataset with machine

Xiaopeng Tang et al.

Summary: By combining industrial data with accelerated aging tests, high-quality battery aging datasets can be recovered to improve the assessment of battery aging with up to 90% experimental time saved.

PATTERNS (2021)

Review Energy & Fuels

Battery thermal management system based on the forced-air convection: A review

Peng Qin et al.

Summary: This paper reviews the developments on the application of forced-air convection into BTMS and summarizes the main optimization routes which include pure forced-air convection, combination with phase change material and heat pipe, and outlooks for future development.

ETRANSPORTATION (2021)

Article Energy & Fuels

A study of cell-to-cell variation of capacity in parallel-connected lithium-ion battery cells

Ziyou Song et al.

Summary: This study investigates the capacity variation among battery cells and demonstrates that the capacity variation decreases over time for cells with similar temperatures, providing a self-balancing mechanism. Additionally, it is found that battery strings with initial cell-to-cell capacity variation degrade slightly faster compared to those with uniform cell capacities.

ETRANSPORTATION (2021)

Review Energy & Fuels

A review of modeling, acquisition, and application of lithium-ion battery impedance for onboard battery management

Xueyuan Wang et al.

Summary: Impedance is closely related to the internal physical and chemical processes of lithium-ion batteries, providing detailed information. This paper reviews over 170 papers and discusses the possibility and value of impedance in onboard battery management, as well as the challenges faced. More significant work is needed to realize a more smart battery management system.

ETRANSPORTATION (2021)

Article Energy & Fuels

The prismatic surface cell cooling coefficient: A novel cell design optimisation tool & thermal parameterization method for a 3D discretised electro-thermal equivalent-circuit model

Xiao Hua et al.

Summary: The study introduces the application of CCC to prismatic lithium iron phosphate cells and develops a three-dimensional electro-thermal equivalent circuit model for optimizing cell and pack design.

ETRANSPORTATION (2021)

Article Engineering, Multidisciplinary

State of charge estimation for lithium-ion batteries based on adaptive dual Kalman filter

Yidan Xu et al.

APPLIED MATHEMATICAL MODELLING (2020)

Article Engineering, Electrical & Electronic

Run-to-Run Control for Active Balancing of Lithium Iron Phosphate Battery Packs

Xiaopeng Tang et al.

IEEE TRANSACTIONS ON POWER ELECTRONICS (2020)

Article Engineering, Electrical & Electronic

Model Migration Neural Network for Predicting Battery Aging Trajectories

Xiaopeng Tang et al.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2020)

Article Green & Sustainable Science & Technology

Combined internal resistance and state-of-charge estimation of lithium-ion battery based on extended state observer

Li Sun et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)

Review Green & Sustainable Science & Technology

A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems

Yujie Wang et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)

Article Energy & Fuels

Advanced diagnostics to evaluate heterogeneity in lithium-ion battery modules

Tanvir R. Tanim et al.

ETRANSPORTATION (2020)

Article Engineering, Electrical & Electronic

Estimation of Cell SOC Evolution and System Performance in Module-Based Battery Charge Equalization Systems

Weiji Han et al.

IEEE TRANSACTIONS ON SMART GRID (2019)

Article Thermodynamics

A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging

Xiaopeng Tang et al.

ENERGY CONVERSION AND MANAGEMENT (2019)

Article Engineering, Electrical & Electronic

Error Analysis of the Model-Based State-of-Charge Observer for Lithium-Ion Batteries

Ping Shen et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)

Article Engineering, Electrical & Electronic

The Co-estimation of State of Charge, State of Health, and State of Function for Lithium-Ion Batteries in Electric Vehicles

Ping Shen et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)

Article Chemistry, Physical

A fast estimation algorithm for lithium-ion battery state of health

Xiaopeng Tang et al.

JOURNAL OF POWER SOURCES (2018)

Article Engineering, Electrical & Electronic

Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus

Xiaosong Hu et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)

Article Engineering, Electrical & Electronic

Improved Battery SOC Estimation Accuracy Using a Modified UKF With an Adaptive Cell Model Under Real EV Operating Conditions

Menatalla Shehab El Din et al.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2018)

Article Engineering, Electrical & Electronic

State of Charge and State of Health Estimation for Lithium Batteries Using Recurrent Neural Networks

Hicham Chaoui et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2017)

Review Chemistry, Physical

A review on the key issues for lithium-ion battery management in electric vehicles

Languang Lu et al.

JOURNAL OF POWER SOURCES (2013)

Article Chemistry, Physical

Advanced mathematical methods of SOC and SOH estimation for lithium-ion batteries

Dave Andre et al.

JOURNAL OF POWER SOURCES (2013)

Article Computer Science, Artificial Intelligence

A new neural network for solving nonlinear convex programs with linear constraints

Yongqing Yang et al.

NEUROCOMPUTING (2011)

Article Computer Science, Artificial Intelligence

Error Minimized Extreme Learning Machine With Growth of Hidden Nodes and Incremental Learning

Guorui Feng et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2009)