Lithium-ion Battery Energy Storage System Research Articles

An Open-Source Energy Arbitrage Model Involving Price Bands for Risk Hedging with Imperfect Price Signals

The increased uptake of variable renewable energy sources has increased electricity price volatility in many energy pool markets, providing an opportunity for storage systems to profit through energy arbitrage. Comparison between the cost or value of storage systems engaging in energy arbitrage should be performed on a levelised basis due to differences in system lifetime. Existing energy arbitrage models with bid/offer curves and imperfect forecasting are typically computationally expensive and are impractical for calculating lifetime levelised cost metrics. In this work, an open-source modular energy arbitrage model with bid and offer curve inputs was developed for a lithium-ion battery energy storage system (BESS) and pumped hydro system (PHS) to analyse lifetime levelised cost and revenue. The mixed integer linear program scheduling module included a new piece-wise linearised description of PHS charging behaviour for rapid optimisation. A one-at-a-time sensitivity analysis indicated that levelised cost and revenue were highly sensitive to discharging efficiency. In a case study based on Australia’s National Electricity Market, imperfect forecasting with no risk hedging was found to increase levelised costs by up to 24% and decrease levelised revenue by up to 50% relative to perfect price forecasting, despite 95% of prices being forecast to be within $35/MWh of the actual trading price. BESS levelised costs were more significantly correlated with consistent low risk bids (Kendall Tau-b of 0.75), since the undiscounted capital costs contribute to a larger proportion of the overall costs than in the PHS systems.

Grid-connected lithium-ion battery energy storage system towards sustainable energy: A patent landscape analysis and technology updates

Presently, as the world advances rapidly towards achieving net-zero emissions, lithium-ion battery (LIB) energy storage systems (ESS) have emerged as a critical component in the transition away from fossil fuel-based energy generation, offering immense potential in achieving a sustainable environment. This study conducts an in-depth analysis of grid-connected LIB ESS patents published from 1998 to 2022, aiming to comprehend essential developments and trends in the technology landscape while identifying key players and inventors. Employing extensive keyword searches within the Lens database, 95 patent documents were extracted along with the bibliometric data. The research highlights two prominent factors in the field of grid-connected LIB ESS patents. Firstly, a detailed patent bibliometric analysis including patent growth trends, keyword analysis, patent distribution over jurisdiction, and subject categories was presented. Moreover, the research identifies key owners, inventors and hierarchical jurisdiction in patent document publishing and evaluates the possibilities for future research sustainability. Secondly, detailed updates regarding technological advancements that are driving sustainable grid-connected LIB ESS development in various sectors such as; gird connected ESS, power conversion system (PCS), energy management system (EMS) and transportation sector are provided. The study concluded that the patents related to grid-connected ESS, minimizing voltage and frequency regulation to achieve grid stability and EMS of LIB are the key trending topics in the field of grid-connected LIB ESS. The comprehensive analysis not only illuminates crucial trends but also provides valuable guidance to future researchers and industry stakeholders, facilitating the path towards sustainable grid-connected LIB ESS and paving the way for a more environmentally conscious energy landscape.

Techno-economic assessment of small-size residential solar PV + battery systems under different tariff structures in Brazil

This paper proposes a methodology to assess the energy and economic impact of adopting small-scale residential photovoltaic (PV) systems paired with lithium-ion battery energy storage (BESS) systems in single-family homes, under the current energy feed-in legislation. The suggested methodology was applied to a case study of a prosumer unit (PU) in Brazil. Data from energy bills, measured PV generation, BESS behaviour, and energy consumption were analysed to compare different viewpoints and estimate key economic indicators. As a result, the PV + BESS combination increases residential users' energy self-consumption and self-sufficiency, resulting in respective increases of 15 % and 2 %. Under the conventional tariff, adopting the PV + BESS system led to an average 29 % reduction in electricity costs compared to scenarios without PV + BESS. Furthermore, by transitioning to the white tariff mode in conjunction with PV + BESS, the PU achieved a 49 % reduction. This result emphasizes the advantages of time-of-use adoption for PV + BESS consumers. A greater discrepancy between tariff periods enhances the feasibility of storing off-peak energy for use during peak periods. Currently, BESS implementation costs impede competitiveness, with attractive LCOS metrics achieved only at costs below $600.00/kWh and MRAs below 9 %. BESS + PV lowers generation costs compared to off-peak rates, increasing the viability of shared usage. Integrating PV + BESS systems with rate switching significantly diminishes electricity expenses. The substantial BESS implementation cost necessitates a noteworthy rate differential for viability, which could potentially impact non-PV and non-BESS consumers.

Alternative Energy Options for a Thai Durian Farm: Feasibility Study and Experiments for the Combination of Solar Photovoltaics and Repurposed Lithium-Ion Batteries

This research examines the viability of incorporating a second-life lithium-ion battery energy storage system with a solar photovoltaic power source to facilitate energy acquisition in two irrigation scenarios at a durian farm located in Thailand. The first option entails selecting the battery with suitable dimensions to effectively harness solar energy following morning irrigation, while the second option involves sizing the battery specifically for storing solar energy solely for the purpose of powering the motor pump. This study conducts an analysis on the degradation of the battery, focusing on the influence of specific environmental conditions and its specification. The degradation analysis employs polynomial functions as an alternative to exponential semi-empirical stress models for fitting stress models. This approach demonstrates a robust fit, as evidenced by a high R-squared value of approximately 1. The economic analysis considers various factors, including solar irradiance derating factors, battery deterioration rate, and photovoltaic power ratings for all scenarios. The sensitivity analysis evaluates the variations in irradiance and costs associated with the battery. When solar radiation levels surpass 500 W/m2 and the cost of the battery remains below $100/kWh, the estimated payback period is approximately 5 years over the duration of the 10-year project lifespan.

A fast-response preheating system coupled with supercapacitor and electric conductive phase change materials for lithium-ion battery energy storage system at low temperatures

The electrochemical performance of lithium batteries deteriorates seriously at low temperatures, resulting in a slower response speed of the energy storage system (ESS). In the ESS, supercapacitor (SC) can operate at −40 °C and reserve time for battery preheating. However, the current battery preheating strategy has a slow heating rate and cannot preheat batteries to a comfortable temperature range during the time reserved by SC. This study proposes a preheating system that combines the instantaneous high-power discharge of SC with the efficient electro-to-thermal conversion of ECPCM, which has a super-fast preheating rate and contributes to the fast response of ESS at low temperatures. Under extreme conditions of −40 °C, the preheating system can recover >85 % discharge capacity and voltage of the battery system in 2 min. By adjusting SC capacitance and ECPCM resistance, the preheating rate of the battery system can reach 69.5 °C/min, and the temperature difference is less than 5 °C. Moreover, the pulse current of SC can reduce the temperature difference inside the battery within 5 °C. The preheating system can also enable the battery system quickly enter super-charging mode, greatly reducing the charging time. The total charging time was reduced by 72 % when the battery pack was preheated to 20 °C. Nevertheless, based on the outcome of this study, this preheating strategy can effectively improve the low-temperature response speed of the ESS and meet the requirements of the microgrid.

Research on frequency modulation capacity configuration and control strategy of multiple energy storage auxiliary thermal power unit

The rapid development of new energy sources has had an enormous impact on the existing power grid structure to support the “dual carbon” goal and the construction of a new type of power system, make thermal power units better cope with the impact on the original grid structure under the background of the rapid development of new energy sources, promote the consumption of new energy sources such as solar and wind energy, and further expand the channels for upgrading and flexibility transformation of thermal power energy storage, improve the stability, safety and economy of thermal power unit operation. Therefore, based on the research status at home and abroad, a hybrid energy storage system is added to solve the above problems. The lithium battery-flywheel control strategy and the regional dynamic primary frequency modulation model of thermal power units are proposed, and study the capacity configuration scheme of flywheel‑lithium battery hybrid energy storage system under a certain energy storage capacity, the frequency modulation performance is evaluated by the system frequency fluctuation degree, fluctuation peak range and other indicators. Study under a certain energy storage capacity thermal power unit coupling hybrid energy storage system to participate in a frequency modulation of the optimal capacity configuration scheme, and perform simulation verification using MATLAB/Simulink. When the thermal power unit is coupled with a 10.8612 MW/2.7151 MWh flywheel energy storage system and a 4.1378 MW/16.5491 MWh lithium battery energy storage system, while adaptive variable coefficient droop control is adopted, the system frequency range is 0.00328 p.u.Hz, and the fluctuation degree of the output power of the thermal power units is 0.00498 p.u.MW, compared to the individual frequency regulation of thermal power units, it reduces 52.07 % and. The results show that when the thermal power unit is disturbed by external load, hybrid energy storage assisted thermal power unit frequency modulation reduces the mechanical loss of thermal power unit to a certain extent and extends the service life of the unit, effectively improve the operation stability and economy of thermal power units, further reduce the phenomenon of abandoning wind and light, and better promote the utilization of new energy.

Fire Accident Risk Analysis of Lithium Battery Energy Storage Systems during Maritime Transportation

The lithium battery energy storage system (LBESS) has been rapidly developed and applied in engineering in recent years. Maritime transportation has the advantages of large volume, low cost, and less energy consumption, which is the main transportation mode for importing and exporting LBESS; nevertheless, a fire accident is the leading accident type in the transportation process of LBESS. This paper applied fault tree analysis and Bayesian network methods to evaluate the fire accident risk of LBESS in the process of maritime transportation. The Bayesian network was constructed via GeNIe 2.3 software, and the probability of LBESS fire accidents during maritime transportation was calculated based on the probability of basic events occurring. The results showed that an unsuitable firefighting system for putting out lithium battery fires, high humidity, and monitoring equipment without a real-time alarm function have the most significant influence on the occurrence of LBESS fire accidents during maritime transportation. The research work of this paper provides a theoretical basis for the risk assessment of LBESS during maritime transportation.

State of health estimation of lithium-ion battery considering sensor uncertainty

The state of health (SOH) is closely related to the stable operation of lithium-ion (Li-ion) battery energy storage systems. Existing methods for SOH estimation assume a reliable multi-source sensor in the battery management system, yet the sensors are prone to failures leading to abnormal measurement data in practical applications. To alleviate the above issue, this paper proposes a detection before fusion multi-model framework (DFMF) considering the uncertainties of multi-source sensor data. Firstly, a density-based spatial clustering of applications with noise is adopted to identify the working states of sensors via detecting the faults from their raw data. Then, the working states of sensors are fed to a state machine to realize the fault isolation. Finally, a data-driven SOH estimation based on multi-source sensors is developed, which includes both the single-sensor mode and the multi-sensor joint mode. The proposed DFMF is validated on two degradation datasets from different aging conditions and chemistries. The experimental results demonstrate the proposed DFMF has a high accuracy and strong robustness in Li-ion SOH estimation. It is noted that the DFMF can provide SOH estimation results with the root mean squared error within 1.68 % and 1.17 % on the two datasets, respectively.

Research on Safety Operation and Maintenance Management and Health Status Assessment for Lithium Battery Energy Storage System

The safe operation and maintenance of lithium batteries not only needs to monitor the working status of lithium batteries timely and accurately, but also needs to evaluate its health status and automatically switch the backup battery when safety hazards are found. However, research on the safe operation and maintenance of lithium batteries is still lacking. In light of this, this paper constructs a safe operation and maintenance mechanism by monitoring the voltage and surface temperature of the lithium battery. In addition, a novel online health assessment model based on GRU-CNN is proposed to find out the potential safety hazards of lithium batteries timely. The working voltage, current and ambient temperature are used as the input features of the model to predict the degradation of lithium batteries in advance. In addition, a security operation and maintenance controller is designed to quickly switch the backup battery pack when a lithium battery pack appears to have performance degradation or security risks. The system realizes the real-time monitoring of the safe operation of lithium batteries and the rapid assessment of health status, providing technical guarantees for the reliable, stable, and safe operation of the lithium battery system. The experimental comparison verified that the proposed assessment model of the status of health (SOH for short) has less prediction error.

Operational risk analysis of a containerized lithium-ion battery energy storage system based on STPA and fuzzy evaluation

Lithium-ion battery energy storage system (BESS) has rapidly developed and widely applied due to its high energy density and high flexibility. However, the frequent occurrence of fire and explosion accidents has raised significant concerns about the safety of these systems. To evaluate the safety of such systems scientifically and comprehensively, this work focuses on a MW-level containerized lithium-ion BESS with the system-theoretic process analysis (STPA) method. The work identified 53 unsafe control actions and corresponding loss scenarios. By combining loss scenarios and expert evaluation opinions, the key risk factors for system operation are obtained. Finally, this work proposed corresponding countermeasures and suggestions to address the key risk factors and improve the safety and reliability of the entire system operation. This work discusses the operational risks of MW-class containerized lithium-ion BESS and provides technical guidance for engineers in system designs, safe operations, and engineering applications.

An analysis of li-ion induced potential incidents in battery electrical energy storage system by use of computational fluid dynamics modeling and simulations: The Beijing April 2021 case study

To further grasp the failure process and explosion hazard of battery thermal runaway gas, numerical modeling and investigation were carried out based on a severe battery fire and explosion accident in a lithium-ion battery energy storage system (LIBESS) in China. The composition and transport law of gas caused by large-scale LIB failure were theoretically analyzed, and the explosion risk of thermal runaway gas mixture in complex space after accidental ignition were systematically discussed by the computational fluid dynamics (CFD) technology. After the investigation, the underground cable trench is the key channel that causes the thermal runaway gas of lithium iron phosphate batteries to be transported to the building 20 m away and induces the explosion. After about 8500 s of battery burning, the average concentration of the thermal runaway mixed gas diffused from the cable trench is 16.4%. The arrangement of obstacles in the accident building is the main factor determining the explosion overpressure of thermal runaway gas, and the overpressure generated at the end of the obstacle path exceeds 70 kPa. Multiple windows in the battery room play an effective explosion-venting effect, but increase the damage range of outdoor high-temperature flame. In addition, the System-Theoretical Accident Model and Processes (STAMP) was used to analyze the causes of the accident, and the safety constraints that should be imposed by the three control levels of the government, functional departments and energy storage power stations were introduced to prevent battery failure and fire accidents in the BESS. The research method and analysis results will provide important ideas and reference for the investigation of fire and explosion accidents in BESS.

Research on application technology of lithium battery assessment technology in energy storage system

Due to the complexity of the state change mechanism of lithium batteries, there are problems such as difficulties in aging characterization. Establishing a state assessment model for lithium batteries can reduce its safety risk in energy storage power station applications. Therefore, this paper proposes a method for establishing a lithium battery model including aging resistance under the combination of digital and analog, and uses the time–frequency domain test analysis method to establish the aging impedance expression to realize the parameterization of the aging process and state estimation of lithium batteries. A battery model that can characterize the battery aging process is established by combining digital and simulation methods, and the equivalent representation of the lithium battery aging process is realized. Finally, a simulation example is designed to verify its effectiveness, which provides important reference value for the practical engineering application of lithium battery energy storage system.

Hybrid lithium-ion battery and hydrogen energy storage systems for a wind-supplied microgrid

Microgrids with high shares of variable renewable energy resources, such as wind, experience intermittent and variable electricity generation that causes supply–demand mismatches over multiple timescales. Lithium-ion batteries (LIBs) and hydrogen (H2) are promising technologies for short- and long-duration energy storage, respectively. A hybrid LIB-H2 energy storage system could thus offer a more cost-effective and reliable solution to balancing demand in renewable microgrids. Recent literature has modeled these hybrid storage systems; however, it remains unknown how anticipated, but uncertain, cost reductions and performance improvements will impact overall system cost and composition in the long term. Here, we developed a mixed integer linear programming (MILP) model for sizing the components (wind turbine, electrolyser, fuel cell, hydrogen storage, and lithium-ion battery) of a 100% wind-supplied microgrid in Canada. Compared to using just LIB or H2 alone for energy storage, the hybrid storage system was found to provide significant cost reductions. A sensitivity analysis showed that components of the H2 subsystem meaningfully impact the total microgrid cost, while the impact of the LIB subsystem is dominated by its energy storage capacity costs. Regarding efficiency, decreased electrolyzer efficiency causes the greatest increase in total system cost, whereas increased fuel cell efficiency has the greatest potential to reduce total system cost. As technologies evolve, the H2 subsystem assumes a greater role (i.e., it is larger and receives/supplies more energy over more hours) compared to the LIB subsystem, but LIB continues to provide frequent intra-day balancing in the microgrid.

Performance Assessment of a Grid-Connected Two-Stage Bidirectional Converter for a Combined PV–Battery Energy Storage System

This paper presents a comprehensive performance assessment of a two-stage power electronic (PE) converter for interfacing the grid of a lithium-ion battery energy storage system (Li-BESS) for building-integrated PV (BIPV) applications. A performance assessment of the control system was conducted for the two-stage PE interface with a common DC-link, which consisted of a bi-directional boost converter with a cascaded PI controller and an AC/DC converter with proportional-integral (PI) and proportional-resonant (PR) controllers. The assessment covered loss analysis and useful lifetime estimation for the 10 kW PE interface with a wide-bandgap SiC power MOSFET at different loads for both the charging and discharging modes of a 50 kWh lithium-ion battery system. Additionally, a performance comparison of various switching frequencies was performed. It was observed that the system was stable up to a switching frequency of 30 kHz, and that increasing the switching frequency improved the responsiveness of the converter by decreasing the settling time; however, there were diminishing returns at higher switching frequencies. To obtain a proper balance between responsiveness and lower loss, a switching frequency of 10 kHz was selected.

Energy Management Strategy Considering Energy Storage System Degradation for Hydrogen Fuel Cell Ship

Abstract A hybrid energy system (HES) including hydrogen fuel cell systems (FCS) and a lithium-ion (Li-ion) battery energy storage system (ESS) is established for hydrogen fuel cell ships to follow fast load transients. An energy management strategy (EMS) with hierarchical control is presented to achieve proper distribution of load power and enhance system stability. In the high-control loop, a power distribution mechanism based on a particle swarm optimization algorithm (PSO) with an equivalent consumption minimization strategy (ECMS) is proposed. In the low-level control loop, an adaptive fuzzy PID controller is developed, which can quickly restore the system to a stable state by adjusting the PID parameters in real time. Compared with the rule-based EMS, hydrogen consumption is reduced by 5.319%, and the stability of the power system is significantly improved. In addition, the ESS degradation model is developed to assess its state of health (SOH). The ESS capacity loss is reduced by 2% and the daily operating cost of the ship is reduced by 1.7% compared with the PSO-ECMS without considering the ESS degradation.

State of Charge and State of Health Estimation of Lithium-Ion Battery Packs With Inconsistent Internal Parameters Using Dual Extended Kalman Filter

Abstract The internal battery parameters of the lithium-ion battery energy storage system may be inconsistent due to different aging degrees during the operation, and the thermal effect can also threaten the safety of the system. In this paper, based on the second-order resistor–capacitor equivalent circuit model and the dual extended Kalman filter (DEKF) algorithm, an electrical simulation model of a LIB pack with inconsistent parameters considering the thermal effect is established, in which state of charge (SOC) and state of health (SOH) are estimated using DEKF, while the temperature is calculated by a thermal module. The simulation results show that the DEKF algorithm has a good effect on battery state and parameter estimation, with the root-mean-square error of voltage is lower than 0.01 V and SOC mean absolute error (MAE) is below 1.50%, while SOH error is 3.37%. In addition, the thermal module can provide an accurate estimation of the inconsistent temperature rise of the battery pack, and the MAE between the model-calculated temperature and the experiment is no more than 6.60%. The results provide the basic data for the scale-up of the electrothermal co-simulation model of the LIB energy storage system.

Research on the adaptability of proton exchange membrane electrolysis in green hydrogen–electric coupling system under multi-operating conditions

The green hydrogen–electric coupling system can consume locally generated renewable energy, thereby improving energy utilization and enabling zero-carbon power supply within a certain range. This study focuses on a green hydrogen–electric coupling system that integrates photovoltaic, energy storage, and proton exchange membrane electrolysis (PEME). Firstly, the impact of operating temperature, power quality, and grid auxiliary services on the characteristics of the electrolysis cell is analyzed, and a voltage model and energy model for the cell are established. Secondly, a multi-operating conditions adaptability experiment for PEME grid-connected operation is designed. A test platform consisting of a grid simulator, simulated photovoltaic power generation system, lithium battery energy storage system, PEME, and measurement and acquisition device is then built. Finally, experiments are conducted to simulate multi-operating conditions such as temperature changes, voltage fluctuations, frequency offsets, harmonic pollution, and current adjustment speed. The energy efficiency and consumption is calculated based on the recorded data, and the results are helpful to guide the operation of the system.

Ageing and energy performance analysis of a utility-scale lithium-ion battery for power grid applications through a data-driven empirical modelling approach

Energy storage systems are becoming one of the most relevant technologies to effectively support renewable energy source (RES) deployment at large. The present work proposes a detailed ageing and energy analysis based on a data-driven empirical approach of a real utility-scale grid-connected lithium-ion battery energy storage system (LIBESS) for providing power grid services. The system under investigation is an operative utility-scale LIBESS integrated with a multi-MW PV plant and connected to the medium voltage network, located in Southern-Italy. The ageing and energy analysis has been performed using data measured by the supervisory control and data acquisition (SCADA) system directly connected with the LIBESS. This large amount of data is collected in a cloud database and then elaborated using proper software tools. This experimental campaign applied on a commercial LIBESS covers the impact of degradation mechanisms, such as cycle and calendar ageing, the battery and global system efficiency as well as the role of auxiliaries' power consumption under normal and power grid services operations. Thanks to the low complexity of the proposed data-driven model, it could be easily replicated in any other LIBESS facility, both operative in real-world framework and in laboratory context. The state-of-health (SOH) estimated by the degradation model implemented in this work after 3 years of operations and after 356 full-cycles equivalents is equal to 95.88 %, with an average capacity loss compared to the nominal capacity of about 1.37 % per year. Energy analysis revealed an average system global efficiency of 85 % for operations close to the nominal power that decreases to 65 % for operations at low power rates. While considering the grid network services operations, the power grid applications investigated are primary frequency regulation, secondary voltage regulation and PV unbalances reduction. Our results show that primary frequency regulation is the most efficient service in terms of ageing and energy performances. It has been evaluated a capacity loss of 0.03 kWh per each full-cycle equivalent performed during primary frequency regulation. Differently, secondary voltage regulation and PV unbalances reduction present a capacity loss of 0.1 kWh and of 0.05 kWh per each full-cycle equivalent, respectively. At the same time, the global efficiency of primary regulation (around 83 %) is remarkably higher compared to secondary voltage regulation (about 47 %) and to PV unbalances reduction (about 55 %). Results support the relevance to identify the most impacting key performance indicators for effective exploitation of LIBESS in power system and network services applications.

Degradation-Conscious Multiobjective Optimal Control of Reconfigurable Li-Ion Battery Energy Storage Systems

Lithium-ion battery energy storage systems are made from sets of battery packs that are connected in series and parallel combinations depending on the application’s needs for power. To achieve optimal control, advanced battery management systems (ABMSs) with health-conscious optimal control are required for highly dynamic applications where safe operation, extended battery life, and maximum performance are critical requirements. The majority of earlier research assumed that the battery cells in these energy storage systems were identical and would vary uniformly over time in terms of cell characteristics. However, in real-world situations, the battery cells might behave differently for a number of reasons. Overcharging and over-discharging are caused by an electrical imbalance that results from the cells’ differences in properties and capacity. Therefore in this study, a stratified real-time control scheme was developed for the dual purposes of minimizing the capacity fade and the energy losses of a battery pack. Each of the cells in the pack is represented by a degradation-conscious physics-based reduced-order equivalent circuit model. In view of the inconsistencies between cells, the proposed control scheme uses a state estimator such that the parametric values of the circuit elements in the cell model are determined and updated in a decentralized manner. The minimization of the capacity fade and energy losses is then formulated as a multiobjective optimization problem, from which the resulting optimal control strategy is realized through the switching actions of a modular multilevel series-parallel converter which interconnects the battery pack to an external AC system. A centralized controller ensures optimal switching sequence of the converter leading to the maximum utilization of the capacity of the battery pack. Both simulation and experimental results are used to verify the proposed methodologies which aim at minimizing the battery degradation by reconfiguring the battery cells dynamically in accordance with the state of health (SOH) of the pack.

An Adaptive Cutoff Frequency Design for Butterworth Low-Pass Filter Pursuing Robust Parameter Identification for Battery Energy Storage Systems

Energy storage systems are key to propelling the current renewable energy revolution. Accurate State-of-Charge estimation of the lithium-ion battery energy storage systems is a critical task to ensure their reliable operations. Multiple advanced battery model-based SOC estimation algorithms have been developed to pursue this objective. Nevertheless, these battery model-based algorithms are sensitive to measurement noises since the measurement noises affect the accuracy of battery model identification, thus leading to inaccurate battery SOC estimation consequently due to modeling error. The Butterworth low-pass filter has proven effectiveness in measurement noise filtering for accurate parameter identification, while the cutoff frequency design relies on prior knowledge of lithium-ion batteries, making its capability limited to general cases. To overcome this issue, this paper proposes an adaptive cutoff frequency design algorithm for the Butterworth low-pass filter. Simulation results show that the low-pass filter functions properly in the presence of multiple scales of measurement noises adopting the proposed work. Consequently, the parameters of the battery model and the SOC of the battery are both identified and estimated accurately, respectively. In detail, the parameters: R0, R1, C1, and the time constant τ are all identified accurately with low relative identification errors of 0.028%, 11.12%, 6.21%, and 5.94%, respectively, in an extreme case. Furthermore, the SOC of the battery can thus be estimated accurately, leaving a low of 0.081%, 0.97%, and 0.14% in the mean and maximum absolute SOC estimation error and the standard deviation, respectively.