Modeling of lithium-ion battery using MATLAB/simulink

Yao, Low Wen; Aziz, Maniruzzaman A.; Kong, Pui Yee; Idris, Nik Rumzi Nik

doi:10.1109/iecon.2013.6699393

Cited by 83 publications

(39 citation statements)

References 5 publications

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“…The simulation model of the battery pack with ISCr was configured with MATLAB/Simulink (MATLAB R2017b, MathWorks, Natick, MA, USA) [50]. In both simulation and experiment configuration, the battery pack was composed of four normal battery cells and a faulted battery cell with ISCr.…”

Section: Simulation Configurationmentioning

confidence: 99%

Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell

et al. 2018

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Early detection of internal short circuit which is main cause of thermal runaway in a lithium-ion battery is necessary to ensure battery safety for users. As a promising fault index, internal short circuit resistance can directly represent degree of the fault because it describes self-discharge phenomenon caused by the internal short circuit clearly. However, when voltages of individual cells in a lithium-ion battery pack are not provided, the effect of internal short circuit in the battery pack is not readily observed in whole terminal voltage of the pack, leading to difficulty in estimating accurate internal short circuit resistance. In this paper, estimating the resistance with the whole terminal voltages and the load currents of the pack, a detection method for the soft internal short circuit in the pack is proposed. Open circuit voltage of a faulted cell in the pack is extracted to reflect the self-discharge phenomenon obviously; this process yields accurate estimates of the resistance. The proposed method is verified with various soft short conditions in both simulations and experiments. The error of estimated resistance does not exceed 31.2% in the experiment, thereby enabling the battery management system to detect the internal short circuit early.

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Section: Simulation Configurationmentioning

confidence: 99%

Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell

et al. 2018

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“…Energy requirement for the sensors, DAS, satellite communication, and subsea acoustic telemetry system are to be met by the onboard energy storage system. In order to calculate the required energy storage requirements, a virtual battery sizing (VBS) tool was developed in MATLAB, which accepts the power demand profile and computes the required battery capacity for the defined mission period, taking into consideration the load profile, battery chemistry, ambient temperature, self-discharge, terminal voltage, and the efficiency of the battery under the envisaged load profile (Daowd et al, 2010;Yao et al, 2013). The power demand pattern in the MSB is shown in Figure 4.…”

Section: Power System Designmentioning

confidence: 99%

Evolution of Reliable and Cost-Effective Power Systems for Buoys Used in Monitoring Indian Seas

Venkatesan¹,

Vedachalam²,

Muthiah³

et al. 2015

mar technol soc j

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A B S T R A C TThis paper details the evolution of reliable and cost-effective data buoy power systems used for environment monitoring applications in the Indian seas. A reliable power system is the key requirement for offshore moored buoys involved in meteorological and tsunami monitoring missions, as unavailability of the operating power results in loss of time-critical data and can have serious impact on societal protection and, in addition, results in costly repairs and reinstallations. As a significant development and driven by stringent IEC 61508 Safety Integrity Level (SIL) standards, a Generation III power system was able to meet the required SIL 4 reliability requirements compared to the Generation I system that complied only with SIL 1. It is found that by using a suggested four slot annual maintenance plan, an operating Generation III hybrid power system, and lead acid batteries powered by solar energy and backed by Lithium thionyl chloride batteries, in addition to meeting the required SIL 4 reliability levels, the energy cost of transmission is reduced to U.S. $1.7 per data set, compared to U.S. $2.7 in the Generation II systems. Ongoing efforts in increasing the green footprint in futuristic systems are detailed. The study provides confidence in the power system's reliable, cost-effective and eco-friendly support to India's Ocean Observation Network program.

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“…While simulating the voltage behavior, the proposed battery simulator applies different modes in different SOC regions. In the past research, the measured data of the internal resistance of a Li-ion battery cell show that the internal resistance in the flat region that is normally 20% to 80% SOC [19,28,29] is less affected by the current rate effect, so ECMs usually model the internal resistance in this SOC region as a constant resistance. However, when the battery SOC is close to the empty or full state, the SOC effect and current rate effect cannot be ignored.…”

Section: Proposed Battery Simulatormentioning

confidence: 99%

A Lithium-Ion Battery Simulator Based on a Diffusion and Switching Overpotential Hybrid Model for Dynamic Discharging Behavior and Runtime Predictions

et al. 2016

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Abstract:A new battery simulator based on a hybrid model is proposed in this paper for dynamic discharging behavior and runtime predictions in existing electronic simulation environments, e.g., PSIM, so it can help power circuit designers to develop and optimize their battery-powered electronic systems. The hybrid battery model combines a diffusion model and a switching overpotential model, which automatically switches overpotential resistance mode or overpotential voltage mode to accurately describe the voltage difference between battery electro-motive force (EMF) and terminal voltage. Therefore, this simulator can simply run in an electronic simulation software with less computational efforts and estimate battery performances by further considering nonlinear capacity effects. A linear extrapolation technique is adopted for extracting model parameters from constant current discharging tests, so the EMF hysteresis problem is avoided. For model validation, experiments and simulations in MATLAB and PSIM environments are conducted with six different profiles, including constant loads, an interrupted load, increasing and decreasing loads and a varying load. The results confirm the usefulness and accuracy of the proposed simulator. The behavior and runtime prediction errors can be as low as 3.1% and 1.2%, respectively.

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Modeling of lithium-ion battery using MATLAB/simulink

Cited by 83 publications

References 5 publications

Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell

Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell

Evolution of Reliable and Cost-Effective Power Systems for Buoys Used in Monitoring Indian Seas

A Lithium-Ion Battery Simulator Based on a Diffusion and Switching Overpotential Hybrid Model for Dynamic Discharging Behavior and Runtime Predictions

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