A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

Hannan, M. A.; Lipu, Molla Shahadat Hossain; Hussain, Aini; Mohamed, Azah

doi:10.1016/j.rser.2017.05.001

Cited by 1,340 publications

(503 citation statements)

References 134 publications

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“…For convenience of comparison, the nominal battery capacity (1300 mAh) is defined as 100% SOC, and the different SOCs of overcharged LIBs will be defined accordingly based on the capacity obtained during charge, expressed as follows [14]:…”

Section: Experimental Designmentioning

confidence: 99%

Investigation into the Fire Hazards of Lithium-Ion Batteries under Overcharging

et al. 2017

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Numerous lithium-ion battery (LIB) fires and explosions have raised serious concerns about the safety issued associated with LIBs; some of these incidents were mainly caused by overcharging of LIBs. Therefore, to have a better understanding of the fire hazards caused by LIB overcharging, two widely used commercial LIBs, nickel manganese cobalt oxide (NMC) and lithium iron phosphate (LFP), with different cut-off voltages (4.2 V, 4.5 V, 4.8 V and 5.0 V), were tested in this work. Some parameters including the surface temperature, the flame temperature, voltage, and radiative heat flux were measured and analyzed. The results indicate that the initial discharging voltage increases with the growth of charge cut-off voltage. Moreover, the higher the cut-off voltage, the longer the discharging time to reach 2.5 V. An overcharged LIB will undergo a more violent combustion process and has lower stability than a normal one, and the increasing cut-off voltage aggravates the severity. In addition, it is also revealed that the NMC fails earlier than the LFP under the same condition. The temperatures for safety vent cracking, ignition, and thermal runaway of LIBs exhibit similar values for the same condition, which demonstrates that the LIB will fail at a certain temperature. Finally, the peak heat flux, total radiative heat flux, and total radiative heat will rise with the increase in voltage.

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Section: Experimental Designmentioning

confidence: 99%

Investigation into the Fire Hazards of Lithium-Ion Batteries under Overcharging

et al. 2017

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“…There are several studies dealing with the problem of estimating the SoC in batteries for different types of applications (e.g., electric vehicles) [18][19][20][21]. Nevertheless, the applicability of the reported results within the WSN context is difficult, as both the battery capacities and discharge profiles considered in these works are very different from those found in sensor nodes.…”

Section: Related Workmentioning

confidence: 99%

Estimating the Lifetime of Wireless Sensor Network Nodes through the Use of Embedded Analytical Battery Models

Rodrigues

Montez

Budke

et al. 2017

JSAN

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Abstract:The operation of Wireless Sensor Networks (WSNs) is subject to multiple constraints, among which one of the most critical is available energy. Sensor nodes are typically powered by electrochemical batteries. The stored energy in battery devices is easily influenced by the operating temperature and the discharge current values. Therefore, it becomes difficult to estimate their voltage/charge behavior over time, which are relevant variables for the implementation of energy-aware policies. Nowadays, there are hardware and/or software approaches that can provide information about the battery operating conditions. However, this type of hardware-based approach increases the battery production cost, which may impair its use for sensor node implementations. The objective of this work is to propose a software-based approach to estimate both the state of charge and the voltage of batteries in WSN nodes based on the use of a temperature-dependent analytical battery model. The achieved results demonstrate the feasibility of using embedded analytical battery models to estimate the lifetime of batteries, without affecting the tasks performed by the WSN nodes.

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“…[6][7][8][9][10][11][12]. In battery management, the accurate estimation of various states of the battery, including state-of-charge (SOC), state-of-health (SOH), and state-of-power (SOP), is a priority [13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Lithium-Ion Battery Online Rapid State-of-Power Estimation under Multiple Constraints

Shun

Huang

et al. 2018

Energies

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Abstract:The paper aims to realize a rapid online estimation of the state-of-power (SOP) with multiple constraints of a lithium-ion battery. Firstly, based on the improved first-order resistance-capacitance (RC) model with one-state hysteresis, a linear state-space battery model is built; then, using the dual extended Kalman filtering (DEKF) method, the battery parameters and states, including open-circuit voltage (OCV), are estimated. Secondly, by employing the estimated OCV as the observed value to build the second dual Kalman filters, the battery SOC is estimated. Thirdly, a novel rapid-calculating peak power/SOP method with multiple constraints is proposed in which, according to the bisection judgment method, the battery's peak state is determined; then, one or two instantaneous peak powers are used to determine the peak power during T seconds. In addition, in the battery operating process, the actual constraint that the battery is under is analyzed specifically. Finally, three simplified versions of the Federal Urban Driving Schedule (SFUDS) with inserted pulse experiments are conducted to verify the effectiveness and accuracy of the proposed online SOP estimation method.

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A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

Cited by 1,340 publications

References 134 publications

Investigation into the Fire Hazards of Lithium-Ion Batteries under Overcharging

Investigation into the Fire Hazards of Lithium-Ion Batteries under Overcharging

Estimating the Lifetime of Wireless Sensor Network Nodes through the Use of Embedded Analytical Battery Models

Lithium-Ion Battery Online Rapid State-of-Power Estimation under Multiple Constraints

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