2022
DOI: 10.1002/er.7874
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Model‐based state of X estimation of lithium‐ion battery for electric vehicle applications

Abstract: Summary In developing an efficient battery management system (BMS), an accurate and computationally efficient battery states estimation algorithm is always required. In this work, the highly accurate and computationally efficient model‐based state of X (SOX) estimation method is proposed to concurrently estimate the different battery states such as state of charge (SOC), state of energy (SOE), state of power (SOP), and state of health (SOH). First, the SOC and SOE estimation is performed using a new joint SOC … Show more

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Cited by 43 publications
(22 citation statements)
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“…En is the rated energy of the battery, and I represents the charging and discharging current of the battery under actual operating conditions. Due to the shortcomings of the power integration method, scholars have proposed a series of improvements, such as solving the SOE value by constructing the mapping relationship among the discharge power, OCV, residual energy, and the SOE [51].…”
Section: Power Integration Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…En is the rated energy of the battery, and I represents the charging and discharging current of the battery under actual operating conditions. Due to the shortcomings of the power integration method, scholars have proposed a series of improvements, such as solving the SOE value by constructing the mapping relationship among the discharge power, OCV, residual energy, and the SOE [51].…”
Section: Power Integration Methodsmentioning
confidence: 99%
“…Some studies suggested that the predicted variables, such as SOC and aging, are not accurate values. However, these parameters are directly used in the battery model to predict the online peak power of the batteries [51]. Later studies put forward an electrochemical model that considers the influence of temperature on internal resistance and capacity [52].…”
Section: Overview Of the State-of-power Predictionmentioning
confidence: 99%
“…In current updated EV models, NMC, NCA, and LFP are mostly preferred for EV applications because of their high safety efficiency, longer life cycle, and more power and energy densities compared with the other chemistries. 53,54 In Figure 1, LFP shows lower energy density, but it offers high power density, high life cycle, fast charging, and very good safety. 55 In the last few years, many renowned automotive companies such as TESLA, HONDA, TOYOTA, FORD, and MITSUBISHI have already implemented LIB chemistries in their EV models.…”
Section: Lib Chemistriesmentioning
confidence: 99%
“…This process is time-consuming and powerful, and it is only effective for training data. Document [ 19 ] selects the recursive least squares method with different forgetting factors to identify equivalent model circuit parameters, and uses the linear Kalman filter to estimate SOC. However, the SOC estimation algorithm based on the Kalman filter requires accurate battery model parameters [ 20 ], because the covariance of process noise and measurement noise is well known [ 21 ].…”
Section: Introductionmentioning
confidence: 99%