2021
DOI: 10.1177/0020294020983376
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Abstract: State of charge (SOC) and state of health (SOH) of batteries are the indispensable control decision variables for online energy management system (EMS) in modern internal combustion engine vehicles. The real-time and accurate determination of SOC and SOH is essential to the reliability and safety of EMS operation. Obtaining good accuracy for the SOC estimation is difficult without considering SOH because of their coupling relationship. Although several works on the joint estimation of SOC and SOH of lithium–io… Show more

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Cited by 6 publications
(1 citation statement)
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“…Zhang et al [8] proposed a method based on actual charge and discharge data to construct a sliding window as model data, giving full play to the length dependence of the LSTM network and the combined attention mechanism of the network to achieve high-precision SOC estimation. Wang et al [9] discussed the modeling of the relationship between SOC and SOH of lead-acid batteries and their online collaborative estimation. A collaborative estimation algorithm is proposed to determine the SOC and SOH of the leadacid battery in real-time.…”
Section: Introductionmentioning
confidence: 99%
“…Zhang et al [8] proposed a method based on actual charge and discharge data to construct a sliding window as model data, giving full play to the length dependence of the LSTM network and the combined attention mechanism of the network to achieve high-precision SOC estimation. Wang et al [9] discussed the modeling of the relationship between SOC and SOH of lead-acid batteries and their online collaborative estimation. A collaborative estimation algorithm is proposed to determine the SOC and SOH of the leadacid battery in real-time.…”
Section: Introductionmentioning
confidence: 99%