Methods of SoC determination of lead acid battery

Křivík, Petr

doi:10.1016/j.est.2017.11.013

Cited by 31 publications

(16 citation statements)

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“…The coulomb counting method [8] and the open circuit voltage method [9] are widely used to the SoC estimation in the last few decades, because they have the characteristics of the simple principle and the less computational effort for the vehicle-mounted BMS system. However, it is difficult to meet with the complex and changeable driving conditions of EVs, due to its low accuracy and poor robustness of the SoC estimation results, so they are now replaced by other methods.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries

Guo

et al. 2020

IEEE Access

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The accurate state of charge (SoC) online estimation is a significant indicator that relates to driving ranges of electric vehicles (EV). The relationship between open circuit voltage (OCV) and SoC plays an important role in SoC estimation for lithium-ion batteries. To compare with the traditional incremental OCV (IO) test and the low current OCV (LO) test, a novel OCV test which combines IO test with LO test (CIL) is proposed in this paper. Based on the reliable parameters online identification of the dual polarization (DP) battery model, two SoC estimation algorithms are compared on the accuracy, robustness and convergence speed for the entire SoC region. Meanwhile, the comparative study of the three OCV-SoC relationships fits by the corresponding OCV tests is discussed in terms of the SoC online estimation under various temperatures. The results show that the adaptive extended Kalman filter (AEKF) algorithm can better improve the accuracy and robustness of SoC estimation than that of the extended Kalman filter (EKF) algorithm. Most importantly, the OCV-SoC relationship obtains from the CIL OCV test method is applied to the AEKF algorithm, which has higher accuracy and better statistical indices of SoC estimation, especially suitable for the low temperature. INDEX TERMS Lithium-ion batteries, state of charge estimation, open circuit voltage test, online parameters identification, adaptive extended Kalman filter algorithm.

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Section: Introductionmentioning

confidence: 99%

Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries

Guo

et al. 2020

IEEE Access

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“…The SOC of lead acid battery is the ratio between the current capacity (CA) and the maximum capacity (CM), which varies depending on the state of health (SOH). The CM (Q) is the usable capacity at the average discharge rate and current discharge temperature [8]. The relationship between the current capacity and the maximum capacity is determined by equation 1.…”

Section: Introductionmentioning

confidence: 99%

Development of an Electronic Load Applied to the Characterization of Electric Batterie

Quintero¹,

Palacio-Fernández²

2020

International Journal of Engineering Research and Technology

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People use batteries as sources of power for electrical and electronic devices in their daily life. Nevertheless, these possess temporary supply limitations due to their state of charge (SOC). A technique used to determine the state of charge is counting amperes, identifying the amount of consumed and of missing amperes according to the initial capacity of the battery. An electronic load consisting of an operational amplifier and an IGBT were used in order to maintain a constant current in the battery discharge process, as well as a data acquisition system that specifies the time needed to obtain the variables of current defined by the electronic load, as well as the battery voltage. Without a heatsink, the Ice current of the IGBT does not remain constant, due to temperature increases exceeding 100°C in less than a minute. A dissipation system with and without ventilation was needed, and the one that kept the current constant was a heatsink for AMD processor with a thermal solution greater than 90W with active ventilation. The discharge curve was managed with it while maintaining the temperature of the IGBT at a maximum value of 46°C during the 4.5 hours, with a current of 4.19A. The initial capacity of the lead acid battery used was close to 19Ah, a little less than that defined by the manufacturer for the new battery (20Ah). One of the biggest problems in determining the state of charge by means of ampere counting is the accuracy of the sensor. To the current sensor used, you can implement filtering stages that improve the SOC value as future work. It should be used that the Vce is below the battery to be discharged. Therefore, this system could not be implemented in 2V batteries, because the Vce voltage in the IGBT exceeds 2V and cannot deliver a potential difference in the resistive load.

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“…The model parameters are calculated by obtaining the variation law of the battery pack's closed-circuit voltage output response. The real-time performance is poor, so it cannot be applied for various working conditions [5]. Recursive least squares (RLS) method is a common identification algorithm based on online estimation to achieve high accuracy.…”

Section: Introductionmentioning

confidence: 99%

State-of-charge Estimation of Lithium-ion Battery Based Online Parameter Identification

Feng

Huang

et al. 2020

E3S Web Conf.

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Accurately estimating the state of charge (SOC) of lithium-ion is very important to improving the dynamic performance and energy utilization efficiency. In order to reduce the influence of model parameters and system coloured noise on SOC estimation accuracy, this paper proposes the SOC estimation based on online identification. Based on the mixed simplified electrochemical model, the forgetting factor recursive least squares (FFRLS) method was used to identify the parameters online, and the SOC estimation was carried out in combination with Unscented Kalman Filter (UKF). Finally, the accuracy and feasibility of the method are verified by Federal Urban Driving Schedule (FUDS), the online identification and SOC estimation are carried out. The experimental results show that the SOC estimation of online parameter identification is more accurate, the system stability is faster and the error is smaller.

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Methods of SoC determination of lead acid battery

Cited by 31 publications

References 0 publications

Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries

Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries

Development of an Electronic Load Applied to the Characterization of Electric Batterie

State-of-charge Estimation of Lithium-ion Battery Based Online Parameter Identification

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