Simulation of SLI Lead-Acid Batteries for SoC, Aging and Cranking Capability Prediction in Automotive Applications

Pilatowicz, Grzegorz; Budde-Meiwes, Heide; Schulte, Dominik; Kowal, Julia; Zhang, Y.; Du, Xinyu; Salman, Mutasim; Gonzales, D.; Alden, Jeffrey M.; Sauer, Dirk Uwe

doi:10.1149/2.019209jes

Cited by 30 publications

(10 citation statements)

References 18 publications

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“…There also exist other equations and methods for computing a battery's released capacity at different discharge currents [20,[24][25][26]. However, in the papers [21,22], it was shown that the empiric equations (2)(3)(4) are the most appropriate for experimental data throughout the entire interval of discharge current variation including at small discharge currents.…”

Section: Generalized Peukert's Equationsmentioning

confidence: 99%

Analysis of Generalized Peukert’s Equations for determining the capacity of nickel-cadmium batteries

Yazvinskaya¹

2018

International Journal of Electrochemical Science

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In this paper, we analysed the use possibility of the generalized Peukert's equations C=C m /(1+(i/i 0) n), C=0.522C m tanh((i/i 0) n /0.522)/(i/i 0) n , and C=C m erfc((i/i k-1)/n)/erfc(-1/n) to compute the released capacity of nickel-cadmium batteries at different discharge currents. It was proven that these equations correspond well to the experimental data throughout the entire variation interval of discharge currents. It was shown that the parameter n does not depend on the nominal capacity of the batteries under examination; however, it possesses various values for batteries of different modes of discharge (Long, Medium, High). Further, it was shown that the functional dependence of a battery's released capacity with a discharge current is determined by the statistical phase transition subjected to the normal distribution law. The proposed statistical mechanism allows us to explain the variation in parameter n depending on the types of batteries under examination.

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Section: Generalized Peukert's Equationsmentioning

confidence: 99%

Analysis of Generalized Peukert’s Equations for determining the capacity of nickel-cadmium batteries

Yazvinskaya¹

2018

International Journal of Electrochemical Science

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“…Remaining capacity is modeled by physical-chemical governing differential equations of lead-acid battery [4,17]. Loss capacity is modeled by various Ah throughput during specific operations deviating from the standard conditions [18,19]. The loss-capacity model basically consists of the voltage and aging model.…”

Section: Introductionmentioning

confidence: 99%

“…The loss-capacity model basically consists of the voltage and aging model. The voltage model is decomposed into static and transient electrical equivalent circuits [19]. The aging model includes corrosion, gassing, acid stratification phenomena [18,19] and degradation of active material [20,21] equations.…”

Section: Introductionmentioning

confidence: 99%

Failure Warning at the End of Service-Life of Lead–Acid Batteries for Backup Applications

et al. 2020

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The prediction of remaining useful life is an important function of battery management systems. Existing research typically focused on factors that determine the quantity of the remaining useful capacity, and are able to determine the remaining useful capacity several years before battery failure to counter hysteresis of variables of lead–acid batteries. These techniques are not suitable at the end of service-life for backup batteries. This paper proposes a linear-superposition–voltage-aging model with three improvements. First, the estimation of the deep-discharge of the proposed voltage model does not require the remaining useful capacity. Second, the internal resistance of the deep-discharge is predicted from the contacting resistance of electrochemical impedance spectroscopy. Third, a morphology correction factor of internal resistance is about to saturate at the end of battery service-life. The model accurately forecasts battery failure at the end of service-life in two groups of accelerated-aging experiments. The proposed method in this paper focuses on the factors that determine quality of remaining useful capacity to counter hysteresis of variables of lead–acid batteries and judge battery failure at the end of service-life.

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“…The main components are typically the inductive element (L), the inner resistance (R i ) as sum of the half-cell resistances, and two RC-elements with R ct,NAM , C ct,NAM and R ct,PAM , C ct,PAM representing each one charge transfer (ct) at the negative active mass (NAM) and positive active mass (PAM). It is expected that the different processes and thus the parameters of the underlying EEC do change differently not only with SoC (e.g., [13,14]), current rate (e.g., [14]) and temperature but with SoH of the battery (e.g., [5,10,11,15]).…”

Section: Introductionmentioning

confidence: 99%

“…Pilatowicz et al [15] have studied the change of EEC elements for a 12 V flooded starting-lighting-ignition (SLI) battery tested with a driving profile. In this profile cycles with high currents (20 I 20 ) and different depth of discharges (up to 50%) were combined with pause phases.…”

Section: Introductionmentioning

confidence: 99%

Battery State Estimation for Lead-Acid Batteries under Float Charge Conditions by Impedance: Benchmark of Common Detection Methods

Badeda¹,

Kwiecien

Schulte³

et al. 2018

Applied Sciences

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Impedance or admittance measurements are a common indicator for the condition of lead-acid batteries in field applications such as uninterruptible power supply (UPS) systems. However, several commercially available measurement units use different techniques to measure and interpret the battery impedance. This paper describes common measurement methods and compares their indication for the state of health (SoH) to those of electrochemical impedance spectroscopy (EIS). For this analysis, two strings consisting each of 24 valve-regulated lead-acid (VRLA) batteries with a rated voltage of 12 V and about 7 Ah capacity were kept under standard UPS conditions in float charge for over 560 days. They were monitored continuously with a LEM Sentinel 2 and went into regular check-ups with impedance measurements by a Hioki BT3554 as well as electrochemical impedance spectroscopy (EIS) measurements with an impedance meter (μEIS). Today it is widely expected that solely the relative increase of the impedance reading is sufficient for the estimation of the available capacity. However, it can be shown that the measured relative increase deviates for different frequencies and therefore the choice of the excitation signal and measurement frequency does make a difference for the calculation of the available capacity. Finally, a method for a more decisive monitoring in field applications is suggested.

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Simulation of SLI Lead-Acid Batteries for SoC, Aging and Cranking Capability Prediction in Automotive Applications

Cited by 30 publications

References 18 publications

Analysis of Generalized Peukert’s Equations for determining the capacity of nickel-cadmium batteries

Analysis of Generalized Peukert’s Equations for determining the capacity of nickel-cadmium batteries

Failure Warning at the End of Service-Life of Lead–Acid Batteries for Backup Applications

Battery State Estimation for Lead-Acid Batteries under Float Charge Conditions by Impedance: Benchmark of Common Detection Methods

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