Approximate least squares

Lunglmayr, Michael; Unterrieder, Christoph; Huemer, Mario

doi:10.1109/icassp.2014.6854489

Cited by 12 publications

(17 citation statements)

References 8 publications

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“…For n = 0, a persistent noise-dependent error term remains for the approximation such thatx (E)ALS =x BLS [24]. In Tab.…”

Section: Estimation Schemementioning

confidence: 99%

“…In the next step, we analyze the influence of the choice of µ. In [24] we show that the ALS estimator converges if µ is chosen to…”

Section: Analysis: Setting Of the Iteration Step Widthmentioning

confidence: 99%

“…For an appropriate choice of µ the error norm x (k) (E)ALS −x 2 converges to zero for n = 0 and k → ∞ [23,24]. For n = 0, a persistent noise-dependent error term remains for the approximation such thatx (E)ALS =x BLS [24].…”

Section: Estimation Schemementioning

confidence: 99%

“…1. Other advantages are its reduced number of needed memory access operations, the simplified memory management and the simple architecture in case of a hardware implementation [23,24].…”

Section: Estimation Schemementioning

confidence: 99%

“…First of all, an estimation scheme is introduced which uses a simplified version of the so-M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT called approximate least squares (ALS) algorithm [23,24]. In addition a novel model description for the voltage transients during phases of no or low loads is presented, used in order to describe the characteristic of the transients for different operating conditions and different cell chemistries.…”

Section: Introductionmentioning

confidence: 99%

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Battery state-of-charge estimation using approximate least squares

Unterrieder

Zhang

Lunglmayr

et al. 2015

Journal of Power Sources

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Novel adaptive method for the estimation of the electromotive force of the battery -The proposed concept offers an accurate state-of-charge and capacity estimation -Analysis and implementation of novel least squares estimation schemes -Use of a-priori information about the battery for the extrapolation process -Evaluation of the proposed concept based on an implementation on a system-on-chip M Abstract In recent years, much effort has been spent to extend the runtime of batterypowered electronic applications. In order to improve the utilization of the available cell capacity, high precision estimation approaches for batteryspecific parameters are needed. In this work, an approximate least squares estimation scheme is proposed for the estimation of the battery state-of-charge (SoC). The SoC is determined based on the prediction of the battery's electromotive force. The proposed approach allows for an improved re-initialization of the Coulomb counting (CC) based SoC estimation method. Experimental results for an implementation of the estimation scheme on a fuel gauge system on chip are illustrated. Implementation details and design guidelines are presented. The performance of the presented concept is evaluated for realistic operating conditions (temperature effects, aging, standby current, etc.). For the considered test case of a GSM/UMTS load current pattern of a mobile phone, the proposed method is able to re-initialize the CC-method

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“…For n = 0, a persistent noise-dependent error term remains for the approximation such thatx (E)ALS =x BLS [24]. In Tab.…”

Section: Estimation Schemementioning

confidence: 99%

“…In the next step, we analyze the influence of the choice of µ. In [24] we show that the ALS estimator converges if µ is chosen to…”

Section: Analysis: Setting Of the Iteration Step Widthmentioning

confidence: 99%

Section: Estimation Schemementioning

confidence: 99%

“…1. Other advantages are its reduced number of needed memory access operations, the simplified memory management and the simple architecture in case of a hardware implementation [23,24].…”

Section: Estimation Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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