Battery State-of-Charge Estimator Using the MARS Technique

Anton, J.C.; Nieto, P.J. Garcı́a; Juez, Francisco Javier de Cos; Lasheras, Fernando Sánchez; Viejo, Cecilio Blanco; Gutiérrez, Nieves Roqueñí

doi:10.1109/tpel.2012.2230026

Cited by 76 publications

(45 citation statements)

References 17 publications

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“…An accurate estimation of the SOC is important to prolong the battery life and improve the performance of the electric vehicle [1,2]. However, because the battery is a strongly nonlinear and time-variable system, in practical applications it is hard to measure the SOC directly due to its complicated electrochemical processes and the influence of various factors [3].…”

Section: Introductionmentioning

confidence: 99%

“…Stateequation : x k`1 " A x x k`Bk u k`wk (1) Observationequation : y k " C k x k`Dk u k`vk (2) where u k is the input of the system, including the battery current, residual capacity, battery temperature, among other variables, and y k is the output of the system, which usually indicates the terminal voltage of the battery. The most difficult challenge of the KF method is determining the state equation and the observation equation.…”

Section: Introductionmentioning

confidence: 99%

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Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm

et al. 2016

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An estimation of the power battery state of charge (SOC) is related to the energy management, the battery cycle life and the use cost of electric vehicles. When a lithium-ion power battery is used in an electric vehicle, the SOC displays a very strong time-dependent nonlinearity under the influence of random factors, such as the working conditions and the environment. Hence, research on estimating the SOC of a power battery for an electric vehicle is of great theoretical significance and application value. In this paper, according to the dynamic response of the power battery terminal voltage during a discharging process, the second-order RC circuit is first used as the equivalent model of the power battery. Subsequently, on the basis of this model, the least squares method (LS) with a forgetting factor and the adaptive unscented Kalman filter (AUKF) algorithm are used jointly in the estimation of the power battery SOC. Simulation experiments show that the joint estimation algorithm proposed in this paper has higher precision and convergence of the initial value error than a single AUKF algorithm.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm

et al. 2016

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“…All of these factors need to be considered when calculating the SoC. Many methods for estimating the SoC have been reported in the literature [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. For instance, measuring cell voltage to calculate the SoC can work well for lead-acid battery chemistries, for which the cell voltage and SoC are fairly linearly related, but is ineffective for lithium-ion, for which the voltage is mostly flat over the battery discharge curve (except at the extremes, where it is non-linear).…”

Section: Introductionmentioning

confidence: 99%

“…The goal is to learn a general rule that maps input variables to outputs. In [20], a statistical learning method called MARS was applied to estimate the SoC of a high capacity battery cell for a simple data profile (constant current-constant voltage charge and constant current discharge) and for a limited range of SoC. These limitations are partially the consequence of the fact that MARS parameters are difficult to estimate.…”

Section: Introductionmentioning

confidence: 99%

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A New Predictive Model for the State-of-Charge of a High-Power Lithium-Ion Cell Based on a PSO-Optimized Multivariate Adaptive Regression Spline Approach

Anton

Nieto

García–Gonzalo

et al. 2016

IEEE Trans. Veh. Technol.

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I. INTRODUCTIONHE rechargeable battery industry is experiencing significant growth driven by an upsurge in portable battery-powered devices, electric vehicles and other industrial applications. A number of different battery chemistries, such as lead-acid, nickel-metal-hydride and lithium-ion, among others, are used in these applications. One of the most popular types of rechargeable battery technologies is the lithium-ion battery. Its chemistry provides a high cell voltage, high energy density, long lifespan and exceptional cyclability. All lithiumion battery applications, especially those used in electric Manuscript received April 30, 2015; revised July 20, 2015. This work was supported in part by the Spanish Science and Innovation Ministry and the Regional Ministry of Principality of Asturias under Grants MINECO-13-DPI2013-46541-R, FC-15-GRUPIN14-073 and MINECO-15-TIN2014-56967-R J. C. Álvarez Antón, J. C. Viera, M. González and C. Blanco Viejo are with the Electrical Engineering Department, University of Oviedo, Campus de Viesques, Gijón, Spain 33204 (+34 985-182553; e-mail: anton@uniovi.es).P. J. Garcia Nieto and E. García Gonzalo are with the Mathematics Department, University of Oviedo, Spain 33007 (e-mail: pjgarcia@uniovi.es).vehicles, require a Battery Management System (BMS). The main objective of a BMS is to maintain the health of all the cells in the battery within the manufacturer's recommended operating conditions in order to prolong the lifespan of the battery pack. One of the most important BMS functional requirements is that of estimating the State-of-Charge (SoC) of the battery or of the individual cells in the battery pack. SoC is an expression of the current battery capacity as a percentage of its maximum capacity. The BMS needs to estimate the SoC in order to report the capacity left in the battery, typically called the "gas gauge". Several applications require accurate measurement of SoC to give users an indication of available runtime. The SoC is also needed to control the battery charging or discharging process. This control can avoid situations such as over-discharging or overcharging, which lead to premature wear-out of the battery. The lithium-ion chemistry operates safely within the designed operating voltages; however, the battery becomes unstable and may pose a safety hazard if overcharged. Over-charging stresses the battery and may lead to damage. Over-discharging also stresses the battery and reduces its lifespan.The available capacity of a battery depends on several factors such as cell chemistry, charging rates, discharging rates and temperature. All of these factors need to be considered when calculating the SoC. Many methods for estimating the SoC have been reported in the literature [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. For instance, measuring cell voltage to calculate the SoC can work well for lead-acid battery chemistries, for which the cell voltage and SoC are fairly linearly related, but is ineffective for lithium-ion, for which the volta...

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Recent Research on Battery Diagnostics, Prognostics, and Uncertainty Management

Jing

Lee

et al. 2016

Advances in Battery Manufacturing, Service, and Management Systems

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Battery State-of-Charge Estimator Using the MARS Technique

Cited by 76 publications

References 17 publications

Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm

Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm

A New Predictive Model for the State-of-Charge of a High-Power Lithium-Ion Cell Based on a PSO-Optimized Multivariate Adaptive Regression Spline Approach

Recent Research on Battery Diagnostics, Prognostics, and Uncertainty Management

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