Battery Monitoring and Electrical Energy Management

Meissner, Eberhard; Richter, G.

doi:10.1016/s0378-7753(02)00713-9

Cited by 211 publications

(28 citation statements)

References 17 publications

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“…The SOC describes the "reversible" [17], while the SOH describes the "irreversible changes" experienced by a battery [17]. The SOC is defined as the ratio of remaining capacity to the capacity when fully charged [16], or the actual amount of charge divided by the total amount of charge [18]. In EVs, the SOC can be used as a kind of fuel gauge, as known from conventional combustion engines.…”

Section: Battery Management Systems As Embedded Systemsmentioning

confidence: 99%

“…Second, transaction data are required, including the charging and discharging cycles of the battery. Third, to estimate the remaining useful life for different reuse scenarios and to assess whether a recombination of battery modules is possible the detailed usage history is needed, including basic condition data such as voltage, current and temperature experience by the battery as functions of time [27]. Based on the data that is needed for making informed reuse decisions, three aspects present themselves to advance BMSs into systems to obtain, store, and evaluate these data along the battery's first life.…”

Section: Extending Bmss For Making Decisions On Battery Reusementioning

confidence: 99%

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Extending Battery Management Systems for Making Informed Decisions on Battery Reuse

Monhof

Beverungen

Klör

et al. 2015

New Horizons in Design Science: Broadening the Research Agenda

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Abstract.A battery management system (BMS) is an embedded system for monitoring and controlling complex battery systems in high-tech goods, such as electric vehicles or military communication devices. BMSs are often designed for simplicity and cost efficiency, storing few crucial data on the condition of batteries. With an increasing trend to reuse batteries, BMSs face a need to implement additional functionality to support decision-making tasks. This functionality requires rich data on the structure, usage history, and condition of a battery that is not supported by current BMS type series. Based on expert interviews and document analyses, we sketch a design theory for implementing BMSs that supply the data required for making decisions on how to best reuse battery systems.

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Section: Battery Management Systems As Embedded Systemsmentioning

confidence: 99%

Section: Extending Bmss For Making Decisions On Battery Reusementioning

confidence: 99%

Extending Battery Management Systems for Making Informed Decisions on Battery Reuse

Monhof

Beverungen

Klör

et al. 2015

New Horizons in Design Science: Broadening the Research Agenda

View full text Add to dashboard Cite

show abstract

“…A model was proposed for crank capability prognosis and impedance spectrometry was used [11]. In some studies the focus is directed towards hybrid EVs where state estimation techniques such as the extended Kalman filter are used [12,13]. Autoregressive integrated moving average and artificial neural networks are also used for both clustering of * Correspondence: turev@gtu.edu.tr measured data and estimation [14].…”

Section: Introductionmentioning

confidence: 99%

A parametric battery state of health estimation method for electric vehicle applications

Sarıkurt¹,

Ceylan²,

Baliikçi³

2017

Turk J Elec Eng & Comp Sci

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Lithium-ion batteries are commonly preferred in electric vehicle applications. The relative capacity and state of health of a battery decrease with age. Therefore, accurate estimation of these parameters is essential. In this study a parametrical approach for estimation of battery state of health is proposed. A hybrid battery model that has a maximum error less than 3% is used. The relative capacity of the battery is estimated by using performance decrement with age.The method is validated by two different set of experiments. The first set is conducted with batteries that were aged by a controlled process and the second set is conducted with randomly aged batteries. The proposed method works successfully in both conditions with maximum error less than 5%.

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“…In order to guarantee safety and prolong lifetime of the battery, various battery management systems (BMS) are employed to ensure that the batteries operate in safe and reliable voltage and temperature range [1]. Monitoring the voltage of each battery cell and the ambient temperature is indispensible for a BMS to manage and control the batteries effectively [2].…”

Section: Introductionmentioning

confidence: 99%

A multi-cell battery pack monitoring chip based on 0.35-µm BCD technology for electric vehicles

Wang

Zhang

et al. 2015

IEICE Electron. Express

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This letter presents a multi-cell battery pack monitoring chip for electric vehicles (EVs). A multiplexer based on p-and n-type lateral doublediffused MOS (LDMOS) transistors is proposed to select the battery voltage in a battery pack with up to 12 series-connected battery cells. Measuring of the cell voltages is realized by a 12-bit incremental ΣΔ analog-to-digital converter (ADC) with offset cancellation. Fabricated in a 0.35-µm Bipolar-CMOS-DMOS (BCD) technology, measurement results show that an absolute conversion error of less than 3 mV is obtained. The conversion time for each cell is less than 600 µs under a 1-MHz clock signal generated by an internal oscillator. The chip area is 4 × 3.8 mm 2 and the current consumption is 510 µA in measuring mode, resulting in a operation power loss of 25.5 mW under a 50-V power supply.

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Battery Monitoring and Electrical Energy Management

Cited by 211 publications

References 17 publications

Extending Battery Management Systems for Making Informed Decisions on Battery Reuse

Extending Battery Management Systems for Making Informed Decisions on Battery Reuse

A parametric battery state of health estimation method for electric vehicle applications

A multi-cell battery pack monitoring chip based on 0.35-µm BCD technology for electric vehicles

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