A microcontroller-based intelligent battery system

Bowen, Leland H.; Zarr, R.; Denton, S.

doi:10.1109/62.282511

Cited by 7 publications

(5 citation statements)

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“…The characteristic of the terminal voltage curve during charging and discharging is used for minimizing the differences between the measured values and the actual SoC of the battery. In [29], a method for determining the SoC for NiMH batteries in notebook applications is presented. The method uses the battery's temperature, voltage and discharge/charge rate measurements to determine SoC, using look-up tables.…”

Section: History Of State-of-charge Indicationmentioning

confidence: 99%

State-of-the-art of battery state-of-charge determination

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Bergveld

Notten

et al. 2005

Meas. Sci. Technol.

248

140

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From the early days of its discovery, humanity has depended on electricity, a phenomenon without which our technological advancements would not have been possible. With the increased need for mobility, people moved to portable power storage—first for wheeled applications, then for portable and finally nowadays wearable use. Several types of rechargeable battery systems, including those of lead–acid, nickel–cadmium, nickel–metal hydride, lithium ion and lithium-ion polymer exist in the market. The most important of them will be discussed in this review. Almost as long as rechargeable batteries have existed, systems able to give an indication about the state-of-charge (SoC) of a battery have been around. Several methods, including those of direct measurements, book-keeping and adaptive systems (Bergveld et al 2002 Battery Management Systems, Design by Modelling (Philips Research Book Series) vol 1 (Boston: Kluwer)) are known in the art for determining the SoC of a cell or battery of cells. An accurate SoC determination method and an understandable and reliable SoC display to the user will improve the performance and reliability, and will ultimately lengthen the lifetime of the battery. However, many examples of poor accuracy and reliability can be found in practice (Bergveld et al 2002, cited above). This review presents an overview on battery technology and the state-of-the-art of SoC methods. The goal of all the presented SoC indication methods is to design an SoC indication system capable of providing an accurate SoC indication under all realistic user conditions, including those of spread—in both battery and user behaviour, a large temperature and current range and ageing of the battery.

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Section: History Of State-of-charge Indicationmentioning

confidence: 99%

State-of-the-art of battery state-of-charge determination

Pop

Bergveld

Notten

et al. 2005

Meas. Sci. Technol.

248

140

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“…Many companies have already released components on the marketplace for battery gauging: Philips Semiconductors (Philips, 1994), Duracell (Duracell, 1994), Benchmarq (Freeman, 1995), National Semiconductors (Bowen et al, 1994), Exar (Stephan, 1995) and Microchip (Watson, 1995). All these companies claim a few percents accuracy \under typical conditions".…”

Section: Issues In Battery Management Modelsmentioning

confidence: 99%

“…All these companies claim a few percents accuracy \under typical conditions". However, most use a non-evolving, pre-de ned model that doesn't take all the e ects described in the following into account (see (Bowen et al, 1994) for instance). Some works towards \adaptivity" are to be mentioned, like (Pesco and al., 1989).…”

Section: Issues In Battery Management Modelsmentioning

confidence: 99%

Discharge Prediction of Rechargeable Batteries with Neural Networks1

Gerard

Patillon

d’Alché‐Buc

1999

ICA

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This article presents an original method to accurately predict the end of discharge of rechargeable batteries inserted in portable electronic equipments. The proposed method is based on two neural networks organized in a masterslave relation. A prediction accuracy of 3% (18 minutes) is reached. A further improvement of the system is introduced by adapting on-line another neural network to the actual battery currently in use. This adaptive method reduces the average error to 10 minutes. Results are promising and implementation, carried out in a portable multimeter prototype, only requires a small amount of the computing power already available inside most portable equipments.

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“…Microcontrollers have a long tradition of serving as intelligent controllers in advanced electronic instruments [1][2][3][4][5][6]. Traditionally microcontrollers from Intel (8751, 80535, etc) and Motorola (68HC11, etc) have dominated microcontroller-based instruments.…”

Section: Introductionmentioning

confidence: 99%

Generation and measurement of pulses and delays with RISC-controllers

Bengtsson¹

1997

Meas. Sci. Technol.

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An instrument for the generation of pulses and delays has been developed for applications in laserspectroscopy experiments. The pulses from a chopped laserbeam are counted, and when a preset value is reached, two signals are generated: one delayed trigger pulse with constant length and one delayed 'shutter pulse' (referred to as the 'shutter window' below) which opens a light shutter and allows one light pulse to enter the experimental region and excite the sample. The delays of the trigger pulse and the shutter window and the width of the shutter window can all be set independently to any value from 0 up to 50 ms with 0.05 ms steps. A separate microcontroller measures the width of the shutter window with an accuracy of 1 µs. The pulse delays and the width of the shutter window are set with thumbwheel potentiometers connected as voltage dividers. A microcontroller reads the set values with a four-channel, 12-bit AD converter. This technique saves a lot of hardware wiring as well as software writing when compared to the alternative of using separate, BCD-coded thumbwheels for each timesetting.In total, the instrument consists of two independent RISC-controllers: one PIC16C55 for counting chopper pulses and generating pulses and delays, and one PIC16C74 for measuring (and displaying) the width of the shutter window. The width of the shutter window is measured with 1 µs resolution by taking full advantage of two different peripherial I/O devices in the PIC16C74: the 16-bit 'input capture' module and the external interrupt facility.

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A microcontroller-based intelligent battery system

Cited by 7 publications

References 0 publications

State-of-the-art of battery state-of-charge determination

State-of-the-art of battery state-of-charge determination

Discharge Prediction of Rechargeable Batteries with Neural Networks1

Generation and measurement of pulses and delays with RISC-controllers

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