| Summary: | 碩士 === 聖約翰科技大學 === 電機工程系碩士班 === 97 === A state of charge (SOC) estimator for lead-acid battery based on artificial neural network by using digital signal processor (DSP) is proposed. To realize a stable supply of electric power in portable apparatus, an accurate and reliable estimation method of SOC in a lead acid battery is required. However the dynamics of the lead acid battery are very complicated. The characteristics of the lead acid battery greatly change due to its degradation. Moreover the portable apparatus has many operating patterns, which are unknown beforehand. Therefore, it is very difficult to accurately estimate the SOC of the lead acid battery.
The proposed estimator uses the input data of open circuit voltage, discharging voltage, and internal resistance of battery to estimate the state of charge for battery under different discharging conditions.
To demonstrate the effectiveness of the proposed estimator, the method has been tested on a 12V, 7AH lead-acid battery under several different discharging conditions. The experimental data are found to be in close agreement. The test results show that the proposed algorithm is efficient and reliable.
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