Enhancing Thermal Performance and Lifetime Cycles of Li-ion Battery in Electric Vehicles

karim Fayez, Mohamed Shafei, Doaa Ibrahim

Abstract


Hybrid energy storage system has essential priority in Electric Vehicle applications. Therefore, the design of an appropriate power sharing algorithm among energy storage components is necessary to improve battery thermal performance and provide extra extension of battery lifetime cycles. This paper presents an analytical study on the effect of using wavelet decomposition-based power sharing algorithm to force the high frequency component to be fed by the supercapacitor and accordingly reduces the thermal stress on the battery. The proposed approach was investigated by applying it on electric vehicle model in ADVISOR Tool/MATLAB using different driving profiles such as Urban Dynamometer Driving Schedule profile, Highway Fuel Economy Test, New York City Cycle, Los Angeles 1992 and new European driving cycle. The results declare that by using proposed power sharing algorithm, the working temperature of lithium battery decreases significantly while battery lifetime cycles increase, apparently. For urban dynamometer driving schedule, the operating temperature of lithium battery is improved much at maximum decomposition levels reaching to only 25.6 °C compared to 35 °C. In addition, the battery lifetime cycles increased from 2213 to 2585 cycles. Neural Networks pattern recognition tool is also applied to classify the driving cycle to the nearest reference cycles chosen to represent the different driving conditions which help to detect the appropriate wavelet decomposition level, achieving better battery thermal performance and battery lifetime cycles.


Keywords


Battery lifetime cycles (BLTC), Battery thermal performance (BTP), Electric Vehicle (EV), Hybrid Energy Storage System (HESS), Lithium Battery, Wavelet Transform (WT), Electric Vehicle(EV)

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v11i3.12105.g8248

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