Abstract
Electric vehicle (EV) is one of the preferred modes of transportation due to less emission of pollutants. The depleted batteries can be refueled by using a battery charging station (BCS), battery swapping station (BSS), and battery swapping van (BSV). Earlier, the depleted batteries were replenished using the different battery charging modes, but due to less flexibility, battery swapping (BS) was preferred over battery charging (BC). However, battery charging is not completely ruled out as it causes less damage to the battery and the swapped batteries have to be charged using battery charging. The forecasting on the arrival of EVs helps the station owner to serve the customers and in optimizing the various cost(s) associated with BSS. Metaheuristics help to arrive at the solutions at a faster rate when compared to the traditional optimization techniques. BSV is the active mode of replenishing energy which increases the effectiveness and efficiency of the battery swapping process. Further, a case study is carried out to understand the need to serve the customer for an unpredicted situation in the service station.
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Raj, N., Suri, M., Deepa, K. (2022). Integration of Battery Charging and Swapping Using Metaheuristics: A Review. In: Tomar, A., Malik, H., Kumar, P., Iqbal, A. (eds) Machine Learning, Advances in Computing, Renewable Energy and Communication. Lecture Notes in Electrical Engineering, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-16-2354-7_23
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