Faculty Publications

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An efficient optimization algorithm for electric vehicle routing problem
(John Wiley and Sons Inc, 2023) Vani, B.V.; Kishan, D.; Ahmad, M.D.W.; Reddy, C.R.P.
There has been a steady increase in the prevalence of electric vehicles (EVs) (electric cars) in the transportation industry. The limited range of EVs and the lack of charging facilities make it harder to gain widespread adoption of the EV service. Several optimisation algorithms for EV routes have not yet resolved the problems of trip time and travel cost. The study provides a Bat optimisation technique to reduce trip time and costs while taking into account customer service requests and EV charging schedules. Taking into account battery capacity, charging duration, and delivery/pickup needs, the suggested method may determine the optimal path to supercharger stations. To demonstrate its effectiveness, it is compared to other state-of-the-art algorithms across a variety of benchmark cases. © 2023 The Authors. IET Power Electronics published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
An efficient battery swapping and charging mechanism for electric vehicles using bat algorithm
(Elsevier Ltd, 2024) Vani, B.V.; Kishan, D.; Ahmad, M.W.; Naresh Kumar Reddy, B.N.K.
The recent surge in electric vehicle (EV) adoption has presented various challenges, notably in the charging and discharging processes of EV batteries, each characterized by unique traits. While conventional charging stations remain popular, battery swap stations (BSS) offer a compelling alternative, addressing issues like prolonged waiting times and potential battery degradation from fast charging. BSS, with its extensive array of battery systems, ensures efficient services for EVs. However, meticulous planning for the charging and discharging operations is imperative for both BSS and the overall grid to guarantee optimal functionality. This paper proposes an efficient approach to enhance the efficiency of battery swapping and charging mechanisms (BSCM) for electric vehicles, leveraging the bat algorithm. The BSCM is conceived as a system that incorporates both the battery swapping mechanism (BSM) and the battery charging mechanism (BCM). The key contribution lies in designing an effective BSCM where the BSM functions as a manager, handling battery swapping requests from EV users, while the BCM acts as a supporter, interfacing with the grid to regulate battery charging and discharging power. To efficiently address the mixed-integer nonlinear program (MINLP) inherent in this system, a Bat algorithm is developed. The results clearly demonstrate the effectiveness of the proposed algorithm in efficiently addressing large-scale problems, producing solutions that closely approach optimality. It promptly achieves a substantial reduction in battery swapping energy by 30% and 24%, respectively, and significantly enhances charging station utilization by 25% and 21% compared to the LSTM-Based Rolling Horizon Approach and Bilevel Optimization Approach. Additionally, the algorithm showcases remarkable improvements in battery swapping performance, boasting a 25% and 19% enhancement, and noteworthy increases in charging station utilization by 20% and 17% compared to the aforementioned approaches. This enhancement in the energy exchange with grid and regulation contributes to the overall efficiency and sustainability of electric vehicle operations. © 2024 Elsevier Ltd

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