Faculty Publications

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Author: search.filters.author.Kashyap, Y.Subject: search.filters.subject.Battery-electric vehicles

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    Adaptive-Energy-Sharing-Based Energy Management Strategy of Hybrid Sources in Electric Vehicles
    (MDPI, 2023) Sidharthan, V.P.; Kashyap, Y.; Kosmopoulos, P.
    The energy utilization of the transportation industry is increasing tremendously. The battery is one of the primary energy sources for a green and clean mode of transportation, but variations in driving profiles (NYCC, Artemis Urban, WLTP class-1) and higher C-rates affect the battery performance and lifespan of battery electric vehicles (BEVs). Hence, as a singular power source, batteries have difficulty in tackling these issues in BEVs, highlighting the significance of hybrid-source electric vehicles (HSEVs). The supercapacitor (SC) and photovoltaic panels (PVs) are the auxiliary power sources coupled with the battery in the proposed hybrid electric three-wheeler (3W). However, energy management strategies (EMS) are critical to ensure optimal and safe power allocation in HSEVs. A novel adaptive Intelligent Hybrid Source Energy Management Strategy (IHSEMS) is proposed to perform energy management in hybrid sources. The IHSEMS optimizes the power sources using an absolute energy-sharing algorithm to meet the required motor power demand using the fuzzy logic controller. Techno-economic assessment wass conducted to analyze the effectiveness of the IHSEMS. Based on the comprehensive discussion, the proposed strategy reduces peak battery power by 50.20% compared to BEVs. It also reduces the battery capacity loss by 48.1%, 44%, and 24%, and reduces total operation cost by 60%, 43.9%, and 23.68% compared with standard BEVs, state machine control (SMC), and frequency decoupling strategy (FDS), respectively. © 2023 by the authors.
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    Adaptive intelligent hybrid energy management strategy for electric vehicles
    (John Wiley and Sons Inc, 2023) Vishnu, S.P.; Kashyap, Y.; Castelino, R.V.
    Electric vehicles (EVs) utilizing hybrid energy sources is a significant step toward a sustainable future in the transportation industry. The electric three-wheeler (3W) considered in the proposed work includes three sources—battery, supercapacitor (SC), and photo-voltaic (PV) panels. In battery electric vehicles (BEV), battery life cycle, energy efficiency, and performance are affected by variations in driving conditions that inhibit their wider adoption. The main focus of the proposed intelligent hybrid energy management strategy (IHEMS) is to enable the vehicle to adaptively manage and diminish the effects of load fluctuations due to varying conditions. IHEMS diverts the load fluctuations to the SC bank by ensuring an effective absolute energy sharing among the sources with a fuzzy logic control algorithm. PV energy is utilized to assist the battery during sunny days. Performance of the EMS in hybrid source EV is analyzed in MATLAB/SIMULINK environment with a combination of three different standard real-time driving profiles (NYCC, Artemis Urban, WLTP class-1). Proposed EMS reduces peak battery power by 20% and 14.35% and improves battery life by 16.4% and 11.4% compared to BEV and conventional EMS, respectively. This proves that the proposed EMS exhibits adaptive energy management irrespective of the driving conditions and ensures improved battery performance and longevity. © 2022 John Wiley & Sons Ltd.