User-Centric Routing and Adaptive Charging EVCS for Battery Longevity and Improved Drive Anxiety

In this article, a user-centric routing and Adaptive Charging Strategy for EV Charging Station (EVCS) is proposed for reducing the Drive Range Anxiety (DRA) and simultaneously improves battery longevity. An IoT-based app is developed, which first collects user data to route and provide information to the user about various available EVCS with the aid of a Fuzzy Logic Controller (FLC). The user can choose the charging modes that are Normal Charging (NC) or Adaptive Charging (ADC) and book the time slots as per the availability. In NC mode of charging, the EV battery immediately gets charged once plugged in, which will reduce the DRA. The ADC mode allows the user to choose minimum State of Charge (SoC) i.e., 50% or 70% upto which the battery will be charged after it is plugged in. Thereafter, the EV charging schedule is done according to the Need of Use (NoU) date and time, ensuring a better drive range in case of emergency, thus reducing the DRA. The ADC reduces Capacity Loss (Qloss) of the EV battery, thereby reducing Calendar Aging (CaA). This ensures that the life and health of the EV battery is improved. The proposed scheme for EVCS is validated in real time using the hardware setup that comprises of 120 V, 26 Ah Lead-Acid and 72 V, 30 Ah Lithium-Ion battery charging system that is controlled by WAVECT WCU300 controller interfaced with ESP-32 and Firebase Realtime Database. The comparison analysis shows that ADC reduces capacity loss by 2% with respect to NC. It also improves DRA with respect to Delayed Charging (DC) by 28.07%. Thus, ADC is the best solution for reducing calendar aging and enhancing battery longevity simultaneously.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3619265
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
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article

User-Centric Routing and Adaptive Charging EVCS for Battery Longevity and Improved Drive Anxiety

Narayan S. Manjarekar, Soumyabrata Barik, Sudarshan Swain, S Suraj et al.
IEEE Access
Advanced Battery Technologies Research
article

User-Centric Routing and Adaptive Charging EVCS for Battery Longevity and Improved Drive Anxiety

Narayan S. Manjarekar, Soumyabrata Barik, Sudarshan Swain, S Suraj, Kumar Kashyap
article en

Abstract

In this article, a user-centric routing and Adaptive Charging Strategy for EV Charging Station (EVCS) is proposed for reducing the Drive Range Anxiety (DRA) and simultaneously improves battery longevity. An IoT-based app is developed, which first collects user data to route and provide information to the user about various available EVCS with the aid of a Fuzzy Logic Controller (FLC). The user can choose the charging modes that are Normal Charging (NC) or Adaptive Charging (ADC) and book the time slots as per the availability. In NC mode of charging, the EV battery immediately gets charged once plugged in, which will reduce the DRA. The ADC mode allows the user to choose minimum State of Charge (SoC) i.e., 50% or 70% upto which the battery will be charged after it is plugged in. Thereafter, the EV charging schedule is done according to the Need of Use (NoU) date and time, ensuring a better drive range in case of emergency, thus reducing the DRA. The ADC reduces Capacity Loss (Qloss) of the EV battery, thereby reducing Calendar Aging (CaA). This ensures that the life and health of the EV battery is improved. The proposed scheme for EVCS is validated in real time using the hardware setup that comprises of 120 V, 26 Ah Lead-Acid and 72 V, 30 Ah Lithium-Ion battery charging system that is controlled by WAVECT WCU300 controller interfaced with ESP-32 and Firebase Realtime Database. The comparison analysis shows that ADC reduces capacity loss by 2% with respect to NC. It also improves DRA with respect to Delayed Charging (DC) by 28.07%. Thus, ADC is the best solution for reducing calendar aging and enhancing battery longevity simultaneously.

IEEE AccessVol. 13
Indian Institute of Technology Dhanbad (IN), Birla Institute of Technology and Science, Pilani - Goa Campus (IN), Birla Institute of Technology and Science, Pilani (IN)
Openalex Percentile: Top 69%
Advanced Battery Technologies Research
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