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Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
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Renewable-based charging in green ride-sharing.

Elisabetta Perotti1, Ana M Ospina2, Gianluca Bianchin3

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This study proposes a game-theoretic mechanism to optimize electric vehicle (EV) charging with renewable energy sources for ride-sharing fleets. It balances maximizing renewable charging with maintaining service quality, ensuring efficient EV fleet operations.

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Area of Science:

  • Energy Systems Engineering
  • Transportation Science
  • Computer Science

Background:

  • Growing adoption of electric vehicles (EVs) necessitates efficient charging strategies.
  • Ride-sharing services are transitioning to 100% electric fleets.
  • Integrating renewable energy for EV charging presents challenges due to intermittency.

Purpose of the Study:

  • To develop a mechanism for maximizing renewable-based EV charging in ride-sharing fleets.
  • To ensure charging strategies do not compromise ride-sharing service quality.
  • To investigate the impact of user willingness to ride-share on charging and service quality.

Main Methods:

  • A game-theoretic approach is employed, involving a power utility and a ride-sharing platform.
  • A novel mechanism incentivizes EV charging during high renewable generation periods.
  • A 'charge request' concept is introduced, managed through bargaining for Nash equilibria.

Main Results:

  • The proposed mechanism successfully shifts EV charging to periods of high renewable energy generation.
  • The strategy effectively adapts to intermittent renewable power sources.
  • Minimal impact on the overall quality of ride-sharing services is demonstrated.

Conclusions:

  • Optimized EV charging is achievable for ride-sharing fleets using renewable energy.
  • Game-theoretic bargaining can align utility incentives with platform operations.
  • User behavior significantly influences the effectiveness of charging strategies and service quality.