Energizing Charging Services for Next-Generation Consumers E-Mobility With Reinforcement Learning and Blockchain
Md Moniruzzaman, Abdulsalam Yassine, M. Shamim Hossain
Abstract
Next-generation consumer electronics and electric vehicle (EV) energy charging technology promise transformative advancements in the automotive industry. One of the main challenges that hinders consumers’ experience is range anxiety particularly relevant in locales where the installation of fixed charging stations (FCSs) is beset by logistical hurdles, notably in rural regions. With the advancement of consumer electronics especially in the design of Mobile Charging Stations (MCSs), EV drivers can now access these MCSs to exchange energy. However, concerns regarding data security and the best strategies to select an MCS to trade energy may negatively impact consumer experiences. This paper delves into the conception of intelligent remedies by proposing the integration of reinforcement learning and blockchain technology to empower EV drivers to access and securely exchange energy with MCSs. We design a Proof of MCSs (PoMCS) as a consensus protocol to select the winning MCSs as block miners in the blockchain. The results of our experiment show that the average gain for the MCSs increases when using the proposed model and therefore inclined to serve more EVs.