A Blockchain-Based Fox Optimization Algorithm for Optimizing and Securing Electrical Vehicles Charging

The adoption of electric vehicles (EVs) is rapidly accelerating, driven by increased environmental awareness and technological advancements. However, EV charging faces security and operational challenges hindering widespread adoption. This paper introduces the first method to address both EV charging schedule optimization and security enhancement. It proposes a novel Secure Optimization for EV Charging (SO-EVC) model which addresses the operational and security challenges for EV charging. At the core of SO-EVC is a new FOA-B algorithm, a blockchain-based optimization model that addresses (i) optimizing charging station (CS) locations and (ii) EV routing to CS. FOA-B integrates the Fox Optimizer with Ethereum blockchain technology, leveraging smart contracts for secure, tamper- proof transactions. FOA-B achieves a transaction throughput of 1,200 TPS, outperforming traditional blockchain systems like Ethereum while maintaining decentralization and security. A case study involving 150 EVs and 10 charging stations demonstrated SO-EVC's ability, through FOA-B, to quickly locate optimal charging stations (in 12 iterations) with a standard deviation of 0.22, and reduced dead EVs to just 8%. FOA-B's computational complexity is linear, ensuring scalability with $O(N \times D \times T)$ for optimization and $O(H \times M)$ for blockchain processes. The model maintained steady performance throughout the simulation, showing resilience to downtime. FOA-B also addresses key blockchain challenges, such as the fork phenomena and selfish mining, through a lightweight consensus model and secure transaction validation. Different battery types and environmental temperatures were considered, demonstrating SO-EVC's adaptability in real-world scenarios through FOA-B. These results confirm that SO-EVC provides a comprehensive solution for secure and optimized EV charging systems.