Empowering highway network: Optimal deployment and strategy for dynamic wireless charging lanes

Amid escalating energy crises and environmental pressures, electric vehicles (EVs) have emerged as an effective measure to reduce reliance on fossil fuels, combat climate change, uphold sustainable energy and environmental development, and strive towards carbon peaking and neutrality goals. This study introduces a nonlinear integer programming model for the deployment of dynamic wireless charging lanes (DWCLs) and EV charging strategy joint optimization in highway networks. Taking into account established charging resources in highway service areas (HSAs), the nonlinear charging characteristics of EV batteries, and the traffic capacity constraints of DWCLs. The model identifies the deployment of charging facilities and the EV charging strategy as the decision-making variables and aims to minimize both the DWCL construction and user charging costs. By ensuring that EVs maintain an acceptable state of charge (SoC), the model combines highway EV charging demand and highway EV charging strategy to optimize the DWCL deployment, thus reducing the construction cost of wireless charging facilities and user charging expenses. The efficacy and universality of the model are demonstrated using the classical Nguyen–Dupius network as a numerical example and a real-world highway network in Guangdong Province, China. Finally, a sensitivity analysis is conducted to corroborate the stability of the model. The results show that the operating speed of EVs on DWCLs has the largest impact on total cost, while battery capacity has the smallest. This comprehensive study offers vital insights into the strategic deployment of DWCLs, promoting the sustainable and efficient use of EVs in highway networks.