User-Centric Aging-Aware Method for Electric Vehicle Charging Optimization

Electric vehicles (EVs) are emerging as a greener and more efficient alternative to internal combustion engine (ICE) vehicles. However, their adoption is still limited by reduced driving range and extended charging times. Nevertheless, EV charging can theoretically occur almost anywhere, enabling users to recharge while engaging in daily activities, thereby reducing the need for fast charging and improving overall user satisfaction. This work investigates this charging approach by introducing a novel classification of EV charging strategies within a “vehicle-centric” versus “user-centric” framework. A new methodology for “user-centric” strategies is proposed, which adapts the charging profiles to user requirements and the EV condition. In particular, the proposed method optimizes a default multistep constant current profile to satisfy time constraints imposed by user activities, such as the duration of a stay at a shopping mall or public office, while minimizing EV battery degradation. The method leverages a digital twin of the EV battery incorporating both electrothermal and aging models to simulate a given charging profile and assess its compliance with the constraints of the charging event. Then, a golden-search-based optimization algorithm is used to identify the most suitable profile. A realistic case study based on real-world charging data is used to assess the performance of the proposed method. Simulation results demonstrate strong alignment with user time preferences, acceptable battery health degradation, and improved charging equipment efficiency, making the approach appealing for both EV users and charging station operators.