User-centered optimization of hybrid battery/supercapacitor storage systems in electric vehicles

This paper presents a multi-objective optimization approach for designing hybrid energy storage systems combining Lithium batteries and supercapacitors in electric vehicles. A desirability-based framework is developed to integrate multiple conflicting objectives, including driving range, system cost, lifetime, and volume occupancy. Each objective is transformed into a normalized satisfaction index using parameterized desirability functions derived from user preferences. These indexes are aggregated into a global performance metric to guide the optimization process. A genetic algorithm is employed to identify optimal configurations that balance trade-offs among objectives. Results demonstrate that the hybrid system significantly improves driving range and lifetime while reducing cost and volume compared to battery-only systems. The proposed method offers a flexible and user-centered design strategy for enhancing electric vehicle performance and reliability.